The developmental origins of obesity Jonathan Wells Professor of Anthropology and Pediatric Nutri<on UCL Ins<tute of Child Health Energy balance and physics The energy balance equa<on Energy
Intake
2 3 2 Energy Energy = ± expenditure stores = 2 + 0 = 2 + 1 = 1 + 1 Weight Stable Weight gain Obesity and energy balance •  The current model •  We eat too much … •  … and/or we are not sufficiently ac<ve It’s the wrong model Articles
Global, regional, and national prevalence of overweight
and obesity in children and adults during 1980–2013:
a systematic analysis for the Global Burden of Disease
Study 2013
Ng et el, Lancet 2014 Marie Ng, Tom Fleming, Margaret Robinson, Blake Thomson, Nicholas Graetz, Christopher Margono, Erin C Mullany, Stan Biryukov, Cristiana Abbafati*, Semaw Ferede Abera*,
Jerry P Abraham*, Niveen M E Abu-Rmeileh*, Tom Achoki*, Fadia S AlBuhairan*, Zewdie A Alemu*, Rafael Alfonso*, Mohammed K Ali*, Raghib Ali*, Nelson Alvis Guzman*,
Walid Ammar*, Palwasha Anwari*, Amitava Banerjee*, Simon Barquera*, Sanjay Basu*, Derrick A Bennett*, Zulfiqar Bhutta*, Jed Blore*, Norberto Cabral*,
Ismael Campos Nonato*, Jung-Chen Chang*, Rajiv Chowdhury*, Karen J Courville*, Michael H Criqui*, David K Cundiff*, Kaustubh C Dabhadkar*, Lalit Dandona*,
Adrian Davis*, Anand Dayama*, Samath D Dharmaratne*, Eric L Ding*, Adnan M Durrani*, Alireza Esteghamati*, Farshad Farzadfar*, Derek F J Fay*, Valery L Feigin*,
Abraham Flaxman*, Mohammad H Forouzanfar*, Atsushi Goto*, Mark A Green*, Rajeev Gupta*, Nima Hafezi-Nejad*, Graeme J Hankey*, Heather C Harewood*,
Rasmus Havmoeller*, Simon Hay*, Lucia Hernandez*, Abdullatif Husseini*, Bulat T Idrisov*, Nayu Ikeda*, Farhad Islami*, Eiman Jahangir*, Simerjot K Jassal*, Sun Ha Jee*,
Mona Jeffreys*, Jost B Jonas*, Edmond K Kabagambe*, Shams Eldin Ali Hassan Khalifa*, Andre Pascal Kengne*, Yousef Saleh Khader*, Young-Ho Khang*, Daniel Kim*,
Ruth W Kimokoti*, Jonas M Kinge*, Yoshihiro Kokubo*, Soewarta Kosen*, Gene Kwan*, Taavi Lai*, Mall Leinsalu*, Yichong Li*, Xiaofeng Liang*, Shiwei Liu*,
Giancarlo Logroscino*, Paulo A Lotufo*, Yuan Lu*, Jixiang Ma*, Nana Kwaku Mainoo*, George A Mensah*, Tony R Merriman*, Ali H Mokdad*, Joanna Moschandreas*,
Mohsen Naghavi*, Aliya Naheed*, Devina Nand*, K M Venkat Narayan*, Erica Leigh Nelson*, Marian L Neuhouser*, Muhammad Imran Nisar*, Takayoshi Ohkubo*,
Samuel O Oti*, Andrea Pedroza*, Dorairaj Prabhakaran*, Nobhojit Roy*, Uchechukwu Sampson*, Hyeyoung Seo*, Sadaf G Sepanlou*, Kenji Shibuya*, Rahman Shiri*,
Ivy Shiue*, Gitanjali M Singh*, Jasvinder A Singh*, Vegard Skirbekk*, Nicolas J C Stapelberg*, Lela Sturua*, Bryan L Sykes*, Martin Tobias*, Bach X Tran*, Leonardo Trasande*,
Hideaki Toyoshima*, Steven van de Vijver*, Tommi J Vasankari*, J Lennert Veerman*, Gustavo Velasquez-Melendez*, Vasiliy Victorovich Vlassov*, Stein Emil Vollset*, Theo Vos*,
Claire Wang*, Sharon XiaoRong Wang*, Elisabete Weiderpass*, Andrea Werdecker*, Jonathan L Wright*, Y Claire Yang*, Hiroshi Yatsuya*, Jihyun Yoon*, Seok-Jun Yoon*,
Yong Zhao*, Maigeng Zhou*, Shankuan Zhu*, Alan D Lopez†, Christopher J L Murray†, Emmanuela Gakidou†‡
Global prevalence of overweight/ obesity Men : 36.9 % Women : 38.0% Summary
Background In 2010, overweight and obesity were estimated to cause 3·4 million deaths, 3·9% of years of life lost, and
3·8% of disability-adjusted life-years (DALYs) worldwide. The rise in obesity has led to widespread calls for regular
monitoring of changes in overweight and obesity prevalence in all populations. Comparable, up-to-date information
about levels and trends is essential to quantify population health effects and to prompt decision makers to prioritise
action. We estimate the global, regional, and national prevalence of overweight and obesity in children and adults
during 1980–2013.
