Please wait a minute...
Shopping Cart Email List Chinese
Advanced Search Fig/Tab
Frontiers of Medicine

ISSN 2095-0217

ISSN 2095-0225(Online)

CN 11-5983/R

Postal Subscription Code 80-967

2018 Impact Factor: 1.847

Featured Articles  |  Most Downloaded  |  Most Reading
Online Submission Subscribe to Our RSS Content Feed
Front. Med.    2015, Vol. 9 Issue (1) : 100-107    https://doi.org/10.1007/s11684-014-0372-9
RESEARCH ARTICLE
Prevalence and determinations of physical inactivity among public hospital employees in Shanghai, China: a cross-sectional study
Xinjian Li1(), Minna Cheng1, Hao Zhang2, Ting Ke2, Yisheng Chen1
1. Department of Cardiovascular Disease Prevention of Shanghai Municipal Center for Disease Control and Prevention, Shanghai 200336, China
2. Shanghai Trade Union for Hospital Employees, Shanghai 200040, China
 Download: PDF(112 KB)   HTML
 Export: BibTeX | EndNote | Reference Manager | ProCite | RefWorks
Abstract

This study aims to explore the prevalence and determinations of physical inactivity among hospital employees in Shanghai, China. A cross-sectional study of 4612 employees aged 19 to 68 years was conducted through stratified cluster sampling from different classes of Shanghai hospitals in 2011. The total physical activity was evaluated using the metabolic equivalent according to the Global Physical Activity Questionnaire. Among the participants, 38.5%, 32.3%, and 64.6% of the employees are inactive at work, commuting, and taking leisure time, respectively. Up to 41.8% of the men and 37.8% of the women (P = 0.012) are physically inactive. When the age and educational level are adjusted, male doctors and medical technicians show a higher percentage of physical inactivity than male workers in logistics (P = 0.001). Among females, employees who are working in second- and third-class hospitals show a higher proportion of physical inactivity than those who are working in community health care centers. Logistic regression analyses show that the odds ratios (ORs) of leisure-time physical inactivity associated with the intensity of physical activity at work are 2.259, 2.897, and 4.266 for men (P<0.001) and 2.456, 3.259, and 3.587 for women (P<0.001), respectively. The time during commuting activities is significantly associated with leisure-time physical inactivity in either sex (OR= 2.116 for men and 2.173 for women, P<0.001). Hospital employees, particularly doctors and medical technicians, show a higher proportion of physical inactivity than other inhabitants in Shanghai. The time and intensity of activity at work and commuting are associated with leisure-time activities.
Keywords physical inactivity      prevalence      determination, employee      public hospital      cross-sectional study     
Corresponding Author(s): Xinjian Li   
Just Accepted Date: 24 October 2014   Online First Date: 11 December 2014    Issue Date: 02 March 2015
 Cite this article:   
Xinjian Li,Minna Cheng,Hao Zhang, et al. Prevalence and determinations of physical inactivity among public hospital employees in Shanghai, China: a cross-sectional study[J]. Front. Med., 2015, 9(1): 100-107.
 URL:  
https://academic.hep.com.cn/fmd/EN/10.1007/s11684-014-0372-9
https://academic.hep.com.cn/fmd/EN/Y2015/V9/I1/100
Characteristic Men, n (%) Women, n (%)
(total number 1203) (total number 3409)
Age (year)
<30 303 (25.2) 1346 (39.5)
30−39 421 (35.0) 1227 (36.0)
40−49 234 (19.5) 614 (18.0)
50−69 245 (20.4) 222 (6.5)
Educational level
High school and the following 194 (16.1) 786 (23.1)
College 206 (17.1) 1392 (40.8)
Undergraduate 527 (43.8) 911 (26.7)
Graduate 276 (22.9) 320 (9.4)
Occupation
Doctor 715 (59.4) 707 (20.7)
Nurse − 2031 (59.6)
Manager 91 (7.6) 196 (5.7)
Worker in logistics 152 (12.6) 70 (2.1)
Medical technician 245 (20.4) 405 (11.9)
