Kristofer Hedman1, Per Sandström2, Hanna Lindblom3, Mats Lowén4, Tomas Faresjö5. 1. Department of Clinical Physiology, and Department of Health, Medicine and Caring Sciences, Linköping University, Linköping, Sweden. 2. Department of Surgery, Department of Biomedical and Clinical Sciences, Linköping University, Linköping, Sweden. 3. Department of Health, Medicine and Caring Sciences, Division of Prevention, Rehabilitation and Community Medicine, Unit of Physiotherapy, Linköping University, Linköping, Sweden. hanna.lindblom@liu.se. 4. Unit for Public Health and Statistics, Department of Health, Medicine and Caring Sciences, Linköping University, Linköping, Sweden. 5. Department of Health, Medicine and Caring Sciences, Division of Prevention, Rehabilitation and Community Medicine, Linköping University, Linköping, Sweden.
Abstract
BACKGROUND: Physical activity has positive effects on several diseases and may reduce the risk of morbidity and the mortality rate. Whether the prevalence of disease and health care consumption differ between the members of sports organizations and the general population has not been established. Hence, this pilot study aimed to compare the prevalence of diseases known to be associated with physical inactivity and health care consumption in members of a large non-profit sports organization and an age-, sex- and geographically matched random sample from the general population. METHODS: Subjects in two Swedish cities who exercised at least once a week and had been members for at least two years in the non-profit sports organization Friskis&Svettis were invited. A randomized age-, sex- and geographically matched sample was drawn from the general population. Data on disease prevalence (by International Statistical Classification of Diseases and Related Health Problems, Tenth Revision (ICD-10) codes) and health care consumption were retrieved using the members' personal identification numbers through a regional health care database. Between-group differences in the prevalence of disease were compared using chi2-tests and logistic regression between members and controls. Health care consumption was defined as the number of visits, stratified by primary and hospital care, and was compared using chi2-tests and Mann-Whitney U-tests. RESULTS: In total, 3015 subjects were included in each group (response rate 11%). Controls had higher prevalence rates of musculoskeletal diseases (13.3% vs. 11.6%, p = 0.047), metabolic disease (10.4% vs. 5.4%, p < 0.001), hypertension (16.6% vs. 11.7%, p < 0.001), psychiatric diseases (8.9% vs. 7.1%, p = 0.012) and lung cancer (0.4% vs. 0%, p = 0.001) than the members. The total number of health care contacts was 22% higher in the controls than in the members, whereas the proportion of subjects with at least one health care visit was larger in the members (89% vs. 79%, p < 0.001). CONCLUSIONS: The prevalence rates of lifestyle diseases related to musculoskeletal, metabolic and psychiatric diseases, hypertension and lung cancer, and the overall health care consumption, were lower among members of a sports organization than among controls. However, longitudinal studies are needed to establish a cause-effect relationship between membership and disease development.
BACKGROUND: Physical activity has positive effects on several diseases and may reduce the risk of morbidity and the mortality rate. Whether the prevalence of disease and health care consumption differ between the members of sports organizations and the general population has not been established. Hence, this pilot study aimed to compare the prevalence of diseases known to be associated with physical inactivity and health care consumption in members of a large non-profit sports organization and an age-, sex- and geographically matched random sample from the general population. METHODS: Subjects in two Swedish cities who exercised at least once a week and had been members for at least two years in the non-profit sports organization Friskis&Svettis were invited. A randomized age-, sex- and geographically matched sample was drawn from the general population. Data on disease prevalence (by International Statistical Classification of Diseases and Related Health Problems, Tenth Revision (ICD-10) codes) and health care consumption were retrieved using the members' personal identification numbers through a regional health care database. Between-group differences in the prevalence of disease were compared using chi2-tests and logistic regression between members and controls. Health care consumption was defined as the number of visits, stratified by primary and hospital care, and was compared using chi2-tests and Mann-Whitney U-tests. RESULTS: In total, 3015 subjects were included in each group (response rate 11%). Controls had higher prevalence rates of musculoskeletal diseases (13.3% vs. 11.6%, p = 0.047), metabolic disease (10.4% vs. 5.4%, p < 0.001), hypertension (16.6% vs. 11.7%, p < 0.001), psychiatric diseases (8.9% vs. 7.1%, p = 0.012) and lung cancer (0.4% vs. 0%, p = 0.001) than the members. The total number of health care contacts was 22% higher in the controls than in the members, whereas the proportion of subjects with at least one health care visit was larger in the members (89% vs. 79%, p < 0.001). CONCLUSIONS: The prevalence rates of lifestyle diseases related to musculoskeletal, metabolic and psychiatric diseases, hypertension and lung cancer, and the overall health care consumption, were lower among members of a sports organization than among controls. However, longitudinal studies are needed to establish a cause-effect relationship between membership and disease development.
Entities:
Keywords:
Lifestyle; Physical inactivity; Training effects
Authors: Carina Wennerholm; Björn Grip; Annakarin Johansson; Hans Nilsson; Marja-Liisa Honkasalo; Tomas Faresjö Journal: Int J Health Geogr Date: 2011-01-12 Impact factor: 3.918
Authors: Ding Ding; Kenny D Lawson; Tracy L Kolbe-Alexander; Eric A Finkelstein; Peter T Katzmarzyk; Willem van Mechelen; Michael Pratt Journal: Lancet Date: 2016-07-28 Impact factor: 79.321
Authors: R R Bannuru; M C Osani; E E Vaysbrot; N K Arden; K Bennell; S M A Bierma-Zeinstra; V B Kraus; L S Lohmander; J H Abbott; M Bhandari; F J Blanco; R Espinosa; I K Haugen; J Lin; L A Mandl; E Moilanen; N Nakamura; L Snyder-Mackler; T Trojian; M Underwood; T E McAlindon Journal: Osteoarthritis Cartilage Date: 2019-07-03 Impact factor: 6.576
Authors: Ulf Ekelund; Jakob Tarp; Jostein Steene-Johannessen; Bjørge H Hansen; Barbara Jefferis; Morten W Fagerland; Peter Whincup; Keith M Diaz; Steven P Hooker; Ariel Chernofsky; Martin G Larson; Nicole Spartano; Ramachandran S Vasan; Ing-Mari Dohrn; Maria Hagströmer; Charlotte Edwardson; Thomas Yates; Eric Shiroma; Sigmund A Anderssen; I-Min Lee Journal: BMJ Date: 2019-08-21
Authors: Sharon L Kolasinski; Tuhina Neogi; Marc C Hochberg; Carol Oatis; Gordon Guyatt; Joel Block; Leigh Callahan; Cindy Copenhaver; Carole Dodge; David Felson; Kathleen Gellar; William F Harvey; Gillian Hawker; Edward Herzig; C Kent Kwoh; Amanda E Nelson; Jonathan Samuels; Carla Scanzello; Daniel White; Barton Wise; Roy D Altman; Dana DiRenzo; Joann Fontanarosa; Gina Giradi; Mariko Ishimori; Devyani Misra; Amit Aakash Shah; Anna K Shmagel; Louise M Thoma; Marat Turgunbaev; Amy S Turner; James Reston Journal: Arthritis Rheumatol Date: 2020-01-06 Impact factor: 10.995