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Combined effect of physical activity and sedentary behavior on body composition in university students
Clinical Nutrition xxx (xxxx) xxx
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Clinical Nutrition journal homepage: http://www.elsevier.com/locate/clnu
Original article
Combined effect of physical activity and sedentary behavior on body composition in university students Mireille Harmouche-Karaki*, Maya Mahfouz, Yara Mahfouz, Nicole Fakhoury-Sayegh, Khalil Helou Department of Nutrition, Faculty of Pharmacy, Saint Joseph University of Beirut, Lebanon B.P. 11-5076, Riad el Solh Beyrouth, 1107 2180, Lebanon
a r t i c l e i n f o
s u m m a r y
Article history: Received 23 October 2018 Accepted 17 June 2019
Background & aims: This study aimed to evaluate the domain-specific physical activity (PA) levels and sitting time of a sample of university students and examine the association of PA with percent body fat. Methods: Two hundred and twenty-one students were included in the analysis. We administered the long form of the International Physical Activity Questionnaire (IPAQ) twice within one-month interval. Total PA as well as occupational, transportation-, housework-, and leisure-related PA were assessed, in addition to sitting time. Dietary intake was derived from six non-consecutive 24-hour dietary recalls. Percent body fat (dependent variable) was analyzed using a bioelectrical impedance analyzer (BIA). Multivariate logistic regression, adjusted for potential confounders, examined the associations of domain-specific PA and sitting time with percent body fat. Results: Men had higher levels of total and leisure PA than women. All participants had prolonged sitting time, with 48% having a sitting time of more than 10.15 hours/day. In multivariate analysis, moderate leisure PA, compared to vigorous PA was associated with a lower percent body fat. This association remained statistically significant even after adjustment for energy intake and sitting time. Houseworkrelated PA was associated with a higher percent body fat. Conclusion: Moderate leisure PA was highly associated with percent body fat even after adjustment for confounding variables. Adequate interventions targeting this kind of leisure should be promoted among universities students. © 2019 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
Keywords: Physical activity Sitting time Percent body fat University students
1. Introduction Recently, the prevalence of non-communicable diseases has globally increased. It is anticipated that they will be the main cause of death by 2020 [1]. In particular, obesity is aggravating, and worldwide levels have tripled since 1975 [2]. According to a report published in 2013 by the National Research Council and the Institute of Medicine, chronic diseases are expanding to reach the young generations, in addition to adults [3]. Among Lebanese university
Abbreviations: BIA, bioelectrical impedance analyzer; BMI, body mass index; IPAQ, International Physical Activity Questionnaire; M, men; MET, metabolic equivalent; OR, odds ratio; PA, physical activity; W, women. * Corresponding author. E-mail addresses: [email protected] (M. Harmouche-Karaki), [email protected] (M. Mahfouz), [email protected] (Y. Mahfouz), [email protected] (N. Fakhoury-Sayegh), [email protected]. lb (K. Helou).
students, levels of overweightness and obesity varied between 15.5e27.6% and 4.1e4.6%, respectively [4,5]. An important contributor to obesity is the replacement of the traditional diet with a westernized pattern, particularly among university students [6e8]; the consumption of energy-dense foods high in fat and sugar has increased at the expense of the intake of fish, fruits, and vegetables [5,9,10]. Another leading cause is sedentary behavior; it is defined as a waking activity that has an energy expenditure of 1.5 metabolic equivalents while sitting or reclining such as screen viewing, reading, and riding in an automobile [11]. Prolonged sitting is associated with increased obesity and other adverse health outcomes, independently of physical activity (PA) levels [12,13]. Even though data on sedentary behaviors among university students are scarce, long sitting hours have been reported worldwide and in Arabic countries [13e16] due to the rapid global evolution and the intense spread of technology [1]. The current obesity pandemic is also associated with reduced PA. There is compelling evidence on the inverse association between total PA
https://doi.org/10.1016/j.clnu.2019.06.015 0261-5614/© 2019 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
Please cite this article as: Harmouche-Karaki M et al., Combined effect of physical activity and sedentary behavior on body composition in university students, Clinical Nutrition, https://doi.org/10.1016/j.clnu.2019.06.015
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M. Harmouche-Karaki et al. / Clinical Nutrition xxx (xxxx) xxx
and percent body fat [17,18]. Despite the public health efforts to improve PA levels, many studies have shown considerable levels of physical inactivity among university students. In a study from 23 countries, the prevalence of physical inactivity was 41.4% ranging from 21.9% to 80.6% [19]. In Lebanon, reported levels of PA among university students were 72.5% in 2010 [20] and 60% in 2014 [21]. Therefore, targeting university students for PA interventions is vital since PA is associated with an enhanced health-related quality of life among university students [22]. In addition, PA patterns established in college are maintained throughout adulthood (carryover effect) [23]. Studies to date have focused predominantly on leisure-related PA, despite the large contribution of domainspecific activities (occupational, transportation, domestic, leisure) to total PA level [24]. Previous findings showed that leisure-time PA was associated with a lower risk of percent body fat, independent of sitting time [17]. However, occupational and housework-related PA showed inconsistent results [17,25]. In Lebanon, although there is evidence on the prevalence of PA, data are lacking on the specific domains of PA and sitting time and their association with anthropometric variables, specifically percent body fat. Therefore, our aim in this study was to evaluate the effect of domain-specific PA and sitting time on percent body fat in a Lebanese sample of students at Saint Joseph University of Beirut Saint Joseph - USJ). (Universite 2. Materials and methods
using the Nutrilog software (Nutrilog SAS, Version 2.30, France). Macronutrients recommended cut-off were used based on the WHO/FAO joint report [28]. 2.4. Anthropometric measurements For each participant, the height was measured using a stadiometer (Health o meter, Sunbeam Products Inc., IL, USA) and was recorded to the nearest 0.1 centimeters (cm). Two measurements were taken and the average differing by 0.5 cm was indicated. Body weight was measured using a mechanical scale (Health o meter, Sunbeam Products Inc., IL, USA) and was recorded to the nearest 0.1 kilograms and noted as the average of two measurements. The body mass index (BMI) was calculated using the formula (weight in kg)/(height in meters)2 and the participants were classified as being overweight or obese if the BMI value ranged between 25 and 29.9 kg/m2 and 30 kg/m2 respectively [2]. Most epidemiological studies relied on BMI to diagnose obesity. However, it was shown to have low sensitivity to identify excess body fat [29,30]. Therefore, body composition analysis was performed using a bioelectrical impedance analyzer, “InBody 720” (InBody, CA, USA), to determine percent body fat for each participant [31]; values > 25% for men and 30% for women were used to indicate an elevated percent body fat [32]. InBody 720 body composition analyzer has been validated and compared to dual-energy x-ray absorptiometry (DXA) and is considered a valid estimator of lean mass and fat mass [33].