Published Online
May 29, 2014
http://dx.doi.org/10.1016/
S0140-6736(14)60460-8
See Online/Comment
http://dx.doi.org/10.1016/
S0140-6736(14)60767-4
It’s a descrip<on Energy balance as symptom •  Robert Lus<g •  Gary Taubes European Journal of Clinical Nutrition (2011), 1–17
& 2011 Macmillan Publishers Limited All rights reserved 0954-3007/11
www.nature.com/ejcn
REVIEW
Obesity and energy balance: is the tail wagging
the dog?
JCK Wells1 and M Siervo2
1
Childhood Nutrition Research Centre, UCL Institute of Child Health, London, UK and 2Human Physiology and Nutrition Unit,
Department of Neuroscience, Faculty of Medicine, University ‘Federico II’ of Naples, Naples, Italy
The scientific study of obesity has been dominated throughout the twentieth century by the concept of energy balance. This
Metabolic perturba<ons •  Refined carbohdrate High insulin levels •  Sedentary behaviour Metabolic inflexibility •  Reduced sleep Decreased sa<ety •  TV, Video games Increased appe<te Your decisions shape metabolism ? Obesity and energy balance
JCK Wells and M Siervo
8
Classic energy balance model of obesity
Causes
DIET
High
energy
intake
Symptoms
PHYSICAL
ACTIVITY
Low
energy
expenditure
Lipogenesis
Fat deposition
Weight gain
Positive
energy
balance
paid to the ta
two widely r
obesity and (a
using the me
re-examine th
Obesity and sl
The increasin
Insulin resistance
with obesity
the scientific
Hyperinsulinaemia
demonstrate
variously of n
mass index, U
PUBLIC HEALTH MESSAGE:
COUNT CALORIES AND BURN MORE THAN YOU CONSUME
tions (Marsh
itudinal stud
Metabolic perturbation model of obesity
again the ass
Wells and Siervo, Eur J Clin Nutr 2011 effect appears
Causes
Symptoms
gain, rather
the scientific
Hyperinsulinaemia
demonstrate p
variously of no
mass index, UPUBLIC HEALTH MESSAGE:
COUNT CALORIES AND BURN MORE THAN YOU CONSUME
tions (Marsha
itudinal studie
Metabolic perturbation model of obesity
again the asso
effect appears t
Causes
Symptoms
gain, rather th
2008; Patel an
Lethargy
DIET
In children,
Hunger
High
Weight gain
sistent, with a
refined
PHYSICAL
carbohydrates ACTIVITY
linear associat
Positive
Hyperinsulinaemia
Metabolic
(Marshall et al.
energy
Lipogenesis
inflexibility
Balance
been reported
Fat deposition
2002; Padez et
United States (
Insulin
Japan (Sekine e
resistance
New Zealand (N
A meta-analysi
PUBLIC HEALTH MESSAGE:
AVOID REFINED CARBOHYDRATES AND GET FIT
compared with
TO BOOST METABOLIC FLEXIBILITY
ratio of obesit
et al., 2008).
Figure 2 Contrasting models of the causation of obesity. (a) In the
Wells nd Siervo, Eur Jbetween
Clin Nutr 2011 traditional energy balance model,
anaimperfect
‘match’
evidence, thes
appetite and physical activity level causes positive energy balance,
implications fo
Metabolism shapes your decisions ? which is considered to drive changes in body weight through
Development affects metabolism Low Birth weight Slow infant growth Rapid infant growth Birth size and catch-­‐up 1.0
Birth weight
Birth Length
0.5
Z-score 0.0
-0.5
-1.0
Catch-up
No change
Catch-down
Ong et al., BMJ 2000 Catch-­‐up and later body composi<on 1.0
Height 5 years
BMI 5 years
0.8
0.6
0.4
Z-score 0.2
0.0
-0.2
-0.4
-0.6
Catch-up
No change
Catch-down
Ong et al., BMJ 2000 regression of body
SDS adjusting for
re given in Table 4.
ssociated with all
models, change in weight SDS was a highly significant
predictor. When waist girth was adjusted for hip girth it
remained independently associated with change in weight
SDS, though the magnitude of the effect (1.4 cm) was greatly
Birth weight in obese children 15
Males
Females
Males
Females
Trunk FM (kg)
10
5
0
-5
-10
2
3
4
S
SDS and waist SDS.
in females (ns).
