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Visualization of Intensity Levels to Reduce the Gap Between Self-Reported and Directly Measured Physical Activity
Published on: March 7, 2019
Relationships between physical activity and other health-related measures using state-based prevalence estimates
Peter D Hart1,2,3, Nestor Asiamah4, Getu Teferi5
1Glenville State University, Glenville, WV 26351, USA.
Background:
Both physical activity and muscle-strengthening activity have known relationships with other health-related variables such as alcohol and tobacco use, diet, and health-related quality of life (HRQOL). The purpose of this study was to explore and quantify the associations between physical activity measures and health-related variables at the higher state level.
Methods:
This cross-sectional study used data from the 2017 and 2019 Behavioral Risk Factor Surveillance System surveys. State-based prevalence (%) estimates were computed for meeting physical activity guidelines (PA), meeting muscle-strengthening activity guidelines (MS), both PA and MS (MB), drinking alcohol (D1), heavy alcohol drinking (HD), fruit consumption (F1), vegetable consumption (V1), good self-rated health (GH), overweight (OW), obesity (OB), current smoking (SN), and smokeless tobacco use (SL). Descriptive statistics, correlation coefficients, and data visualization methods were employed.
Results:
Strongest associations were seen between PA and F1 (2017: r=0.717 & 2019: r=0.695), MS and OB (2017: r=-0.781 & 2019: r=-0.599), PA and GH (2017: r=0.631 & 2019: r=0.649), PA and OB (2017: r=-0.645 & 2019: r=-0.763), and MB and SN (2017: r=-0.713 & 2019: r=-0.645). V1 was associated only with PA (2017: r=0.335 & 2019: r=0.357) whereas OW was not associated only with PA. Canonical correlation analysis showed the physical activity variables were directly related (r c=0.884, P<0.001) to the health variables.
Conclusion:
This study used high-level data to support the many known relationships between PA measures and health-related variables.
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