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Physical activity level and associated factors among civil servants in Xi’an, China
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Original research
Physical activity level and associated factors among civil servants in Xi’an, China Lijun Sun a,1 , Xun Jiang b,1 , Xin Zhao c , Yuhai Zhang a , Yongyong Xu a,∗ , Lei Shang a,∗ a b c
Department of Health Statistics, School of Public Health, Fourth Military Medical University, China Department of Paediatrics, Tangdu Hospital, Fourth Military Medical University, China Nautical and Aviation Medical Center, Navy General Hospital, China
a r t i c l e
i n f o
Article history: Received 23 January 2015 Received in revised form 15 July 2015 Accepted 25 August 2015 Available online xxx Keywords: Cross-sectional study Adult Exercise International physical activity questionnaire (Chinese version)
a b s t r a c t Objectives: This study investigated physical activity levels and associated factors among civil servants in Xi’an, China, to provide reference data for the implementation of health improvement strategies among civil servants. Design: A cross-section study. Methods: A random sample of 1000 civil servants aged 18–60 years and employed by the Xi’an civic government was assessed by using the Chinese version of the International Physical Activity Questionnaire. Associations between physical activity and sociodemographic characteristics, family history of chronic disease, and existing disease were evaluated by the Mann–Whitney U-test, Kruskal–Wallis H-test, and binary logistic regression. Results: The response rate was 92.4%. The median physical activity score was 2227 metabolic equivalents of task (MET) minutes per week (interquartile range [IQR]: 1308–3802 MET min/week). Among the 924 participants, 7.4% did not meet minimum recommendations for physical activity, 57.3% had moderate activity levels, and 35.4% had high activity levels. Participants spent most of their time on occupational activities (median: 869 MET min/week, IQR: 228–1953 MET min/week). Female sex (odds ratio [OR]:0.40, 95% confidence interval [CI]:0.29–0.55), age ≥ 51 years (OR: 0.45, 95%CI: 0.27–0.75), and family history of chronic disease (OR: 0.67, 95%CI: 0.48–0.94) were associated with significantly lower odds of a high activity level. Conclusions: Most civil servants in Xi’an, China, have moderate activity levels. Some have high activity levels, but few engage in vigorous-intensity physical activity. Interventions to encourage a high level of physical activity are needed, especially for women, older civil servants, and those with family histories of chronic disease. © 2015 Sports Medicine Australia. Published by Elsevier Ltd. All rights reserved.
1. Introduction As an important health-related behavior in daily life, physical activity has major health benefits related to reducing the risks of coronary heart disease, stroke, diabetes, hypertension, depression, etc. Physical activity is a key determinant of energy expenditure and, thus, is fundamental to energy balance and weight control.1 Nevertheless, despite these benefits, the World Health Organization (WHO) has consistently reported that one
∗ Corresponding authors. E-mail addresses: [email protected] (Y. Xu), [email protected] (L. Shang) 1 Lijun Sun and Xun Jiang have an equal contribution to this study, they are co-first author.
in three adults worldwide is not sufficiently active (e.g., activity levels <600 metabolic equivalents of task [MET] min/week). Each year, 3.2 million people die due to physical inactivity, which was the fourth leading risk factor for death worldwide in 2009.2 A recent study showed that 31% of adults worldwide are physically inactive, with proportions of physical inactivity ranging from 17% in Southeast Asia to 43% in the United States and eastern Mediterranean.3 Among Chinese adults, average weekly physical activity fell by 32% between 1991 and 2006.4 Increasing urbanization and rapid economic development in China have been linked to reductions in occupational and overall physical activity.5 Some population groups, such as civil servants, tend to be less physically active and more vulnerable to chronic diseases than the general population. Obesity was found to be more prevalent among Nepalese civil servants than in the general population.6
http://dx.doi.org/10.1016/j.jsams.2015.08.003 1440-2440/© 2015 Sports Medicine Australia. Published by Elsevier Ltd. All rights reserved.
Please cite this article in press as: Sun L, et al. Physical activity level and associated factors among civil servants in Xi’an, China. J Sci Med Sport (2015), http://dx.doi.org/10.1016/j.jsams.2015.08.003
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2
The Whitehall II, Helsinki Health, and Japanese Civil Servants studies all suggested that the work-related stress, long working hours, and limited time for physical activity of civil servants were associated with chronic disease and increased mortality rates among civil servants in London, Finland, and Japan, respectively.7 For these reasons, assessments of the physical activity of civil servants should be an essential component of any intervention aimed at supporting the struggle against physical inactivity . Any understanding of the factors associated with the level of physical activity is necessary for designing and implementing interventions to increase physical activity for at-risk civil servants. Numerous studies of physical activity-related factors have been conducted on school adolescents.8 However, few such studies have focused on civil servants and, to the best of our knowledge, no study has quantitatively described physical activity levels among civil servants in China. Therefore, the aim of this study was to identify the physical activity level (with consideration of activity intensity) and associated factors among civil servants in Xi’an, China, with the end goal of providing reference data for the development and implementation of health improvement strategies in this group of workers.
2. Methods This cross-sectional survey included civil servants employed in the Xi’an civic government who underwent annual health examinations at Xijing and Tangdu Hospitals in Xi’an, between July and September 2012. A total of 1000 participants, who were randomly selected by a computer program and identified by birth date, name, and address from the data register of the health examination centers of the two hospitals, were invited to participate in the study. The Human Subject Review Committee of Fourth Military Medical University approved this study. All participants provided written informed consent before taking part in the survey. Xijing and Tangdu Hospitals are two of the largest AAA hospitals in Xi’an. The AAA distinction is awarded to the best hospitals in China. Hospitals with this distinction have the capacity to provide high-level medical services and education and to undertake major scientific research projects. The two hospitals treat a comprehensive spectrum of diseases and cover the whole population of Xi’an. Their health examination centers are designated institutions for annual health examinations for all civil servants in the Xi’an civic government. Eligible participants were 18–60 years and able to read and write well enough to fill out the physical activity questionnaire. Civil servants with serious diseases or disabilities that limited daily physical activity were excluded from the study. Physical activity was assessed by the self-administered longform Chinese version of the International Physical Activity Questionnaire (IPAQ-C).9 The long-form IPAQ-C was designed primarily for population surveillance of physical activity among adults (aged 15–69 years). It comprises 31 questions about the frequency of and time spent walking and engaging in moderate- and vigorousintensity activities in four domains: work, active transportation, domestic and garden, and leisure time. Participants were asked to recall their activities during the last 7 days. The IPAQ-C has been shown to have moderate to good test–retest reliability (intraclass correlation coefficient: 0.89) and good validity (partial r coefficient: 0.58).9 IPAQ-C data include categorical and continuous indicators of physical activity. Because of the non-normal distribution of energy expenditure in many populations, the IPAQ Research Committee has suggested that continuous indicators be presented as median
MET values (in min/week) and interquartile ranges (IQRs), rather than as means.10 One MET is equal to energy expenditure during rest, ∼3.5 ml O2 kg−1 min−1 in adults.11 MET
min/week = minutes of activity per day
× days per week × MET value
(1)
