1
00:00:00,000 --> 00:00:03,060
DR. KRISTA ZANETTI: Welcome to the 
second day of the NIH Workshop on  

2
00:00:03,060 --> 00:00:07,620
Multigenerational Nutritional Influences on 
Health and Disease. I’m Dr. Krista Zanetti,  

3
00:00:07,620 --> 00:00:12,960
one of the scientific leads for the workshop, 
along with Dr. Ashley Vargas. We had a day filled  

4
00:00:12,960 --> 00:00:17,640
with exciting and informative presentations 
yesterday on the foundational concepts  

5
00:00:17,640 --> 00:00:23,820
within the field and individual-level aspects of 
multigenerational influences on nutrition. Today,  

6
00:00:23,820 --> 00:00:29,700
we will continue with more exciting presentations 
that focus on family- and society-level aspects  

7
00:00:29,700 --> 00:00:35,820
of multigenerational influences on nutrition. 
These aspects are equally as important as the  

8
00:00:35,820 --> 00:00:41,700
individual aspects. And today, we have the 
opportunity to learn more about those. Again,  

9
00:00:41,700 --> 00:00:47,580
today, to reach the goals identifying the next 
steps needed for research in multigenerational  

10
00:00:47,580 --> 00:00:54,720
nutritional effects, we need each of you to click 
on the Zoom Q&A and ask the critical questions  

11
00:00:54,720 --> 00:00:59,580
that will push the discussion towards the most 
important research gaps and opportunities.  

12
00:01:01,020 --> 00:01:05,880
I will now introduce the keynote speaker 
and be your moderator for this presentation.  

13
00:01:06,900 --> 00:01:11,580
Dr. Mary Barker from the University of South 
Hampton will be our keynote speaker and will  

14
00:01:11,580 --> 00:01:16,140
present on the family- and societal-level 
aspects of multigenerational influences on  

15
00:01:16,140 --> 00:01:21,180
nutrition. During the presentation, virtual 
participants, please share your questions in  

16
00:01:21,180 --> 00:01:26,220
the Q&A box. And I want to thank Dr. Montessa 
Mitchell in the NIH Office of the Director,  

17
00:01:26,220 --> 00:01:29,700
who will assist with prioritizing 
questions during this discussion.

18
00:01:29,700 --> 00:01:34,200
DR. MARY BARKER: Thank you. Good morning, 
everybody. Thank you, Krista. Thank you,  

19
00:01:34,200 --> 00:01:38,760
everybody. Thank you, Ashley. Thank you for the 
invitation. I was very flattered to receive the  

20
00:01:38,760 --> 00:01:42,720
invitation, though a little bit baffled and did 
actually have to check with Krista and Ashley  

21
00:01:42,720 --> 00:01:47,760
that it really was me that they wanted to come and 
speak. But yes, apparently it was, so here I am.  

22
00:01:48,780 --> 00:01:55,440
So, the other thing I wanted to say before I 
start was how wonderful my father, David Barker,  

23
00:01:55,440 --> 00:02:01,380
would have thought yesterday’s meeting was. He 
would have loved the science and the biology that  

24
00:02:01,380 --> 00:02:07,920
you were all speaking about. He’d have been blown 
away by the fact that 10 years after his death,  

25
00:02:07,920 --> 00:02:14,520
his legacy is still being explored in a room full 
of really exciting scientists and a room full of  

26
00:02:14,520 --> 00:02:19,500
excited people. So, thank you for that. And I 
thank Usha for the kind words she said about  

27
00:02:19,500 --> 00:02:26,340
my father yesterday. So, today, I…I’m going to 
do something that’s…is a little bit different  

28
00:02:26,340 --> 00:02:34,180
from what Usha did. Usha did the most phenomenal 
review yesterday of a whole field of amazing and  

29
00:02:34,860 --> 00:02:38,160
groundbreaking epidemiological and 
other work. I’m not going to do that.  

30
00:02:39,360 --> 00:02:44,760
I’m going to do something a bit more prosaic. 
I’m going to tell you, really, what I think  

31
00:02:44,760 --> 00:02:50,820
about the way people experience nutrition, and 
the way they experience diet, and the impact  

32
00:02:50,820 --> 00:02:58,680
that those experiences have, and the context in 
which they eat food and experience nutrition,  

33
00:02:58,680 --> 00:03:05,700
how that impacts their own health and the health 
of multiple generations and across generations.  

34
00:03:07,440 --> 00:03:12,900
So, the first thing, really, to understand, 
which may sound obvious, but actually,  

35
00:03:13,500 --> 00:03:20,280
it pays us to sometimes stop and think, is that 
not everybody finds nutrition quite as important  

36
00:03:20,280 --> 00:03:26,880
or exciting as we do. This is a rather lovely 
quote—and a rather sad quote, in some ways—from  

37
00:03:26,880 --> 00:03:33,900
a young woman that we spoke to in a study we did 
some years ago, who was very young. She was 16.  

38
00:03:33,900 --> 00:03:41,220
She was just…she was pregnant. She had nowhere to 
live, so she was living in a mother and baby unit,  

39
00:03:41,220 --> 00:03:47,400
which is set up in the U.K. that we have for 
very young pregnant women. And when we were  

40
00:03:47,400 --> 00:03:52,440
speaking to her, it was about the context of 
nutrition and diet and looking after herself.  

41
00:03:52,440 --> 00:03:57,120
And an early question in these conversations was, 
“What’s important to you during this pregnancy?”  

42
00:03:57,840 --> 00:04:03,660
And you can see that basically…her basic needs 
were the most important thing. And yes, nutrition  

43
00:04:03,660 --> 00:04:09,480
is a basic need, but unless she has somewhere 
safe to live, a…a job, she has an ability to  

44
00:04:09,480 --> 00:04:15,360
actually learn and progress herself, and she’s 
able to look after that baby, then actually  

45
00:04:15,360 --> 00:04:21,300
nutrition comes a very poor one, two, three, four, 
five, six, seven after all those other things.  

46
00:04:21,300 --> 00:04:26,940
And that’s worth bearing in mind, because I think 
the rest of my talk, really, I want to set…I  

47
00:04:27,840 --> 00:04:33,420
want to set nutrition within that kind of context 
of what really bothers and preoccupies people for  

48
00:04:33,420 --> 00:04:41,580
an awful lot of their lives. So, this model, 
the…socioecological model has been used for  

49
00:04:41,580 --> 00:04:46,380
many years. And I’m sure many of you recognize 
it. It was introduced by Whitehead and Dahlgren  

50
00:04:46,380 --> 00:04:53,160
in the…in the early ’90s, and it really puts 
health in a…in this lovely rainbow context. And  

51
00:04:53,160 --> 00:04:58,740
we call it the rainbow model for short. So, for 
health [inaudible] nutrition…so, at the center of  

52
00:04:58,740 --> 00:05:03,960
the diagram, there are…there is the individual 
and all the individual-level impacts on…on  

53
00:05:07,080 --> 00:05:11,520
people. So, all the constitutional stuff, their 
age, their sex, as it says there; their gender;  

54
00:05:11,520 --> 00:05:17,220
and also things to do…how they respond 
generally. Their psychology, if you like. So,  

55
00:05:17,220 --> 00:05:25,740
individual-level lifestyle factors then operate on 
that individual; things like…things like, I guess,  

56
00:05:25,740 --> 00:05:29,700
your…your choices that you make about things that 
you like to do, things that you don’t like to do.  

57
00:05:29,700 --> 00:05:35,040
And then there’s your social/community networks 
over the top of that; you know, who you respond  

58
00:05:35,040 --> 00:05:41,640
to and who you work with and where you live. And 
then there is the kind of…the broader green level  

59
00:05:41,640 --> 00:05:46,560
of the rainbow, which really describes much more 
about your environment and the way you live and  

60
00:05:46,560 --> 00:05:54,360
work and the conditions that you live within. And 
then outside of that, the blue-purple level is the  

61
00:05:54,360 --> 00:06:03,000
sort of general policy, cultural, sociological 
context of your…of you. So, if we think about  

62
00:06:03,000 --> 00:06:09,000
all these levels and the way that they interact 
with one another and the way they interact with  

63
00:06:09,000 --> 00:06:15,240
what people then choose or don’t choose—we all 
have to eat—then we can see that the actual…the  

64
00:06:16,320 --> 00:06:21,720
behavior of putting a certain food item in 
your mouth is a hugely constrained one. It’s  

65
00:06:21,720 --> 00:06:27,240
not a free choice very often, and it depends 
on so, so many other things. So, the choices  

66
00:06:27,240 --> 00:06:32,040
that mothers make for themselves and the choices 
that mothers make for their children, I believe  

67
00:06:32,040 --> 00:06:37,680
the point of my talk today is to explain or to 
make us think a bit more about the constraints  

68
00:06:37,680 --> 00:06:44,580
on those choices and why women and families and 
young people end up doing the things they do.  

69
00:06:47,400 --> 00:06:53,640
So, many years ago in Southampton, we started 
something called the Southampton Women’s Survey.  

70
00:06:53,640 --> 00:07:02,580
And it was a study of 12,500 women in Southampton. 
It was a preconception study…Sonia. And we  

71
00:07:02,580 --> 00:07:08,100
recruited 12,500 women and produced…who produced 
very kindly for us about 3,000 pregnancies.  

72
00:07:10,620 --> 00:07:15,792
Part of what we did with the…the baseline 
group, if you like, of 12,500 women was  

73
00:07:15,792 --> 00:07:22,620
some very interesting work. And the…the graph 
shows you that what we found very predictive  

74
00:07:22,620 --> 00:07:28,020
of their quality of diet was their educational 
qualifications, their educational attainment.  

75
00:07:29,340 --> 00:07:34,050
This is…not earth-shattering news. I mean, this is 
quite an old slide now. You can see the data are  

76
00:07:34,050 --> 00:07:39,360
quite old. But it never fails to amaze me. So…so, 
you’ve got highest educational qualification  

77
00:07:39,360 --> 00:07:45,000
across the bottom. And in the U.K. terms, these 
are…like…so, no educational qualifications; GCSE  

78
00:07:45,000 --> 00:07:54,180
is what we do at the age of 16; A-levels are what 
we do at 18; and HND and Degree are beyond 18.  

79
00:07:54,960 --> 00:08:00,840
So, you can see that the proportion of women who 
have the poorest quality diet by our standards  

80
00:08:00,840 --> 00:08:07,320
as part of the study were much, much more 
likely to fall in the No Education group.  

81
00:08:07,860 --> 00:08:12,780
But the striking thing about this, as I said, 
is that this response is graded. So, for every  

82
00:08:12,780 --> 00:08:17,220
each individual increase…for every individual 
increase in level of educational attainment,  

83
00:08:18,120 --> 00:08:25,200
there are fewer women who fall in the 
poorest-quality diet group, which is very  

84
00:08:25,200 --> 00:08:28,920
interesting because very little is taught in the 
U.K. schools about food. This is not nutrition  

85
00:08:28,920 --> 00:08:33,900
education we’re talking about. This is education 
generally. And somebody—and I can’t remember now  

86
00:08:33,900 --> 00:08:37,560
who it was who mentioned it yesterday—talked about 
education—I think it was Usha, actually—talked  

87
00:08:37,560 --> 00:08:41,880
about education as being protective of women’s 
quality of diet and children’s quality of diet.  

88
00:08:42,420 --> 00:08:47,280
And this graph, this particular analysis, 
triggered my colleagues and I to go in and have  

89
00:08:47,280 --> 00:08:51,780
a think about why education might be protective, 
what was it about education, given that these  

90
00:08:51,780 --> 00:08:55,080
women were not learning about…you know, the 
longer they were in school was not telling  

91
00:08:55,080 --> 00:09:00,780
them more about how to cook and eat. It was just 
education per se. So, we embarked on a series of  

92
00:09:01,620 --> 00:09:06,120
studies, some of which were qualitative, so 
we interviewed and we ran focus groups, and  

93
00:09:06,120 --> 00:09:11,640
some of which were quantitative—we did surveys, we 
collected data on a one-to-one basis from lots and  

94
00:09:11,640 --> 00:09:19,140
lots of women and all over Southampton. And what 
we found was that there were four key things that  

95
00:09:20,160 --> 00:09:25,800
seemed to identify amongst women of lower 
educational attainment why they might not be  

96
00:09:25,800 --> 00:09:33,840
eating so well. So, the four blue squares—kind of 
rounded squares—in the middle of this diagram are  

97
00:09:33,840 --> 00:09:40,800
the four factors which we found in surveys to…to 
independently predict women’s quality of diet.  

98
00:09:41,640 --> 00:09:44,940
So, whether they had social support…and 
these are very different in women of  

99
00:09:44,940 --> 00:09:47,820
higher educational attainment. These 
were not features of women of higher  

100
00:09:47,820 --> 00:09:51,120
educational attainment’s diet. It did 
not predict in the same way. These were  

101
00:09:51,120 --> 00:09:54,780
predictive of a diet for these women of low 
educational attainment. Very particular.  

102
00:09:55,860 --> 00:10:00,960
So, we found that social support was very 
important for eating well. So…so if women  

103
00:10:00,960 --> 00:10:06,000
lacked social support, it was much harder for them 
to…to eat well. And that’s within the family and  

104
00:10:06,000 --> 00:10:09,840
with outside the family. And I’m not going to 
read the quotes because you can see them, but  

105
00:10:09,840 --> 00:10:15,240
they are illustrative of what we mean by lacking 
social support. They found it really difficult  

106
00:10:15,240 --> 00:10:19,500
to prioritize food over competing priorities, 
the priorities that I just suggested just now.  

107
00:10:20,820 --> 00:10:24,810
The women who doesn’t…really didn’t like cooking 
would be using the microwave. It just wasn’t head  

108
00:10:24,810 --> 00:10:30,720
space for her, if you like, to take on cooking. 
This thing called lower sense of self-efficacy  

109
00:10:30,720 --> 00:10:35,520
and sense of control over life is really 
about a woman’s individual belief that she  

110
00:10:35,520 --> 00:10:40,620
has the…the capacity to overcome problems. And 
this was really, really important. Her sense of  

111
00:10:40,620 --> 00:10:45,420
personal agency in her life was really important 
and predictive in her quality of diet, as well.  

112
00:10:46,680 --> 00:10:51,480
I love that, “My husband tells me what to cook and 
I cook it.” My husband rolls his eyes every time I  

113
00:10:51,480 --> 00:10:55,200
show him this slide. It couldn’t be more different 
in our house, as you can probably imagine.  

114
00:10:56,460 --> 00:11:00,300
And then the last of these four is that 
actually this kind of fundamental belief  

115
00:11:00,300 --> 00:11:04,620
that maybe eating well wasn’t that…wasn’t really 
that important. And I never know quite what to  

116
00:11:04,620 --> 00:11:09,180
say about this particular factor because…because 
people’s instinctual response is to say, “Well,  

117
00:11:09,180 --> 00:11:13,920
we [inaudible]. Obviously, it’s important. You 
know, we all think it’s terribly important. It’s  

118
00:11:13,920 --> 00:11:17,700
very important.” But, again, I think this is 
relative to the other things that are happening  

119
00:11:17,700 --> 00:11:22,860
in…in women’s lives, particularly in…in this 
context, and I think we have to think about  

120
00:11:23,700 --> 00:11:29,400
why they might not push healthy if actually 
keeping your children safe and stopping your  

121
00:11:29,400 --> 00:11:35,640
husband being violent is…comes kind of first. 
Right? So, this was the…to…to put this in  

122
00:11:35,640 --> 00:11:40,920
context of the socioecological model, this was the 
kind of…the first two levels, if you like. This  

123
00:11:40,920 --> 00:11:45,410
was the individual and the…I can’t even remember 
which color it is now. I should now, shouldn’t I,  

124
00:11:45,410 --> 00:11:49,440
but I…I can’t remember. This was the kind of 
individual lifestyle and some of the social  

125
00:11:49,440 --> 00:11:55,560
factors. So, going slightly broader outside those 
factors into the next layer of the socioecological  

126
00:11:56,100 --> 00:12:01,500
model, we also found that women spoke a lot about 
the socioeconomic and community factors that they  

127
00:12:01,500 --> 00:12:06,420
had to deal with and the way these impacted 
their diet. And of course, unsurprisingly,  

128
00:12:06,420 --> 00:12:12,780
money and food insecurity was a major factor. So, 
again, if I can buy 20 sausages for a pound—that’s  

129
00:12:12,780 --> 00:12:17,700
about $1.30 in today’s exchange rate—and I know 
they’ll eat that. God only knows what’s in those  

130
00:12:17,700 --> 00:12:23,040
sausages, but she knows the kids will eat it. 
And the…the backstory to that is you can only  

131
00:12:23,040 --> 00:12:27,360
afford to buy food which you know is not going 
to be wasted. If you take a risk and buy lots of  

132
00:12:27,360 --> 00:12:32,040
fresh fruit and vegetables and spend your precious 
dollars, pounds, on fresh fruits and vegetables,  

133
00:12:32,040 --> 00:12:35,160
and then they rot and get thrown away and the 
kids don’t eat them, then you’re in big trouble  

134
00:12:35,160 --> 00:12:38,940
because you’ve got nothing else to eat. So, you 
buy 20 sausages for a pound, knowing that they’re  

135
00:12:38,940 --> 00:12:43,200
probably not the best thing you can buy and feed 
your children. But what other choice do you have?  

136
00:12:44,400 --> 00:12:47,940
And then there’s the whole shopping experience, 
the whole, kind of, access experience. So,  

137
00:12:47,940 --> 00:12:51,600
women who don’t drive and she’s taking her kids 
shopping. And we’ve all been there. Those of us  

138
00:12:51,600 --> 00:12:55,920
who have ever shopped with small children will 
know exactly what that’s like. And…and, you know,  

139
00:12:55,920 --> 00:12:59,760
there’s a…you can have a lot of sympathy for the 
fact that she’s actually going to get herself in  

140
00:12:59,760 --> 00:13:03,600
and out of that shop as fast as possible, that 
she’s not going to spend time considering food  

141
00:13:03,600 --> 00:13:08,520
labels and the relative content of this over 
that and…and…and doing anything other than just  

142
00:13:08,520 --> 00:13:12,420
getting out there, having spent as little money as 
possible, with as much food to feed her children  

143
00:13:12,420 --> 00:13:16,680
as possible. And then the last one I’m always very 
interested in because it never occurred to me. But  

144
00:13:16,680 --> 00:13:21,660
if you live in a tower block or a block apartment, 
you’re very…and you have small children, you’re  

145
00:13:21,660 --> 00:13:26,160
very dependent on the lifts working. And I spent 
enough time in Southampton and enough time in the  

146
00:13:26,160 --> 00:13:30,060
tower blocks to know that the lifts are quite 
often not working. So, what the hell do you do?  

147
00:13:30,060 --> 00:13:33,780
I mean, that is a choice I’ve never really got my 
head around. Do you leave your kids at the bottom  

148
00:13:33,780 --> 00:13:38,040
in the pushchair while you take the shopping up? 
Or do you take the kids up and leave the shopping  

149
00:13:38,040 --> 00:13:42,480
at the bottom? Both of which you might risk 
losing on the way. I don’t know how you resolve  

150
00:13:42,480 --> 00:13:46,680
that conundrum, but it’s a real one for a lot of 
women. And I guess what that might make you do is  

151
00:13:46,680 --> 00:13:50,400
not buy a lot of heavy fresh fruits and vegetables 
because then you can take everything up at once,  

152
00:13:50,400 --> 00:13:55,500
up the stairs. And…and it’s another reason for…for 
poor women eating and choosing the way they do.  

153
00:13:56,280 --> 00:14:01,020
And I just…so, I put this slide in because it 
struck me very forcibly when I was reading and  

154
00:14:01,020 --> 00:14:05,940
preparing for this talk that things, of course, 
must be getting pretty terrible in the States,  

155
00:14:05,940 --> 00:14:10,080
too. The cost of living crisis is hitting all 
of us everywhere. And the statistics I read  

156
00:14:10,080 --> 00:14:14,280
from what looks like a local research group—and 
I don’t know anything about the Urban Institute,  

157
00:14:14,280 --> 00:14:19,500
but their stuff looks pretty, pretty reputable—25% 
of American adults reported being food insecure.  

158
00:14:19,500 --> 00:14:25,980
That’s shocking and striking and a terrible thing 
that we should be thinking about. And so, for food  

159
00:14:25,980 --> 00:14:31,800
insecure, read all those things that we’ve just 
heard about, about women and the…and families  

160
00:14:31,800 --> 00:14:36,480
and the difficulties they have to…the challenges 
they have to overcome in order to feed themselves.  

161
00:14:38,520 --> 00:14:44,880
So, food insecurity clearly constrains choices 
very profoundly…food choices and nutrition and  

162
00:14:44,880 --> 00:14:51,000
diets very profoundly. And there’s a quote that 
I am going to show you now from a tweet that I  

163
00:14:51,000 --> 00:14:55,380
showed Krista—and I don’t know if anyone else last 
year…I can't remember who else was at the meeting that I attended last  

164
00:14:55,380 --> 00:15:04,620
year when I met Krista—from a very famous cook 
in the U.K. Her name is Jack Monroe. And she  

165
00:15:04,620 --> 00:15:10,920
champions cooking very cheap, very good food, and 
she is very politically active and a defender of  

166
00:15:12,840 --> 00:15:18,900
poor families eating as well as they can for the 
money they have. And you’ll have to excuse the…the  

167
00:15:18,900 --> 00:15:23,880
stars. “You can cook meals from scratch with 
nothing—You CAN’T cook meals from scratch with  

168
00:15:23,880 --> 00:15:28,500
nothing. You can’t buy cheap food with nothing. 
The issue is not ‘skills,’ it’s 12 years of  

169
00:15:28,500 --> 00:15:33,600
Conservative cuts to social support.” A little 
political U.K. dig. “The square root of F-all is  

170
00:15:33,600 --> 00:15:39,000
always going to be F-all, no matter how creatively 
you’re told to dice it.” And I think this is a  

171
00:15:39,000 --> 00:15:42,360
really important point that we need to think 
about. You know, at what point do our choices  

172
00:15:42,360 --> 00:15:46,980
become so constrained that actually they’re not 
choices at all? And when we spend a lot of time  

173
00:15:47,760 --> 00:15:53,220
talking about nutrition education and teaching 
particularly women and young families how to cook,  

174
00:15:53,220 --> 00:15:57,300
we have to remember the context in which 
they’re trying to do that. And actually,  

175
00:15:57,300 --> 00:16:02,520
it’s not really about nutritional education and 
skills. It’s about so, so many other things,  

176
00:16:02,520 --> 00:16:07,020
and we must not forget that. And by making it 
all about nutrition educational skills, we’re  

177
00:16:07,020 --> 00:16:11,940
making this an individual responsibility, and it’s 
clearly, clearly not an individual responsibility.  

178
00:16:11,940 --> 00:16:16,740
Food choices, if they’re that constrained, are 
not an individual responsibility or choice.  

179
00:16:18,540 --> 00:16:24,780
So, having told you about the situation for 
families and the kind of things that they  

180
00:16:24,780 --> 00:16:27,240
have to deal with and the choices 
that they have to make, I want to  

181
00:16:28,560 --> 00:16:33,720
move on to answer some of the questions—or one of 
the questions—that we were asked to consider. So,  

182
00:16:33,720 --> 00:16:38,820
what is the most promising…or the one most 
promising scientific or technological opportunity  

183
00:16:38,820 --> 00:16:43,980
moving forward? For me, this is all about young 
people. And those of you who I’ve spoken to in  

184
00:16:43,980 --> 00:16:48,060
the last 24 hours will not be surprised by this 
because I beef on about young people all the time.  

185
00:16:48,060 --> 00:16:54,420
I think it’s about adolescent development. I think 
it’s about harnessing what we now know about young  

186
00:16:54,420 --> 00:16:57,960
people and about adolescent development and the 
adolescent life course theories, and I think we  

187
00:16:57,960 --> 00:17:03,660
are missing a massive trait. So, for me, the thing 
we need to do is really work with adolescents. And  

188
00:17:03,660 --> 00:17:06,060
there was a very good series, in which I only 
played a very small part…[inaudible] small  

189
00:17:06,060 --> 00:17:13,260
part in the Lancet recently about adolescent 
nutrition, which I would recommend to anyone. It’s  

190
00:17:13,260 --> 00:17:18,720
really broad and, in the way those Lancet 
series are, covers a huge amount of ground,  

191
00:17:18,720 --> 00:17:26,820
from what we know about growth and development and 
young people through to what constrains and limits  

192
00:17:26,820 --> 00:17:33,120
that or…contrains their food choices really across 
the world and also suggests some interventions  

193
00:17:33,120 --> 00:17:40,680
and the way we need to work with them. So, why 
do I think adolescents are so important? Well,  

194
00:17:40,680 --> 00:17:45,300
this slide, which I’m sure many of you have seen, 
comes from my friend Keith Godfrey’s publication  

195
00:17:46,200 --> 00:17:53,220
some years ago. So, you can see that this is a…a 
rather complicated looking but actually quite  

196
00:17:53,220 --> 00:17:57,120
simple idea, which is that if you invest 
in different stages of the life course,  

197
00:17:57,120 --> 00:18:02,160
your energies and your commitment to improving 
health and nutrition, then you get different  

198
00:18:02,160 --> 00:18:07,620
levels of payback at different time points. And 
for me, the…the thing about this grant is that  

199
00:18:07,620 --> 00:18:15,840
if you—sorry, this graph—is, if you invest in 
adolescents, you are not only investing in that  

200
00:18:15,840 --> 00:18:21,840
young person’s health now, you’re also changing 
the trajectory for that young person as they get  

201
00:18:21,840 --> 00:18:28,680
to become an adult, but you’re also improving the 
health of the next generation. You get the best  

202
00:18:29,700 --> 00:18:34,020
bang for your buck, for want of a better 
expression. The best return of your investment  

203
00:18:34,020 --> 00:18:39,720
by investing in adolescents. And that really is 
why almost all my work now is with adolescents—on  

204
00:18:39,720 --> 00:18:44,580
top of which, I just really like them. I think 
they’re great. So, just to rehearse my work with  

205
00:18:44,580 --> 00:18:48,600
young people, it’s also a developmental stage 
that affects health, as I said, not just now,  

206
00:18:48,600 --> 00:18:55,140
but in later life. We also know that there 
is great potential to effect sustained change  

207
00:18:55,140 --> 00:19:00,120
in behavior and lots of other things, too, in 
development to protect future generations’ health.  

208
00:19:01,260 --> 00:19:04,860
Of course, there are lots of challenges of 
working with young people. They do, actually,  

209
00:19:04,860 --> 00:19:10,320
in surveys, have the poorest health behaviors 
of any population group. They eat worse,  

210
00:19:11,340 --> 00:19:16,380
they exercise least. They experiment with 
drugs. They don’t sleep much, or they sleep  

211
00:19:16,380 --> 00:19:19,980
at the wrong time. All of the things that we 
would like not to do, they do in abundance.  

212
00:19:21,960 --> 00:19:29,040
But also, so many mental health problems are 
established in…in adolescence. It’s a massive…a  

213
00:19:29,040 --> 00:19:32,880
massive issue. So, you’re working not just 
for the population who actually are struggling  

214
00:19:32,880 --> 00:19:37,080
with their own health behaviors to stay healthy, 
they’re actually really struggling, many of them,  

215
00:19:37,080 --> 00:19:41,640
with their own mental health problems. But for me, 
those…that makes this an even more important time  

216
00:19:41,640 --> 00:19:46,500
to invest. So, we spent a lot of time talking 
to young people, and we have a big study called  

217
00:19:48,180 --> 00:19:51,480
EACH-B, Engaging Adolescents in Changing 
Behavior, which has taught us lots and lots of  

218
00:19:51,480 --> 00:19:58,020
things, and we’ve been running this for the last 6 
years now. And what we have really come to realize  

219
00:19:58,020 --> 00:20:03,480
is what we need to understand if we’re going to 
improve adolescent nutrition. So, the yellow blob  

220
00:20:03,480 --> 00:20:08,460
really is about the fact that…that young people 
actually know that they need to be eating well  

221
00:20:08,460 --> 00:20:12,060
and looking after themselves and sleeping and 
exercising. This is not news to them. They know.  

222
00:20:12,060 --> 00:20:17,760
But the thing is, they operate through their own 
agenda and to a set of their own constraints. So,  

223
00:20:17,760 --> 00:20:25,260
these three colored blobs underneath represent 
the major…the major parts of the agenda that  

224
00:20:25,260 --> 00:20:30,120
they work to. So, I do what others do. I 
need…I need to meet my needs for relatedness.  

225
00:20:30,660 --> 00:20:36,600
I need to relate to my…to my peers. It’s very 
important to me. I want healthy to fit into  

226
00:20:36,600 --> 00:20:41,280
my life. I need to be…it needs to be…part of my 
general confidence. It has to be not a separate  

227
00:20:41,280 --> 00:20:45,960
thing. It has to work with everything else I do. 
And this is my life. I need to be a [inaudible].  

228
00:20:47,400 --> 00:20:52,020
I need to make my own decisions. So, 
autonomy, competence, and relatedness,  

229
00:20:52,020 --> 00:20:55,920
three factors which actually overlay…very 
nicely the theory of self-determination,  

230
00:20:56,700 --> 00:21:00,840
are the basic needs that young people are trying 
to meet when we’re trying to persuade them to  

231
00:21:00,840 --> 00:21:05,220
eat well and look after themselves. And this is a 
lovely piece of work done by my colleague, Sarah  

232
00:21:05,880 --> 00:21:12,360
Shaw, who looks at the impact of the food…because 
it’s a joint impact, it’s a social environment,  

233
00:21:12,360 --> 00:21:15,480
young people hanging out with their 
friends, and the food environment where they  

234
00:21:15,480 --> 00:21:19,500
shopped for independent…and made independent 
food choices where they went to restaurants,  

235
00:21:19,500 --> 00:21:24,240
and how these two environmental factors 
that kind of…one of those layers of the  

236
00:21:24,240 --> 00:21:29,100
rainbow interacted with those individual 
psychological basic needs that young people  

237
00:21:29,100 --> 00:21:35,280
have to produce their food choices. And 
she…she identified and tested these…these  

238
00:21:37,200 --> 00:21:41,520
factors, not just in qualitative but also then 
in quantitative surveys. And she’s done some very  

239
00:21:41,520 --> 00:21:45,960
interesting work following young people in real 
time looking at the choices that they’re making.  

240
00:21:48,360 --> 00:21:54,060
So, other work we’ve done with young people, 
where that first…very first quote I showed  

241
00:21:54,060 --> 00:22:00,300
you came from, is with young pregnant women. 
Very young mothers. And some years ago, again,  

242
00:22:00,300 --> 00:22:06,180
we conducted some work with 106 young 
women between the ages of…15 and 22,  

243
00:22:06,180 --> 00:22:11,700
who were interviewed by not us, because we 
decided very early on there was no way a bunch of  

244
00:22:13,260 --> 00:22:19,080
middle-class academics were going to get anywhere 
near the really quite disenfranchised group of  

245
00:22:19,080 --> 00:22:24,000
young pregnant women that we…we wanted to talk 
to. So, we hired a…a social enterprise to do  

246
00:22:24,000 --> 00:22:27,960
the interviewing for us. And they were incredibly 
effective. Interviewing 106 young pregnant women  

247
00:22:27,960 --> 00:22:33,120
in Southampton…in a very short space of time was 
a phenomenal thing. So, top tip for anyone who  

248
00:22:33,120 --> 00:22:38,580
wants to do research with communities that are 
quite often ignored: Get someone else to do your  

249
00:22:38,580 --> 00:22:45,540
talking for you, from a part of the community. 
Okay. So, what we learned about these young women  

250
00:22:46,140 --> 00:22:50,460
and their eating habits was that they fell into 
three kinds of groups, really. There were those  

251
00:22:50,460 --> 00:22:54,180
who were trying really hard. They were eating 
really regularly, who had…and who managed to  

252
00:22:54,180 --> 00:22:58,140
hang on to their aspirations for themselves 
and their future. And these were young women  

253
00:22:58,140 --> 00:23:01,680
who were making the link between what they 
were eating and the baby they were carrying.  

254
00:23:03,180 --> 00:23:08,340
We had some young women in this group who knew 
things weren’t getting quite right but really  

255
00:23:08,340 --> 00:23:14,160
wanted to eat better and eat more. And they had 
relationships with their midwives, and they had,  

256
00:23:14,160 --> 00:23:17,760
again, some aspirations for a healthy baby, 
and, again, were making the baby–diet link.  

257
00:23:18,840 --> 00:23:23,160
And then we had another group, a third group 
of young women, who were very disengaged,  

258
00:23:24,780 --> 00:23:29,160
who…really, their aspirations were very short 
term. They really weren’t thinking much about  

259
00:23:29,160 --> 00:23:33,480
what they put in their mouths and the way it was 
going to feed their baby, and they skipped a lot  

260
00:23:33,480 --> 00:23:38,700
of meals. So, we have these three women—these, 
sorry, three groups of young women. And the point  

261
00:23:38,700 --> 00:23:42,720
about these three groups is that actually, these 
individual differences, these group differences  

262
00:23:42,720 --> 00:23:46,680
between women, meant that they were going to vary 
very much in their engagement with the midwives  

263
00:23:46,680 --> 00:23:51,480
and the people who were there to support them. You 
can imagine that the engagement of the…the women  

264
00:23:51,480 --> 00:23:55,800
who were skipping meals, the skippers, was not 
going to be the same as the regular eaters. And  

265
00:23:55,800 --> 00:24:00,780
that’s, again, something we need to understand, is 
that one intervention doesn’t work for everybody.  

266
00:24:00,780 --> 00:24:05,340
You need to tailor the interventions, and you 
need to understand whom you are tailoring those  

267
00:24:05,340 --> 00:24:10,500
interventions and what is important for 
them before you can do that. So, this is a  

268
00:24:12,360 --> 00:24:16,920
rather wordy but rather lovely diagram that my 
colleague Sofia introduced…[inaudible] introduced  

269
00:24:17,760 --> 00:24:21,300
to us as…as part of this work that she was 
running, which really shows the intersect  

270
00:24:21,300 --> 00:24:25,380
between the views of the young mother and 
the midwives, whom we also interviewed,  

271
00:24:25,380 --> 00:24:29,340
who were working with these young women. And 
again, you can see the autonomy, competence,  

272
00:24:29,340 --> 00:24:35,700
and relatedness being really, really basic needs 
of the mother…the young mothers, and how important  

273
00:24:35,700 --> 00:24:40,560
it is for the midwives and the support that 
the young mothers were having to intersect  

274
00:24:40,560 --> 00:24:45,840
and to meet these basic needs that we needed to 
understand before we could actually design any  

275
00:24:45,840 --> 00:24:50,040
kind of service which was likely to support their 
nutrition. And I am more than happy to talk about  

276
00:24:50,040 --> 00:24:57,120
any of this later, but I’m going to skip on in the 
interest of time. So, how do we actually realize  

277
00:24:57,120 --> 00:25:02,880
these improvements in multigenerational health 
through investment in adolescence? And here are  

278
00:25:04,020 --> 00:25:09,600
a few quotes from the Lancet series on 
adolescent nutrition, and very nicely  

279
00:25:09,600 --> 00:25:15,480
phrased by George Patton, who sadly died last 
year or earlier this year, very shockingly.  

280
00:25:16,200 --> 00:25:22,140
He was a…a friend and a wonderful advocate 
for adolescent health and nutrition, and  

281
00:25:22,140 --> 00:25:28,320
the world of adolescent researchers will miss him 
greatly. But the important things about…about what  

282
00:25:28,320 --> 00:25:33,060
I put on this slide is really that the programs 
that we offer, they have to be intersectional. So,  

283
00:25:33,060 --> 00:25:38,760
I know we want to improve diet. But what…what 
the…this review was saying is that having looked  

284
00:25:38,760 --> 00:25:43,320
at all the evidence, we’re not going to improve 
young people’s diet if we just focus on health  

285
00:25:43,320 --> 00:25:47,820
services or nutritional services. They need to be 
intersectoral. They need to work with educational  

286
00:25:47,820 --> 00:25:51,960
settings, they need to work with the social care, 
they need to work, yes, with health services.  

287
00:25:51,960 --> 00:25:56,640
And…but they also need to work with food retailers 
and with local communities and, to some extent, in  

288
00:25:56,640 --> 00:26:01,620
domestic households. We…nutrition is…is, as we all 
heard yesterday, as we all commented yesterday,  

289
00:26:01,620 --> 00:26:07,620
is such a complex…diet is such a complex behavior 
and constrained by so many things that we really  

290
00:26:07,620 --> 00:26:12,660
need to address all of those things. We can’t 
just zone in. We need to be cognizant first.  

291
00:26:14,580 --> 00:26:22,380
And following that, logically, the most effective 
policies will therefore have to stretch beyond  

292
00:26:22,380 --> 00:26:26,520
health and nutrition. They’ll have to take in 
the departments of education, the departments  

293
00:26:26,520 --> 00:26:30,300
of business, all the government…across 
government—certainly in the U.K.,  

294
00:26:30,300 --> 00:26:35,040
across government—departments in order 
to actually improve the end point,  

295
00:26:35,040 --> 00:26:40,560
which is adolescent nutrition, particularly, as 
it says here, with adolescents who are the most  

296
00:26:40,560 --> 00:26:45,600
socioeconomic disadvantaged…advantaged. So, for 
the next question that we were asked to consider:  

297
00:26:45,600 --> 00:26:51,480
What’s the biggest scientific challenge? And 
I’m nearing the end of my talk now. So, for me,  

298
00:26:52,800 --> 00:26:57,180
aside from, “How on earth do we work with young 
people effectively?” which I think I’ve already  

299
00:26:57,180 --> 00:27:04,680
covered, it’s about finding a way of generating 
the high-quality evidence of effectiveness that  

300
00:27:04,680 --> 00:27:08,280
we need of interventions, and it’s—I’m all about 
interventions, as you’ve probably gathered—that  

301
00:27:09,180 --> 00:27:17,940
doesn’t involve our current trial processes, which 
are—as we talked [inaudible] go there—are large  

302
00:27:17,940 --> 00:27:24,540
sledgehammers cracking nuts, and we don’t ever get 
the response or the results that we want because  

303
00:27:25,320 --> 00:27:29,640
we just have the wrong methodology. At the moment, 
we are running big public health trials to look at  

304
00:27:29,640 --> 00:27:37,020
things like a…a…programs that address adolescent 
nutrition and finding…nothing particularly useful  

305
00:27:37,020 --> 00:27:42,360
at the end of it of…you know, effect size at 
the end of these things is…is, for public health  

306
00:27:42,360 --> 00:27:47,160
trials, fairly unhelpful. We need to find better, 
effective methods…methods of doing that. So,  

307
00:27:47,160 --> 00:27:52,500
that’s my…my big plea and my big beef, and it 
has been for some time. And the other thing  

308
00:27:52,500 --> 00:27:57,540
is something that Sonia introduced yesterday, is 
we need to include the full and diverse range of  

309
00:27:57,540 --> 00:28:05,640
participants in our trial. There is a shameful…a 
shameful history of all of us working with those  

310
00:28:05,640 --> 00:28:11,700
who are most keen to work with us as our research 
participants, which excludes all the people that  

311
00:28:11,700 --> 00:28:15,240
we really should be working with, the people 
who are most disenfranchised, most distrustful,  

312
00:28:15,240 --> 00:28:21,240
and most in need of support and help. And I think 
that that it’s more than high time that we address  

313
00:28:21,240 --> 00:28:28,020
that. So, to find ways of reaching the not so 
much hard to reach as the easy to ignore, as my  

314
00:28:28,020 --> 00:28:32,820
lovely colleague always puts it, that, again, is 
our biggest…I think, one of our biggest kinds of  

315
00:28:32,820 --> 00:28:37,920
challenges. And I’m going to finish now just 
by acknowledging all the amazing families and  

316
00:28:38,880 --> 00:28:42,780
awesome young people that we spoke to and who 
shared their thoughts and their time with us;  

317
00:28:42,780 --> 00:28:51,278
and all my amazing colleagues who…I can’t begin 
to tell you what a fantastic bunch of people I  

318
00:28:51,278 --> 00:28:52,740
work with in the U.K. and have done this for 
some years; and our funders, who put up with  

319
00:28:52,740 --> 00:28:57,180
me and my endless ranting about the things 
that I care about. Thank you very much.

