Browsing by Author "Yaya, Sanni"

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    Does economic growth reduce childhood stunting? a multicountry analysis of 89 demographic and health surveys in sub-Saharan Africa
    (BMJ Publishing, 2020-01) Yaya, Sanni; Uthman, Olalekan A.; Kunnuji, Michael; Navaneetham, Kannan; Akinyemi, Joshua O.; Kananura, Rornald Muhumuza; Adjiwanou, Visseho; Adetokunboh, Olatunji; Bishwajit, Ghose
    Background: There is mixed evidence and lack of consensus on the impact of economic development on stunting, and likewise there is a dearth of empirical studies on this relationship in the case of sub-Saharan Africa. Thus, this paper examines whether economic growth is associated with childhood stunting in low-income and middle-income sub-Saharan African countries. Methods: We analysed data from 89 Demographic and Health Surveys conducted between 1987 and 2016 available as of October 2018 using multivariable multilevel logistic regression models to show the association between gross domestic product (GDP) per capita and stunting. We adjusted the models for child’s age, survey year, child’s sex, birth order and country random effect, and presented adjusted and unadjusted ORs. Results: We included data from 490 526 children. We found that the prevalence of stunting decreased with increasing GDP per capita (correlation coefficient=−0.606, p<0.0001). In the unadjusted model for full sample, for every US$1000 increase in GDP per capita, the odds of stunting decreased by 23% (OR=0.77, 95% CI 0.76 to 0.78). The magnitude of the association between GDP per capita and stunting was stronger among children in the richest quintile. After adjustment was made, the association was not significant among children from the poorest quintile. However, the magnitude of the association was more pronounced among children from low-income countries, such that, in the model adjusted for child’s age, survey year, child’s sex, birth order and country random effect, the association between GDP per capita and stunting remained statistically significant; for every US$1000 increase in GDP per capita, the odds of stunting decreased by 12% (OR=0.88, 95% CI 0.87 to 0.90). Conclusion: There was no significant association between economic growth and child nutritional status. The prevalence of stunting decreased with increasing GDP per capita. This was more pronounced among children from the richest quintile. The magnitude of the association was higher among children from low-income countries, suggesting that households in the poorest quintile were typically the least likely to benefit from economic gains. The findings could serve as a building block needed to modify current policy as per child nutrition-related programmes in Africa.
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    Epidemiology of multimorbidity among people living with HIV in sub-Saharan Africa : a systematic review protocol
    (BMJ Publishing, 2020-12) Oladimeji, Kelechi Elizabeth; Dzomba, Armstrong; Adetokunboh, Olatunji; Zungu, Lindiwe; Yaya, Sanni; Ter Goon, Daniel
    Introduction: Sub-Saharan Africa remains the epicentre of the HIV pandemic, yet enormous knowledge gaps still exist to elicit a comprehensive portrait of multimorbidity and HIV linkage. This study aims to conduct a systematic meta-analysis of peer-reviewed literature to investigate the current status of multimorbidity epidemiology among people living with HIV (PLHIV) in sub-Saharan Africa. Methods and analysis: Our review will assess observational studies (ie, cohort, case–control and cross-sectional) on multimorbidity associated with HIV/AIDS between 1 January 2005 and 31 October 2020 from sub-Saharan Africa. Databases to be searched include PubMed/MEDLINE, Scopus, Web of Science, Cochrane library, African Index Medicus and African Journals Online. We will also search the WHO clinical trial registry and databases for systematic reviews. The search strategy will involve the use of medical subject headings and key terms to obtain studies on the phenomena of HIV and multimorbidity at high precision. Quality assessment of eligible studies will be ascertained using a validated quality assessment tool for observational studies and risk of bias through sensitivity analysis to identify publication bias. Further, data on characteristics of the study population, multimorbid conditions, epidemiological rates and spatial distribution of multimorbid conditions in PLHIV will be extracted. Heterogeneity of individual studies will be evaluated using the I2 statistic from combined effect size estimates. The statistical analysis will be performed using STATA statistical software V.15 and results will be graphically represented on a forest plot.