A MET value was assigned to each type of activity according to the IPAQ Research Committee, as follows: MET value for walking = 3.3 MET, moderate-intensity activity = 4.0 MET, vigorousintensity activity = 8.0 MET.10 For the estimation of energy expenditure, the IPAQ scoring guideline states that MET scores in min/week are equivalent to kilocalories for a 60-kg person. Thus, the data were converted to energy expenditure per week, adjusted for weight (kcal/week/kg).12 We computed MET minute scores for walking, moderate-intensity activity, vigorous-intensity activity, and total physical activity using the following equation: MET minute score = MET minutes ×
weight [in kilograms] 60 kg
(2)
We categorized total physical activity (MET min/week) scores into three levels: low activity/physical inactivity (<600 MET min/week), moderate activity (600–2999 MET min/ week), and high activity (≥3000 MET min/week).10 Moderate- and vigorous-intensity activities represent the type of physical activity. Moderate and high levels represent the total scores of the physical activity. To explore factors related to physical activity level, the following data were collected by using a self-administered questionnaire developed by the research team: sex (men/women), age (≤30, 31–40, 41–50, and ≥51 years), marital status (married/other), education level (years of formal education ≤12, 13–16, and ≥17 years), family income (monthly income per family member ≤1000, 1001–3000, and ≥3001 RMB), family history of chronic disease (hypertension, cancer, diabetes; yes/no), existing disease (hypertension, cancer, diabetes; yes/no), height (cm), and weight (kg). Height and weight were measured by the research team using standard methods and were used to compute the body mass index (BMI). According to the WHO classification,13 BMI was categorized as underweight (≤18.5 kg/m2 ), normal weight (18.6–24.9 kg/m2 ), or overweight (≥25.0 kg/m2 ). Five nurses, who had worked at the health examination centers for at least 5 years, collected the data. All of them had received training before the survey to ensure that they understood the purpose and requirements of the study. The nurses conducted faceto-face interviews and explained the study aims and requirements to participants before they completed the self-administered questionnaire. To ensure a higher response rate, these 10- to 15-min interviews were conducted before participants’ health examinations. One main investigator carefully checked survey responses and conducted telephone interviews to obtain complete information when necessary. EpiData 3.1 (version 3.1; EpiData Association, Odense, Denmark) was used to construct the study database. Data from questionnaires were entered into the database using the double entry mode to ensure accuracy, and a logic check for errors was performed. Qualitative data are reported as absolute numbers and percentages. The Mann–Whitney U-test or Kruskal–Wallis H-test and Nemenyi test were used to compare categorical variables describing physical activity level. Binary logistic regression was used to analyze factors (i.e., sex, age, BMI, education level, family income, and family history of chronic disease) related to high activity level (dependent variable). Odds ratios (ORs) with 95% confidence intervals
Please cite this article in press as: Sun L, et al. Physical activity level and associated factors among civil servants in Xi’an, China. J Sci Med Sport (2015), http://dx.doi.org/10.1016/j.jsams.2015.08.003
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(CIs) were calculated. A P value <0.05 was considered to indicate statistical significance. All analyses were performed by using the Statistical Package for the Social Sciences (version 17.0; SPSS Inc., Chicago, IL, USA). 3. Results A total of 924 civil servants (415 women, 509 men; 92.4% response rate) completed this study. Participants’ mean age was 41.5 ± 13.6 years (range: 18–60 years). The age distribution of the sample was as follows: 22.6% of participants were ≤30 years, 34.1% were 31–40 years, 23.1% were 41–50 years, and 23.1% were ≥51 years old. The mean BMI was 23.5 ± 3.0 kg/m2 . Most participants were married (88.1%) and had 13–16 years of education (80.8%). Most participants (75.3%) had a family history of chronic disease. In terms of existing disease, 10.1% of participants had hypertension, 1.3% had cancer, and 6.3% had diabetes. Table 1 shows the physical activity scores for the total sample and by sociodemographic and health characteristics. The total physical activity score in the work domain was higher than in other domains (P < 0.05). All domain scores were higher among men than women (P < 0.05), except for the domestic and garden activity scores that did not differ between men and women. Significant differences in all scores (except in the domestic and garden activity domain) were observed among the age groups (P < 0.05). The largest difference was between participants aged ≥51 years and those of other ages in the work, moderate-intensity, vigorous-intensity, and total score domains. Scores of participants ≥51 years old in those domains were the lowest among all participants (P < 0.05). Work, moderate-intensity, vigorous-intensity, and total physical activity scores differed by education level (P < 0.05), with higher physical activity scores being observed at higher education levels. There was no significant difference by marital status in any domain score. Scores in the work, walking, moderate-intensity, vigorous-intensity, and total domains of participants with a family income ≥3001 RMB were significantly higher than those with a family income of 1001–3000 RMB (P < 0.05). Transportation and total physical activity scores differed according to BMI (P < 0.05), with higher BMI being associated with higher physical activity scores. The work and vigorous-intensity activity scores were significantly lower among participants with compared to those without a family history of chronic disease (P < 0.05). Work scores were lower among participants with hypertension or diabetes than among those without these conditions (P < 0.05). Physical activity levels for the total sample are presented according to sociodemographic and health characteristics in Table 2. A moderate activity level was significantly more common among women, participants aged ≥51 years, and participants with a family history of chronic disease (P < 0.05). A low activity level was more common among underweight than among normalweight or overweight participants (P < 0.05). A high activity level was more common participants with ≥17 years of education and income ≤1000 RMB than among less-educated participants and those with higher incomes (P < 0.05). No significant difference in activity level was observed according to marital status or existing disease (hypertension, cancer, or diabetes). Factors related to a high physical activity level are presented in Table 3. Binary logistic regression showed that female sex (OR: 0.40, 95% CI: 0.29–0.55; P < 0.05), age ≥51 years (OR: 0.45, 95% CI: 0.27–0.75; P < 0.05), and a family history of chronic disease (OR: 0.67, 95% CI: 0.48–0.94; P < 0.05) were associated with significantly lower odds of having a high activity level. 4. Discussion Physical activity is an important contributor to preventing and controlling chronic disease. An understanding of physical activity
3
level and associated factors contributes to evidence-based planning of public health interventions. The present study demonstrated that sex, age, and family history of chronic disease are key factors related to physical activity level among civil servants in Xi’an. According to the WHO, about 6–8% of adults aged 25–64 years have a low level of physical activity, 8–11% have a moderate level of activity, and 80% to 85% have a high level of activity.14–16 By comparison, 7.4%, 57.3%, and 35.4% of subjects in our study had low, moderate, and high levels of activity, respectively. These findings may suggest that civil servants in Xi’an have a lower level of physical activity, on average, compared to the general population worldwide. However, differences in the prevalence of physical activity must be interpreted with caution. The IPAQ measures physical activity levels in a wide and holistic range of domains of daily life. Well-recognized deviations in physical activity behavior due to seasonal and climatic differences may be responsible for disparities in results among countries.17 Moreover, differences in physical activity estimates may be attributable to the different survey times used in various studies. Finally, our sample comprised a subset of the general population rather than the general population as a whole. Consistent with the results of a survey conducted in Malaysia,18 work-related activity was the most common form of physical activity in the present sample. Activity levels in the work, transportation, and leisure-time domains were higher