International Journal for Equity in Health (Jun 2024)

Neighbourhood effect and inequality in access to essential health services among mother–child paired samples: a decomposition analysis of data from 58 low- and middle-income countries

  • Seun Anjorin,
  • Elvis Anyaehiechukwu Okolie,
  • Chinwe Onuegbu,
  • Mukhtar Ijaiya,
  • Abimbola Ayorinde,
  • Oyinlola Oyebode,
  • Olalekan Uthman

DOI
https://doi.org/10.1186/s12939-024-02194-4
Journal volume & issue
Vol. 23, no. 1
pp. 1 – 11

Abstract

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Abstract Introduction Neighbourhood effect on health outcomes is well established, but little is known about its effect on access to essential health services (EHS). Therefore, this study aimed to assess the contributing factors to access to EHS in slum versus non-slum settings. Methodology The most recent data from 58 Demographic and Health Surveys (DHS) conducted between 2011 and 2018 were used, including a total of 157,000 pairs of currently married women aged 15–49 and their children aged 12–23 months. We used meta-analysis techniques to examine the inequality gaps in suboptimal access to EHS between mother-children pairs living in slums and non-slums. Blinder-Oaxaca decomposition technique was used to identify the factors contributing to the inequality gaps in each low- and middle-income country (LMIC) included. Result The percentage of mother–child pairs living in slums ranged from 0.5% in Egypt to 63.7% in Congo. Meta-analysis of proportions for the pooled sample revealed that 31.2% [27.1, 35.5] of slum residents and 20.0% [15.3, 25.2] among non-slum residents had suboptimal access to EHS. We observed significant pro-slum inequalities in suboptimal access to EHS in 28 of the 52 LMICs with sufficient data. Of the 34 African countries included, 16 showed statistically significant pro-slum inequality in suboptimal access to EHS, with the highest in Egypt and Mali (2.64 [0.84–4.44] and 1.76 [1.65, 1.87] respectively). Findings from the decomposition analysis showed that, on average, household wealth, neighbourhood education level, access to media, and neighbourhood-level illiteracy contributed mostly to slum & non-slum inequality gaps in suboptimal access to EHS. Conclusion The study showed evidence of inequality in access to EHS due to neighbourhood effects in 26 LMICs. This evidence suggests that increased focus on the urban poor might be a important for increasing access to EHS and achieving the universal health coverage (UHC) goals.