Does economic growth reduce childhood stunting? A multicountry analysis of 89 Demographic and Health Surveys in sub-Saharan Africa

Dados Bibliográficos

ID21878458
AutoresSanni Yaya (0000-0002-4876-6043, University of Ottawa, autor correspondente), Olalekan Abdulrahman Uthman (0000-0002-8567-3081, University of Warwick), Michael Kunnuji (0000-0001-5108-5639, University of Lagos), K Navaneetham (0000-0002-5847-4669, University of Botswana), Joshua Akinyemi (0000-0002-0675-2110, University of Ibadan), Joshua O Akinyemi (University of Ibadan), Rornald Muhumuza Kananura (0000-0002-9915-1989, London School of Economics and Political Science), Vissého Adjiwanou (0000-0003-0892-3021, Université du Québec à Montréal), Olatunji Adetokunboh (0000-0002-4608-3951, Stellenbosch University), Bishwajit Ghose (0000-0003-4461-3821, University of Ottawa), Ghose Bishwajit (University of Ottawa)
Ano2020
Volume5
Fascículo1
Páginase002042
Data de publicação2020-01-01
Peer ReviewedSim
Open AccessSim
TipoARTICLE
PeriódicoBMJ Global Health (JOURNAL)
Identificadores do periódicoISSN: 2059-7908 • E-ISSN: 2059-7908
EditoraBMJ (PUBLISHER • GB)
DOI10.1136/bmjgh-2019-002042
PMID32133174
OpenAlexW3001070178
IdiomaEN
Citações recebidas10
Referências citadas63

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

Economic growth · Economics · Environmental health · Gross domestic product · Logistic regression · Odds · Per capita · Population · Breastfeeding Practices and Influences · Child Nutrition and Water Access · Demography · Medicine · Poverty, Education, and Child Welfare