among civil servants in Xi’an than among Malay adults12 (869 vs. 297, 356 vs. 155, and 429 vs. 155 MET min/week, respectively). However, the domestic and garden activity scores were significantly lower among our participants than among Malay adults (252 vs. 558 MET min/week).18 This result may reflect the growing popularity of technological products and reduction of living space. Evidence from the WHO suggests that participation in vigorousintensity physical activity is a key indicator of physical activity level, showing more reliability and validity than moderate-intensity activity.3 Furthermore, Lee suggested that vigorous-intensity activity has more benefits in terms of lowering the mortality rate compared to moderate-intensity activity.19 We observed a very low score for vigorous-intensity activity (0 MET min/week) among civil servants in Xi’an, which differed substantially from the value observed among Malay adults (240 MET min/week).12 Therefore, increased effort should be made to promote vigorous-intensity physical activity among civil servants in China. Similar to the previous finding that men spend more time than women engaged in physical activity,20 male civil servants were more physically active than their female counterparts in all but the domestic and garden domain in the present study. Chu and Moy18 reported higher energy expenditures among women than men in the domestic and garden domain, as women traditionally engage in household tasks. In contrast, we observed no sex-based difference in domestic and garden activity in the present study, perhaps because participation in such activity is distributed more equitably between urban men and women. Langsetmo21 reported strong evidence that physical activity is inversely associated with BMI. However, in the current study, physical activity was not associated with BMI. This result may be partly due to the cross-sectional study design and lack of access to participants’ baseline data, as well as potential confounding factors such as job strain, overtime work of civil servants. The age-related decline in physical activity observed in this study is consistent with the findings of previous studies conducted elsewhere, although different measures were used to estimate physical activity level.22 The observed reduction in all physical activity domain scores with increasing age may reflect reduced self-efficacy,23 poor health,24 and an increasingly sedentary lifestyle after retirement.22 Thornórarinsson25 suggested a positive relationship between physical activity and educational level. Similarly, we found significantly
Please cite this article in press as: Sun L, et al. Physical activity level and associated factors among civil servants in Xi’an, China. J Sci Med Sport (2015), http://dx.doi.org/10.1016/j.jsams.2015.08.003
Work
Transportation
Domestic and garden
Leisure time
Walking
Moderate-intensity
Vigorous-intensity
Total
869 (228–1953)
356 (43–607)
252 (114–488)
429 (185–914)
1155 (644–1733)
770 (304–1440)
0 (0–416)
2227 (1308–3802)
509 415
1140 (376–2393) 627 (128–1554)a
418 (136–716) 297 (0–462)a
237 (115–484) 285 (114–488)
528 (244–1179) 358 (132–684)a
1307 (813–2025) 972 (520–1422)a
880 (304–1690) 645 (312–1199)a
0 (0–664) 0 (0–160)a
2710 (1430–4615) 1926 (1068–2943)a
Age (years) ≤30 31–40 41–50 ≥51
209 315 213 187
1034 (416–2050) 990 (388–1965) 1095 (485–2284) 0 (0–1223)a,b,c
339 (13–615) 251 (0–539) 366 (34–689)b 429 (257–616)b,c
263 (130–472) 252 (80–477) 240 (133–590) 279 (144–474)
388 (73–730) 330 (78–880) 519 (222–1325)a,b 528 (316–814)a,b
1201 (690–1814) 1020 (411–1733) 1271 (762–1844)b 1109 (829–1536)
741 (247–1448) 819 (329–1440) 1027 (475–1074)a,b 454 (228–1013)a,b,c
0 (0–604) 0 (0–496) 0 (0–637) 0 (0–0)a,b,c
2314 (1375–3975) 2300 (1275–3916) 2619 (1627–4325) 1588 (1111–2761)a,b,c
Education (years) ≤12 13–16 ≥17
129 747 48
83 (0–1341) 924 (330–1973)a 1688 (847–2402)a,b
381 (134–602) 341 (39–594) 425 (0–817)
268 (142–589) 248 (113–470) 323 (123–536)
483 (246–845) 424 (172–889) 681 (216–1524)
1021 (639–1526) 1155 (635–1739) 1389 (814–2462)
540 (228–1218) 780 (324–1435)a 1159 (662–2301)a,b
0 (0–0) 0 (0–420)a 395 (0–1416)a,b
1706 (1107–3343) 2244 (1325–3839) 3215 (2084–6816)a,b
Marital status Married Other
814 110
851 (210–1944) 1030 (368–2018)
356 (36–590) 356 (91–696)
250 (117–475) 297 (73–608)
435 (185–909) 414 (173–996)
1144 (626–1725) 1212 (772–1969)
772 (321–1392) 722 (222–1663)
0 (0–382) 0 (0–645)
2220 (1286–3703) 2940 (2340–3360)
Family economic status (monthly per family member; RMB) ≤1000 1001–3000 ≥3001
35 380 509
627 (0–3138) 463 (0–1643) 1140 (494–2036)b
347 (0–825) 391 (193–644) 295 (0–554)b
407 (150–1040) 248 (96–514) 252 (120–467)
570 (0–1395) 118 (414–838) 445 (231–997)
990 (508–2129) 1022 (595–1650) 1254 (784–1755)b
910 (206–2183) 500 (223–1365) 900 (437–1439)b
0 (0–1184) 0 (0–186)a 0 (0–580)b
2794 (1435–6945) 1847 (1090–3600) 2482 (1501–3768)b
BMI (kg/m2 ) ≤18.5 18.6–24.9 ≥25.0
37 650 237
487 (153–1552) 844 (225–1863) 1044 (253–2393)
213 (13–457) 332 (38–593) 424 (91–720)a,b
270 (15–560) 248 (114–465) 270 (120–590)
388 (34–758) 423 (178–913) 445 (252–924)
911 (304–1380) 1099 (635–1709) 1205 (787–1937)a
472 (143–1625) 744 (319–1334) 887 (273–1755)
0 (0–165) 0 (0–480) 0 (0–320)
1450 (775–3317) 2200 (1283–3589) 2437 (1428–4466)a,b
696 228
772 (190–1881) 1168 (297–2234)a
353 (72–580) 369 (0–690)
248 (118–468) 291 (81–599)
436 (211–861) 419 (44–1099)
1129 (684–1682) 1172 (561–2045)
760 (309–1368) 833 (292–1717)
0 (0–312) 0 (0–713)a
2159 (1282–3483) 2582 (1349–4751)
Hypertension Yes No
93 831
358 (0–1790) 897 (295–1973)a
409 (19–767) 347 (47–585)
240 (0–540) 256 (120–480)
528 (263–1070) 424 (174–889)
1021 (647–1827) 1155 (644–1733)
540 (159–1522) 792 (329–1440)a
0 (0–186) 0 (0–420)
1706 (1057–4382) 2248 (1331–3710)
Cancer Yes No
12 912
618 (418–2761) 881 (223–1953)
400 (0–658) 356 (49–607)
334 (44–1350) 252 (114–488)
443 (21–2489) 429 (185–906)
816 (191–1984) 1155 (648–1733)
983 (408–2296) 766 (304–1434)
0 (0–1108) 0 (0–404)
2630 (1882–6262) 2222 (1296–3776)
Diabetes Yes No
58 866
238 (0–1391) 900 (277–1974)a
373 (206–554) 351 (35–611)
235 (65–540) 256 (117–488)
501 (263–882) 429 (178–915)
1047 (638–1427) 1155 (624–1756)
571 (222–1053) 795 (314–1449)
0 (0–145) 0 (0–433)
1888 (1054–3554) 2241 (1318–3813)
Family history of chronic disease Yes No Existing diseases
Data are presented as median values (interquartile ranges) of MET min/week. MET, metabolic equivalent of task; BMI, body mass index. P < 0.05 vs.a first, b second, and c third entries in each category.
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Total Sex Men Women
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Please cite this article in press as: Sun L, et al. Physical activity level and associated factors among civil servants in Xi’an, China. J Sci Med Sport (2015), http://dx.doi.org/10.1016/j.jsams.2015.08.003
Table 1 Physical activity scores of civil servants according to sociodemographic and health characteristics (MET min/week).
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Table 2 Physical activity levels according to sociodemographic and health characteristics. n (%)
Low (n = 68)
Moderate (n = 529)
High (n = 327)
Sex Men Women
509 (55.1) 415 (44.9)
25 (4.9) 43 (10.4)
258 (50.7) 271 (65.3)
226 (44.4) 101 (24.3)
Age (years) ≤30 31–40 41–50 ≥51
209 (22.6) 315 (34.1) 213 (23.1) 187 (20.2)
21 (10.0) 30 (9.5) 8 (3.8) 9 (4.8)
111 (53.1) 165 (52.4) 114 (53.5) 139 (74.3)
77 (36.8) 120 (38.1) 91 (42.7) 39 (20.9)
BMI (kg/m2 ) ≤18.5 18.6–24.9 ≥25.0
37 (4.0) 650 (70.3) 237 (25.6)
6 (16.2) 51 (7.8) 11 (4.6)
21 (56.8) 377 (58.0) 131 (55.3)
10 (27.0) 222 (34.2) 95 (40.1)
Education (years) ≤12 13–16 ≥17
129 (14.0) 747 (80.8) 48 (5.2)
8 (6.2) 59 (7.9) 1 (2.1)
86 (66.7) 421 (56.4) 22 (45.8)
35 (27.1) 267 (35.7) 25 (52.1)
Marital status Married Other
814 (88.1) 110 (11.9)
57 (7.0) 11 (11.0)
476 (58.5) 53 (48.2)
281 (34.5) 46 (41.8)
Family economic status (monthly per family member; RMB) ≤1000 1001–3000 ≥3001
35 (3.8) 380 (41.1) 509 (55.1)
2 (5.7) 36 (9.5) 30 (5.9)
16 (45.7) 227 (59.7) 286 (56.2)
17 (48.6) 117 (30.8) 193 (37.9)
Family history of chronic disease Yes No
696 (75.3) 228 (24.7)
44 (6.3) 24 (10.5)
425 (61.1) 104 (45.6)
227 (32.6) 100 (43.9)
Existing disease Hypertension Yes No
93 (10.1) 831 (89.9)
7 (7.5) 61 (7.3)
55 (59.1) 474 (57.0)
31 (33.3) 296 (35.6)
Cancer Yes No
12 (1.3) 912 (98.7)
0 (0.0) 68 (7.5)
7 (58.3) 522 (57.2)
5 (41.7) 322 (35.3)
Diabetes Yes No
58 (6.3) 866 (93.7)
4 (6.9) 64 (7.4)
39 (67.2) 490 (56.6)
15 (25.9) 312 (36.0)
924 (100)
68 (7.4)
529 (57.3)
327 (35.4)
Total
U value/H valuea
P
82,267.500
0.000
17.281
0.001
6.610
0.037
9.075
0.011
42,610.500
0.348
9.255
0.010
73,234.000
0.046
37,776.500
0.686
4886.000
0.466
22,829.000
0.185
Data are presented as n (%). a Obtained by the Mann–Whitney U-test and Kruskal–Wallis H-test.
