Heterogeneity in disparities by income in cardiovascular risk factors across 209 US metropolitan areas

Figures

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  Fig. 1. Income-based Inequalities for Each Risk Factor And Cardiovascular Disease Prevalence by Relative Index of Inequality, Adjusted for Age and Sex, in 209 Metropolitan Areas of the United States from 2012 to 2019. Footnote: Box and whisker plot of the Relative Index of Inequality (RII) of each risk factor for each core-based statistical area. Each point represents a metropolitan area. Higher RII is indicative of greater inequality. Greater variability in RII for each risk factor is indicative of greater heterogeneity in disparities for this risk factor across metropolitan areas. These were adjusted for age and sex.

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  Fig. 2. 209 Metropolitan Areas of the United States Ranked by Relative Index of Inequality for Five Cardiovascular Disease Risk Factors and Prevalence, Adjusted for Age and Sex from 2012 to 2019. Footnote: Categories were created using outcome-specific quintiles. Metropolitan areas were placed in quintiles of the Relative Index of Inequality (RII) for each risk factor and color coded. Darker areas represent metropolitan areas with greater disparities in a given factor. These were adjusted for age and sex.

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  Fig. 3. Relative Index of Inequality, Adjusted for Age, Sex, and Race/Ethnicity, in 209 Metropolitan Areas of the United States at the Average, +1 Standard Deviation, and –1 Standard Deviation of Metropolitan-Level Contextual Variables from 2012 to 2019. Footnote: Depicts the relative index of inequality (RII) (and 95 % confidence interval) of each contextual variable that was studied. The green bar represents the average metropolitan area level of each variable, the blue bar represents metropolitan areas with + 1 SD of each variable and the red bar represents metropolitan areas with −1 SD of each variable. Given this, contextual variables where the blue bar is to the right of the green bar and red bar is to the left of the green bar demonstrate greater disparities with greater values of that variable and vice versa. These were adjusted for age, sex, and race/ethnicity. NH: non-Hispanic, PCP pop: primary care physicians per capita. (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.)

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  Fig. 4. Magnitude of Heterogeneity in Income-Based Inequalities in Cardiovascular Risk Factors and Prevalence in Four Sequentially Adjusted Models across 209 Metropolitan Areas of the United States from 2012 to 2019. Footnote: Depicts the amount of heterogeneity in each risk factor that can be accounted for by sequentially adjusting for each variable. The pink bar represents heterogeneity before adjustment (empty or unadjusted model). The green bars represent the change in heterogeneity after adjusting for individual variables: age, sex, and (for the second green bar) race. The blue bar represents the heterogeneity after adjusting for the contextual variables. The closer to −100%, the more heterogeneity can be described by a given variable. (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.)