320
00:28:57,180 --> 00:29:04,380
[Applause]

321
00:29:04,380 --> 00:29:05,580
DR. KRISTA ZANETTI: Thank you, Dr. Barker,  

322
00:29:05,580 --> 00:29:08,838
for a…it’s your choice. I think 
you’re, you’re welcome to stay there—

323
00:29:08,860 --> 00:29:10,520
since you’re going 
to be the only one answering questions.

324
00:29:10,520 --> 00:29:11,560
DR. MARY BARKER: Okay.

325
00:29:11,560 --> 00:29:16,320
DR. KRISTA ZANETTI: And so, we thank you for 
an engaging presentation. And we will now take  

326
00:29:16,320 --> 00:29:21,960
questions. Again, those attending virtually, 
please share any questions you have in the  

327
00:29:21,960 --> 00:29:26,820
Q&A box. And for those in the room please raise 
your physical hand, and we’ll do our best to get  

328
00:29:26,820 --> 00:29:33,960
to as many questions as we can. So, we do have 
an online question, so I think we’re going to  

329
00:29:33,960 --> 00:29:38,507
start with our…our…our virtual participants 
this morning. Turn it over to Dr. Mitchell.

330
00:29:38,507 --> 00:29:42,960
DR. MONTESSA MITCHELL: All right. 
Our first question starts off with:  

331
00:29:42,960 --> 00:29:49,320
“My close family member is a single mom of three 
kids, and I was struck by how heavily she relied  

332
00:29:49,320 --> 00:29:53,760
on screen time and snack foods to manage 
the kids’ behavior. She actually threatened  

333
00:29:53,760 --> 00:29:58,920
them with fruit as a snack if they didn’t 
behave. Do you find that parenting resources  

334
00:29:58,920 --> 00:30:03,960
and skills are a widespread issue potentially 
contributing to the overall diets of families?”

335
00:30:03,960 --> 00:30:09,120
DR. MARY BARKER: That’s obviously a 
really good and very important question.  

336
00:30:10,800 --> 00:30:15,840
I mean, the things that strike me about that 
question are that this is a single parent of  

337
00:30:15,840 --> 00:30:22,020
three small children, and that woman, I suspect, 
if she’s anything like any of the other single  

338
00:30:22,020 --> 00:30:26,580
parents I know, spends a lot of time just getting 
by, just doing what she has to and dealing with  

339
00:30:26,580 --> 00:30:30,120
the things that are the most important things 
she has to deal with. She has to keep her kids  

340
00:30:30,120 --> 00:30:34,980
safe. She has to keep her kids fed. She has 
to go to work, presumably. She has to do all  

341
00:30:34,980 --> 00:30:40,080
those things that she has to do. Probably 
screen time, kinds of snacks they’re eating,  

342
00:30:40,080 --> 00:30:44,700
come about 150th on her list of really 
important things to think about. So…so,  

343
00:30:46,080 --> 00:30:51,060
I hesitate to dismiss this, and I’m not 
dismissing this question at all. And of course,  

344
00:30:52,320 --> 00:30:56,880
parenting skills are really important. But 
for me, maybe we could look about in terms  

345
00:30:56,880 --> 00:31:03,960
of parenting support. And I think the support 
we give young families in Western society,  

346
00:31:03,960 --> 00:31:09,000
which is really the [inaudible] about, 
is lamentable. And I think if we really,  

347
00:31:09,000 --> 00:31:14,280
really want to address things like the major 
crisis in mental health there is at the moment,  

348
00:31:15,360 --> 00:31:20,400
we need to support young families much, much 
better. And we don’t, at the moment. And the  

349
00:31:20,400 --> 00:31:25,320
wraparound support for single parents is just 
nonexistent. It just…it doesn’t exist. So,  

350
00:31:25,320 --> 00:31:29,760
I would hesitate to put this on the woman and say 
her parenting skills were lacking and point more  

351
00:31:29,760 --> 00:31:35,580
to the fact that we as a society and a community 
do not support young parents to do the…to do what  

352
00:31:35,580 --> 00:31:40,260
we all want them to do. To do, frankly, what 
they would like to do, too. And I would like  

353
00:31:40,260 --> 00:31:46,740
to put that back out onto us, really, our society 
to have a think about how we spend our resources,  

354
00:31:46,740 --> 00:31:51,120
and maybe redirect some of our resources 
towards…to more of our resources towards  

355
00:31:51,120 --> 00:31:55,200
developing systems which support young families, 
rather than blame them for being bad parents.

356
00:31:57,440 --> 00:32:01,158
DR. MONTESSA MITCHELL: I’m sorry. Joe?

357
00:32:01,158 --> 00:32:07,200
AUDIENCE MEMBER (JOE): That,   that was a great talk. And…and I really 
appreciate the model you showed about how our  

358
00:32:07,200 --> 00:32:11,700
diet is influenced by these multilevel factors. 
And I…and I wonder if you have any thoughts about  

359
00:32:13,200 --> 00:32:18,900
whether we need to incorporate artificial 
intelligence into there, thinking about how food  

360
00:32:18,900 --> 00:32:24,900
apps and how AI is being incorporated in decisions 
around welfare for families. And…and just…there’s  

361
00:32:24,900 --> 00:32:29,520
a lot of ways that AI is going to creep into our 
lives in the next…you know, probably not even  

362
00:32:29,520 --> 00:32:34,080
decades, years, you know. And I think it could 
influence how, you know, some of these things  

363
00:32:34,080 --> 00:32:37,980
that are related to diet. And whether you and 
your colleagues have thought about that at all.

364
00:32:37,980 --> 00:32:42,000
DR. MARY BARKER: That’s an…an amazing question, 
Joe. And the short answer is: No, I haven’t  

365
00:32:42,000 --> 00:32:46,244
thought about it at all. But I would love to hear 
what you think about it. I mean, how is it going  

366
00:32:46,244 --> 00:32:50,460
to affect…how is it going to affect the…the…the 
way that we feed people or the way that we—

367
00:32:50,460 --> 00:32:53,400
AUDIENCE MEMBER (JOE): I mean, the thing I 
think about is, like, we’re…most of us…I’m,  

368
00:32:53,400 --> 00:32:57,300
I’m looking around. A lot of us have these 
fitness watches or activity tracking. You know,  

369
00:32:57,300 --> 00:33:02,340
people are using, you know, calorie counting 
apps or other diet apps. And, like, you know,  

370
00:33:02,340 --> 00:33:05,400
you get to the point where your watch, you 
know, your iPhone tells you, “You know,  

371
00:33:05,400 --> 00:33:09,300
you haven’t eaten blueberries in a while, so 
you should eat some blueberries.” Right? And  

372
00:33:09,300 --> 00:33:13,183
so how much of it’s going to be our choice 
versus the app’s choice or the, you know…?

373
00:33:13,183 --> 00:33:16,260
DR. MARY BARKER: That’s, well, that’s interesting. 
Now you’ve honed it down onto apps. I do have,  

374
00:33:16,260 --> 00:33:22,380
of course, apps…views on apps and watches. 
They are used by a select few and almost  

375
00:33:22,380 --> 00:33:25,140
always by people who don’t really need 
the nutritional advice because they’re  

376
00:33:25,140 --> 00:33:28,500
probably just fine. So, actually, the 
people that we’re talking about who  

377
00:33:28,500 --> 00:33:32,400
really are needy probably don’t use 
the apps or the watches. And I think  

378
00:33:33,720 --> 00:33:39,240
people like me who use apps and watches—and people 
like you, presumably—we’re fine just as we are.  

379
00:33:39,240 --> 00:33:42,540
And actually, I’m not going to worry about us too 
much. I’m much, much more bothered about people  

380
00:33:42,540 --> 00:33:47,040
who don’t use that…have that kind of access to 
AI. What I thought you were going to talk about  

381
00:33:47,040 --> 00:33:53,160
is actually the way that maybe the kind of food 
marketing and food retailers work, which I am  

382
00:33:53,160 --> 00:33:58,080
sure there must be AI involved in the algorithms 
they use, or there must be algorithms they use  

383
00:33:58,080 --> 00:34:02,940
for supplying different areas of the country and 
different shops with different food. We know that  

384
00:34:02,940 --> 00:34:07,260
the convenience stores, for example, you know, are 
very clever at meeting the needs of the local…or  

385
00:34:07,260 --> 00:34:10,680
the demand from the local populations. 
And therefore, constrain access to…to—

386
00:34:10,680 --> 00:34:13,800
AUDIENCE MEMBER (JOE): Well, and…and I don’t 
mean to dominate the conversation. I think  

387
00:34:13,800 --> 00:34:17,460
the last question plays into that with 
the mom who’s talking about, you know,  

388
00:34:17,460 --> 00:34:21,430
her kids on screen time. You know, it’s the, you 
know, the advertising that they’re exposed to—

389
00:34:21,457 --> 00:34:23,896
in those apps, 
as well, might be targeted towards them—

390
00:34:23,896 --> 00:34:24,453
DR. MARY BARKER: Yep.

391
00:34:24,453 --> 00:34:26,023
AUDIENCE MEMBER (JOE): —in certain 
ways around their eating choices.

392
00:34:26,023 --> 00:34:32,100
DR. MARY BARKER: I think there is a criminal, 
criminal lack of attention to the…to the way food  

393
00:34:32,100 --> 00:34:37,020
is marketed to children. But I think…I’d like to 
think…certainly in the U.K., there’s been certain  

394
00:34:37,020 --> 00:34:42,960
push to legislate and to…to limit the amount 
of food marketing to children. But it’s been  

395
00:34:42,960 --> 00:34:47,820
pushed backed by our glorious government 
often. Sorry. Don’t let me get political.

396
00:34:47,820 --> 00:34:54,480
DR. ASHLEY VARGAS: So, this is a tremendous talk, 
and it really reminded me of all the things when  

397
00:34:54,480 --> 00:34:58,500
I was growing up when we didn’t have a lot of 
resources, and now I’m a different place. So,  

398
00:34:58,500 --> 00:35:03,360
thank you for, I think, bringing it back to 
the human. I’m wondering, as…as a biologist,  

399
00:35:04,140 --> 00:35:10,080
this sort of stuff seems like we can’t fix it. 
Like, this is just too hard to fix. All of these  

400
00:35:10,080 --> 00:35:13,800
limitations that people have to deal with. It’s 
so much easier to think about the mechanisms  

401
00:35:13,800 --> 00:35:18,240
and the biology and what gene is interacting 
with what gene. And that’s hard to know. I  

402
00:35:18,240 --> 00:35:23,520
wondered if you had an example where…where an 
intervention was successful. Because you kind  

403
00:35:23,520 --> 00:35:28,740
of hinted at public health interventions being 
difficult and challenging. And I know it’s hard  

404
00:35:28,740 --> 00:35:33,540
to…to…to work with the populations that we really 
need to work with. But is there a silver lining  

405
00:35:33,540 --> 00:35:38,040
or a glimmer of something that you…you have 
seen work or a model that you have seen work?

406
00:35:38,040 --> 00:35:49,200
DR. MARY BARKER: That’s a really good question. 
Yes, there are. There are models. And there  

407
00:35:49,200 --> 00:35:54,120
are…we know there are—at a policy level, a 
structural level—there are things that we  

408
00:35:54,120 --> 00:36:02,400
know that work. Like unconditional financial 
benefits. We know they raise people’s health  

409
00:36:03,240 --> 00:36:09,000
standards and…and…improve their lives. But 
we don’t offer them. We know that things  

410
00:36:09,000 --> 00:36:14,460
like what we call Sure Start in the U.K., we know 
that…so, this is a bit like your Healthy Start,  

411
00:36:14,460 --> 00:36:20,160
very well organized. We know that the families who 
have a lot of engagement with Sure Start do…do so  

412
00:36:20,160 --> 00:36:24,360
much better. The Family Nurse Partnership, 
for example, that’s…or the Nurse-Family  

413
00:36:24,360 --> 00:36:29,760
Partnership, I think you call it here. That’s been 
incredibly successful long term in preventing the  

414
00:36:29,760 --> 00:36:34,020
children born to…to mothers who live in very 
difficult circumstances being sucked back into  

415
00:36:34,020 --> 00:36:39,780
kind of repeat cycles of deprivation. There are 
structural interventions which we know work. Now,  

416
00:36:39,780 --> 00:36:45,900
they’re a long, long way from the biology. I’m 
very sorry. But actually, they are…the structural  

417
00:36:45,900 --> 00:36:49,860
ones seem to be the interventions that work. 
The individual-level interventions are much,  

418
00:36:49,860 --> 00:36:56,280
much harder to…to…to get right. There are…and 
I’m talking public health here. I think if you  

419
00:36:56,280 --> 00:37:01,440
then hone down on particular populations who have 
particular clinical needs, we’re much better at  

420
00:37:01,440 --> 00:37:06,180
designing effective interventions and working with 
those groups effectively. But that’s because—in  

421
00:37:07,020 --> 00:37:11,520
my view—because they already have a fundamental 
motivation to engage. You have diabetes,  

422
00:37:11,520 --> 00:37:15,600
you’re much more likely to engage. You’re still 
not very likely to engage, but you’re much more  

423
00:37:15,600 --> 00:37:19,320
likely to engage than you are…when you’re a 
young person, you’re going to live forever,  

424
00:37:20,160 --> 00:37:24,780
you’re fine. Why would you engage in public 
health intervention? Because you’re fine. So…so  

425
00:37:25,620 --> 00:37:30,180
it comes down in…in terms of individual-level 
interventions and behavioral intervention, it  

426
00:37:30,180 --> 00:37:35,982
comes down to a kind of…an existing motivational 
state, and we know that, too. Yes, there are  

427
00:37:35,982 --> 00:37:40,721
glimmers of hope. But I don’t know where the 
biology fits into that. Sorry. That’s your job.

428
00:37:40,721 --> 00:37:44,160
DR. KRISTA ZANETTI: I’m going to piggy…I’m going 
to piggyback really quickly off Ashley’s question.  

429
00:37:44,160 --> 00:37:49,800
We do have an online question, then we’ll get to 
you, Drew, so we have a plan. Piggybacking off  

430
00:37:49,800 --> 00:37:56,280
of Ashley’s question, thinking about this from the 
perspective of what scientific questions we should  

431
00:37:56,280 --> 00:38:01,980
be asking…so, going back to thinking about a path 
forward or strategies to improve the ability for  

432
00:38:01,980 --> 00:38:07,020
those people facing these constraints and their 
ability to focus on healthy diet and nutrition,  

433
00:38:08,220 --> 00:38:13,680
what do we think are scientific questions 
we should be asking to further explore how  

434
00:38:13,680 --> 00:38:17,040
to address these issues? Because I think a lot 
of what we’re trying to think about today is:  

435
00:38:17,040 --> 00:38:23,460
What are the questions we need to be asking, and 
how are we going to address these challenges? So,  

436
00:38:23,460 --> 00:38:28,260
do you have any thoughts on, you know, 
maybe what…what we need to ask or what  

437
00:38:28,260 --> 00:38:32,460
has been asked? And…and you had mentioned some 
other studies that, you know, maybe needs to  

438
00:38:32,460 --> 00:38:37,620
be redesigned as far as adolescents. It’s sort of 
two different things. But it…it brings me back to:  

439
00:38:37,620 --> 00:38:42,420
What are those key scientific questions 
we need to be asking to help address these  

440
00:38:42,420 --> 00:38:46,483
issues and individuals that are facing these 
constraints that seem to be over…overwhelming?

441
00:38:46,483 --> 00:38:51,240
DR. MARY BARKER: So, most of my thinking 
about, you know, how we get this right is…is  

442
00:38:51,240 --> 00:38:56,460
about adolescents. And I do think adolescents 
are a really, really important population for  

443
00:38:56,460 --> 00:39:02,280
us to focus on as a scientific community because 
the…the potential there is so huge. So, when I’m  

444
00:39:02,280 --> 00:39:05,280
thinking…when we’re thinking about adolescents 
and we’re working with doing a particularly  

445
00:39:05,280 --> 00:39:10,200
interesting piece of work at the moment looking 
at the intersect between culture and cultural  

446
00:39:10,200 --> 00:39:18,000
experience. Not…not…not…it’s kind of arts and 
culture, rather than…creative culture rather than  

447
00:39:18,000 --> 00:39:24,060
any other…definition of culture. And it’s taken 
us down a road of thinking very much about how we  

448
00:39:24,060 --> 00:39:28,620
engage young people in thinking about their diet 
and their health and their well-being generally.  

449
00:39:29,880 --> 00:39:35,160
And what we have found based on two very 
interesting published papers, which looked  

450
00:39:35,160 --> 00:39:39,480
at great big cohorts very long-running 
cohorts—and I can find both of those papers  

451
00:39:39,480 --> 00:39:44,160
if anyone’s interested—is that actually, if you 
raise young people’s aspirations for themselves,  

452
00:39:44,160 --> 00:39:47,340
general aspirations, you know, “What do you 
want to do when you grow up?” kind of questions,  

453
00:39:47,340 --> 00:39:54,720
“How can we support to…to…to achieve that?” If you 
do that, then health benefits follow. And we know  

454
00:39:54,720 --> 00:40:00,360
this because raising young people’s aspirations 
is associated…or young people’s aspirations are  

455
00:40:00,360 --> 00:40:05,940
associated in observational studies, longitudinal 
studies, with better health and well-being long  

456
00:40:05,940 --> 00:40:13,920
term; better…better life satisfaction as adults, 
as middle-aged adults; and longevity. So…so,  

457
00:40:15,720 --> 00:40:21,600
the thinking that we’re doing at the moment is 
(a) what’s…how does that work? So, if you raise  

458
00:40:21,600 --> 00:40:26,340
young people’s aspirations, it seems to kind of 
dawn on them that actually…well, in fact, they  

459
00:40:26,340 --> 00:40:29,280
know. If you have these conversations with young 
people—and we’re working on methods of having  

460
00:40:29,280 --> 00:40:33,420
those conversations effectively at the moment—is 
it dawns on them that, actually, they have to  

461
00:40:33,420 --> 00:40:37,860
learn to eat properly, they have to…they have 
to look after themselves, they have to exercise,  

462
00:40:37,860 --> 00:40:42,660
they have to eat well in order to achieve 
those things that they want to achieve. So,  

463
00:40:43,200 --> 00:40:47,940
so the…the…and this is a long ways from diet and 
nutrition, but if you can work with educational  

464
00:40:47,940 --> 00:40:51,600
establishments, if you can work with cultural 
establishments, if you can work across the board,  

465
00:40:51,600 --> 00:40:56,700
as we said, with young people to raise their 
aspirations, then you may well have a fighting  

466
00:40:56,700 --> 00:41:01,920
chance of improving their diet, their health, 
their mental health, their general well-being.  

467
00:41:02,760 --> 00:41:07,620
And…and it’s about…perhaps the big scientific 
challenge for us, then, is how do we raise young  

468
00:41:07,620 --> 00:41:13,080
people’s aspirations? And I go…I go back to that 
adolescent nutrition paper in the Lancet, the…the  

469
00:41:13,080 --> 00:41:18,900
policy programs paper, which said these approaches 
have to be intersectional. Now, you sat here in…in  

470
00:41:18,900 --> 00:41:25,020
NIH are in a very good position to pull those 
intersectional levers. And it strikes me that  

471
00:41:25,020 --> 00:41:30,960
very few other organizations or institutions can 
do that in the way that you can. So, over to you.

472
00:41:30,960 --> 00:41:37,560
DR. MONTESSA MITCHELL: All right. first,  

473
00:41:37,560 --> 00:41:43,080
you did get a kudos in the Q&A for your first 
response. They said, “Excellent response.”  

474
00:41:44,400 --> 00:41:48,960
And your second question is: How have you explored 
the impact of social determinants of health on  

475
00:41:48,960 --> 00:41:54,480
young mothers’ eating habits, specifically the 
impact of types of jobs and time for eating?

476
00:41:54,480 --> 00:41:58,500
DR. MARY BARKER: Well, that’s another really, 
really good question. We’ve explored those  

477
00:41:58,500 --> 00:42:02,640
things qualitatively and quantitatively 
to some extent. And the…and the…the  

478
00:42:04,140 --> 00:42:09,420
slide that I showed…go back to it. Don’t know 
where it went. I actually managed to mess  

479
00:42:11,340 --> 00:42:14,940
up…which is the one that I wanted? This one. 
I don’t know how I get it back on display now.  

480
00:42:16,860 --> 00:42:24,180
That’s right. That one. So, that was part 
of an exploration of all the things that  

481
00:42:24,180 --> 00:42:29,760
we thought might affect young…young women’s 
diets and ability to feed themselves. So…so,  

482
00:42:30,720 --> 00:42:36,300
we did ask them in the big survey that we 
did with, with 372 young women with families,  

483
00:42:36,300 --> 00:42:40,980
about whether they work and whether they didn’t 
work, and about how time was an issue. And the  

484
00:42:40,980 --> 00:42:45,180
interesting thing about time, and it comes up when 
you have…in all the discussions that we’ve had,  

485
00:42:45,180 --> 00:42:49,800
both in the interviews and in the policy work, 
is that time is a kind of…everybody doesn’t  

486
00:42:49,800 --> 00:42:56,100
have enough time. And time is a sort of proxy for 
how important this is to you. Because, actually,  

487
00:42:56,100 --> 00:43:01,140
all of us find time for things that are really, 
really important to us. And I think we just come  

488
00:43:01,140 --> 00:43:06,900
back to the point that having…not having time 
to cook is probably more to do with the fact  

489
00:43:06,900 --> 00:43:12,180
that other things are more important, like the 
fact that you have to run two jobs or like the  

490
00:43:12,180 --> 00:43:17,880
fact that actually you…you…you scoot in on your 
heels to pick up your kids from school to get them  

491
00:43:17,880 --> 00:43:21,840
home. They’re starving. You feed them whatever 
you can as fast as possible because otherwise  

492
00:43:22,380 --> 00:43:27,420
you get earache. So…so, time is a funny thing, 
and it’s the first thing that we all say that  

493
00:43:27,420 --> 00:43:32,940
we don’t have, we don’t have access to. 
But very often, it’s a…it’s a relative  

494
00:43:32,940 --> 00:43:38,520
response to…to what it is. So, it’s more 
about…if we’re going to then work with families,  

495
00:43:38,520 --> 00:43:42,720
it’s more about working with their priorities. 
So, what are your priorities? What do you have  

496
00:43:42,720 --> 00:43:50,760
to do first? How could we support you so that you 
can find time to do this cooking that you want to  

497
00:43:50,760 --> 00:43:55,980
do? And…and having those conversations. And we 
have developed a…a very good method of having  

498
00:43:55,980 --> 00:43:59,760
conversations with large numbers of people, 
which I can talk about later, to support them  

499
00:43:59,760 --> 00:44:05,675
to make those changes. Does that answer the 
question? Good. Drew had a question for us.

500
00:44:05,675 --> 00:44:07,116
DR. KRISTA ZANETTI: Yes, Drew. I 
think we have time for one more.

501
00:44:07,116 --> 00:44:09,000
AUDIENCE MEMBER (DREW): Yes. And this 
is more of a…more of a comment than  

502
00:44:09,000 --> 00:44:11,650
a question. And…and first of 
all, Mary, thank you. This is—

503
00:44:11,676 --> 00:44:15,060
AUDIENCE MEMBER (DREW): —super important. 
And…and to follow on what Ashley mentioned  

504
00:44:15,060 --> 00:44:19,380
and…and what you had talked about, there 
was…schools are another venue where…where  

505
00:44:19,380 --> 00:44:24,960
there is opportunity for…for interventions in 
the…in the…nutrition space. And that’s…and…and  

506
00:44:24,960 --> 00:44:29,280
that became quite evident during COVID 
when…when kids lost access to school.

507
00:44:29,280 --> 00:44:30,006
DR. MARY BARKER: Yeah.

508
00:44:30,006 --> 00:44:34,319
AUDIENCE MEMBER (DREW): And I…what I…what I really 
appreciate about…about your…your lens, Mary, is  

509
00:44:34,320 --> 00:44:38,280
we…we spent a lot of time yesterday really focused 
on the…on…on the early part of the first 1,000  

510
00:44:38,280 --> 00:44:43,620
days, and that’s super important. But that…those 
next 1,000 weeks, or 7,000 days, you know, into  

511
00:44:43,620 --> 00:44:48,780
adolescence, you know, is also, as you mentioned, 
incredibly important. And that’s…and that’s often  

512
00:44:48,780 --> 00:44:52,680
a gap of when we think about longitudinal 
research and think…and think about cohorts,  

513
00:44:52,680 --> 00:44:57,780
we often focus on…on the parents and the children, 
but…but not…not the…not the children as they  

514
00:44:57,780 --> 00:45:02,040
grow up. And so, I think it’s…it’s…as…as we think 
about, you know, moving…moving the field forward,  

515
00:45:02,040 --> 00:45:06,360
you know, that…that…that adolescent…that early 
childhood/adolescent period is extraordinarily  

516
00:45:06,360 --> 00:45:11,023
important. And that’s often a group of individuals 
that…that gets lost in…in the research space.

517
00:45:11,023 --> 00:45:14,040
DR. MARY BARKER: It absolutely does. And thank 
you for bringing that up. And I meant to say that  

518
00:45:14,040 --> 00:45:18,840
earlier, is that we have ignored adolescents for 
a very long time. We’ve…in…in the research field,  

519
00:45:18,840 --> 00:45:24,300
we kind of just assume that they’re kind of big 
kids or small adults. And they’re not. There…there  

520
00:45:24,300 --> 00:45:28,800
is a distinct and discrete life course phase. 
It has its very own developmental trajectory.  

521
00:45:28,800 --> 00:45:35,040
Astonishing things happen physiologically and 
psychologically during adolescence. You know,  

522
00:45:35,040 --> 00:45:40,500
their brains basically melt and get completely 
reformed. And, sorry, somebody once quoted me  

523
00:45:40,500 --> 00:45:43,620
that…on that, and I felt mortified that I’d 
actually said that, so, please don’t ever quote  

524
00:45:44,760 --> 00:45:49,260
me. Melting brains. I just lose all my kudos 
as a psychologist if I go on saying that.  

525
00:45:50,040 --> 00:45:55,080
But I think…I think, you know, the 
opportunity…it’s…it’s the…it’s the second critical  

526
00:45:55,080 --> 00:45:59,340
life course phase, which we have paid almost no 
attention to. And I can’t quite understand why,  

527
00:45:59,340 --> 00:46:02,340
except that a lot of people find adolescents 
quite scary and difficult to deal with.  

528
00:46:03,420 --> 00:46:10,780
Yeah, they are, but, you know, it’s 
fun. Does that answer? Okay. Thank you.

529
00:46:10,780 --> 00:46:14,940
DR. KRISTA ZANETTI: Well, I think for…to 
keep us on time, even though I…I’m sure  

530
00:46:14,940 --> 00:46:20,820
there are…there’s much more to discuss, that was 
really a, you know, an excellent presentation and  

531
00:46:20,820 --> 00:46:24,780
great discussion. So, I want to thank everybody 
who contributed to the discussion and thank Dr.  

532
00:46:24,780 --> 00:46:30,660
Barker for her thoughtful feedback and a great 
talk. And you set the stage quite nicely for  

533
00:46:30,660 --> 00:46:35,760
our day two presentations and discussions that 
are going to focus on nutritional influences  

534
00:46:35,760 --> 00:46:39,660
beyond individuals. So, we’re looking forward 
to the rest of the day. So, having said that,  

535
00:46:39,660 --> 00:46:45,660
I am going to turn it over to our third 
session, to Dr. Somdat Mahabir from the  

536
00:46:45,660 --> 00:46:50,160
National Cancer Institute. Oh, yes. Sorry. 
Let’s give Dr. Barker a round of applause.  

537
00:46:51,780 --> 00:46:56,040
And I will now turn it over to Dr. Somdat 
Mahabir from the National Cancer Institute  

538
00:46:56,040 --> 00:47:00,360
to introduce the next session and 
our speakers. And…and thank you all.

539
00:47:00,360 --> 00:47:06,780
DR. SOMDAT MAHABIR: Good morning, again. Thank 
you very much, Krista. That was a great session.  

540
00:47:06,780 --> 00:47:11,940
I think most of us could…can relate to the things 
that were said there. In fact, most people.  

541
00:47:14,220 --> 00:47:23,760
So, welcome to session three. And this session 
is on family and society-level aspects of  

542
00:47:23,760 --> 00:47:30,240
multigenerational influence of nutrition. And I 
am Somdat from the National Cancer Institute. I’ll  

543
00:47:30,240 --> 00:47:35,520
be your moderator for this session. I’m also 
a member of the planning committee, and I’m  

544
00:47:35,520 --> 00:47:41,340
really happy the way how this meeting has kind of 
turned out and look forward to all the sessions.  

545
00:47:43,500 --> 00:47:50,340
Also like to thank Dr. Kellie Casavale from 
FDA who has been assisting me here. She will  

546
00:47:50,340 --> 00:47:56,040
be serving as my copilot. Hopefully, 
we’ll run the session smoothly. So,  

547
00:47:56,580 --> 00:48:02,520
Dr. Merilee Brockaway will begin the session and 
join us virtually from the University of Calgary,  

548
00:48:03,060 --> 00:48:09,420
with a presentation on maternal health, delivery 
method, and lactation-related influences.  

549
00:48:10,920 --> 00:48:17,400
The rest of her session will be presented from 
right here in the room, at the NIH campus that  

550
00:48:17,400 --> 00:48:23,640
we’re in here, in this room. And Dr. Kristen 
Stowers from the University of Connecticut  

551
00:48:23,640 --> 00:48:28,980
will be present on food, environment, and 
environmental justice. Very interesting  

552
00:48:28,980 --> 00:48:36,300
topic. Then we’ll move onto Dr. Joseph Brown 
from Brown University School of Public Health.  

553
00:48:37,560 --> 00:48:43,080
And his presentation will be on food 
contaminants that have multigenerational  

554
00:48:43,080 --> 00:48:50,460
effects and nutrition-related outcomes. Last 
but not least, we’ll then listen to Dr. Carrie  

555
00:48:50,460 --> 00:48:55,440
Breton from the Keck School of Medicine 
of the University of Southern California,  

556
00:48:55,440 --> 00:49:03,360
and she’ll present on the effects of the built 
environment on multigenerational nutrition-related  

557
00:49:03,360 --> 00:49:10,200
health and disease. So, I will now turn it 
over to Dr. Brockaway to get us started.

558
00:49:10,200 --> 00:49:11,580
DR. MERILEE (MEREDITH) BROCKWAY: Thank you very 
much. Can everyone see my presentation screen? All  

559
00:49:11,580 --> 00:49:18,960
right. Well, I want to thank you for inviting 
me to present. Thank you to Ashley and Krista,  

560
00:49:19,920 --> 00:49:23,880
and I want to highlight that I’m going to 
be talking about maternal health, delivery,  

561
00:49:23,880 --> 00:49:30,900
but really centered around lactation and that 
impact it has on infant health and long term  

562
00:49:30,900 --> 00:49:38,100
health outcomes. So, I do want to acknowledge 
that I do have some funding and thank my funders,  

563
00:49:38,100 --> 00:49:43,740
but none of my funding is in conflict with what 
I’m presenting today. Also, coming from Calgary,  

564
00:49:43,740 --> 00:49:49,140
it is our tradition in Canada to acknowledge the 
traditional territories from which we come. So,  

565
00:49:49,140 --> 00:49:54,180
here in Calgary is the traditional territories 
of the people of Treaty 7 region, in southern  

566
00:49:54,180 --> 00:49:59,820
Alberta, and the city of Calgary is also home 
to the Métis Nation of Alberta, Region 3. And  

567
00:49:59,820 --> 00:50:06,840
we thank our traditional peoples for their…for 
their lens. So what we’re going to discuss today  

568
00:50:06,840 --> 00:50:13,140
is we’re going to discuss how breastfeeding and 
human milk feeding impact child health outcomes.  

569
00:50:14,220 --> 00:50:21,420
We’re going to explore maternal factors in human 
milk and how human milk composition and breastmilk  

570
00:50:21,420 --> 00:50:26,880
production are informed by those. We’re going 
to explore the impact of labor and delivery  

571
00:50:26,880 --> 00:50:31,920
on breastfeeding and the microbiome. We’re going 
to explore breastfeeding supplementation options  

572
00:50:31,920 --> 00:50:37,500
because we know not all infants can breastfeed. 
And then we’re going to talk about the challenges  

573
00:50:37,500 --> 00:50:44,460
and opportunities in lactation and breastfeeding 
research. So, I think we’re all familiar with the  

574
00:50:44,460 --> 00:50:48,660
World Health Organization recommendations and 
many health organization recommendations about  

575
00:50:48,660 --> 00:50:53,700
breastfeeding exclusivity for the first 
6 months of life, and then continued and  

576
00:50:53,700 --> 00:50:59,820
sustained breastfeeding for 2 years and beyond. 
And likely you’re all familiar with the hierarchy  

577
00:50:59,820 --> 00:51:06,120
of evidence, but when we overlay that with the 
child health benefits related to breastfeeding,  

578
00:51:06,120 --> 00:51:11,400
we can see that there’s varied evidence…levels of 
evidence for how breastfeeding relates to child  

579
00:51:11,400 --> 00:51:16,020
health outcomes. So we have strong evidence 
for things like necrotising enterocolitis  

580
00:51:16,020 --> 00:51:21,120
in pre-term infants, ear infections, 
respiratory infections, and GI infections.  

581
00:51:21,660 --> 00:51:25,920
Those are systematic reviews. We’ve actually 
got systematic reviews of systematic reviews  

582
00:51:25,920 --> 00:51:31,140
on that. And then medium-level evidence where 
we may have a few systematic reviews not quite  

583
00:51:31,140 --> 00:51:36,840
so many studies or clear associations between 
things like asthma and allergies, SIDS, obesity,  

584
00:51:37,620 --> 00:51:42,840
things like that and breastfeeding. And then much 
weaker evidence looking at cognitive development,  

585
00:51:42,840 --> 00:51:49,260
type II diabetes, and metabolic issues, and dental 
carries with breastfeeding. And I’ve just taken  

586
00:51:49,260 --> 00:51:54,180
the liberty of moving asthma and allergy…allergy 
into the medium levels of evidence because we’re  

587
00:51:54,180 --> 00:51:57,960
starting to see quite a good…bit more good 
evidence come out supporting the relationship  

588
00:51:57,960 --> 00:52:03,180
with breastfeeding, and I’m going to talk about 
that later. But we do have to be careful that  

589
00:52:03,180 --> 00:52:08,400
historically our information and our evidence 
around breastfeeding is pretty much based on  

590
00:52:08,400 --> 00:52:13,680
observational data, clearly because it’s hard to 
do experimental research in human populations.  

591
00:52:14,700 --> 00:52:20,700
But we have started to see some very good 
research come out about breastfeeding,  

592
00:52:20,700 --> 00:52:25,800
and one example I’m going to highlight here is 
the child study out of Canada. There’s other  

593
00:52:25,800 --> 00:52:31,980
cohort studies similar across the world. But for 
us in our context, the child study, it’s a large  

594
00:52:31,980 --> 00:52:37,920
cohort study, of about 3,000 families. It was 
one of the first studies to actually ask good  

595
00:52:37,920 --> 00:52:43,200
questions about breastfeeding and then look 
at biological outcomes such as stool samples,  

596
00:52:43,200 --> 00:52:46,980
blood draws, things like that, and 
start to look at mechanistic effects.  

597
00:52:47,700 --> 00:52:52,800
So, what they really have sought out—and part of 
this child program—is looking at how breastfeeding  

598
00:52:52,800 --> 00:52:58,320
relates to those health outcomes that we have seen 
with the levels of evidence and trying to identify  

599
00:52:58,320 --> 00:53:04,380
mechanisms of how breastfeeding and breastmilk can 
form those outcomes. Things like gut microbiota,  

600
00:53:04,380 --> 00:53:08,940
epigenetics, metabolism, lung function, 
immunity—things we heard about yesterday.  

601
00:53:10,260 --> 00:53:16,200
And a lot of that clearly comes from milk 
composition. So what’s in the milk? The  

602
00:53:16,200 --> 00:53:21,420
microbiota, the human milk oligosaccharides, 
immune factors, fatty acids, hormones,  

603
00:53:21,420 --> 00:53:28,620
and vitamins, and how those impact the mechanisms 
of child health. But of course, we have a pretty  

604
00:53:28,620 --> 00:53:35,820
good understanding that maternal health, both 
physically, mentally, and socially, do impact milk  

605
00:53:35,820 --> 00:53:42,240
composition and…and subsequently those mechanisms. 
And we have modifiable health issues…aspects like  

606
00:53:42,240 --> 00:53:49,260
obesity, nutrition and then…confidence and 
lifestyle choices. And then we have fixed  

607
00:53:49,260 --> 00:53:54,720
aspects that can inform milk composition, 
like age, genetics, ethnicity. And also,  

608
00:53:54,720 --> 00:54:02,700
those do also inform biologically infant health 
outcomes and successfully the breastfeeding that  

609
00:54:02,700 --> 00:54:11,400
can—if mom is successful with breastfeeding—and 
can sustain it for as long as possible. So when  

610
00:54:11,400 --> 00:54:17,460
we compare human milk composition or breastmilk 
composition to formula, we can see—and I have two  

611
00:54:17,460 --> 00:54:24,660
different descriptions here…or pictures—we can see 
formula originally was created as a nutritional  

612
00:54:24,660 --> 00:54:29,520
replacement. So the macro…micronutrients of 
breastmilk, back when we didn’t have a very  

613
00:54:29,520 --> 00:54:35,520
good understanding of all the different components 
in breastmilk. But now we know breastmilk has a  

614
00:54:35,520 --> 00:54:42,060
variety of biotic components, it’s got immuno 
components, it’s got hormones and vitamins,  

615
00:54:42,060 --> 00:54:49,500
and things we’re really trying to work hard now to 
replicate in different formula products. And so,  

616
00:54:49,500 --> 00:54:54,660
as we start to produce different formula products 
that have these different components, we’re very  

617
00:54:54,660 --> 00:55:00,360
interested now in looking at breastmilk to see 
what is in breastmilk and…and how we can study it.  

618
00:55:01,020 --> 00:55:07,380
So, with that in mind, in our postdoc lab—I did a 
postdoc with Dr. Meghan Azad out of the University  

619
00:55:07,380 --> 00:55:13,200
Manitoba—we asked the question: how does human 
milk composition inform child growth? And I have  

620
00:55:13,200 --> 00:55:18,300
to tell you, this was an overly ambitious 
question. We conducted a systematic review  

621
00:55:19,380 --> 00:55:26,340
and ended up reviewing almost 10,000 abstracts 
for screening and ended up with three distinct  

622
00:55:26,340 --> 00:55:32,220
manuscripts, one of which has been published—it’s 
up here—looking at micronutrients. So we had 28  

623
00:55:32,220 --> 00:55:38,580
articles looking at micronutrients, 57 looking 
at macronutrients, and 75 looking at bioactives.  