higher total, work, moderate-intensity and, especially, vigorousintensity physical activity scores among participants with higher education levels. In binary logistic regression analysis, educational level was not associated with a high level of physical activity. These results are not contradictory because each education-level group had few high-level participants. The relationship between marital status and physical activity remains unclear, and is influenced by how couples support one another.26 We did not observe any relationship between marital status and physical activity, which suggests that marriage doesn’t work to promote physical activity among civil servants. A previous report suggested that lower family income is associated with a lower physical activity level and poorer health outcomes.27 We found no influence of family income on physical activity levels in binary logistic analysis. However, there was large variability of data for family income ≤1000 RMB, which confused the results and suggested that civil servants making ≤1000 RMB (monthly per family member) had a much more diversified lifestyle than other groups. Hordern28 suggested that exercise training, in combination with other lifestyle strategies, could help to prevent the onset of type 2 diabetes mellitus and improve glycemic control in those with prediabetes and cardiovascular risk profiles. However, in the present study, there was no significant difference between civil servants
who had or did not have existing diseases. Therefore, the individuals may not be aware of the benefits of increased physical activity. Furthermore, participants with family histories of chronic disease generally had lower physical activity levels, possibly reflecting the predominance of family numbers’ negative attitudes about physical activity. This finding is in accordance with a previous study demonstrating that adults with a family history of chronic disease are less inclined to engage in regular physical activity.29 In addition to the cross-sectional design and lack of access to participants’ baseline data, this study was limited by the use of selfreported data on physical activity. Self-reported data are subject to error and recall biases. These limitations may have led to an overor underestimation of the prevalence of physical activity. However, to our knowledge, no similar study has examined physical activity levels of civil servants in China. Our study involved a large number of subjects and is characterized by a high degree of external validity. Our results can serve as an important reference for efforts to improve the physical activity levels of civil servants in several ways. Awareness of the importance and benefits of physical activity can be raised among the whole population. At-risk population groups can be targeted for further education. Finally, supportive environments that facilitate physical activity by civil servants can be created, with rewards for physically active individuals to encourage this behavior. As our participants were all civil
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6 Table 3 Factors related to a high level of physical activity.
ˇ
Wald
P
OR
95% CI
Sex Men Women
– −0.912
– 32.153
– 0.000
1 0.402
– (0.293–0.550)
Age (years) ≤30 31–40 41–50 ≥51
– −0.030 0.189 −0.795
– 0.024 0.745 9.382
– 0.877 0.388 0.002
1 1.031 1.208 0.452
– (0.703–1.511) (0.787–1.855) (0.272–0.751)
BMI (kg/m2 ) ≤18.5 18.6–24.9 ≥25.0
– 0.195 0.252
– 0.240 0.431
– 0.624 0.343
1 1.216 1.287
– (0.556–2.657) (0.553–2.993)
Education (years) ≤12 13–16 ≥17
– 0.187 0.544
– 0.585 1.979
– 0.444 0.160
1 1.206 1.724
– (0.746–1.947) (0.807–3.681)
– −0.507 −0.498
– 1.730 1.638
– 0.188 0.201
1 0.602 0.607
– (0.283–1.282) (0.283–1.303)
– −0.404
– 5.475
– 0.019
1 0.668
– (0.476–0.937)
Family income (monthly per family member; RMB) ≤1000 1001–3000 ≥3001 Family history of chronic disease No Yes OR, odds ratio; CI, confidence interval; BMI, body mass index.
servants from Xi’an, our recommendations are focused on this group. 5. Conclusion We found that most civil servants in Xi’an, have moderate activity levels. Some have high activity levels, but very few engage in vigorous-intensity physical activity. Sex, age, and family history of chronic disease were key factors related to physical activity, with lower activity levels being more common among women, older participants, and those with family histories of chronic disease. Our results suggest that increased participation in high-level and vigorous-intensity physical activity should be encouraged, especially in these target groups. Practical implications • Most civil servants in Xi’an have moderate physical activity levels. • Sex, age, and family history of chronic disease are associated with physical activity. • Physical activity, especially high-level and vigorous physical activity, should be encouraged. Acknowledgements This study was supported by National Natural Science Foundation of China (No. 81273175). The research team is grateful to all of the study participants, as well as to Prof. Shoou-Yih D. Lee at the University of Michigan (USA) for editing the manuscript. References 1. World Health Organization (WHO). Global Recommendations on Physical Activity for Health, Geneva, Switzerland, WHO Press, 2010. Available online http://whqlibdoc.who.int/publications/2010/9789241599979 eng.pdf at: (accessed 20 November 2014). 2. World Health Organization (WHO). Global health risks: mortality and burden of disease attributable to selected major risks, World Health Organization (WHO), 2013. Avaliable at: http://www.who.int/ healthinfo/global burden disease/GlobalHealthRisks report full.pdf (accessed 8 December 2013).
3. Hallal PC, Andersen LB, Bull FC et al. Global physical activity levels: surveillance progress, pitfalls, and prospects. Lancet 2012; 380(9838):247–257. 4. Ng SW, Norton EC, Popkin BM. Why have physical activity levels declined among Chinese adults? Findings from the 1991–2006 China Health and Nutrition Surveys. Soc Sci Med 2009; 68(7):1305–1314. 5. Kohl HW, Craig CL, Lambert EV et al. The pandemic of physical inactivity: global action for public health. Lancet 2012; 380(9838):294–305. 6. Simkhada P, Poobalan A, Simkhada PP et al. Knowledge, attitude, and prevalence of overweight and obesity among civil servants in Nepal. Asia Pac J Public Health 2011; 23(4):507–517. 7. Lallukka T, Lahelma E, Rahkonen O et al. Associations of job strain and working overtime with adverse health behaviors and obesity: evidence from the Whitehall II Study, Helsinki Health Study, and the Japanese Civil Servants Study. Soc Sci Med 2008; 66(8):1681–1698. 8. Shi Z, Lien N, Kumar BN, Holmboe-Ottesen G. Physical activity and associated socio-demographic factors among school adolescents in Jiangsu Province, China. Prev Med 2006; 43(3):218–221. 9. Deng HB, Macfarlane DJ, Thomas GN et al. Reliability and validity of the IPAQChinese: the Guangzhou Biobank Cohort Study. Med Sci Sports Exerc 2008; 40(2):303–307. 10. Fan M, Lyu J, He P. Chinese guidelines for data processing and analysis concerning the International Physical Activity Questionnaire. Zhonghua Liuxingbingxue Zazhi 2014; 35(8):961–964. 11. Hagströmer M, Oja P, Sjöström M. The International Physical Activity Questionnaire (IPAQ): a study of concurrent and construct validity. Public Health Nutr 2006; 9(06):755–762. 12. Chu AH, Moy F. Association between physical activity and metabolic syndrome among Malay adults in a developing country, Malaysia. J Sports Sci Med 2014; 17(2):195–200. 13. World Health Organization (WHO). Obesity: preventing and managing the global epidemic. Report of a WHO consultation. World Health Organ Tech Rep Ser 2000; 894:i–xii. 14. World Health Organization (WHO). Tanzania STEPS survey 2012: fact sheet, World Health Organization (WHO), 2015. Available from: (accsesed http://www.who.int/chp/steps/UR Tanzania FactSheet 2012.pdf 15 May 2015). 15. World Health Organization (WHO). Benin STEPS Survey 2008, World Health Organization (WHO), 2015. Avaliable at: http://www.who.int/ chp/steps/2008 Benin FactSheet EN.pdf (accessed 15 May 2015). 16. World Health Organization (WHO). Mozambique STEPS Survey World Health Organization (WHO), 2015. Avaliable at: 2005, http://www.who.int/chp/steps/2005 Mozambique FactSheet EN.pdf (accessed 15 May 2015). 17. Guthold R, Ono T, Strong KL et al. Worldwide variability in physical inactivity—a 51-country survey. Am J Prev Med 2008; 34(6):486–494. 18. Chu AH, Moy FM. Associations of occupational, transportation, household and leisure-time physical activity patterns with metabolic risk factors among middle-aged adults in a middle-income country. Prev Med 2013; 57:S14–S17. 19. Lee IM, Paffenbarger RS. Associations of light, moderate, and vigorous intensity physical activity with longevity—the Harvard Alumni Health Study. Am J Epidemiol 2000; 151(3):293–299.
