The links between agriculture diversity and child nutrition in rural Myanmar
Rammohan, Anu (1); Pritchard, Bill (2); Dibley, Michael (2) (2016). 'The links between agriculture diversity and child nutrition in rural Myanmar' Paper presented at the annual conference of the HDCA, Tokyo 2016.
Food and nutrition insecurity are among the world’s most pressing problems, with an estimated 843 million people world-wide classified as being undernourished (FAO, IFAD & WFP, 2013: 46). Undernourishment is a pivotal problem for international development because lack of nutrition leverages into other forms of deprivation that reinforce disadvantage. In particular, in many developing countries improvements in key nutritional indicators among rural populations are significantly lagging other measures of social and economic progress (FAO, WFP & IFAD, 2012). Research from India – where this has certainly been the case (Pritchard et al., 2013) – has proposed that the root of this problem is an agriculture-nutrition disconnect (Gillespie et al, 2012). In spite of the substantial scholarly attention and policy influence these arguments have recently garnered, their evidentiary base remains narrow (Ruel et al., 2013). Haddad (2013) and Pinstrup-Andersen (2013) have both recently argued that we do not have a comprehensive framework to explain what happens to household food and nutrition security as livelihoods change.
The aim of this paper is to analyse and empirically test the relationship between childhood nutrition and household agricultural production in rural Myanmar. Rural Myanmar provides an ideal location for testing the concept of the agriculture-nutrition disconnect, given its status as a mainly agrarian country that is simultaneously a net food exporter but with severe problems of rural poverty and malnutrition.
The data for this analysis comes from the 2013 Livelihoods and Food Security Trust Fund (LIFT) survey. The dataset surveyed 4000 households across 252 villages and collected detailed information on household socio-economic, demographic and labour market characteristics. The LIFT dataset has detailed information on the socio-economic and demographic characteristics of the households and for the purposes of our study, also has detailed information on food intakes, self-reported food security and anthropometric measures of children aged between 0-59 months. The primary unit of analysis is the individual child aged between 6- 59 months for whom complete information is available for all our variables of interest.
The two anthropometric measures of weight-for-height (a measure of wasting) and height-for-age (a measure of stunting) provide a cheap and simple assessment of a child’s nutrition status, and are considered to be good indicators of a child’s nutritional status. We estimate a series of regression models to explain stunting and wasting outcomes, and variation in height-for-age Z-scores among 1,067 children 0–59 months of age. Our results highlight regional variations in child nutrition, and find poor nutrition among children of different age groups correlated with variables such as household’s socioeconomic status, land ownership, agricultural yields, specific crop groups, and the consumption of own production.