GENERALIZED POISSON REGRESSION (GPR) MODEL ON STUNTING CASES IN EAST NUSA TENGGARA PROVINCE

Abstract

Stunting is a child development disorder due to chronic malnutrition and recurrent infections characterized by a height below average. The purpose of this study was to determine the Generalized Poisson Regression (GPR) model in stunting cases in East Nusa Tenggara Province and the factors that influence the incidence these events in 2022. The Generalized Poisson Regression method has been implemented to analyse the problem of overdispersion in the data. Data from the Central Bureau of Statistics (BPS) of East Nusa Tenggara Province is used. The data consits of the number of stunting cases in toddlers (Y), Percentage of Low Weight Infants (BBLR) (X1), Percentage of Toddlers Immunized with Complete Basis (X2), Percentage of Infants Exclusively Breastfed (X3), Number of Undernourished Toddlers (X4), Percentage of Poor People (X5) and Percentage of Access to Proper Sanitation (X6). Results showed that the Generalized Poisson Regression model is µ = exp(5.044 + 0.0005604X4 − 0.01173X6) with two predictor variables that significantly affect
stunting cases, namely the number of under-five malnourished children (X4) and the percentage of
access to proper sanitation (X6).