Journal of Physical Activity Research
ISSN (Print): 2576-1919 ISSN (Online): 2574-4437 Website: https://www.sciepub.com/journal/jpar Editor-in-chief: Peter Hart
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Journal of Physical Activity Research. 2022, 7(2), 98-105
DOI: 10.12691/jpar-7-2-4
Open AccessArticle

Bivariate and Multivariate Associations between Physical Activity and Body Measure Variables in US Adults, 2017-2020 Pre-pandemic

Peter D. Hart1,

1Health Promotion Research, Havre, MT 59501

Pub. Date: August 03, 2022

Cite this paper:
Peter D. Hart. Bivariate and Multivariate Associations between Physical Activity and Body Measure Variables in US Adults, 2017-2020 Pre-pandemic. Journal of Physical Activity Research. 2022; 7(2):98-105. doi: 10.12691/jpar-7-2-4

Abstract

Background: Examining the extent to which physical activity (PA) and body measure (BM) variables correlate is useful for the promotion of a healthy lifestyle. Therefore, the purpose of this study was to examine the associations between PA and BM variables in a representative sample of US adults. Methods: Participants 20+ years of age from the 2017-2020 (pre-pandemic, 3.2 year) National Health and Nutrition Examination Survey (NHANES) were used. PA variables included work (VWPA, MWPA), recreation (VRPA, MRPA), transportation (TPA), sedentary time (SED), moderate-to-vigorous PA (MVPA), met PA guidelines status (METPA), and physical inactivity status (PIA). BM variables included body mass index (BMI), waist circumference (WC), arm circumference (AC), BMI category (BMICAT), obese status (OBESE), and overweight status (OVWT). Spearman correlations were computed both for bivariate association and controlling for age, race, and income. Multiple logistic regression was used to examine the adjusted relationship between PA and BM categorical variables. All analyses were performed separately by sex. Results: Multivariate BM correlations were strongest for TPA and OVWT (males) and MVPA and WC (females). Adjusted models showed the odds of being obese were greatest for those reporting low (versus high) amounts of VRPA in both males (OR = 1.84, 95% CI: 1.28 - 2.67) and females (OR = 2.47, 95% CI: 1.83 - 3.34). Additionally, odds of meeting PA guidelines were greatest for those with low (versus high) WC in males (OR = 1.51, 95% CI: 1.2 3- 1.84) and low (versus high) BMI in females (OR = 2.06, 95% CI: 1.73 - 2.46). Conclusion: Results from this study indicate that PA and BM variables are related in U.S. adults prior to the COVID pandemic. Furthermore, low WC for males and low BMI for females were the stronger adjusted categorical predictors of meeting PA guidelines.

Keywords:
physical activity body composition epidemiology population health pre-pandemic

Creative CommonsThis work is licensed under a Creative Commons Attribution 4.0 International License. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/

References:

[1]  Wei J, Liu X, Xue H, Wang Y, Shi Z. Comparisons of visceral adiposity index, body shape index, body mass index and waist circumference and their associations with diabetes mellitus in adults. Nutrients. 2019 Jul 12; 11(7): 580.
 
[2]  Recalde M, Davila-Batista V, Díaz Y, Leitzmann M, Romieu I, Freisling H, Duarte-Salles T. Body mass index and waist circumference in relation to the risk of 26 types of cancer: a prospective cohort study of 3.5 million adults in Spain. BMC medicine. 2021 Dec; 19(1): 1-4.
 
[3]  Momin M, Fan F, Li J, Jia J, Zhang L, Zhang Y, Huo Y. Joint effects of body mass index and waist circumference on the incidence of hypertension in a community-based Chinese population. Obesity facts. 2020; 2(2): 245-55.
 
[4]  Canoy D, Cairns BJ, Balkwill A, Wright FL, Green J, Reeves G, Beral V, Million Women Study Collaborators. Coronary heart disease incidence in women by waist circumference within categories of body mass index. European journal of preventive cardiology. 2013 Oct 1; 20(5): 759-62.
 
[5]  Roswall N, Li Y, Sandin S, Ström P, Adami HO, Weiderpass E. Changes in body mass index and waist circumference and concurrent mortality among Swedish women. Obesity. 2017 Jan; 25(1): 215-22.
 
[6]  Lo K, Huang YQ, Shen G, Huang JY, Liu L, Yu YL, Chen CL, Feng YQ. Effects of waist to height ratio, waist circumference, body mass index on the risk of chronic diseases, all-cause, cardiovascular and cancer mortality. Postgraduate Medical Journal. 2021 May 1; 97(1147): 306-11.
 
[7]  Kim YH, Kim SM, Han KD, Jung JH, Lee SS, Oh SW, Park HS, Rhee EJ, Lee WY, Yoo SJ. Waist circumference and all-cause mortality independent of body mass index in Korean population from the National Health Insurance Health Checkup 2009-2015. Journal of clinical medicine. 2019 Jan 10; 8(1): 72.
 
[8]  Lisko I, Stenholm S, Raitanen J, Hurme M, Hervonen A, Jylhä M, Tiainen K. Association of body mass index and waist circumference with physical functioning: the vitality 90+ study. Journals of Gerontology Series A: Biomedical Sciences and Medical Sciences. 2015 Jul 1; 70(7): 885-91.
 
