Apoorva Nambiar, Indian Institute of Technology Bombay
Satish B Agnihotri, Indian Institute of Technology Bombay
Arunachalam Dharmalingam, Monash University
Ashish Singh, School of Management, Indian Institute of Technology
There is a strong need for micro-level data and integration of GIS tools to identify pockets of low-high levels of undernutrition and to study the problem in a nuanced way. This will enable customized and evidence-based planning to produce malnutrition free enclaves with consequent ripple effect. Hence, the study aims to conduct a region-specific analysis for an Indian state having high rates of undernourished children. Data from the Concurrent Monitoring survey at the sub-district level and the district-level National Family Health Survey data were analysed. Various spatial analysis techniques were applied to understand the spatial heterogeneity at the micro-level. Multiple spatial regression models were used to examine the spatial correlates at the sub-district level. Logistic regression models, poor-rich ratio and concentration indices, were measured to understand the economic inequalities with respect to underweight in children and to estimate the adjusted effect of various socio-economic determinants of undernutrition specific to the emerging clusters within the state. Results indicated that given the sheer regional diversity in India, both in terms of child undernutrition as well as its correlates, there is a strong need to develop a region-specific evidence-base at the micro level to develop a plan of action for eliminating child malnutrition.
Keywords: Data visualisation, Demographic and social surveys, Spatial analysis/regression, Spatial statistics
Presented in Session 3. Undernutrition Among Children and Adolescents in India: From Micro- to Macro-Level Variations