2.1. Study sample 2.5. Physical activity assessment The minimal sample size (n ¼ 252) was calculated based on the prevalence of overweightness and obesity among Lebanese university students (20.7%) [5], an alpha error of 5% and the precision of estimate (d ¼ 0.056), (20%p) [26]. We selected a random sample of 500 students from the university database using a random cluster sampling stratified by campus and gender and proportionate to the university total sample size. Subjects were contacted by phone to request for their participation in the study. They were offered a free dietary consultation in addition to free body composition analysis, as a motivation for participation. Twohundred fifty-two subjects agreed to participate after signing the consent form (response rate 50.4%). Thirty-one participants withdrew from the study resulting in a final sample of 221 (Flowchart S1 of the study available online). 2.2. Data collection Data were collected regarding age, gender, crowding index, and smoking. Crowding index was defined as the total number of coresidents per household, excluding the newborn infant, divided by the total number of rooms, excluding the kitchen and the bathrooms. Each participant was asked about his medical history: the presence of current or previous medical conditions, the year of diagnosis, and currently administered treatments. They were also asked about their first-degree family history of overweightness/ obesity. 2.3. Dietary recalls We assessed the dietary intake of the participants using 24-hour dietary recalls of three days (two weekdays and a day of the weekend) repeated twice within an interval of four weeks to obtain a total of six non-consecutive 24-hour dietary recalls. The five steps multiple-pass method proposed by the United States Department of Agriculture was adopted [27]. Dietary recalls were analyzed to calculate energy and macronutrients intakes of the participants
PA was assessed using the long form of the “International Physical Activity Questionnaire” (IPAQ) that estimates PA level across four domains: occupational, domestic, transportation, and leisure. A previously validated version of the IPAQ [34] was administered by dietitians twice within one-month interval and the average value was used. Volunteers answered questions about the frequency and duration of each PA intensity and domain. Only activities that lasted for a minimum of 10 minutes were accounted for in the questionnaire. The IPAQ scoring system was used to calculate Metabolic Equivalents of PA domains (MET.min/week). A value of 600 MET.min/week was used as a cut-off point of the PA level based on the Centers for Disease Control and Prevention, the American College of Sports Medicine and U.S. Department of Health and Human Services health recommendations of 30 minutes five times a week (totaling 150 minutes/week) [35]. Low, moderate, and high PA levels are equivalent to <600; 600 and <3000; and 3000 MET.min/week, respectively. Estimates related to the sedentary time were also indicated for weekdays and weekends. The time spent sitting was calculated in hours per day and was estimated based on the following questions from the long version of the IPAQ: “During the last seven days, how much time did you usually spend sitting on a weekday?”; “During the last seven days, how much time did you usually spend sitting on a weekend day?” [36]. 2.6. Statistical analysis Categorical variables were expressed as frequency and percentages, while continuous variables were expressed as mean and standard deviation. The chi-square test of association was used to assess the association between different independent variables (sociodemographic, health-related, and PA variables) and the dependent variable (percent body fat), stratified by gender. Multivariate logistic regression (with 95% confidence interval [CI]) was conducted to assess the relationship between PA domains (total, job-related, transportation-related, housework-related, leisure-
Please cite this article as: Harmouche-Karaki M et al., Combined effect of physical activity and sedentary behavior on body composition in university students, Clinical Nutrition, https://doi.org/10.1016/j.clnu.2019.06.015
M. Harmouche-Karaki et al. / Clinical Nutrition xxx (xxxx) xxx
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Table 1 Descriptive statistics of the study sample (n ¼ 221). Variable Sociodemographic variables Age (years)a Crowding index n (%)b <1 1 Living conditions n (%) Campus Off campus Field of studies n (%) Health sciences Non-health sciences Health-related variables Smoking n (%) Non smoker Former smoker Current smoker Family history of obesity n (%) Absence Presence Energy intake (Kcal) <2000 (W)/2500 kcal (M) 2000 (W) or 2500 kcal (M) Carbohydrates intake (% total energy intake)c <55% 55e75% Protein intake (% total energy intake)c <15% 15% Lipids intake (% total energy intake)c <30% 30% Eating out n (%) < once a week 1e4 times a week 4 times a week Anthropometric variables Body mass index n (%) <18.5 kg/m2 18.5e24.9 kg/m2 25e29.9 km/m2 30 kg/m2 Percent body fat n (%)d <25 _ or 30% \ 25 _ or 30% \ Physical activitye Total PA level n (%) <600 MET.min/week 600e3000 MET.min/week 3000 MET.min/week Job-related PA n (%) <600 MET.min/week 600e3000 MET.min/week 3000 MET.min/week Transportation-related PA n (%) <600 MET.min/week 600e3000 MET.min/week Housework-related PA n (%) <600 MET.min/week 600e3000 MET.min/week Leisure-related PA n (%) <600 MET.min/week 600e3000 MET.min/week 3000 MET.min/week Leisure type PA Walking Moderate PA Vigorous PA
Men n ¼ 97
Women n ¼ 124
Total n ¼ 221
p-value
22.0 ± 3.8
21.0 ± 2.7
21.5 ± 3.3
0.026 NS
80 (82.5) 17 (17.5)
99 (79.8) 25 (20.2)
179 (81.0) 42 (19.0)
7 (7.2) 90 (92.8)
3 (2.4) 121 (97.6)
10 (4.5) 211 (95.5)
49 (50.5) 48 (49.5)
71 (57.3) 53 (42.7)
120 (54.3) 101 (45.7)
47 (48.5) 3 (3.1) 47 (48.5)
97 (78.2) 5 (4.0) 22 (17.7)
144 (65.2) 8 (3.6) 69 (31.2)
45 (46.4) 52 (53.6)
65 (52.4) 59 (47.6)
110 (49.8) 111 (50.2)
57 (58.8) 40 (41.2)
102 (82.3) 22 (17.7)
159 (71.9) 62 (28.1)
84 (86.6) 13 (13.4)
103 (83.1) 21 (16.9)
187 (84.6) 34 (15.4)
53 (54.6) 44 (45.4)
73 (58.9) 51 (41.1)
126 (57.0) 95 (43.0)
14 (14.4) 83 (85.6)
23 (18.5) 101 (81.5)
37 (16.7) 184 (83.3)
66 (68.0) 28 (28.9) 3 (3.1)
83 (66.9) 37 (29.8) 4 (3.2)
149 (67.4) 65 (29.4) 7 (3.2)
8 (8.2) 47 (48.5) 35 (36.1) 7 (7.2)
12 (9.7) 90 (72.6) 19 (15.3) 3 (2.4)
20 (9.0) 137 (62.0) 54 (24.4) 10 (4.5)
76 (78.4) 21 (21.6)
64 (51.6) 60 (48.4)
140 (63.3) 81 (36.7)
17 (17.5) 60 (61.9) 20 (20.6)
40 (32.3) 67 (54.0) 17 (13.7)
57 (25.8) 127 (57.5) 37 (16.7)
84 (86.6) 9 (9.3) 4 (4.1)
107 (86.3) 14 (11.3) 3 (2.4)
191 (86.4) 23 (10.4) 7 (3.2)
92 (94.8) 5 (5.2)
114 (91.9) 10 (8.1)
206 (93.2) 15 (6.8)
91 (93.9) 6 (6.2)
111 (89.5) 13 (10.5)
202 (91.4) 19 (8.6)
33 (34.0) 51 (52.6) 13 (13.4)
71 (57.3) 48 (38.7) 5 (4.0)
104 (47.1) 99 (44.8) 18 (8.1)
10 (10.3) 54 (55.7) 33 (34.0)
19 (15.3) 39 (31.5) 66 (53.2)
29 (13.1) 93 (42.1) 99 (44.8)
0.089
NS
<0.001
NS
0.000
NS
NS
NS
NS
0.001
<0.001
0.035
NS
NS
NS
0.001
0.001
(continued on next page)
Please cite this article as: Harmouche-Karaki M et al., Combined effect of physical activity and sedentary behavior on body composition in university students, Clinical Nutrition, https://doi.org/10.1016/j.clnu.2019.06.015
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Table 1 (continued ) Variable
Men n ¼ 97
Women n ¼ 124
Total n ¼ 221
Sitting time (hours/day) <10.15 hours/day 10.15 hours/day
45 (46.4) 52 (53.6)
70 (56.5) 54 (43.5)
115 (52.0) 106 (48.0)
p-value NS
Statistical tests used: c2-test for group comparison of categorical variables and t-test for continuous variables; mean ± standard deviation (SD) were reported for quantitative data; frequencies and percentages were reported for qualitative data; p < 0.05 was considered as significant; NS ¼ non-significant (p > 0.10). a Mean ± standard deviation (SD). b Crowding index was defined as the total number of co-residents per household, excluding the newborn infant, divided by the total number of rooms, excluding the kitchen and the bathrooms. c Macronutrients recommended cut-off were used based on the WHO/FAO joint report [28]. d Values > 25% for men and 30% for women were used to indicate an elevated percent body fat [32]. e PA, Physical activity; MET, metabolic equivalent task; Total PA level (MET-minutes/week) ¼ Total physical activity MET-minutes/week ¼ sum of (Job PA þ Transportation PA þ Housework PA þ Leisure PA MET-minutes/week scores). Low PA level is equivalent to values < 600 MET.min/week. Moderate PA level is equivalent to values 600 and <3000 MET.min/week. High PA level is equivalent to values 3000 MET.min/week.
