Economic and Consumption Variables and Their Associations with Stunting Prevalence: A Provincial Analysis of the Indonesian Child Nutritional Status Survey 2019

Abstract

The study aims to analyze the relationship between economic and food consumption variables with stunting prevalence among Indonesian children. The unit of analysis for this cross-sectional study was secondary data set from 2019 for 34 provinces obtained from Statistics Indonesia, the Food Security Agency, and the Ministry of Health of the Republic of Indonesia. In the majority of provinces (88.24%) the stunting prevalence was still categorized as serious public health problem with the prevalence of 30% or higher. The economic outlook in 2019 showed an economic growth, decrease in Gini ratio and the unemployment rate in 34 provinces. However, the poverty rate was very diverse between provinces and concentrated in eastern Indonesia. There were 17 provinces that had higher food than non-food expenditures. There were 31 provinces with normal energy adequacy level and 28 with normal protein adequacy level. However, there was no provinces reached maximum score in Desirable Dietary Pattern (DDP) as the indicator for food diversity, signaling that none of the provinces achieved adequate diversity in food consumption in 2019. The multivariate linear regression with backward elimination technique showed that seven of independent variables were qualified for the final model with R2 of 0.7406. The three variables significantly correlated with stunting prevalence (p<0.05) were food expenditure, protein adequacy level, and DDP score. Hence, these variables can be categorized as causal factors for stunting at provincial level analysis which can feed the food and nutrition policy and its monitoring and evaluation strategy. However, further analysis is needed to determine the direct and indirect relationship between economic factors, food expenditure, and food consumption with the prevalence of stunting among children in Indonesia so that stunting prevention and alleviation programs can be more precise and optimal.

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