1. The effect of paid maternity leave on early childhood growth in low and middle income countries Deepa Jahagirdar June 10, 2016 Canadian Society for Epidemiology and Biostatistics Student Conference

2. Child Malnutrition Poor long-term outcomes StuntingWasting Low height-for-age Low weight-for-height 161 million preventable evidence mainly around household/individual- level interventions lack of evidence for policy options

3. Policy intervention HAZ = height for age z score

4. How could maternity leave policies affect child growth? Childcare quality Vaccinations Increased birthweight Interaction with healthcare Attention Breastfeeding Dietary diversity

5. Outcome Height –for-age z score Exposure Legislated weeks of paid maternity leave DEFINITIONS Research Question What is the average effect of longer legislated paid maternity leave duration on child height –for-age z score?

6. DATA SOURCES MachEquity & WORLD Maternity Leave Policy Database Demographic and Health Surveys (DHS) 2000-2013 Country-level Individual-level World Development Indicators & Global Development Finance Country-level Country information Individual information

7. GENERAL STRATEGY The challenge of identifying policy effects Who represents the ‘counterfactual’? Substitute (‘Natural Policy’ experiment) Population 2Population 1 Gold standard (Randomized experiment)

8. GENERAL STRATEGY Time 1 Time 2 Average child outcome (z-score) Z1 Z2 Average child outcome (z-score) Z3 Z4 ‘treated’ ‘control’ Effect of interest = (Z2 - Z1) – (Z4 - Z3) ‘Difference-in-difference’ Z2 - Z1 = Change in child z-score under different maternity leave policies (at Time 1 and Time 2) Z4 – Z3 = Change in child z-score that would have occurred anyway (no maternity leave policy change) ‘treated’ ‘control’

9. GENERAL STRATEGY Parallel trends assumption Controlling for anything time-varying

10. Control countries: no maternity leave policy change Treated countries: at least one maternity leave policy change Lesotho, Bangladesh, Uganda, Zimbabwe, Zambia 33 countries 138 surveys from 38 DHS countries Sample: -children aged 5 years and younger -born 1996-2014 n=604,041

11. MATERNITY LEAVE CHANGES

12. MEAN HAZ SCORES PRE-POLICY The mean height-for-age z score pre-2006= -1.46 (SD = 1.60) in control countries -1.84 (SD=1.50) in treated countries (Parallel trends assumption) HAZ = height for age z score

13. METHOD Linear regression

14. CONFOUNDERS Maternal educational attainment Maternal literacy Maternal height Birth order Urban/rural residence Household socioeconomic status Interval between births Mother’s age at delivery Recent child illness Individual-levelCountry-level GDP per capita Female labour force participation Health expenditure per capita Total health expenditure Government effectiveness Urbanization Maternity leave durationChild growth X

15. RESULTS Main analysis Model i*Model ii**Model iii** Effect estimate [95% CI] -0.032 [-0.10, 0.04] -0.068 [-0.17, 0.04] -0.104 [-0.22, 0.00] *With fixed effects for country and birth year only **Model i, with further adjustment for individual-level confounders ***Model ii, with further adjustment for country-level confounders

16. RESULTS Sensitivity analyses Children assigned the legislated maternity leave in place two years BEFORE their birth year t = birth year Children assigned the legislated maternity leave in place two years AFTER their birth year

17. RESULTS Sensitivity analyses Beta = mean effect of a 1 month increase in legislated paid maternity leave on height for age z score FTE = full-time equivalent months paid maternity leave AnalysisBeta [95% CI] Main Analysis -0.104 [-0.22; 0.00] Restrict to under age 2s only -0.072 [-0.28; 0.13] Exclude height-for-age z score 2+ -0.088 [-0.18; 0.00] Using maternity leave full-time equivalent as the exposure -0.036 [-0.13; 0.05]

18. CONCLUSION Inconclusive finding on whether maternity leave improves child growth outcomes Other things to consider:  strong general increasing trend  the timing of stunting interventions  limitations

19. ACKNOWLEDGEMENTS MACHEquity program (2011-2016), which is funded by the Canadian Institutes of Health Research (FRN 115209), with complementary funding from the Gates Foundation. Dr Arijit Nandi Dr Sam HarperDr Jody Heymann Thank you deepa.jahagirdar@mail.mcgill.ca