Socioeconomic disparities in health outcomes in the United States in the late 2010s: results from four national population-based studies

Despite perpetuating socioeconomic differences in health, there have been no recent updates on prevalence rates of general health indicators by SES aside from the NCHS report, which does not delve deeper into the intersections of race/ethnicity, age, and income or education [9]. A lack of knowledge about the recent prevalence of adverse health outcomes by socioeconomic categories limits us to an understanding of socioeconomic disparities in health during the last decade. This study addressed this limitation of knowledge by describing recent patterns of socioeconomic differences in health indicators among children, young and middle-aged adults, and older adults and comparing the pattern and extent of socioeconomic disparities in health across different data sources. We first estimated socioeconomic differences in prevalence rates of respondent-rated poor health and obesity by age groups and then by age and race/ethnicity groups in the late 2010s given that socioeconomic status is strongly related to race/ethnicity in the U.S. [30, 31].

Our findings revealed clear and consistent socioeconomic gradients in respondent-rated poor health among the three age groups and all 12 age and race/ethnicity groups, after adjusting for sociodemographic characteristics (i.e., age, sex, race/ethnicity, education, or income). Specifically, prevalence rates of poor health were often the highest among those in the lowest income and education categories regardless of age cohort and race/ethnicity. We also observed a large health gap between those in the middle levels of income and education and those in the highest levels. The socioeconomic gradients in respondent-rated poor health align with earlier evidence indicating socioeconomic gradients in health in the U.S. [1, 4,5,6,7,8, 10,11,12,13]. Of note, the extent of socioeconomic disparities in respondent-rated poor health appeared to decrease compared to that in the 2000s estimated by Braveman et al. [1]. For example, when using the NHANES, the percentage of non-high school graduate adults with poor health decreased from 77.4% in 1994–2004 to 70.7% in 2017–2020 while the percentage of college graduate adults with poor health increased from 30.0% to 38.8% during the same observation period.

On the other hand, obesity rates showed less evident socioeconomic differences than respondent-rated poor health. Specifically, in the education models, consistent educational differences in obesity were found only among the total sample and Whites, but not among Asians, Blacks, and Hispanics. In particular, when comparing it to statistics in 2005–2007 [1], educational differences in obesity became more pronounced—while BRFSS showed no educational differences in 2005–2007, significant educational differences in obesity were observed in 2016–2020. Income differences in obesity were inconsistent across all age and racial/ethnic groups. The results indicate that different socioeconomic patterns in the two health indicators are possibly due to different underlying mechanisms of respondent-rated health and obesity. While respondent-rated health status represents an individual’s overall health status and well-being, obesity is specifically related to metabolic and cardiovascular risk. Socioeconomic status may be more impactful for certain health outcomes. The explanation is in line with previous research reporting a less clear socioeconomic gradient in body mass index, scores for healthy eating, and prevalence rates of diabetes [1, 6]. Future research is needed to elaborate underlying mechanisms of different socioeconomic patterns in various health indicators, which helps policy makers and practitioners design more targeted programs to decrease socioeconomic gaps in health.

The overall picture of socioeconomic disparities in health was found to be more complicated by considering age and race/ethnicity. When comparing prevalence rates of respondent-rated poor health between the lowest and highest income and education categories, Blacks and Hispanics appeared to have the largest socioeconomic difference during childhood. Given Blacks and Hispanics often had the highest rates of respondent-rated poor health and obesity in the same income and education levels, regardless of age groups, policies and programs designed for Black and Hispanic children from households with low SES may help alleviate health disparities by both SES and race/ethnicity. On the other hand, although Blacks often had worse health outcomes than other racial/ethnic groups, Whites had the largest socioeconomic difference in respondent-rated health for young and middle age adulthood; and for older adulthood, Whites and Hispanics often had the largest socioeconomic difference in respondent-rated health. In other words, for adults, Blacks had worse health outcomes across all SES categories than other racial/ethnic groups, but their socioeconomic differences in health were relatively small. The results imply that policy strategies designed to promote health of adults with low SES may be more likely to target Whites, which may not be effective to tackle racial/ethnic disparities in health. Thus, multiple policy strategies should be adopted to alleviate both racial/ethnic and socioeconomic disparities in adult health. Future research is warranted to investigate underlying mechanisms for racial/ethnic and socioeconomic differences in health across age groups for a better understanding of interactions between age, race/ethnicity, and SES in health disparities.

Looking across the data sources, there are visible differences in prevalence rates of health conditions across data sources when using the same health measures around the same time and controlling for the same factors. Prevalence rates for NHANES were notably higher compared to all three other data sources, and the NHIS produced the lowest prevalence rates of respondent-rated health status. The results are consistent with Nelson et al. [22] who reported differences in prevalence rates of health indicators (e.g., height, weight, and respondent-rated health status) between the NHIS and the BRFSS. Specifically, while Nelson et al. [22] found lower estimates of respondent-rated health in NHIS compared to BRFSS as is with the present study, obesity rates were higher in NHIS than BRFSS, which is the opposite in our study. Nelson et al.’s study is nearly two-decades old, and our findings align with the findings from Pemberton et al.’s study [23] in that that the NHIS estimates tend to be lower than other data sources. Investigating the nuances of differences across data sources is beyond the scope of this study, but differences in estimates possibly result from several methodological differences, such as type and mode of data collection, weighting and representativeness of the sample, question placement, wording, format, use of proxy reporting for youth, and not completely overlapping data collection periods. Future research needs to examine underlying reasons for different estimates of health indicators to understand which data sources may provide the most accurate estimates of the population’s health levels.

This study has several limitations. Our analysis was limited to two health indicators, respondent-rated health status and obesity. Although the measures are widely used and represent general health status [1, 4, 5, 24, 25], using a more comprehensive set of health indicators will allow future studies to examine different mechanisms underlying socioeconomic disparities in various health indicators. This study did not use precisely overlapping years due to various reasons explained in the methods; however, there were no major events (e.g., recessions or pandemics) in the years utilized across data sources. Also, this study did not examine mechanisms of health disparities. Future research needs to compare mechanisms of health disparities by SES and race/ethnicity. Racial/ethnic disparities in health may be related to racial/ethnic discrimination, racial/ethnic segregation, and lack of health-promoting resources in minority neighborhoods that Blacks and Hispanics often experience in their daily life. Further research is warranted to include various potential causes of racial/ethnic and socioeconomic disparities for an investigation of mechanisms of health disparities. Another limitation of this study is that respondent-assessed body mass index was used to operationalize obesity in the NHIS, BRFSS, and HRS. Although the NHANES has body mass index information objectively measured by a trained technician, more replication studies are needed to draw solid conclusions. Lastly, although our study is unique in that Asians, who have been understudied in past literature, are included in our analysis, our study could not include more specific Asian subgroups, Pacific Islanders, American Indians, or Hispanic subpopulations due to a lack of sufficient data.

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