related, and leisure type) and percent body fat, adjusted for confounders (energy intake, sitting time, eating out, family history of obesity etc.). For the multivariate analysis, three models were built. Variables were included in the multivariate models by selecting those (apart from energy intake and sitting time) that were significantly associated with percent body fat, using the enter method. Model 1 examined the association between houseworkrelated PA and percent body fat adjusted for eating out and family history of obesity. Model 2 had a comparison between vigorous and moderate leisure PA and association with percent body fat; adjustment was made for housework-related PA, eating out, and family history of obesity. In Model 3, Model 2 was further adjusted for energy intake and sitting time. All tests were two-tailed and the significant level was set at p < 0.05. Statistical analyses were performed using IBM SPSS (IBM SPSS Statistics for Windows, Version 20, IBM corp., Armonk, NY). 2.7. Ethical statement All procedures performed in this study were in accordance with the ethical standards of the institutional research committee and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards. This study was approved by the Ethics Committee of Saint Joseph University of Beirut (USJ-201219). Informed consent was obtained from all participants included in the study. 3. Results 3.1. Characteristics of the participants The characteristics of the 221 participants are summarized in Table 1. Men had a higher BMI but lower body fat percent than women. They also had a significantly higher prevalence of total PA and leisure-related PA than women. 3.2. Association of participants characteristics with percent body fat Table 2 shows the association between participants’ characteristics and percent body fat. A family history of obesity and a higher frequency of eating out were associated with higher percent body fat. However, practicing more moderate leisure PA was associated with a lower percent body fat. Table 3 represents the multivariate analysis testing the association between PA domains and percent body fat. A higher odds ratio (OR) of elevated percent body fat was observed with housework-related PA 600 versus < 600 MET.min/week (OR ¼ 2.912; CI ¼ 1.086e7.811; p ¼ 0.034) after adjusting for eating out and family history of obesity (Model 1). When compared to vigorous leisure PA, moderate leisure PA was associated with a
lower OR of elevated percent body fat after adjusting for housework-related PA, eating out, and family history of obesity (OR ¼ 0.500; CI ¼ 0.266e0.939; p ¼ 0.031) (Model 2). When Model 2 was further adjusted for energy intake and sitting time, the association remained statistically significant for moderate PA (versus vigorous PA) (Model 3). 4. Discussion To our knowledge, this is the first study examining sitting time and domain-specific PA (occupational, transportation, housework, leisure) with percent body fat among Lebanese university students. Our results showed that men had a higher prevalence of moderate and vigorous PA level in total and leisure activities than women. No significant differences were detected between genders in the remaining domains. This is consistent with several studies that previously examined gender differences in PA [1,20]. Motives for the practice of PA generally differ between the two genders. While male university students are motivated by intrinsic factors like strength, positive health, enjoyment, and competition, female university students are more motivated by extrinsic factors like weight management and appearance [37]. A major finding of the present study was that moderate leisure PA, compared to vigorous leisure PA, was associated with a lower percent body fat. Moderate leisure PA corresponds to bicycling at a regular pace, swimming at a regular pace, doubles tennis and other activities performed at the same intensity [36]. Conversely, participants with higher housework related PA had higher percent body fat. No other associations were observed with total PA, occupational, or transportation-related PA. While total leisure PA showed an association with percent body fat at the limit of significance only, moderate leisure PA was associated with lower adiposity more than vigorous leisure PA, independent of sitting time. This is in accordance with previous studies where moderate PA had a negative association with body fat mass [38,39]; this association was previously shown to be more consistent than that with vigorous PA [39,40]. A meta-analysis revealed that among overweight adults, visceral adipose tissue decreased most with aerobic training at threshold 60e70% maximal heart rate or 45e55% VO2max [39]. Similarly, in a study on 197 young adults, moderate PA had more beneficial associations on body composition, while vigorous PA had a positive effect mostly on cardiorespiratory fitness [40]. An explanation is that during low intensity PA, the exercise duration is long, and fat is the main energy substrate; whereas during high intensity PA, the duration is short and carbohydrates are used as the major fuel [41]. Housework-related PA was associated with a higher percent body fat in our study, possibly because of the relatively low contribution of housework PA to the total PA level of university students (as shown in our study) in addition to the common
Please cite this article as: Harmouche-Karaki M et al., Combined effect of physical activity and sedentary behavior on body composition in university students, Clinical Nutrition, https://doi.org/10.1016/j.clnu.2019.06.015
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Table 2 Association between participants’ characteristics and percent body fat (n ¼ 221). Variable Sociodemographic variables Age (years)a Crowding index n (%)b <1 1 Living conditions n (%) Campus Off campus Field of studies n (%) Health sciences Non-health sciences Health-related variables Smoking n (%) Non smoker Former smoker Current smoker Family history of obesity n (%) Absence Presence Energy intake (Kcal) <2000 (W)/2500 kcal (M) 2000 (W) or 2500 kcal (M) Carbohydrates intake (% total energy intake) <55% 55e75% Protein intake (% total energy intake) <15% 15% Lipids intake (% total energy intake) <30% 30% Eating out n (%) < once a week 1e4 times a week 4 times a week Physical activityc Total PA level n (%) <600 MET.min/week 600e3000 MET.min/week 3000 MET.min/week Job-related PA n (%) <600 MET.min/week 600e3000 MET.min/week 3000 MET.min/week Transportation-related PA n (%) <600 MET.min/week 600e3000 MET.min/week Housework-related PA n (%) <600 MET.min/week 600e3000 MET.min/week Leisure-related PA n (%) <600 MET.min/week 600 MET.min/week Leisure type PA n (%) Walking Moderate PA Vigorous PA Sitting time (hours/day) <10.15 hours/day 10.15 hours/day
Low percent body fat (<25% M/30% W) [32] n ¼ 140
High percent body fat (25 M or 30% W) [32] n ¼ 81
Total n ¼ 221
p-value
21.3 ± 2.5
21.7 ± 4.2
21.5 ± 3.3
NS NS
115 (82.1) 25 (17.9)
64 (79.0) 17 (21.0)
179 (81) 42 (19)
8 (5.7) 132 (94.3)
2 (2.5) 79 (97.5)
10 (4.5) 211 (95.5)
77 (55.0) 63 (45.0)
43 (53.1) 38 (46.9)
120 (54.3) 101 (45.7)
96 (68.6) 4 (2.9) 40 (28.6)
48 (59.3) 4 (4.9) 29 (35.8)
144 (65.2) 8 (3.6) 69 (31.2)
80 (57.1) 60 (42.9)
31 (38.3) 50 (61.7)
111 (50.2) 110 (49.8)
100 (71.4) 40 (28.6)
59 (72.8) 22 (27.2)
159 (71.9) 62 (28.1)
117 (83.6) 23 (16.4)
70 (86.4) 11 (13.6)
187 (84.6) 34 (15.4)
80 (57.1) 60 (42.9)
46 (56.8) 35 (43.2)
126 (57) 95 (43)
25 (17.9) 115 (82.1)
12 (14.8) 69 (85.2)
37 (16.7) 184 (83.3)
101 (72.1) 37 (26.4) 2 (1.4)
48 (59.3) 28 (34.6) 5 (6.2)
149 (67.4) 65 (29.4) 7 (3.2)
35 (25.0) 78 (55.7) 27 (19.3)
22 (27.2) 49 (60.5) 10 (12.3)
57 (25.8) 127 (57.5) 37 (16.7)
125 (89.3) 10 (7.1) 5 (3.6)
66 (81.5) 13 (16) 2 (2.5)
191 (86.4) 23 (10.4) 7 (3.2)
129 (92.1) 11 (7.9)
77 (95.1) 4 (4.9)
206 (93.2) 15 (6.8)
132 (94.3) 8 (5.7)
70 (86.4) 11 (13.6)
202 (91.4) 19 (8.6)
59 (42.1) 81 (57.9)
45 (55.6) 36 (44.4)
104 (47.1) 117 (52.9)
19 (13.6) 68 (48.6) 53 (37.9)
10 (12.3) 25 (30.9) 46 (56.8)
29 (13.1) 93 (42.1) 99 (44.8)
68 (48.6) 72 (51.4)
47 (58.0) 34 (42.0)
115 (52) 106 (48)
NS
NS
NS
0.007
NS
NS
NS
NS
0.048
NS
NS
NS
0.044
0.054
0.018
NS
Statistical tests used: c2-test for group comparison of categorical variables and t-test for continuous variables; mean ± standard deviation (SD) were reported for quantitative data; frequencies and percentages were reported for qualitative data; p < 0.05 was considered as significant; NS ¼ non-significant (p > 0.10). Low percent body fat was defined as < 25% for men and <30% for women; high percent body fat was defined as 25% for men and 30% for women [32]. a Mean ± standard deviation (SD). b Crowding index was defined as the total number of co-residents per household, excluding the newborn infant, divided by the total number of rooms, excluding the kitchen and the bathrooms. c PA, Physical activity; MET, metabolic equivalent task; Total PA level (MET-minutes/week) ¼ Total physical activity MET-minutes/week ¼ sum of (Job PA þ Transportation PA þ Housework PA þ Leisure PA MET-minutes/week scores). Low PA level is equivalent to values < 600 MET.min/week. Moderate PA level is equivalent to values 600 and <3000 MET.min/week. High PA level is equivalent to values 3000 MET.min/week.
