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Cardiovascular disease (CVD) risk stratification often relies on anthropometric measures that do not fully reflect central adiposity or differences across populations. The Body Roundness Index (BRI) is a body-shape indicator that may improve assessment of cardiometabolic risk, but evidence from large national cohorts remains limited. This study analyzed harmonized data from the China Health and Retirement Longitudinal Study (CHARLS, 2015) and the U.S. National Health and Nutrition Examination Survey (NHANES, 2005–2016) to examine the relationship between BRI and prevalent CVD. Participants were grouped into quartiles of BRI, with the highest quartile serving as the reference. Weighted multivariable logistic regression models were used to estimate odds ratios (ORs) and 95% confidence intervals (CIs), with sequential adjustment for demographic and clinical covariates. Subgroup analyses were performed to evaluate heterogeneity across population strata, and an extreme gradient boosting (XGBoost) model was applied to assess the relative importance of BRI and other predictors. In both cohorts, individuals with CVD were older and had higher prevalences of hypertension and diabetes, whereas BRI distributions differed between cohorts. Lower BRI quartiles were associated with greater odds of CVD. Compared with Q4, Q1 was associated with increased CVD risk in CHARLS (OR 1.73, 95% CI 1.14-2.68; p=0.012) and NHANES (OR 1.82, 95% CI 1.44-2.30; p<0.001). These findings suggest that lower BRI is associated with higher CVD risk and may complement conventional anthropometric measures in population-based cardiovascular risk assessment.
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The same dataset can be analysed in different justifiable ways to answer the same research question, potentially challenging the robustness of empirical science1-3. In this crowd initiative, we investigated the degree to which research findings in the social and behavioural sciences are contingent on analysts' choices. We examined a stratified random sample of 100 studies published between 2009 and 2018, in which, for one claim per study, at least five reanalysts independently reanalysed the original data. The statistical appropriateness of the reanalyses was assessed in peer evaluations, and the robustness indicators were inspected along a range of research characteristics and study designs. We found that 34% of the independent reanalyses yielded the same result (within a tolerance region of ±0.05 Cohen's d) as the original report; with a four times broader tolerance region, this indicator increased to 57%. Of the reanalyses conducted, 74% reached the same conclusion as the original investigation, 24% yielded no effects or inconclusive results and 2% reported the opposite effect. This exploratory study indicates that the common single-path analyses in social and behavioural research should not be simply assumed to be robust to alternative analyses4. Therefore, we recommend the development and use of practices to explore and communicate this neglected source of uncertainty. © 2026. The Author(s), under exclusive licence to Springer Nature Limited.
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