-15
-2
-1
0
1
2
3
4
Birth weight SDS
Figure 4 Association between birth weight SDS and DXA trunk fat mass
Wells et al., Int J Obes 2011 residual. Trunk fat mass was regressed on height. Trunk fat mass residual was
calculated as the actual value minus the value predicted from the subject’s
height. The correlation was "0.31 in males (P ¼ 0.04) and "0.15 in females
(ns).
Post-­‐natal growth in obese children Programming of body compo
JCK Wells et al
current size.9 Such ad
Males
as to whether birth w
Females
birth, is the actual pr
10
This statistical issue
because, since they
5
achieve empirically
statistical adjustmen
0
predicts later fat dist
fied by high rates of w
-5
easier to detect.
Birth weight SDS
-10
significantly greater
covered the normal r
-15
ing 5.23 SDS. Within
-1
0
1
2
3
4
5
6
7
a (non-significant) co
Change in weight SDS
many other studies,
association with curr
Figure 5 Association between change in weight SDS from birth to follow-up
and DXA trunk fat mass residual. Trunk fat mass was regressed on height.
was apparent. This
Wells e
t a
l., I
nt J
O
bes 2011 Trunk fat mass residual was calculated as the actual value minus the value
magnitude of lean m
predicted from the subject’s height. The correlation was 0.66 in males
part on their adipo
(Po0.0001) and 0.61 in females (Po0.0001).
Trunk fat (kg)
15
!"#$%&'()*('
Consequences of catch-­‐up growth Birth order: not undernutri<on Birth weights 1860-1984
279
380037003600-
/
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ol
.r'l
cm
#.J
L
.r'l
on IHC Titles] At: 15:02 16 June 2010
03
3500-
o
340033003200310030000
Parity
Figure 1. Birth weight as a function of parity for the total set of data. Squares show mean birth
weight for each parity. SE for paraity 2 is 9 g increasing to an SE of 57 g for parity 8. Two regression lines
are plotted; one based on birth weights for parity 1 and 2, the other based on birth weights for parity 2
to 12. Birth weights for parity 9 to 12 are not plotted due to there being only a small number of cases.
Rosenberg, Ann Hum Biol 1988 !"#$%&'()*+'
Catch-­‐up in first-­‐borns 0.4
Height SDS
0.2
0.0
-0.2
-0.4
p = 0.016
p = 0.001
p = 0.001
Firstborn
Later born
-0.6
ns
-0.8
-4
0
4
8
12
16
20
24
28
32
36
40
44
48
Age, months
Wells et al., Am J Epidemiol 2011 Birth order and adult obesity + 10.3 kg weight + 7.4 kg fat mass Siervo et al., Eat Weight Disord 2011 Maternal low birth weight Maternal obesity Offspring obesity Cnajngius et al., Int J Obes 2012 Maternal low birth weight Low birth weight Maternal obesity 3 x Offspring obesity Cnajngius et al., Int J Obes 2012 Breast-­‐milk of diabe<c mothers Figure 1—Relative body weight at 2 years of age in thirds of intake of DBM (error bars # 95%
CI).
Plagemann and Associate
breast milk provided by their biologica
(diabetic) mother may result in an in
creased relative body weight and in
creased prevalence of obesity at 2 years o
age, independent of birth weight, gesta
tional age, sex, age, type of maternal dia
betes, or maternal BMI. In contrast
neonatal intake of banked breast mil
from healthy nondiabetic women has
beneficial effect on later body weight an
glucose tolerance in childhood. Althoug
the volume of diabetic breast milk in
gested neonatally significantly predicte
relative body weight at 2 years of age
body weight itself was the only significan
predictor of glucose tolerance at follow
up, as revealed by stepwise regressio
analysis.
To our knowledge, only one stud
has investigated the impact of the amoun
of certain types of milk ingested neona
tally on later outcome, in general. Singha
et al. (26) observed a beneficial effect o
the amount of banked donor breast mil
ingested during neonatal life, as com
pared with formula milk, on blood pres
sure later in the childhood of preterm
newborns. In a number of studies, de
creased body weight, diminished risk fo
obesity, and decreased risk for develop
ment of type 2 diabetes were observed i
breast-fed infants (1– 6). Moreover, b
analyzing potential influences of a wid
Plagemann et al.,Diabetes Care 2002 confounders, plus additional adjustment
for relative body weight at follow-up, did
during childhood served as independent
variables. Table 5 shows that, by stepwise
Interac<ons Diet composi<on Developmental effects Body weight Physical ac<vity The role of food Refined carbohydrate Protein, fat Lethargy, hunger Energy, sa<ety