Author

Wyatt Wutz

Date of Award

January 2021

Document Type

Thesis

Degree Name

Master of Science (MS)

Department

Kinesiology & Public Health Education

First Advisor

Grant Tomkinson

Abstract

Purpose: To establish gender- and age-group specific criterion-referenced cut-points for handgrip strength (HGS) associated with metabolic syndrome (MetS) in United States (U.S.) adults. Methods: A secondary analysis of data from the 2011–12 and 2013–14 cycles of the National Health and Nutrition Examination Survey was performed on U.S. adults aged 20 years and older. HGS was measured using handheld dynamometry. MetS was measured as the presence of three or more cardiometabolic risk factors according to the American Heart Association criteria. Crude and fully adjusted receiver operating characteristic (ROC) curves were used to identify gender- and age group-specific cut-points for HGS associated with increased MetS. Effect sizes for the area under the curve of 0.56, 0.64, and 0.71 were used as thresholds for low, moderate, and high discriminatory ability, respectively. Results: Crude ROC models demonstrated negligible discriminatory ability of HGS to detect MetS (AUC range: 0.49 to 0.55), with negligible to low discriminatory ability for the detection of the component risk factors (AUC range: 0.49 to 0.61). Adjusted ROC models demonstrated low to moderate discriminatory ability of HGS to detect MetS (range AUC: 0.55 to 0.70), with negligible to moderate discriminatory ability for the detection of the component risk factors (AUC range: 0.49 to 0.69). Conclusion: This study is the first to establish criterion-referenced cut-points for HGS to detect MetS in U.S. adults. HGS shows negligible to low discriminatory ability to detect MetS and its risk components, with the discriminatory ability of HGS improving with the addition of covariates. Although these findings do not support the use of HGS as a diagnostic tool for the detection of MetS among U.S. adults, future studies should consider other muscular fitness measures to identify health-related cut-points for MetS.

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