Please cite this article as: Harmouche-Karaki M et al., Combined effect of physical activity and sedentary behavior on body composition in university students, Clinical Nutrition, https://doi.org/10.1016/j.clnu.2019.06.015
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M. Harmouche-Karaki et al. / Clinical Nutrition xxx (xxxx) xxx
Table 3 Multivariate analysis showing odds ratios of elevated percent body fat according to leisure type PA and housework-related PA in a sample of university students (n ¼ 221). OR
Model 1a Housework-related PA 600 vs < 600 MET.min/week Eating Out 1e4 times/week vs < once a week 4 times/week vs < once a week Family history of obesity Presence vs Absence Model 2a Leisure type PA Walking vs vigorous PA Moderate PA vs vigorous PA Housework-related PA 600 vs < 600 MET.min/week Eating Out 1e4 times/week vs < once a week 4 times/week vs < once a week Family history of obesity Presence vs Absence Model 3a Leisure type PA Walking vs vigorous PA Moderate PA vs vigorous PA Housework-related PA 600 vs < 600 MET.min/week Eating Out 1e4 times/week vs < once a week 4 times/week vs < once a week Family history of obesity Presence vs Absence Energy intake (Kcal) 2000/2500 kcal vs < 2000/2500 kcal Sitting time (hours/day) 10.15 hours/day vs < 10.15 hours/day
95% CI
p-value
Lower bound
Upper bound
2.91
1.09
7.81
0.034
1.49 5.05
0.80 0.92
2.77 27.68
NS 0.062
2.07
1.17
3.68
0.013
0.52 0.50
0.21 0.27
1.29 0.94
NS 0.031
2.68
0.97
7.40
0.057
1.38 4.22
0.74 0.74
2.60 24.03
NS NS
2.11
1.18
3.79
0.012
0.53 0.50
0.21 0.26
1.31 0.94
NS 0.032
2.62
0.95
7.27
0.064
1.35 4.14
0.71 0.71
2.56 24.29
NS NS
2.18
1.21
3.95
0.01
0.87
0.45
1.68
NS
0.69
0.38
1.24
NS
NS ¼ non-significant (p > 0.10); p < 0.05 was considered as significant. Percent body fat took into consideration gender; Moderate and Vigorous Leisure PA correspond to the type of leisure PA reported in the IPAQ. a Percent body fat was adjusted for Model 1 eating out and family history of obesity; Model 2 housework-related PA, eating out and family history of obesity; Model 3: energy intake and sitting time in addition to Model 2.
presence of domestic helpers in Lebanese houses [42]. Previous studies provided mixed findings [25,43,44]; in a study on Flemish adults, household chores appeared to be the most important predictors of percent body fat in both genders [25]. However, a crosssectional study among 4563 adults in the United Kingdom showed that even though domestic PA accounted for a significant proportion of daily PA level, it was negatively associated with leanness, suggesting that “it may not be sufficient to provide all of the benefits normally associated with meeting the physical activity guidelines” [44]. Several studies have suggested that occupational PA was inversely associated with percent body fat [25,45]. In a recent interventional study, percent body fat was inversely associated with occupational short bouts of moderate-vigorous PA only among workers who did not meet PA guidelines [45]. Furthermore, an inverse association was observed between occupational PA and percent body fat [25]. In contrast, other studies did not show similar associations with job-related PA [17,46], similarly to the current study. Transportation-related PA was not associated with percent body fat. Previous data reported an inverse association with adiposity [43]. In a cross-sectional study conducted in the United Kingdom, “commuting via active or public transport was significantly associated with lower percent body fat than commuting via private transport” [47]. Nevertheless, many other studies did not show similar associations with transportation-related PA [17,25,46],
which is in line with our study. An explanation might be the inconsistent use of active transportation among Lebanese in favor of private cars [48]. Other factors influencing active transportation are time-related barriers and students’ living conditions [49]; most of the students in the present sample live relatively far from the campus and not in nearby dormitories. Sedentary behavior, a major independent factor, correlated with percent body fat. Current evidence suggests that sitting for eight hours or more per day was associated with 62% of higher odds of obesity than sitting for less than four hours/day, after adjustment for confounding variables [13]. In the current study, sitting time did not affect the association between moderate leisure PA and percent body fat. A systematic review of the correlates of sedentary behaviors among university students concluded that the association between sedentary behavior and obesity is inconsistent [50]. Previous data also suggested that PA seems more important than sedentary behavior in relation to obesity [17,25]. Nevertheless, this does not deny the negative impact of sedentary behavior on students’ health. In the present study, a considerably high level of sitting time was observed among university students, exceeding the level associated with high mortality rate (seven hours) [12]. A previous study revealed that replacing long sedentary bouts with brief sedentary bouts or moderate to vigorous PA among workers had beneficial effects on obesity indicators, including percent body fat [51].
