ABSTRACT
Though India’s rank has improved in the recent Global Hunger Index, contributed largely by the fall in the underweight rates and stunting rates, for children, concerns of high level of undernutrition in rural pockets remain. This moderate nutrition improvement was apparent after the NFHS-4 data was released. Looking back is useful, to strategise future action. This chapter aims at linking child underweight rates to agricultural land productivity, a proxy for agricultural prosperity, and to the provisioning of public services, using district level two data (DLHS-2) in the first quinquennium of the twenty-first century. It examines determinants of agricultural productivity on one hand and child underweight on the other. The study overcomes the limitation of non-availability of agriculture-related information in most household-level nutrition surveys faced by empirical studies with district-level analysis, that enables combining of data from different sources on nutrition, agriculture and public provisioning.
The study estimates a three-stage least squares (3SLS) model with a log-linear specification. Unlike many earlier studies, the results indicate a possible positive relationship between agricultural land productivity and child underweight rates. Unlike other studies that consider only the net area sown, agricultural productivity calculations use cultivable land and crop-livestock district GDP at constant prices averaged over three years. Cultivable land includes fallows, grazing lands cultivable waste such as bushes, grooves, water puddles etc., in addition to net area sown.
Agricultural land productivity equations clearly show that rainfall, irrigation, percentage of non-food crops, food abundance in terms of triennium average food production per capita, and percentage of women education above secondary level (also a proxy for men’s education) significantly influence agricultural land productivity per hectare at constant prices in value terms at the district level. Land operational inequality has a negative influence on land productivity but not significant. Rainfall, per capita foodgrain production and women’s education above secondary level have higher elasticity with respect to land productivity. The agro-climatic zonal dummies are all significant when we take central plateau hill region with lowest productivity as the reference zone.
The second equation explains factors influencing the percentage of children under six with normal status (the remaining children after deducting the percentage of underweight children from 100). Agricultural land productivity per hectare, percentage of women with secondary education show significant positive influence on percentage of children who are not underweight. Prevalence of anaemia among pregnant women, households without access to toilets, and prevalence of childhood diarrhoea among children below three years had significant negative influence on percentage of normal status of children.
Public services that influence child nutrition appear to be immunisation program, population with access to any government health facility, and offtake of foodgrain for public distribution among the poor have all shown significant positive influence on children with normal weight for age status. The main conclusion is that agriculture productivity child nutrition links as well as public provisioning links to improved child nutrition were apparent more than a decade ago but neglected in policy circles for future action.
