Early Origins of Adult Health and Disease: Early Origins of Adult Health and Disease: Early Origins of Adult Health and Disease: Early Origins of Adult Health and Disease:

Impact on Global Health and NutritionImpact on Global Health and NutritionImpact on Global Health and NutritionImpact on Global Health and Nutrition

R. Uauy INTA-U Chile LSHTM–London UK

Note: for non-commercial purposes only

Impact of Programming: publications

• Dörner G. Perinatal hormone levels and brain organization. In: Stumpf WE, Grant LD (eds) Anatomical neuroendocrinology. Basel, Karger. 1975; 245-252

• Metabolic programming (274 since 2009 ) (902 since 2005) (1,120 since 2000) (1,170 since 1995) (1,180 since 1991)

• Barker programming (3420 since 2009) (14,500 since 2005) (17,600 since 2000) (20,500 since 1995) (21,300 since 1991)

concluded that environmental influences during critical periods of development are capable to determine functions of metabolic processes in adult life

To be born, grow, develop, and survive

To adapt to the ecosystem we live in

To succeed in passing on our genes

To reproduce before we age and die

….we were really selectedWe were programmed?

Developmental Plasticity

• Able to find and select food (hunter, gatherer, scavenger), progressively nutrient dense diet

• Able to survive and thrive in different enviroment, foods, climate. Adaptive capacity

• Able to learn from experience and transfer this to kindred, post natal brain growth, delay somatic growth

• Able to choose mates with selective advantage .

• Able to grow food and keep surplus for “rainy day” .

Traits that provided selective Traits that provided selective

advantage to Homo Sapiens Sapiensadvantage to Homo Sapiens Sapiens

Years-2 .1 - -0.9-0 .8 - 0.30.4 - 1.31.4 - 2.52.6 - 3.73.8 - 5.05.1 - 6.46.5 - 7.77.8 - 11No Data

Difference by gender in disability adjusted life expectancy at birth 2009

Women are programmed to live longer:

but not always

A single genotype can produce many phenotypes, depending on many contingenciesencountered during development. That is, phenotype is an outcome of a complex series ofdevelopmental processes that are influenced by environmental factors as well as genes .

H. F. Nijhout, 1999

Programming and Developmental Plasticity

Programmed to grow and develop according to age ge

Determinants of loss

• Examine recent global mortality trends in the burden of nutrition related death and disability.

• Assess the short and long term consequences of malnutrition in light of the early origins of adult disease hypothesis.

• Characterize the double burden of disease and the continuum between malnutrition in early life and th e epidemic of nutrition related chronic disease.

• Need to redefine interventions with a life course perspective to address undernutrition and nutrition related chronic disease with a common agenda

Objectives of this presentation

Life expectancy at birth 1955–2010Life expectancy at birth Life expectancy at birth 19551955––20102010

1960 1980 2000 2020

80

70

60

50

40

30

20

10

0

(yea

rs)

Developed

Developing: low mortality

high mortality

Developed

Developing: low mortality

high mortality

1920-49

1861-1919

SURVIVAL CURVES 1861-1999 SWEDEN

1950-59

RGJ Westendorp AJCN83:404S–9S 2006.

We live in a World with Large Inequalities

Population

Income

1960 1970 1980 1990 2000

LIFE EXPECTANCY AT BIRTH 1960-2000

McMichael THE LANCET Vol 363 2004

1960 1970 1980 1990 2000

LIFE EXPECTANCY AT BIRTH 1960-2000 McMichael THE LANCET Vol 363 2004

0

25

50

75

100

20 40 60 80 100 120

age (years)

1930

1960

2000

PREVENTING DEATH AND DISABILITY PREVENTING DEATH AND DISABILITY PREVENTING DEATH AND DISABILITY PREVENTING DEATH AND DISABILITY %

Su

rviv

al

Low Obesity

High Obesity

Early DisabilityMyocardial infarct Stroke Diabetes CancerDementia Functional losses

Men Born Men BornCondition 1830–45 1918–27

Heart disease 55.9 65.4Arthritis 53.7 64.7Neoplasm 59.0 66.6Respiratory 53.8 65.0

Age of Onset of Some Chronic Conditions among American Males near the Beginning and near the End of the Twentieth Century

Robert Vogel http://www.nber.org/papers/w9941 August 2003

at Different Values of Mean Log GDP per Capita GDP, Data from Penn World Tables

1% change in ASR associated with a 0.05% increase in growth rate, while a 1% in investment/GDP ratio was associated with a 0.014% increase.