Please cite this article as: Harmouche-Karaki M et al., Combined effect of physical activity and sedentary behavior on body composition in university students, Clinical Nutrition, https://doi.org/10.1016/j.clnu.2019.06.015
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Interestingly, there was no association between energy and macronutrients intakes with percent body fat. It has been recently outlined that even though energy intake is an important factor of weight gain, reducing it might not be enough to lose body weight [52]. Moreover, in line with the J-shaped association between energy expenditure and energy intake reported by Mayer et al, “energy intake matches energy expenditure at higher levels of energy expenditure. However, at low levels of energy expenditure, this tight association is disrupted and high levels of energy intake persist, resulting in weight gain” [53]. One limitation of the present study is the cross-sectional design, which prohibits causal inference, but enables the evaluation of associations. In the future, we plan to implement suitable interventions and re-assess PA levels and domains as well as sedentary behavior. Another limitation is that we did not study whether percent body fat correlates with disease risk, e.g. metabolic syndrome, diabetes, arterial hypertension, etc. Moreover, the relatively small sample size might have affected the power in the analyses. In addition, participants were selected from one university only, which does not permit for the generalizability of the results. The use of a questionnaire instead of a more objective measure (such as accelerometer) to assess PA is an additional limitation. This is due to recall bias and because the last seven days may not represent the habitual PA level. Hence, this was accounted for in this study by repeating the IPAQ twice, within one-month interval. Leisure PA might be more accurately reported by respondents while filling out the IPAQ, given that it has a more planned and structured nature. The absence of associations with occupational and transportationrelated PA may be because the majority of the students had low levels of non-leisure-related activities. A major strength was the assessment of domain-specific PA and its correlates using an internationally validated questionnaire; to our knowledge, this is the first study in Lebanon that used the long form of the IPAQ. Moreover, data on PA domain is lacking especially among university students in Lebanon and the Middle East. Therefore, sufficient data was provided in this study for the formulation of PA promotion strategies. Lastly, the BIA that was used to measure body composition is the most cost-effective method, with high precision and feasibility. Even though BMI was mostly used as the adiposity parameter in previous studies, it was shown to have low sensitivity to identify excess body fat [29,30]. In conclusion, we found that although university students spend long hours sitting, they can compensate for the negative effects of this behavior by practicing moderate leisure PA. This is the first study to shed the light on the effect of moderate activities vs. vigorous in a student community even with long sitting hours. It is also the first to provide a unique insight on patterns of PA and sedentary behavior in a sample of Lebanese university students. This may allow us to properly implement adequate interventions focusing on reducing the long periods spent sitting on campuses, as well as increasing PA level of moderate leisure PA and common daily activities across occupational and transportation-related PA domains. Formatting of funding sources This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors. CRediT author statement Mireille Harmouche-Karaki: Conceptualization, Methodology, Data curation, Software, Writing- Reviewing and Editing, Supervision. Maya Mahfouz: Data curation, Software, Writing- Original draft preparation. Yara Mahfouz: Software, Writing- Original draft
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preparation. Nicole Sayegh: Data curation, Software. Khalil Helou: Conceptualization, Supervision. Conflict of interest The authors declare that they have no conflict of interest. Acknowledgements The authors would like to gratefully thank Pr. Pascale Salameh (Lebanese University, Lebanon) for proofreading the manuscript. Appendix A. Supplementary data Supplementary data to this article can be found online at https://doi.org/10.1016/j.clnu.2019.06.015. References [1] Mehio Sibai A, Nasreddine L, Mokdad AH, Adra N, Tabet M, Hwalla N. Nutrition transition and cardiovascular disease risk factors in Middle East and North Africa countries: Reviewing the evidence. Ann Nutr Metab 2010;57:193e203. https://doi.org/10.1159/000321527. [2] World Health Organization. Obesity and overweight. 2018. http://www.who. int/news-room/fact-sheets/detail/obesity-and-overweight. [Accessed 11 October 2018]. [3] National research council, Institute of Medicine. U.S. Health in International perspective: shorter lives, poorer health. 2013. https://doi.org/10.17226/ 13497. [4] El-Kassas G, Ziade F. Exploration of the dietary and lifestyle behaviors and weight status and their self-perceptions among Health Sciences university students in North Lebanon. BioMed Res Int 2016. https://doi.org/10.1155/ 2016/9762396. J, Zeidan N, et al. Assessment of [5] Salameh P, Jomaa L, Issa C, Farhat G, Salame dietary intake patterns and their correlates among university students in Lebanon. Front Public Health 2014;2. https://doi.org/10.3389/fpubh.2014. 00185. [6] Golzarand M, Mirmiran P, Jessri M, Toolabi K, Mojarrad M, Azizi F. Dietary trends in the Middle East and North Africa: an ecological study (1961 to 2007). Public Health Nutr 2012;15:1835e44. https://doi.org/10.1017/S13689 80011003673. [7] Popkin BM, Adair LS, Ng SW. Global nutrition transition and the pandemic of obesity in developing countries. Nutr Rev 2012;70:3e21. https://doi.org/ 10.1111/j.1753-4887.2011.00456.x. [8] Rahim HFA, Sibai A, Khader Y, Hwalla N, Fadhil I, Alsiyabi H, et al. Noncommunicable diseases in the Arab world. Lancet 2014;383:356e67. https:// doi.org/10.1016/S0140-6736(13)62383-1. M, Parent-Massin D. Food consump[9] Nasreddine L, Hwalla N, Sibai A, Hamze tion patterns in an adult urban population in Beirut, Lebanon. Public Health Nutr 2006;9. https://doi.org/10.1079/PHN2005855. [10] Naja F, Nasreddine L, Itani L, Adra N, Sibai AM, Hwalla N. Association between dietary patterns and the risk of metabolic syndrome among Lebanese adults. Eur J Nutr 2013;52:97e105. https://doi.org/10.1007/s00394-011-0291-3. [11] Mansoubi M, Pearson N, Clemes SA, Biddle SJ, Bodicoat DH, Tolfrey K, et al. Energy expenditure during common sitting and standing tasks: examining the 1.5 MET definition of sedentary behaviour. BMC Public Health 2015;15. https://doi.org/10.1186/s12889-015-1851-x. [12] Biddle SJH, Bennie JA, Bauman AE, Chau JY, Dunstan D, Owen N, et al. Too much sitting and all-cause mortality: is there a causal link? BMC Public Health 2016;16:635. https://doi.org/10.1186/s12889-016-3307-3. [13] Bullock VE, Griffiths P, Sherar LB, Clemes SA. Sitting time and obesity in a sample of adults from Europe and the USA. Ann Hum Biol 2017;44:230e6. https://doi.org/10.1080/03014460.2016.1232749. [14] Al-Hariri M, Alkahtani S, Abdelgayed A M. Impact of life behaviour on students physical fitness at university of dammam in Saudi Arabia. Acad Res Int 2014;5:87e93. [15] Musaiger AO, Awadhalla MS, Al-Mannai M, AlSawad M, Asokan GV. Dietary habits and sedentary behaviors among health science university students in Bahrain. Int J Adolesc Med Health 2015;29. https://doi.org/10.1515/ijamh2015-0038. [16] Mabry R, Koohsari MJ, Bull F, Owen N. A systematic review of physical activity and sedentary behaviour research in the oil-producing countries of the Arabian Peninsula. BMC Public Health 2016;16. https://doi.org/10.1186/ s12889-016-3642-4. [17] Wanner M, Martin BW, Autenrieth CS, Schaffner E, Meier F, Brombach C, et al. Associations between domains of physical activity, sitting time, and different measures of overweight and obesity. Prev Med Rep 2016;3:177e84. https:// doi.org/10.1016/j.pmedr.2016.01.007.
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Contents lists available at ScienceDirect
Clinical Nutrition journal homepage: http://www.elsevier.com/locate/clnu
Original article
Combined effect of physical activity and sedentary behavior on body composition in university students Mireille Harmouche-Karaki*, Maya Mahfouz, Yara Mahfouz, Nicole Fakhoury-Sayegh, Khalil Helou Department of Nutrition, Faculty of Pharmacy, Saint Joseph University of Beirut, Lebanon B.P. 11-5076, Riad el Solh Beyrouth, 1107 2180, Lebanon
a r t i c l e i n f o
s u m m a r y
Article history: Received 23 October 2018 Accepted 17 June 2019
Background & aims: This study aimed to evaluate the domain-specific physical activity (PA) levels and sitting time of a sample of university students and examine the association of PA with percent body fat. Methods: Two hundred and twenty-one students were included in the analysis. We administered the long form of the International Physical Activity Questionnaire (IPAQ) twice within one-month interval. Total PA as well as occupational, transportation-, housework-, and leisure-related PA were assessed, in addition to sitting time. Dietary intake was derived from six non-consecutive 24-hour dietary recalls. Percent body fat (dependent variable) was analyzed using a bioelectrical impedance analyzer (BIA). Multivariate logistic regression, adjusted for potential confounders, examined the associations of domain-specific PA and sitting time with percent body fat. Results: Men had higher levels of total and leisure PA than women. All participants had prolonged sitting time, with 48% having a sitting time of more than 10.15 hours/day. In multivariate analysis, moderate leisure PA, compared to vigorous PA was associated with a lower percent body fat. This association remained statistically significant even after adjustment for energy intake and sitting time. Houseworkrelated PA was associated with a higher percent body fat. Conclusion: Moderate leisure PA was highly associated with percent body fat even after adjustment for confounding variables. Adequate interventions targeting this kind of leisure should be promoted among universities students. © 2019 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
Keywords: Physical activity Sitting time Percent body fat University students
1. Introduction Recently, the prevalence of non-communicable diseases has globally increased. It is anticipated that they will be the main cause of death by 2020 [1]. In particular, obesity is aggravating, and worldwide levels have tripled since 1975 [2]. According to a report published in 2013 by the National Research Council and the Institute of Medicine, chronic diseases are expanding to reach the young generations, in addition to adults [3]. Among Lebanese university
Abbreviations: BIA, bioelectrical impedance analyzer; BMI, body mass index; IPAQ, International Physical Activity Questionnaire; M, men; MET, metabolic equivalent; OR, odds ratio; PA, physical activity; W, women. * Corresponding author. E-mail addresses: [email protected] (M. Harmouche-Karaki), [email protected] (M. Mahfouz), [email protected] (Y. Mahfouz), [email protected] (N. Fakhoury-Sayegh), [email protected]. lb (K. Helou).
