Disparities in quality of life by race, gender, and sexual orientation: An intersectional analysis of population-representative data in Gauteng, South Africa

Nicholas Metheny; Gabriel John Dusing; Pedzisai Ndagurwa; Sthembiso Pollen Mkhize

doi:10.1016/j.socscimed.2024.117651

Disparities in quality of life by race, gender, and sexual orientation: An intersectional analysis of population-representative data in Gauteng, South Africa

Soc Sci Med. 2024 Dec 21:366:117651. doi: 10.1016/j.socscimed.2024.117651. Online ahead of print.

Authors

Nicholas Metheny¹, Gabriel John Dusing², Pedzisai Ndagurwa³, Sthembiso Pollen Mkhize⁴

Affiliations

¹ Nell Hodgson Woodruff School of Nursing, 1520 Clifton Rd. NE, Atlanta, GA, 30322, USA; Division of Nursing and Midwifery, University of Cape Town, Observatory, Cape Town, 7935, South Africa.
² Faculty of Health, York University, 4700 Keele Street Toronto, ON, M3J 1P3, Canada; Li Ka Shing Knowledge Institute, St Michael's Hospital, 30 Bond St, Toronto, ON, M5B 1W8, Canada. Electronic address: gabrieljdusing@gmail.com.
³ Gauteng City-Region Observatory, University of Johannesburg, University of the Witwatersrand, 11 Jorissen Street, Johannesburg, South Africa.
⁴ Gauteng City-Region Observatory, University of Johannesburg, University of the Witwatersrand, 11 Jorissen Street, Johannesburg, South Africa; School of Geographical Sciences, University of Bristol, University Road, Bristol, BS8 1SS, UK.

PMID: 39721164
DOI: 10.1016/j.socscimed.2024.117651

Abstract

Background: South Africa's history of apartheid has led to persistent inequalities. While progress has been made since 1994, disparities in quality of life (QoL) remain, particularly along racial lines. This study examines how race, gender, and sexual orientation intersect to influence QoL in Gauteng - South Africa's most populous and economically vibrant province.

Methods: Using data from the Gauteng City-Region Observatory's QoL 6 (2020/2021) Survey, we analyzed a sample of 10,760 respondents. We employed inverse probability weighting with regression adjustment (IPWRA) to estimate the Average Treatment Effect (ATE) of race, gender, and sexual minority status on QoL, while controlling for socioeconomic factors.

Results: Significant QoL disparities were observed across intersecting identities. White heterosexual men had the highest QoL scores, while Black sexual minority women had the lowest. After adjusting for covariates, all Black groups exhibited significantly lower QoL scores compared to their White counterparts. The largest gap was between White sexual minority women and Black sexual minority men (ATE: -14.47; 95%CI: -17.18,-11.76). Within the Black population, heterosexual men had significantly higher QoL than heterosexual women (ATE: -0.98; 95%CI: -1.54, -0.42).

Conclusions: Despite progress since apartheid, substantial QoL disparities persist in Gauteng, primarily along racial lines, particularly in access to services and socio-economic opportunities. The intersectionality of race, gender, and sexual orientation creates distinct vulnerabilities, particularly for Black sexual minority women. These findings suggest that current policies aimed at improving equity may be insufficient. Addressing these disparities requires a multifaceted approach that considers the complex interplay of race, gender, and sexual orientation in shaping QoL.