[9]  Kang K, Lee WW, Lee JJ, Park JM, Kwon O, Kim BK. Comparison of body mass index, waist circumference, and waist-height ratio in predicting functional outcome following ischemic stroke. Journal of thrombosis and thrombolysis. 2017 Aug; 44(2): 238-44.
 
[10]  Hyun YY, Lee KB, Chung W, Kim YS, Han SH, Oh YK, Chae DW, Park SK, Oh KH, Ahn C. Body Mass Index, waist circumference, and health-related quality of life in adults with chronic kidney disease. Quality of Life Research. 2019 Apr; 28(4): 1075-83.
 
[11]  Wang L, Crawford JD, Reppermund S, Trollor J, Campbell L, Baune BT, Sachdev P, Brodaty H, Samaras K, Smith E. Body mass index and waist circumference predict health-related quality of life, but not satisfaction with life, in the elderly. Quality of Life Research. 2018 Oct; 27(10): 2653-65.
 
[12]  Piercy KL, Troiano RP, Ballard RM, Carlson SA, Fulton JE, Galuska DA, George SM, Olson RD. The physical activity guidelines for Americans. Jama. 2018 Nov 20; 320(19): 2020-8.
 
[13]  Ku PW, Chen LJ, Fox KR, Chen YH, Liao Y, Lin CH. Leisure-time, domestic, and work-related physical activity and their prospective associations with all-cause mortality in patients with cardiovascular disease. The American Journal of Cardiology. 2018 Jan 15; 121(2): 177-81.
 
[14]  Li R, Zhang S, Li Q, Meng Q, Zu C, Zhang Y, He P, Liu M, Zhou C, Ye Z, Wu Q, Yang S, Zhang Y, Liu C, Qin X. Transportation physical activity and new-onset hypertension: A nationwide cohort study in China. Hypertens Res. 2022 Jul 13. Epub ahead of print. PMID: 35831583.
 
[15]  Torres ER, Bendlin BB, Kassahun-Yimer W, Magnotta VA, Paradiso S. Transportation physical activity earlier in life and areas of the brain related to dementia later in life. Journal of transport & health. 2021 Mar 1; 20: 100992.
 
[16]  Dogra S, Copeland JL, Altenburg TM, Heyland DK, Owen N, Dunstan DW. Start with reducing sedentary behavior: A stepwise approach to physical activity counseling in clinical practice. Patient Education and Counseling. 2021 Sep 13.
 
[17]  Luijckx E, Lohse T, Faeh D, Rohrmann S. Joints effects of BMI and smoking on mortality of all-causes, CVD, and cancer. Cancer Causes & Control. 2019 May; 30(5): 549-57.
 
[18]  Tobias DK, Hu FB. The association between BMI and mortality: implications for obesity prevention. The Lancet Diabetes & Endocrinology. 2018 Dec 1; 6(12): 916-7.
 
[19]  Kim SH, Lim J, Lee J, Park HS. Relationship of domain-specific quality of life with body mass index and waist circumference in a Korean elderly population. Aging Clinical and Experimental Research. 2021 Dec; 33(12): 3257-67.
 
[20]  Song DK, Hong YS, Sung YA, Lee H. Waist circumference and mortality or cardiovascular events in a general Korean population. Plos one. 2022 Apr 27; 17(4): e0267597.
 
[21]  Nishiwaki M, Nakashima N, Ikegami Y, Kawakami R, Kurobe K, Matsumoto N. A pilot lifestyle intervention study: effects of an intervention using an activity monitor and Twitter on physical activity and body composition. The Journal of Sports Medicine and Physical Fitness. 2016 Mar 8; 57(4): 402-10.
 
[22]  Akinbami LJ, Chen TC, Davy O, Ogden CL, Fink S, Clark J, et al. National Health and Nutrition Examination Survey, 2017–March 2020 prepandemic file: Sample design, estimation, and analytic guidelines. National Center for Health Statistics. Vital Health Stat 2(190). 2022.
 
[23]  SAS Institute Inc. 2015. Base SAS 9.4 Procedures Guide. 5th ed. Cary, NC: SAS Institute Inc. Available: http://support.sas.com.
 
[24]  Wei T, Simko VR, Levy M. R package “corrplot”: Visualization of a Correlation Matrix. 2017. Version 0.84. 2021 Apr.
 
[25]  Zhu W, Cheng Z, Howard VJ, Judd SE, Blair SN, Sun Y, Hooker SP. Is adiposity associated with objectively measured physical activity and sedentary behaviors in older adults?. BMC geriatrics. 2020 Dec; 20(1): 1-8.
 
[26]  Cárdenas Fuentes G, Bawaked RA, Martínez González MÁ, Corella D, Subirana Cachinero I, Salas-Salvadó J, Estruch R, Serra-Majem L, Ros E, Lapetra Peralta J, Fiol M. Association of physical activity with body mass index, waist circumference and incidence of obesity in older adults. European journal of public health. 2018 Oct 1; 28(5): 944-50.
 
[27]  Chu AH, Ng SH, Koh D, Müller-Riemenschneider F. Reliability and validity of the self-and interviewer-administered versions of the Global Physical Activity Questionnaire (GPAQ) PLoS One. 2015; 10: e0136944.