students, levels of overweightness and obesity varied between 15.5e27.6% and 4.1e4.6%, respectively [4,5]. An important contributor to obesity is the replacement of the traditional diet with a westernized pattern, particularly among university students [6e8]; the consumption of energy-dense foods high in fat and sugar has increased at the expense of the intake of fish, fruits, and vegetables [5,9,10]. Another leading cause is sedentary behavior; it is defined as a waking activity that has an energy expenditure of 1.5 metabolic equivalents while sitting or reclining such as screen viewing, reading, and riding in an automobile [11]. Prolonged sitting is associated with increased obesity and other adverse health outcomes, independently of physical activity (PA) levels [12,13]. Even though data on sedentary behaviors among university students are scarce, long sitting hours have been reported worldwide and in Arabic countries [13e16] due to the rapid global evolution and the intense spread of technology [1]. The current obesity pandemic is also associated with reduced PA. There is compelling evidence on the inverse association between total PA
https://doi.org/10.1016/j.clnu.2019.06.015 0261-5614/© 2019 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
Please cite this article as: Harmouche-Karaki M et al., Combined effect of physical activity and sedentary behavior on body composition in university students, Clinical Nutrition, https://doi.org/10.1016/j.clnu.2019.06.015
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and percent body fat [17,18]. Despite the public health efforts to improve PA levels, many studies have shown considerable levels of physical inactivity among university students. In a study from 23 countries, the prevalence of physical inactivity was 41.4% ranging from 21.9% to 80.6% [19]. In Lebanon, reported levels of PA among university students were 72.5% in 2010 [20] and 60% in 2014 [21]. Therefore, targeting university students for PA interventions is vital since PA is associated with an enhanced health-related quality of life among university students [22]. In addition, PA patterns established in college are maintained throughout adulthood (carryover effect) [23]. Studies to date have focused predominantly on leisure-related PA, despite the large contribution of domainspecific activities (occupational, transportation, domestic, leisure) to total PA level [24]. Previous findings showed that leisure-time PA was associated with a lower risk of percent body fat, independent of sitting time [17]. However, occupational and housework-related PA showed inconsistent results [17,25]. In Lebanon, although there is evidence on the prevalence of PA, data are lacking on the specific domains of PA and sitting time and their association with anthropometric variables, specifically percent body fat. Therefore, our aim in this study was to evaluate the effect of domain-specific PA and sitting time on percent body fat in a Lebanese sample of students at Saint Joseph University of Beirut Saint Joseph - USJ). (Universite 2. Materials and methods
using the Nutrilog software (Nutrilog SAS, Version 2.30, France). Macronutrients recommended cut-off were used based on the WHO/FAO joint report [28]. 2.4. Anthropometric measurements For each participant, the height was measured using a stadiometer (Health o meter, Sunbeam Products Inc., IL, USA) and was recorded to the nearest 0.1 centimeters (cm). Two measurements were taken and the average differing by 0.5 cm was indicated. Body weight was measured using a mechanical scale (Health o meter, Sunbeam Products Inc., IL, USA) and was recorded to the nearest 0.1 kilograms and noted as the average of two measurements. The body mass index (BMI) was calculated using the formula (weight in kg)/(height in meters)2 and the participants were classified as being overweight or obese if the BMI value ranged between 25 and 29.9 kg/m2 and 30 kg/m2 respectively [2]. Most epidemiological studies relied on BMI to diagnose obesity. However, it was shown to have low sensitivity to identify excess body fat [29,30]. Therefore, body composition analysis was performed using a bioelectrical impedance analyzer, “InBody 720” (InBody, CA, USA), to determine percent body fat for each participant [31]; values > 25% for men and 30% for women were used to indicate an elevated percent body fat [32]. InBody 720 body composition analyzer has been validated and compared to dual-energy x-ray absorptiometry (DXA) and is considered a valid estimator of lean mass and fat mass [33].
2.1. Study sample 2.5. Physical activity assessment The minimal sample size (n ¼ 252) was calculated based on the prevalence of overweightness and obesity among Lebanese university students (20.7%) [5], an alpha error of 5% and the precision of estimate (d ¼ 0.056), (20%p) [26]. We selected a random sample of 500 students from the university database using a random cluster sampling stratified by campus and gender and proportionate to the university total sample size. Subjects were contacted by phone to request for their participation in the study. They were offered a free dietary consultation in addition to free body composition analysis, as a motivation for participation. Twohundred fifty-two subjects agreed to participate after signing the consent form (response rate 50.4%). Thirty-one participants withdrew from the study resulting in a final sample of 221 (Flowchart S1 of the study available online). 2.2. Data collection Data were collected regarding age, gender, crowding index, and smoking. Crowding index was defined as the total number of coresidents per household, excluding the newborn infant, divided by the total number of rooms, excluding the kitchen and the bathrooms. Each participant was asked about his medical history: the presence of current or previous medical conditions, the year of diagnosis, and currently administered treatments. They were also asked about their first-degree family history of overweightness/ obesity. 2.3. Dietary recalls We assessed the dietary intake of the participants using 24-hour dietary recalls of three days (two weekdays and a day of the weekend) repeated twice within an interval of four weeks to obtain a total of six non-consecutive 24-hour dietary recalls. The five steps multiple-pass method proposed by the United States Department of Agriculture was adopted [27]. Dietary recalls were analyzed to calculate energy and macronutrients intakes of the participants