Net Effect of a 1 % Change in Adult Survival Rate(A SR) on GDP Gr owth

G. Anderson et al NEJM 3563: 209-11 2007

Major Diseases and Conditions in The World

Nutrition defines in great part how many will survive infancy & how they will live and die

Years of age

0

25

50

75

100

20 40 60 80 100 120

1930

2000

Foetus /Infants / Children• LBW/IUGR • Stunting and wasting• Micronutrient deficiency (Vit A,I, Zn, Fe) • Infection (HIV/AIDS)

Adults / Elderly• Cardiovascular (CHD, Stroke )• Obesity /Diabetes/ dyslipidemia• Cancer related to diet• Osteoporosis• Aging

Ideal

% su

rvival

Nutrition-Infection interact with genes to determine in great part, how we grow physically and develop mentally, what diseases we most likely

will suffer during our life span and finally how we will age and die.

DisabilityPhysical /Mental

% of total DALYs lost

Vit A deficiency

Iron deficiency

% of total DALYs lost

Blood Pressure

Cholesterol

171 million children under 5 are stunted171 million children under 5 are stunted

Source: WHO Global Database on Child Growth and Malnutri tion, May 2009

0 10 20 30 40 50 600

10

20

30

40

50

60

70

Regions

South America

Middle America / Caribbean

South East Asia

South Asia

Near East / North Africa

Sub-Saharan Africa

China

Prevalence of Low Birth Weight (%)

Pre

vale

nce

of s

tunt

ing

(%)

Extracted from: ACC/SCN, 1997

The prevalence of Low Birth Weight and StuntingLow Birth Weight and Stunting are Related Low Birth Weight and Stunting are Related

L BW and Infant Underweight are Related L BW and Infant Underweight are Related

UN/SCN 6UN/SCN 6thth WNR 2010WNR 2010

Maternal Underweight & LBW are Related Maternal Underweight & LBW are Related

UN/SCN 6UN/SCN 6thth WNR 2010WNR 2010

Relative Risk for Association Between 1Relative Risk for Association Between 1--cm gain Maternal Height cm gain Maternal Height

Mortality Among Children < 5 yrs of ageMortality Among Children < 5 yrs of age

J E Özaltin et al JAMA303: 1507-16 2010

Stunting prevalence and number affected in developing countries

1990 2000 2010

010

2030

4050

Stu

ntin

g (%

)

40.3

48.6

23.7

39.3

37.7

18.1

38.2

27.6

13.5

1990 2000 20100

5010

015

020

0

Num

ber

of s

tunt

ed (

mill

ions

)

45

190

13

51

138

10

60

100

7

AFRICA ASIA LATIN AMERICASource: Department of Nutrition, World Health Organization

Number affected Stunting prevalence

Mean z-scores for age all 54 studies, relative to the WHO standard

Source: Victora CG, de Onis M, Hallal PC, Blössner M, Shrimpton R. Worldwide timing of growth faltering: revisiting implications for interventions using the World Health Organization growth standards. Pediatrics, 2010 (Feb 15Epub print)

Mean Height Z by age, relative to WHO standard (1–59 m).

