Multilevel Survival Analysis of Factors Associated with Under-Five Mortality in Manipur

ABSTRACT

Background: Child mortality is a major public health issue. The studies on under‑five mortality that ignore the hierarchical facts mislead the interpretation of the results due to observations in the same cluster sharing common cluster‑level random effects. Objectives: The present study uses a multilevel model to analyze under‑five mortality and identify the significant factors for under‑five mortality in Manipur. Methods: National Family Health Survey‑5 (2019–21) data are used in the present study. Amultilevel mixed‑effect Weibull parameter survival model was fitted to determine the factors affecting under‑five mortality. We construct three‑level data, individual levels are nested within primary sampling units (PSUs), and PSUs are nested within districts. Results: Out of the 3225 under‑five children, 85 (2.64%) died. The three‑level mixed‑effects Weibull parametric survival model with PSUs nested within the districts, the likelihood‑ratio test with Chi‑square value = 10.98 and P = 0.004 < 0.05 indicated that the model with random‑intercept effects model with PSUs nested within the districts fits the data better than the fixed effect model. The four covariates, namely the number of birth in the last 5 years, age of mother at first birth, use of contraceptive, and size of child at birth, were found as the risk factor for under‑five mortality at a 5% level of significance. Conclusions: In the random‑intercept effect model, the two estimated variances of the random‑intercept effects for district and PSU levels are 0.27 and 0.31, respectively. The values indicate variations (unobserved heterogeneities) in the risk of death of the under‑five children between districts and PSUs levels.