624
00:55:38,580 --> 00:55:43,440
So I’m not really going to talk about the 
results we found because actually, in a lot  

625
00:55:43,440 --> 00:55:48,960
of situations we struggled to identify consistent 
associations between many human milk components,  

626
00:55:48,960 --> 00:55:56,820
specifically the bioactives, and infant growth. 
And that’s because we found that over…over 85  

627
00:55:56,820 --> 00:56:01,860
percent of those studies really struggled with 
quality. They were either moderate or low quality.  

628
00:56:01,860 --> 00:56:07,500
And a lot of that was really…really related to 
failing to adequately account for confounding,  

629
00:56:07,500 --> 00:56:15,000
specifically breastfeeding exclusivity 
and maternal factors that inform human  

630
00:56:15,000 --> 00:56:22,380
milk composition. So those are two very important 
aspects of breastfeeding and human lactation that  

631
00:56:22,380 --> 00:56:27,120
really were missed by a lot of studies exploring 
human milk composition and in…infant growth.  

632
00:56:28,320 --> 00:56:32,580
So with that, I want to move 
onto talking about maternal  

633
00:56:32,580 --> 00:56:37,080
factors that play a role in human milk 
composition but also in breastfeeding.  

634
00:56:37,920 --> 00:56:45,600
So, I think it became apparent from Dr. Barker’s 
presentation that nutrition is complex, there’s  

635
00:56:45,600 --> 00:56:51,180
lots of different social influences, and that is 
also true with breastfeeding. So breastfeeding is  

636
00:56:51,180 --> 00:56:57,780
a complex interplay between mother and infant and 
the environment. And Dr. Lars Bode has posed it as  

637
00:56:57,780 --> 00:57:04,140
kind of a triadic relationship, not only between 
mother and infant and…but also the human milk. So,  

638
00:57:04,140 --> 00:57:08,520
it’s kind of a triadic relationship. But 
there’s also other things to consider,  

639
00:57:08,520 --> 00:57:15,840
such as environmental influences. So, what mom 
is exposed to can influence milk composition.  

640
00:57:16,980 --> 00:57:21,540
Social influences can influence how 
successful mom is with breastfeeding,  

641
00:57:21,540 --> 00:57:27,780
perceived milk insufficiency, or if they choose to 
continue breastfeeding long term or exclusively.  

642
00:57:27,780 --> 00:57:32,880
And then, of course, economic influences. 
We consistently see in the literature that  

643
00:57:32,880 --> 00:57:38,160
mothers who are of higher socio-economic status 
tend to be more successful with breastfeeding.  

644
00:57:38,760 --> 00:57:43,740
And then cultural influences, as well. When 
you look across countries globally, we see  

645
00:57:43,740 --> 00:57:48,900
much different breastfeeding rates. The UK, for 
example, has very low breastfeeding rates. Canada,  

646
00:57:48,900 --> 00:57:55,320
we have quite high. And the U.S. is in the…the 
80s for initiation. So, really culture has a big  

647
00:57:55,320 --> 00:58:01,020
role to play on that. But when we think about the 
direct effects of maternal health on breastfeeding  

648
00:58:01,020 --> 00:58:09,000
behaviors, human milk production, and composition, 
we have limited evidence. So, with nutrition it  

649
00:58:09,000 --> 00:58:13,440
would…you would think that what mom eats would 
directly impact the milk composition, but that’s  

650
00:58:13,440 --> 00:58:18,960
not necessarily true. In fact, we only have 
pretty strong evidence looking at fatty acids,  

651
00:58:18,960 --> 00:58:25,680
such as fish composition. That does improve DHA in 
human milk composition. Vitamin C is another one.  

652
00:58:25,680 --> 00:58:32,280
And I’ve just highlighted one study that looks at 
fructose, because we have a lot more fructose in  

653
00:58:32,280 --> 00:58:36,960
our diet, and actually, fructose transports right 
into the breastmilk, and we do see quite high  

654
00:58:36,960 --> 00:58:43,980
fructose levels in breastmilk, so that’s something 
that’s interesting. Obesity is another issue that  

655
00:58:43,980 --> 00:58:48,960
interplays with human milk composition but also 
with breastfeeding. So we know that mothers who  

656
00:58:48,960 --> 00:58:55,380
are obese tend to have issues with lactogenesis, 
so they have delayed milk production and often  

657
00:58:55,380 --> 00:59:00,660
tend to supplement a lot more than mothers who are 
not obese. We also have seen some evidence that  

658
00:59:00,660 --> 00:59:05,700
there’s higher fat concentrations and higher 
lactose concentrations in their breastmilk.  

659
00:59:07,200 --> 00:59:13,560
Mothers who have endocrine issues such as 
diabetes, thyroid, or polycystic ovarian syndrome,  

660
00:59:14,520 --> 00:59:19,740
really struggle with lactogenesis. So if those 
are untreated or not managed well, we see that  

661
00:59:19,740 --> 00:59:24,600
these mothers tend to supplement or struggle with 
breastfeeding, and so their babies tend to get  

662
00:59:24,600 --> 00:59:31,200
less breastmilk. We’ve also done some research 
looking at mothers who have chronic illness, and  

663
00:59:31,200 --> 00:59:37,620
if their symptoms aren’t well managed, they tend 
to stop breastfeeding a lot earlier than mothers  

664
00:59:37,620 --> 00:59:42,900
who don’t have chronic illness, and they also are 
less likely to exclusively breastfeed. So we see  

665
00:59:42,900 --> 00:59:48,420
some challenges there. And then mental health is 
an interesting one and a hard conundrum to nail  

666
00:59:48,420 --> 00:59:53,820
down because we see that moms with mood disorders, 
such as depression, are less likely to breastfeed.  

667
00:59:53,820 --> 00:59:58,620
But we’re not sure which to really…way that 
relationship goes. We don’t know if breastfeeding  

668
00:59:58,620 --> 01:00:05,700
leads to lower…or…sorry, if breastfeeding leads 
to reduced depression, or if depression leads to  

669
01:00:05,700 --> 01:00:09,960
reduced breastfeeding. So we’re not sure if…if 
the chicken comes before the egg on that one.  

670
01:00:11,820 --> 01:00:17,100
And then the social environment, of course. 
So breastfeeding success is very contingent  

671
01:00:17,100 --> 01:00:22,440
on the social surroundings. So, if mothers are 
surrounded by mothers and aunties and sisters  

672
01:00:22,440 --> 01:00:27,420
that have breastfed, they’re likely more…more 
likely to continue to breastfeed and be more  

673
01:00:27,420 --> 01:00:32,040
successful compared to mothers who are 
not surrounded by those who breastfeed.  

674
01:00:34,320 --> 01:00:41,700
So thinking about…going forward about the impacts 
of labor and delivery, the impacts on mom and baby  

675
01:00:41,700 --> 01:00:47,100
and breastfeeding success, but also, I’m 
going to thread that into the microbiome,  

676
01:00:47,100 --> 01:00:54,240
because a lot of my work looks at the microbiome 
and infant health. So we learned yesterday, and  

677
01:00:54,240 --> 01:01:00,000
I’m sure all of you are aware, that the microbiome 
is very important for developing infant health.  

678
01:01:00,000 --> 01:01:06,600
There’s that critical window of about 1,000 days 
from conception to 2 years of age, whereas if we  

679
01:01:06,600 --> 01:01:13,440
have a dysbiotic microbiome, we’re going to see 
likely some adverse childhood health outcomes  

680
01:01:13,440 --> 01:01:19,860
as opposed to if we have a eubiotic or a good 
microbiome. And we all know early life exposures  

681
01:01:19,860 --> 01:01:28,080
can really inform that microbiome. But also, we 
have to understand that the experience of birth  

682
01:01:28,080 --> 01:01:33,720
in hospital can inform breastfeeding outcomes 
as well. So if breastfeeding is successful. So  

683
01:01:33,720 --> 01:01:38,880
this is kind of multifaceted. So I just want to 
highlight a typical birthing experience in North  

684
01:01:38,880 --> 01:01:44,700
America. It’s pretty similar to Canada in the 
United States, but I tried to make the numbers as  

685
01:01:44,700 --> 01:01:51,480
U.S.-centric as possible. So about 98% of births 
happen in hospital, and about 30% of those births  

686
01:01:51,480 --> 01:01:56,760
are born via C-section. So we know C-section 
deliveries are sterile, and we have a disruption  

687
01:01:56,760 --> 01:02:01,140
to the microbiome there. And you’ll see later, 
they’re also very disruptive to breastfeeding.  

688
01:02:01,860 --> 01:02:08,100
And then the antibiotic exposure piece. We 
have about 40% of infants who are exposed to  

689
01:02:08,100 --> 01:02:14,880
antibiotics in labor or early in life. So that’s 
through group B strep prophylaxis that’s possibly  

690
01:02:14,880 --> 01:02:20,940
due to premature prolonged rupture of membranes. 
If moms have a fever and if moms have a C-section,  

691
01:02:20,940 --> 01:02:27,000
we often give antibiotics prophylactically. So 
a lot of infants are exposed to antibiotics.  

692
01:02:28,140 --> 01:02:32,280
And then if we look at breastfeeding—so 
initiation rates, they vary a little bit,  

693
01:02:32,280 --> 01:02:38,700
but in Canada, they’re about 96%, and in the 
U.S. they’re 9…or 83%. But regardless of that,  

694
01:02:38,700 --> 01:02:45,180
we see that Caesarean-section babies get 
supplemented to a much higher extent than  

695
01:02:45,180 --> 01:02:50,220
babies who are born vaginally. And that makes 
sense, because a Caesarean-section, it’s major  

696
01:02:50,220 --> 01:02:55,560
abdominal surgery, mom’s had a lot of fluids 
on board, so there’s a lot of aspects that can  

697
01:02:55,560 --> 01:03:01,680
disrupt breastfeeding in the short term, which in 
turn turns to earlier cessation of breastfeeding  

698
01:03:01,680 --> 01:03:07,380
and less exclusive breastfeeding. So, we see that 
the C-section deliveries can significantly impact  

699
01:03:07,380 --> 01:03:12,480
the success of breastfeeding. But also, when you 
think about it from a microbiome perspective,  

700
01:03:12,480 --> 01:03:20,040
you can see that a lot of infants not only have 
one adverse exposure to their microbiome early in  

701
01:03:20,040 --> 01:03:25,980
life, but they can actually have multiple ones. So 
bringing this back to the context of human milk,  

702
01:03:25,980 --> 01:03:31,380
I just want to focus on that antibiotic exposure 
piece. And I just came back from a really great  

703
01:03:31,380 --> 01:03:37,020
microbiome conference where this paper was 
presented. Again, this is from the child study,  

704
01:03:37,020 --> 01:03:43,680
and it really is looking at Bifidobacterium 
longum subspecies infantis. And this  

705
01:03:44,520 --> 01:03:49,200
microbio…microbe came up multiple times during 
this conference. So, it’s really starting to show  

706
01:03:49,200 --> 01:03:56,820
evidence that this particular microbe, now that we 
can do that shallow shotgun deep sequencing, keeps  

707
01:03:56,820 --> 01:04:03,480
coming up as something that is related to good 
infant health outcomes. And this study found that  

708
01:04:03,480 --> 01:04:10,200
breastfeeding was protective of childhood asthma 
when infants were exposed to antibiotics. So, if  

709
01:04:10,200 --> 01:04:15,900
the infants were breastfeeding while they received 
antibiotics, they virtually had no increased risk  

710
01:04:15,900 --> 01:04:21,600
of asthma, but if they weren’t breastfeeding, they 
were three times more likely to develop asthma.  

711
01:04:21,600 --> 01:04:25,500
So, when they explored this from a microbiome 
perspective, they found it was really related  

712
01:04:25,500 --> 01:04:34,920
to that B-longum infantis, which clustered well 
with some various HMOs: the DFLNT, 3’SL. I’m not  

713
01:04:34,920 --> 01:04:41,880
going to read them all. But…so we were seeing some 
really nice activity that they consumed those HMOs  

714
01:04:41,880 --> 01:04:48,960
quite specifically. And we saw multiple studies 
come out and talk about this B-infantis being  

715
01:04:48,960 --> 01:04:55,020
quite a protective organism. The interesting thing 
is it’s starting to become a missing microbe.  

716
01:04:55,560 --> 01:05:03,180
So, in Canada, in several of our cohort studies, 
we only see this B-infantis in 14 to 16% of the  

717
01:05:03,180 --> 01:05:10,140
population of infants. And in the U.S., it’s less 
than 10%. However, when we look at non-Western  

718
01:05:10,140 --> 01:05:16,500
infants, it’s between 60 and 80%. So we’re 
starting to see that microbe disappear in  

719
01:05:16,500 --> 01:05:22,140
certain Western cultures. And if you think about 
the experiences with Caesarian-section birth,  

720
01:05:22,140 --> 01:05:28,440
with antibiotics exposure, and the disruptions 
we’ve had over generations of breastfeeding,  

721
01:05:28,440 --> 01:05:34,560
it is possible that those influences have 
cut down on the prevalence of this microbe.  

722
01:05:36,060 --> 01:05:41,940
So, when we consider the more…main factors 
around the establishment of the gut microbiome—so  

723
01:05:41,940 --> 01:05:47,400
antibiotics, mode of delivery, gestational 
age, and infant feeding—we have pretty good  

724
01:05:47,400 --> 01:05:52,620
evidence to show that human milk and breastmilk 
feeding can actually recover the microbiome,  

725
01:05:52,620 --> 01:05:59,280
be pre…protective against those long-term health 
effects. But it’s important to consider are we  

726
01:05:59,280 --> 01:06:05,040
losing important microbes from multigenerational 
overuse of antibiotics or lack of breastfeeding.  

727
01:06:05,040 --> 01:06:11,640
Some questions to…to consider is can we replenish 
these missing microbiomes and is evolution going  

728
01:06:11,640 --> 01:06:16,680
to compensate? We don’t know. So, it…it…this is 
quite an interesting, new, and very novel finding.  

729
01:06:17,700 --> 01:06:23,340
So, I want to move on to discuss…because we 
know that not all infants can breastfeed or  

730
01:06:23,340 --> 01:06:27,840
do breastfeed, and some mothers do struggle with 
breastfeeding. So, thinking about supplementation  

731
01:06:27,840 --> 01:06:34,080
options and how those compare to kind of the gold 
standard of direct breastfeeding. So when we look  

732
01:06:34,080 --> 01:06:42,060
at direct breastfeeding, we see that there’s lots 
of probiotic bacteria, prebiotics evident in human  

733
01:06:42,060 --> 01:06:47,400
milk oligosaccharides, but the skin-to-skin 
contact and the act of the infant latching  

734
01:06:47,400 --> 01:06:53,580
on the breast actually results in something called 
retrograde flow—an exchange of the oral microbiome  

735
01:06:53,580 --> 01:06:58,920
of the infant with the mammary glands—so you get 
that direct exchange of microbiome between mom and  

736
01:06:58,920 --> 01:07:05,820
infant. So, when we think about pumping breastmilk 
and serving it raw, we still have very similar  

737
01:07:05,820 --> 01:07:12,120
probiotic, macro and micronutrients, immunological 
factors, but we don’t get that exchange of the  

738
01:07:12,120 --> 01:07:17,700
microbiome between mom and infant, but still 
quite good as far as the other components. But  

739
01:07:17,700 --> 01:07:24,240
if we start to intervene with that milk and freeze 
it, then we start to reduce on the components and  

740
01:07:24,240 --> 01:07:29,820
they start to degrade. So, our probiotics start 
to die off. The prebiotics and postbiotics remain  

741
01:07:29,820 --> 01:07:35,940
relatively stable. We start to see a reduction in 
those immunological factors. Immunoglobulins are  

742
01:07:35,940 --> 01:07:42,180
pretty temperamental, so they do degrade quite 
quickly. And then, pasteurized donor human milk  

743
01:07:42,180 --> 01:07:48,660
is becoming more common and more prevalent. And 
it’s a very good alternative to breastfeeding when  

744
01:07:48,660 --> 01:07:54,840
moms can’t breastfeed, but we do see with the 
processing of pasteurization—the freeze-thaws,  

745
01:07:54,840 --> 01:08:00,720
the tube…moving the milk through the tubes, and 
the pasteurization process—we have virtually no  

746
01:08:00,720 --> 01:08:06,240
probiotic activity, but our prebiotics and 
postbiotics remain relatively stable. Our  

747
01:08:06,240 --> 01:08:11,460
immunological factors drop considerably, and 
our macro and micronutrients do degrade a bit.  

748
01:08:12,120 --> 01:08:18,780
And then of course, formula. We have pretty good 
evidence to show that formula can be disruptive  

749
01:08:18,780 --> 01:08:24,720
to the microbiome. They’re starting to add in 
some pro- and prebiotic aspects, but again,  

750
01:08:24,720 --> 01:08:32,280
the evidence on that is pretty new and not well 
explored. And again, the immunological factors,  

751
01:08:32,280 --> 01:08:38,340
the responsiveness of human milk to the infant’s 
environment, we don’t get that with formula. And  

752
01:08:38,340 --> 01:08:42,720
the reason why I highlight those last two 
is that is my program of research—comparing  

753
01:08:42,720 --> 01:08:46,920
pasteurized donor human milk to formula 
milk when we have to supplement infants.  

754
01:08:47,580 --> 01:08:53,520
So, moving on to the two slides that everybody’s 
talked about throughout this conference, is what  

755
01:08:53,520 --> 01:08:58,020
is the biggest scientific challenge that needs 
to be addressed? And for me, it’s that quality of  

756
01:08:58,020 --> 01:09:03,720
breastfeeding evidence. We’ve historically under 
researched and under reported breastfeeding. We  

757
01:09:03,720 --> 01:09:08,760
haven’t done a good job assessing breastfeeding, 
or, when we’re doing house research, we don’t  

758
01:09:08,760 --> 01:09:13,080
account for breastfeeding. So, we don’t 
even think to ask about it. And actually,  

759
01:09:13,080 --> 01:09:18,360
this is really interesting, and it’s surprising 
to a lot of people. We don’t have a consistent,  

760
01:09:18,360 --> 01:09:23,820
well-validated infant feeding assessment tool. 
Most of us use the World Health Organization,  

761
01:09:24,900 --> 01:09:32,340
or Miriam Labbok’s work on…of assessing 
breastfeeding, but we all ask the questions  

762
01:09:32,340 --> 01:09:36,960
a little bit differently. So we really need to 
come up with a consistent and well-validated  

763
01:09:36,960 --> 01:09:43,200
infant feeding tool we can use across studies. 
And then again, a lot of studies…the majority of  

764
01:09:43,200 --> 01:09:50,400
studies really don’t look at that confounding…or 
potential confounding, such as maternal factors or  

765
01:09:50,400 --> 01:09:55,800
that…looking at the environmental aspects that can 
influence breastfeeding as well. And then this is  

766
01:09:55,800 --> 01:10:02,100
a really tough one, because human studies are hard 
to do experimentally with breastfeeding research.  

767
01:10:02,100 --> 01:10:09,120
But with the increased availability of donor milk, 
we are able to do randomized control trials. Donor  

768
01:10:09,120 --> 01:10:13,560
milk is not as good as, like, raw breastmilk, 
but we can still look at that human milk,  

769
01:10:13,560 --> 01:10:19,440
exclusive human milk diet. But because we’re 
dealing with this experimental design barrier,  

770
01:10:19,440 --> 01:10:23,880
we still deal with a lot of skepticism about 
the evidence of breastfeeding in the clinical  

771
01:10:23,880 --> 01:10:29,820
environment. So, the big piece I want to nail home 
there is that our challenge right now is still  

772
01:10:29,820 --> 01:10:36,000
that quality of evidence. So moving forward, 
what do we have to look forward to? There is  

773
01:10:36,000 --> 01:10:41,460
definitely increased momentum and a shift that 
is value…valuing the importance of human milk  

774
01:10:41,460 --> 01:10:46,860
and breastfeeding on infant and maternal health 
outcomes. We’re starting to see some prominent  

775
01:10:46,860 --> 01:10:52,080
human milk and breastfeeding scientists emerge. 
There’s the International Human Milk Institute  

776
01:10:52,080 --> 01:10:57,900
down at UC San Diego—and I saw Drew down there 
in April—so that’s a really, really exciting  

777
01:10:57,900 --> 01:11:02,580
development. And we’re also starting to see 
increasing priority around women’s health. So  

778
01:11:02,580 --> 01:11:09,120
more funding for research in this really important 
area. That being said, we really need to balance  

779
01:11:09,120 --> 01:11:17,820
our biomedical research with a…a humanistic 
lens so that we adequately incorp…adequately  

780
01:11:17,820 --> 01:11:23,880
incorporate the role of mothers and how they can 
influence lactation and breastfeeding science.  

781
01:11:24,960 --> 01:11:30,900
And the other thing is, is we tend to look 
at human milk singularly, rather than as a  

782
01:11:30,900 --> 01:11:38,100
contingent of a larger group or a network of 
components that work together. So long term,  

783
01:11:38,100 --> 01:11:45,840
we have some really amazing technology right 
now that we can get in, deeply phenotype the…the  

784
01:11:45,840 --> 01:11:51,180
different biological measures that we’re looking 
at, especially with the microbiome. And looking  

785
01:11:51,180 --> 01:11:57,660
at these longitudinal studies and getting deeper 
and deeper, as that one study of the child did, to  

786
01:11:57,660 --> 01:12:02,940
see…you know, it’s these particular bugs that are 
really important or these particular metabolites  

787
01:12:02,940 --> 01:12:07,920
that are really important over a series of 
repeated assessments. So our…really working  

788
01:12:07,920 --> 01:12:14,940
down into that deep phenotyping and then bringing 
it back to the larger, kind of, picture. And then,  

789
01:12:14,940 --> 01:12:20,940
this is one of Meghan Azad’s, kind of, soapboxes, 
but really using machine learning to develop a  

790
01:12:20,940 --> 01:12:26,340
complex, interactive system of understanding 
human milk as it works as a network, rather  

791
01:12:26,340 --> 01:12:31,320
than those individual pieces, and then how that 
interplays with breastfeeding and health outcomes.  

792
01:12:32,220 --> 01:12:36,900
So with that, I want to thank you for the 
opportunity to give you this firehose of  

793
01:12:36,900 --> 01:12:41,520
information about human milk and lactation. 
And I’ll pass it on to the next speaker.

794
01:12:41,520 --> 01:12:44,760
DR. SOMDAT MAHABIR: Thank 
you. Thank you very much.  

795
01:12:51,000 --> 01:12:56,160
In the interest of time, we’ll move right on to 
our next speaker, Dr. Stowers from the University  

796
01:12:56,160 --> 01:13:03,600
of Connecticut. As she’s going to get set up 
here, I just want to ask our speakers to please  

797
01:13:03,600 --> 01:13:08,880
keep track of time. One of the challenges, 
as you know, in moderating a session, which  

798
01:13:08,880 --> 01:13:15,480
is partially in and virtual is that we don’t have 
the opportunity to give them the clue to wrap up,  

799
01:13:15,480 --> 01:13:20,760
and they don’t really see the flashing red light 
as well. So, in some way, the speakers here are  

800
01:13:20,760 --> 01:13:27,600
kind of at disadvantage. But nevertheless, 
we look forward to hearing the next session.

801
01:13:27,600 --> 01:13:32,400
DR. KRISTEN COOKSEY STOWERS: Good morning, 
everyone. I’m Kristen Cooksey Stowers. I’m  

802
01:13:32,400 --> 01:13:37,140
an assistant professor at UConn with the Rudd 
Center for Food Policy and now Health, it used  

803
01:13:37,140 --> 01:13:43,080
to be Obesity. And I just want to start with a 
huge thanks for the Office of Nutrition Research  

804
01:13:43,080 --> 01:13:48,540
for putting this event on and for inviting me. 
Yesterday, I learned so much and have learned  

805
01:13:48,540 --> 01:13:54,240
so much from the talks already. So, it’s truly a 
pleasure. Today, I’ll be presenting on advancing  

806
01:13:54,240 --> 01:14:00,000
nutrition and health equity via CDPR research on 
neighborhood food environments. I just wanted to  

807
01:14:00,000 --> 01:14:05,100
provide a brief overview of where I’ll go today. 
I want to level set with some language on defining  

808
01:14:05,100 --> 01:14:12,000
health equity. I wanted to give a brief overview 
of some important health equity health frameworks  

809
01:14:12,000 --> 01:14:18,960
that address food and nutrition. I provide some 
very quick, short examples of my own food swamp  

810
01:14:18,960 --> 01:14:26,220
research situated in health equity frameworks. 
I wanted to share a few tools and theoretical  

811
01:14:26,220 --> 01:14:31,320
frameworks from authentic community and resident 
engagement literature that I think folks in this  

812
01:14:31,320 --> 01:14:36,060
room would find particularly helpful, just as 
sort of an FYI for later. And then, of course,  

813
01:14:36,060 --> 01:14:43,620
as requested, I’ll end with the…directions. So, 
what is health equity? It’s a principle that’s  

814
01:14:43,620 --> 01:14:48,540
underlying or commitment to reduce and ultimately 
eliminate disparities in health and its social  

815
01:14:48,540 --> 01:14:54,480
determinants. So, I think what’s interesting is 
the terms health equity and health disparities  

816
01:14:54,480 --> 01:15:00,180
are often used inter…interchangeably. But they’re 
not quite synonymous. They’re related. But health  

817
01:15:00,180 --> 01:15:05,340
inequities or health disparity is rooted in social 
disadvantage. So, to improve health inequities,  

818
01:15:05,340 --> 01:15:10,920
we have to in…address social context. And I really 
love sharing this quote, that “If an effort does  

819
01:15:10,920 --> 01:15:15,960
not address poverty, discrimination, or their 
health-damaging consequences for groups of people  

820
01:15:15,960 --> 01:15:20,520
who have…who have historically been excluded 
or marginalized, it’s probably not a health  

821
01:15:20,520 --> 01:15:24,960
equity effort.” So it’s a little gut check that I 
like to also sort of anchor myself and my lab in.  

822
01:15:24,960 --> 01:15:29,700
Folks, now, we have seen this visual many 
times, I’ll just briefly address…what  

823
01:15:29,700 --> 01:15:34,860
I wanted to highlight here is that health equity 
research is about intentionality and meeting  

824
01:15:34,860 --> 01:15:40,680
people where they are. So, there’s often a bit of 
a…a…a tension between a quality framework that are  

825
01:15:40,680 --> 01:15:46,260
concerned with getting everything…every population 
the same thing regardless of outcome. Right? So,  

826
01:15:46,260 --> 01:15:52,380
I tend to look at these boxes here as resources, 
investments, funding. All of the resources and  

827
01:15:52,380 --> 01:15:58,020
things that we…we give in our space, sometimes we 
can be more concerned with making sure everyone  

828
01:15:58,020 --> 01:16:03,300
has the same thing, even if it doesn’t get us to 
the…the optimal health outcome, nutrition equity.  

829
01:16:04,740 --> 01:16:09,540
Equity is about meeting people where they are and 
giving that concentrated time, focus, research,  

830
01:16:09,540 --> 01:16:14,460
and investment to the populations that need it. 
Liberation of…of course, getting to a point in  

831
01:16:14,460 --> 01:16:18,960
society where we have no barriers to health. I…I 
think that, like, to look at the…picture as a  

832
01:16:18,960 --> 01:16:24,960
symbol of that. But we have this call to action, 
honestly, this reality of where we are now,  

833
01:16:24,960 --> 01:16:31,080
where we…where we continuously have research 
and focus on the same populations over and over,  

834
01:16:31,080 --> 01:16:36,600
where there are some populations that remain 
understudied and undersupported. Just briefly,  

835
01:16:36,600 --> 01:16:41,340
in…in health equity spaces, we have this “first 
do no harm” principle, so this idea that without  

836
01:16:41,340 --> 01:16:47,700
careful design and implementation, PSE strategies 
may inadvertently widen health inequities. So,  

837
01:16:47,700 --> 01:16:53,460
we may not…you know, we don’t want to do that. 
But every…every action and decision is a health  

838
01:16:53,460 --> 01:16:57,300
equity–related action and decision, whether we are 
intentional and thoughtful about it or not. So,  

839
01:16:57,300 --> 01:17:01,920
it behooves us to think…to leverage some of these 
theoretical frameworks and thoughtfulness that  

840
01:17:02,880 --> 01:17:07,440
have…about issues that…around social 
determinants that we don’t make matters worse.  

841
01:17:08,760 --> 01:17:13,500
So, this brings me to my first point of the 
day, which is: Health equity researchers and  

842
01:17:13,500 --> 01:17:19,440
multigenerational nutritional researchers need 
to talk. Health equity and social determinants of  

843
01:17:19,440 --> 01:17:25,740
health frameworks have limited multigenerational 
perspectives and vice…and vice-versa. These  

844
01:17:25,740 --> 01:17:30,060
frameworks are so rich in terms of understanding 
[inaudible] and history, and organizational  

845
01:17:30,060 --> 01:17:35,460
behaviors, and policy. But they should better 
integrate it in nutritional…multigenerational  

846
01:17:35,460 --> 01:17:40,560
nutrition research moving forward, if we truly 
want to tackle social resources and the causes  

847
01:17:40,560 --> 01:17:48,180
of the issue. So, one of my favorite frameworks in 
this space is the Sonar…Solar/Irwin model from the  

848
01:17:48,180 --> 01:17:54,397
World Health Organization. And they identified the 
social determinants of health as being the social,  

849
01:17:54,397 --> 01:17:58,380
economic, and political contexts. That’s going 
to be policy, government, and I think a crucial  

850
01:17:58,380 --> 01:18:03,960
one is cultural societal value. That’s one that we 
kind of can miss from time to time. Socioeconomic  

851
01:18:03,960 --> 01:18:08,460
position is just where we think about race and 
we think about intersectionality and citizenship  

852
01:18:08,460 --> 01:18:16,560
status. All of these aspects sort of drive a 
lot of what we see at the material…circumstance  

853
01:18:16,560 --> 01:18:21,660
level and intermediary determinant of…of level 
of health and…and so, this is where we finally  

854
01:18:21,660 --> 01:18:27,900
get to food availability. And all of these factors 
then drive health equity impacts and well-being.  

855
01:18:29,040 --> 01:18:32,760
This version…I’m sorry…it’s a bit cut off 
here. This version of the social determinants  

856
01:18:32,760 --> 01:18:39,120
of health framework I…I like a lot because it 
gives a head nod to the interconnectedness of  

857
01:18:39,120 --> 01:18:43,020
them. Right? Some of the versions sort of map 
them out all separately but they don’t talk to  

858
01:18:43,020 --> 01:18:46,380
each other. They have nothing to do with each 
other. But aren’t they the same population,  

859
01:18:46,380 --> 01:18:50,520
the same households, and in a lot of cases 
the same individuals? So, I think what this  

860
01:18:50,520 --> 01:18:54,300
does nicely is it makes us think about: What is 
that intersection between neighborhoods, food,  

861
01:18:54,300 --> 01:18:59,040
and transportation; and neighborhood, food, and 
race and identity; and neighborhood, food, and  

862
01:18:59,040 --> 01:19:04,560
the health care sector? It helps us to line up how 
we might finally get out of our silo…silo. What it  

863
01:19:04,560 --> 01:19:10,200
doesn’t do as clearly is to help us to think 
about…well, the…the topic of this conference,  

864
01:19:10,200 --> 01:19:16,860
time, generations. Right? So I think it…the 
information is there. [audio interference] So,  

865
01:19:16,860 --> 01:19:21,360
I also wanted to highlight fundamental cause 
theory—another really important theory that  

866
01:19:21,360 --> 01:19:26,760
we ground our…our health equity work in. 
Fundamental cause theory is this idea that  

867
01:19:26,760 --> 01:19:32,220
flexible resources, money, power, prestige, 
neighborhood context, social connectedness,  

868
01:19:33,360 --> 01:19:38,220
create and maintain the wicked health 
inequities that all of us are trying to address.  

869
01:19:39,600 --> 01:19:45,300
Social racism has…has been identified as one 
of those key root causes and cultural resources  

870
01:19:45,300 --> 01:19:51,000
that we need to pay attention to and incorporate 
in our research. Relatedly, racial residential  

871
01:19:51,000 --> 01:19:57,000
segregation is an environmental play space 
fundamental cause that is well documented as being  

872
01:19:57,000 --> 01:20:01,440
important for the nutrition equity and health 
equity. I’ll just briefly share this quote that I  

873
01:20:01,440 --> 01:20:06,480
think is helpful: “Neighborhoods bundle together 
beneficial or less than beneficial sets of  

874
01:20:06,480 --> 01:20:11,280
circumstances, such as the availability of helpful 
foods and good medical care. The importance  

875
01:20:11,280 --> 01:20:15,780
of neighborhoods and understanding racial 
differences in health is hard to overstate.”  

876
01:20:17,880 --> 01:20:24,060
So, this brings me to the “place, not race” 
paradigm that we talk a lot about in the  

877
01:20:24,060 --> 01:20:29,640
health equity idea. And this research suggests 
that it’s more so the racial disparities in…in  

878
01:20:29,640 --> 01:20:34,560
types of environments than the individual 
racial groups themselves or [inaudible]  

879
01:20:34,560 --> 01:20:37,980
the racial groups themselves. So, this 
is a study from Southwest Baltimore,  

880
01:20:37,980 --> 01:20:41,820
where they looked at integrated neighborhoods 
and what happened to the health outcomes and  

881
01:20:41,820 --> 01:20:47,460
the racial experience when…when it’s more sort of 
a level set. In this case, the disparities between  

882
01:20:47,460 --> 01:20:53,400
White and Black Americans in terms of obesity and 
diabetes…dissipate. So, when the environment is…is  

883
01:20:53,400 --> 01:20:58,980
comparable and we have integrated neighborhoods, 
then it…it…it is an advancement to health equity.  

884
01:21:00,000 --> 01:21:05,760
Another important study is the Moving to 
Opportunity study, which is…was led by the…the…the  

885
01:21:05,760 --> 01:21:12,720
Housing…the Department of Housing and Urban 
Development. In this study, over 4,000 mothers  

886
01:21:12,720 --> 01:21:16,920
with low income had the opportunity to move from 
a neighborhood with a high level of poverty to  

887
01:21:16,920 --> 01:21:24,060
one with a lower level of poverty. This is one of 
the most notable interventions and experiments on  

888
01:21:24,060 --> 01:21:28,800
improving extreme obesity and diabetes, and it 
wasn’t an obesity intervention at all. Right?  

889
01:21:28,800 --> 01:21:33,780
So this makes us…or at least by intent, right? 
And…but the…the mechanisms are not understood. So,  

890
01:21:33,780 --> 01:21:38,040
this gets…this gets me excited because this…this 
tells us that we should be paying attention to  

891
01:21:38,040 --> 01:21:43,620
policy, neighborhood context, right? For us, 
all…all of the interventions and changes in the  

892
01:21:43,620 --> 01:21:47,784
social context, we can consider interventions 
for multigenerational…understanding wealth  

893
01:21:47,784 --> 01:21:54,480
as a generational effect. Another study that I 
think is really important to flag here is one from  

894
01:21:54,480 --> 01:22:00,240
the PHRESH Study, which…which…it included a 
supermarket in a food desert. And what’s really  

895
01:22:00,240 --> 01:22:05,040
interesting about this is that there were, 
in fact, increases in improvements to diet  

896
01:22:05,040 --> 01:22:10,440
quality in the study, but they weren’t related 
to the supermarket at all. Right? Be…and…and  

897
01:22:10,440 --> 01:22:15,360
the research…documents that because the uptake 
of the supermarket wasn’t high enough for it to  

898
01:22:15,360 --> 01:22:20,940
really have translated to effect. What…what drove 
the improvements in diet quality were seeing the  

899
01:22:20,940 --> 01:22:25,380
neighborhood being revitalized…that…and that 
lowered stress and that improved neighborhood  

900
01:22:25,380 --> 01:22:30,600
satisfaction and then people felt better and they 
ate better. So, again, continuing this theme of we  

901
01:22:30,600 --> 01:22:36,720
need to keep our eyes on what may not commonly be 
perceived as nutrition interventions as absolutely  

902
01:22:37,800 --> 01:22:41,160
being related to what we do. So, 
this brings me to my second point:  

903
01:22:41,160 --> 01:22:46,800
More research on the multigenerational effects and 
drivers of food swamps is needed. So, these are  

904
01:22:46,800 --> 01:22:53,160
just some…some…some pictures from some newspaper 
articles that I’ve covered my work on food swamps.  

905
01:22:53,160 --> 01:22:57,120
And as you can see from the headlines, they’re 
really leaning to the equity-oriented aspects  

906
01:22:57,120 --> 01:23:03,300
of food environments, as well as their impacts 
on Black populations and Hispanic populations.  

907
01:23:04,920 --> 01:23:09,660
So, just to step…back a moment and define food 
swamps, a lot of folks are more familiar with  

908
01:23:09,660 --> 01:23:14,340
the term “food desert,” which are defined 
as areas that lack access to a supermarket.  

909
01:23:15,120 --> 01:23:21,000
I was at the USDA as an econ intern when the Food 
Desert Locator Map dropped, and I was like, wow!  

910
01:23:21,000 --> 01:23:23,640
This is amazing, these new terms. So, 
that’s what my lived experience was.  

911
01:23:24,600 --> 01:23:30,600
However, what the food desert measure and 
metaphor does not capture is everything else  

912
01:23:30,600 --> 01:23:36,480
in the built food environment. The intent is to 
map spatially access to supermarkets. It’s not  

913
01:23:36,480 --> 01:23:43,740
meant to demonstrate relative balance or sort of 
a more comprehensive assessment of equity between  

914
01:23:43,740 --> 01:23:48,720
food store types, like food swamp measures. 
So, a big…so one of the key things that I’ve  

915
01:23:49,380 --> 01:23:53,280
aimed to do in my work is to contribute to 
the measurement and identification of food  

916
01:23:53,280 --> 01:23:57,600
swamps to build upon food desert research…food 
desert research. These are both important.  

917
01:23:59,100 --> 01:24:03,420
Never have food swamps have been associated 
with obesity-related disparities among adults,  

918
01:24:03,420 --> 01:24:08,460
and I’m including some of my work. I published 
another paper in 2020 that shows that…that  

919
01:24:09,720 --> 01:24:16,800
food swamp exposure nationally was linked 
to…increased adverse diet outcomes—or habits,  

920
01:24:16,800 --> 01:24:22,740
rather—and that Black Americans were particularly 
at risk for this. Food swamps have been linked  

921
01:24:22,740 --> 01:24:27,300
to dietary habits among Black adults and 
teenage girls in Baltimore. Diabetes-related  

922
01:24:27,300 --> 01:24:31,560
hospitalization—so, not just diagnoses of…of 
prevalence, but being hospitalized for diabetes.  

923
01:24:32,940 --> 01:24:36,840
And then also they’ve been linked 
to differences in exterior…unhealthy  

924
01:24:38,160 --> 01:24:44,460
marketing at the restaurant level. And…and lastly, 
diet quality among preschoolers and foods served  

925
01:24:44,460 --> 01:24:48,060
within family childcare homes. So, that’s one of 
the studies that I’ll briefly share some details  

926
01:24:48,060 --> 01:24:53,640
about in a moment. Food swamps have also been 
linked to other neighborhood level disparities.  