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20. World Health Organization (WHO). Physical activity and women, World Health Organization (WHO), 2013. Avaliable at: http://www.who.int/ dietphysicalactivity/factsheet women/en/ (accessed 15 May 2015). 21. Langsetmo L, Hitchcock CL, Kingwell EJ et al. Physical activity, body mass index and bone mineral density-associations in a prospective population-based cohort of women and men: The Canadian Multicentre Osteoporosis Study (CaMos). Bone 2012; 50(1):401–408. 22. Teh C, Lim K, Chan Y et al. The prevalence of physical activity and its associated factors among Malaysian adults: findings from the National Health and Morbidity Survey 2011. Public Health 2014; 128(5):416–423. 23. Netz Y, Raviv S. Age differences in motivational orientation toward physical activity: an application of social-cognitive theory. J Psychol 2004; 138(1):35–48. 24. Moschny A, Platen P, Klaassen-mielke R et al. Barriers to physical activity in older adults in germany: a cross-sectional study. Int J Behav Nutr Phys Act 2011; 11:559.
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25. Thornórarinsson ET, Harðarson T, Sigvaldason H et al. The relationship between educational level, physical activity and mortality. Laeknabladid 2002; 88(6):497–502. 26. Texas A&M University, Marital physical activity, 2015, Avaliable at: http://dlt.tamu.edu/Previous/MPA.html (accessed 20 May 2015). 27. Low Income Populations and Physical Activity, Retrieved from: http://www.bms.com/Documents/together on diabetes/2012-SummitAtlanta/Physical-Activity-for-Low-Income-Populations-The-HealthTrust.pdf. 28. Hordern MD, Dunstan DW, Prins JB et al. Exercise prescription for patients with type 2 diabetes and pre-diabetes: a position statement from Exercise and Sport Science Australia. J Sports Sci Med 2012; 15(1):25–31. 29. Shuval K, Chiu CY, Barlow CE et al. Family history of chronic disease and meeting Public Health Guidelines for physical activity: the Cooper Center Longitudinal Study. Mayo Clin Proc 2013; 88(6):588–592.
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Contents lists available at ScienceDirect
Journal of Science and Medicine in Sport journal homepage: www.elsevier.com/locate/jsams
Original research
Physical activity level and associated factors among civil servants in Xi’an, China Lijun Sun a,1 , Xun Jiang b,1 , Xin Zhao c , Yuhai Zhang a , Yongyong Xu a,∗ , Lei Shang a,∗ a b c
Department of Health Statistics, School of Public Health, Fourth Military Medical University, China Department of Paediatrics, Tangdu Hospital, Fourth Military Medical University, China Nautical and Aviation Medical Center, Navy General Hospital, China
a r t i c l e
i n f o
Article history: Received 23 January 2015 Received in revised form 15 July 2015 Accepted 25 August 2015 Available online xxx Keywords: Cross-sectional study Adult Exercise International physical activity questionnaire (Chinese version)
a b s t r a c t Objectives: This study investigated physical activity levels and associated factors among civil servants in Xi’an, China, to provide reference data for the implementation of health improvement strategies among civil servants. Design: A cross-section study. Methods: A random sample of 1000 civil servants aged 18–60 years and employed by the Xi’an civic government was assessed by using the Chinese version of the International Physical Activity Questionnaire. Associations between physical activity and sociodemographic characteristics, family history of chronic disease, and existing disease were evaluated by the Mann–Whitney U-test, Kruskal–Wallis H-test, and binary logistic regression. Results: The response rate was 92.4%. The median physical activity score was 2227 metabolic equivalents of task (MET) minutes per week (interquartile range [IQR]: 1308–3802 MET min/week). Among the 924 participants, 7.4% did not meet minimum recommendations for physical activity, 57.3% had moderate activity levels, and 35.4% had high activity levels. Participants spent most of their time on occupational activities (median: 869 MET min/week, IQR: 228–1953 MET min/week). Female sex (odds ratio [OR]:0.40, 95% confidence interval [CI]:0.29–0.55), age ≥ 51 years (OR: 0.45, 95%CI: 0.27–0.75), and family history of chronic disease (OR: 0.67, 95%CI: 0.48–0.94) were associated with significantly lower odds of a high activity level. Conclusions: Most civil servants in Xi’an, China, have moderate activity levels. Some have high activity levels, but few engage in vigorous-intensity physical activity. Interventions to encourage a high level of physical activity are needed, especially for women, older civil servants, and those with family histories of chronic disease. © 2015 Sports Medicine Australia. Published by Elsevier Ltd. All rights reserved.
1. Introduction As an important health-related behavior in daily life, physical activity has major health benefits related to reducing the risks of coronary heart disease, stroke, diabetes, hypertension, depression, etc. Physical activity is a key determinant of energy expenditure and, thus, is fundamental to energy balance and weight control.1 Nevertheless, despite these benefits, the World Health Organization (WHO) has consistently reported that one
∗ Corresponding authors. E-mail addresses: [email protected] (Y. Xu), [email protected] (L. Shang) 1 Lijun Sun and Xun Jiang have an equal contribution to this study, they are co-first author.
in three adults worldwide is not sufficiently active (e.g., activity levels <600 metabolic equivalents of task [MET] min/week). Each year, 3.2 million people die due to physical inactivity, which was the fourth leading risk factor for death worldwide in 2009.2 A recent study showed that 31% of adults worldwide are physically inactive, with proportions of physical inactivity ranging from 17% in Southeast Asia to 43% in the United States and eastern Mediterranean.3 Among Chinese adults, average weekly physical activity fell by 32% between 1991 and 2006.4 Increasing urbanization and rapid economic development in China have been linked to reductions in occupational and overall physical activity.5 Some population groups, such as civil servants, tend to be less physically active and more vulnerable to chronic diseases than the general population. Obesity was found to be more prevalent among Nepalese civil servants than in the general population.6
http://dx.doi.org/10.1016/j.jsams.2015.08.003 1440-2440/© 2015 Sports Medicine Australia. Published by Elsevier Ltd. All rights reserved.
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2
The Whitehall II, Helsinki Health, and Japanese Civil Servants studies all suggested that the work-related stress, long working hours, and limited time for physical activity of civil servants were associated with chronic disease and increased mortality rates among civil servants in London, Finland, and Japan, respectively.7 For these reasons, assessments of the physical activity of civil servants should be an essential component of any intervention aimed at supporting the struggle against physical inactivity . Any understanding of the factors associated with the level of physical activity is necessary for designing and implementing interventions to increase physical activity for at-risk civil servants. Numerous studies of physical activity-related factors have been conducted on school adolescents.8 However, few such studies have focused on civil servants and, to the best of our knowledge, no study has quantitatively described physical activity levels among civil servants in China. Therefore, the aim of this study was to identify the physical activity level (with consideration of activity intensity) and associated factors among civil servants in Xi’an, China, with the end goal of providing reference data for the development and implementation of health improvement strategies in this group of workers.
