Survival parametric models to estimate the factors of under-five child mortality

Aims: Child survival status is one of the major health-related concerns in all over the developing countries. There are various socioeconomic, demographic, environmental, and proximate and biological factors which are responsible for under-five child mortality. Our aim was to find the significant factors among various responsible factors under study using parametric and semi-parametric models. Materials and Methods: In this article, National Family Health Survey (NFHS)-IV data is used state of Uttar Pradesh in India after authentication and permission. Cox regression analysis (semi-parametric model) was performed to obtain the significant role of variables. Parametric models (Weibull, exponential, log-logistic, and log-normal) were performed to estimate the survival. Results: By using the Cox regression model, it was found that socioeconomic, demographic (education level, women's age, and religion), and proximate and biological factors (women's age in years, total number of children ever born, birth in the last 5 years, number of living children, currently breastfeeding, smokers, desire for more children, size of child, delivery by cesarean section, antenatal care visits, and birth order) play a significant role in the context of under-five child mortality. Based on the Akaike Information Criterion's (32985.3) minimum value, the Weibull model was found to be best fitted among all the other parametric models. Conclusions: There is used different parametric models. It is found that Weibull model is best fitted among all models. The study concludes that child mortality influences by the different factors. The study suggests that public health researcher, clinicians, health policy makers and other demographer need to implement more health programs related to child health especially for the under-five year children.