ArticlePhysical activity and nutrition2025
Development of a prediction model for metabolic syndrome based on physical activity and fitness in individuals with physical disabilities.
Article in Physical activity and nutrition, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
purposeThe objective of this study was to develop a predictive model to estimate the number of risk factors associated with metabolic syndrome based on physical activity and fitness in individuals with physical disabilities.
methodsA total of 134 adults aged ≥ 30 years with severe physical disabilities diagnosed over 1 year were enrolled in this study. Standardized procedures were used to collect anthropometric data, blood samples, and physical fitness measurements. Participants were randomly assigned to the derivation (70%) and validation (30%) sets. The derivation set was subjected to a stepwise multiple regression analysis to develop a predictive equation. Criteria and cross-validity were assessed using Bland-Altman plots, and the model's ability to identify metabolic syndrome was evaluated using receiver operating characteristic (ROC) analysis.
resultsThe final model included neck circumference, the number of medications, leisure-time physical activity, and muscular strength, with an R² value of 0.397 and a standard error of the estimate of 1.019. The predicted values closely match the measured values for both sets. ROC analysis indicated good to excellent classification performance (derivation set: area under the curve [AUC], 0.867; 95% confidence interval [CI], 0.796-0.937; p < 0.001; validation set: AUC, 0.765; 95% CI, 0.617-0.913; p = 0.009).
conclusionA regression model based on physical activity and fitness could provide a simple, non-invasive approach to estimating the risk of metabolic syndrome in individuals with physical disabilities.
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