ArticleFrontiers in nutrition2025
Associations between eight anthropometric indices and Parkinson's disease: a nationwide population-based study.
Article in Frontiers in nutrition, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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2 citing papers in PubMed.
- Associations between five anthropometric indices and fecal incontinence: A cross-sectional study based on the 2005 to 2010 NHANES data.Medicine · 2026Article
- Central adiposity and sex influence lipid and glucose indices in Mexican adults: implications for metabolic risk assessment.Frontiers in nutrition · 2026Article
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3 authors.
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Abstract
Background: Previous studies have explored the associations between obesity and Parkinson's disease (PD), often using body mass index (BMI) as the main metric. However, findings remain inconsistent. Anthropometric indices-quantitative measures of body shape, size, and fat distribution-offer alternative ways to assess adiposity. This study aimed to evaluate the associations between eight anthropometric indices and PD prevalence. Methods: Data were obtained from the National Health and Nutrition Examination Survey (NHANES), conducted in the U.S. from 1999 to 2020. A total of 41,374 participants aged 20 years and older were included, among whom 354 were diagnosed with PD. Eight anthropometric indices were analyzed: waist-to-weight index (WWI), conicity index (CI), a body shape index (ABSI), body roundness index (BRI), waist-to-height ratio (WHtR), BMI, waist circumference (WC), and weight (WT). Weighted multivariable logistic regression models were used to assess the association between these indices and PD. Restricted cubic spline (RCS) models were employed to examine dose-response relationships. Subgroup and sensitivity analyses were conducted to validate the robustness of the findings. Results: Significant differences were observed between the study groups, with positive and independent correlations identified between PD and all anthropometric measures, except BMI. After full adjustment, each 1-standard deviation increase in WWI, CI, ABSI, BRI, WHtR, WC, and WT was associated with an elevated PD risk by 34, 42, 36, 18, 21, 25, and 16%, respectively. RCS analysis revealed a linear relationship between CI, ABSI, BRI, WtHR, WC, WT, and PD prevalence, whereas WWI exhibited a nonlinear association. The subgroup and sensitivity analyses confirmed the consistency of these associations. Conclusion: Higher values of several anthropometric indices, particularly the ABSI, WWI, and CI, were associated with increased PD prevalence. These findings highlight the potential role of fat distribution rather than overall adiposity in PD pathogenesis. Anthropometric measures may be valuable tools for early PD risk identification and targeted prevention strategies.
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