Working Paper 10. Young Lives: A Case Study of Sample Design for Longitudinal Research
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‘The bigger the better’ – mothers' social networks and child nutrition in Andhra Pradesh
Abstract Objective It is hypothesised that mothers' social networks can positively affect child nutrition through the sharing of health knowledge and other resources. The present study describes the composition of mothers' networks, examines their association with child nutrition, and assesses whether health knowledge is shared within networks. Design and setting Cross-sectional data for mothers of young children from Andhra Pradesh (south India) were combined with existing data from the Young Lives study, in which the mothers were participating (n = 282). Results The composition of social networks varied between urban and rural areas, with urban networks being larger, more female, more literate and with a greater proportion of members living outside the household and being non-family. There was a positive association between child's height-for-age Z-score and mother's network size and network literacy rate. The association with network literacy was stronger among the poorest households. Women commonly reported seeking or receiving health advice from network members. Conclusion Big and literate social networks are associated with better child nutrition, especially among the poor. The dissemination of health knowledge between network members is a plausible way in which social networks benefit child nutrition in India. Further research into the underlying mechanisms is necessary to inform the development of interventions that channel health information through word of mouth to the most excluded and vulnerable families.
Panel Attrition from the Panel Study of Income Dynamics Household Income, Marital Status, and Mortality
This analysis is concerned with the determinants of panel attrition from the Panel Study of Income Dynamics and with its consequences for estimation of dynamic behavioral models which exploit the panel or longitudinal information-household income dynamics, marriage formation and dissolution, and adult mortality risk. We develop and estimate joint models of attrition and one or more of these substantive processes, and allow for correlation across the equations through random effects. Although we find evidence of significant selectivity in attrition behavior, the biases that are introduced by ignoring selective attrition are very mild.