To examine the associations between conventional and novel obesity indices with fall risk and severity. Data from 13,778 adults aged 65 years and older, obtained from the Chinese Longitudinal Healthy Longevity Survey, were analyzed. Logistic regression analyses, restricted cubic splines, and receiver operating characteristic curve were used to assess the relationships. After multivariable adjustment, central obesity, assessed by waist circumference, was inversely associated with fall risk. The odds ratio (OR) and 95% confidence interval (95%CI) was 0.91 (0.82–0.99, p = 0.031). In contrast, compared with the lowest quartile, the highest weight-adjusted waist index (WWI) quartile was positively associated with fall risk (OR: 1.15, 95%CI: 1.02–1.30, p = 0.022). WWI also exhibited significant associations with fall severity. Compared with the lowest quartile, the highest WWI quartile was significantly associated with one fall (OR: 1.6, 95%CI: 1.16–2.21, p = 0.005), recurrent falls (OR: 1.8, 95%CI: 1.31–2.47, p < 0.001), and injurious falls (OR: 1.76, 95%CI: 1.3–2.4, p < 0.001). These associations between WWI and fall outcomes remained consistent across multiple subgroup analyses. The area under the curve for WWI in discriminating fall risk and severity ranged from 0.55 to 0.58. A WWI ≥11.8 cm/√kg was associated with 30% ( p = 0.034), 65% ( p < 0.001), and 52% ( p < 0.001) higher risk of a single fall, recurrent falls, and fall injury, respectively. Sensitivity analysis using complete-case data confirmed the robustness of the main findings. WWI was significantly associated with fall risk and severity in older adults. Further prospective studies are essential to validate its predictive value in fall risk stratification and prevention. • First large-scale study linking obesity metrics to fall risk and severity in older adults. • WWI demonstrates superior performance compared with BMI, ABSI, and BRI in assessing fall risk and severity. • WWI ≥11.8 cm/√kg is the optimal threshold for elevated fall risk and severity. • WWI shows promise as a simple and practical tool for large-scale fall-risk screening.
Chen et al. (Mon,) studied this question.