Fine and Gray competing risk regression model to study the cause-specific under-five child mortality in Bangladesh.

BACKGROUND: The cause-specific under-five mortality of Bangladesh has been studied by fitting cumulative incidence function (CIF) based Fine and Gray competing risk regression model (1999). For the purpose of analysis, Bangladesh Demographic and Health Survey (BDHS), 2011 data set was used. METHODS: Three types of mode of mortality for the under-five children are considered. These are disease, non-disease and other causes. Product-Limit survival probabilities for the under-five child mortality with log-rank test were used to select a set of covariates for the regression model. The covariates found to have significant association in bivariate analysis were only considered in the regression analysis. RESULTS: Potential determinants of under-five child mortality due to disease is size of child at birth, while gender of child, NGO (non-government organization) membership of mother, mother's education level, and size of child at birth are due to non-disease and age of mother at birth, NGO membership of mother, and mother's education level are for the mortality due to other causes. CONCLUSION: Female participation in the education programs needs to be increased because of the improvement of child health and government should arrange family and social awareness programs as well as health related programs for women so that they are aware of their child health.

Log-Logistic Proportional Odds Model for Analyzing Infant Mortality in Bangladesh.

Log-logistic parametric survival regression model has been used to find out the potential determinants of infant mortality in Bangladesh using the data extracted from Bangladesh Demographic and Health Survey, 2011. First, nonparametric product-limit approach has been used to examine the unadjusted association between infant mortality and covariate of interest. It is found that maternal education, membership of nongovernmental organizations, age of mother at birth, sex of child, size of child at birth, and place of delivery play an important role in reducing the infant mortality, adjusting relevant covariates.