What can longitudinal research tell us about adolescent health?

Research findings from Young LivesElisabetta Aurino

(with Jere Behrman, Mary Penny and Whitney Schott)

Why adolescent nutrition?Adolescence period of rapid physical and

psychosocial developmentAdolescent health is intrinsically and

instrumentally important for development: Possibility of catch-up from earlier nutritional

deficiencies Reap the “demographic dividend” through better

health and education and increased productivity for the largest youth population in history

Achieving better nutrition before conception and improve the nutritional status of the next generation

Despite the growing focus on adolescent nutrition, many knowledge gaps existKey data and evidence gaps (van Lieshout et al

2014, Global Nutrition Report 2015): Descriptive evidence on diets/nutritional status

(incl. overnutrition) Role of nutritional and dietary factors on puberty

and adolescent health status Linkages between maternal nutrition during

adolescence and offspring health

Summer 2015: Call for proposals on the analysis of existing datasets on the status of adolescent nutrition

Young Lives study design

A “taste” of our research so far

We have been analysing the Young Lives data with the following aims:Describe nutrition & diets at different ages

Examine differences by cohort, and gender, rural/urban, wealth

Examine how well the Minimum Dietary Diversity indicator for Women predicts nutrition at different ages

Investigate the role of prenatal and childhood nutrition on menarche

Examine the relation between maternal nutrition and her offspring’s health

Descriptive stats for 12-years-olds in 2006 and 2013a

Ethiopia India Peru VietnamOC YC OC YC OC YC OC YC

Stunted (ZHFA < -2 SD)

0.30 0.29 0.34 0.29 0.31 0.19 0.31 0.20(0.46) (0.45) (0.47) (0.45) (0.46) (0.39) (0.46) (0.40)

Thin (ZBMI-for-age < -

2 SD)0.36 0.41 0.34 0.33 0.01 0.01 0.17 0.14(0.48) (0.49) (0.47) (0.47) (0.11) (0.10) (0.38) (0.34)

Overweight (ZBMI-for-age >

2)0.00 0.01 0.02 0.02 0.09 0.11 0.02 0.04(0.06) (0.08) (0.15) (0.12) (0.28) (0.32) (0.13) (0.21)

Minimum Women Dietary Diversity

(at least 5 groups out of 9)

N/A 0.09 N/A 0.14 0.56 0.34

(0.29) (0.35) (0.50) (0.47)

a Mean (SD)

Gender inequalities in nutrition & diets vary by context & age (and girls are not always the disadvantaged ones)

Ethiopia India Peru Vietnam

-0.3-0.2-0.1

00.10.20.30.4

Differences (girls – boys) in se-lected nutrition indicators, YC, 12

years (2013)ZHFAZBMI-for-ageDietary diversity**

**

***

**

***

Diets are changing rapidly for 12-year-olds…

Estimates adjusted for: gender , birth order, caregiver's age, gender, years of schooling, head of the household gender and age, household size, place of residence, wealth indexSource: Aurino, Fernandes, Penny 2016, Public Health Nutrition

P=0.001

P=0.001

…With wide variation in their composition

Cross-cohort change in sugar consumption, 2006-2013, rural/urban

Estimates adjusted for: gender , birth order, caregiver's age, gender, years of schooling, head of the household gender and age, household size, place of residence, wealth indexSource: Aurino, Fernandes, Penny 2016, Public Health Nutrition

2016: FAO/FANTA/USAID launched a new dichotomous indicator (MDD-W): Whether or not women 15-49 years of age have consumed

at least five out of ten defined food groups the previous day or night.

Indicator developed to proxy micronutrient adequacy

Does the index predict ZHFA for girls at 12, 15 years and 19 old as well?

What’s the relation between diets and nutrition in adolescents?

