ArticleJournal of physical activity & health2017
Combining Activity-Related Behaviors and Attributes Improves Prediction of Health Status in NHANES.
Article in Journal of physical activity & health, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
4 citing papers in PubMed.
- Study design and methods for the physical activity index (PAI) feasibility pilot trial for breast and colon cancer survivors in North Carolina.Contemporary clinical trials communications · 2025Article
- Feasibility of a Physical Activity Index in Clinical Practice: Perspectives of Providers and Cancer Patients.Oncology issues · 2024Article
- Rethinking physical activity assessment in cancer survivors: a multi-component approach using NHANES data.Journal of cancer survivorship : research and practice · 2022Article
- Development and Testing of an Integrated Score for Physical Behaviors.Medicine and science in sports and exercise · 2019Article
Corrections and comments
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Authors and funding
5 authors.
Funding
Abstract
backgroundThis paper tested whether a physical activity index (PAI) that integrates PA-related behaviors (ie, moderate-to-vigorous physical activity [MVPA] and TV viewing) and performance measures (ie, cardiorespiratory fitness and muscle strength) improves prediction of health status.
methodsParticipants were a nationally representative sample of US adults from 2011 to 2012 NHANES. Dependent variables (self-reported health status, multimorbidity, functional limitations, and metabolic syndrome) were dichotomized. Wald-F tests tested whether the model with all PAI components had statistically significantly higher area under the curve (AUC) values than the models with behavior or performance scores alone, adjusting for covariates and complex survey design.
resultsThe AUC (95% CI) for PAI in relation to health status was 0.72 (0.68, 0.76), and PAI-AUC for multimorbidity was 0.72 (0.69, 0.75), which were significantly higher than the behavior or performance scores alone. For functional limitations, the PAI AUC was 0.71 (0.67, 0.74), significantly higher than performance, but not behavior scores, while the PAI AUC for metabolic syndrome was 0.69 (0.66, 0.73), higher than behavior but not performance scores.
conclusionsThese results provide empirical support that an integrated PAI may improve prediction of health and disease. Future research should examine the clinical utility of a PAI and verify these findings in prospective studies.
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