927
01:24:54,540 --> 01:25:00,960
A little bit of…for example, residential 
segregation, and neighborhood blight and  

928
01:25:00,960 --> 01:25:04,620
housing vacancy. So, again, going back to 
that framework where we need to start to  

929
01:25:04,620 --> 01:25:08,880
think about the inter…interconnectedness 
of…of the social determinants of health.  

930
01:25:09,960 --> 01:25:13,440
Also, food swamps have been linked to 
neighborhood crime and social disorder.  

931
01:25:14,520 --> 01:25:18,660
So, one of the studies that I…that I 
published, and mentioned just…just now,  

932
01:25:19,500 --> 01:25:23,100
demonstrated that food swamps were a 
stronger predictor of obesity prevalence  

933
01:25:23,760 --> 01:25:29,400
and geographic disparity in obesity…obesity 
prevalence compared to food deserts. This is  

934
01:25:29,400 --> 01:25:36,120
a national sample of all counties in the U.S., and 
what we see is when we think about transportation  

935
01:25:36,120 --> 01:25:41,400
systems, where again, that interconnectedness, 
the food swamp effects was higher in areas  

936
01:25:41,400 --> 01:25:45,900
where the community was less mobile. So, where 
there was lower car…vehicle ownership or there  

937
01:25:45,900 --> 01:25:51,240
was less reliable public transport, the food 
swamp effects and obesity was much higher. So,  

938
01:25:51,240 --> 01:25:56,040
we can imagine…so, that tells us that the local 
environment, the walkable environment, is…in…that  

939
01:25:56,040 --> 01:26:00,660
surround folks’ home where they live, workplace, 
worship is really important to think about.  

940
01:26:03,240 --> 01:26:08,940
Having formatting issues here. A…a common 
argument or common concern in health equity  

941
01:26:08,940 --> 01:26:13,440
work is economic status and wealth inequality. 
These are common things we talk about. So,  

942
01:26:13,440 --> 01:26:19,680
I wanted to test how that played into these built 
environment disparities. And the results show that  

943
01:26:20,580 --> 01:26:25,620
regardless of wealth inequality measured by 
the Gini coefficient, the food…the food swamp  

944
01:26:25,620 --> 01:26:30,660
effect in obesity persists. So, that means 
that they’re both important. That means even  

945
01:26:30,660 --> 01:26:36,300
if we improve income and wealth inequality, 
that will not get us away from addressing the  

946
01:26:36,300 --> 01:26:45,540
built environment issues that we see. Here’s 
a study that was funded by NHLBI…excuse me.  

947
01:26:47,100 --> 01:26:55,020
The R01 parent grant for this study is…the PIs are 
Dr. Jiang and Patty Risica…my collaborators and  

948
01:26:55,020 --> 01:27:01,740
mentors on the grant, and they did a randomized 
control trial of family childcare homes,  

949
01:27:01,740 --> 01:27:05,460
and an improvement environment, the physical 
activity and food environments within those homes.  

950
01:27:06,540 --> 01:27:12,060
So, I added a secondary analysis to look at 
the built food environment surrounding those  

951
01:27:12,060 --> 01:27:16,560
homes to better understand what we saw 
them in…in, within the food…the family,  

952
01:27:16,560 --> 01:27:20,640
childcare homes, and ultimately what 
these young…the young kids consumed.  

953
01:27:22,980 --> 01:27:28,080
Just briefly about…in terms of the demographics, 
there were over 300 children enrolled or assessed  

954
01:27:28,080 --> 01:27:34,080
in this study. A very ethnically diverse 
sample of over 58% Hispanic. We think about  

955
01:27:34,080 --> 01:27:38,100
a lot about that…that…that combination 
or intersectionality of culture and race.  

956
01:27:38,640 --> 01:27:42,900
So, there was 16% Black in the…in 
the sample. But as you can see,  

957
01:27:43,680 --> 01:27:48,900
toddlers are spending a lot of time in family 
childcare homes, childcare centers in general.  

958
01:27:49,620 --> 01:27:55,260
But this warrants…this warrants additional 
attention, right? Because 73% of the children,  

959
01:27:55,260 --> 01:27:59,100
their parents reported that they 
are there 8 hours a day or more,  

960
01:27:59,880 --> 01:28:08,160
right? And 84% eat breakfast there, 97% eat 
lunch there, and 8% actually stay for dinner.  

961
01:28:10,740 --> 01:28:14,940
So, just briefly, a little bit more about 
the…the data set. The research team went in,  

962
01:28:14,940 --> 01:28:19,020
they observed the food environment within 
the family childcare home. They did place  

963
01:28:19,020 --> 01:28:24,360
weights. They watched what the kids ate, 
consumed, and then ATI scores were computed.  

964
01:28:25,620 --> 01:28:30,480
ATI 2015 scores were computed. The provider 
demographics come from the provider survey,  

965
01:28:30,480 --> 01:28:36,120
and the child demographics come from the parent 
survey. So, in terms of key findings, about 12% of  

966
01:28:36,120 --> 01:28:41,580
the family childcare homes were located in food 
deserts; 58% were located in food swamps. So,  

967
01:28:41,580 --> 01:28:45,480
again, it’s both/and, right? We have areas 
that are one or the other. They’re both.  

968
01:28:45,480 --> 01:28:50,760
They’re neither. There’s a term “food oasis” where 
they’re neither; 26% of the family childcare homes  

969
01:28:50,760 --> 01:28:57,780
were in high food crop–exposure areas. Meaning 
67% to 88% of all food retail surrounding the  

970
01:28:57,780 --> 01:29:03,240
family childcare home were considered unhealthy. 
Fast food restaurant, the Brown Bag restaurant,  

971
01:29:04,380 --> 01:29:10,380
just outlets not serving majority healthy 
options. Higher neighborhood food swamp exposure  

972
01:29:10,380 --> 01:29:14,820
surrounding the family childcare home was related 
to the family childcare providers serving more  

973
01:29:14,820 --> 01:29:21,000
fried foods, including potatoes, higher-sugar, 
and high-fat foods, as well as low-fat…fat meat.  

974
01:29:22,200 --> 01:29:27,660
The lower diet…the child diet quality scores 
were also lower, and we looked at the…the  

975
01:29:27,660 --> 01:29:32,940
specific categories within the scores and saw 
there was more vegetable consumption for kids  

976
01:29:32,940 --> 01:29:39,120
that are in family childcare homes in food 
swamps and higher intake of saturated fats.  

977
01:29:41,400 --> 01:29:46,620
Another study that I wanted to briefly 
mention is one that my colleague at Harvard,  

978
01:29:46,620 --> 01:29:51,540
Dr. Juliana Cohen, graciously added me 
to…allowed me to add a follow-up study  

979
01:29:51,540 --> 01:29:56,340
to her K that was funded by NIDDK, where she was 
looking at quick-service restaurant environments  

980
01:29:56,340 --> 01:30:00,600
and then parent–child diet to see what they chose 
and consume within the quick-service restaurant.  

981
01:30:00,600 --> 01:30:05,940
By the neighborhood research, I say, “Oh, you 
know, I wonder, are there spatial differences  

982
01:30:05,940 --> 01:30:09,600
if your neighborhood environment primes you 
up for a certain level of behavior?” So,  

983
01:30:09,600 --> 01:30:15,300
we were able to collaborate and…and explore 
this a bit together. In terms of key methods  

984
01:30:15,300 --> 01:30:19,920
to keep in mind, just briefly, the…these are four 
quick-service restaurants in the New England area.  

985
01:30:21,240 --> 01:30:26,640
After sort of all…of the different caveats, 
the…the…the analytics sample of children was 149,  

986
01:30:27,780 --> 01:30:31,200
and as I said, these are…this is observational 
data, so the research team going into the  

987
01:30:31,200 --> 01:30:36,900
quick-service restaurant and watching what the 
parent–child diets do. In terms of key findings,  

988
01:30:36,900 --> 01:30:42,360
sugary drink consumption among children in QSR 
was just much higher than we expected, just  

989
01:30:42,360 --> 01:30:47,280
descriptively, right? So the line the…the line 
here of 25 is what the American Heart Association  

990
01:30:47,280 --> 01:30:53,520
recommends of 25 grams of sugar a day for a kid, 
and the blue dots are where the kids were in terms  

991
01:30:53,520 --> 01:30:58,320
of their…the sugar in their drinks, right? 
So, that’s a red flag for us to keep in mind.  

992
01:30:59,340 --> 01:31:04,380
The regression results interestingly found no 
difference though in neighborhood status. So,  

993
01:31:04,380 --> 01:31:10,020
they just were high in…in food service 
restaurants. It didn’t change by neighborhood  

994
01:31:10,020 --> 01:31:16,440
status. But importantly, Latinx children were more 
likely than non-Latinx children to consume sugary  

995
01:31:16,440 --> 01:31:24,360
drinks in a quick-service restaurant. Just to flag 
a cue…to…to flag a…a few key takeaways from this  

996
01:31:24,360 --> 01:31:29,100
study, is the children are more likely to acquire 
and consume sugary drinks and QSRs relative to  

997
01:31:29,100 --> 01:31:33,540
healthy alternatives. I think this work elevates 
some of the policy efforts that are around, like  

998
01:31:33,540 --> 01:31:39,180
healthier default for food service restaurants. 
And…but further investigation is needed when you  

999
01:31:39,180 --> 01:31:44,520
think about ethnic disparities in sugary drink 
consumption among young kids. So, briefly,  

1000
01:31:44,520 --> 01:31:49,920
food for thought, how much should researchers 
rely on communities and residents to design  

1001
01:31:49,920 --> 01:31:55,140
and implement studies examining multigenerational 
influences on nutrition-related health inequities?  

1002
01:31:56,340 --> 01:32:02,340
Full alert, I’ll share what I think about 
this. We can absolutely better leverage CBPR  

1003
01:32:02,340 --> 01:32:06,840
methods and authentic resident engagement tools 
to…I just spoke to it, right, yesterday. I’m  

1004
01:32:06,840 --> 01:32:12,420
looking at Sonia, who looks at the stage grade 
from…yesterday, improving the recruitment and  

1005
01:32:12,420 --> 01:32:16,620
retention of communities of color and other 
historically marginalized populations. So,  

1006
01:32:16,620 --> 01:32:22,080
the methods can help us do that. And importantly, 
advance health equity in a sustainable, authentic  

1007
01:32:22,080 --> 01:32:27,900
root cause–oriented way. This is just a website 
that I think for later…FYI, screenshot it please,  

1008
01:32:27,900 --> 01:32:32,700
or…or whatever you do to keep notes. I’ve been 
working with Healthy Food Policy Project for 7  

1009
01:32:32,700 --> 01:32:38,640
years now, and this is a tool that…that focuses 
on food access and policy change through authentic  

1010
01:32:38,640 --> 01:32:43,320
resident engagement. You can take some of these 
tools and do an assessment with yourself and your  

1011
01:32:43,320 --> 01:32:47,760
lab to assess: Where are we on the spectrum? How 
ready are we to engage with the community? So,  

1012
01:32:47,760 --> 01:32:52,980
I think it’s just a very helpful tool. Here’s a 
brief definition of authentic resident engagement.  

1013
01:32:52,980 --> 01:32:58,500
Ultimately, it’s about inclusivity at all 
stages of the research and policy change.  

1014
01:32:59,760 --> 01:33:04,260
The working principles I want to flag is that in 
our work, we need to consider addressing power  

1015
01:33:04,260 --> 01:33:10,980
imbalance, building trust, using an asset-based 
approach, right? To acknowledge the resilience  

1016
01:33:10,980 --> 01:33:17,040
that the communities and residents and patients 
have had before we even showed up. And to take an  

1017
01:33:17,040 --> 01:33:25,740
anti-racism stance. This tool demonstrates that 
community engagement is a spectrum. It’s not  

1018
01:33:25,740 --> 01:33:30,420
that…you know, you’re all the way there or you’re 
not. It’s…you can…you can jump in at any point.  

1019
01:33:30,420 --> 01:33:35,700
You can absolutely grow. It’s a dynamic, iterative 
process of looking to see: Are we ignoring in the  

1020
01:33:35,700 --> 01:33:41,100
community? Are we informing the community? Are we 
consulting, involving, collaborating, all the way  

1021
01:33:41,100 --> 01:33:45,240
to deferring to the community, where the community 
and the residents are really driving the questions  

1022
01:33:45,240 --> 01:33:50,580
and even the interpretation and dissemination of 
the data? And this one gets a little tricky. This  

1023
01:33:50,580 --> 01:33:56,460
is what is causing us to even be participatory 
in how we budget with our grants. Briefly, this  

1024
01:33:56,460 --> 01:34:03,300
is a CBPR, an example of some of my CBPR work in 
Hartford. I won’t go into the weeds too much, but  

1025
01:34:03,300 --> 01:34:07,740
I wanted to share, you know, just some highlights 
of what dissemination and co-development with…with  

1026
01:34:07,740 --> 01:34:13,020
residents look like. These are the communities 
I work with. It is a federally designation of  

1027
01:34:13,020 --> 01:34:16,560
Hartford…Promise Zones. So, I wanted to flag 
that. North Hartford was designated a Promise  

1028
01:34:16,560 --> 01:34:21,000
Zone under the Obama administration, so that 
really just sort of should, you know, give you a  

1029
01:34:21,000 --> 01:34:27,480
visual in mind of the level of this investment and 
level of poverty in the community that I’m working  

1030
01:34:27,480 --> 01:34:32,640
with on a day-to-day basis. A lot is going on in 
Hartford in terms of, they want the supermarket.  

1031
01:34:33,180 --> 01:34:37,620
There are…there’s revitalization efforts. There’s 
policy change happening with the city council.  

1032
01:34:37,620 --> 01:34:42,240
They just put out a resolution to sort of in food 
deserts and address food swamps in the north end.  

1033
01:34:43,260 --> 01:34:47,700
But for this audience, I wanted to flag my 
relationship with this work. This is not…my work  

1034
01:34:47,700 --> 01:34:55,020
is not post-intervention at this time. I am at the 
table sometimes at 10:00, 11:00 at night at the Y  

1035
01:34:55,020 --> 01:35:00,600
with the community, trying to help infuse evidence 
and research into the decisions to begin with,  

1036
01:35:00,600 --> 01:35:04,680
right? Because sometimes by the time we show up, 
so much has been determined that we’re…right,  

1037
01:35:04,680 --> 01:35:08,040
as researchers, we’re just trying to catch up. 
So, I’m bringing all this evidence to bear and  

1038
01:35:08,040 --> 01:35:12,060
inform this work to help steer and support the 
community in figuring out what they want done.  

1039
01:35:12,840 --> 01:35:16,620
These are the aspects of the [inaudible] 
work…we’ve done audits, we’ve done resident  

1040
01:35:16,620 --> 01:35:22,440
surveys. I conduct photo voice research, which is 
a qualitative study, but photos are the data and  

1041
01:35:22,440 --> 01:35:28,560
the community tells their story. And I also did a 
policy audit. These are pictures from the audit.  

1042
01:35:29,220 --> 01:35:34,140
And ultimately, I co-developed these community 
resources. So, of course, the manuscript,  

1043
01:35:34,140 --> 01:35:41,400
the…the professional conferences. We did all that. 
But we also co-developed these translation of  

1044
01:35:41,400 --> 01:35:46,620
these materials with residents in the community. 
We have a social media campaign based on some of  

1045
01:35:46,620 --> 01:35:52,620
this work. And in this…this side of the slide, you 
might be able to see the neighborhood profiles,  

1046
01:35:52,620 --> 01:35:58,140
who took the data from the Food Swamp Audit, 
created maps, and worked with the community to  

1047
01:35:58,140 --> 01:36:02,640
help tell the story that they wanted told about 
their own community. How do you want this shared?  

1048
01:36:02,640 --> 01:36:06,840
And they said, “We want you to lead with our 
resilience and our assets. Before you get to  

1049
01:36:06,840 --> 01:36:11,400
the problem, or the calls to action, please tell 
about the rich history of North Hartford.” These  

1050
01:36:11,400 --> 01:36:16,260
are pictures from the photo voice…just in terms of 
community assets and talking about transportation,  

1051
01:36:16,260 --> 01:36:22,800
but talking about the emotional and mental health 
impacts of hearing that a supermarket or a healthy  

1052
01:36:22,800 --> 01:36:26,940
outlet was going to open and just seeing it 
lay barren for years and years and years.  

1053
01:36:28,740 --> 01:36:32,280
We ran the resident survey and found the 
residents of food swamps are less likely  

1054
01:36:32,280 --> 01:36:37,800
to experience both types of food insecurity. 
We looked at COVID-related food insecurity,  

1055
01:36:37,800 --> 01:36:42,660
which is an interesting one, and we…we’ll do 
follow-up research to explore this because  

1056
01:36:42,660 --> 01:36:49,080
what we suspect is that residents of food 
swamps are just perceiving a variety of food,  

1057
01:36:49,080 --> 01:36:52,680
but not necessarily getting that type of 
food. Right…that’s where the, sort of,  

1058
01:36:52,680 --> 01:36:58,980
the…the nutrition and…and food insecurity, hunger 
paradigm come together. Hispanics were more likely  

1059
01:36:58,980 --> 01:37:04,440
to experience COVID-related food insecurity, 
and non-Hispanics were more likely to go to a  

1060
01:37:04,440 --> 01:37:10,080
food pantry more frequently. We think this has to 
do with perceived safety…is there a safe place?  

1061
01:37:10,860 --> 01:37:16,380
Post the former administration, there’s certain 
populations that…that they’re reporting fearful  

1062
01:37:16,380 --> 01:37:21,420
to show back up in food…food pantry, and we have 
no reason to believe that they don’t need it. But  

1063
01:37:21,420 --> 01:37:25,740
there’s just a perceived safety issue that is 
something keep in mind. These are pictures from  

1064
01:37:25,740 --> 01:37:31,080
the photo voice…gallery walk that I co-developed 
with the community at the city hall. The mayor  

1065
01:37:31,080 --> 01:37:37,920
showed up, the city hall…city council folks 
showed up to…to…to discuss important research  

1066
01:37:37,920 --> 01:37:43,620
and important to discuss the change that should 
follow it. And this brings me to my conclusion.  

1067
01:37:43,620 --> 01:37:51,120
In terms of the number one challenge that I see in 
this area at the moment, is our relationship with  

1068
01:37:51,120 --> 01:37:55,740
our…as researchers with historically oppressed, 
marginalized communities that are underrepresented  

1069
01:37:55,740 --> 01:38:00,540
in nutrition work due to recruitment and 
retention issues. As researchers, when we  

1070
01:38:00,540 --> 01:38:05,220
take the time to build and maintain trust, given 
our competing deadlines for promotion, and tenure,  

1071
01:38:05,220 --> 01:38:10,380
and our grant deadlines, we’ll take the time to 
build diverse research teams with representation  

1072
01:38:10,380 --> 01:38:14,340
from the community. Sometimes recruiting and 
hiring directly from the community will absolutely  

1073
01:38:14,340 --> 01:38:20,580
help folks answer your call, open their door for 
you, and you’re elevating training and resources  

1074
01:38:20,580 --> 01:38:25,920
in that same community. When we take the time to 
share resources and…and power with the community,  

1075
01:38:25,920 --> 01:38:29,760
with residents and patients…this is a tricky 
one because then we’re sharing budget…budget  

1076
01:38:29,760 --> 01:38:36,900
information and being transparent, those things. 
In terms of opportunities, multigenerational  

1077
01:38:36,900 --> 01:38:41,700
nutritional researchers should leverage CBPR 
methods and principles. It helps to maximize  

1078
01:38:41,700 --> 01:38:45,960
impact in a sustainable way and elevate voices. 
We can think of ourselves as playing a support  

1079
01:38:45,960 --> 01:38:52,140
role to policy makers and decision makers that, 
as I said before, in the…personal harm slide.  

1080
01:38:52,860 --> 01:38:57,660
We are making decisions that impact health equity, 
whether we are being cognizant and calling it that  

1081
01:38:57,660 --> 01:39:01,620
or not. So, we should work with them. We should 
say, “Hey, we’re here with our skills and training  

1082
01:39:01,620 --> 01:39:06,060
and resources. Let us help make this decision.” 
And another opportunity that I think is exciting  

1083
01:39:06,060 --> 01:39:09,180
is that we can expand the comprehensive 
measures of neighborhood food environments,  

1084
01:39:09,180 --> 01:39:14,220
including but not limited to food…to food swamps, 
but also validated measures on consumer-level food  

1085
01:39:14,220 --> 01:39:17,460
environments like the one that discussed today, 
childcare setting, the quick-service restaurant.  

1086
01:39:17,460 --> 01:39:22,620
And we should absolutely…because we’re…we’re 
not out of the woods completely. But we should  

1087
01:39:22,620 --> 01:39:28,140
leverage what…what we’ve just been through 
with COVID, and the…revitalization efforts,  

1088
01:39:28,140 --> 01:39:32,940
like the Biden American Rescue Plan, to think of 
natural experiments that can help us understand  

1089
01:39:32,940 --> 01:39:41,820
these societal policy neighborhoods and social 
changes over time, but also across generations.  

1090
01:39:42,780 --> 01:39:47,640
With that, I’d like to thank, again, the office 
of Nutrition Research for inviting me here,  

1091
01:39:47,640 --> 01:39:51,780
the funders, my academic collaborators, community 
partners, including my resident advisors,  

1092
01:39:52,620 --> 01:39:56,640
and my training from the…from my Health 
Equity for the People Lab. Thank you.

1093
01:39:56,640 --> 01:40:03,480
DR. SOMDAT MAHABIR:  

1094
01:40:03,480 --> 01:40:08,700
Thank you very much. We are now running 
way short of time, so I don’t want to put  

1095
01:40:08,700 --> 01:40:13,500
too much pressure on the other speakers. Maybe 
we’ll have to chew into some of our lunchtime  

1096
01:40:13,500 --> 01:40:19,920
so that we can get some good questions and so 
forth. So, next speaker is Dr. Joseph Braun.

1097
01:40:19,920 --> 01:40:24,840
DR. JOSEPH BRAUN: All right, 
well thank you to the organizers,  

1098
01:40:24,840 --> 01:40:26,580
to Kristen and Ashley for inviting me here today.  

1099
01:40:27,180 --> 01:40:31,140
It’s…it’s my pleasure to be here, and it’s been a 
really interesting series of talks to hear so far.  

1100
01:40:32,220 --> 01:40:35,640
I just want to start out by disclaiming that 
I have been financially compensated as an  

1101
01:40:35,640 --> 01:40:40,080
expert witness for plaintiffs and litigation 
related to PFAS-contaminated drinking water  

1102
01:40:40,080 --> 01:40:43,500
in New Hampshire. And PFAS is the chemical 
we’re going to be talking about most today.  

1103
01:40:44,940 --> 01:40:50,760
So, I want to start out by bringing this idea 
forward that chemical exposures can make us obese,  

1104
01:40:50,760 --> 01:40:56,400
and this idea isn’t new. Nicholas Kristof from 
the New York Times wrote about this over 10  

1105
01:40:56,400 --> 01:41:01,320
years ago—“Warnings From a Flabby Mouse”—where he 
highlighted a study from Retha Newbold, who was at  

1106
01:41:01,320 --> 01:41:08,580
the National Toxicology Program, where these two 
mice were exposed in utero to either nothing or  

1107
01:41:08,580 --> 01:41:13,500
diethylstilbestrol, which is a synthetic estrogen. 
And you can guess which…which mouse is exposed  

1108
01:41:13,500 --> 01:41:19,920
to the…to the DES. It was the fatter, larger 
mouse there. Bruce Blumberg and Leo Trasande,  

1109
01:41:20,460 --> 01:41:26,280
both researchers have written books about the 
obesogen effect or other endocrine-disrupting  

1110
01:41:26,280 --> 01:41:33,000
chemicals and how they can impact the risk 
of obesity and related diseases. And this  

1111
01:41:33,000 --> 01:41:36,420
really shouldn’t be—I…I think biologically 
there’s…there’s good reason to suspect that  

1112
01:41:36,420 --> 01:41:41,640
this is happening. We know from pharmaceuticals 
that there is actually pharmaceutical obesogens  

1113
01:41:41,640 --> 01:41:45,900
and thiazolidinediones are an example of this. 
These are a class of drugs that are used to treat  

1114
01:41:45,900 --> 01:41:51,300
type 2 diabetes, Rosiglitazone and pioglitazone 
being two of them used here in the United States.  

1115
01:41:52,260 --> 01:41:56,880
And these are PPAR-gamma agonists, so they 
actually bind to the PPAR receptor inside our body  

1116
01:41:56,880 --> 01:42:02,880
and impact metabolism. And they can actually cause 
an on average 11-pound weight gain among diabetics  

1117
01:42:02,880 --> 01:42:07,500
who take this, which is a paradoxical effect if 
you have diabetes, you’d think. But what’s really  

1118
01:42:07,500 --> 01:42:12,420
interesting is actually weight gain in these 
persons is…is correlating with better metabolic  

1119
01:42:12,420 --> 01:42:17,040
control. And it’s thought that largely this is 
due to the fact that these drugs help take fat  

1120
01:42:17,040 --> 01:42:22,440
away from the inside around the organs and move 
it to the periphery of the body, which is where  

1121
01:42:22,440 --> 01:42:29,280
it could be “healthier fat.” So, there’s this 
redistribution phenomenon. So, what about chemical  

1122
01:42:29,280 --> 01:42:34,200
exposures? Well, we’re exposed to a…a…a…a large 
number of endocrine-disrupting chemicals, and I’ll  

1123
01:42:34,200 --> 01:42:39,540
talk about PFAS today, as well as some others, and 
we think that many of the mechanisms that they can  

1124
01:42:39,540 --> 01:42:44,880
impact obesity are similar to what might be going 
on with thiazolidinediones, like PPAR agonism,  

1125
01:42:44,880 --> 01:42:50,040
but also general endocrine disruption that can 
impact metabolism and energy homeostasis, as  

1126
01:42:50,040 --> 01:42:55,200
well as appetite and satiety. We also think that 
there may be…some of these chemicals can inhibit  

1127
01:42:55,200 --> 01:43:01,800
11-β-hydroxysteroid dehydrogenase 2, and thus 
increase cortisol levels and possibly also impact  

1128
01:43:01,800 --> 01:43:08,160
DNA methylation and other epigenetic mechanisms to 
affect gene expression. And the net result of this  

1129
01:43:08,160 --> 01:43:15,360
is that we end up with adipose tissue accrual and 
alterations in metabolic function. The class of  

1130
01:43:15,360 --> 01:43:19,740
chemicals that I’ve been studying with…with regard 
to this are PFAS or polyfluoroalkyl substances.  

1131
01:43:21,240 --> 01:43:26,100
And PFAS are a…also known as the “Forever 
Chemicals.” This is a diverse class of…of …of  

1132
01:43:26,700 --> 01:43:31,620
thousands of chemicals that are characterized by 
having these—this long carbon chain that’s only  

1133
01:43:31,620 --> 01:43:36,540
fully or partially fluorinated. And these 
chemicals have very high environmental persistence  

1134
01:43:36,540 --> 01:43:40,320
and in some cases may stay in the environment 
for the…the rest of the planet’s history.  

1135
01:43:41,400 --> 01:43:46,620
They’re designed to be persistent. And they have 
these desirable chemical and physical properties  

1136
01:43:46,620 --> 01:43:51,060
that make them useful for a lot of products that 
we use in our everyday lives. They’re used in  

1137
01:43:51,060 --> 01:43:56,640
stain and water-repellent textiles, like vortex. 
They’re used in food packaging, like popcorn  

1138
01:43:56,640 --> 01:44:02,280
bags and grease-proof wrappers. They’re used to 
manufacture non-stick cookware, as well as stain  

1139
01:44:02,280 --> 01:44:08,220
resistant—other textiles, rugs, and furniture. 
They’re used in cosmetic products and in aqueous  

1140
01:44:08,220 --> 01:44:12,660
film forming foams or firefighting foams that are 
used on a military bases or civilian airfields.  

1141
01:44:14,400 --> 01:44:19,440
These chemicals have long biologic half-lives in 
our bodies, ranging from 3 to 7 years for some  

1142
01:44:19,440 --> 01:44:23,700
of them. So, they stick around in us for…for a 
long time. Thus, the name the Forever Chemicals.  

1143
01:44:25,800 --> 01:44:30,360
They’re extensively used. It’s estimated that 
they’re used in thousands of products. I just  

1144
01:44:30,360 --> 01:44:34,380
gave you a few highlights there, but they’re used 
in these obscure things too, like guitar strings.  

1145
01:44:34,380 --> 01:44:41,700
You know, they coat guitar strings with PFAS. 
They get…they’re used in…in anti-fog coatings  

1146
01:44:41,700 --> 01:44:48,120
on goggles and glasses. And they’ve also been 
widely distributed in our environment. Here in the  

1147
01:44:48,120 --> 01:44:53,040
United States, it’s estimated that they’re used at 
over 57,000 sites—industrial or commercial sites.  

1148
01:44:53,940 --> 01:44:58,140
And hundreds of millions of people are in this 
country are exposed to two of these compounds,  

1149
01:44:58,140 --> 01:45:03,300
PFOA and PFOS, at levels above a provisional 
guideline being set by the EPA for drinking  

1150
01:45:03,300 --> 01:45:09,540
water limits. And they’re detected in the blood 
of everyone here in the United States and largely  

1151
01:45:09,540 --> 01:45:14,460
in other industrial countries, as well. As I 
mentioned, they persist in our body for years.  

1152
01:45:16,800 --> 01:45:22,560
Now, the tie to diet is that, there’s…it’s…at 
least half of our exposure to some of these PFAS  

1153
01:45:22,560 --> 01:45:28,440
comes from diet, and in some cases, it’s close 
to 95%. This can be from contaminated fish, eggs,  

1154
01:45:28,440 --> 01:45:32,160
and meat, but also from food contact 
materials. So, things like grease,  

1155
01:45:32,160 --> 01:45:36,720
food wrappers that I mentioned, or popcorn 
bags or other plastic bottles that are  

1156
01:45:36,720 --> 01:45:43,140
fluorinated and coated in order to impart 
better…decrease their permeability. So,  

1157
01:45:43,140 --> 01:45:48,960
we can be exposed to these chemicals not only from 
our food but our food containers. Drinking water  

1158
01:45:48,960 --> 01:45:53,760
is also a major source of exposure, particularly 
for infants. This includes from trans-lactational  

1159
01:45:53,760 --> 01:45:58,800
transfer for…for breastfed infants, as well 
as formula made with contaminated water.  

1160
01:46:01,680 --> 01:46:06,960
Now, in terms of obesity related diseases, 
there’s been a…a number of studies examining  

1161
01:46:06,960 --> 01:46:12,480
PFAS in relationship to cardiometabolic disease 
in adults. The last time we did a review of this,  

1162
01:46:12,480 --> 01:46:16,200
in the last year, we found that there’s at 
least four studies and…and the majority of  

1163
01:46:16,200 --> 01:46:21,840
these suggesting that mid-adulthood exposure 
to PFAS or mixtures of PFAS—because there’s not  

1164
01:46:21,840 --> 01:46:25,320
just one of them—is associated with 
increased risk of type 2 diabetes.  

1165
01:46:25,860 --> 01:46:31,260
They’ve also been consistently associated with 
dyslipidemia, and there’s some evidence that  

1166
01:46:31,260 --> 01:46:37,260
lifestyle interventions may ameliorate their 
effects, such that having better diet and more  

1167
01:46:37,260 --> 01:46:42,120
physical activity may decrease the…the effects 
of PFAS on the risk of type 2 diabetes, which  

1168
01:46:42,120 --> 01:46:45,660
is some work that was done by Andreas Cardenas 
and highlighted in the lower right panel here.  

1169
01:46:48,060 --> 01:46:51,960
More recently, there was a paper by Wen and 
colleagues that published in EHP showing that  

1170
01:46:51,960 --> 01:46:57,540
PFAS may be associated with premature mortality. 
This is data linking NHANES data to the National  

1171
01:46:57,540 --> 01:47:04,920
Death Index and showing that increasing levels of 
PFAS in people’s…in people’s PFOS, which is one of  

1172
01:47:04,920 --> 01:47:09,780
these PFAS, was associated with increased hazard 
of mortality from either heart disease or cancer.  

1173
01:47:10,320 --> 01:47:15,900
And they did some counterfactual calculations 
to estimate the attributable number of deaths  

1174
01:47:15,900 --> 01:47:20,280
that we could avoid if we move the top 
third of people in the PFOS distribution  

1175
01:47:20,280 --> 01:47:23,820
to the bottom third, and estimated 
that there’s somewhere over 200,000  

1176
01:47:23,820 --> 01:47:27,780
deaths that could have been prevented. Now 
there’s lots of assumptions baked into that,  

1177
01:47:27,780 --> 01:47:30,720
I know, but this is…this is a highlight 
that there could be a really large  

1178
01:47:31,500 --> 01:47:36,420
attributable fraction here that has a…a pretty 
profound absolute effect on…on mortality.  

1179
01:47:38,940 --> 01:47:44,220
So, our research group has been thinking about 
early life origins of cardiometabolic disease and  

1180
01:47:44,220 --> 01:47:50,400
obesity and really focusing on PFAS lately, and 
I—you know, this intersects very nicely with diet  

1181
01:47:50,400 --> 01:47:55,380
because we think for…for PFAS, there’s—diet is one 
of the primary sources of our exposure to these  

1182
01:47:55,380 --> 01:48:03,000
chemicals. And in addition, diet has an…an…an 
important impact on our life, both prenatally  

1183
01:48:03,000 --> 01:48:08,700
and…and inter-generationally. A lot of the work 
we’re doing comes from the health outcomes and  

1184
01:48:08,700 --> 01:48:12,540
measures of the environment study or home study. 
This is a prospective pregnancy and birth cohort  

1185
01:48:12,540 --> 01:48:18,840
study in the Cincinnati, Ohio, area that was 
initiated in 2003 to 2006, and we follow—have  

1186
01:48:18,840 --> 01:48:24,420
been following—up approximately 400 children from 
the second trimester of pregnancy until now, 16  

1187
01:48:24,420 --> 01:48:28,620
to 18 years of age. We’re doing ongoing follow-up 
visits right now with them and have brought about  

1188
01:48:28,620 --> 01:48:33,300
100 back in. They’re actually grownups now. So, we 
come back in and we don’t…we don’t consent their  

1189
01:48:33,300 --> 01:48:38,580
mom…we don’t have to get them…consent from 
their moms anymore. It’s from them. And we  

1190
01:48:38,580 --> 01:48:43,560
have really detailed health phenotyping of these 
children, beginning as early as one year of age,  

1191
01:48:44,520 --> 01:48:48,420
really focused on neurodevelopment. And then 
in these later years we’ve been focusing on  

1192
01:48:48,420 --> 01:48:52,440
cardiometabolic health, bone health, as well 
as mental health, like anxiety and depression.  

1193
01:48:54,060 --> 01:48:58,500
A paper we published a few years 
ago by a…a former postdoc Nan Li,  

1194
01:48:58,500 --> 01:49:03,240
was looking at prenatal exposure to PFOA, which 
was one of these polyfluoroalkyl substances,  

1195
01:49:03,240 --> 01:49:08,580
in relationship to cardiometabolic disease at age 
12. And we created a cardiometabolic risk score,  

1196
01:49:08,580 --> 01:49:13,080
which is shown over on the…on the left 
panel there. Can I get a laser here?  

1197
01:49:18,300 --> 01:49:22,920
Laser? Nope. Nope. That’s up and down. No. Oh, 
okay. I don’t get, I don’t get the laser. Okay.  

1198
01:49:23,880 --> 01:49:29,160
So, PFAS concentrations, PFOA concentrations 
are on the…in the mom’s blood are on the x-axis,  

1199
01:49:29,160 --> 01:49:31,440
and on the y-axis there’s this 
cardiometabolic risk score,  

1200
01:49:31,440 --> 01:49:35,460
and we see this sort of nonlinear association 
with increasing cardiometabolic risk, with  

1201
01:49:35,460 --> 01:49:41,760
increasing PFOA. We saw similar associations with 
fat mass that we measured with…with a DEXA scan.  

1202
01:49:42,660 --> 01:49:46,680
And we also looked at this mixture of four 
PFAS and found that PFOA was really driving  

1203
01:49:46,680 --> 01:49:51,240
the association between cardiometabolic 
risk and…and this mixture of PFAS.  

1204
01:49:52,980 --> 01:49:57,780
My colleague Jessie Buckley has also been looking 
at prenatal PFAS exposure in relationship to bone  

1205
01:49:57,780 --> 01:50:02,700
health, and in these same kids at age 12, we 
looked at bone mineral density at multiple sites  

1206
01:50:04,080 --> 01:50:09,240
and found that higher levels of PFOA, as well as 
this PFAS mixture, were associated with lower bone  

1207
01:50:09,240 --> 01:50:15,240
density, and that these associations were somewhat 
stronger in males and at cortical bone sites,  

1208
01:50:15,240 --> 01:50:20,100
with the implication of this then being that we 
may be setting kids on this trajectory towards  

1209
01:50:20,100 --> 01:50:24,720
lower bone mass early in life, and thus at 
increased risk of osteoporosis later in life.  

1210
01:50:26,880 --> 01:50:31,500
We’ve also been doing work to investigate 
relation—biological mechanisms underlying  

1211
01:50:31,500 --> 01:50:37,320
this. And in this work published by postdoc Jamie 
Liu, we looked at DNA methylation in cord blood  

1212
01:50:37,320 --> 01:50:42,480
leukocytes at—or in leukocytes at delivery, as 
well as age 12 years of age in these children,  

1213
01:50:42,480 --> 01:50:49,320
and found that several PFAS were associated 
with CpG methylation, and we were actually  

1214
01:50:49,320 --> 01:50:54,780
able to replicate several of these in another…in 
another independent cohort. And many of these  

1215
01:50:54,780 --> 01:50:58,560
genes were related to cancers, cognitive 
health, cardiovascular and kidney disease;  

1216
01:50:58,560 --> 01:51:03,720
nothing specifically related to cardiometabolic 
disease or obesity, much like some of the work  

1217
01:51:03,720 --> 01:51:08,700
Rick…Rick Pilsner was talking about yesterday. 
But…but broadly that they suggested there  

1218
01:51:08,700 --> 01:51:13,080
could be these implications more globally for 
health. So, what was notable here is that these  

1219
01:51:13,080 --> 01:51:20,100
associations with DNA methylation and PFO—PFAS 
concentrations—in pregnancy were persistent. So,  

1220
01:51:20,100 --> 01:51:24,240
they persisted out to age 12 years of 
age. So, we saw increases or decreases  

1221
01:51:24,240 --> 01:51:28,500
in methylation that persisted across 
the life span up until we had measured.  