Grade of working hospital
Third class 560 (46.6) 1746 (51.2)
Second class 543 (45.1) 1400 (41.1)
CHCC 100 (8.3) 263 (7.7)
Tab.1  Demographic characteristics of participants
Men Women Both
n % (95% CI) n % (95% CI) n % (95% CI)
Inactive at work 510 42.4 (39.6−45.2) 1264 37.1 (35.5−38.7) 1774 38.5 (37.1−39.9)
Inactive at commuting 432 35.9 (33.2−38.6) 1059 31.1 (29.5−32.6) 1491 32.3 (31.0−33.7)
Inactive at leisure time 640 53.2 (50.4−56.1) 2338 68.6 (67.0−70.1) 2978 64.6 (63.2−66.0)
Tab.2  Distribution of participants classified as doing no work, commuting, and leisure-time physical inactivity by sex and overall
Men Women
n % (95% CI) n % (95% CI)
Total 511 41.8 (39.0−44.6) 1287 37.8 (36.1−39.4)
Age group (year)
<30 114 36.0 (30.5−41.4) 541 40.2 (37.6−42.8)
30−39 212 49.6 (44.9−54.4) 465 37.9 (35.2−40.6)
40−49 96 41.0 (34.7−47.4) 213 34.7 (30.9−38.5)
50−59 89 36.3 (30.3−42.4) 68 30.6 (24.5−36.7)
c 2 = 18.805, P<0.001 c 2 = 10.664, P = 0.014
Education
High school and the following 60 30.4 (23.9−36.9) 270 34.4 (31.0−37.7)
College 86 39.8 (33.1−46.6) 534 38.4 (35.8−40.9)
Undergraduate 224 42.1 (37.9−46.4) 361 39.6 (36.4−42.8)
Graduate 141 50.7 (44.8−56.7) 122 38.1 (32.8−43.5)
c 2 = 20.085, P<0.001 c 2 = 5.470, P = 0.140
Occupation
Doctor 327 45.7 (42.1−49.4) 276 39.0 (35.4−42.6)
Nurse 0 − 762 37.5 (35.4−39.6)
Manager 38 41.8 (31.4−52.1) 73 37.2 (30.4−44.1)
Worker in logistics 40 26.3 (19.2−33.4) 25 35.7 (24.2−47.2)
Medical technician 98 40.0 (33.8−46.2) 151 37.3 (32.6−42.0)
c 2 = 19.854, P = 0.001 c 2 = 0.728, P = 0.948
Hospital grade
Third class 255 44.6 (40.5−48.8) 702 40.2 (37.9−42.5)
Second class 218 39.6 (35.5−43.7) 513 36.6 (34.1−39.2)
CHCC 38 38.0 (28.3−47.7) 72 27.4 (22.0−32.8)
c 2 = 2.826, P = 0.243 c 2 = 17.256, P<0.001
Tab.3  Proportion of participants with total physical inactivity by age, sex, education, occupation, and hospital grade
Men Women
OR 95% CI OR 95% CI
Age group (year)
<30 Ref. Ref.
30−39 1.666 1.225−2.266 0.874 0.740−1.032
40−49 1.208 0.840−1.737 0.775 0.631−0.952
50−59 1.346 0.882−2.054 0.695 0.502−0.960
Education
High school and the following Ref. Ref.
College 1.241 0.764−2.017 1.112 0.919−1.345
Undergraduate 1.187 0.705−1.998 1.122 0.885−1.422
Graduate 1.462 0.804−2.659 0.876 0.610−1.259
Occupation
Doctor 1.949 1.182−3.213 1.207 0.700−2.080
Nurse − − 0.968 0.584−1.604
Manager 1.759 0.951−3.253 1.002 0.561−1.791
Worker in logistics Ref. Ref.
Medical technician 1.663 1.016−2.721 1.029 0.601−1.763
Hospital grade
Third class 1.196 0.741−1.931 1.790 1.324−2.421
Second class 1.063 0.671−1.685 1.487 1.100−2.010
CHCC Ref. Ref.
Tab.4  Odds ratio (OR) and 95% confidence interval (CI) for total physical inactivity
Crude OR Adjusted OR
OR 95% CI OR 95% CI
Men
Activity at work
Low or inactivity Ref. Ref
Only moderate intensity 2.588 1.949−3.436 2.259 1.675−3.045
Only vigorous intensity 2.910 1.516−5.586 2.897 1.482−5.666
Moderate and vigorous intensity 4.453 3.217−6.162 4.266 3.015−6.037
Travel to and from workplaces
<10?min continuously Ref.
≥10?min continuously 2.645 2.005−3.488 2.116 1.572−2.848
Women
Activity at work
Low or inactivity Ref. Ref.
Only moderate intensity 2.668 2.187−3.254 2.456 1.999−3.017
Only vigorous intensity 3.241 1.919−5.474 3.259 1.910−5.561
Moderate and vigorous intensity 3.791 2.960−4.855 3.587 2.778−4.631
Travel to and from workplaces
<10?min continuously Ref. Ref.
≥10?min continuously 2.647 2.162−3.241 2.173 1.763−2.680
Tab.5  ORs and 95% CI for inactivity during leisure-time based on occupation and commuting physical activity categories by sex
1 W Drygas, T Kostka, A Jegier, H Kuński. Long-term effects of different physical activity levels on coronary heart disease risk factors in middle-aged men. Int J Sports Med 2000; 21(4): 235–241
https://doi.org/10.1055/s-2000-309 pmid: 10853693
