Estimating the trends of childhood mortality indicators and effects of its determinants
a case study of Cameroon
From independence in 1960 up to 2010, Cameroon has adopted different development plans, ranging from a series of six five years development plans to the Growth and Employment Strategy Paper whose implementation started in 2010. The implementations of these plans have let Cameroon through all the phases of a typical business cycle. It is assumed that each phase had different impacts on Childhood Mortality Indicators and its Covariates. This study sought to evaluate the trends of childhood mortality indicators and the impacts of their determinants on the trends in each of the four Demographic Health Surveys (DHS) conducted in Cameroon respectively in 1991, 1998, 2004 and 2011.
Using survival models (synthetic cohort life tables), we estimated four Childhood Mortality indicators (PNMR, NMR, IMR, and U5MR) for each of the four DHS datasets. Besides, we used both univariate and multivariate Cox Proportional Hazard Models and the Stratified Cox procedure to investigate the impacts of 29 determinants on each of the four childhood mortality indicators considered.
We obtained the following mortality rates per 1000 live births; for the 1991 dataset PNMR is 22.6, NMR is 36.2, IMR is 58.8 and U5MR is 120.4. For the 1998 dataset; PNMR is 25.5, NMR is 36.5, IMR is 62 and U5MR is 138.1. For the 2004 dataset; PNMR is 29.8, NMR is 33.1, IMR is 62.9 and U5MR is 141.2. And lastly for the 2011 dataset; PNMR is 19.4, NMR is 32, IMR is 51.4 and U5MR is 117.2. The results also show that the most consistent determinants of childhood mortality across the four surveys includes; Child Vaccination Status, Mothers’ Number of Birth, Mothers’ Current Marital Status, Mothers’ Level of Education, Mothers’ Preceding Birth Interval, Where The Child Is Raised, Mothers’ Current Age, and Mothers Age At First Birth.
Results from univariate analysis revealed that on average the trend of the 29 determinants improved significantly across the four surveys. However, multivariate analysis shows that the magnitude and direction of the correlation in most cases were found to fluctuate from one dataset to another as outlined in chapter four.
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