Disparities in Guideline-Recommended Statin Use for Prevention of Atherosclerotic Cardiovascular Disease by Race, Ethnicity, and Gender : A Nationally Representative Cross-Sectional Analysis of Adults in the United States

Abstract

Background: Although statins are a class I recommendation for prevention of atherosclerotic cardiovascular disease and its complications, their use is suboptimal. Differential underuse may mediate disparities in cardiovascular health for systematically marginalized persons.

Objective: To estimate disparities in statin use by race-ethnicity-gender and to determine whether these potential disparities are explained by medical appropriateness of therapy and structural factors.

Design: Cross-sectional analysis.

Setting: National Health and Nutrition Examination Survey from 2015 to 2020.

Participants: Persons eligible for statin therapy based on 2013 and 2018 American College of Cardiology/American Heart Association blood cholesterol guidelines.

Measurements: The independent variable was race-ethnicity-gender. The outcome of interest was use of a statin. Using the Institute of Medicine framework for examining unequal treatment, we calculated adjusted prevalence ratios (aPRs) to estimate disparities in statin use adjusted for age, disease severity, access to health care, and socioeconomic status relative to non-Hispanic White men.

Results: For primary prevention, we identified a lower prevalence of statin use that was not explained by measurable differences in disease severity or structural factors among non-Hispanic Black men (aPR, 0.73 [95% CI, 0.59 to 0.88]) and non-Mexican Hispanic women (aPR, 0.74 [CI, 0.53 to 0.95]). For secondary prevention, we identified a lower prevalence of statin use that was not explained by measurable differences in disease severity or structural factors for non-Hispanic Black men (aPR, 0.81 [CI, 0.64 to 0.97]), other/multiracial men (aPR, 0.58 [CI, 0.20 to 0.97]), Mexican American women (aPR, 0.36 [CI, 0.10 to 0.61]), non-Mexican Hispanic women (aPR, 0.57 [CI, 0.33 to 0.82), non-Hispanic White women (aPR, 0.69 [CI, 0.56 to 0.83]), and non-Hispanic Black women (aPR, 0.75 [CI, 0.57 to 0.92]).

Limitation: Cross-sectional data; lack of geographic, language, or statin-dose data.

Conclusion: Statin use disparities for several race-ethnicity-gender groups are not explained by measurable differences in medical appropriateness of therapy, access to health care, and socioeconomic status. These residual disparities may be partially mediated by unobserved processes that contribute to health inequity, including bias, stereotyping, and mistrust.

Primary funding source: National Institutes of Health.

Figure 1.. Conceptual model depicting differences and disparities in statin use.

The overall difference in statin use between the reference group and minoritized groups reflects patient factors that influence the medical appropriateness of statin use and disparities in access to statins. By accounting for patient factors such as age, disease severity, and medical comorbidities, disparities in statin use can be estimated. The influence of care-process factors, such as bias, stereotyping, and mistrust, can be estimated by also accounting for structural factors, such as health insurance and socioeconomic status indicators. Adapted from the Institute of Medicine framework for evaluating unequal treatment (16).

Figure 2.. aPRs for statin use for primary prevention of ASCVD by race-ethnicity-gender category

Model 1 was unadjusted, thereby reflecting differences in statin use that are influenced by patient factors that contribute to the medical appropriateness of care, structural factors, and care-process factors. Model 2 was adjusted for measurable patient factors only, thereby reflecting disparities that are influenced by structural factors and care-process factors. Model 3 was adjusted for measurable patient factors and structural factors, thereby reflecting disparities unexplained by structural factors. These residual disparities may reflect unobserved mediators of health inequity, including bias, stereotyping, and mistrust. Results weighted to the United States population. Adjusted PRs were derived from marginally adjusted prevalence estimates calculated from multivariable logistic regression models. Adjusted PRs for covariates are presented in Supplemental table 3.

Figure 3.. aPRs for statin use for secondary prevention of ASCVD complications by race-ethnicity-gender category

Model 1 was unadjusted, thereby reflecting differences in statin use that are influenced by patient factors that contribute to the medical appropriateness of care, structural factors, and care-process factors. Model 2 was adjusted for measurable patient factors only, thereby reflecting disparities that are influenced by structural factors and care-process factors. Model 3 was adjusted for measurable patient factors and structural factors, thereby reflecting disparities unexplained by structural factors. These residual disparities may reflect unobserved mediators of health inequity, including bias, stereotyping, and mistrust. Results weighted to the United States population. Adjusted PRs were derived from marginally adjusted prevalence estimates calculated from multivariable logistic regression models. Adjusted PRs for covariates are presented in Supplemental table 4.