2. Methods This cross-sectional survey included civil servants employed in the Xi’an civic government who underwent annual health examinations at Xijing and Tangdu Hospitals in Xi’an, between July and September 2012. A total of 1000 participants, who were randomly selected by a computer program and identified by birth date, name, and address from the data register of the health examination centers of the two hospitals, were invited to participate in the study. The Human Subject Review Committee of Fourth Military Medical University approved this study. All participants provided written informed consent before taking part in the survey. Xijing and Tangdu Hospitals are two of the largest AAA hospitals in Xi’an. The AAA distinction is awarded to the best hospitals in China. Hospitals with this distinction have the capacity to provide high-level medical services and education and to undertake major scientific research projects. The two hospitals treat a comprehensive spectrum of diseases and cover the whole population of Xi’an. Their health examination centers are designated institutions for annual health examinations for all civil servants in the Xi’an civic government. Eligible participants were 18–60 years and able to read and write well enough to fill out the physical activity questionnaire. Civil servants with serious diseases or disabilities that limited daily physical activity were excluded from the study. Physical activity was assessed by the self-administered longform Chinese version of the International Physical Activity Questionnaire (IPAQ-C).9 The long-form IPAQ-C was designed primarily for population surveillance of physical activity among adults (aged 15–69 years). It comprises 31 questions about the frequency of and time spent walking and engaging in moderate- and vigorousintensity activities in four domains: work, active transportation, domestic and garden, and leisure time. Participants were asked to recall their activities during the last 7 days. The IPAQ-C has been shown to have moderate to good test–retest reliability (intraclass correlation coefficient: 0.89) and good validity (partial r coefficient: 0.58).9 IPAQ-C data include categorical and continuous indicators of physical activity. Because of the non-normal distribution of energy expenditure in many populations, the IPAQ Research Committee has suggested that continuous indicators be presented as median
MET values (in min/week) and interquartile ranges (IQRs), rather than as means.10 One MET is equal to energy expenditure during rest, ∼3.5 ml O2 kg−1 min−1 in adults.11 MET
min/week = minutes of activity per day
× days per week × MET value
(1)
A MET value was assigned to each type of activity according to the IPAQ Research Committee, as follows: MET value for walking = 3.3 MET, moderate-intensity activity = 4.0 MET, vigorousintensity activity = 8.0 MET.10 For the estimation of energy expenditure, the IPAQ scoring guideline states that MET scores in min/week are equivalent to kilocalories for a 60-kg person. Thus, the data were converted to energy expenditure per week, adjusted for weight (kcal/week/kg).12 We computed MET minute scores for walking, moderate-intensity activity, vigorous-intensity activity, and total physical activity using the following equation: MET minute score = MET minutes ×
weight [in kilograms] 60 kg
(2)
We categorized total physical activity (MET min/week) scores into three levels: low activity/physical inactivity (<600 MET min/week), moderate activity (600–2999 MET min/ week), and high activity (≥3000 MET min/week).10 Moderate- and vigorous-intensity activities represent the type of physical activity. Moderate and high levels represent the total scores of the physical activity. To explore factors related to physical activity level, the following data were collected by using a self-administered questionnaire developed by the research team: sex (men/women), age (≤30, 31–40, 41–50, and ≥51 years), marital status (married/other), education level (years of formal education ≤12, 13–16, and ≥17 years), family income (monthly income per family member ≤1000, 1001–3000, and ≥3001 RMB), family history of chronic disease (hypertension, cancer, diabetes; yes/no), existing disease (hypertension, cancer, diabetes; yes/no), height (cm), and weight (kg). Height and weight were measured by the research team using standard methods and were used to compute the body mass index (BMI). According to the WHO classification,13 BMI was categorized as underweight (≤18.5 kg/m2 ), normal weight (18.6–24.9 kg/m2 ), or overweight (≥25.0 kg/m2 ). Five nurses, who had worked at the health examination centers for at least 5 years, collected the data. All of them had received training before the survey to ensure that they understood the purpose and requirements of the study. The nurses conducted faceto-face interviews and explained the study aims and requirements to participants before they completed the self-administered questionnaire. To ensure a higher response rate, these 10- to 15-min interviews were conducted before participants’ health examinations. One main investigator carefully checked survey responses and conducted telephone interviews to obtain complete information when necessary. EpiData 3.1 (version 3.1; EpiData Association, Odense, Denmark) was used to construct the study database. Data from questionnaires were entered into the database using the double entry mode to ensure accuracy, and a logic check for errors was performed. Qualitative data are reported as absolute numbers and percentages. The Mann–Whitney U-test or Kruskal–Wallis H-test and Nemenyi test were used to compare categorical variables describing physical activity level. Binary logistic regression was used to analyze factors (i.e., sex, age, BMI, education level, family income, and family history of chronic disease) related to high activity level (dependent variable). Odds ratios (ORs) with 95% confidence intervals
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(CIs) were calculated. A P value <0.05 was considered to indicate statistical significance. All analyses were performed by using the Statistical Package for the Social Sciences (version 17.0; SPSS Inc., Chicago, IL, USA). 3. Results A total of 924 civil servants (415 women, 509 men; 92.4% response rate) completed this study. Participants’ mean age was 41.5 ± 13.6 years (range: 18–60 years). The age distribution of the sample was as follows: 22.6% of participants were ≤30 years, 34.1% were 31–40 years, 23.1% were 41–50 years, and 23.1% were ≥51 years old. The mean BMI was 23.5 ± 3.0 kg/m2 . Most participants were married (88.1%) and had 13–16 years of education (80.8%). Most participants (75.3%) had a family history of chronic disease. In terms of existing disease, 10.1% of participants had hypertension, 1.3% had cancer, and 6.3% had diabetes. Table 1 shows the physical activity scores for the total sample and by sociodemographic and health characteristics. The total physical activity score in the work domain was higher than in other domains (P < 0.05). All domain scores were higher among men than women (P < 0.05), except for the domestic and garden activity scores that did not differ between men and women. Significant differences in all scores (except in the domestic and garden activity domain) were observed among the age groups (P < 0.05). The largest difference was between participants aged ≥51 years and those of other ages in the work, moderate-intensity, vigorous-intensity, and total score domains. Scores of participants ≥51 years old in those domains were the lowest among all participants (P < 0.05). Work, moderate-intensity, vigorous-intensity, and total physical activity scores differed by education level (P < 0.05), with higher physical activity scores being observed at higher education levels. There was no significant difference by marital status in any domain score. Scores in the work, walking, moderate-intensity, vigorous-intensity, and total domains of participants with a family income ≥3001 RMB were significantly higher than those with a family income of 1001–3000 RMB (P < 0.05). Transportation and total physical activity scores differed according to BMI (P < 0.05), with higher BMI being associated with higher physical activity scores. The work and vigorous-intensity activity scores were significantly lower among participants with compared to those without a family history of chronic disease (P < 0.05). Work scores were lower among participants with hypertension or diabetes than among those without these conditions (P < 0.05). Physical activity levels for the total sample are presented according to sociodemographic and health characteristics in Table 2. A moderate activity level was significantly more common among women, participants aged ≥51 years, and participants with a family history of chronic disease (P < 0.05). A low activity level was more common among underweight than among normalweight or overweight participants (P < 0.05). A high activity level was more common participants with ≥17 years of education and income ≤1000 RMB than among less-educated participants and those with higher incomes (P < 0.05). No significant difference in activity level was observed according to marital status or existing disease (hypertension, cancer, or diabetes). Factors related to a high physical activity level are presented in Table 3. Binary logistic regression showed that female sex (OR: 0.40, 95% CI: 0.29–0.55; P < 0.05), age ≥51 years (OR: 0.45, 95% CI: 0.27–0.75; P < 0.05), and a family history of chronic disease (OR: 0.67, 95% CI: 0.48–0.94; P < 0.05) were associated with significantly lower odds of having a high activity level. 4. Discussion Physical activity is an important contributor to preventing and controlling chronic disease. An understanding of physical activity