1222
01:51:30,300 --> 01:51:35,340
We’ve also been using the ECHO Cohorts 
to investigate associations between PFAS  

1223
01:51:35,340 --> 01:51:41,400
and, and BMI in work using over 1300 kids 
from eight of these cohorts. We’ve looked  

1224
01:51:41,400 --> 01:51:47,460
at prenatal PFOA concentrations or prenatal PFAS 
concentrations in relationship to BMI at ages two  

1225
01:51:47,460 --> 01:51:53,820
to five in children from ECHO. And in this work 
published by Jamie Liu, just, just recently in the  

1226
01:51:53,820 --> 01:52:00,060
last couple months here, we found some evidence 
a little bit mixed that PFAS concentrations were  

1227
01:52:00,060 --> 01:52:04,500
associated with increased BMI—which is on the 
left panel there—and then risk of overweight or  

1228
01:52:04,500 --> 01:52:09,720
obesity on the right axis. And these were…we 
looked at quintiles of PFAS concentrations,  

1229
01:52:09,720 --> 01:52:14,520
as well as their mixture. We did see strong 
evidence of a mixture effect, but we did find  

1230
01:52:14,520 --> 01:52:20,340
that some individual PFAS were associated with 
increased risk of obesity, like PFOS—there was a  

1231
01:52:20,340 --> 01:52:28,380
trend suggesting that—as well as for some of these 
longer chain PFAS, like PFUNDA and NMFOSAA . Not  

1232
01:52:28,380 --> 01:52:34,020
always consistent evidence of dose response, some 
cases a threshold, but, again, sort of this…this  

1233
01:52:34,020 --> 01:52:39,300
evidence again that…that these chemicals could 
have these long-term health effects on child BMI.  

1234
01:52:41,280 --> 01:52:47,880
Another thing that we’ve been investigating are 
how can we prevent PFAS exposure and related  

1235
01:52:47,880 --> 01:52:52,620
health effects. And I think this goes to what, you 
know, I was really happy to see Dr. Barker talking  

1236
01:52:52,620 --> 01:52:57,540
about interventions and…and we were talking about 
this last night, and…and the slides that have  

1237
01:52:57,540 --> 01:53:01,200
been shown sort of about, you know, what’s the 
health effects versus the cost and difficulty of  

1238
01:53:01,200 --> 01:53:06,420
doing these, you know, with preventing exposure 
way on the left there—although maybe the cost  

1239
01:53:06,420 --> 01:53:10,680
and difficulty we talked last night might be 
far higher than we…we…we’d like to think—but  

1240
01:53:11,640 --> 01:53:15,420
that, you know, we…we can certainly get more 
bang for our buck if we can prevent exposure.  

1241
01:53:17,220 --> 01:53:22,920
We’ve done some work to start to think about ways 
to decrease PFAS exposure in our environment. So,  

1242
01:53:22,920 --> 01:53:27,240
we did a quasi-experimental study actually at 
our School of Public Health a couple of years  

1243
01:53:27,240 --> 01:53:33,420
ago where we installed Corsi-Rosenthal boxes, 
which were indoor air filtration system that  

1244
01:53:33,420 --> 01:53:38,580
was designed by Richard Corsi and Jim Rosenthal; 
two air quality engineers. These were developed in  

1245
01:53:38,580 --> 01:53:45,300
response to COVID pandemic to improve indoor air 
quality. So, these are just four consumer-grade  

1246
01:53:45,300 --> 01:53:51,060
filters that are taped together with duct tape 
and a box…a box fan on the top. You turn it on,  

1247
01:53:51,060 --> 01:53:56,220
and it increases air change…air change in 
the room. And they’re really effective.  

1248
01:53:56,220 --> 01:53:59,640
They’re more effective than a commercial air 
filter that you can buy, you know, online.  

1249
01:54:01,020 --> 01:54:07,320
And so we dropped these into these 17 rooms. We 
did monitoring for exposure before and after the  

1250
01:54:07,320 --> 01:54:11,220
intervention. This was our little exposure rig 
here. We’re also measuring…so we could measure  

1251
01:54:11,220 --> 01:54:15,780
PFAS and other semivolatile compounds in the 
air. We also measured temperature and relative  

1252
01:54:15,780 --> 01:54:22,440
humidity. And we found actually that we were 
able to lower concentrations of six PFAS by  

1253
01:54:22,440 --> 01:54:28,440
30 to 60% in the air with this intervention. And 
so…and this plot here is showing you the before  

1254
01:54:28,440 --> 01:54:32,220
and during intervention distribution 
of these six PFAS concentrations,  

1255
01:54:32,220 --> 01:54:37,560
as well as each individual room change in PFAS 
concentrations before versus during intervention.  

1256
01:54:38,700 --> 01:54:43,320
And these were really pretty profound effects 
for…for air—for reducing the indoor air  

1257
01:54:43,320 --> 01:54:47,340
concentrations. You know, we were able to get, you 
know, about…reduce it by about half on average.  

1258
01:54:48,240 --> 01:54:52,200
So, this is…this is pretty big. Now, the, the 
real question now that we’re trying to follow  

1259
01:54:52,200 --> 01:54:56,880
up with this is to determine whether or not 
this translates into measurable reductions in  

1260
01:54:56,880 --> 01:55:02,760
exposure that we can—in, in our bodies. Air isn’t 
a major pathway of PFAS exposure for most of us;  

1261
01:55:03,660 --> 01:55:07,320
however, for young children it could be 
since they spend more time closer to the  

1262
01:55:07,320 --> 01:55:12,540
ground. They’re also…so they have a different 
breathing zone. And we might also be pulling  

1263
01:55:12,540 --> 01:55:17,520
some of the PFAS that would be in the dust or in 
other places out of the air when we do this. So,  

1264
01:55:17,520 --> 01:55:21,360
we’re…we’re interested and we’re seeking funding 
to go and try to do these sorts of intervention  

1265
01:55:21,360 --> 01:55:26,460
studies with the Corsi boxes and see if we 
can reduce body burden and improve health.  

1266
01:55:29,040 --> 01:55:35,700
Related to diet, there’s, you know, packaged 
and processed foods could be a source of PFAS  

1267
01:55:35,700 --> 01:55:40,860
exposure as well as other EDCs. We know that 
these chemicals are used in food packaging and  

1268
01:55:40,860 --> 01:55:44,280
processing, and as I said earlier, they 
also contaminate the…the food supply.  

1269
01:55:45,060 --> 01:55:49,380
Two studies have suggested that processed 
and packaged food consumptions related to  

1270
01:55:49,380 --> 01:55:52,980
higher levels of phthalates, which Rick was 
talking…Rick was talking about yesterday,  

1271
01:55:52,980 --> 01:55:59,160
as well as phenols. There’s not been any studies 
of PFAS that I’m aware of. And this study I’m  

1272
01:55:59,160 --> 01:56:04,680
highlighting on the right here was developed 
with Menichetti and colleagues developed a new  

1273
01:56:05,460 --> 01:56:10,860
processing index of food based on the NOVA 
Index that uses a machine learning algorithm  

1274
01:56:10,860 --> 01:56:16,500
to classify foods into their degree of processing. 
And then they looked at this food processing index  

1275
01:56:17,160 --> 01:56:22,620
in terms of consumption of individuals 
in relationship to a variety of diseases,  

1276
01:56:22,620 --> 01:56:27,900
and then some chemical exposures, as well as other 
health-related biomarkers. This is the NHANES.  

1277
01:56:27,900 --> 01:56:32,760
This is cross-sectional data, but the…the food 
processing index was associated with these disease  

1278
01:56:32,760 --> 01:56:38,400
outcomes, as well as some exposures that we 
think may be found in…in foods or food packaging.  

1279
01:56:39,480 --> 01:56:44,100
And my colleague Jessie Buckley has also published 
a study…a study showing that sandwiches, burgers,  

1280
01:56:44,100 --> 01:56:48,060
French fries, potato products, and ice cream 
pops are associated with higher levels of  

1281
01:56:48,060 --> 01:56:53,040
urinary phthalates in individuals. So, it seems 
that there’s specific food items as well as  

1282
01:56:53,700 --> 01:56:56,760
markers of the degree of processing that seems to  

1283
01:56:56,760 --> 01:57:00,360
be related to these chemical exposures 
and possibly also cardiometabolic  

1284
01:57:03,300 --> 01:57:08,220
disease. We recently have been thinking about also 
how do we prevent exposure related disease? And  

1285
01:57:08,220 --> 01:57:12,420
for PFAS, this is really important because, 
you know, once these get into our body, it’s  

1286
01:57:12,420 --> 01:57:16,860
virtually impossible to get rid of them. 
You know, so you can’t do anything about  

1287
01:57:16,860 --> 01:57:22,020
the exposure to PFAS that you’ve had in terms of 
getting rid of it. So, we need to do something  

1288
01:57:22,020 --> 01:57:26,580
for populations who have been exposed but 
want to reduce their disease risk. So,  

1289
01:57:26,580 --> 01:57:31,560
as I mentioned earlier, some of these studies in 
adults have found that better diets and physical  

1290
01:57:31,560 --> 01:57:36,360
activity seems to buffer the effects of PFAS 
exposure and risk of type 2 diabetes. And so,  

1291
01:57:36,360 --> 01:57:41,640
we looked at this in a…in our cohort, where 
we found that children with higher physical  

1292
01:57:41,640 --> 01:57:47,640
activity at age 12, we didn’t see this association 
between PFOA concentrations and cardiometabolic  

1293
01:57:47,640 --> 01:57:52,500
risk among those children with higher physical 
activity—which is the orange dash line and  

1294
01:57:52,500 --> 01:57:56,340
confidence interval. Whereas those children 
with lower physical activity, we saw increased  

1295
01:57:57,240 --> 01:58:02,520
cardiometabolic risk with increasing prenatal PFOA 
concentrations, suggesting that physical activity  

1296
01:58:02,520 --> 01:58:07,680
may buffer some of the effects of prenatal 
exposure to PFOA on cardiometabolic risk.  

1297
01:58:08,940 --> 01:58:13,920
And this interaction…interaction was significant, 
and it was really driven by insulin resistance  

1298
01:58:13,920 --> 01:58:19,020
and adiponectin leptin ratio, as well as 
visceral fat content. And some suggestion too,  

1299
01:58:19,020 --> 01:58:23,160
that this physical activity modified 
this association for the PFAS mixture.  

1300
01:58:25,500 --> 01:58:31,680
So, in terms of some of the challenges and 
opportunities we have, so I think…I think…thinking  

1301
01:58:31,680 --> 01:58:35,700
about signal-to-noise ratio here with 
intergenerational effects is really important.  

1302
01:58:36,540 --> 01:58:40,260
And I liken this to the…to butterfly wings and 
sledgehammers. You know, we have some exposures  

1303
01:58:40,260 --> 01:58:44,040
that we…are probably have like sort of butterfly 
wing effects, right? They’re not very big.  

1304
01:58:45,000 --> 01:58:47,460
They…they can…that doesn’t mean they’re 
not important, but they’re going to be  

1305
01:58:47,460 --> 01:58:51,060
hard to detect in most studies. And then 
there’s the sledgehammers, right? You know,  

1306
01:58:51,060 --> 01:58:57,780
smoking is a big sledgehammer. Diethylstilbestrol 
in exposure in utero. That’s a sledgehammer.  

1307
01:58:57,780 --> 01:59:00,780
So, when we’re looking at these studies, 
we really need to think about like,  

1308
01:59:00,780 --> 01:59:05,580
what sort of effect size are we expecting with 
this exposure? How long do we expect to see  

1309
01:59:05,580 --> 01:59:10,320
it for? What’s our sample size? You know, it’s 
sort of going back to some basic epidemiologic  

1310
01:59:10,320 --> 01:59:15,120
questions. I think we got…and…and the study design 
principles. We have to be really thoughtful about  

1311
01:59:15,120 --> 01:59:19,920
that because we may miss things otherwise, or 
we…and, and we also need to show that there’s  

1312
01:59:19,920 --> 01:59:25,380
some proof of principle here. So, I think looking 
at sledgehammers is a good place to start. I know  

1313
01:59:25,380 --> 01:59:29,280
it was…it’s not as sexy and exciting to look at 
sledgehammers—like we don’t need another study  

1314
01:59:29,280 --> 01:59:33,600
telling us that smoking is bad—but I think 
as proof of concept, it’s really important,  

1315
01:59:33,600 --> 01:59:36,600
because if you don’t see stuff with the 
sledgehammers, there may not be something  

1316
01:59:36,600 --> 01:59:42,000
there for the phthalates or the PFAS or the 
other things. Exposure data quality is really  

1317
01:59:42,000 --> 01:59:46,440
important—especially, you know, whether it’s diet 
or chemical exposures, often these historical  

1318
01:59:46,440 --> 01:59:50,160
cohorts don’t have this collective. Even some 
things like air pollution are really…you know,  

1319
01:59:50,160 --> 01:59:54,900
we can’t measure going back historically because 
we didn’t measure it back then. You know. So,  

1320
01:59:55,740 --> 02:00:01,140
this is important to think about is what sort of 
exposure data…what’s the quality of this? And then  

1321
02:00:01,140 --> 02:00:07,620
as I was alluding to sort of what’s the long-term 
effects of this? So, we often see things. These  

1322
02:00:07,620 --> 02:00:11,940
health effects manifest in childhood, but do 
they persist out into adolescence, adulthood,  

1323
02:00:11,940 --> 02:00:16,080
and on? And if they’re not persisting there, 
would they persist inter-generationally? So,  

1324
02:00:16,080 --> 02:00:19,140
I think those are…those…those are 
important studies that we need to do.  

1325
02:00:21,300 --> 02:00:25,980
I think there’s opportunities…Rick was pointing 
out, you know, we can determine if dads matter.  

1326
02:00:26,880 --> 02:00:29,340
I think I…we...and I’ll…and I’ll 
talk a little bit about this.  

1327
02:00:30,240 --> 02:00:35,520
We can utilize existing studies like the 
collaborative Perinatal project and ECHO or use,  

1328
02:00:36,240 --> 02:00:41,580
you know, these natural and existing experiments 
that have been done, like the Overkalix study.  

1329
02:00:42,720 --> 02:00:47,820
And I think more interventions to identify ways 
to reduce or prevent exposure. And I think diet  

1330
02:00:47,820 --> 02:00:51,300
is a great place to do this with chemical 
exposures because we can kill two birds  

1331
02:00:51,300 --> 02:00:56,100
with one stone by improving people’s diet. 
You know, we can get them better macro and  

1332
02:00:56,100 --> 02:00:59,940
micronutrient profiles in terms of what they’re 
eating and also reduce their chemical exposures.  

1333
02:01:02,580 --> 02:01:07,740
PFAS is just one of many potential obesogens. You 
know, there’s a laundry list that have been…that  

1334
02:01:07,740 --> 02:01:11,880
have been thought of that may be obesogens, 
like phthalates, brominated flame retardants,  

1335
02:01:11,880 --> 02:01:16,620
[inaudible]. So, I think we need to be also 
thinking very much more comprehensively  

1336
02:01:16,620 --> 02:01:20,580
about this chemical soup we live in and these 
mixtures and what their health effects are.  

1337
02:01:22,200 --> 02:01:27,840
And in terms of some of the intergenerational 
effects and how this may impact human health in  

1338
02:01:27,840 --> 02:01:33,480
terms of relative to dads, we have some data that 
is—this is hot off the presses and unpublished—but  

1339
02:01:34,200 --> 02:01:38,880
we have been doing…following children who are 
born to couples seeking fertility treatment  

1340
02:01:38,880 --> 02:01:45,600
from a clinic in…in Massachusetts General Hospital 
and looking at maternal and paternal preconception  

1341
02:01:45,600 --> 02:01:50,520
and prenatal phthalate exposures, and had 
done follow-up now on about 200 children,  

1342
02:01:50,520 --> 02:01:56,640
age 6 to 10 years of age. We have data on 
about 100 fathers in terms—both in terms of  

1343
02:01:56,640 --> 02:02:02,220
their exposure and then some follow-up data on 
them as well. And we’ve been finding that higher  

1344
02:02:02,220 --> 02:02:07,680
levels of some of these pthalates in dad’s urine 
before pregnancy is associated with alterations  

1345
02:02:07,680 --> 02:02:12,420
in children’s eating behaviors, where they have 
more of these food approach behaviors that would  

1346
02:02:12,420 --> 02:02:18,840
be associated with more obesogenic on…with being 
obesogenic. So this is, this is work that we’re,  

1347
02:02:18,840 --> 02:02:23,160
that a grad student, Jordana Leader, is 
just about to submit for publication. I  

1348
02:02:23,160 --> 02:02:28,320
think she might have submitted yesterday, 
in fact. So this…stay tuned for this. So,  

1349
02:02:28,320 --> 02:02:33,000
I just want to close by acknowledging a long, 
a long list of colleagues and…and mentors who  

1350
02:02:33,000 --> 02:02:36,060
have helped me over the years with all this, 
as well as funding from the National Institute  

1351
02:02:36,060 --> 02:02:40,440
of Environmental Health Sciences and then study 
participants from home and…and the PEACE studies.

1352
02:02:40,440 --> 02:02:41,460
DR. SOMDAT MAHABIR: Thank you.  

1353
02:02:49,680 --> 02:02:53,970
Right. Thank you very much. So, our 
next speaker is Dr. Carrie Breton.

1354
02:02:53,970 --> 02:03:02,460
DR. CARRIE BRETON: All right. Well, thank 
you so much for inviting me here today,  

1355
02:03:02,460 --> 02:03:08,460
and I will be wrapping up this session and 
pretty much the only thing between you and lunch.

1356
02:03:09,660 --> 02:03:10,032
UNIDENTIFIED SPEAKER: [inaudible].

1357
02:03:10,032 --> 02:03:16,620
DR. CARRIE BRETON: …And Q&A, sorry. (laughs) 
So I will…I’ll try to be brief here.  

1358
02:03:18,240 --> 02:03:24,960
And, so I’m going to be talking a little bit 
about built environments and how the built  

1359
02:03:24,960 --> 02:03:29,760
environment and different aspects of neighborhood 
characteristics can affect multi…multigenerational  

1360
02:03:29,760 --> 02:03:38,340
nutrition-related health. Before I start, I really 
want to highlight again some of the challenges we  

1361
02:03:38,340 --> 02:03:44,040
pricked a little bit about these both yesterday 
and today, and particularly relevant for the topic  

1362
02:03:44,040 --> 02:03:49,860
that I’m going to address in the next few minutes. 
But when we think about multigenerational studies,  

1363
02:03:49,860 --> 02:03:56,520
time is not always on our side, so a long time 
period is needed to observe changes across  

1364
02:03:56,520 --> 02:04:02,580
multiple generations. And another point that we 
definitely heard yesterday and again today is that  

1365
02:04:03,300 --> 02:04:06,000
there’s generally been a lack of 
standardization of methodology,  

1366
02:04:06,000 --> 02:04:12,240
both in exposure assessments and also when we 
talk about phenotyping health outcomes. So this  

1367
02:04:12,240 --> 02:04:18,300
makes it hard to compare across cohorts, but 
it also makes it hard to compare across time.  

1368
02:04:18,300 --> 02:04:24,180
Families also tend to have lived…shared living 
environments and shared behavior. So teasing  

1369
02:04:24,180 --> 02:04:32,220
apart the…across the generation, the effects from 
one particular generation or another when we have  

1370
02:04:32,220 --> 02:04:37,800
correlated environments and shared environments 
is a challenge. And perhaps, most germane to my  

1371
02:04:37,800 --> 02:04:43,920
talk right now, that there is a need to balance 
individual responsibility for health with the  

1372
02:04:43,920 --> 02:04:51,060
structural and societal responsibility for 
health. So I want to start by defining what I  

1373
02:04:51,060 --> 02:04:56,580
mean by the built environment, because these are 
changeable, manmade aspects of the environment.  

1374
02:04:56,580 --> 02:05:01,260
They can include things like urban 
design, land use, transportation systems.  

1375
02:05:01,860 --> 02:05:07,380
So they have the potential to support or 
constrain eating behavior and activity behavior.  

1376
02:05:07,920 --> 02:05:14,160
Examples include access to grocery stores, food 
vendors, food swamps that you’ve heard about, but  

1377
02:05:14,160 --> 02:05:19,800
also it seems like walkability in a neighborhood, 
greenness, tree cover, transportation networks,  

1378
02:05:19,800 --> 02:05:28,800
transportation density, and even the pollution 
that may come with proximity to transportation.  

1379
02:05:31,260 --> 02:05:36,960
And last year there was a scoping review that was 
published that specifically was looking at the  

1380
02:05:36,960 --> 02:05:41,640
built environment in relation to diet, physical 
activity, and obesity. So I wanted to start there,  

1381
02:05:41,640 --> 02:05:47,820
sharing some of those results. While this was a…a 
review that really looked at the evidence of the  

1382
02:05:47,820 --> 02:05:52,740
data within a single generation, not necessarily 
across generation, I…I think there’s some key  

1383
02:05:52,740 --> 02:05:58,620
points worth mentioning. Quality of dietary intake 
appeared to be associated with the availability of  

1384
02:05:58,620 --> 02:06:04,320
grocery stores. Higher levels of physical activity 
appeared to be most consistently associated with  

1385
02:06:04,320 --> 02:06:10,600
greater walkability, and lower weight status was 
associated with greater diversity in land use mix.  

1386
02:06:12,120 --> 02:06:20,040
The authors of this review also presented 
some concerns again tended to  

1387
02:06:20,040 --> 02:06:27,540
revolve around methodology and methodological 
limitations, including some concerns over poor  

1388
02:06:27,540 --> 02:06:32,700
quality of existing studies, and advocated 
for stronger study design and stronger  

1389
02:06:32,700 --> 02:06:38,760
standardization of definitions that we use across 
the study, along with valid and reliable measure.  

1390
02:06:40,860 --> 02:06:47,400
Just to share, in a little bit more detail, two 
of the figures from this review, this one shows  

1391
02:06:47,400 --> 02:06:51,720
the primary characteristics of the environment 
and the built environment that were associated  

1392
02:06:51,720 --> 02:06:57,180
with physical activity. And the top ones 
included walkability, recreational facilities,  

1393
02:06:57,180 --> 02:07:06,180
nearby shops and services, as well as proximity 
to park and trails. And when we looked at weight  

1394
02:07:06,180 --> 02:07:12,480
or when they looked at weight status, aspects of 
the…of the built environment, such land use mix,  

1395
02:07:12,480 --> 02:07:18,360
the aesthetic of the environment around you, the 
overall food environment, and again, availability  

1396
02:07:18,360 --> 02:07:22,440
of parks and playgrounds, these were all some 
of the highest predictors of weight status.  

1397
02:07:25,440 --> 02:07:31,380
So again, that didn’t address multigenerationality 
at all. But I did want to highlight a study,  

1398
02:07:31,380 --> 02:07:36,960
that came out almost 10 years ago now that 
really was one…one of the first that I  

1399
02:07:36,960 --> 02:07:43,920
could find looking at some aspect of the social 
environment in…across multiple generations. And  

1400
02:07:43,920 --> 02:07:49,140
this was the Aberdeen children was a 1950s 
study. They had three generations, so they  

1401
02:07:49,140 --> 02:07:55,200
looked…and…and we’re really asking the question 
about what might predict offspring size at first,  

1402
02:07:56,160 --> 02:08:02,400
looking at the grandmother’s generation as well 
as the parent generation. And their main takeaway  

1403
02:08:02,400 --> 02:08:08,520
from the study was that the social environment, 
as well as the mother’s own growth, were the two  

1404
02:08:08,520 --> 02:08:14,400
biggest predictors of offspring size. So I wanted 
to share with you a quote that I thought quite  

1405
02:08:15,240 --> 02:08:19,740
germane 10 years ago for…for where we 
are right now, and I’ll let you read it.  

1406
02:08:20,460 --> 02:08:26,520
But the…the …the major take home is that, 
you know, we need to balance individual  

1407
02:08:26,520 --> 02:08:33,000
characteristics that we know we can intervene 
on with the social environment and really think  

1408
02:08:33,000 --> 02:08:39,300
about our structural environment and how, how we 
as individuals interact with that environment.  

1409
02:08:40,260 --> 02:08:45,480
and I’ll just caveat that in this setting, 
social environment was really just defined  

1410
02:08:45,480 --> 02:08:50,880
as social class. So, I think there’s a lot 
more that we can do, but it does provide a  

1411
02:08:50,880 --> 02:08:56,460
nice starting point illustrating the…that 
we can try to look across generations.  

1412
02:08:58,260 --> 02:09:02,460
So, I would like to share with you some 
research that we’ve been doing in Los  

1413
02:09:02,460 --> 02:09:07,560
Angeles. This is in our MADRES pregnancy cohort, 
part of an environmental health disparity center  

1414
02:09:07,560 --> 02:09:15,540
that we’ve been running in LA for the last 7 or 8 
years. So, we have enrolled about just over 1,100  

1415
02:09:15,540 --> 02:09:22,020
pregnant women in the greater Los Angeles area. 
The neighborhoods are illustrated on this map  

1416
02:09:22,020 --> 02:09:28,200
of greater Los Angeles, shaded in pink with the 
darker colors, just having a greater density of  

1417
02:09:28,200 --> 02:09:34,620
participants in that urban core of Los Angeles. We 
recruit in early pregnancy, and we follow mothers  

1418
02:09:34,620 --> 02:09:42,060
and children for…through about 4 to 5 years of 
the child’s life. So we have started to really  

1419
02:09:42,060 --> 02:09:49,140
look at neighborhood-level characteristics of 
our population. On the left is a map, again,  

1420
02:09:49,140 --> 02:09:54,360
these are all…will all be the maps of sort of the 
greater Los Angeles area. Outlined in pink are the  

1421
02:09:54,360 --> 02:10:01,500
neighborhoods in which our participants reside, 
and on the left is…are our neighborhoods overlaid  

1422
02:10:01,500 --> 02:10:07,380
with census-based data for race and ethnicity, 
where purple are Asian…from Asian communities,  

1423
02:10:07,380 --> 02:10:12,540
green are predominantly Hispanic communities, and 
yellow predominantly Black or African American  

1424
02:10:12,540 --> 02:10:18,420
communities. So I think what you can see just 
visually is that our population…the majority of  

1425
02:10:18,420 --> 02:10:23,400
our population lives in neighborhoods that are 
predominantly Hispanic. And in fact, 75% or so  

1426
02:10:23,400 --> 02:10:30,120
of our population self-identify…self-identified 
as Hispanic. On the right, we’ve overlaid those  

1427
02:10:30,120 --> 02:10:35,580
same neighborhoods with historical redlining 
information from 1930s in Los Angeles. The redline  

1428
02:10:35,580 --> 02:10:41,580
neighborhoods are shown in yellow and red. And 
so also, I think what’s striking is that many of  

1429
02:10:41,580 --> 02:10:48,720
our neighborhoods are…our participants are living 
in neighborhoods that were historically redlined.  

1430
02:10:51,900 --> 02:10:57,060
So, there are many different characteristics 
that we can look at and think about when we  

1431
02:10:57,060 --> 02:11:01,920
talk about neighborhoods. And this—we’ve 
been doing work in our center that’s been  

1432
02:11:01,920 --> 02:11:06,060
led by my colleague and co-investigator, 
Rima Habre, who’s an exposure scientist.  

1433
02:11:07,020 --> 02:11:11,460
So outlined here in the diagram are really 
several different aspects of neighborhoods that  

1434
02:11:11,460 --> 02:11:16,140
we can look at. They expand from demographics 
to socioeconomics to the built environment,  

1435
02:11:16,140 --> 02:11:22,320
which is my focus today, as well as the chemical 
environment and physical environment. And then,  

1436
02:11:22,320 --> 02:11:29,580
in terms of social environments, specific indices 
that we can map onto our residential addresses  

1437
02:11:29,580 --> 02:11:36,240
are things such as the walkability index, 
greenness and tree cover indices, food deserts,  

1438
02:11:36,240 --> 02:11:43,200
transportation networks, food insecurity, food 
swamps should be added to this list. And then  

1439
02:11:43,200 --> 02:11:48,060
on the right, you can see the distribution 
to some of the metrics in our population and  

1440
02:11:48,060 --> 02:11:53,700
about 800 of our MADRES participants. The 
top one shown on the right is actually the  

1441
02:11:53,700 --> 02:11:59,460
CES score. This is the CalEnviroScreen score, 
which is a cumulative index of neighborhood  

1442
02:11:59,460 --> 02:12:06,420
burden for the state of California. And I’ll show 
you more on that in the next slide. In fact—so  

1443
02:12:06,420 --> 02:12:14,580
the CalEnviroScreen is really—the overall burden 
score ranges from zero to 100, with 100 showing…or  

1444
02:12:14,580 --> 02:12:18,480
indicating sort of the most environmentally 
burdened neighborhoods across the state of  

1445
02:12:18,480 --> 02:12:23,160
California. This is comprised of two subscores 
that are multiplied together. One of them is a  

1446
02:12:23,160 --> 02:12:29,700
population susceptibility score, so this…some 
exposures such as—thinking about crime rates,  

1447
02:12:30,660 --> 02:12:37,980
asthma prevalence rate, poverty. And then the 
pollution burden score really tries to get at  

1448
02:12:37,980 --> 02:12:44,460
proximity to hazardous chemicals, industrial waste 
sites, air pollution levels, and things like that.  

1449
02:12:44,460 --> 02:12:51,300
So, the highest levels are shown in pink and red. 
And I think what you can see is that many of our  

1450
02:12:51,300 --> 02:12:58,020
neighborhoods were very highly in the pink and 
red, indicated on this index. So really indicating  

1451
02:12:58,020 --> 02:13:03,780
total sets of population susceptibility point 
of view and from pollution point of view that,  

1452
02:13:03,780 --> 02:13:08,340
our participants are living in neighborhoods 
that are highly burdened. In fact, 60% of our  

1453
02:13:08,340 --> 02:13:13,020
participants live in the 10% most highly burdened 
neighborhoods across the state of California.  

1454
02:13:17,460 --> 02:13:21,060
But we can also look at things 
like distance to supermarkets. So,  

1455
02:13:21,960 --> 02:13:27,000
on the left is a zoomed-out version of LA, 
and our neighborhoods are outlined in blue,  

1456
02:13:27,000 --> 02:13:32,340
with yellow indicating the supermarkets, 
and green areas…areas of green are shaded.  

1457
02:13:33,060 --> 02:13:39,300
Our proximity was in a 1-mile walk to one or 
more supermarkets. And the righthand side is  

1458
02:13:39,300 --> 02:13:44,700
the zoomed-in area, in LA, just to sort 
of show you more specifically that the  

1459
02:13:44,700 --> 02:13:48,360
areas of concern would actually be the areas 
that are yellow with the red dots. So these  

1460
02:13:48,360 --> 02:13:54,480
are areas that do not have supermarket access 
within that 1-mile walk. There…this is more of  

1461
02:13:55,320 --> 02:14:02,760
a…you can access a supermarket within about a 
10-minute drive from your home. So…so we can  

1462
02:14:02,760 --> 02:14:07,320
start to look at some of these indices and try and 
release them to health…health outcomes. And so,  

1463
02:14:07,320 --> 02:14:14,820
one of our interests has been looking at obesity 
risks and infant fat and lean mass early in life.  

1464
02:14:14,820 --> 02:14:20,640
And so, we have begun measuring infant fat and 
lean mass using an instrument known as an EchoMRI,  

1465
02:14:20,640 --> 02:14:27,000
which measures full body fat mass, lean mass, 
free water, and total water. This image is of the  

1466
02:14:27,000 --> 02:14:33,540
machine shown right here. And it takes 3 minutes 
to do. It’s a quantitative measure, it’s not an  

1467
02:14:33,540 --> 02:14:43,680
imaging MRI. And it…and it’s no radiation. So 
unlike [inaudible] we don't have any radiation concerns. So, to date, we have done  

1468
02:14:43,680 --> 02:14:49,920
about 111 infants. We put them in and measure 
their fat and lean mass at about 1 month of age.  

1469
02:14:52,080 --> 02:14:55,800
And we have started to look at some of 
these built environment characteristics  

1470
02:14:55,800 --> 02:14:59,820
in relation to infant fat and lean mass. 
And what we’re seeing in preliminary data,  

1471
02:14:59,820 --> 02:15:06,000
is that when we look at tree canopy, for no matter 
what cluster we use to sort of—around the home to  

1472
02:15:06,000 --> 02:15:13,140
quantify the tree canopy—we’re seeing a positive 
association between presence and density of tree  

1473
02:15:13,140 --> 02:15:19,200
canopy with lean mass in…in them. But we don’t 
see any associations with fat mass. And when we  

1474
02:15:19,200 --> 02:15:24,000
looked at food deserts, we also don’t…haven’t 
seen any strong associations with fat or lean  

1475
02:15:27,780 --> 02:15:30,900
mass. Not strictly built environment, but 
looking at the Gini Index, which you heard  

1476
02:15:30,900 --> 02:15:35,040
about before, more of a socioeconomic 
indicator. We also were looking at…so  

1477
02:15:36,060 --> 02:15:43,020
this proportion of income inequality in a given 
neighborhood and whether it might relate to infant  

1478
02:15:43,020 --> 02:15:47,940
characteristics and found that higher Gini 
Index in pregnancies negatively correlated  

1479
02:15:47,940 --> 02:15:53,940
with newborn adiponectin levels…adiponectin 
levels. So, adiponectin is interesting because  

1480
02:15:54,660 --> 02:16:00,060
it’s an anti-inflammatory molecule produced 
by fat tissues. It can affect many different  

1481
02:16:00,060 --> 02:16:07,140
organ systems, and most notably, I think, in 
thinking about nutrition and metabolic health,  

1482
02:16:07,140 --> 02:16:13,260
it can help regulate lipid and glucose problems 
in…in the liver. So, we don’t yet know what  

1483
02:16:13,260 --> 02:16:18,600
this means. We don’t know the implications of…of 
changing, adiponectin levels in this population  

1484
02:16:18,600 --> 02:16:24,600
at 1 month of age, but this is something that, 
I think it’s preliminary and intriguing and,  

1485
02:16:25,620 --> 02:16:27,720
something that we’re going to follow up on.  

1486
02:16:30,360 --> 02:16:36,000
I have a postdoc, Nancy, who has also been very 
interested in looking at growth trajectories of  

1487
02:16:36,000 --> 02:16:40,260
our infants through the first 2 years of 
life. So I want to, wanted to just share  

1488
02:16:40,260 --> 02:16:47,520
with you some of this work, really looking 
at the combination of maternal diet in  

1489
02:16:47,520 --> 02:16:52,859
the third trimester of pregnancy in the context 
of child neighborhood characteristics, which is  

1490
02:16:52,859 --> 02:16:59,939
the Childhood Opportunity Index, which really just 
tries to, quantify the quality of a neighborhood  

1491
02:16:59,939 --> 02:17:04,859
in which a child lives and how much opportunity 
is in the neighborhood. And I think what’s most  

1492
02:17:04,859 --> 02:17:13,080
striking…so this…the plot that you see here are 
growth trajectory starting in utero. So it’s a  

1493
02:17:13,080 --> 02:17:18,120
combination of fetal growth in the third trimester 
through birth weight, through 2 years of life.  

1494
02:17:18,120 --> 02:17:25,260
And, almost immediately, in the third trimester 
of pregnancy, you see a divergence of the green  

1495
02:17:25,260 --> 02:17:30,359
and brown curve from the blue and red. And 
really that represents the difference between  

1496
02:17:30,359 --> 02:17:36,359
communities…children who were born in communities 
with high COI versus low COI. So green and brown  

1497
02:17:37,560 --> 02:17:43,859
trajectories are the trajectories of 
children born in the high COI neighborhoods,  

1498
02:17:43,859 --> 02:17:50,399
whereas blue and red are in low COI neighborhoods. 
Now, the more modest differences are seen with the  

1499
02:17:50,399 --> 02:17:58,080
dietary pattern, which we identified as high in 
fruits, oils, and vegetables. and so if we compare  

1500
02:17:58,080 --> 02:18:04,439
the highest quartile to the lowest quartile of 
this dietary pattern, we see modest reductions in  

1501
02:18:04,439 --> 02:18:09,179
the growth and attained weight at 2 years within 
each of those categories. But I think by far the  

1502
02:18:09,180 --> 02:18:15,960
most striking observation is that there’s these 
diverging growth patterns, from the get-go in  

1503
02:18:15,960 --> 02:18:20,700
children, depending on the opportunity of 
the neighborhoods in which they are born.  

1504
02:18:22,859 --> 02:18:28,019
If we now take a step broader and look 
nationwide, there…I wanted to share with  

1505
02:18:28,020 --> 02:18:32,760
you a couple different publications coming out of 
Echo, which have addressed characteristics of the  

1506
02:18:32,760 --> 02:18:37,260
built environment and thinking about birth 
outcomes and weight trajectories. And so,  

1507
02:18:37,260 --> 02:18:44,700
published last year by Sheena Martenies, 
was a…was a publication really looking at an  

1508
02:18:44,700 --> 02:18:49,019
index similar to the CalEnviroScreen but 
created on a national level, and whether  

1509
02:18:50,280 --> 02:18:54,479
children who were born in high…communities 
with higher overall burden, whether there’s  

1510
02:18:54,479 --> 02:18:57,599
differences in birth outcomes, and 
what they observed was that indeed,  

1511
02:18:58,320 --> 02:19:04,380
there was lower birthweight and earlier 
gestational age at birth in children who  

1512
02:19:04,380 --> 02:19:08,880
were born in communities with these…with 
higher scores on this burden index.  

1513
02:19:12,120 --> 02:19:19,439
Similarly, in another paper that came out last 
year, they were interested in looking at two  

1514
02:19:19,439 --> 02:19:23,939
different aspects of neighborhood vulnerabilities. 
Again, one of them was the COI, the Child  

1515
02:19:23,939 --> 02:19:29,759
Opportunity Index that’s shown on the left. The 
other was the Social Vulnerability Index, which  

1516
02:19:29,760 --> 02:19:35,939
is created by the CDC. And both of these were 
looking at growth trajectories…BMI trajectories  

1517
02:19:35,939 --> 02:19:42,780
from birth through 20 years of life, and both…in 
looking at both measures, they really saw similar  

1518
02:19:42,780 --> 02:19:47,580
pattern of [inaudible], which is that residence 
and neighborhoods with higher opportunity or lower  

1519
02:19:47,580 --> 02:19:54,180
social vulnerability in early life were associated 
with an overall lower BMI trajectory and lower  

1520
02:19:54,180 --> 02:20:00,240
risk of obesity. And I think what’s most striking 
is that they looked at these indices at different  

1521
02:20:00,240 --> 02:20:07,019
time points, and the strongest associations were 
at birth. That maternal environment, in utero,  

1522
02:20:08,040 --> 02:20:12,660
mattered. It mattered a lot for 
a 20-year trajectory of growth.  

1523
02:20:15,960 --> 02:20:22,920
And the last bit of data I wanted to share, also 
coming out of Echo just this year was looking  

1524
02:20:22,920 --> 02:20:29,040
at the effects of a policy intervention 
on a national level. And so this was…the  

1525
02:20:30,840 --> 02:20:36,899
goal here was to look at the trends in BMI 
nationally in children after…before and after  

1526
02:20:36,899 --> 02:20:42,059
implementation of the Healthy Hunger-Free Kids 
Act of 2010. And so this act was really meant  

1527
02:20:42,060 --> 02:20:47,760
to intervene on school lunches and try to improve 
the quality of school lunches. And I think what  

1528
02:20:47,760 --> 02:20:54,120
you see pretty strikingly in this slide is that 
BMI trajectories on the left in sort of the white  

1529
02:20:54,120 --> 02:21:00,240
shaded area, and in the blue and dark blue lines, 
that’s the overall trajectory of BMI from about,  

1530
02:21:00,240 --> 02:21:07,019
what, 2005 to 2016, so trending slightly upward 
over time. And then after the intervention,  

1531
02:21:07,020 --> 02:21:13,740
you see a…a marked change in that trajectory 
of BMI compared to sort of the dashed lines,  

1532
02:21:13,740 --> 02:21:18,300
which is where it was projected to have gone 
had there not been any policy intervention.  