PA was assessed using the long form of the “International Physical Activity Questionnaire” (IPAQ) that estimates PA level across four domains: occupational, domestic, transportation, and leisure. A previously validated version of the IPAQ [34] was administered by dietitians twice within one-month interval and the average value was used. Volunteers answered questions about the frequency and duration of each PA intensity and domain. Only activities that lasted for a minimum of 10 minutes were accounted for in the questionnaire. The IPAQ scoring system was used to calculate Metabolic Equivalents of PA domains (MET.min/week). A value of 600 MET.min/week was used as a cut-off point of the PA level based on the Centers for Disease Control and Prevention, the American College of Sports Medicine and U.S. Department of Health and Human Services health recommendations of 30 minutes five times a week (totaling 150 minutes/week) [35]. Low, moderate, and high PA levels are equivalent to <600; 600 and <3000; and 3000 MET.min/week, respectively. Estimates related to the sedentary time were also indicated for weekdays and weekends. The time spent sitting was calculated in hours per day and was estimated based on the following questions from the long version of the IPAQ: “During the last seven days, how much time did you usually spend sitting on a weekday?”; “During the last seven days, how much time did you usually spend sitting on a weekend day?” [36]. 2.6. Statistical analysis Categorical variables were expressed as frequency and percentages, while continuous variables were expressed as mean and standard deviation. The chi-square test of association was used to assess the association between different independent variables (sociodemographic, health-related, and PA variables) and the dependent variable (percent body fat), stratified by gender. Multivariate logistic regression (with 95% confidence interval [CI]) was conducted to assess the relationship between PA domains (total, job-related, transportation-related, housework-related, leisure-
Please cite this article as: Harmouche-Karaki M et al., Combined effect of physical activity and sedentary behavior on body composition in university students, Clinical Nutrition, https://doi.org/10.1016/j.clnu.2019.06.015
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Table 1 Descriptive statistics of the study sample (n ¼ 221). Variable Sociodemographic variables Age (years)a Crowding index n (%)b <1 1 Living conditions n (%) Campus Off campus Field of studies n (%) Health sciences Non-health sciences Health-related variables Smoking n (%) Non smoker Former smoker Current smoker Family history of obesity n (%) Absence Presence Energy intake (Kcal) <2000 (W)/2500 kcal (M) 2000 (W) or 2500 kcal (M) Carbohydrates intake (% total energy intake)c <55% 55e75% Protein intake (% total energy intake)c <15% 15% Lipids intake (% total energy intake)c <30% 30% Eating out n (%) < once a week 1e4 times a week 4 times a week Anthropometric variables Body mass index n (%) <18.5 kg/m2 18.5e24.9 kg/m2 25e29.9 km/m2 30 kg/m2 Percent body fat n (%)d <25 _ or 30% \ 25 _ or 30% \ Physical activitye Total PA level n (%) <600 MET.min/week 600e3000 MET.min/week 3000 MET.min/week Job-related PA n (%) <600 MET.min/week 600e3000 MET.min/week 3000 MET.min/week Transportation-related PA n (%) <600 MET.min/week 600e3000 MET.min/week Housework-related PA n (%) <600 MET.min/week 600e3000 MET.min/week Leisure-related PA n (%) <600 MET.min/week 600e3000 MET.min/week 3000 MET.min/week Leisure type PA Walking Moderate PA Vigorous PA
Men n ¼ 97
Women n ¼ 124
Total n ¼ 221
p-value
22.0 ± 3.8
21.0 ± 2.7
21.5 ± 3.3
0.026 NS
80 (82.5) 17 (17.5)
99 (79.8) 25 (20.2)
179 (81.0) 42 (19.0)
7 (7.2) 90 (92.8)
3 (2.4) 121 (97.6)
10 (4.5) 211 (95.5)
49 (50.5) 48 (49.5)
71 (57.3) 53 (42.7)
120 (54.3) 101 (45.7)
47 (48.5) 3 (3.1) 47 (48.5)
97 (78.2) 5 (4.0) 22 (17.7)
144 (65.2) 8 (3.6) 69 (31.2)
45 (46.4) 52 (53.6)
65 (52.4) 59 (47.6)
110 (49.8) 111 (50.2)
57 (58.8) 40 (41.2)
102 (82.3) 22 (17.7)
159 (71.9) 62 (28.1)
84 (86.6) 13 (13.4)
103 (83.1) 21 (16.9)
187 (84.6) 34 (15.4)
53 (54.6) 44 (45.4)
73 (58.9) 51 (41.1)
126 (57.0) 95 (43.0)
14 (14.4) 83 (85.6)
23 (18.5) 101 (81.5)
37 (16.7) 184 (83.3)
66 (68.0) 28 (28.9) 3 (3.1)
83 (66.9) 37 (29.8) 4 (3.2)
149 (67.4) 65 (29.4) 7 (3.2)
8 (8.2) 47 (48.5) 35 (36.1) 7 (7.2)
12 (9.7) 90 (72.6) 19 (15.3) 3 (2.4)
20 (9.0) 137 (62.0) 54 (24.4) 10 (4.5)
76 (78.4) 21 (21.6)
64 (51.6) 60 (48.4)
140 (63.3) 81 (36.7)
17 (17.5) 60 (61.9) 20 (20.6)
40 (32.3) 67 (54.0) 17 (13.7)
57 (25.8) 127 (57.5) 37 (16.7)
84 (86.6) 9 (9.3) 4 (4.1)
107 (86.3) 14 (11.3) 3 (2.4)
191 (86.4) 23 (10.4) 7 (3.2)
92 (94.8) 5 (5.2)
114 (91.9) 10 (8.1)
206 (93.2) 15 (6.8)
91 (93.9) 6 (6.2)
111 (89.5) 13 (10.5)
202 (91.4) 19 (8.6)
33 (34.0) 51 (52.6) 13 (13.4)
71 (57.3) 48 (38.7) 5 (4.0)
104 (47.1) 99 (44.8) 18 (8.1)
10 (10.3) 54 (55.7) 33 (34.0)
19 (15.3) 39 (31.5) 66 (53.2)
29 (13.1) 93 (42.1) 99 (44.8)
0.089
NS
<0.001
NS
0.000
NS
NS
NS
NS
0.001
<0.001
0.035
NS
NS
NS
0.001
0.001
(continued on next page)
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Table 1 (continued ) Variable
Men n ¼ 97
Women n ¼ 124
Total n ¼ 221
Sitting time (hours/day) <10.15 hours/day 10.15 hours/day
45 (46.4) 52 (53.6)
70 (56.5) 54 (43.5)
115 (52.0) 106 (48.0)
p-value NS
Statistical tests used: c2-test for group comparison of categorical variables and t-test for continuous variables; mean ± standard deviation (SD) were reported for quantitative data; frequencies and percentages were reported for qualitative data; p < 0.05 was considered as significant; NS ¼ non-significant (p > 0.10). a Mean ± standard deviation (SD). b Crowding index was defined as the total number of co-residents per household, excluding the newborn infant, divided by the total number of rooms, excluding the kitchen and the bathrooms. c Macronutrients recommended cut-off were used based on the WHO/FAO joint report [28]. d Values > 25% for men and 30% for women were used to indicate an elevated percent body fat [32]. e PA, Physical activity; MET, metabolic equivalent task; Total PA level (MET-minutes/week) ¼ Total physical activity MET-minutes/week ¼ sum of (Job PA þ Transportation PA þ Housework PA þ Leisure PA MET-minutes/week scores). Low PA level is equivalent to values < 600 MET.min/week. Moderate PA level is equivalent to values 600 and <3000 MET.min/week. High PA level is equivalent to values 3000 MET.min/week.
