Non-Linear Effects of Continuous Predictors on Malnutrition Status of Children in Bangladesh


  • Tasmiah Sad Sutopa Department of Statistics, University of Dhaka
  • Wasimul Bari Department of Statistics, University of Dhaka



Child’s age, Generalized additive regression model, Malnutrition, Mother’s age, Mother’s BMI, Non-linear effect, Stunting.


Background: To explore non-linear effects of continuous covariates on response variable, generalized additive model (GAM) has now been extensively used. The main aim of this study is to explore the non-linear effect of some selected continuous covariates on malnutrition status of children in Bangladesh using logistic additive model.

Methods: To determine the factors of malnutrition status of children in Bangladesh, data are excluded from Bangladesh Demographic and Health survey 2014 (BDHS 2014). The anthropometric index of nutrition status, stunting is used as binary response variable and several demographic, socio-economic and health related variables are used as covariates. Bivariate analysis and additive logistic regression model is used to uncover the non-linear effect of included continuous variables as well as effect of categorical covariates on stunting in the study.

Results: The analysis exposes that mother’s current age, mother’s BMI and child’s age have significant non-linear impact on stunting of children.

Conclusion: The analysis suggests that to improve nutrition status of children in Bangladesh, the government should take necessary steps targeting women in higher and lower age groups and women with higher and lower BMI. Moreover, the children after 20 months should be properly taken care of for achieving better nutritional health.


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