Cumulative social disadvantage and health-related quality of life: national health interview survey 2013-2017

Kobina Hagan, Division of Health Equity and Health Disparities Research, Center for Outcomes Research, Houston Methodist, Houston, TX, USA.
Zulqarnain Javed, Division of Health Equity and Health Disparities Research, Center for Outcomes Research, Houston Methodist, Houston, TX, USA.
Miguel Cainzos-Achirica, Division of Health Equity and Health Disparities Research, Center for Outcomes Research, Houston Methodist, Houston, TX, USA.
Adnan A. Hyder, Center on Commercial Determinants of Health, Milken Institute School of Public Health, The George Washington University, Washington, DC, USA.
Elias Mossialos, Department of Health Policy, London School of Economics and Political Sciences, London, UK.
Tamer Yahya, Division of Cardiovascular Prevention and Wellness, Department of Cardiology, Houston Methodist DeBakey Heart & Vascular Center, 6550 Fannin St Suite 1801, 77030, Houston, TX, USA.
Isaac Acquah, Division of Health Equity and Health Disparities Research, Center for Outcomes Research, Houston Methodist, Houston, TX, USA.
Javier Valero-Elizondo, Division of Health Equity and Health Disparities Research, Center for Outcomes Research, Houston Methodist, Houston, TX, USA.
Alan Pan, Division of Health Equity and Health Disparities Research, Center for Outcomes Research, Houston Methodist, Houston, TX, USA.
Nwabunie Nwana, Division of Health Equity and Health Disparities Research, Center for Outcomes Research, Houston Methodist, Houston, TX, USA.
Mohamad Taha, Division of Cardiovascular Prevention and Wellness, Department of Cardiology, Houston Methodist DeBakey Heart & Vascular Center, 6550 Fannin St Suite 1801, 77030, Houston, TX, USA.
Khurram Nasir, Division of Health Equity and Health Disparities Research, Center for Outcomes Research, Houston Methodist, Houston, TX, USA. knasir@houstonmethodist.org.

Document Type

Journal Article

Publication Date

9-4-2023

Journal

BMC public health

Volume

23

Issue

1

DOI

10.1186/s12889-023-16168-8

Keywords

HALex; Health and Activity Limitation Index; Health-related quality of life; Quality of life; Social determinants of health

Abstract

BACKGROUND: Evidence for the association between social determinants of health (SDoH) and health-related quality of life (HRQoL) is largely based on single SDoH measures, with limited evaluation of cumulative social disadvantage. We examined the association between cumulative social disadvantage and the Health and Activity Limitation Index (HALex). METHODS: Using adult data from the National Health Interview Survey (2013-2017), we created a cumulative disadvantage index by aggregating 47 deprivations across 6 SDoH domains. Respondents were ranked using cumulative SDoH index quartiles (SDoH-Q1 to Q4), with higher quartile groups being more disadvantaged. We used two-part models for continuous HALex scores and logistic regression for poor HALex (< 20th percentile score) to examine HALex differences associated with cumulative disadvantage. Lower HALex scores implied poorer HRQoL performance. RESULTS: The study sample included 156,182 respondents, representing 232.8 million adults in the United States (mean age 46 years; 51.7% women). The mean HALex score was 0.85 and 17.7% had poor HALex. Higher SDoH quartile groups had poorer HALex performance (lower scores and increased prevalence of poor HALex). A unit increase in SDoH index was associated with - 0.010 (95% CI [-0.011, -0.010]) difference in HALex score and 20% higher odds of poor HALex (odds ratio, OR = 1.20; 95% CI [1.19, 1.21]). Relative to SDoH-Q1, SDoH-Q4 was associated with HALex score difference of -0.086 (95% CI [-0.089, -0.083]) and OR = 5.32 (95% CI [4.97, 5.70]) for poor HALex. Despite a higher burden of cumulative social disadvantage, Hispanics had a weaker SDoH-HALex association than their non-Hispanic White counterparts. CONCLUSIONS: Cumulative social disadvantage was associated with poorer HALex performance in an incremental fashion. Innovations to incorporate SDoH-screening tools into clinical decision systems must continue in order to accurately identify socially vulnerable groups in need of both clinical risk mitigation and social support. To maximize health returns, policies can be tailored through community partnerships to address systemic barriers that exist within distinct sociodemographic groups, as well as demographic differences in health perception and healthcare experience.

Department

Global Health

Link to Full Text

Share

COinS