1533
02:21:21,420 --> 02:21:27,720
So, I’ll just end with my own thoughts about 
the challenges and…and opportunities for the  

1534
02:21:27,720 --> 02:21:33,180
future. And, I think…you know, we have plenty of 
literature on aspects of the built environment  

1535
02:21:33,180 --> 02:21:37,979
within a single generation. I showed just 
very…just a very quick glimpse at some of what  

1536
02:21:37,979 --> 02:21:45,419
that might look like. But as I think we’ve heard 
thematically throughout yesterday and today, there  

1537
02:21:45,960 --> 02:21:51,359
are…there’s just a lot less that’s known across 
generations, specifically when I think about the  

1538
02:21:51,359 --> 02:21:59,700
built environment. And our ability to track that 
in a standardized fashion across generations is  

1539
02:21:59,700 --> 02:22:09,660
also a…I think remains a huge challenge. And then 
I would just sort augment on to that, that our…we  

1540
02:22:09,660 --> 02:22:14,939
need to do our due diligence to try to tease 
apart the shared environment that will cross,  

1541
02:22:15,960 --> 02:22:19,020
you know, that does cross across 
generations to really try to understand,  

1542
02:22:19,020 --> 02:22:23,940
the effect within each generation 
and then also across each generation.  

1543
02:22:25,740 --> 02:22:28,859
So, opportunities that exist 
to do this though, I think,  

1544
02:22:29,460 --> 02:22:36,780
really lie in…in thinking about the intersection 
of how we individually interact then with the  

1545
02:22:36,780 --> 02:22:41,939
environment around us. And, and I would argue that 
there’s probably a role for 1. looking and trying  

1546
02:22:41,939 --> 02:22:46,259
to take advantage of mobility setting. I think 
we saw one example of that a little bit earlier,  

1547
02:22:47,040 --> 02:22:55,140
in both directions. So if we can, you know…as 
families either hopefully go more upwardly mobile,  

1548
02:22:55,140 --> 02:22:59,160
can we take advantage of the change across 
the different environments and really look  

1549
02:22:59,160 --> 02:23:04,740
at whether we can see and disentangle some of 
these effects. But I think there’s also a role for  

1550
02:23:05,520 --> 02:23:12,180
more personalized type study designs looking at 
ecological momentary assessment type designs,  

1551
02:23:12,180 --> 02:23:18,660
for instance, where you can really capture in real 
time and a snapshot and of an individual response  

1552
02:23:18,660 --> 02:23:22,680
to their environment around that. And so then you 
get that perception of the environment and not  

1553
02:23:22,680 --> 02:23:31,140
just the GIS-based sort of index or…or assessment 
of the neighborhood defined by some sort of buffer  

1554
02:23:31,140 --> 02:23:39,060
around a residential address. And with that, I 
will end with acknowledgement to a large number of  

1555
02:23:39,899 --> 02:23:46,559
collaborators and staff and students and postdocs 
that make all of this work possible. Thank you.

1556
02:23:46,560 --> 02:23:56,760
DR. SOMDAT MAHABIR: Thank you very much. 
So, I’d like to take this opportunity to  

1557
02:23:56,760 --> 02:24:02,880
invite all the speakers to come and sit 
up front here so we can start our Q&A.  

1558
02:24:06,899 --> 02:24:12,420
I think you would agree with me that this was 
really a wonderful session. Kind of varied,  

1559
02:24:14,100 --> 02:24:20,760
and we’ll try not to tie it together. 
Disparities [inaudible] to built environment.  

1560
02:24:22,319 --> 02:24:27,179
So, I think the way we’ll start to do this,  

1561
02:24:27,180 --> 02:24:34,284
let’s give the people online the opportunity 
first. So, we’ll…one online, one in house.

1562
02:24:34,284 --> 02:24:40,740
DR. KELLIE CASAVALE: How 
much time do we have today?  

1563
02:24:40,740 --> 02:24:44,580
All right. We do have a number of 
questions that have come in online. So,  

1564
02:24:44,580 --> 02:24:48,059
hi. Thank you again for the session. 
That was really, really fabulous.  

1565
02:24:49,080 --> 02:24:53,939
And to everybody listening online, I’m Kellie 
Casavale from FDA. And so the first question  

1566
02:24:54,660 --> 02:25:03,660
that we have, I…I think is for Merilee who is 
online. And the question is, “Regarding the  

1567
02:25:03,660 --> 02:25:10,740
composition of human milk, what is the influence 
of maternal insulin on insulin content in human  

1568
02:25:10,740 --> 02:25:16,439
milk and insulin, and the infants, which we 
know influences fetal growth and metabolism?”

1569
02:25:18,800 --> 02:25:24,960
DR. MERILEE (MEREDITH) BROCKWAY: That’s a great 
question. And insulin is…definitely, can be  

1570
02:25:24,960 --> 02:25:32,040
impactful for the infant nutrition. So, it hasn’t 
been well examined because a. we try to keep,  

1571
02:25:32,040 --> 02:25:38,640
obviously, maternal diabetes well controlled, 
so we don’t like to have high insulin levels in  

1572
02:25:38,640 --> 02:25:45,300
moms. Therefore, it won’t be as prevalent in 
milk. And then also, in uncontrolled diabetes,  

1573
02:25:45,300 --> 02:25:51,300
those mothers are not that successful in 
breastfeeding. So, my understanding is that  

1574
02:25:51,300 --> 02:25:56,819
insulin will pass through the breast milk, but 
I don’t think we have very good evidence around  

1575
02:25:56,819 --> 02:26:03,179
what the impact of that is on infants. I can 
look into that and get back to you with a more  

1576
02:26:03,180 --> 02:26:08,100
comprehensive answer if you want to pop your email 
into the chat and I can give you a better answer.  

1577
02:26:08,100 --> 02:26:13,920
But as I mentioned before, the level of evidence 
and the data around it is pretty sparse, I think.

1578
02:26:13,920 --> 02:26:23,048
DR. SOMDAT MAHABIR: Thank you. Any question 
from the audience here? Oh, it’s not yet done.

1579
02:26:23,048 --> 02:26:24,519
DR. KELLIE CASAVALE: [inaudible]
DR. SOMDAT MAHABIR: Okay, Kelly.

1580
02:26:24,519 --> 02:26:34,123
DR. KELLIE CASAVALE: Okay. Anybody in the 
audience have a question before I ask mine?  Okay. Go ahead, Mary.

1581
02:26:34,123 --> 02:26:37,500
DR. MARY BARKER: I’m trying to decide which 
of my list of questions to start with.  

1582
02:26:40,080 --> 02:26:46,080
I’m going to start with Kristen’s question. That 
was a great talk. I loved it. I was going to love  

1583
02:26:46,080 --> 02:26:53,160
it, wasn’t I? But I did, so that’s good. I loved 
the…the framing that you put on everything. I was  

1584
02:26:53,160 --> 02:26:58,559
very, very interested in your descriptions of 
the non-nutrition–specific interventions, which  

1585
02:26:58,560 --> 02:27:08,280
had nutritional outcomes. I think non-nutrition 
specific, as in nutrition-sensitive interventions,  

1586
02:27:08,280 --> 02:27:13,080
are probably the way to go. So, the global 
kind of more structural, broader interventions,  

1587
02:27:13,080 --> 02:27:16,500
which address a whole load of issues which 
have nutritional impacts. What was really  

1588
02:27:16,500 --> 02:27:19,920
interesting is that they measured nutritional 
outcomes in that study you talked about. I’ve  

1589
02:27:19,920 --> 02:27:23,700
had a quick look for it and can’t find it, 
so I’m going to come and see you later and  

1590
02:27:23,700 --> 02:27:28,679
I want your list…all your references from your 
talk. Can you tell me about…anything more about  

1591
02:27:28,680 --> 02:27:32,280
that study about why they ended up measuring 
nutritional outcomes when actually they didn’t  

1592
02:27:32,280 --> 02:27:38,700
set out to measure any or didn’t set out to 
assess them? It was the one…it was the study  

1593
02:27:38,700 --> 02:27:44,760
where they planted a new supermarket into a 
neighborhood where there was no supermarket.  

1594
02:27:46,920 --> 02:27:50,939
The one…no, sorry. It was the one where they 
moved…they moved. No, it wasn’t actually that  

1595
02:27:50,939 --> 02:27:55,740
one. I was wrong. It’s the place…it’s the 
study where they moved…relocated a load  

1596
02:27:55,740 --> 02:28:00,359
of families into a slightly less disadvantaged 
neighborhood and found reduction in obesity and…

1597
02:28:00,359 --> 02:28:03,179
DR. KRISTEN COOKSEY STOWERS: The 
moving to opportunity study? Yes. 

1598
02:28:03,840 --> 02:28:07,183
Okay. So the technology distracted me 
one more time for the actual question.

1599
02:28:07,183 --> 02:28:11,399
DR. MARY BARKER: I just…can you tell me more about 
it? Can you tell me more about it, because I’m  

1600
02:28:11,399 --> 02:28:16,500
really interested in the whole nutrition-sensitive 
interventions rather than nutrition-specific  

1601
02:28:16,500 --> 02:28:19,319
interventions. How do they…how do they 
end up measuring nutritional outcomes?

1602
02:28:19,319 --> 02:28:25,019
DR. KRISTEN COOKSEY STOWERS: Yeah. 
So, I think…great question and  

1603
02:28:25,620 --> 02:28:30,624
I mean the…the affluent tent of, like, big picture 
because so many papers and so many analysis.

1604
02:28:30,648 --> 02:28:35,099
DR. KRISTEN COOKSEY STOWERS: I mean, it’s one 
of the biggest in terms of housing research  

1605
02:28:35,100 --> 02:28:40,551
and segregation and those kinds of things. 
So, hundreds of …I mean, I can’t even…right?

1606
02:28:40,551 --> 02:28:43,531
DR. MARY BARKER: Okay. That’s interesting.

1607
02:28:43,531 --> 02:28:48,000
DR. KRISTEN COOKSEY STOWERS: Yeah. So…so, 
but the…the initial intent of the study was  

1608
02:28:48,000 --> 02:28:55,260
to understand, really, how to…how to manage 
concentrated poverty. And I think some of  

1609
02:28:55,260 --> 02:29:02,100
the research leveraging, you know, the history of 
structural racism as it relates to policy is that,  

1610
02:29:02,100 --> 02:29:05,820
you know, the government sort of, you 
know, trying to see, like, how should…how  

1611
02:29:07,380 --> 02:29:15,660
should we best manage clusters of poverty? Do 
we want to sort of allow it to spread or should  

1612
02:29:15,660 --> 02:29:20,580
we think and test…do an experiment to see, you 
know, who built it up so high? I’m from Chicago,  

1613
02:29:20,580 --> 02:29:24,660
so they’re…they’re called projects and they’re 
short, hence their nickname “projects,” and people  

1614
02:29:24,660 --> 02:29:29,939
that live there forget that it was…like, projects 
are not just sort of a by chance name. They were  

1615
02:29:29,939 --> 02:29:37,019
actual projects by the housing department 
to explore poverty and housing among young,  

1616
02:29:37,020 --> 02:29:42,420
low-income mothers and really, plainly put, 
what to do with them. Right? Do we stack them  

1617
02:29:42,420 --> 02:29:48,420
up yay high? Do we allow them…give them back 
[inaudible] get…gave a head nod to do this  

1618
02:29:48,420 --> 02:29:53,640
socioeconomic status, right? Because we all, even 
in nutrition, should give vouchers. Should we give  

1619
02:29:53,640 --> 02:29:59,399
double bucks? Should we give coupons and, you 
know, and…and wish them many blessings, if you  

1620
02:29:59,399 --> 02:30:06,299
will. That’s great. But we also have spatial-built 
neighborhood aspects that we have to tackle. So,  

1621
02:30:06,300 --> 02:30:09,178
it’s another one of those both-end questions. 
So, there’s so many…happy to [inaudible]—

1622
02:30:09,178 --> 02:30:10,991
DR. MARY BARKER: Okay. I—[overlapping voices]

1623
02:30:10,991 --> 02:30:13,295
DR. KRISTEN COOKSEY STOWERS: —so 
many papers that come out of this.

1624
02:30:13,295 --> 02:30:15,780
DR. MARY BARKER: So, what’s 
really interesting is…is  

1625
02:30:16,920 --> 02:30:22,260
that you’ve drawn our attention to a…a major 
housing study. A study about housing, which  

1626
02:30:22,260 --> 02:30:26,880
has the additional implications, which I think 
for all of us, there’s a kind of wakeup call,  

1627
02:30:26,880 --> 02:30:30,780
but there are areas of literature we would not 
go to. I don’t know anything about the housing  

1628
02:30:30,780 --> 02:30:38,340
literature, but clearly, I should and…and to 
be much broader in our…in our looking. And Joe,  

1629
02:30:38,340 --> 02:30:40,020
so would that be a…
[Inaudible cross-talk]

1630
02:30:40,020 --> 02:30:46,020
DR. JOSEPH BRAUN: But you know, 
it’s interesting because, you know,  

1631
02:30:46,020 --> 02:30:48,386
I think housing is an interesting aspect because, 
you know, we have studies we’re going through  

1632
02:30:48,386 --> 02:30:56,399
right now where we’ve done some interventions 
[inaudible] originally targeting less, but now  

1633
02:30:56,399 --> 02:31:00,540
we’re trying to see if it affects other chemicals 
in the environment because it’s cleaned up.  

1634
02:31:00,540 --> 02:31:03,740
And so housing may be again, a 
way to go after multiple things.

1635
02:31:03,740 --> 02:31:04,500
DR. MARY BARKER: Yeah.
DR. JOSEPH BRAUN: Nutrition,

1636
02:31:04,500 --> 02:31:08,880
indoor chemical exposures that are coming 
from emanating indoor environments and built  

1637
02:31:08,880 --> 02:31:13,620
materials. So, I think…I think, you know, you’re 
right, the home is a really important aspect that  

1638
02:31:13,620 --> 02:31:16,783
centers on a lot of things, you spend a lot of 
time there. So there’s a lot of things we can do.

1639
02:31:16,783 --> 02:31:19,290
DR. MARY BARKER: And where 
your home is, which I think…

1640
02:31:19,290 --> 02:31:21,840
DR. KRISTEN COOKSEY STOWERS: Yeah, and I…and 
I would add…I would add to those points,  

1641
02:31:21,840 --> 02:31:26,100
water. This is where some of my work is evolving, 
right? When we…when we sort of frame it as a,  

1642
02:31:26,100 --> 02:31:30,420
you know, a sugary drink issue, 
even…even addressing disparities,  

1643
02:31:30,420 --> 02:31:34,680
you know, if we stay in our house nutrition, 
forget the impact of the housing piece that  

1644
02:31:34,680 --> 02:31:39,720
we look at the qualitative research. It’s not just 
simple as folks don’t know. They have no intention  

1645
02:31:39,720 --> 02:31:43,800
to drink water. There are actual legitimate 
concerns about drinking water from their home,  

1646
02:31:43,800 --> 02:31:48,840
and issues like Flint, Michigan, that elevated 
all types of things. And I think…I think…and it’s  

1647
02:31:48,840 --> 02:31:52,800
a thing that started yesterday, right? Getting 
out of silos, getting…going across departments  

1648
02:31:52,800 --> 02:31:58,020
and…and…and sort of why highlighted again, 
both are cross-cultural determinants because  

1649
02:31:58,020 --> 02:32:01,838
it’s not as clean. And, you know, one or 
the other, they’re all interconnected.

1650
02:32:01,838 --> 02:32:04,139
DR. KELLIE CASAVALE: All right, so in the 
interest of time, we’re going to move on to  

1651
02:32:04,140 --> 02:32:08,100
the next question. I could literally talk about 
that topic for at least two hours with you guys.  

1652
02:32:09,120 --> 02:32:15,000
Getting all sorts of good ideas. So, the next 
question, I think, is also primarily…and it’s  

1653
02:32:15,000 --> 02:32:20,520
related to the measures that you mentioned as 
being gaps in the end. And the question is,  

1654
02:32:20,520 --> 02:32:26,640
“do you have any thoughts about the questionnaires 
used in CDC’s infant feeding practices study as a  

1655
02:32:26,640 --> 02:32:31,800
solution to adequately assessing infant and early 
childhood diet? That…I know I had a very similar  

1656
02:32:31,800 --> 02:32:36,288
question because I also work in this area of 
acquiring adequate federal data in the space.

1657
02:32:36,288 --> 02:32:41,160
DR. MERILEE (MEREDITH) BROCKWAY: Yeah, it’s an 
excellent question. And the CDC questionnaire is a  

1658
02:32:41,160 --> 02:32:47,040
beautiful questionnaire. It really comprehensively 
looks at infant feeding. The challenge is…is  

1659
02:32:47,040 --> 02:32:52,439
because it’s a large questionnaire, so participant 
burden is a concern. So, when we’re working with  

1660
02:32:52,439 --> 02:32:57,599
cohort studies or intervention trials and 
looking at infant feeding as an outcome,  

1661
02:32:57,600 --> 02:33:03,060
that questionnaire is…it would really add to 
participant burden. So, I think if we were to  

1662
02:33:03,060 --> 02:33:07,500
develop kind of a consistent questionnaire 
that is just kind of a short form, I guess,  

1663
02:33:07,500 --> 02:33:13,020
that would be ideal, that it’s just a series 
of like four or five questions and are able to 

1664
02:33:13,020 --> 02:33:18,300
capture similar information but not as 
granular for those larger cohort studies.

1665
02:33:18,300 --> 02:33:22,439
DR. KELLIE CASAVALE: All right, 
great, thank you. Okay. And now  

1666
02:33:22,439 --> 02:33:26,519
I’m going to ask my question from in the 
room, and this question is for Joseph, and  

1667
02:33:26,520 --> 02:33:33,180
I’m also going to use your sledgehammer analogy 
because I do…I do like that. So, in your talk  

1668
02:33:33,180 --> 02:33:38,520
you mentioned utilizing existing studies. And 
the National Health and Nutrition Examination  

1669
02:33:39,960 --> 02:33:46,800
Study measures many different data points that are 
related to PFAS for ages 1 year and older. And so,  

1670
02:33:46,800 --> 02:33:52,380
what kind of bio samples or other measures—so 
for infants—do you think would help elucidate  

1671
02:33:52,380 --> 02:33:57,359
those sledgehammers in infant exposures to 
PFAS and also other environmental chemicals?

1672
02:33:57,359 --> 02:34:03,000
DR. JOSEPH BRAUN: I…I mean the…the…I mean there 
are bio…there are bank biospecimens from NHANES  

1673
02:34:03,000 --> 02:34:07,140
as far as I’m aware. You know, the…the 
biomonitoring program for NHANES though,  

1674
02:34:07,740 --> 02:34:11,639
I don’t remember the exact details for every 
exposure, every micronutrient they measure, but  

1675
02:34:11,640 --> 02:34:16,899
that doesn’t encompass always down to infancy. So, 
a lot of factors aren’t measured down in early—

1676
02:34:16,899 --> 02:34:19,560
DR. KELLIE CASAVALE: So, I’ll just…I’ll 
just add to that that they don’t collect  

1677
02:34:20,160 --> 02:34:22,252
blood, for example, on infants at all.

1678
02:34:22,297 --> 02:34:23,637
DR. JOSEPH BRAUN: No, no, 
no. It’s only done at one.

1679
02:34:23,637 --> 02:34:25,890
DR. KELLIE CASAVALE: So, what kind of bio 
samples do you think would be most valuable?

1680
02:34:25,890 --> 02:34:28,800
DR. JOSEPH BRAUN: I…I mean, blood is valuable, 
but so is, you know, we can measure a lot of  

1681
02:34:28,800 --> 02:34:34,560
things in urine. Increasingly, people are 
doing some stuff with hair. It’s…it doesn’t  

1682
02:34:34,560 --> 02:34:40,319
work for everything though. So I think those 
are reasonable places to start. You know,  

1683
02:34:40,319 --> 02:34:44,099
the other thing…the other things just to collect 
are things like, you know, there’re…people are  

1684
02:34:44,100 --> 02:34:49,200
using the…the exposome wristbands that can absorb 
lots of things from the environment. But the issue  

1685
02:34:49,200 --> 02:34:52,620
is whether those are actually indicative of 
exposure. It’s not also something you can  

1686
02:34:52,620 --> 02:34:56,460
put on an infant. You got to find a way to, you 
know, put it on them that…that doesn’t involve  

1687
02:34:56,460 --> 02:35:01,020
going around their wrist because it won’t stay 
there. So I think…I think there’re…but I think,  

1688
02:35:01,020 --> 02:35:05,040
again, urine is probably the best bet to get 
at a lot of things, particularly because I  

1689
02:35:05,040 --> 02:35:08,939
think a lot of manufacturers who have made 
these persistent pollutants are switching  

1690
02:35:08,939 --> 02:35:12,419
to making things less persistent, which means 
they’re going to get excreted in the urine more.

1691
02:35:13,439 --> 02:35:19,439
DR. SOMDAT MAHABIR: Wonderful. I…just for Joseph, 
as well, and Carrie, I’m going to have…make a  

1692
02:35:19,439 --> 02:35:25,080
quick comment—you may not be familiar with some 
of these resources—and then a question. So,  

1693
02:35:25,080 --> 02:35:32,280
I’m glad to hear your talk on PFAS. And sometime 
when you think about nutrition, people don’t tend  

1694
02:35:32,280 --> 02:35:39,300
to think about these two together and the built 
environment as well. At the National Cancer  

1695
02:35:39,300 --> 02:35:46,260
Institute, we have a program, which is now in the 
second year, where we have funded five large-scale  

1696
02:35:46,260 --> 02:35:51,600
prospective cohorts. This is called the…the 
Cohorts for Environmental Exposures and Cancer  

1697
02:35:51,600 --> 02:35:57,540
Risk. I’m leading that program and PFAS is one 
of the things that we are working on. These are  

1698
02:35:57,540 --> 02:36:04,620
large-scale efforts. We do have a pregnancy cohort 
as well. So, I agree with you that urine is a good  

1699
02:36:04,620 --> 02:36:09,840
sample and the PDMS wrist band and so forth—these 
are new tools that are being used to address these  

1700
02:36:09,840 --> 02:36:16,260
things. So, my question to you is, in terms 
of food contaminants, in addition to PFAS,  

1701
02:36:17,220 --> 02:36:22,080
there are other food contaminants that are 
chemicals and then we have additive effects.  

1702
02:36:22,859 --> 02:36:29,700
Do you…what are your thoughts about some of 
these in terms of obesity and other outcomes?

1703
02:36:29,700 --> 02:36:31,920
DR. JOSEPH BRAUN: Oh,  

1704
02:36:31,920 --> 02:36:38,040
I…I think in terms of the…I think one of 
the…one of the promising technologies out  

1705
02:36:38,040 --> 02:36:43,680
there right now are use of these high-resolution 
mass spec platforms to do non-targeted analysis,  

1706
02:36:44,760 --> 02:36:48,540
you know, to measure lots of things, 
whether it’s in urine or blood or…or serum.  

1707
02:36:49,439 --> 02:36:53,519
So that’s one route to go to get individual-level 
exposure. You know, you can do similar things with  

1708
02:36:53,520 --> 02:36:59,340
dust or air samples as well, or these…or these...for these 
wristbands. You know, the other…the other piece,  

1709
02:36:59,340 --> 02:37:03,540
and this is an FDA thing, crosses into FDA’s 
territory is, you know, food contaminants,  

1710
02:37:04,200 --> 02:37:09,300
and doing a better job monitoring those. And 
so, I…I think there’s…I think there’s a lot  

1711
02:37:09,300 --> 02:37:14,399
of promise in using nontargeted analysis, and 
then, you know, a lot of biostatistical methods  

1712
02:37:14,399 --> 02:37:20,280
have been developed to look at mixture effects, 
whether they’re antagonistic or agonistic or…or  

1713
02:37:21,600 --> 02:37:25,740
aggregate effects. And so, I think there’s, you 
know, the…the, we have caught up in that way,  

1714
02:37:25,740 --> 02:37:31,740
and in fact, there’s probably too many methods 
now, biostatistically speaking. And so I think,  

1715
02:37:31,740 --> 02:37:35,099
you know, we…we have a lot of tools now at our 
disposal to look at lots of these things. The…the  

1716
02:37:35,100 --> 02:37:38,580
key is going to be having the data…the…the 
large-scale data resources to do it with.

1717
02:37:38,580 --> 02:37:44,519
DR. CARRIE BRETON: I would, also 
just add that…I mean, I think we  

1718
02:37:44,520 --> 02:37:50,940
know metals are a good example of known…known 
contaminants in…in some of the food supply. And  

1719
02:37:51,780 --> 02:37:56,939
so while we can…I think…it’s a great effort 
to identify more contaminants that we don’t  

1720
02:37:56,939 --> 02:38:02,099
necessarily know of. We also could still 
push the envelope and do more work to  

1721
02:38:03,060 --> 02:38:09,180
reduce the levels of the things we do know 
about at, you know, either, especially maybe  

1722
02:38:09,180 --> 02:38:14,399
targeting some of these vulnerable windows 
of…of development, whether that’s adolescents,  

1723
02:38:14,399 --> 02:38:20,700
whether that’s, you know, fetal development. So, 
I…I think there’s room to grow there as well.

1724
02:38:20,700 --> 02:38:25,080
DR. SOMDAT MAHABIR: Wonderful. And…and some 
of the work related to the built environment,  

1725
02:38:25,080 --> 02:38:32,040
I think the California teachers study, just 
where you sit, I am also very much active…that’s,  

1726
02:38:32,580 --> 02:38:37,920
over 120,000 participants. They’re doing 
a lot of this fancy work as well,  

1727
02:38:37,920 --> 02:38:41,441
and I think it’s time for us to think 
how to integrate the food there as well.

1728
02:38:41,441 --> 02:38:45,780
DR. CARRIE BRETON: Yeah. The nice thing about the 
built…you know, a lot of the built environment  

1729
02:38:45,780 --> 02:38:51,660
is that you can at least start…as long as you 
gather residential history, and I would argue  

1730
02:38:51,660 --> 02:38:56,160
do it more than once, and then you can capture 
mobility, and then you can start to look across  

1731
02:38:56,160 --> 02:39:00,780
them. But then you have…that opens your door 
to so many of these things pretty easily.

1732
02:39:00,780 --> 02:39:13,800
DR. KRISTEN COOKSEY STOWERS:  I also just wanted make another shameless 
plug for equity considerations with this,  

1733
02:39:13,800 --> 02:39:18,660
and honestly, you know, the…the issues of toxins 
and these types of environmental exposures  

1734
02:39:18,660 --> 02:39:23,880
are a key motive…a motivator for me, having been 
interested in food swamp environments because  

1735
02:39:23,880 --> 02:39:30,479
they’re literally a spatial clustering in context 
to disproportionately impact certain populations  

1736
02:39:30,479 --> 02:39:36,839
than others. And so, I’m sure, you know, there’s 
tons of work, you know, and there’s seeds in place  

1737
02:39:36,840 --> 02:39:43,480
that would just advocate for paying attention to 
these issues as drivers of place-based inequities.

1738
02:39:43,480 --> 02:39:45,899
DR. SOMDAT MAHABIR: Yeah. I 
mean…and I can tell you for sure,  

1739
02:39:45,899 --> 02:39:49,859
in all of these large-scale studies, 
you have multiethnic population. I  

1740
02:39:49,859 --> 02:39:53,880
like to tell people we cannot study 
health disparities with just one type  

1741
02:39:53,880 --> 02:39:59,673
of individual…groups. Right? One population. 
It’s not going to work. Anyway, Dr. Manuela.

1742
02:39:59,673 --> 02:40:03,720
DR. MANUELA ORJUELA-GRIMM: Thank you. I 
mean, just a really phenomenal panel like  

1743
02:40:03,720 --> 02:40:11,520
everyone has said, and I just wanted to raise 
one…one topic that I…I think maybe alludes to  

1744
02:40:11,520 --> 02:40:18,240
some…some aspects that were being discussed, but 
that I think we haven’t discussed specifically,  

1745
02:40:18,240 --> 02:40:24,359
which is the aspect of food preparation, 
which I think touches on modifying exposure,  

1746
02:40:24,359 --> 02:40:29,160
and has to do with the built environment, the 
indoor environment, and I just wondered…and…and  

1747
02:40:30,600 --> 02:40:36,600
that also is an equity issue because there are…are 
lots of variations. It’s something that we’ve done  

1748
02:40:36,600 --> 02:40:45,840
work on, but I am…sort of stumbled onto exposures 
that we didn’t realize were happening because of  

1749
02:40:45,840 --> 02:40:54,060
collecting data on how…who was on 24-hour recalls 
and then realizing, “Oh, this is actually how  

1750
02:40:54,060 --> 02:40:59,819
they’re preparing it.” This is just opening 
up opportunities for thinking about exposure.  

1751
02:40:59,819 --> 02:41:06,420
I just wondered if the panel could talk about 
that element or the food utilization aspect.

1752
02:41:06,420 --> 02:41:11,340
DR. JOSEPH BRAUN: I…I mean the classic example, 
sort of, you know, the lead…lead-based cookware  

1753
02:41:11,340 --> 02:41:16,439
and…and pottery that’s used in Mexico or in 
other, you know, traditional South and Latin  

1754
02:41:16,439 --> 02:41:20,759
American cooking. That would be one example of 
that. I’m not aware of it for sort of…I mean, for  

1755
02:41:20,760 --> 02:41:24,600
other contaminants I guess could creep, you know, 
using plastics and products and things like that.  

1756
02:41:25,620 --> 02:41:30,479
So yeah, I think it…but I think you’re right. 
It…it…it adds in another layer of that…of…of  

1757
02:41:30,479 --> 02:41:35,040
where can…where we can be exposed to things 
and how that modifies diets and…and exposures.

1758
02:41:35,040 --> 02:41:41,160
DR. CARRIE BRETON:  

1759
02:41:41,160 --> 02:41:45,840
I guess I would just ask the question sort 
of back it—do we have a great instrument  

1760
02:41:45,840 --> 02:41:52,319
or tool for even assessing this, and it’s 
one to be so population specific to that?  

1761
02:41:54,660 --> 02:41:57,540
I…I would imagine we need to 
do some work on that area.

1762
02:41:57,540 --> 02:42:04,800
DR. KRISTEN COOKSEY STOWERS: I would  

1763
02:42:04,800 --> 02:42:06,420
just say…add, you know, going back to, 
[inaudible]. I would just go back to...well, you know,  

1764
02:42:06,420 --> 02:42:10,920
my comment with you just now about, like, 
clustering and like place/space drivers,  

1765
02:42:10,920 --> 02:42:14,399
and certain behaviors. So, there’s 
going to be literally geographic areas  

1766
02:42:14,399 --> 02:42:19,080
and neighborhoods that are more designed 
for, you know, cooking at home to start,  

1767
02:42:19,080 --> 02:42:25,559
let alone in…versus areas that are designed 
for becuase of the space and food environment  

1768
02:42:25,560 --> 02:42:32,820
and a variety of advertising and all type of 
stuff, it’s primed for a lot of eating out and,  

1769
02:42:34,260 --> 02:42:40,140
you know, restaurant food which, again, food 
supply issues, contamination. So again, these  

1770
02:42:40,140 --> 02:42:45,540
are these issues that are…been…have disparities 
and clustering that we should pay attention.

1771
02:42:45,540 --> 02:42:50,819
DR. KELLIE CASAVALE: Thank you. All right, we’re 
going to take one more question from online.  

1772
02:42:52,380 --> 02:42:58,620
And this question is, “Are there 
any specific recommendations for  

1773
02:42:58,620 --> 02:43:02,220
the nutrition support of pregnant 
women with chronic illnesses?  

1774
02:43:03,180 --> 02:43:08,819
OB-GYN units typically do not provide specific 
recommendations to these high-risk pregnant women,  

1775
02:43:08,819 --> 02:43:12,599
and the metabolic consequences 
for their babies are high.”  

1776
02:43:18,600 --> 02:43:20,156
Oh, yes, please go ahead, Marilee.

1777
02:43:20,156 --> 02:43:24,479
DR. MERILEE (MEREDITH) BROCKWAY: Okay. I can take 
a crack at that one. So, I think that speaks to  

1778
02:43:24,479 --> 02:43:30,359
kind of the fracturing of care for pregnant 
women with chronic diseases, because often,  

1779
02:43:30,359 --> 02:43:37,259
OB-GYNs don’t feel that they’re well-prepared to 
support pregnant women with a chronic disease with  

1780
02:43:37,260 --> 02:43:43,680
specific needs, and then their care provider who 
is going with the chronic disease care maybe isn’t  

1781
02:43:43,680 --> 02:43:48,359
as comfortable with the pregnancy aspect. 
So, there is definitely a disconnect with  

1782
02:43:48,359 --> 02:43:54,299
the nutritional requirements for specific needs. 
I think, kind of, the generic response is just  

1783
02:43:54,300 --> 02:44:00,180
to eat healthy and do as well as you can. Just 
linking back to the presentation that I talked  

1784
02:44:00,180 --> 02:44:07,200
about with chronic illnesses and lactation, a big 
issue was symptom management in pregnancy. So,  

1785
02:44:07,200 --> 02:44:12,120
if the symptoms weren’t well managed in pregnancy, 
those women were less likely to breastfeed. So,  

1786
02:44:12,120 --> 02:44:18,599
I think that’s also a concern that OB-GYNs don’t 
feel comfortable with…what…as well is that using  

1787
02:44:18,600 --> 02:44:22,020
medications to manage symptoms 
in such a high-risk population.  

1788
02:44:24,540 --> 02:44:27,000
So, I don’t have a good answer, essentially.

1789
02:44:27,000 --> 02:44:34,200
DR. CARRIE BRETON: I would…I would just add that, 
at least anecdotally, that…and some practitioners  

1790
02:44:34,200 --> 02:44:39,899
might refer out to like a nutritionist, 
but then access to nutritionists is…is not  

1791
02:44:39,899 --> 02:44:47,160
necessarily timely, or at least not right now. 
And…I mean…so…so then…and time is of the essence  

1792
02:44:47,160 --> 02:44:51,359
if you’re trying to intervene in a, you know, 
especially in…in a pregnancy. So I feel like,  

1793
02:44:51,359 --> 02:44:57,259
I mean, that’s a challenge that, I mean, I’m no 
expert in, but would be worth thinking about.

1794
02:44:57,260 --> 02:45:09,180
DR. KRISTEN COOKSEY STOWERS: [inaudible]  

1795
02:45:09,180 --> 02:45:14,760
The better integration between health care systems 
and food banking systems and these kinds of more  

1796
02:45:14,760 --> 02:45:19,980
systemic changes seem promising. Like there are a 
lot…there’s a lot more sort of discussion around  

1797
02:45:21,359 --> 02:45:26,099
health care systems, screening for social 
determinants of health, and things of that nature.  

1798
02:45:26,100 --> 02:45:32,220
And I think that this is a population where if we 
really invest on the intervention of the response  

1799
02:45:32,220 --> 02:45:36,960
to someone’s screening of a social determinant 
of health, like food insecure…like moving beyond,  

1800
02:45:36,960 --> 02:45:41,520
“Okay, where here’s a referral list to find your 
pantry,” right? Or “Here’s a list of social….”  

1801
02:45:41,520 --> 02:45:46,740
If we can get beyond that and really better 
understand like how to respond to the unique  

1802
02:45:46,740 --> 02:45:50,760
needs of that…that patient…that pregnant mother, 
what they tell us, they have an issue in the  

1803
02:45:50,760 --> 02:45:55,020
social determinants of health realm. It’s really 
promising in that way. Right now, the integration  

1804
02:45:55,020 --> 02:46:00,060
is there, but it’s just more like an FYI 
information sheet. We need to think more broadly  

1805
02:46:00,060 --> 02:46:03,600
about integrating from a social determinants, 
structural determinants of health standpoint.

1806
02:46:03,600 --> 02:46:06,960
DR. SOMDAT MAHABIR: Thank you all 
very much. If there is no final  

1807
02:46:06,960 --> 02:46:12,180
question from the audience here, I would 
like to call this session a close. So,  

1808
02:46:12,180 --> 02:46:18,060
thank you all, speakers, and those who 
ask questions. Thanks a lot. Lunch time.  

1809
02:46:18,060 --> 02:46:21,300
[Applause]

1810
02:46:21,300 --> 02:46:26,280
I think we need to be back 
here, 1:40. Have a great lunch.

1811
02:46:26,280 --> 02:46:36,240
MS. KIMBERLEA GIBBS:  Welcome to session four, which is Next Steps 
for Multigenerational Nutrition Studies. I’m  

1812
02:46:36,240 --> 02:46:42,120
Lieutenant Commander Gibbs, and I work 
in NICHD. I’ll be your moderator for this  

1813
02:46:42,120 --> 02:46:47,340
session. I’d like to welcome and introduce 
Dr. Janina Galler from Harvard University,  

1814
02:46:47,340 --> 02:46:52,740
who will present on Lessons Learned in 
Multigenerational Nutrition Studies. Ma’am.

1815
02:46:52,740 --> 02:47:07,500
DR. JANINA GALLER:   Hi. I wanted to first, thank you all for inviting 
me to this very exciting meeting and challenging  

1816
02:47:07,500 --> 02:47:16,800
meeting, and I’m going to, today, summarize 
my own work on multigenerational malnutrition,  

1817
02:47:17,340 --> 02:47:23,040
and…and end with the challenges and opportunities  

1818
02:47:23,040 --> 02:47:27,180
that the meeting for the past 2 days 
has presented us with in that light.  

1819
02:47:32,399 --> 02:47:35,399
This is an overview of what 
I will be talking about. I’m  

1820
02:47:35,399 --> 02:47:38,099
going to go through very quickly 
because of the time limitations.  

1821
02:47:40,140 --> 02:47:45,660
One out of three children globally under the 
age of 5 years suffers from malnutrition,  

1822
02:47:45,660 --> 02:47:52,439
and I’m going to be talking today about a 
very long-term multigenerational study which  

1823
02:47:52,439 --> 02:47:59,759
has been carried on now for over 50 years. The 
classic definition, according to UNICEF and WHO,  

1824
02:48:00,899 --> 02:48:08,580
of malnutrition is the combination of stunting 
and wasting, and roughly 30% of the global child  

1825
02:48:08,580 --> 02:48:13,859
population under the age of 5 suffers from this 
condition. And as you can see, the definition,  

1826
02:48:13,859 --> 02:48:20,799
strictly speaking, is under two standard 
deviations below median weight for age. The  

1827
02:48:21,600 --> 02:48:28,800
prevalence of undernutrition in young children 
globally has declined, but is nowhere near what  

1828
02:48:28,800 --> 02:48:34,680
our original goals were for the beginning 
of the century. As you can see, in 2020,  

1829
02:48:34,680 --> 02:48:45,720
20.8% of children were still impacted, and most 
of these lived in sub-Saharan Africa and in Asia.  

1830
02:48:46,859 --> 02:48:53,700
And again, this is a distribution of the 
global…of the percentages of children  

1831
02:48:53,700 --> 02:48:59,220
globally, and the prevalence of childhood 
malnutrition. And again, you can see, where  

1832
02:48:59,220 --> 02:49:05,220
the major concentrations are, but malnutrition 
continues to occur in all parts of the world.  

1833
02:49:06,600 --> 02:49:13,080
In the U.S., although we don’t specifically 
identify an issue with undernutrition, even  

1834
02:49:13,080 --> 02:49:19,500
the New York Times identified the extreme problem 
that we have in this country with hunger. Hunger  

1835
02:49:19,500 --> 02:49:26,880
which carries on for any sustained period of time 
can, of course, result in overt undernutrition.  