Source: Victora CG, de Onis M, Hallal PC, Blössner M, Shrimpton R. Worldwide timing of growth faltering: revisiting implications for interventions using the World Health Organization growth standards. Pediatrics, 2010 (Feb 15Epub print)

PrePregnancy

Height BMI

MaternalGlucoseInsulin

PlacentalFetal blood

flow

Fetal growth

restriction

Fetal Macrosomia

Weight gain with

limited length gain

EarlyAdiposityrebound

Early Pubertal

maturation

CentralObesity

Metabolic syndrome

High BMIObesity

+ E

nergy

Balance

Hormonal responses

Hormonal responsesEpigenetic changes

Pre-natal Post-natal

Infection and other

Environmental Epigenetic Factors

Fetal & Infant nutrition

Brain Development

Growth muscle/bone Weight & HEIGHTBody composition

Metabolic ProgrammingCHO, Lipids, Proteinshormone,receptor,gene

Short term

Immunity

Locomotion

Work Capacity

Cognitive capacity & Education

Culture

Long term NutritionDiet School Failure

Poor Education

Lower Income

Infections

Stunting

Lower Income

Obesity

Diabetes

Obesity

Cor Heart Dis

Cancer

High BP/Stroke

Aging related

functional loss

The cost of hunger: Social and economic impact of child undernutrition in Central America and the

Dominican Republic

Rodrigo MartínezAndrés Fernández

www.cepal.org/publicaciones/xml/9/32669/DP_CostHunger.pdf

CONSEQUENCES OF UNDERNUTRITION

UNDERNUTRITIONUNDERNUTRITION

Productivity

Social Exclusion Unemployment

Mortality School performance

Morbidity Acute & Chronic

Mental Development

Increase Costs (private– públic)

Malnutrition not only affects those who are malnourished but also affects the whole of society

Martínez R y Fernández A. Modelo de análisis del impacto social y económico de la desnutrición infantil en A.L. CEPAL 08

Malnutrition is both an ethical and a socio-economic

problem

Why do we need to evaluate Economic Impact

• Prioritisation is both desirable and inevitable• Economic evaluation is a systematic and

transparent framework for assessing benefits • It helps make decisions, it doesn’t make them• It tells us nothing about affordability, equity, ethical

concerns and political feasibility• Methodological challenges and uncertainties

associated with DOHAD type interventions to improve health of next generation need to be addressed.

It estimates the health costs of pre-school boys and girls who suffer from undernutrition during the year of analysis,

It considers the educational costs stemming from the undernutrition children now in school suffered during the first five years of life

Includes economic costs due to lost productivity by working-age individuals who were exposed to under-nutrition before the age of five.

The cost of hunger: Social and economic impact of child undernutrition…

Incidental retrospective dimension (Estimate of the cost of undernutrition in a country’s population for a given year)

Serves to project the present and future losses incurred as a result of medical treatment, repetition of grades in school, andlower productivity caused by under-nutrition among children under the age of five in each country, in a specific year.

Based on that, potential savings derived from actions taken to achieve nutritional objectives can be estimated (for example, to attain MDG1, reducing undernutrition by half by 2015).

The cost of hunger: Social and economic impact of child undernutrition…

Prospective: potential savings approach

Incidental

Age at which effects are documented

Ag

e a

t w

hic

h l

oss o

ccu

rss o

r id

en

tifi

ed

0 - 4

6 - 18

15 - 64

X

Health

Education

Productivity

Prospective

1826411

4

Retrospective

TWO APPROACHES IN EVALUATING COSTS OF HUNGER TWO APPROACHES IN EVALUATING COSTS OF HUNGER

Economic losses for 13 countries was Economic losses for 13 countries was US $ 17 Billion or 3.4% of aggregate GNPUS $ 17 Billion or 3.4% of aggregate GNP

Cost of malnutrition (dollars and as percent GNP 2004-2005)

Fuente: CEPAL, sobre la base de información oficial y registro de costos de educación de cada país; Ingresos y escolaridad, de encuestas de hogares de cada país

Central America &

Dominican Rep(2004)

Andean Countries &

Paraguay (2005)

Total (Million dollars)

6,659 10,552

Percent GNP 6.4 2.6

0

500

1000

1500

2000

2500

3000

3500

4000

4500

VEN CRI PAR PAN PER COL ECU RDO NIC BOL ELS HON GUA0%

2%

4%

6%

8%

10%

12%

Total Cost Percent GNP

Mill

ion

dol

lars

Impact of malnutrition in Latin America(2004-05)

source: Economic Commission for Latin America ECLA 2008

Higher mortality and lost opportunity for education determine 93% of the cost of hunger. Health is only 6.5%

and school repetition less than 1%.

