Abstract: (see Poster Gallery) Socioeconomic Disparities in Health Outcomes in the United States: Results from Four National Population-Based Studies (Society for Social Work and Research 27th Annual Conference - Social Work Science and Complex Problems: Battling Inequities + Building Solutions)

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SSWR 2023 Poster Gallery: as a registered in-person and virtual attendee, you have access to the virtual Poster Gallery which includes only the posters that elected to present virtually. The rest of the posters are presented in-person in the Poster/Exhibit Hall located in Phoenix A/B, 3rd floor. The access to the Poster Gallery will be available via the virtual conference platform the week of January 9. You will receive an email with instructions how to access the virtual conference platform.

540P (see Poster Gallery) Socioeconomic Disparities in Health Outcomes in the United States: Results from Four National Population-Based Studies

Saturday, January 14, 2023
Phoenix C, 3rd Level (Sheraton Phoenix Downtown)
* noted as presenting author
Yeonwoo Kim, PhD, Assistant Professor, University of Texas at Arlington, TX
Christian Vazquez, PhD, Assistant Professor, University of Texas at Arlington, Arlington, TX
Catherine Cubbin, PhD, Associate Dean of Research, University of Texas at Austin, Austin, TX
Background/Purpose: Despite the importance of monitoring health disparities by multiple socioeconomic categories, there have been no recent updates on the prevalence of general health indicators by socioeconomic categories while considering the intersectionality of age, race/ethnicity, and socioeconomic status. In addition, although the population’s true levels of health by socioeconomic categories cannot be captured by using only one data source, none has compared current extent and patterns of health disparities across different nationally representative data sources in the United States. The present study aims to update the prevalence estimates of health indicators by education and income categories across three age groups (children, middle-aged adults, and older adults) by using four nationally representative data sources. We also examine socioeconomic differences in health by race/ethnicity subgroups.

Methods: Data were obtained from four nationally representative data sources from the US: The National Health Interview Survey [NHIS] (2015-2018); the National Health and Nutrition Examination Survey [NHANES] (2017-2020); the Behavioral Risk Factor Surveillance System [BRFSS] (2016-2020); and the Health & Retirement Study [HRS] (2016). Respondent-rated poor health and obesity were selected as the health indicators of interest. Socioeconomic factors included percentages of the federal poverty level and years of educational attainment. We conducted a logistic regression analysis to calculate adjusted prevalence rates of respondent-rated poor health and obesity by income and education categories after controlling for sociodemographic characteristics (i.e., age, sex, and race/ethnicity). A complex sampling design was applied in all analyses.

Results: Prevalence rates across racial/ethnic groups and age groups demonstrated clear and consistent socioeconomic gradients in respondent-rated poor health. Prevalence rates of respondent-rated poor health were the highest among those in the lowest income and education categories, and the rates decreased as income and education levels increased. On the other hand, there were less evident socioeconomic differences in obesity rates across all data sources, racial/ethnic groups, and age groups. For children, rates of obesity appeared to decrease as income and education went up, but with less apparent socioeconomic patterns when using the NHANES data. In middle-aged and older adult samples, education gradient patterns were observed in the NHIS, the BRFSS, and the HRS data, but not in the NHANES data, and the income gradient in obesity was less apparent across data sources. Overall, the NHANES data tends to produce higher prevalence rates of respondent-rated poor health and obesity across all groups and socioeconomic factors compared to three other data sources.

Conclusions/Implications: Our results confirmed earlier evidence indicating socioeconomic disparities in respondent-rated poor health across all age and race/ethnicity groups by using several nationally representative datasets. The results suggest an urgent need for action to alleviate pervasive health disparities by socioeconomic status. Further research is needed to elaborate on the underlying mechanisms of different socioeconomic patterns in various health indicators. Future research is also needed to investigate potentially modifiable factors underlying socioeconomic disparities in health, which may help design targeted health promotion programs.