3
level and associated factors contributes to evidence-based planning of public health interventions. The present study demonstrated that sex, age, and family history of chronic disease are key factors related to physical activity level among civil servants in Xi’an. According to the WHO, about 6–8% of adults aged 25–64 years have a low level of physical activity, 8–11% have a moderate level of activity, and 80% to 85% have a high level of activity.14–16 By comparison, 7.4%, 57.3%, and 35.4% of subjects in our study had low, moderate, and high levels of activity, respectively. These findings may suggest that civil servants in Xi’an have a lower level of physical activity, on average, compared to the general population worldwide. However, differences in the prevalence of physical activity must be interpreted with caution. The IPAQ measures physical activity levels in a wide and holistic range of domains of daily life. Well-recognized deviations in physical activity behavior due to seasonal and climatic differences may be responsible for disparities in results among countries.17 Moreover, differences in physical activity estimates may be attributable to the different survey times used in various studies. Finally, our sample comprised a subset of the general population rather than the general population as a whole. Consistent with the results of a survey conducted in Malaysia,18 work-related activity was the most common form of physical activity in the present sample. Activity levels in the work, transportation, and leisure-time domains were higher among civil servants in Xi’an than among Malay adults12 (869 vs. 297, 356 vs. 155, and 429 vs. 155 MET min/week, respectively). However, the domestic and garden activity scores were significantly lower among our participants than among Malay adults (252 vs. 558 MET min/week).18 This result may reflect the growing popularity of technological products and reduction of living space. Evidence from the WHO suggests that participation in vigorousintensity physical activity is a key indicator of physical activity level, showing more reliability and validity than moderate-intensity activity.3 Furthermore, Lee suggested that vigorous-intensity activity has more benefits in terms of lowering the mortality rate compared to moderate-intensity activity.19 We observed a very low score for vigorous-intensity activity (0 MET min/week) among civil servants in Xi’an, which differed substantially from the value observed among Malay adults (240 MET min/week).12 Therefore, increased effort should be made to promote vigorous-intensity physical activity among civil servants in China. Similar to the previous finding that men spend more time than women engaged in physical activity,20 male civil servants were more physically active than their female counterparts in all but the domestic and garden domain in the present study. Chu and Moy18 reported higher energy expenditures among women than men in the domestic and garden domain, as women traditionally engage in household tasks. In contrast, we observed no sex-based difference in domestic and garden activity in the present study, perhaps because participation in such activity is distributed more equitably between urban men and women. Langsetmo21 reported strong evidence that physical activity is inversely associated with BMI. However, in the current study, physical activity was not associated with BMI. This result may be partly due to the cross-sectional study design and lack of access to participants’ baseline data, as well as potential confounding factors such as job strain, overtime work of civil servants. The age-related decline in physical activity observed in this study is consistent with the findings of previous studies conducted elsewhere, although different measures were used to estimate physical activity level.22 The observed reduction in all physical activity domain scores with increasing age may reflect reduced self-efficacy,23 poor health,24 and an increasingly sedentary lifestyle after retirement.22 Thornórarinsson25 suggested a positive relationship between physical activity and educational level. Similarly, we found significantly
Please cite this article in press as: Sun L, et al. Physical activity level and associated factors among civil servants in Xi’an, China. J Sci Med Sport (2015), http://dx.doi.org/10.1016/j.jsams.2015.08.003
Work
Transportation
Domestic and garden
Leisure time
Walking
Moderate-intensity
Vigorous-intensity
Total
869 (228–1953)
356 (43–607)
252 (114–488)
429 (185–914)
1155 (644–1733)
770 (304–1440)
0 (0–416)
2227 (1308–3802)
509 415
1140 (376–2393) 627 (128–1554)a
418 (136–716) 297 (0–462)a
237 (115–484) 285 (114–488)
528 (244–1179) 358 (132–684)a
1307 (813–2025) 972 (520–1422)a
880 (304–1690) 645 (312–1199)a
0 (0–664) 0 (0–160)a
2710 (1430–4615) 1926 (1068–2943)a
Age (years) ≤30 31–40 41–50 ≥51
209 315 213 187
1034 (416–2050) 990 (388–1965) 1095 (485–2284) 0 (0–1223)a,b,c
339 (13–615) 251 (0–539) 366 (34–689)b 429 (257–616)b,c
263 (130–472) 252 (80–477) 240 (133–590) 279 (144–474)
388 (73–730) 330 (78–880) 519 (222–1325)a,b 528 (316–814)a,b
1201 (690–1814) 1020 (411–1733) 1271 (762–1844)b 1109 (829–1536)
741 (247–1448) 819 (329–1440) 1027 (475–1074)a,b 454 (228–1013)a,b,c
0 (0–604) 0 (0–496) 0 (0–637) 0 (0–0)a,b,c
2314 (1375–3975) 2300 (1275–3916) 2619 (1627–4325) 1588 (1111–2761)a,b,c
Education (years) ≤12 13–16 ≥17
129 747 48
83 (0–1341) 924 (330–1973)a 1688 (847–2402)a,b
381 (134–602) 341 (39–594) 425 (0–817)
268 (142–589) 248 (113–470) 323 (123–536)
483 (246–845) 424 (172–889) 681 (216–1524)
1021 (639–1526) 1155 (635–1739) 1389 (814–2462)
540 (228–1218) 780 (324–1435)a 1159 (662–2301)a,b
0 (0–0) 0 (0–420)a 395 (0–1416)a,b
1706 (1107–3343) 2244 (1325–3839) 3215 (2084–6816)a,b
Marital status Married Other
814 110
851 (210–1944) 1030 (368–2018)
356 (36–590) 356 (91–696)
250 (117–475) 297 (73–608)
435 (185–909) 414 (173–996)
1144 (626–1725) 1212 (772–1969)
772 (321–1392) 722 (222–1663)
0 (0–382) 0 (0–645)
2220 (1286–3703) 2940 (2340–3360)
Family economic status (monthly per family member; RMB) ≤1000 1001–3000 ≥3001
35 380 509
627 (0–3138) 463 (0–1643) 1140 (494–2036)b
347 (0–825) 391 (193–644) 295 (0–554)b
407 (150–1040) 248 (96–514) 252 (120–467)
570 (0–1395) 118 (414–838) 445 (231–997)
990 (508–2129) 1022 (595–1650) 1254 (784–1755)b
910 (206–2183) 500 (223–1365) 900 (437–1439)b
0 (0–1184) 0 (0–186)a 0 (0–580)b
2794 (1435–6945) 1847 (1090–3600) 2482 (1501–3768)b
BMI (kg/m2 ) ≤18.5 18.6–24.9 ≥25.0
37 650 237
487 (153–1552) 844 (225–1863) 1044 (253–2393)
213 (13–457) 332 (38–593) 424 (91–720)a,b
270 (15–560) 248 (114–465) 270 (120–590)
388 (34–758) 423 (178–913) 445 (252–924)
911 (304–1380) 1099 (635–1709) 1205 (787–1937)a
472 (143–1625) 744 (319–1334) 887 (273–1755)
0 (0–165) 0 (0–480) 0 (0–320)
1450 (775–3317) 2200 (1283–3589) 2437 (1428–4466)a,b
696 228
772 (190–1881) 1168 (297–2234)a
353 (72–580) 369 (0–690)
248 (118–468) 291 (81–599)
436 (211–861) 419 (44–1099)
1129 (684–1682) 1172 (561–2045)
760 (309–1368) 833 (292–1717)
0 (0–312) 0 (0–713)a
2159 (1282–3483) 2582 (1349–4751)
Hypertension Yes No
93 831
358 (0–1790) 897 (295–1973)a
409 (19–767) 347 (47–585)
240 (0–540) 256 (120–480)
528 (263–1070) 424 (174–889)
1021 (647–1827) 1155 (644–1733)
540 (159–1522) 792 (329–1440)a
0 (0–186) 0 (0–420)
1706 (1057–4382) 2248 (1331–3710)
Cancer Yes No
12 912
618 (418–2761) 881 (223–1953)
400 (0–658) 356 (49–607)
334 (44–1350) 252 (114–488)
443 (21–2489) 429 (185–906)
816 (191–1984) 1155 (648–1733)
983 (408–2296) 766 (304–1434)
0 (0–1108) 0 (0–404)
2630 (1882–6262) 2222 (1296–3776)
Diabetes Yes No
58 866
238 (0–1391) 900 (277–1974)a
373 (206–554) 351 (35–611)
235 (65–540) 256 (117–488)
501 (263–882) 429 (178–915)
1047 (638–1427) 1155 (624–1756)
571 (222–1053) 795 (314–1449)
0 (0–145) 0 (0–433)
1888 (1054–3554) 2241 (1318–3813)
Family history of chronic disease Yes No Existing diseases
Data are presented as median values (interquartile ranges) of MET min/week. MET, metabolic equivalent of task; BMI, body mass index. P < 0.05 vs.a first, b second, and c third entries in each category.
