The effects of social determinants on children's health outcomes in Bangladesh slums through an intersectionality lens: An application of multilevel analysis of individual heterogeneity and discriminatory accuracy (MAIHDA).

Proloy Barua, Eliud Kibuchi, Bachera Aktar, Sabrina Fatema Chowdhury, Imran Hossain Mithu, Zahidul Quayyum, Noemia Teixeira de Siqueira Filha, Alastair H Leyland, Sabina Faiz Rashid, Linsay Gray
Author Information
  1. Proloy Barua: BRAC James P Grant School of Public Health, BRAC University, Dhaka, Bangladesh. ORCID
  2. Eliud Kibuchi: MRC/CSO Social and Public Health Sciences Unit, University of Glasgow, Glasgow, United Kingdom. ORCID
  3. Bachera Aktar: BRAC James P Grant School of Public Health, BRAC University, Dhaka, Bangladesh.
  4. Sabrina Fatema Chowdhury: BRAC James P Grant School of Public Health, BRAC University, Dhaka, Bangladesh. ORCID
  5. Imran Hossain Mithu: BRAC James P Grant School of Public Health, BRAC University, Dhaka, Bangladesh.
  6. Zahidul Quayyum: BRAC James P Grant School of Public Health, BRAC University, Dhaka, Bangladesh.
  7. Noemia Teixeira de Siqueira Filha: Department of Health Sciences, University of York, York, United Kingdom.
  8. Alastair H Leyland: MRC/CSO Social and Public Health Sciences Unit, University of Glasgow, Glasgow, United Kingdom.
  9. Sabina Faiz Rashid: BRAC James P Grant School of Public Health, BRAC University, Dhaka, Bangladesh.
  10. Linsay Gray: MRC/CSO Social and Public Health Sciences Unit, University of Glasgow, Glasgow, United Kingdom.

Abstract

Empirical evidence suggests that the health outcomes of children living in slums are poorer than those living in non-slums and other urban areas. Improving health especially among children under five years old (U5y) living in slums, requires a better understanding of the social determinants of health (SDoH) that drive their health outcomes. Therefore, we aim to investigate how SDoH collectively affects health outcomes of U5y living in Bangladesh slums through an intersectionality lens. We used data from the most recent national Urban Health Survey (UHS) 2013 covering urban populations in Dhaka, Chittagong, Khulna, Rajshahi, Barisal, Sylhet, and Rangpur divisions. We applied multilevel analysis of individual heterogeneity and discriminatory accuracy (MAIHDA) to estimate the Discriminatory Accuracy (DA) of the intersectional effects estimates using Variance Partition Coefficient (VPC) and the Area Under the Receiver Operating Characteristic Curve (AUC-ROC). We also assessed the Proportional Change in Variance (PCV) to calculate intersectional effects. We considered three health outcomes: cough, fever, and acute respiratory infections (ARI) in U5y.We found a low DA for cough (VPC = 0.77%, AUC-ROC = 61.90%), fever (VPC = 0.87%, AUC-ROC = 61.89%) and ARI (VPC = 1.32%, AUC-ROC = 66.36%) of intersectional strata suggesting that SDoH considered do not collectively differentiate U5y with a health outcome from those with and without a health outcome. The PCV for cough (85.90%), fever (78.42%) and ARI (69.77%) indicates the existence of moderate intersectional effects. We also found that SDoH factors such as slum location, mother's employment, age of household head, and household's garbage disposal system are associated with U5y health outcomes. The variables used in this analysis have low ability to distinguish between those with and without health outcomes. However, the existence of moderate intersectional effect estimates indicates that U5y in some social groups have worse health outcomes compared to others. Therefore, policymakers need to consider different social groups when designing intervention policies aimed to improve U5y health outcomes in Bangladesh slums.

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Word Cloud

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