Department of Statistics
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Item Foreign aid-Economic Growth Nexus in Africa: Does Financial Development Matter?(International Economic Journal, 2022) Appiah-Otoo, I.; Appiah, I.K.; Acheampong, A.O.; et al.This study explored the role of financial development in foreign aid (measured by agriculture, humanitarian, health, economic infrastructure and services, and education aid) and economic growth relationships for 37 African countries spanning the 2002–2018 period. Using the instrumental variable generalized method of moments model, our findings indicated that while foreign aid impedes Africa’s growth, financial development spurs economic growth. The conditional effect analysis showed that financial development conditions foreign aid to spur economic growth. The country-specific analysis further showed that foreign aid has a higher growth elasticity in countries with relatively better financial systems, such as Mauritius, South Africa, Gabon, Tunisia, and Botswana, whilst the growth elasticity of aid is smaller in countries with a relatively weak financial system, such as Malawi, Guinea-Bissau, Sierra Leone, and the Democratic Republic of Congo. The study recommended the need for for policymakers in Africa to implement innovative ways to improve domestic revenue mobilization. The study also recommended that policymakers in Africa should create an enabling environment that will enhance the development of Africa’s financial system to mitigate the adverse effect of aid on economic growth.Item Characterization of Healthy Housing in Africa: Method, Profiles, and Determinants(Journal of Urban Health, 2022) Iddi, S.; Muindi, K.; Gitau, H.; Mberu, B.Housing is a key social determinant of health, with implications for both physical and mental health. The measurement of healthy housing and studies characterizing the same in sub-Saharan Africa (SSA) are uncommon. This study described a methodological approach employed in the assessment and characterization of healthy housing in SSA using the Demographic and Health Survey (DHS) data for 15 countries and explored healthy housing determinants using a multiple survey-weighted logistic regression analysis. For all countries, we demonstrated that the healthy housing index developed using factor analysis reasonably satisfied with both reliability and validity tests and can therefore be used to describe the distribution of healthy housing across different groups and in understanding the linkage with individual health outcomes. We infer from the results that unhealthy housing remains quite high in most SSA countries. Having a male head of household was associated with decreased odds of healthy housing in Burkina Faso (OR = 0.80, CI = 0.68–0.95), Cameroon (OR=0.65, CI=0.57, 0.76), Malawi (OR=0.70, CI=0.64–0.78), and Senegal (OR=0.62, CI=0.51– 0.74). Further, increasing household size was associated with reducing odds of healthy housing in Kenya (OR=0.53, CI=0.44–0.65), Namibia (OR=0.34, CI=0.24–0.48), Nigeria (OR=0.57, CI=0.46–0.71), and Uganda (OR=0.79, CI=0.67–0.94). Across In all countries, household wealth was a strong deterrent of healthy housing, with middle and rich households having higher odds of residing in healthy homes compared to poor households. Odds ratios ranged from 3.63 (CI = 2.96–4.44) for households in the middle wealth group in the DRC to 2812.2 (CI = 1634.8–4837.7) in Namibia’s wealthiest households. For other factors, the analysis also showed variation across countries. Our findings provide timely insights for the implementation of housing policies across SSA countries, drawing attention to aspects of housing that would promote occupant health and wellbeing. Beyond the contribution to the measurement of healthy housing in SSA, our paper highlights key policy and program issues that need further investigation in the search for pathways to addressing the healthy housing demand across most SSA countries. This has become critical amid the COVID-19 pandemic, where access to healthy housing is pivotal in its control.Item Housing and health outcomes: evidence on child morbidities from six Sub-Saharan African countries(BMC Pediatrics, 2023) Muindi, K.; Iddi, S.; Gitau, H.; Mberu, B.Background The connection between healthy housing status and health is well established. The quality of housing plays a significant role in infectious and non-communicable as well as vector-borne diseases. The global burden of disease attributable to housing is considerable with millions of deaths arising from diarrheal and respiratory diseases annually. In sub-Saharan Africa (SSA), the quality of housing remains poor although improvements have been documented. There is a general dearth of comparative analysis across several countries in the sub-region. We assess in this study, the association between healthy housing and child morbidity across six countries in SSA. Methods We use the Demographic and Health Survey (DHS) data for six countries where the most recent survey collected health outcome data on child diarrhoea, acute respiratory illness, and fever. The total sample size of 91,096 is used in the analysis (representing 15, 044 for Burkina Faso, 11, 732 for Cameroon, 5, 884 for Ghana, 20, 964 for Kenya, 33, 924 for Nigeria, and 3,548 for South Africa). The key exposure variable is healthy housing status. We control for various factors associated with the three childhood health outcomes. These include quality housing status, residency (rural/urban), age of the head of the household, mother’s education, mother’s BMI status, marital status, mother’s age, and religious status. Others include the child’s gender, age, whether the child is from multiple or single births, and breastfeeding status. Inferential analysis using survey-weighted logistic regression is employed. Results Our findings indicate that housing is an important determinant of the three outcomes investigated. Compared to unhealthier housing, healthy housing status was found to be associated with reduced odds of diarrhoea in Cameroon [Healthiest: aOR=0.48, 95% CI, (0.32,0.71), healthier: aOR=0.50, 95% CI,(0.35,0.70), Healthy: aOR=0.60, 95% CI, (0.44,0.83), Unhealthy: aOR=0.60, 95% CI, (0.44,0.81)], Kenya [Healthiest: aOR=0.68, 95% CI, (0.52,0.87), Healtheir: aOR=0.79, 95% CI, (0.63,0.98), Healthy: aOR=0.76, 95% CI, (0.62,0.91)], South Africa[Healthy: aOR=0.41, 95% CI, (0.18, 0.97)], and Nigeria [Healthiest: aOR=0.48, 95% CI,(0.37,0.62), Healthier: aOR=0.61, 95% CI,(0.50,0.74), Healthy: aOR=0.71, 95%CI, (0.59,0.86), Unhealthy: aOR=0.78, 95% CI, (0.67,0.91)], and reduced odds of Acute Respiratory Infection in Cameroon [Healthy: aOR=0.72, 95% CI,(0.54,0.96)], Kenya [Healthiest: aOR=0.66, 95% CI, (0.54,0.81), Healthier: aOR=0.81, 95% CI, (0.69,0.95)], and Nigeria [Healthiest: aOR=0.69, 95% CI, (0.56,0.85), Healthier: aOR=0.72,95% CI, (0.60,0.87), Healthy: aOR=0.78, 95% CI, (0.66,0.92), Unhealthy: aOR=0.80, 95% CI, (0.69,0.93)] while it was associated with increased odds in Burkina Faso [Healthiest: aOR=2.45, 95% CI, (1.39,4.34), Healthy: aOR=1.55, 95% CI, (1.09,2.20)] and South Africa [Healthy: aOR=2.36 95% CI, (1.31, 4.25)]. In addition, healthy housing was significantly associated with reduced odds of fever among children in all countries except South Africa [Healthiest: aOR=2.09, 95% CI, (1.02, 4.29)] where children living in the healthiest homes had more than double the odds of having fever. In addition, household-level factors such as the age of the household head, and place of residence were associated with the outcomes. Child-level factors such as breastfeeding status, age, and sex, and maternal-level factors such as education, age, marital status, body mass index (BMI), and religion were also associated with the outcomes. Conclusions The dissimilarity of findings across similar covariates and the multiple relations between healthy housing and under 5 morbidity patterns show unequivocally the heterogeneity that exists across African countries and the need to account for different contexts in efforts to seek an understanding of the role of healthy housing in child morbidity and general health outcomes