Original Research

Age, gender and household infrastructural inequality in COVID-19: Contextual analysis of Mamelodi

Simon M. Marcus, Caitlin V. Gardiner
South African Family Practice | Vol 66, No 1 : Part 3| a5924 | DOI: https://doi.org/10.4102/safp.v66i1.5924 | © 2024 Simon M. Marcus, Caitlin V. Gardiner | This work is licensed under CC Attribution 4.0
Submitted: 06 February 2024 | Published: 22 July 2024

About the author(s)

Simon M. Marcus, Department of Family Medicine, Faculty of Health Science, University of the Witwatersrand, Johannesburg, South Africa
Caitlin V. Gardiner, Department of Global Health and Social Medicine, King’s College, London, United Kingdom; and, SAMRC/Wits Developmental Pathways for Health Research Unity, Department of Paediatrics, School of Clinical Medicine, University of the Witwatersrand, Johannesburg, South Africa

Abstract

Background: Age, gender and household infrastructure are important social determinants affecting health inequalities. This study aims to assess the ways that age and gender of the household head and household infrastructure intersect to create relative advantage and disadvantage in COVID-19 vulnerability.

Methods: Using household primary care survey data from Mamelodi, Gauteng, headed households were sorted into three risk categories for each of the relevant infrastructural determinants of COVID-19. Bivariate ordinal logistic regression was used to determine the odds of households falling into each risk category. The proportion of high-risk (HR) categories and dwelling types was also calculated.

Results: Households headed by someone ≥ 65 years were less likely to be in all HR categories and more frequently had formal houses. Male-head households were more likely to be HR for water, sanitation and hygiene infrastructure and indoor pollution; however, female-headed households (FHHs) were at higher risk for crowding. In Mamelodi, households headed by ≥ 65 years olds were relatively infrastructurally protected, likely because of pro-equity housing policy, as were FHHs, except for crowding. The care load on FHHs results in their infrastructural protection benefiting more community members, while simultaneously incurring risk.

Conclusion: Infrastructural support based on the household head’s age and gender could improve targeting and the effectiveness of health interventions. These results demonstrate the importance of a contextual understanding of gender and age inequalities and tailoring public health support based on this understanding.

Contribution: This research describes patterns of health-related infrastructural inequality, identifies ways to improve health interventions, and demonstrates the importance of equity-focused policy in an African context.

 


Keywords

social determinants of health; LMICs; urban health; health inequalities; vulnerable populations; health policy

Sustainable Development Goal

Goal 5: Gender equality

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