2 IM Lee, RS Paffenbarger Jr. Associations of light, moderate, and vigorous intensity physical activity with longevity. The Harvard Alumni Health Study. Am J Epidemiol 2000; 151(3): 293–299
https://doi.org/10.1093/oxfordjournals.aje.a010205 pmid: 10670554
3 CL Li, JD Lin, SJ Lee, RF Tseng. Associations between the metabolic syndrome and its components, watching television and physical activity. Public Health 2007; 121(2): 83–91
https://doi.org/10.1016/j.puhe.2006.08.004 pmid: 17188724
4 RR Pate, M Pratt, SN Blair, WL Haskell, CA Macera, C Bouchard, D Buchner, W Ettinger, GW Heath, AC King, A Kriska, AS Leon, BH Marcus, J Morris, Jr RS Paffenbarger, K Patrick, ML Pollock, JM Rippe, J Sallis, JH Wilmore . Physical activity and public health. A recommendation from the Centers for Disease Control and Prevention and the American College of Sports Medicine. JAMA 1995; 273(5): 402–407
https://doi.org/10.1001/jama.1995.03520290054029 pmid: 7823386
5 J Zhang, J Chaaban. The economic cost of physical inactivity in China. Prev Med 2013; 56(1): 75–78
https://doi.org/10.1016/j.ypmed.2012.11.010 pmid: 23200874
6 World Health Organization. Global Status Report on Noncommunicable Diseases 2010. Geneva: World Health Organization, 2010: 18–19
7 Chinese Center for Disease Control and Prevention. Report on Chronic Disease Risk Factor Surveillance in China 2007. Beijing: People’s Medical Publishing House (in Chinese, Abstract in English)
8 K Heikkilä, EI Fransson, ST Nyberg, M Zins, H Westerlund, P Westerholm, M Virtanen, J Vahtera, S Suominen, A Steptoe, P Salo, J Pentti, T Oksanen, M Nordin, MG Marmot, T Lunau, KH Ladwig, M Koskenvuo, A Knutsson, F Kittel, KH Jöckel, M Goldberg, R Erbel, N Dragano, D DeBacquer, E Clays, A Casini, L Alfredsson, JE Ferrie, A Singh-Manoux, GD Batty, M Kivimäki; IPD-Work Consortium. Job strain and health-related lifestyle: findings from an individual-participant meta-analysis of 118,000 working adults. Am J Public Health 2013; 103(11): 2090–2097
https://doi.org/10.2105/AJPH.2012.301090 pmid: 23678931
9 H Wu, TS Chi, L Chen, L Wang, YP Jin. Occupational stress among hospital nurses: cross-sectional survey. J Adv Nurs 2010; 66(3): 627–634
https://doi.org/10.1111/j.1365-2648.2009.05203.x pmid: 20423397
10 J Li, W Yang, SI Cho. Gender differences in job strain, effort-reward imbalance, and health functioning among Chinese physicians. Soc Sci Med 2006; 62(5): 1066–1077
https://doi.org/10.1016/j.socscimed.2005.07.011 pmid: 16120473
11 EJ Brunner, T Chandola, MG Marmot. Prospective effect of job strain on general and central obesity in the Whitehall II Study. Am J Epidemiol 2007; 165(7): 828–837
https://doi.org/10.1093/aje/kwk058 pmid: 17244635
12 SM Ali, M Lindström. Psychosocial work conditions, unemployment, and leisure-time physical activity: a population-based study. Scand J Public Health 2006; 34(2): 209–216
https://doi.org/10.1080/14034940500307515 pmid: 16581714
13 GPAQ: Global Physical Activity Questionnaire (version 2.0).
14 T Armstrong, R Bonita. Capacity building for an integrated noncommunicable disease risk factor surveillance system in developing countries. Ethn Dis 2003; 13(Suppl 2): S13–S18
pmid: 13677407
15 FC Bull, TS Maslin, T Armstrong. Global physical activity questionnaire (GPAQ): nine country reliability and validity study. J Phys Act Health 2009; 6(6): 790–804
pmid: 20101923
16 IM Lee, EJ Shiroma, F Lobelo, P Puska, SN Blair, PT Katzmarzyk; the Lancet Physical Activity Series Working Group. Effect of physical inactivity on major non-communicable diseases worldwide: an analysis of burden of disease and life expectancy. Lancet 2012; 380(9838): 219–229
https://doi.org/10.1016/S0140-6736(12)61031-9 pmid: 22818936
17 XJ Li, JY Xu, WJ Zhong. Report on Chronic Disease and Risk Factors Surveillance in Shanghai 2007. Shanghai: Shanghai Popular Science Press, 2012 (in Chinese, Abstract in English)