Minimum dietary diversity predicts to adolescent girls’ height-for-age z-scores

12 years old (YC)

15 years old (OC)

19 years old (OC)

Bivariate correlation

Adjusted coefficienta

Bivariate correlation

Adjusted coefficienta

Bivariate correlation

Adjusted coefficienta

Minimum dietary diversity (5 out of 9 food groups)

0.173***

0.104*** 0.13*** 0.04 0.16*** 0.05

(0.043) (0.040) [0.04] [0.04] [0.04] [0.04]a Estimates adjusted for: age in months, number of meals, maternal age, overweight, height, household wealth index, urban residence , country

Does childhood nutrition predict the timing of puberty? Early puberty predicts some cancers, CVD, adolescent

health risk behaviours, and psychosocial disorders Hypothesis of in utero programming of timing of

menarche, but later nutrition may mediate this relation Direction of association between prenatal nutrition and

onset of puberty not always consistent

Absence of comparative evidence, particularly from high-malnutrition contexts

At 12 years old, about one third of the sample in India, Peru and Vietnam has reached puberty

Prenatal and subsequent changes in nutrition influence menarche

Fastest growth between one and 8 years

Fastest weight change between one and 8 years

Fastest growth between birth and one year

Fastest weight change between birth and one year

Low birthweight (<2500 gr)

60%

50%

60%

30%

-35%

Hazard of early menarche Multivariate Weibull model, pooled

sample (N=1,858) P<0.05

P<0.01

P<0.01

P<0.1

P<0.01

Estimates adjusted for: BMI at 8 years, first child, mother’s height, urban location at Round 1, wealth index at 8 years, consumption of: fruits and vegetables, meat & fish, eggs, legumes, milk & dairy at 8 years, country dummy

How about the new generation?

At 19 years, 15% OC girls have become mothers.We can examine the relation between their pre-pubertal and adolescent nutrition and their children’s health

We can also control for the adolescent’s mother nutrition, hence we have a three-generation model of nutrition

Nutrition during puberty is linked to offspring’s outcomes

  Birthweight Low Birthweighta

HAZ age 8 lowest tercile 26.34 [110.33] -0.06 [0.08]HAZ age 8 highest tercile 85.6 [114.68] -0.01[0.08]BAZ age 8 lowest tercile -94.31 [105.74] 0.05 [0.08]BAZ age 8 highest tercile 208.92** [104.45] -0.07 [0.07]Positive change in height ranking, 8-12 years 268.47** [119.26] -0.07 [0.08]Positive change in BMI ranking, 8-12 years -20.48 [120.26] -0.06 [0.09]Negative change in height ranking, 8-12 years 12.17 [107.55] 0.04 [0.08]Negative change in BMI ranking, 8-12 years -296.59**

[129.95] 0.01 [0.09]YL adolescent met minimum dietary diversity (ate 5 of 9 food groups), age 16 122.64 [98.24] -0.07 [0.07]

YL adolescent received prenatal care during pregnancy 378.78** [189.58] -0.12 [0.13]YL adolescent enrolled in school at age 16 213.26** [97.99] -0.05 [0.07]R-squared 0.34 0.17Notes: Regressions also control for: positive and negative percentile change in height and BMI between ages 12 and 16 and between ages 16 and 20, YL adolescent's age in months at first birth, an indicator for YL adolescent having entered puberty early, number of meals eaten at 16 years old, YL adolescent’s child is first born, YL adolescent prenatal health good (of 3 categories), YL adolescent child difficult labour, YL adolescent's mother's height, age, education and overweight, YL adolescent father’s completed grades of schooling, HH wealth index at 16, urban residence at 16, country dummies. Standard errors in brackets; *** p<0.01, ** p<0.05, * p<0.1. a Indicates coefficients are from linear probability model.

We are still “in progress”!

Limitations of YL for this type of research: Unobserved factors Difficult to provide “causal estimates” YL multi-purpose and not nutrition study

A lot of work still needs to be done: Longitudinal research can illuminate on physical, social

and economic trajectories of adolescent health in different settings

Thanks for your comments/feedback! e.aurino@imperial.ac.uk