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Modeling the determinants of under-five mortality using logit regression
(2014-10-16) Boachie-Yiadom, Sampson
Child mortality, also known as under-five mortality refers to the death of infants and children under age of five. The objectives of this thesis are to identify the significant determinants of under-five mortality, set up a logit model and use it to predict under-five mortality in the Tano South district of Ghana. The district was divided into four zones and the target populations were identified using the purposive sampling. A total sample size of 200 mothers or caregivers was used, of which 50 were selected randomly from each zone. Binary logit regression was the main statistical tool for the analysis of data. The results revealed that higher parity, in particular grandmultigravidae parity has adverse significant impact on under-five mortality. Among the diseases, both anaemia and malaria showed adverse significant impact on under-five mortality. However, while there are factors that adversely impact on under-five mortality, others such as the use of treated bed net, child vaccine, not exclusive and exclusive breast feeding reduce its likelihood. It is therefore recommended that more education and sensitization on precautionary measures and good health should be given to mothers, especially mothers of grandmultigravidae parity. Additionally, education on the use treated bed-nets in the homes of mothers should be intensified.