1836
02:49:27,720 --> 02:49:34,979
In 2020, food insecurity and undernutrition 
impacted one…one of four—and by some studies, one  

1837
02:49:34,979 --> 02:49:40,919
of five—U.S. children; approximately 16 million 
children have been impacted. And I think what  

1838
02:49:40,920 --> 02:49:48,600
we all cannot forget, and since this is my first 
meeting since the end of the COVID crisis, during  

1839
02:49:48,600 --> 02:49:54,660
the COVID pandemic, these figures escalated, and 
we really don’t have a present count of what the  

1840
02:49:54,660 --> 02:50:00,840
prevalence is in the United States or elsewhere, 
but we can only assume that’s substantially worse.  

1841
02:50:03,000 --> 02:50:08,760
I would like to draw your attention 
to a slide that many others in this  

1842
02:50:08,760 --> 02:50:14,700
meeting have…have presented similarly, talking 
about critical periods of brain development,  

1843
02:50:14,700 --> 02:50:22,139
and what we understand this to be are periods when 
the brain grows most…most rapidly and is therefore  

1844
02:50:22,140 --> 02:50:29,100
most vulnerable to nutritional insult. What 
is important about this is that it’s generally  

1845
02:50:29,100 --> 02:50:36,600
been accepted that if malnutrition in humans 
occurs anywhere between the second trimester of  

1846
02:50:36,600 --> 02:50:42,899
pregnancy and 2 years of age, the findings are 
generally thought to be irreversible. I think  

1847
02:50:42,899 --> 02:50:49,139
that’s an important point, and I will carry 
out this theme throughout my presentation.  

1848
02:50:49,979 --> 02:50:55,559
Also, it’s important in thinking about 
translational studies to look at what  

1849
02:50:55,560 --> 02:51:00,359
rapid periods of brain growth are, because 
they are different in different species  

1850
02:51:00,359 --> 02:51:05,979
and it’s important to have, obviously, a 
comparable period of rapid brain growth.  

1851
02:51:06,899 --> 02:51:14,759
The Barbados Nutrition Study is a study that Frank 
Ramsey and I actually started together in 1973,  

1852
02:51:14,760 --> 02:51:25,080
but it was based on a cohort of children that were 
first identified by him in 1967 to 1972. In 1966,  

1853
02:51:25,080 --> 02:51:31,200
Barbados became an independent country. For 
those of you who have not been in Barbados, it’s  

1854
02:51:31,200 --> 02:51:38,519
a tiny little island in the Eastern Caribbean, 
and it’s approximately 15 by 20 miles big, and  

1855
02:51:38,520 --> 02:51:48,121
it has a population of about 285,000 individuals, 
most of whom are of lower-middle-class background.  

1856
02:51:48,660 --> 02:51:53,220
There are very few people in upper class 
backgrounds, although this is now changing.  

1857
02:51:54,300 --> 02:52:01,380
In 1966, when the…country became independent, the 
first Prime Minister recognized that malnutrition  

1858
02:52:01,380 --> 02:52:11,399
was one of the major childhood issues on the 
island, and he identified and declared the need  

1859
02:52:11,399 --> 02:52:18,660
to tackle this particular problem, and identified 
Frank Ramsey, my colleague from Barbados,  

1860
02:52:19,380 --> 02:52:23,220
to establish a study to track these children.  

1861
02:52:24,720 --> 02:52:35,700
So, in 1973, when I joined the study part B, we…we 
actually started to not just collect the children,  

1862
02:52:35,700 --> 02:52:41,939
but also to think of this in terms of a study, and 
the study participants actually include children  

1863
02:52:41,939 --> 02:52:47,040
with exposure to grade two, grade three protein 
energy malnutrition restricted to the first year  

1864
02:52:47,040 --> 02:52:54,899
of life, so all of the kids had normal birth 
weights, and early childhood histories that  

1865
02:52:54,899 --> 02:53:02,040
you know, had them with Apgars of greater than 8. 
They had no birth complications, they had regular  

1866
02:53:02,040 --> 02:53:08,519
prenatal care, and no childhood encephalopathic 
events. Controls were from the same neighborhoods  

1867
02:53:08,520 --> 02:53:14,520
and classrooms, and they were matched by 
age, gender, and handedness to the PEM group,  

1868
02:53:15,240 --> 02:53:22,620
and we, as you can see, highlighted in red the 
children were exposed only for a year or less,  

1869
02:53:22,620 --> 02:53:29,939
early in their lives, and thereafter, were 
involved in a nationally supported intervention  

1870
02:53:29,939 --> 02:53:36,540
program, which provided nutrition education, 
nutrition supplementation, a stipulation program,  

1871
02:53:36,540 --> 02:53:42,359
which was roughly two to three mornings a 
week that was available to the children.  

1872
02:53:42,359 --> 02:53:47,580
They had all the routine health care through 
the national nutrition center until 12 years  

1873
02:53:47,580 --> 02:53:56,340
of age and had regular visits by home…by public 
health care givers. So, these kids were heavily  

1874
02:53:56,340 --> 02:54:01,440
engaged in what we considered at that point to 
be the state-of-the-art intervention program,  

1875
02:54:02,100 --> 02:54:07,260
and…and therefore were documented as 
never suffering from malnutrition again.  

1876
02:54:10,080 --> 02:54:14,819
We collected these children, and these children 
are now roughly 55 years of age, and we’ve  

1877
02:54:14,819 --> 02:54:22,799
tracked them throughout their lives, and we also 
have extensive data on their mothers, and also  

1878
02:54:22,800 --> 02:54:31,380
on their offspring who were…are now roughly 30 
years of age, ranging from 6 to 30 years of age.  

1879
02:54:33,359 --> 02:54:39,779
The etiology of childhood malnutrition 
in Barbados in 1966 really arose from  

1880
02:54:39,779 --> 02:54:47,160
several…for several reasons, some of which 
were addressed previously about why children  

1881
02:54:47,160 --> 02:54:52,500
develop malnutrition. First of all, there was 
no government policy supporting breastfeeding  

1882
02:54:52,500 --> 02:54:58,260
or child…a child leave policy, so mothers 
had to return to work almost immediately.  

1883
02:54:59,760 --> 02:55:06,840
Socioeconomic conditions in a sugar-rearing 
country are very tenuous. If sugar markets are  

1884
02:55:06,840 --> 02:55:12,840
high, there are no issues, and if sugar markets 
are low, there is poverty on the island. So,  

1885
02:55:12,840 --> 02:55:18,600
just to give you an example, in 1967, when…when 
the data collection was started on the sample,  

1886
02:55:18,600 --> 02:55:27,240
80% of the income of the family went to food and 
housing, so that’s very little wiggle room if…you  

1887
02:55:27,240 --> 02:55:33,179
know, if there are issues in terms of the cost 
and availability of sugar globally. There were  

1888
02:55:33,180 --> 02:55:38,040
major cultural factors that played a role. There 
is…continues to be a practice of early weaning  

1889
02:55:38,040 --> 02:55:45,060
to bush teas, and also Barbados is a matriarchal 
society, so it’s highly dependent on the women as  

1890
02:55:45,060 --> 02:55:53,460
the providers in that society, and male support 
is not necessarily available. And, finally,  

1891
02:55:53,460 --> 02:56:00,359
health conditions played an important role. We 
all know about the important role of infections,  

1892
02:56:00,359 --> 02:56:07,439
including diarrhea and measles as a precipitance 
in a marginally nourished…population. And also,  

1893
02:56:07,439 --> 02:56:13,799
as was mentioned earlier, maternal depression also 
leads to the early cessation of breastfeeding,  

1894
02:56:13,800 --> 02:56:20,279
and results in malnutrition in populations, 
and was certainly a factor here. On this slide,  

1895
02:56:20,279 --> 02:56:25,500
I hope to show a popular Calypso song at 
the time, which talks about another cultural  

1896
02:56:25,500 --> 02:56:31,380
factor. “Endorse de cou cou and gi me another 
share, dem children en wuk no way.” And again,  

1897
02:56:31,380 --> 02:56:37,319
it’s the demand by the man of the household to 
get the cou because the children are not working,  

1898
02:56:37,319 --> 02:56:43,380
and so again, the focus and the priority would 
not have been on the children. This is a summary  

1899
02:56:43,380 --> 02:56:51,479
of our multidisciplinary research focus in this 
in the Barbados nutrition study, and seven waves  

1900
02:56:51,479 --> 02:56:56,099
of data collection that allowed us to collect a 
wide range of data on mental health and behavioral  

1901
02:56:56,100 --> 02:57:04,920
outcomes, cognitive functions, a comprehensive 
assessment of medical health and ecology factors,  

1902
02:57:04,920 --> 02:57:12,660
epigenetics, and more recently, neuroimaging, 
including qEEG and… and NIRS on this population.  

1903
02:57:14,160 --> 02:57:20,399
This is a summary of 50 years of 
work in this population in one slide,  

1904
02:57:21,000 --> 02:57:29,640
and basically, what I want to emphasize here 
is that there are changes across the board,  

1905
02:57:29,640 --> 02:57:37,020
but the really important changes that we observed 
were a fourfold increase in attention deficits in  

1906
02:57:37,020 --> 02:57:42,899
the population—and I’m mentioning this because, 
at the time we started to work in Barbados,  

1907
02:57:42,899 --> 02:57:49,979
attention deficit disorder was only recognized 
as being a Western disorder. So, ours was the  

1908
02:57:49,979 --> 02:57:57,000
first paper published in the Journal of Child and 
Adolescent Psychiatry that talked about attention  

1909
02:57:57,000 --> 02:58:03,660
deficits in a developing country. So, I think 
that’s an extremely important point. And also,  

1910
02:58:03,660 --> 02:58:09,540
we didn’t come in with a preconceived notion. 
What we did was we created this to identify  

1911
02:58:09,540 --> 02:58:15,960
the…this issue. We had a classroom questionnaire, 
which describes lots of behaviors that would be  

1912
02:58:15,960 --> 02:58:23,399
typical of children of this age and basically, 
you know, used principal components analysis to  

1913
02:58:23,399 --> 02:58:30,960
reduce the data, and what emerged was what looked 
for…for the likes of…of anything else, looked like  

1914
02:58:30,960 --> 02:58:37,080
the attention deficit disorders that were also 
seen in this country. The percentages were such  

1915
02:58:37,080 --> 02:58:44,640
that 15% of the control and 60% of the children 
with histories of malnutrition in the first year  

1916
02:58:44,640 --> 02:58:50,640
of life had an attention deficit disorder. We 
replicated this finding, and I’ll describe some  

1917
02:58:50,640 --> 02:58:57,120
of the replications many times, at least five 
times over the…life span of the individual,  

1918
02:58:57,120 --> 02:59:05,160
and the attention deficit disorders continued 
into adulthood. There were also conduct problems,  

1919
02:59:05,160 --> 02:59:11,939
maladaptive personality traits, depressive 
symptoms, and in the area of neuropsychological  

1920
02:59:11,939 --> 02:59:20,219
testing, IQ deficits for school performance and 
lots of changes in relationship to the executive  

1921
02:59:20,220 --> 02:59:26,760
functioning of these children. An important 
point in the long-term longitudinal study is  

1922
02:59:26,760 --> 02:59:33,540
that we recently have documented a severalfold 
rise in accelerated cognitive decline in the  

1923
02:59:33,540 --> 02:59:41,340
population at age 55. And it is closely linked to 
the early diagnosis at age 5 of attention deficits  

1924
02:59:41,340 --> 02:59:48,000
in the population. So, having a diagnosis in this 
setting of an attention deficit disorders predict  

1925
02:59:48,000 --> 02:59:51,779
cognitive decline at a very 
early stage in this population.  

1926
02:59:53,220 --> 02:59:59,100
Again, there were also health concerns; 
diabetes was elevated, especially in females;  

1927
02:59:59,100 --> 03:00:05,161
metabolic syndrome; and a decline in social 
status, which…which…which was very significant.  

1928
03:00:06,840 --> 03:00:13,260
In the next generation, in generation two, 
and…and I’m only going to report 16 to 30,  

1929
03:00:13,260 --> 03:00:18,359
so there the…the data are directly comparable 
with the adults in the previous slide.  

1930
03:00:18,359 --> 03:00:25,740
We also reported attention deficit disorders, 
personality traits being altered, depressive  

1931
03:00:25,740 --> 03:00:32,160
symptoms being…being altered. What we did not 
diagnose at this particular stage of development  

1932
03:00:32,160 --> 03:00:39,779
was any change in BMI or metabolic syndrome, but 
again, they are only 30, and we don’t know yet,  

1933
03:00:39,779 --> 03:00:46,740
you know, what…what will emerge at a later 
point in time. So, what it appears is that  

1934
03:00:47,279 --> 03:00:52,559
some of the behavioral findings that we 
observed in the first generation do carry over,  

1935
03:00:52,560 --> 03:01:00,420
even with carefully adjusting for not only 
socioeconomic factors, age, and sex, but also  

1936
03:01:00,420 --> 03:01:06,779
a range of extra nutritional factors that we have 
documented carefully in this population. Because  

1937
03:01:06,779 --> 03:01:12,899
of my background as a child psychiatrist, we also 
collected extensive data on maternal depression  

1938
03:01:12,899 --> 03:01:19,019
and child maltreatment. So, all the findings that 
you see reported will have been adjusted for those  

1939
03:01:19,020 --> 03:01:27,600
other early adversities, as well. So, this is a 
summary of the slides, specifically one of our  

1940
03:01:28,560 --> 03:01:35,880
slides on the CAARS, which is the Conner’s 
Adult Attention Deficit Rating Scale, and  

1941
03:01:35,880 --> 03:01:40,740
this is, actually a study that was conducted 
intergenerationally by one of my daughters,  

1942
03:01:42,000 --> 03:01:50,460
[inaudible], and basically, what you can see 
here is that the darker bars represent the  

1943
03:01:50,460 --> 03:01:57,779
first generation, and the lighter bars represent 
the second generation. And you can see comparable  

1944
03:01:58,439 --> 03:02:06,000
differences, again, in…in the various categories 
of, especially inattentiveness and DSM-IV  

1945
03:02:06,660 --> 03:02:17,099
ADHD symptoms, between the…the various 
groups. Now, to supplement a lot of this work,  

1946
03:02:17,819 --> 03:02:25,080
which originally started out really as a study 
of behavior cognition, brain, and health,  

1947
03:02:26,340 --> 03:02:32,520
as newer technologies evolved and were 
available, we became very multidisciplinary.  

1948
03:02:32,520 --> 03:02:40,200
One of our important collaborations have been with 
[inaudible] at…at Mount Sinai, with whom we’ve  

1949
03:02:40,200 --> 03:02:44,519
been working on epigenetics effects. And 
I…again, I just want to summarize very quickly,  

1950
03:02:44,520 --> 03:02:52,380
this is a paper we had published in Biological 
Psychiatry showing that in both G1 and G2, there  

1951
03:02:52,380 --> 03:02:58,620
were many methylation changes. I think what’s 
important about this paper in particular is that  

1952
03:02:58,620 --> 03:03:06,180
to…to our knowledge, it was the first paper that 
actually correlated these changes with attention  

1953
03:03:06,180 --> 03:03:13,380
deficits and IQ deficits in the population. So, 
there was a significant correlation between the  

1954
03:03:13,380 --> 03:03:19,680
genes that we saw across the board. A particularly 
interesting gene…let me start on the next slide,  

1955
03:03:19,680 --> 03:03:28,320
which is specifically a slide talking about the 
74 G2 offspring. Some of the important genes  

1956
03:03:29,760 --> 03:03:37,319
were the DPPA5, which is a very potent 
developmental gene that has to do with early  

1957
03:03:37,319 --> 03:03:45,299
brain development, a HOXB gene, HLA-DPA, but what 
was really exciting for us was to see that, there  

1958
03:03:45,300 --> 03:03:53,220
were…was significant enrichment in 183 impacted 
genes that relate to immune function. So, this  

1959
03:03:53,220 --> 03:03:57,660
was, a really interesting finding, and something 
that we’re continuing to work on at this point.  

1960
03:03:59,040 --> 03:04:04,620
Now, there are other aspects of our 
research having to do with neuroimaging,  

1961
03:04:04,620 --> 03:04:10,979
which is a more recent focus, NIRS, which we’ve 
been conducting in this population, as well, but  

1962
03:04:10,979 --> 03:04:16,679
what I want to spend a few minutes talking about 
our…is our translational research. In addition  

1963
03:04:16,680 --> 03:04:23,939
to the…the work, the 50-year Barbados Nutrition 
Study, we also conduct animal…studies of animal  

1964
03:04:23,939 --> 03:04:32,040
models of…of protein malnutrition, and the first 
series of studies that I was involved in concerned  

1965
03:04:32,040 --> 03:04:36,660
a colony that I inherited from [inaudible] Stewart 
at the London School of Tropical Hygiene and  

1966
03:04:36,660 --> 03:04:44,340
Medicine. In 1973, I flew over a colony of rats 
with 20 generations of malnutrition from London,  

1967
03:04:44,340 --> 03:04:52,260
where they lived for a number of years at MIT, and 
because the opportunity of…of following this very  

1968
03:04:52,260 --> 03:05:00,180
important colony transgenerationally. And the 
bottom line to that series of studies is that  

1969
03:05:00,720 --> 03:05:08,399
there were multiple changes in…in a range 
of behaviors, and whereas females seem to  

1970
03:05:08,399 --> 03:05:15,120
recover within two generations, it took males 
four generations to recover, so there was  

1971
03:05:15,120 --> 03:05:23,279
definitely a gender difference, and also talks of 
the importance of studying both genders in…in all  

1972
03:05:23,279 --> 03:05:29,340
these area studies. I mention that because it’s 
not unusual in rodent studies in particular to  

1973
03:05:29,340 --> 03:05:36,540
focus on male rats, and I know NIH has tried to 
encourage everybody to…to also look at females,  

1974
03:05:36,540 --> 03:05:41,460
but it’s not done as often because of the 
varying complexities, and also being able to…to  

1975
03:05:41,460 --> 03:05:49,500
look at them outside of hormonal changes, but we 
clearly see cognitive differences in that study.  

1976
03:05:49,500 --> 03:05:55,979
So, just a couple of quick findings that 
corroborate the attentional findings that we  

1977
03:05:55,979 --> 03:06:04,919
have found in our youth population. This is a.. a 
2000–2019 study that we published, looking at the  

1978
03:06:04,920 --> 03:06:14,760
acts of glucose uptake in the prefrontal cortex, 
and what you see here is that…that executive  

1979
03:06:14,760 --> 03:06:21,899
functions are selectively impacted in the brain 
of rodents that have been exposed to both prenatal  

1980
03:06:21,899 --> 03:06:32,879
and longer-term malnutrition. And this paper 
by one of our more junior faculty in 2020 was  

1981
03:06:32,880 --> 03:06:40,500
particularly exciting because what it shows is 
that it isn’t that there are deficits, it’s the  

1982
03:06:40,500 --> 03:06:45,779
fact that the brain actually reorganizes itself, 
very much like what happens to the heart after  

1983
03:06:45,779 --> 03:06:53,099
a myocardial infarction. It actually develops 
alternate pathways, and he was able to…document  

1984
03:06:53,100 --> 03:06:59,340
that NR rodents, whereas the normal pathway during 
sustained attention paths would have been through  

1985
03:06:59,340 --> 03:07:05,279
the prefrontal cortex, which was not operating in 
the previously malnourished rodents. They were,  

1986
03:07:05,279 --> 03:07:11,160
however, using a pathway through the right 
hippocampus, the right hippocampal formation, and  

1987
03:07:11,160 --> 03:07:18,180
were able to achieve the same outcome, which is 
extremely interesting and, you know…and may have,  

1988
03:07:18,180 --> 03:07:23,520
you know, further translational opportunities as 
we think about intervention. Okay, so let me just  

1989
03:07:23,520 --> 03:07:30,900
summarize some of our key findings real quickly, 
and then move on to…to the…to our larger overview.  

1990
03:07:32,279 --> 03:07:39,300
Our work in Barbados, again, which my 
collaboration with Frank Ramsey until his death,  

1991
03:07:39,300 --> 03:07:45,300
which was roughly 15 years ago. As a result of 
our work, we were able to eliminate childhood  

1992
03:07:45,300 --> 03:07:52,500
malnutrition completely from Barbados by 1980. 
Frank Ramsey was knighted for that work, and,  

1993
03:07:53,880 --> 03:07:59,040
you know, it’s probably the greatest achievement 
from my perspective of…of my work in Barbados.  

1994
03:08:00,000 --> 03:08:05,640
Number two, despite a 12-year national 
intervention program, the BNS shows that  

1995
03:08:05,640 --> 03:08:11,040
early malnutrition limited to the first year 
of life still impacts mental health, cognitive,  

1996
03:08:11,040 --> 03:08:17,279
and health outcomes over the life span and across 
generations. These findings parallel our early  

1997
03:08:17,279 --> 03:08:22,859
intergenerational studies in a rodent model, and 
I think this is extremely important, and…and it  

1998
03:08:22,859 --> 03:08:28,740
goes back to that slide I showed you of critical 
timing of brain development. But what is really  

1999
03:08:28,740 --> 03:08:34,439
interesting is the transgenerational impact. 
Attention deficits and impaired executive control  

2000
03:08:34,439 --> 03:08:40,019
are probably the most pervasive effects, even 
after controlling for extra nutritional factors.  

2001
03:08:41,580 --> 03:08:48,960
Importantly, we have a series of papers on 
this. The attentional deficits lead to poor  

2002
03:08:48,960 --> 03:08:53,939
performance at age 11, when there’s a national 
examination called the Common Entrance Exam,  

2003
03:08:53,939 --> 03:08:58,439
which dictates whether you go to an…an 
academic high school or a trade school.  

2004
03:08:59,760 --> 03:09:07,620
That attention deficits at age 5 predict how 
the child does at age 11 on this national exam,  

2005
03:09:07,620 --> 03:09:13,559
which in turn predicts what the social status 
and economic earning potential is at age 4.  

2006
03:09:14,220 --> 03:09:22,020
So, there’s an incredible impact of the history 
of early childhood malnutrition, and resulting  

2007
03:09:22,020 --> 03:09:26,460
in a decline in earning potential and social 
status, which only gets worse over generations.  

2008
03:09:27,960 --> 03:09:33,120
I talked previously about the epigenetic changes. 
What I’m excited about is the fact that it allows  

2009
03:09:33,120 --> 03:09:37,200
us to think about potentially reversible 
effects, that’s what so exciting, I think,  

2010
03:09:37,200 --> 03:09:43,139
for all of us here, in that particular 
area, we have not worked on microbiomes,  

2011
03:09:43,140 --> 03:09:48,420
and as I shared with some of you yesterday, it’s 
partially because of cultural restrictions in  

2012
03:09:48,420 --> 03:09:53,220
Barbados we can’t collect those…those 
samples as much as we’d like to.  

2013
03:09:54,779 --> 03:10:01,679
Finally, multidisciplinary research really 
can contribute to…to the early identification  

2014
03:10:01,680 --> 03:10:06,720
of high risk and resilient individuals. I 
would like to emphasize that even though  

2015
03:10:06,720 --> 03:10:14,460
we do see 60% of children in childhood—and up 
to 45% in adulthood—with attention deficits,  

2016
03:10:16,200 --> 03:10:22,260
you still have 40 to 50% of the population 
that did not have these outcomes,  

2017
03:10:22,260 --> 03:10:28,979
these adverse outcomes, and I think that one 
thing our translational research, focus has…has  

2018
03:10:28,979 --> 03:10:34,559
led us to is this whole concept of looking at 
resilience in these individuals as a way of  

2019
03:10:34,560 --> 03:10:43,560
identifying ways to culturally and appropriately 
intervene. So, the malnutrition-poverty cycle.  

2020
03:10:44,160 --> 03:10:52,620
My mentor in the 19…’60s, actually, from 1968 
until his death in 1973 was Herbert Birch.  

2021
03:10:54,000 --> 03:11:00,720
This is a…a very well-known figure, which I have 
modified over time, which he published as…as a  

2022
03:11:00,720 --> 03:11:07,740
theoretical figure. Because I think what…what you 
all may not realize is that until the late 1960s,  

2023
03:11:07,740 --> 03:11:16,559
all children globally with malnutrition were 
dying, and it was not until UNICEF contributed  

2024
03:11:16,560 --> 03:11:23,939
for oral rehydration therapy that these children 
finally began to survive, and the question of  

2025
03:11:23,939 --> 03:11:30,299
quality of life became a significant issue, and it 
was at that time that this particular version of  

2026
03:11:30,300 --> 03:11:35,460
this slide was published. What we have done over 
the past 50 years is basically fill in the pieces  

2027
03:11:35,460 --> 03:11:43,200
of this entire picture in terms of trying to look 
at how the generational process continues. And  

2028
03:11:44,640 --> 03:11:50,460
if you look under the word “malnutrition” and 
a couple of other places, I have indicated  

2029
03:11:50,460 --> 03:11:54,720
areas where I think, you know, we have a 
lot of opportunity in terms of further…  

2030
03:11:55,500 --> 03:12:02,279
further research studies, specifically looking 
at mechanisms underlying how these effects occur  

2031
03:12:02,279 --> 03:12:10,500
and…and how we understand the whole concept of 
resilience. So, I’d like to take the next few  

2032
03:12:10,500 --> 03:12:17,100
minutes to talk about what I’ve heard the last 
couple of days and how it relates to my own  

2033
03:12:17,100 --> 03:12:25,620
experience with…with having worked for 50 years 
in…in several multigenerational venues. So, again,  

2034
03:12:25,620 --> 03:12:30,779
you know, you may want to just take this home and, 
you know, read it, or…or not read it, as the case  

2035
03:12:30,779 --> 03:12:37,139
may be, but I think we all talked for the last 2 
days about how important multigenerational studies  

2036
03:12:37,140 --> 03:12:43,741
of nutrition are in terms of looking at health 
outcomes of children and into the next generation.  

2037
03:12:44,939 --> 03:12:51,000
Again, one of the important take-home messages 
from the BNS, from the Barbados Nutrition Study,  

2038
03:12:51,000 --> 03:12:58,560
is that it’s not only limited to the prenatal 
period. And…and again you know, even Barker many  

2039
03:12:58,560 --> 03:13:03,420
times, you know, referred to the fact that, 
that early postnatal environment is equally  

2040
03:13:03,420 --> 03:13:09,779
important. It really is the entire period from the 
second trimester to age 2. It’s not just…just the  

2041
03:13:09,779 --> 03:13:18,059
prenatal period. Everyone talks about the need 
to standardize methods, which…which we all agree  

2042
03:13:18,060 --> 03:13:23,399
would be necessary. Many of the very important 
studies, including studies such as the Dutch  

2043
03:13:23,399 --> 03:13:29,639
famine and some of the other major famine studies, 
have a major problem in that the children were  

2044
03:13:29,640 --> 03:13:34,500
never examined at the time, and we don’t really 
have precise measures of their nutritional status  

2045
03:13:34,500 --> 03:13:41,460
at the time that they experienced, the history 
of malnutrition. It’s really by history, and  

2046
03:13:41,460 --> 03:13:48,960
by history of exposure, so that was the reason, in 
part, for undertaking this particular study, which  

2047
03:13:48,960 --> 03:13:56,340
is a prospective study. So, standardizing methods 
is…is very important, including measures of other  

2048
03:13:56,939 --> 03:14:04,319
factors that can influence individuals when 
they’re exposed to these issues is very important,  

2049
03:14:04,319 --> 03:14:10,439
so you have to also look at…at other aspects of 
the environment. We heard a lot this morning about  

2050
03:14:10,439 --> 03:14:15,540
the broader context of shared environments, 
neighborhoods, and, most importantly to me,  

2051
03:14:15,540 --> 03:14:22,080
public policy. I’ve spent a lot of time trying 
to convince a lot of people that this is all very  

2052
03:14:22,080 --> 03:14:28,680
meaningful, and we need money to support research 
in this area and to support interventions in this  

2053
03:14:28,680 --> 03:14:36,960
area. Do dads matter? Another very important and 
salient topic, some of our early rodent studies  

2054
03:14:36,960 --> 03:14:42,960
show that yes, they do, and we’ve heard a lot 
of really exciting work about yes, they do,  

2055
03:14:42,960 --> 03:14:47,760
you know, from…from several researchers in 
the last 2 days. We need to consider both  

2056
03:14:47,760 --> 03:14:54,540
paternal and maternal contributions as much as 
possible, and both genetically and otherwise.  

2057
03:14:55,800 --> 03:15:00,000
The interaction between nutrition and other 
exposures, including food contaminants, is…is  

2058
03:15:00,000 --> 03:15:08,340
another very important area. Food can mitigate 
the effects of…of certain food contaminants,  

2059
03:15:08,340 --> 03:15:16,859
of proper nutrition, but also the contamination of 
undernutrition of other exposures is problematic.  

2060
03:15:16,859 --> 03:15:21,960
Translational research can identify underlying 
mechanisms and generate hypotheses because  

2061
03:15:21,960 --> 03:15:29,760
testing in human populations…without our rat 
work, I wouldn’t have known where to go. It…it  

2062
03:15:29,760 --> 03:15:34,979
really would have been a fishing expedition, 
and so, you know, again, I think it’s vitally  

2063
03:15:34,979 --> 03:15:39,179
important that we support this work, you know, 
that…that you really need to go from the lab,  

2064
03:15:40,680 --> 03:15:45,660
you know, to…to…to the larger population and the 
larger community, which has always been NICHD’s  

2065
03:15:45,660 --> 03:15:52,500
focus from the get-go. Okay, interdisciplinary 
approach is critical. Again, as we get more and  

2066
03:15:52,500 --> 03:16:00,060
more complex and have more and more technology, we 
have to work in a multidisciplinary way. You know,  

2067
03:16:00,060 --> 03:16:06,180
I was one of the first people who really pulled 
in people from a wide array of backgrounds, mostly  

2068
03:16:06,180 --> 03:16:11,640
because of, you know just wanting to expand and 
extend, you know, the breadth of our… of our work.  

2069
03:16:11,640 --> 03:16:17,700
But now, with new technology, we can really do 
this effectively. We have to think about targeted  

2070
03:16:17,700 --> 03:16:23,399
intervention programs that are actionable. This 
has to be a priority. Prevention is the biggest  

2071
03:16:23,399 --> 03:16:28,500
dimension, but I don’t know that we’re going to 
be able to prevent undernutrition—especially,  

2072
03:16:28,500 --> 03:16:35,939
you know, with the COVID experience the last 3 
years, it’s out of our control. But we therefore  

2073
03:16:35,939 --> 03:16:40,979
need to think about certainly early interventions, 
but I thought Dr. Barker’s, you know, attention  

2074
03:16:40,979 --> 03:16:47,519
earlier today to opportunities during adolescence 
are well taken. In 2015, you know, I participated  

2075
03:16:47,520 --> 03:16:54,120
in an NICHD conference on the interaction 
between early nutrition and inflammatory factors,  

2076
03:16:54,120 --> 03:17:01,979
and we actually published a paper on adolescence 
in Pediatrics, and there’s really no better time  

2077
03:17:01,979 --> 03:17:07,139
to think of that, intervention for so many 
reasons. And finally, there is the need,  

2078
03:17:07,140 --> 03:17:14,460
the ongoing, ever-present need to change public 
policy. We need to support…we have the opportunity  

2079
03:17:14,460 --> 03:17:20,520
to support analysis of previously collected data. 
There is a lot of data that has been collected  

2080
03:17:20,520 --> 03:17:27,540
multigenerationally, long term that has just been 
left out there without support, and I think it  

2081
03:17:27,540 --> 03:17:33,120
would be…this is the time to call it back in, 
I think we can make use…I’m not saying that you  

2082
03:17:33,120 --> 03:17:38,340
should not be doing new studies, but I think you 
can also make use of existing data. And finally,  

2083
03:17:38,340 --> 03:17:44,520
I’m thrilled to see people here, you know, with 
K awards you know, at…at junior stages of their  

2084
03:17:44,520 --> 03:17:49,500
careers because that’s the way to the future 
is to support the next generation. Finally,  

2085
03:17:49,500 --> 03:17:54,420
I’d like to, you know…this is just a quick list 
of all the horrible things that can happen in  

2086
03:17:54,420 --> 03:18:00,600
multigenerational research. I thought I would…I 
was originally going to talk about lemons to  

2087
03:18:00,600 --> 03:18:04,979
lemonade, but I’m actually doing the reverse 
right now. So, these, these are things that  

2088
03:18:04,979 --> 03:18:09,660
have happened to me, and everyone else who’s 
worked in this type of research, and yet we  

2089
03:18:09,660 --> 03:18:15,479
continue with it because of how important it is. 
There are attrition factors. The great thing about  

2090
03:18:15,479 --> 03:18:22,859
the BNS is that we know where 80 to 90% of our 
population is: 60% of them remain in Barbados,  

2091
03:18:22,859 --> 03:18:28,920
the rest of them live in Toronto, for the most 
part. So, it’s been…that’s been a positive thing,  

2092
03:18:28,920 --> 03:18:35,279
but not… not something a lot of people have 
benefited from. Not only is there an issue with  

2093
03:18:35,279 --> 03:18:41,700
methodology and unique, more precise measures, 
but the other big headache is the fact that  

2094
03:18:41,700 --> 03:18:47,700
measures change over time. You have different gold 
standards over time. And so, we have had to…in…in  

2095
03:18:48,420 --> 03:18:54,120
our multiple waves of data collection, frequently 
have had to retest using the old measure,  

2096
03:18:54,120 --> 03:18:58,680
and also include the new measures to be able to 
see how they compare in the very same populations,  

2097
03:18:58,680 --> 03:19:03,540
and you’re obligated to do that, but it’s a 
headache. It’s one of the lovely things about  

2098
03:19:03,540 --> 03:19:08,880
doing, you know, long-term and multigenerational 
research. Changing data analytic approaches,  

2099
03:19:09,420 --> 03:19:15,359
how we deal with missing data, mixed models, all 
of this is important. I’ve, you know, had to learn  

2100
03:19:15,359 --> 03:19:21,059
the SAS inside out to be able to…to deal with some 
of the, data issues. Missing data’s a very big  

2101
03:19:21,060 --> 03:19:27,300
piece of it. We find, sometimes, retrospectively 
that we forgot to collect data on certain people,  

2102
03:19:27,300 --> 03:19:31,979
or they didn’t show up for a particular phase 
of the study because they had a beauty parlor  

2103
03:19:31,979 --> 03:19:37,200
appointment. I had that most recently, you 
know, when we doing our, our NIRS qEEG work.  

2104
03:19:38,760 --> 03:19:44,939
Another interesting and important challenge is 
the multidisciplinary approaches because you as a  

2105
03:19:44,939 --> 03:19:50,040
researcher have to learn new languages, so that’s 
a real push sometimes. You know, I was sharing  

2106
03:19:50,040 --> 03:19:55,380
with some of my colleagues yesterday that, you 
know, when I started to work with my very dear,  

2107
03:19:55,380 --> 03:20:00,660
wonderful neuro anatomist and learned that they 
were using [inaudible] to publish, you know,  

2108
03:20:00,660 --> 03:20:07,200
these highly quoted papers, and here we are, you 
know, being told that an N of, you know, roughly  

2109
03:20:07,200 --> 03:20:12,120
550 individuals is too small because there are all 
these studies out there, you heard it yesterday,  

2110
03:20:12,120 --> 03:20:20,819
you know, going up to 60,000. You know, it’s 
learning those languages, not only about ends, but  

2111
03:20:20,819 --> 03:20:25,679
strategy, and kind of talk to one another, and so 
on, has…has always been an interesting challenge.  

2112
03:20:25,680 --> 03:20:33,060
Leadership plans and staff retention are critical. 
You know, I’ve heard a number…I have a dear  

2113
03:20:33,060 --> 03:20:40,680
colleague who had an office next to mine, had a 
50-year study, and passed away without you know,  

2114
03:20:40,680 --> 03:20:47,580
leaving someone to…to take over. And NIH usually 
requires when you’re doing grants to identify,  

2115
03:20:47,580 --> 03:20:54,240
you know, who the next person in line is, but not 
everybody takes that seriously. Staff retention,  

2116
03:20:55,080 --> 03:21:00,479
is a very important piece in a longitudinal 
study. I have been blessed in Barbados with people  

2117
03:21:00,479 --> 03:21:08,099
who worked on the study in the 1960s and…and 
continued until their death, basically, you know,  

2118
03:21:08,100 --> 03:21:14,040
on the project, but that’s not usual, and staff 
turnover is a nightmare. IRB challenges people.  

2119
03:21:14,040 --> 03:21:20,760
IRB challenges with maintaining long-term data is 
an insurmountable headache, and I am very thankful  

2120
03:21:20,760 --> 03:21:26,580
for the IRB at Mass General for not giving me 
a hard time about this. Changes in government  

2121
03:21:26,580 --> 03:21:33,660
policy. I can remember in 1980, when…when Reagan, 
took over and I was a U.S. Senate Fellow at that  

2122
03:21:33,660 --> 03:21:40,200
time, that suddenly we went from a country, you 
know, under Kennedy, etc., you know, including  

2123
03:21:41,580 --> 03:21:47,760
focused on nutrition of children in this country, 
to being told that there is no nutrition issue  

2124
03:21:47,760 --> 03:21:52,140
anymore. You know, government policy changes all 
the time, and when you’re working in developing  

2125
03:21:52,140 --> 03:21:58,380
countries, or working in communities that are 
at…at greater risk, government policy is a  

2126
03:21:58,380 --> 03:22:03,359
very big deal. So, I’d just like to conclude 
with my last three comments, which have…are  

2127
03:22:04,020 --> 03:22:09,960
a direct statement to NIH, which are, number one, 
please remember, you’re talking about and thinking  

2128
03:22:09,960 --> 03:22:16,500
about multigeneration studies. The lack of 
continuity and funding leads to subject attrition  

2129
03:22:16,500 --> 03:22:23,939
and loss of staff, and irrevocable changes to a 
longitudinal study. It can’t happen [inaudible].  

2130
03:22:23,939 --> 03:22:31,439
Stable funding is urgently needed, and the usual 
models for NIH of the 5-year limit and the cap. I  

2131
03:22:31,439 --> 03:22:36,419
mean, we never used to have a cap, now there’s a 
cap. It’s really problematic when you’re talking  

2132
03:22:36,420 --> 03:22:42,420
about not only long-term studies, but studies 
that should be translational and should be  

2133
03:22:42,420 --> 03:22:48,240
multidisciplinary. These are…are…it’s, it’s 
very hard to get your epigenetic colleagues  

2134
03:22:48,240 --> 03:22:55,019
to do anything under $250,000 a year, I 
can tell you. And finally, grant review.  

2135
03:22:56,399 --> 03:23:01,080
I mean, you do this all the time, but 
these multigeneration studies really have  

2136
03:23:01,080 --> 03:23:06,779
the need for special review process because the 
ordinary, you know…and…and again, I’ve been on  

2137
03:23:06,779 --> 03:23:15,059
over 100 study sections, I’ve chaired three of 
them. We don’t know anything about, you know,  

2138
03:23:15,060 --> 03:23:20,220
multigenerational, you know, research, and you 
need…you need a group of reviewers who really can  

2139
03:23:21,180 --> 03:23:25,380
you know, decipher this, etc. Anyway, that’s 
it for today, and thank you very much.

2140
03:23:25,380 --> 03:23:36,914
MS. KIMBERLEA GIBBS:   Thank you so much, Dr. Galler. 
I invite you to come sit, and—

2141
03:23:36,915 --> 03:23:37,804
DR. JANINA GALLER: Okay.