Health (Morbidity)

7%Education

(Repetition) 1%

Productivity (Education )

41%

Productivity (Mortality)

52%lost productivity based on poor linear growth

Deaths attributable to 16 leading risk factors: all countries, 2001

30003000 60006000 70007000 8000800000 10001000 20002000

Deaths (000)Deaths (000)

40004000 50005000

Low mortality – Developing countries

High mortality – Developing countries

Developed countries

Adapted from World Health Report 2003

Blood pressureTobacco Use

CholesterolUnderweight

Unsafe sexFruit & vegetableHigh body mass IndexPhysical inactivityAlcohol

Unsafe water, hygiene

Indoor smoke/fuelsIron deficiency

Urban air pollutionZinc deficiencyVitamin A deficiencyUnsafe health/injections

WHO Chronic Disease report 2005

% of total DALYs lost

OBESITY

Under nutrition

Applying DOHAD to ChinaApplying DOHAD to China ’’s s Emerging Disease Burden and Emerging Disease Burden and

Projected Costs to SocietyProjected Costs to Society

Relative Risks (RR), for Coronary Heart Disease (CH D) Expressed as Multiples (X)

effect modeled effect not modeled

Saturated Fatas % Diet

Overweight/obesity

Hypertension

Diabetes

CHD

Stunting

Low BirthWeight

f

g

X1.25

X1.3h

X5i

a

X3b

X2c

X1.3d

X1.9e

(Popkin B, Horton S and Kim S et al Nut Revs 2001)

Proportion of chronic diseasecan be traced back to nutrition

in early life for China 1995

9.2%

11.3%

33.9%

Fruit/veg as% Diet

Saturated fatas % Diet

Overweight/obesity

Hypertension

CHD

Stunting

Low BirthWeight

Diabetes

Stroke

Cancer

effect modeled effect not modeled (Popkin B, Horton S and Kim S et al Nut Revs 2001)

Proportion of chronic diseasecan be projected to nutrition

in early life for China 2025

10.8%

4.7%

18.8%

Fruit/veg as% Diet

Saturated fatas % Diet

Overweight/obesity

Hypertension

CHD

Stunting

Low BirthWeight

Diabetes

Stroke

Cancer

effect modeled effect not modeled (Popkin B, Horton S and Kim S et al Nut Revs 2001)

Human costs of diet-related NCDs

1995• 2.5 m deaths (43.2% of

all deaths)

• 1.04 m cancer deaths

• 0.35 m CHD deaths

• 1.11 m stroke deaths

2025• 7.63 m deaths (52.0%

of all deaths)

• 3.77 m cancer deaths

• 1.45 m CHD deaths

• 2.41 m stroke deaths

(Popkin B, Horton S and Kim S et al Nut Revs 2001)

Costs of lost work – death

$5.76 bn 0.8% of GDP

Hospital costs $11.74 bn 1.6% of GDP

Total costs $17.40 bn 2.4% of GDP

Economic Costs of Diet-related NCDs: China 95

(Popkin B, Horton S and Kim S et al Nut Revs 2001)

Economic costs of dietEconomic costs of diet --related NCDsrelated NCDs

China’s economic cost of diet-related non communica ble disease is 2.4 percent of GDP*

(Popkin B, Horton S and Kim S et al Nut Revs 2001)

* GDP loss likely to be much higher when taking into account morbidity

Applying DOHAD to Central Applying DOHAD to Central America Stunted Indigenous America Stunted Indigenous

Mayan: Need to invest in Mayan: Need to invest in Human Capital Development Human Capital Development

Human Capital Study 2002-04

� Original sample : 2393

� Target sample : 1856 (1) (2)

� Achieved : 1560 ( 84 % of target )

1. Known to be alive and living in Guatemala in 2002

2. 272 died , mostly in early childhood; 163 left the country and 102 are lost

to follow-up

Differences in height at 3 yrs, in growth from 3yrs-to adulthood and in adult height in Guatemalans compared to Mex-American by level of stunting at 3 years of age: Males

