A nationwide analysis of more than one million young adults in the United States has revealed striking differences in the prevalence of early-onset cardiovascular disease, with risk shaped not by a single social characteristic but by the way sex, race and ethnicity, education, income, and health insurance overlap. The study, published in BMC Public Health, suggests that some combinations of disadvantage are associated with dramatically higher cardiovascular risk than would be predicted by adding the effects of each factor separately. The findings arrive as cardiovascular disease increasingly affects adults who are still in their twenties, thirties, and early forties, challenging the long-standing assumption that heart disease is primarily a problem of older age.
Researchers analyzed data from 1,030,504 US adults between 18 and 44 years old who participated in the Behavioral Risk Factor Surveillance System, or BRFSS, between 2015 and 2024. The BRFSS is a large, ongoing national health survey coordinated by the US Centers for Disease Control and Prevention. It collects information on health conditions, health behaviors, access to medical care, insurance status, and socioeconomic circumstances. In this study, the investigators used the survey to estimate the prevalence of early-onset cardiovascular disease and to examine how social conditions intersected to create distinct patterns of risk across the young adult population.
Across the entire sample, the weighted prevalence of early-onset cardiovascular disease was 2.1 percent. On the surface, that figure may appear modest, but its national implications are substantial because it applies to a very large population. More importantly, the average concealed enormous differences between social groups. The researchers divided participants into 240 intersectional strata based on combinations of sex, race or ethnicity, education, income, and health insurance coverage. The estimated probability of cardiovascular disease ranged from just 0.04 percent in the lowest-risk stratum to 15.91 percent in the highest-risk stratum, representing a more than 400-fold difference.
To investigate these patterns, the team used a statistical framework known as Multilevel Analysis of Individual Heterogeneity and Discriminatory Accuracy, or MAIHDA. Unlike conventional analyses that examine sex, race, income, or education one variable at a time, MAIHDA treats each combination of characteristics as a social context. This allows researchers to distinguish between two effects. The first is the additive effect, in which each disadvantage contributes independently to risk. The second is the intersectional effect, in which the combination produces an outcome that is greater or smaller than the sum of its separate parts. In practical terms, the method asks whether belonging simultaneously to several socially disadvantaged groups creates a unique pattern of risk.
The statistical results indicated substantial heterogeneity between the 240 strata. The variance partition coefficient, or VPC, was 23.5 percent, meaning that nearly one-quarter of the unexplained variation in cardiovascular disease prevalence was associated with differences between the intersectional groups rather than only with individual-level variation. The median odds ratio, or MOR, was 2.60. This measure translates group-level variation into an odds-ratio scale: if two otherwise similar individuals were randomly selected from two different strata, the median difference in their odds of cardiovascular disease would be 2.6-fold. Together, the VPC and MOR indicate that social patterning was not a minor statistical detail but a substantial feature of the data.
The analysis also showed that standard additive models captured only 44.6 percent of the observed inequality. In other words, simply assigning separate effects to sex, race or ethnicity, education, income, and insurance would leave more than half of the disparity unexplained. Of the 235 strata with sufficient information for detailed intersectional assessment, 99—42.1 percent—showed statistically significant intersectional effects. Fifty-eight strata experienced what the researchers described as intersectional penalties, with cardiovascular risk higher than expected from the individual characteristics alone. Forty-one showed intersectional protections, with risk lower than expected.
One of the most unexpected patterns involved Asian adults, who appeared prominently at both extremes of the risk distribution. The highest predicted risk was observed among uninsured, low-income, low-education Asian men, whose estimated probability of early-onset cardiovascular disease reached 15.91 percent. At the same time, other Asian strata were among the groups with the lowest predicted risk. This divergence illustrates why broad racial categories can conceal major internal differences. A population that appears relatively protected when considered as a whole may contain smaller groups facing severe risks because of interactions involving economic hardship, limited education, lack of insurance, gender, migration-related barriers, occupational conditions, or restricted access to preventive care.
The researchers then compared the period before the COVID-19 pandemic with the years following its onset to determine whether these disparities changed over time. The median odds ratio increased from 3.43 before the pandemic to 4.19 afterward, corresponding to a relative increase of 22.2 percent. This pattern suggests that the distance between high-risk and low-risk intersectional groups widened after the pandemic. However, the confidence interval for the relative change ranged from a slight decrease of 0.4 percent to an increase of 44.7 percent, indicating statistical uncertainty around the exact size of the change. The result should therefore be interpreted as evidence of a concerning widening trend rather than definitive proof that the pandemic alone caused the increase.
The findings point toward mechanisms that operate across multiple levels of society. Uninsurance can delay diagnosis and limit access to blood-pressure checks, cholesterol testing, diabetes screening, and treatment. Low income can increase exposure to unstable housing, food insecurity, chronic stress, and jobs with irregular schedules or physical hazards. Lower educational opportunity may affect health literacy and the ability to navigate a fragmented healthcare system, although education itself is also closely tied to employment and income. These conditions can influence smoking, diet, physical activity, sleep, medication access, and exposure to chronic stress. Over time, such pressures may contribute to hypertension, metabolic disease, inflammation, and vascular injury—the biological pathways that accelerate cardiovascular disease at younger ages.
Because the study used retrospective serial cross-sectional data, it can identify population patterns but cannot establish that any particular social characteristic directly caused cardiovascular disease in an individual. The BRFSS also relies heavily on survey responses, and the analysis may not capture every relevant factor, including neighborhood conditions, immigration status, occupational exposures, detailed healthcare use, or the quality of insurance coverage. Even so, the scale of the dataset and the use of an intersectional statistical model provide a powerful warning: treating young adults as a single low-risk population may hide concentrated pockets of severe disease. The authors argue that prevention should move beyond individual lifestyle advice toward structurally informed strategies, including affordable coverage, earlier screening, culturally responsive care, and targeted support for multiply marginalized communities. As early-onset cardiovascular disease becomes more visible, the study suggests that the most effective interventions will need to address not only what individuals do, but also the social environments that determine which healthy choices are realistically available.
Subject of Research: Early-onset cardiovascular disease and intersectional health inequalities among US adults aged 18–44
Article Title: Early-onset CVD at the intersection of sex, race/ethnicity, education, income, and health insurance in the US: a nationwide intersectional analysis
Article References: Gu, J., Li, J., Wu, S. et al. “Early-onset CVD at the intersection of sex, race/ethnicity, education, income, and health insurance in the US: a nationwide intersectional analysis.” BMC Public Health (2026).
Image Credits: AI Generated
DOI: 10.1186/s12889-026-29108-z
Keywords: Cardiovascular disease, early-onset CVD, intersectionality, health inequities, social determinants of health, young adults, COVID-19 pandemic, BRFSS, MAIHDA, health insurance