18 C Gidlow, LH Johnston, D Crone, N Ellis, D James. A systematic review of the relationship between socio-economic position and physical activity. Health Educ J 2006; 65(4): 338–367
https://doi.org/10.1177/0017896906069378
19 RC Brownson, AA Eyler, AC King, DR Brown, YL Shyu, JF Sallis. Patterns and correlates of physical activity among US women 40 years and older. Am J Public Health 2000; 90(2): 264–270
https://doi.org/10.2105/AJPH.90.2.264 pmid: 10667189
20 ES Ford, RK Merritt, GW Heath, KE Powell, RA Washburn, A Kriska, G Haile. Physical activity behaviors in lower and higher socioeconomic status populations. Am J Epidemiol 1991; 133(12): 1246–1256
pmid: 2063832
21 XZ He, DW Baker. Differences in leisure-time, household, and work-related physical activity by race, ethnicity, and education. J Gen Intern Med 2005; 20(3): 259–266
https://doi.org/10.1111/j.1525-1497.2005.40198.x pmid: 15836530
22 AC King, SN Blair, DE Bild, RK Dishman, PM Dubbert, BH Marcus, NB Oldridge, RS Paffenbarger Jr, KE Powell, KK Yeager. Determinants of physical activity and interventions in adults. Med Sci Sports Exerc 1992; 24(Suppl 6): S221–S236
https://doi.org/10.1249/00005768-199206001-00005 pmid: 1625548
23 T Pisljar, T van der Lippe, L den Dulk. Health among hospital employees in Europe: a cross-national study of the impact of work stress and work control. Soc Sci Med 2011; 72(6): 899–906
https://doi.org/10.1016/j.socscimed.2010.12.017 pmid: 21330025
24 A Kouvonen, J Vahtera, T Oksanen, J Pentti, AK Väänänen, T Heponiemi, P Salo, M Virtanen, M Kivimäki. Chronic workplace stress and insufficient physical activity: a cohort study. Occup Environ Med 2013; 70(1): 3–8
https://doi.org/10.1136/oemed-2012-100808 pmid: 23014593
25 MJ Smith, MJ Colligan, JJ Hurrell. A review of NIOSH psychological stress research-1977. In: Occupational Stress: Proceedings of the Conference on Occupational Stress (DHEW NIOSH, publication no. 78−156). Washington, DC: U.S. Government Printing Office, 1978
26 A Holtermann, JL Marott, F Gyntelberg, K Søgaard, P Suadicani, OS Mortensen, E Prescott, P Schnohr. Does the benefit on survival from leisure time physical activity depend on physical activity at work? A prospective cohort study. PLoS ONE 2013; 8(1): e54548
https://doi.org/10.1371/journal.pone.0054548 pmid: 23349926
27 EI1 Fransson, K Heikkilä, ST Nyberg, M Zins, H Westerlund, P Westerholm, A Väänänen, M Virtanen, J Vahtera, T Theorell, S Suominen, A Singh-Manoux, J Siegrist, S Sabia, R Rugulies, J Pentti, T Oksanen, M Nordin, ML Nielsen, MG Marmot, LL Magnusson Hanson, IE Madsen, T Lunau, C Leineweber, M Kumari, A Kouvonen, A Koskinen, M Koskenvuo, A Knutsson, F Kittel, KH Jöckel, M Joensuu, IL Houtman, WE Hooftman, M Goldberg, GA Geuskens, JE Ferrie, R Erbel, N Dragano, D De Bacquer, E Clays, A Casini, H Burr, M Borritz, S Bonenfant, JB Bjorner, L Alfredsson, M Hamer, GD Batty, M Kivimäki. Job strain as risk factor for leisure-time physical inactivity: an individual-participant Meta-analysis of up to 170000 men and women. The IPD-Work Consortium. Am J Epidemiol 2012; 176: 1078–1089
https://doi.org/10.1093/aje/kws336 pmid: 23144364
[1] Dahai Zhao, Zhiruo Zhang. Qualitative analysis of direction of public hospital reforms in China[J]. Front. Med., 2018, 12(2): 218-223.
[2] N.V. Vasilyeva, E.R. Raush, M.V. Rudneva, T.S. Bogomolova, A.E. Taraskina, Yong Fang, Fengmin Zhang, N.N. Klimko. Etiology of invasive candidosis agents in Russia: a multicenter epidemiological survey[J]. Front. Med., 2018, 12(1): 84-91.
[3] Jun-Jie XIAO MD, Yi-Han CHEN MD, PhD, . Prevalence of cardiovascular diseases in China[J]. Front. Med., 2010, 4(1): 16-20.
Viewed
Full text


Abstract

Cited
  Shared   
  Discussed