-4.6

-8.6

-13.2

1.9 1.1 1.1

-2.8

-7.4

-12.1-15

-10

-5

0

5

Not stuntedModerately stuntedVery stunted

3 Years 3-Adult Adult Stature

+ Adjusted for family SES in 1975, maternal education, village of origin and age at follow-up.

cm

Schooling by level of stunting at 3 yrs of age: differences withrespect to the grand mean; 5.1yrs males and 4.5yrs females

0.89

0.5

0.08

0.29

-0.64-0.77

-1

-0.5

0

0.5

1

Males (P < .001)

Females (P = 0.003)

None(HAZ > -2 )

Moderate(-3 < HAZ ≤ -2)

Severe(HAZ ≤ -3 )

+ Adjusted for family SES in 1975, maternal education, village of origin and age at follow-up.

Growth retardation at 3 years

Years

Income (Quetzales) by level of stunting at 3 yrs: differences relative to grand mean, Q26,100 men and Q8,376 women

36263224

1119

-589

-3248

-1770

-4000

-2000

0

2000

4000

Males (P = 0.03)

Females (P = 0.03)

None(HAZ > -2 )

Moderate(-3 < HAZ ≤ -2)

Severe(HAZ ≤ -3 )

+ Adjusted for family SES in 1975, maternal education, village of origin and age at follow-up.

Growth retardation at 3 years

Quetzales

The Human Capital 2002-04 Study in Guatemala: a follow-up to the INCAP Longitudinal Study 1969-77

Age in 2003 26 to 41 years

Original cohort 2393

Target sample† 1856

Measured 1570

% of target sample 85%

% of original cohort 66%†Living in Guatemala, traceable. 272 had died, 163 left the country and 102 were untraceable

Hoddinott J, Behrman JR, Martorell JR Labor Force activities and income among young Guatemalan Adults . Food Nutr. Bull 2005, 26 (suppl 1) 98-109 Maluccio JA, Melgar P, Mendez H, Murphy A FSocial and economic development and change in four Guatemalan villages: Demographics, schooling, occupation and assets Food Nutr. Bull 2005, 26 (suppl 1) 25-45Hoddinott J, Maluccio JA, Behrman JR, Flores R, Martorell R Effect of a nutrition intervention during early childhood on economic productivity in Guatemalan adults Lancet 2008; 371: 411–16

Characteristics of participants in (atole & fresco) supplemented or not from 0-24 m of age

Hoddinott J, et al Lancet 2008; 371: 411–16

Differences in income between atole vs fresco supplemented at different ages

0-24m

0-36m

36-72m

Age range

of supp

Hoddinott J, et al Lancet 2008; 371: 411–6

The panel was guided predominantly by consideration of economic costs and benefits. The panel acknowledged the difficulties that cost benefit analysis must overcome, both in principle and as a practical matter, but agreed that the cost-benefit approach was an indispensable method.

In setting priorities, the panel took account of strengths and weaknesses of the specific cost-benefit appraisals under revie w, and gave weight both to the institutional preconditions for success and to the demands of ethical or humanitarian urgency.

Jagdish Bhagwati of Columbia U *Robert Fogel U of Chicago Bruno Frey of the U of Zurich, Justin Yifu Lin of Peking U,.

*Douglass North /Washington U St Louis Thomas Schelling/U of Maryland, *Vernon Smith /George Mason U N Stokey U of Chicago

* Nobel laureates 2004

2004Economists Members of the Panel

2004

Etiologic DeterminantsMeasures of Effect (Impact)

• Relative risk (RR) indicates how much more likely outcome (IUGR or PTB) occurs in women with vs without the risk factor:

• Etiologic fraction (EF) is the proportion of the outcome in a given population that can be attributed to the risk factor:

• Preventable risk fraction (PRF) is the proportion of the outcome that can be avoided by preventive measures. Requires evaluation of effectiveness under real life conditions (efficacy is not the same).

RR = I / IE E

EF = P(RR-1)

P(RR-1) + 1