3. Electronic Theses and Dissertations (ETDs) - All submissions
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Item Socioeconomic determinants of infant mortality in Kenya(2008-10-23T10:09:47Z) Mustafa, HishamBackground: This study examines the socioeconomic factors associated with infant and postneonatal mortality in Kenya and tries to quantify these associations in order to put those factors in ranked order so as to prioritize them in health policy plans aiming to decrease infant and postneonatal mortality. The study has used wealth index, mother’s highest educational level, mother’s occupation and place of residence as exposures of interest. Methods: The study uses analytical cross-sectional design through secondary data analysis of the 2003 Kenyan Demographic and Health Survey (KDHS) dataset for children. Series of logistic regression models were fitted to select the significant factors both in urban and rural areas and for infant and postneonatal mortality, separately, through the use of backward stepwise technique. Then the magnitude of the significance for each variable was tested using the Wald’s test, and hence the factors were ranked ordered according to their overall P-value. Results: After excluding non-singleton births and children born less than one year before the survey, a sample size of 4 495 live births was analyzed with 458 infants died before the first year of life giving IMR of 79.6 deaths per 1000 live births. After adjusting for all biodemographic and other health outcome determining factors, the analyses show no significant association between socioeconomic factors and infant mortality in both urban and rural Kenya. The exclusion of deaths that occurred in the first month of ages shows that risk of postneonatal (OR 3.09; CI: 1.29 – 7.42) mortality, in urban Kenya, were significantly higher for women working in agricultural sector than nonworking women. While in rural Kenya, the risk of postneonatal (OR 0.42; CI: 0.20 – 0.90) mortality were significantly lower for mothers with secondary school level of education than mothers with no education. Conclusions: There is lack of socioeconomic differentials in infant mortality in both urban and rural Kenya. However, breastfeeding, ethnicity and gender of the child in urban areas on one hand and breastfeeding, ethnicity and fertility factors on the other hand are the main predictors of mortality in this age group. Furthermore, results for postneonatal mortality show that level of maternal education is the single most important socioeconomic determinant of postneonatal mortality in urban Kenya while mother’s occupation is the single most important socioeconomic determinant of postneonatal mortality in rural areas. Other determinants of postneonatal mortality are ethnicity and gender of the child in urban areas, while in rural areas; the other main predictors are ethnicity, breast feeding and fertility factors.Item Factors associated with mortality from childhood malaria in Navrongo DSS Site, Ghana, 1995-2000(2008-05-15T08:14:38Z) Chalwe, Victor F.ABSTRACT: Background: Malaria is endemic throughout Ghana and continues to be a major public health concern especially among pregnant women and children under the age of five. The Ministry of Health (MoH) estimates that over the past ten years, there have been 2-3 million cases of malaria each year, representing 40 percent of outpatient cases, while severe malaria accounts for 33-36 percent of in-patients. Malaria also accounts for 25 percent of the deaths in children under the age of five (GHS, 2001). Correct identification of risk factors could focus interventions at reducing malaria mortality in children. Demographic Surveillance System (DSS) sites have been established and they generate high quality population based longitudinal health and demographic data. The DSS conduct Verbal Autopsies to determine probable causes of death. Objective: This study examines factors affecting childhood malaria mortality in Northern Ghana, using longitudinal data collected by the Navrongo DSS during the period 1995- 2000. It deals especially with the role of socioeconomic factors (mother’s education, family wealth index based on the possessions and housing characteristics and residence, and possession of bed net) and the demographic characteristics (child’s sex and age, and mother’s age). Design: Secondary data analysis of longitudinal data collected by the Navrongo Health Research Centre. Multinomial logistic regression was used to compare the relative risk in three groups of children i.e. those who died of Malaria and those who died of other causes to those who survived as base. Results: Overall, for the deaths due to malaria, older children (1-5years) had a higher risk (RRR 1.4, 95%CI 1.25-1.57 P <0.0001) of dying compared to the infants. Equally, children born of older mothers (maternal age at birth of child >30 years) had a higher risk (RRR 1.28, 95%CI 1.15-1.42 P <0.0001). However, maternal education and residence had a protective effect, with children born of mothers who had some education (RRR 0.79, 95%CI 0.67-0.93 P=0.004) and residing in urban area (RRR 0.61, 95%CI 0.46-0.82 P=0.001) having a lower risk. Similarly, those children whose families are in the highest wealth index had a lower risk (RRR 0.76, 95%CI 0.63-0.91 P=0.003). Interestingly, the same factors were associated with deaths occurring due to other causes, but with varying degree of association. Whereas sex of child was not associated with malaria deaths, being female offered a lower risk of dying from other causes (RRR 0.9, 95%CI 0.84-0.98 P=0.017). It was observed that children in the older age group (1-5 years) were at higher risk of dying (RRR 1.14, 95%CI 1.05-1.25 P=0.002) just as those born of older mothers (RRR 1.16, 95%CI 1.07-1.26 P <0.0001). Even in this group, maternal education (RRR 0.87, 95%CI 0.76-0.98 P=0.023), a higher wealth index (RR 0.87, 95%CI 0.77-0.99 P=0.032 and RRR 0.63 95%CI 0.54-0.73 P <0.0001 for the two highest categories of wealth indices respectively), and area of residence (RRR 0.67, 95%CI 0.55-0.83 P <0.0001) offered a reduction in the risk of dying. Conclusion: The study identified the risk factors (age and sex of the child and mother’s age, maternal education, wealth and residence of the family) associated with malaria mortality and other causes of death in childhood in northern Ghana and this should help formulate cost effective interventions such as health education.