2142
03:23:37,804 --> 03:23:41,760
MS. KIMBERLEA GIBBS: We’ll have a quick 
question and answer session. To our audience,  

2143
03:23:41,760 --> 03:23:46,380
if you have any questions and you’re online, 
please drop them in the question and answer  

2144
03:23:46,380 --> 03:23:53,279
box. I’d like to thank also Dr. Vargas for helping 
me to navigate and prioritize the questions. So,  

2145
03:23:53,279 --> 03:23:57,540
let’s get started. We can start in the room 
and then we’ll transfer over to our virtual  

2146
03:23:57,540 --> 03:24:02,201
audience. Does anyone have any questions 
or comments for her? Yes, of course.

2147
03:24:02,201 --> 03:24:05,819
DR. ASHLEY VARGAS: Okay. Ashley Vargas. 
So, Dr. Galler, I can’t talk and see you,  

2148
03:24:05,819 --> 03:24:10,620
but fantastic presentation. I have a hard 
question for you, which maybe is no surprise.  

2149
03:24:11,520 --> 03:24:16,859
We’ve heard a lot about what we know, what we 
don’t know, we need more observational studies,  

2150
03:24:16,859 --> 03:24:23,040
we need more intervention. If you had to pick 
one…or, can you make an argument for why we  

2151
03:24:23,040 --> 03:24:26,519
need to do more intervention research, 
are we ready for that? Even policy level,  

2152
03:24:26,520 --> 03:24:31,140
individual level, whatever, or do 
you really think the best bang for  

2153
03:24:31,140 --> 03:24:41,800
the buck is in more observational and 
more discovery science at this stage?

2154
03:24:41,800 --> 03:24:46,380
DR. JANINA GALLER: So, I don’t think you really 
have to make that choice in the sense that,  

2155
03:24:46,920 --> 03:24:51,660
you know, I really think that 
well planned intervention and,  

2156
03:24:53,279 --> 03:24:56,819
you know, really have…you 
have the ability to capture a  

2157
03:24:58,260 --> 03:25:04,020
lot of this information by both looking at 
intervened and…and non-intervened individuals so,  

2158
03:25:04,020 --> 03:25:09,000
you know, that’s an opportunity to be able to, to 
look here. But I really think that, at this point  

2159
03:25:09,000 --> 03:25:15,180
in time, I think the best bang for the buck is 
to begin to think about, you know, research that  

2160
03:25:15,180 --> 03:25:20,700
also drives you know, intervention [inaudible]. 
I think that we…we need to be able to do that,  

2161
03:25:20,700 --> 03:25:25,739
and I think we should be able to document all of 
the various dimensions that have been talked about  

2162
03:25:25,739 --> 03:25:35,673
the last 2 days, you know, by doing that. Whether 
it leads to public policy—I would hope as such.

2163
03:25:35,673 --> 03:25:42,120
AUDIENCE MEMBER:  

2164
03:25:42,120 --> 03:25:44,680
Yes. Sure. [inaudible]  

2165
03:25:46,979 --> 03:25:52,799
Yeah. I was glad to hear about Barbados study. 
I am from the part of the world. It is really  

2166
03:25:52,800 --> 03:25:59,880
that malnutrition has been eliminated in Barbados? 
What about undernutrition? Barbados is a part of  

2167
03:26:00,479 --> 03:26:06,719
CARICOM, as you may know, is the group of 
nations, and they have a big problem with  

2168
03:26:06,720 --> 03:26:13,739
undernutrition. I don’t know about malnutrition. 
And this varies by ethnicity. they…You know,  

2169
03:26:13,739 --> 03:26:19,355
CARICOM countries are very multi…multiethnic, 
so can you talk about the dimensions of that?

2170
03:26:19,355 --> 03:26:24,600
DR. JANINA GALLER: Yeah. So, Barbados is a 
little unusual in that it’s 99% homogenous.  

2171
03:26:24,600 --> 03:26:33,420
It’s…it’s…it’s not like Trinidad or even Jamaica 
in terms of…of…of diversity. It’s not particularly  

2172
03:26:33,420 --> 03:26:42,960
diverse. And 1% are White, and 99% are of 
African ORIGIN, North…North African…origin, so,  

2173
03:26:43,560 --> 03:26:49,680
we have less diversity than in other places. 
There is not a problem with undernutrition at  

2174
03:26:49,680 --> 03:26:54,479
this point. The problem in Barbados is…is what we 
have seen globally, which is with overnutrition,  

2175
03:26:54,479 --> 03:27:02,279
at this point. So, we actually have a…a study 
funded by a Toronto foundation at this very  

2176
03:27:02,279 --> 03:27:08,700
moment, you know, look…looking specifically 
at…at the impact of not only overnutrition,  

2177
03:27:08,700 --> 03:27:15,359
but the over-representation in our population 
of…of overnutrition. So, as you know,  

2178
03:27:15,359 --> 03:27:23,099
the flipside of malnutrition is that when people 
recover from malnutrition, they frequently enter  

2179
03:27:23,100 --> 03:27:27,960
a phase of overnutrition, which is exactly what 
we’re seeing on the island at this point. Now,  

2180
03:27:27,960 --> 03:27:35,279
in CARICOM countries, there continues to be an 
issue, indeed, with undernutrition and not so  

2181
03:27:35,279 --> 03:27:41,580
much frank malnutrition, but with undernutrition, 
but Barbados has been spared. Barbados actually  

2182
03:27:41,580 --> 03:27:48,660
is 58 of 189 countries, and it’s actually, 
believe it or not, much to my consternation,  

2183
03:27:48,660 --> 03:27:54,479
considered an upper-income country, which means 
that are not eligible for any funding from  

2184
03:27:54,479 --> 03:28:00,120
Fogarty. It has been the bane of my existence. 
It’s really been very, very difficult because,  

2185
03:28:00,120 --> 03:28:04,439
on the one hand, we…we are classified as a 
developing country. On the other hand, they’re  

2186
03:28:04,439 --> 03:28:10,500
seen as an upper-income country. So, its health 
statistics in terms of mortality, morbidity,  

2187
03:28:11,160 --> 03:28:15,599
maternal…mortality, in particular, are really 
excellent, comparable to the U.S. population.

2188
03:28:15,600 --> 03:28:21,000
MS. KIMBERLEA GIBBS: Thank you, and we’ll 
move to our last question. Dr. Buffington?

2189
03:28:21,000 --> 03:28:24,359
DR. SHELLY BUFFINGTON: Dr. Galler, excellent 
talk. And so, I remember from our conversation  

2190
03:28:24,359 --> 03:28:28,739
yesterday, and then you showing the parameters 
here on your chart, that you first tried to do  

2191
03:28:28,739 --> 03:28:33,779
these EEGs, and kind of the larger neuro 
measurements in the ’70s, and I see this  

2192
03:28:33,779 --> 03:28:39,179
40-year gap, but I saw another check mark in, 
you know, the 2010s, right? And so, were…how  

2193
03:28:39,180 --> 03:28:44,220
were you able to change the cultural perception 
of those tests, and, obviously coming from an  

2194
03:28:44,220 --> 03:28:48,420
interest in microbiome [inaudible], they’re not 
really willing to consider giving fecal samples  

2195
03:28:48,420 --> 03:28:53,460
so it can be analyzed. Is there any sort of, I 
guess, lesson to be learned, you know, in your  

2196
03:28:53,460 --> 03:28:57,779
experience with the EEGs that could be ultimately 
applied toward, you know, fecal sampling?

2197
03:28:57,779 --> 03:29:01,859
DR. JANINA GALLER: That…that’s a really 
interesting you know, perspective, and…and…and  

2198
03:29:01,859 --> 03:29:09,719
a great question. So, what we were talking about 
is the fact that some of the mothers, early on,  

2199
03:29:09,720 --> 03:29:20,040
when we did EEGs of the children in 1977—they 
were 5–11 years of age—actually told us that their  

2200
03:29:20,040 --> 03:29:25,019
children developed, you know, significant migraine 
headaches a result, you know, they had seizures,  

2201
03:29:25,020 --> 03:29:30,720
you know, resulting from the EEGs. There were 
a lot of cultural taboos, you know, insofar  

2202
03:29:30,720 --> 03:29:35,640
as the work. I…I think what’s changed things is 
the fact that, you know, exposure to, you know,  

2203
03:29:35,640 --> 03:29:44,220
the internet, media in general, we provided…we 
have maintained a terrific communication with  

2204
03:29:44,220 --> 03:29:48,960
the community, you know, educating them when 
we publish papers. They are not only given  

2205
03:29:48,960 --> 03:29:54,180
copies of…of the papers, but we actually talk 
about it. I give public lectures on the island,  

2206
03:29:54,180 --> 03:30:00,000
so we really familiarized them with…with the 
work, and I think that has helped to…for them  

2207
03:30:00,000 --> 03:30:09,359
to overcome. And when we did the most recent, you 
know, redo of the qEEG we…we unfortunately don’t  

2208
03:30:09,359 --> 03:30:15,179
have any really good MRI units on the island, and 
it’s too complicated to take them off the island,  

2209
03:30:15,180 --> 03:30:20,820
so we can’t…we can’t do that. But they were…they 
were more than willing to…to participate with us.  

2210
03:30:21,420 --> 03:30:26,340
And…and the answer is yes. I mean, I think that 
over time, they may be more open to…to things  

2211
03:30:26,340 --> 03:30:32,700
like microbiome studies as more scientific studies 
on the island are…are published about the benefits  

2212
03:30:32,700 --> 03:30:37,679
of it. You know, many of the people, not even the 
physicians, you know, listen in on University of  

2213
03:30:37,680 --> 03:30:44,460
Miami Medical Center Grand Rounds, and, you know, 
people are at a very different place in education.  

2214
03:30:44,460 --> 03:30:49,680
I thought someone was going to, in fact, comment 
on why the CAARS scores were so much higher the  

2215
03:30:49,680 --> 03:30:55,260
second generation, and the theory behind that 
is that the kids all grew up being exposed to  

2216
03:30:55,260 --> 03:31:00,600
computers and iPads. They…they are each given a 
computer when they go to school; they have one.  

2217
03:31:00,600 --> 03:31:06,660
So you know…and again, it’s known that CAARS and 
attention deficits are higher when kids are using,  

2218
03:31:06,660 --> 03:31:12,120
you know, this type of medium. So, I…I think 
there’s an opportunity, but we’re really not there  

2219
03:31:12,120 --> 03:31:17,399
at this point. In fact, we can’t even collect 
fecal samples, you know, for…for epigenetics.  

2220
03:31:17,399 --> 03:31:23,279
They won’t…that’s something else that’s not 
culturally allowed. We can do tape recordings,  

2221
03:31:23,279 --> 03:31:27,599
let’s say, of interviews that I have with 
individuals. But I think that the best solution,  

2222
03:31:27,600 --> 03:31:34,140
really, is not only their personal education, but 
also retaining…and again, a very important piece  

2223
03:31:34,140 --> 03:31:39,239
of the multigenerational long-term study, you 
have to maintain a connection with the population,  

2224
03:31:39,239 --> 03:31:43,979
and they have to feel that they are the 
priority and you’re not simply there in a  

2225
03:31:43,979 --> 03:31:48,719
colonial way collecting data from them, and not 
giving them…nothing in return. Unfortunately,  

2226
03:31:48,720 --> 03:31:53,857
that has been the case in other studies, 
but not…you know, not in ours, so, yeah.

2227
03:31:53,857 --> 03:31:57,899
MS. KIMBERLEA GIBBS: Wow. So, you 
are getting kudos in the…from,  

2228
03:31:57,899 --> 03:32:03,120
from the virtual audience. I’ll read it. This 
is a splendid talk, thank you so much for it,  

2229
03:32:03,120 --> 03:32:09,660
and I’ll echo that sentiment. Thank you so much. 
We are going to take a 5-minute break in the room.  

2230
03:32:09,660 --> 03:32:15,300
[Applause]

2231
03:32:15,300 --> 03:32:22,640
We’ll take a 5-minute break in the room and we’ll 
invite our virtual audience to join us at 3:40.

2232
03:32:30,000 --> 03:32:38,580
DR. ASHLEY VARGAS:   So, for the virtual audience, us in the room, 
we’re going to do a breakout session and report  

2233
03:32:38,580 --> 03:32:42,960
back to you all at 3:40, so that’s why we’re 
asking you to come back. For those of you in  

2234
03:32:42,960 --> 03:32:47,279
the room, please hold tight as we work towards 
getting you together in groups. Thank you,  

2235
03:32:47,279 --> 03:32:53,219
again. Okay, everyone, Ashley Vargas, NICHD. 
We’re here to report out from the wonderful  

2236
03:32:53,220 --> 03:32:57,720
breakout sessions we’ve had in-house here 
with our speakers, and we want to first thank  

2237
03:32:57,720 --> 03:33:02,220
the speakers for their time and expertise 
today, and over the past 2 days, really,  

2238
03:33:02,220 --> 03:33:08,220
and this all comes to a culmination, hopefully, in 
these breakout sessions. So, I’m going to start,  

2239
03:33:08,220 --> 03:33:12,720
and then I’ll have my colleagues who also helped 
to moderate the breakout sessions introduce  

2240
03:33:12,720 --> 03:33:18,899
themselves briefly before they do their report 
out. So, one of the first questions we asked were:  

2241
03:33:18,899 --> 03:33:24,700
What are the overarching scientific questions 
that are needed…oops, can’t see that word. To  

2242
03:33:28,500 --> 03:33:31,260
advance, we’ll go with, the field of 
multi[generational effects related]  

2243
03:33:32,160 --> 03:33:39,300
to nutrition forward? So in the first breakout 
group, we had a couple points. So, the first was  

2244
03:33:39,300 --> 03:33:44,460
improving the understanding of parents, including 
fathers, at the biological level and behavioral  

2245
03:33:44,460 --> 03:33:51,060
levels, and they…the speakers specifically 
emphasize the effects moderation of parents  

2246
03:33:51,060 --> 03:33:57,840
on child health outcomes and making sure we 
capture both mothers and fathers. There was  

2247
03:33:57,840 --> 03:34:04,080
also an interest in integrating multiple levels, 
so I think we saw a great break to…yesterday about  

2248
03:34:05,819 --> 03:34:11,819
more biologically focused individual-level things, 
and today we focused on family and multilevel  

2249
03:34:11,819 --> 03:34:16,500
interventions. And so, the speakers emphasized 
that we needed to bring all of those together  

2250
03:34:17,160 --> 03:34:24,599
and develop meaningful understanding of how 
nutrition affects individuals and families  

2251
03:34:24,600 --> 03:34:31,260
and societies across generations—so, a big 
task. We also were high…we also were advised  

2252
03:34:31,260 --> 03:34:36,660
to improve and develop methods that really allow 
us to identify those critical windows. And so,  

2253
03:34:36,660 --> 03:34:42,540
we know some of them, but those vary, probably, 
on an individual situation, and we need to develop  

2254
03:34:42,540 --> 03:34:51,180
better methods for improving our ability to 
measure those. And then the very last one is…I…I  

2255
03:34:51,180 --> 03:34:54,899
almost captured this verbatim, so you can see. 
We have a speaker who would really love to see  

2256
03:34:54,899 --> 03:35:01,019
a model where you can effectively layer all these 
comorbidities into a score. And so, we know that  

2257
03:35:01,020 --> 03:35:03,899
there are things like the child vulnerability 
score, and there are some scores out there,  

2258
03:35:03,899 --> 03:35:09,239
but we wanted to emphasize the opportunities we 
have to improve on that with a growing body of  

2259
03:35:09,239 --> 03:35:13,859
knowledge. So, with that, we also had a couple 
other breakout sessions on this same question,  

2260
03:35:13,859 --> 03:35:18,899
so I’m going to turn this over to my colleague, 
Dr. Kellie Casavale from FDA, to take over.

2261
03:35:18,899 --> 03:35:23,819
DR. KELLIE CASAVALE: All right, thank you, Ashley. 
I’m Kellie Casavale, senior science advisor for  

2262
03:35:23,819 --> 03:35:33,840
nutrition at FDA CFSAN, and if we can go onto the 
next slide…oh, it’s on…oh, it’s me? Okay. So, we  

2263
03:35:33,840 --> 03:35:42,359
did hear some of the similar things that speakers 
in Ashley’s group described, and so multiple  

2264
03:35:42,359 --> 03:35:48,839
speakers mentioned a number of things, but we also 
had a lot of variety across the group. And so,  

2265
03:35:48,840 --> 03:35:56,760
one of the topics that speakers mentioned were 
also related to the role of the male contribution,  

2266
03:35:56,760 --> 03:36:03,120
but also, when addressing dyads, to consider not 
just the mothers, also the mother and father, as  

2267
03:36:03,120 --> 03:36:10,080
well as including both societal as well biological 
influences that are influenced by fathers.  

2268
03:36:11,460 --> 03:36:20,520
There also was some discussion around preclinical 
models really with a focus on the persistent  

2269
03:36:20,520 --> 03:36:27,660
effects that may not have been…been teased out, 
or paid attention to in the past, and really  

2270
03:36:27,660 --> 03:36:33,840
thinking about those persistent effects from 
the perspective of the timing of those pieces.  

2271
03:36:35,580 --> 03:36:43,439
So, there was also comments around work being 
done on girls, but less being done with boys,  

2272
03:36:43,979 --> 03:36:51,419
and to understand timing and reproductive health, 
to go beyond just discussing reproductive health,  

2273
03:36:51,420 --> 03:36:58,020
focusing just on females, and to focus 
on both boys and girls because of the  

2274
03:36:58,020 --> 03:37:06,660
generations of parents. We talked a lot about 
reversible effects underlying the models,  

2275
03:37:06,660 --> 03:37:12,960
and so the speakers were very interested in 
understanding more and studying more about,  

2276
03:37:14,160 --> 03:37:20,639
you know, there are insults and deficits that 
occur early in life, but…that have effects,  

2277
03:37:20,640 --> 03:37:26,640
but are there things that can happen in other 
stages of life that are positive and can help  

2278
03:37:26,640 --> 03:37:34,800
to reverse or address those early insults 
or deficits? There was points made around  

2279
03:37:34,800 --> 03:37:42,540
in adolescence as being an unappreciated 
window in this regard on how nutrition  

2280
03:37:42,540 --> 03:37:49,500
and other inventions—interventions—can be an 
opportunity. In addition, school-aged children  

2281
03:37:49,500 --> 03:37:57,239
were thought to be more ignored, with the focus 
currently being more on preschool and adolescence,  

2282
03:37:57,239 --> 03:38:03,059
so the data is not really captured kind of 
consistently across those early life stages.  

2283
03:38:04,680 --> 03:38:10,380
Similar to the comment that Ashley heard, 
there was some interest in scales or severity  

2284
03:38:10,380 --> 03:38:15,420
of acute malnutrition and how that differs 
from other events that influence outcomes.  

2285
03:38:16,920 --> 03:38:22,739
There was a comment regarding nutrient and 
toxic interactions being part of studies,  

2286
03:38:22,739 --> 03:38:28,139
not just one side or the other. And then, how 
do we learn…use machine learning to integrate  

2287
03:38:28,140 --> 03:38:34,380
all of the -omics of this, of what we have learned 
from past studies to use them as predictors and to  

2288
03:38:34,380 --> 03:38:41,939
identify those critical windows? And this is our 
second slide. There’s interest in having a proof  

2289
03:38:41,939 --> 03:38:48,779
of concept for key exposures, the quote-unquote 
“sledgehammers,” noting that through the  

2290
03:38:48,779 --> 03:38:55,500
discussions in this workshop, there’s a…a lot of 
information being focused on prenatal, F1 and F2,  

2291
03:38:55,500 --> 03:39:01,859
but not the proof of concept for what those key 
sledgehammer exposures are multigenerationally.  

2292
03:39:02,640 --> 03:39:09,060
And then disentangling the genetic from those 
environmental effects using studies that may use  

2293
03:39:09,060 --> 03:39:15,000
twin studies and then other methodologies that can 
help to really identify the…environmental effects.  

2294
03:39:18,180 --> 03:39:22,800
There’s interest in really 
looking at natural experiments,  

2295
03:39:22,800 --> 03:39:28,739
and so, understanding that our world is not 
static, that things are constantly changing,  

2296
03:39:28,739 --> 03:39:34,080
and we are constantly living in natural 
experiments, and so how can we learn from  

2297
03:39:34,080 --> 03:39:41,640
those situations about what has worked and what 
has not worked, including what has worked at the  

2298
03:39:41,640 --> 03:39:47,820
population and policy levels versus more focused 
individual intervention–level interventions?  

2299
03:39:50,640 --> 03:39:56,880
And so, really, there was additional comments 
about focusing on the most vulnerable, but having  

2300
03:39:56,880 --> 03:40:01,500
those most vulnerable really being the ones that 
are vulnerable to the multigenerational effects.  

2301
03:40:02,939 --> 03:40:09,299
There’s interest in studies around the vehicle of 
transmission of those multigenerational effects.  

2302
03:40:10,680 --> 03:40:17,700
And then focusing on historical issues. What are 
the current issues, and how are they a result of  

2303
03:40:17,700 --> 03:40:25,319
historical issues? And in this regard, there were 
comments around distinguishing between issues that  

2304
03:40:25,319 --> 03:40:32,880
are social versus biological drivers, and the 
interactions of those, specifically over time,  

2305
03:40:32,880 --> 03:40:41,279
historically leading to the current point 
in time. As an example of this, evolution of  

2306
03:40:41,279 --> 03:40:47,399
food marketing, food environments, food cost, 
and how those impacts have changed over time,  

2307
03:40:47,399 --> 03:40:54,599
and over generations, and are not static. It was 
also described that when it comes to studying  

2308
03:40:54,600 --> 03:41:04,020
disparities and…and…inequalities, that there’s a 
lack of theoretical bases and frameworks that can  

2309
03:41:04,020 --> 03:41:12,060
be used to help identify drivers across studies. 
And I believe that was it, all of that loveliness.

2310
03:41:12,060 --> 03:41:20,581
MS. KIMBERLEA GIBBS: Okay, we’ll turn it over to 
Dr. Sonia…or Dr. Montessa Mitchell to take over.

2311
03:41:24,859 --> 03:41:32,880
DR. MONTESSA MITCHELL: So…That’s very low. So, 
we proposed the second question, which was:  

2312
03:41:32,880 --> 03:41:36,660
What do you now think are the most immediate 
actions that should be taken over the next 5  

2313
03:41:36,660 --> 03:41:42,720
years to move multigenerational effects related 
to nutrition forward? And with our group,  

2314
03:41:42,720 --> 03:41:50,160
we really heard that there is a desire 
to discover which investment stages of  

2315
03:41:50,160 --> 03:41:55,920
life yield the highest return—so, where do we get 
the best bang for our buck, as was said earlier?  

2316
03:41:56,819 --> 03:42:04,439
And they want to identify [audio drop]. So, to 
wrap it up, the best way to assess nutritional  

2317
03:42:04,439 --> 03:42:10,679
status over time is still a struggle, and we need 
to look at what would be most useful in advancing  

2318
03:42:10,680 --> 03:42:17,640
this area, as well as ideal and…consistent 
ways to talk to each other to make it easier,  

2319
03:42:17,640 --> 03:42:23,279
too. There was also interest in exploring 
innovative markers of nutritional status that are  

2320
03:42:23,279 --> 03:42:28,920
relevant for capturing multigenerational effects, 
as well. And so, I’ll go ahead and turn it over.

2321
03:42:28,920 --> 03:42:40,620
DR. SONIA ARTEAGA:  Hello. I’m Sonia Arteaga. I’m cohort lead with the 
ECHO Program. So, first I want to say thank you,  

2322
03:42:40,620 --> 03:42:44,880
because this was really fun. It was fast 
and furious, and the ideas were flowing,  

2323
03:42:44,880 --> 03:42:51,899
so that was great, so thank you. Okay, so…so, 
what did we talk about in the room? So,  

2324
03:42:51,899 --> 03:42:56,160
one of the first things that came up was have 
a…a PACE for multigenerational cohorts—and no  

2325
03:42:56,160 --> 03:43:00,479
one could remember what PACE stands for. I don’t 
know if anyone now can remember what PACE stands  

2326
03:43:00,479 --> 03:43:06,000
for, but it’s birth epigenetic cohorts, I 
believe, at NIEHS, and the idea is getting  

2327
03:43:06,000 --> 03:43:09,180
all of these multigenerational cohorts 
together, and how many do we have? Like,  

2328
03:43:09,180 --> 03:43:13,979
do an…an assessment of that. We also talked 
about proof of concept with sledgehammer,  

2329
03:43:13,979 --> 03:43:19,500
so that came up in the first group, too. 
The importance of standardizing biospecimen  

2330
03:43:19,500 --> 03:43:25,380
collection, and then providing recommendations 
for other groups to also do very similar things.  

2331
03:43:26,460 --> 03:43:31,560
Similar to PACE, finding existing cohorts 
that have kids and recruiting the parents,  

2332
03:43:32,520 --> 03:43:37,201
and this comes up later, also. It’s this idea 
of let’s find those cohorts that have…that  

2333
03:43:39,239 --> 03:43:45,840
have been ongoing, assess the participants, then 
assess the grandparent and assess the child,  

2334
03:43:45,840 --> 03:43:50,220
so you get this three-gen effect. 
And some examples include GUTS,  

2335
03:43:50,220 --> 03:43:56,640
which is…I don’t…Growing Up Today Study 
from the Nurse’s Health Study, and then  

2336
03:43:56,640 --> 03:44:01,201
the children’s centers at NIEHS could…those 
are examples of where some of these…we…we  

2337
03:44:02,700 --> 03:44:08,819
could recruit the children and assess them and 
their parents and children. The idea was brought  

2338
03:44:08,819 --> 03:44:13,739
up: Can we do something with electronic health 
records to construct a multigenerational cohort?  

2339
03:44:14,640 --> 03:44:21,420
So, that’s another idea. How about supplements to 
existing original cohort studies to do extra work?  

2340
03:44:22,680 --> 03:44:28,859
We talked about standardizing protocols and 
this idea of going backwards and forwards,  

2341
03:44:28,859 --> 03:44:32,040
like I mentioned—participant, 
grandmother or grandfather,  

2342
03:44:32,040 --> 03:44:37,380
and then the child. The idea of developing 
an equity-based framework for nutrition  

2343
03:44:37,380 --> 03:44:43,500
research—that really is multigenerational 
in…in its work, so taking time into account.  

2344
03:44:44,520 --> 03:44:49,439
Then I…The idea of assessing what is the 
low-hanging fruit for community-based work? What  

2345
03:44:49,439 --> 03:44:55,319
is really important for the community? And that 
can help us with [inaudible]

2346
03:44:55,319 --> 03:45:02,040
making the…the results more meaningful and 
impactful for participants. We also talked  

2347
03:45:02,040 --> 03:45:07,560
about developing predictive biomarker…biomarkers 
to identify highest…the highest-risk individuals.  

2348
03:45:08,640 --> 03:45:15,960
The idea of looking at links between early 
nutrition and attention challenges in children.  

2349
03:45:17,220 --> 03:45:21,660
Recruiting more diverse participants—recruiting, 
retaining, engaging more diverse participants.  

2350
03:45:21,660 --> 03:45:28,680
Leveraging other epigenetic clocks, how 
to integrate predictive information. Also,  

2351
03:45:28,680 --> 03:45:35,040
this idea came up of geographical mobility 
and assessing the impact on nutrition. How  

2352
03:45:35,040 --> 03:45:41,040
do we capture it? So, how do we develop a tool 
to do that? So, it’s the idea that someone’s  

2353
03:45:41,040 --> 03:45:45,120
parents came from Mexico, then they moved to 
California, and now their kids are in Maryland,  

2354
03:45:45,120 --> 03:45:49,559
or something like that. How do we assess 
those contextual geographical variables?  

2355
03:45:50,640 --> 03:45:54,600
Also, talking to methodologists 
to develop better methods,  

2356
03:45:54,600 --> 03:46:00,420
especially when it comes to interventions. 
More opportunities for us to get together,  

2357
03:46:00,420 --> 03:46:09,600
not…for different disciplines. So, this gets 
to the intersectoral collaborations, so, how do  

2358
03:46:09,600 --> 03:46:11,263
you allow behavioral and social sciences to 
all come together. Looking at…outcomes that  

2359
03:46:11,263 --> 03:46:16,500
are just…that are just [inaudible], but also other 
outcomes that are of…of interest to participants,  

2360
03:46:17,040 --> 03:46:24,239
such as quality of life, education. The idea, 
also, of doing these…we do multisite trials  

2361
03:46:24,239 --> 03:46:27,660
all the time. How about doing multisite 
animal studies with some of our controls?  

2362
03:46:28,500 --> 03:46:35,792
Doing more…replication studies. And this one I 
did not put down, but it did come up: Leverage  

2363
03:46:35,792 --> 03:46:41,150
ECHO to do a lot of what has been mentioned 
up above. Like I said, I did not mention that;  

2364
03:46:41,150 --> 03:46:46,574
someone else did. So, that’s why it’s up. So, 
yeah. So, that’s what our group discussed.

2365
03:46:46,574 --> 03:46:52,500
UNIDENTIFIED SPEAKER: Okay. I want to thank our moderators 
and our notetakers and our participants.  

2366
03:46:53,399 --> 03:46:58,859
These are all individual ideas that speakers 
came up with, not a consensus, but NIH is really  

2367
03:46:58,859 --> 03:47:03,779
appreciative of all these different ideas, and 
I hope that the audience is also appreciative of  

2368
03:47:03,779 --> 03:47:07,679
this ideas, and we’ll see some really great grants 
coming in eventually from some of you, leveraging  

2369
03:47:07,680 --> 03:47:13,320
from the…the connections you’ve made today or 
yesterday with your multidisciplinary colleagues.  

2370
03:47:13,979 --> 03:47:18,120
So, with that, I’m going to turn it back 
over to Dr. Krista Zanetti to close us.

2371
03:47:18,120 --> 03:47:19,680
DR. KRISTA ZANETTI: Okay.  

2372
03:47:28,020 --> 03:47:36,060
So, I think after the last 2 days, we realize 
that we can honestly probably spend an entire  

2373
03:47:36,060 --> 03:47:45,540
5 days discussing this topic or more. But at the 
same time, we all have day jobs, and we have a lot  

2374
03:47:45,540 --> 03:47:51,960
of things going on, so we had to, you know, really 
think about what we could fit in to reasonable a  

2375
03:47:51,960 --> 03:47:59,939
2-day meeting to think about the breadth of what 
is in this space. So, it was a lot, and I think  

2376
03:47:59,939 --> 03:48:05,219
that we’ve learned a lot, and I think that we have 
a lot of really good feedback and individual ideas  

2377
03:48:05,220 --> 03:48:11,280
that came in. The potential ideas and things 
to be considered to move this field forward.  

2378
03:48:12,840 --> 03:48:19,080
And I know it’s also tough, the hybrid format, 
and…and I know a lot of people broadcasted,  

2379
03:48:19,080 --> 03:48:23,240
and I want to thank you all for hanging in there 
with us; it’s been a long time since we’ve put one  

2380
03:48:23,240 --> 03:48:27,120
of these meetings on. So, we’ve been really…we 
were really excited to have the opportunity to  

2381
03:48:27,120 --> 03:48:33,779
bring speakers into the NIH and have them here, 
and we were also really thrilled to have the  

2382
03:48:33,779 --> 03:48:38,279
opportunity to broadcast it out to all of you. So, 
we know there were some technical difficulties,  

2383
03:48:38,279 --> 03:48:43,620
and we appreciate your patience and hanging 
in there with us, and we thank you so much for  

2384
03:48:43,620 --> 03:48:47,372
attending. So, having said that, I’m going to move 
on to some additional thank yous. First, I want to  

2385
03:48:47,372 --> 03:48:56,940
thank the organizing [committee]. I’m not going to 
read all the individual names out, as it’s a lot  

2386
03:48:57,479 --> 03:49:02,939
and it’s the end of the day, and here we have it 
on the slide. But what I do…I’d rather take that  

2387
03:49:02,939 --> 03:49:10,019
time to say thank you so much to the organizing 
committee. My sincerest gratitude to you. You  

2388
03:49:10,020 --> 03:49:17,460
have been amazing to work with. And we have had 
meetings of almost every week for the last 5  

2389
03:49:17,460 --> 03:49:22,920
months, and the individuals you see listed here 
really stepped up to the plate, and they were  

2390
03:49:22,920 --> 03:49:28,319
committed to make this meeting happen. They were 
fantastic to work with. They were…it was fun…the  

2391
03:49:28,319 --> 03:49:32,700
meetings just talking about this, thinking 
about how to have this meeting and thinking  

2392
03:49:32,700 --> 03:49:38,399
about the…the commitment and ideas and everything 
that kind of goes into whether or not you want to  

2393
03:49:38,399 --> 03:49:43,799
spend, you know, an hour-plus a week when you 
have many things on your plate to keep meeting  

2394
03:49:43,800 --> 03:49:50,160
and meeting. You know, sometimes it’s asking a 
lot, and these individuals really…I couldn’t have  

2395
03:49:50,160 --> 03:49:54,779
been happier to work with them, so thank you all 
so much, and I want to give a special shout-out  

2396
03:49:55,439 --> 03:50:02,519
to Kimberly Barch, and she did all of the 
logistics for the meeting, as far as the emailing  

2397
03:50:02,520 --> 03:50:09,180
and making sure that Dr. Vargas and I dotted our 
i’s and crossed our t’s and made sure we didn’t  

2398
03:50:09,180 --> 03:50:15,840
forget anything. And I also want to send a special 
shoutout to Janiya Peters, who was also logistics  

2399
03:50:15,840 --> 03:50:23,100
and made sure everything ran, our Zoom was up 
and going, thinking of everything from getting  

2400
03:50:23,100 --> 03:50:27,660
the room, making sure it was set up, and all 
of those little things that sometimes we forget  

2401
03:50:27,660 --> 03:50:34,979
to make sure that this meeting happened, and it 
happened very well, so I want to thank all of you.  

2402
03:50:41,279 --> 03:50:43,380
And I couldn’t get them up 
here…and then, I also, of course,  

2403
03:50:43,380 --> 03:50:50,819
want to thank our speakers. We know that it’s 
the middle of summer. We know that some of you  

2404
03:50:50,819 --> 03:50:55,979
had to shift around for your vacations and time 
with family, and some of you were able to come  

2405
03:50:55,979 --> 03:51:00,419
one day but not the other because you already had 
commitments, but you said, “Hey, I will fly in in  

2406
03:51:00,420 --> 03:51:06,180
the morning, I will present, I will fly out in the 
evening, I will jump on Zoom the next day to the  

2407
03:51:06,180 --> 03:51:10,800
breakout sessions and to watch,” and…and I know we 
asked a lot for you being in the middle of July,  

2408
03:51:10,800 --> 03:51:17,640
but we couldn’t be happier that you all accepted 
our invitation to participate, to present, and  

2409
03:51:17,640 --> 03:51:24,960
to give us a lot to think about. And I think that 
we…we saw so…so much in how much goes into this,  

2410
03:51:24,960 --> 03:51:29,279
you know, multigenerational nutritional 
influences space over the last 2 days,  

2411
03:51:29,279 --> 03:51:35,460
and we couldn’t have done it without all of 
you, and I thank you so much for…for…for coming,  

2412
03:51:35,460 --> 03:51:42,480
for presenting, for letting us pick your brains 
during the breakout sessions. We thank you.  

2413
03:51:42,480 --> 03:51:49,680
[Applause]

2414
03:51:49,680 --> 03:51:55,560
So…and I know that after 2 days, we are all 
tired, and I know the participants watching  

2415
03:51:56,640 --> 03:51:59,640
in…watching the broadcast are also 
probably tired because it was a lot,  

2416
03:51:59,640 --> 03:52:05,340
so I don’t want to belabor the point. 
I think we can wrap up this…yes, Drew?

2417
03:52:05,340 --> 03:52:07,560
AUDIENCE MEMBER (DREW): Oh, 
how about Krista and Ashley?

2418
03:52:07,560 --> 03:52:15,120
DR. KRISTA ZANETTI: Thank you very much.  

2419
03:52:15,120 --> 03:52:20,220
I will say, it is very easy to work with Ashley, 
so that’s what makes…that’s what made this a lot  

2420
03:52:20,220 --> 03:52:25,620
easier. Very, very easy. Very easy to work with 
Ashley, so it’s a joy. So, you know, I…I know  

2421
03:52:25,620 --> 03:52:32,279
we all…all want to…get onto flights and trains 
and things, and…and…and…you know, and for those  

2422
03:52:32,279 --> 03:52:36,660
of us in D.C., get back into the traffic and get 
home, so for those of you that are participating  

2423
03:52:38,100 --> 03:52:42,048
virtually, thank you so much. We thank you 
for coming. Oh, we have a question. Mary.

2424
03:52:42,048 --> 03:52:44,419
AUDIENCE MEMBER (MARY): I just 
want to ask, what happens next?

2425
03:52:44,419 --> 03:52:49,439
DR. KRISTA ZANETTI: Oh. Well, we will evaluate the 
information, we will look at it, and we will…you  

2426
03:52:50,340 --> 03:52:54,600
know, think about what those next steps are. 
A lot of that…a lot goes into that, including,  

2427
03:52:54,600 --> 03:52:59,700
you know, planning, and we will be in 
touch after, so, you know, a lot goes into,  

2428
03:52:59,700 --> 03:53:04,500
kind of…we will be thinking forward, and you 
all will probably be getting emails from us  

2429
03:53:04,500 --> 03:53:10,260
in the not-too-distant future. So, are there 
any other questions before we wrap up? Yes,  

2430
03:53:10,260 --> 03:53:12,359
one in the back? It’s like, you’re 
like, as soon as I’m ready to wrap up,  

2431
03:53:12,359 --> 03:53:15,179
there’s going to be a hand. One more. 
Do you want to turn your microphone on?

2432
03:53:15,180 --> 03:53:21,540
AUDIENCE MEMBER: A few of us have been chatting…over the last 
couple of days about the workshop,  

2433
03:53:21,540 --> 03:53:27,239
paper, for…that…not just involves 
NIH staff but also some of us who,  

2434
03:53:27,239 --> 03:53:29,815
of course, would volunteer. Will one 
of those emails be a solicitation, or…?

2435
03:53:29,815 --> 03:53:35,219
DR. KRISTA ZANETTI: Yes, I think if the speakers 
want to write white papers, of course, we’re  

2436
03:53:35,220 --> 03:53:40,380
not…we’re not going to not support that. We’re 
going to support that wholeheartedly. So, that  

2437
03:53:40,380 --> 03:53:46,020
will be some of the future emails that you get. 
So, those of you that are in the room, be thinking  

2438
03:53:46,020 --> 03:53:49,800
about whether you want to participate in that. And 
also, you know, you have a long flight home or a  

2439
03:53:49,800 --> 03:53:56,400
train ride; think about, maybe, some of the ideas 
on what a white paper you might want to write is.  

2440
03:53:56,939 --> 03:54:00,064
You know, even though you’re all probably going 
to want to just take a nap. But think about that  

2441
03:54:00,064 --> 03:54:08,639
on the way out. So, I think we have a lot to look 
forward to, and it’s been a long 2 days for us,  

2442
03:54:08,640 --> 03:54:14,220
and I want to wrap up. And I just want to thank 
you all again, and we look forward to continuing  

2443
03:54:14,220 --> 03:54:17,940
to think about this important space. So, 
everybody have a great rest of your day.

2444
03:54:17,940 --> 03:54:21,165
[Applause]