Income Disparities in Absolute Cardiovascular Risk and Cardiovascular Risk Factors in the United States, 1999-2014

Odutayo, Ayodele; Gill, Peter; Shepherd, Shaun; Akingbade, Aquila; Hopewell, Sally; Tennankore, Karthik; Hunn, Benjamin H.M.; Emdin, Connor A.

doi:10.1001/jamacardio.2017.1658

Cited by 104 publications

(75 citation statements)

References 23 publications

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“…48 Autonomic dysfunction and chronic inflammation may contribute to the link between obesity and diabetes. 49 The increase in prediabetes and diabetes among low-income youth, combined with existing socioeconomic disparities and a growing burden of cardiometabolic disease among adults, 5,44 is cause for concern. Increasing CVD risk factors such as obesity and diabetes among youth and young adults may be contributing to observed increases in burden of stroke among younger adults.…”

Section: Figurementioning

confidence: 99%

“…1 A substantial burden of cardiovascular risk factors exists among adolescents in the United States 2 and globally, 3 and emerging evidence suggests that patterns of cardiovascular health are established early and track into adulthood. 4 There are striking disparities in risk factors and CVD across socioeconomic strata in the United States, 5,6 and lower socioeconomic status may influence CVD risk through diverse pathways including increased exposure to environmental hazards such as poor air quality; decreased educational attainment and poorer health behaviors; decreased access to health care; decreased family, neighborhood, and community resources such as healthy food and safe places for physical activity; and increased chronic stress associated with violence, deprivation, or discrimination. 7,8 Few studies have examined secular trends in CVD risk factors and disparities among adolescents despite the fact that disparities may be widening, given the increasing income inequality in the United States.…”

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confidence: 99%

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Income Disparities and Cardiovascular Risk Factors Among Adolescents

2018

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BACKGROUND AND OBJECTIVES: Socioeconomic disparities in cardiovascular health among adults have been documented, but disparities during adolescence are less understood. In this study, we examined secular trends in 7 cardiovascular risk factors and disparities among US adolescents. METHODS: We analyzed NHANES data from 1999 to 2014, including 11 557 (4854 fasting) participants aged 12 to 19 years. To examine trends in cardiovascular risk factors, adolescents were stratified into 3 groups on the basis of family poverty-income ratio: low income (poverty-income ratio, <1.3), middle income (≥1.3 and <3.5), and high income (≥3.5). RESULTS: From 1999 to 2014, the prevalence of obesity increased (16.5%-21.0%, P = .001) but only among low-and middle-income adolescents, with significant disparities in prevalence by income (21.7% vs 14.6% among low-versus high-income adolescents, respectively, in 2011-2014). In addition, there were significant and persistent disparities in the prevalence of smoking (20.8% vs 7.4% among low-versus high-income adolescents, respectively, in 2011-2014), low-quality diet (67.8% vs 49.0%), and physical inactivity (25.6% vs 17.0%). No significant disparities were observed in the prevalence of prediabetes and diabetes, hypertension, or hypercholesterolemia, although the prevalence of prediabetes and diabetes increased among low-income adolescents (21.4%-28.0%, P = .01). Overall, the prevalence of adolescents with 2 or more risk factors declined (48.3% to 37.1%, P<.001), but this decline was only significant for high-and middle-income adolescents. CONCLUSIONS: Recent improvements in cardiovascular health have not been equally shared by US adolescents of varying socioeconomic status.

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Section: Figurementioning

confidence: 99%

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confidence: 99%

Income Disparities and Cardiovascular Risk Factors Among Adolescents

2018

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“…The extensive research on the relationship between social determinants and race-ethnic disparities in noncommunicable diseases, including heart disease and stroke, has largely been characterized by long-term exposures leading to differences in disease ourcomes 16,17 . However, the social determinants of infectious disease are less well-characterized.…”

Section: Covid-19 Cases Who Live In Dense Households and Low-income Cmentioning

confidence: 99%

The disproportionate rise in COVID-19 cases among Hispanic/Latinx in disadvantaged communities of Orange County, California: A socioeconomic case-series

Chow

Soun

Glavis-Bloom

et al. 2020

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Background: Recent epidemiological evidence has demonstrated a higher rate of hospitalizations and deaths among minorities. This pattern of race-ethnic disparities emerging throughout the United States raises the question of what social factors may influence spread of a highly transmissible novel coronavirus. The purpose of this study is to describe race-ethnic and socioeconomic disparities associated with COVID-19 in patients in our community in Orange County, California and understand the role of individual-level factors, neighborhood-level factors, and access to care on outcomes.Methods: This is a case-series of COVID-19 patients from the University of California, Irvine (UCI) across six-weeks between 3/12/2020 and 4/22/2020. Note, California's shelter-in-place order began on 3/19/2020. Individual-level factors included race-ethnicity status were recorded.Neighborhood-level factors from census tracts included median household income, mean household size, proportion without a college degree, proportion working from home, and proportion without health insurance were also recorded.Results: A total of 210-patients tested were COVID-19 positive, of which 73.3% (154/210) resided in Orange County. Hispanic/Latinx patients residing in census tracts below the median income demonstrated exponential growth (rate = 55.9%, R2 = 0.9742) during the study period.In addition, there was a significant difference for both race-ethnic (p < 0.001) and income bracket (p = 0.001) distributions prior to and after California's shelter-in-place. In addition, the percentage of individuals residing in neighborhoods with denser households (p = 0.046), lower levels of college graduation (p < 0.001), health insurance coverage (p = 0.01), and ability to work from home (p < 0.001) significantly increased over the same timeframe.Conclusions and Relevance: Our study examines the race-ethnic disparities in Orange County, CA, and highlights vulnerable populations that are at increased risk for contracting COVID-19.Our descriptive case series illustrates that we also need to consider socioeconomic factors, which ultimately set the stage for biological and social disparities.

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“…Beyond ongoing national health policy initiatives, it is increasingly evident that factors outside of the hospital walls contribute significantly to the incidence, progression, and outcomes of cardiovascular disease (13,14). Major gains still need to be made to address the social determinants of cardiovascular disease.…”

Section: Why Develop Cardiovascular Policy Leaders?mentioning

confidence: 99%