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Table 1 Physical activity scores of civil servants according to sociodemographic and health characteristics (MET min/week).
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Table 2 Physical activity levels according to sociodemographic and health characteristics. n (%)
Low (n = 68)
Moderate (n = 529)
High (n = 327)
Sex Men Women
509 (55.1) 415 (44.9)
25 (4.9) 43 (10.4)
258 (50.7) 271 (65.3)
226 (44.4) 101 (24.3)
Age (years) ≤30 31–40 41–50 ≥51
209 (22.6) 315 (34.1) 213 (23.1) 187 (20.2)
21 (10.0) 30 (9.5) 8 (3.8) 9 (4.8)
111 (53.1) 165 (52.4) 114 (53.5) 139 (74.3)
77 (36.8) 120 (38.1) 91 (42.7) 39 (20.9)
BMI (kg/m2 ) ≤18.5 18.6–24.9 ≥25.0
37 (4.0) 650 (70.3) 237 (25.6)
6 (16.2) 51 (7.8) 11 (4.6)
21 (56.8) 377 (58.0) 131 (55.3)
10 (27.0) 222 (34.2) 95 (40.1)
Education (years) ≤12 13–16 ≥17
129 (14.0) 747 (80.8) 48 (5.2)
8 (6.2) 59 (7.9) 1 (2.1)
86 (66.7) 421 (56.4) 22 (45.8)
35 (27.1) 267 (35.7) 25 (52.1)
Marital status Married Other
814 (88.1) 110 (11.9)
57 (7.0) 11 (11.0)
476 (58.5) 53 (48.2)
281 (34.5) 46 (41.8)
Family economic status (monthly per family member; RMB) ≤1000 1001–3000 ≥3001
35 (3.8) 380 (41.1) 509 (55.1)
2 (5.7) 36 (9.5) 30 (5.9)
16 (45.7) 227 (59.7) 286 (56.2)
17 (48.6) 117 (30.8) 193 (37.9)
Family history of chronic disease Yes No
696 (75.3) 228 (24.7)
44 (6.3) 24 (10.5)
425 (61.1) 104 (45.6)
227 (32.6) 100 (43.9)
Existing disease Hypertension Yes No
93 (10.1) 831 (89.9)
7 (7.5) 61 (7.3)
55 (59.1) 474 (57.0)
31 (33.3) 296 (35.6)
Cancer Yes No
12 (1.3) 912 (98.7)
0 (0.0) 68 (7.5)
7 (58.3) 522 (57.2)
5 (41.7) 322 (35.3)
Diabetes Yes No
58 (6.3) 866 (93.7)
4 (6.9) 64 (7.4)
39 (67.2) 490 (56.6)
15 (25.9) 312 (36.0)
924 (100)
68 (7.4)
529 (57.3)
327 (35.4)
Total
U value/H valuea
P
82,267.500
0.000
17.281
0.001
6.610
0.037
9.075
0.011
42,610.500
0.348
9.255
0.010
73,234.000
0.046
37,776.500
0.686
4886.000
0.466
22,829.000
0.185
Data are presented as n (%). a Obtained by the Mann–Whitney U-test and Kruskal–Wallis H-test.
higher total, work, moderate-intensity and, especially, vigorousintensity physical activity scores among participants with higher education levels. In binary logistic regression analysis, educational level was not associated with a high level of physical activity. These results are not contradictory because each education-level group had few high-level participants. The relationship between marital status and physical activity remains unclear, and is influenced by how couples support one another.26 We did not observe any relationship between marital status and physical activity, which suggests that marriage doesn’t work to promote physical activity among civil servants. A previous report suggested that lower family income is associated with a lower physical activity level and poorer health outcomes.27 We found no influence of family income on physical activity levels in binary logistic analysis. However, there was large variability of data for family income ≤1000 RMB, which confused the results and suggested that civil servants making ≤1000 RMB (monthly per family member) had a much more diversified lifestyle than other groups. Hordern28 suggested that exercise training, in combination with other lifestyle strategies, could help to prevent the onset of type 2 diabetes mellitus and improve glycemic control in those with prediabetes and cardiovascular risk profiles. However, in the present study, there was no significant difference between civil servants
who had or did not have existing diseases. Therefore, the individuals may not be aware of the benefits of increased physical activity. Furthermore, participants with family histories of chronic disease generally had lower physical activity levels, possibly reflecting the predominance of family numbers’ negative attitudes about physical activity. This finding is in accordance with a previous study demonstrating that adults with a family history of chronic disease are less inclined to engage in regular physical activity.29 In addition to the cross-sectional design and lack of access to participants’ baseline data, this study was limited by the use of selfreported data on physical activity. Self-reported data are subject to error and recall biases. These limitations may have led to an overor underestimation of the prevalence of physical activity. However, to our knowledge, no similar study has examined physical activity levels of civil servants in China. Our study involved a large number of subjects and is characterized by a high degree of external validity. Our results can serve as an important reference for efforts to improve the physical activity levels of civil servants in several ways. Awareness of the importance and benefits of physical activity can be raised among the whole population. At-risk population groups can be targeted for further education. Finally, supportive environments that facilitate physical activity by civil servants can be created, with rewards for physically active individuals to encourage this behavior. As our participants were all civil
Please cite this article in press as: Sun L, et al. Physical activity level and associated factors among civil servants in Xi’an, China. J Sci Med Sport (2015), http://dx.doi.org/10.1016/j.jsams.2015.08.003
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6 Table 3 Factors related to a high level of physical activity.
ˇ
Wald
P
OR
95% CI
Sex Men Women
– −0.912
– 32.153
– 0.000
1 0.402
– (0.293–0.550)
Age (years) ≤30 31–40 41–50 ≥51
– −0.030 0.189 −0.795
– 0.024 0.745 9.382
– 0.877 0.388 0.002
1 1.031 1.208 0.452
– (0.703–1.511) (0.787–1.855) (0.272–0.751)
BMI (kg/m2 ) ≤18.5 18.6–24.9 ≥25.0
– 0.195 0.252
– 0.240 0.431
– 0.624 0.343
1 1.216 1.287
– (0.556–2.657) (0.553–2.993)
Education (years) ≤12 13–16 ≥17
– 0.187 0.544
– 0.585 1.979
– 0.444 0.160
1 1.206 1.724
– (0.746–1.947) (0.807–3.681)
– −0.507 −0.498
– 1.730 1.638
– 0.188 0.201
1 0.602 0.607
– (0.283–1.282) (0.283–1.303)
– −0.404
– 5.475
– 0.019
1 0.668
– (0.476–0.937)
Family income (monthly per family member; RMB) ≤1000 1001–3000 ≥3001 Family history of chronic disease No Yes OR, odds ratio; CI, confidence interval; BMI, body mass index.
servants from Xi’an, our recommendations are focused on this group. 5. Conclusion We found that most civil servants in Xi’an, have moderate activity levels. Some have high activity levels, but very few engage in vigorous-intensity physical activity. Sex, age, and family history of chronic disease were key factors related to physical activity, with lower activity levels being more common among women, older participants, and those with family histories of chronic disease. Our results suggest that increased participation in high-level and vigorous-intensity physical activity should be encouraged, especially in these target groups. Practical implications • Most civil servants in Xi’an have moderate physical activity levels. • Sex, age, and family history of chronic disease are associated with physical activity. • Physical activity, especially high-level and vigorous physical activity, should be encouraged. Acknowledgements This study was supported by National Natural Science Foundation of China (No. 81273175). The research team is grateful to all of the study participants, as well as to Prof. Shoou-Yih D. Lee at the University of Michigan (USA) for editing the manuscript. References 1. World Health Organization (WHO). Global Recommendations on Physical Activity for Health, Geneva, Switzerland, WHO Press, 2010. Available online http://whqlibdoc.who.int/publications/2010/9789241599979 eng.pdf at: (accessed 20 November 2014). 2. World Health Organization (WHO). Global health risks: mortality and burden of disease attributable to selected major risks, World Health Organization (WHO), 2013. Avaliable at: http://www.who.int/ healthinfo/global burden disease/GlobalHealthRisks report full.pdf (accessed 8 December 2013).
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