related, and leisure type) and percent body fat, adjusted for confounders (energy intake, sitting time, eating out, family history of obesity etc.). For the multivariate analysis, three models were built. Variables were included in the multivariate models by selecting those (apart from energy intake and sitting time) that were significantly associated with percent body fat, using the enter method. Model 1 examined the association between houseworkrelated PA and percent body fat adjusted for eating out and family history of obesity. Model 2 had a comparison between vigorous and moderate leisure PA and association with percent body fat; adjustment was made for housework-related PA, eating out, and family history of obesity. In Model 3, Model 2 was further adjusted for energy intake and sitting time. All tests were two-tailed and the significant level was set at p < 0.05. Statistical analyses were performed using IBM SPSS (IBM SPSS Statistics for Windows, Version 20, IBM corp., Armonk, NY). 2.7. Ethical statement All procedures performed in this study were in accordance with the ethical standards of the institutional research committee and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards. This study was approved by the Ethics Committee of Saint Joseph University of Beirut (USJ-201219). Informed consent was obtained from all participants included in the study. 3. Results 3.1. Characteristics of the participants The characteristics of the 221 participants are summarized in Table 1. Men had a higher BMI but lower body fat percent than women. They also had a significantly higher prevalence of total PA and leisure-related PA than women. 3.2. Association of participants characteristics with percent body fat Table 2 shows the association between participants’ characteristics and percent body fat. A family history of obesity and a higher frequency of eating out were associated with higher percent body fat. However, practicing more moderate leisure PA was associated with a lower percent body fat. Table 3 represents the multivariate analysis testing the association between PA domains and percent body fat. A higher odds ratio (OR) of elevated percent body fat was observed with housework-related PA 600 versus < 600 MET.min/week (OR ¼ 2.912; CI ¼ 1.086e7.811; p ¼ 0.034) after adjusting for eating out and family history of obesity (Model 1). When compared to vigorous leisure PA, moderate leisure PA was associated with a
lower OR of elevated percent body fat after adjusting for housework-related PA, eating out, and family history of obesity (OR ¼ 0.500; CI ¼ 0.266e0.939; p ¼ 0.031) (Model 2). When Model 2 was further adjusted for energy intake and sitting time, the association remained statistically significant for moderate PA (versus vigorous PA) (Model 3). 4. Discussion To our knowledge, this is the first study examining sitting time and domain-specific PA (occupational, transportation, housework, leisure) with percent body fat among Lebanese university students. Our results showed that men had a higher prevalence of moderate and vigorous PA level in total and leisure activities than women. No significant differences were detected between genders in the remaining domains. This is consistent with several studies that previously examined gender differences in PA [1,20]. Motives for the practice of PA generally differ between the two genders. While male university students are motivated by intrinsic factors like strength, positive health, enjoyment, and competition, female university students are more motivated by extrinsic factors like weight management and appearance [37]. A major finding of the present study was that moderate leisure PA, compared to vigorous leisure PA, was associated with a lower percent body fat. Moderate leisure PA corresponds to bicycling at a regular pace, swimming at a regular pace, doubles tennis and other activities performed at the same intensity [36]. Conversely, participants with higher housework related PA had higher percent body fat. No other associations were observed with total PA, occupational, or transportation-related PA. While total leisure PA showed an association with percent body fat at the limit of significance only, moderate leisure PA was associated with lower adiposity more than vigorous leisure PA, independent of sitting time. This is in accordance with previous studies where moderate PA had a negative association with body fat mass [38,39]; this association was previously shown to be more consistent than that with vigorous PA [39,40]. A meta-analysis revealed that among overweight adults, visceral adipose tissue decreased most with aerobic training at threshold 60e70% maximal heart rate or 45e55% VO2max [39]. Similarly, in a study on 197 young adults, moderate PA had more beneficial associations on body composition, while vigorous PA had a positive effect mostly on cardiorespiratory fitness [40]. An explanation is that during low intensity PA, the exercise duration is long, and fat is the main energy substrate; whereas during high intensity PA, the duration is short and carbohydrates are used as the major fuel [41]. Housework-related PA was associated with a higher percent body fat in our study, possibly because of the relatively low contribution of housework PA to the total PA level of university students (as shown in our study) in addition to the common
Please cite this article as: Harmouche-Karaki M et al., Combined effect of physical activity and sedentary behavior on body composition in university students, Clinical Nutrition, https://doi.org/10.1016/j.clnu.2019.06.015
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Table 2 Association between participants’ characteristics and percent body fat (n ¼ 221). Variable Sociodemographic variables Age (years)a Crowding index n (%)b <1 1 Living conditions n (%) Campus Off campus Field of studies n (%) Health sciences Non-health sciences Health-related variables Smoking n (%) Non smoker Former smoker Current smoker Family history of obesity n (%) Absence Presence Energy intake (Kcal) <2000 (W)/2500 kcal (M) 2000 (W) or 2500 kcal (M) Carbohydrates intake (% total energy intake) <55% 55e75% Protein intake (% total energy intake) <15% 15% Lipids intake (% total energy intake) <30% 30% Eating out n (%) < once a week 1e4 times a week 4 times a week Physical activityc Total PA level n (%) <600 MET.min/week 600e3000 MET.min/week 3000 MET.min/week Job-related PA n (%) <600 MET.min/week 600e3000 MET.min/week 3000 MET.min/week Transportation-related PA n (%) <600 MET.min/week 600e3000 MET.min/week Housework-related PA n (%) <600 MET.min/week 600e3000 MET.min/week Leisure-related PA n (%) <600 MET.min/week 600 MET.min/week Leisure type PA n (%) Walking Moderate PA Vigorous PA Sitting time (hours/day) <10.15 hours/day 10.15 hours/day
Low percent body fat (<25% M/30% W) [32] n ¼ 140
High percent body fat (25 M or 30% W) [32] n ¼ 81
Total n ¼ 221
p-value
21.3 ± 2.5
21.7 ± 4.2
21.5 ± 3.3
NS NS
115 (82.1) 25 (17.9)
64 (79.0) 17 (21.0)
179 (81) 42 (19)
8 (5.7) 132 (94.3)
2 (2.5) 79 (97.5)
10 (4.5) 211 (95.5)
77 (55.0) 63 (45.0)
43 (53.1) 38 (46.9)
120 (54.3) 101 (45.7)
96 (68.6) 4 (2.9) 40 (28.6)
48 (59.3) 4 (4.9) 29 (35.8)
144 (65.2) 8 (3.6) 69 (31.2)
80 (57.1) 60 (42.9)
31 (38.3) 50 (61.7)
111 (50.2) 110 (49.8)
100 (71.4) 40 (28.6)
59 (72.8) 22 (27.2)
159 (71.9) 62 (28.1)
117 (83.6) 23 (16.4)
70 (86.4) 11 (13.6)
187 (84.6) 34 (15.4)
80 (57.1) 60 (42.9)
46 (56.8) 35 (43.2)
126 (57) 95 (43)
25 (17.9) 115 (82.1)
12 (14.8) 69 (85.2)
37 (16.7) 184 (83.3)
101 (72.1) 37 (26.4) 2 (1.4)
48 (59.3) 28 (34.6) 5 (6.2)
149 (67.4) 65 (29.4) 7 (3.2)
35 (25.0) 78 (55.7) 27 (19.3)
22 (27.2) 49 (60.5) 10 (12.3)
57 (25.8) 127 (57.5) 37 (16.7)
125 (89.3) 10 (7.1) 5 (3.6)
66 (81.5) 13 (16) 2 (2.5)
191 (86.4) 23 (10.4) 7 (3.2)
129 (92.1) 11 (7.9)
77 (95.1) 4 (4.9)
206 (93.2) 15 (6.8)
132 (94.3) 8 (5.7)
70 (86.4) 11 (13.6)
202 (91.4) 19 (8.6)
59 (42.1) 81 (57.9)
45 (55.6) 36 (44.4)
104 (47.1) 117 (52.9)
19 (13.6) 68 (48.6) 53 (37.9)
10 (12.3) 25 (30.9) 46 (56.8)
29 (13.1) 93 (42.1) 99 (44.8)
68 (48.6) 72 (51.4)
47 (58.0) 34 (42.0)
115 (52) 106 (48)
NS
NS
NS
0.007
NS
NS
NS
NS
0.048
NS
NS
NS
0.044
0.054
0.018
NS
Statistical tests used: c2-test for group comparison of categorical variables and t-test for continuous variables; mean ± standard deviation (SD) were reported for quantitative data; frequencies and percentages were reported for qualitative data; p < 0.05 was considered as significant; NS ¼ non-significant (p > 0.10). Low percent body fat was defined as < 25% for men and <30% for women; high percent body fat was defined as 25% for men and 30% for women [32]. a Mean ± standard deviation (SD). b Crowding index was defined as the total number of co-residents per household, excluding the newborn infant, divided by the total number of rooms, excluding the kitchen and the bathrooms. c PA, Physical activity; MET, metabolic equivalent task; Total PA level (MET-minutes/week) ¼ Total physical activity MET-minutes/week ¼ sum of (Job PA þ Transportation PA þ Housework PA þ Leisure PA MET-minutes/week scores). Low PA level is equivalent to values < 600 MET.min/week. Moderate PA level is equivalent to values 600 and <3000 MET.min/week. High PA level is equivalent to values 3000 MET.min/week.
Please cite this article as: Harmouche-Karaki M et al., Combined effect of physical activity and sedentary behavior on body composition in university students, Clinical Nutrition, https://doi.org/10.1016/j.clnu.2019.06.015
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Table 3 Multivariate analysis showing odds ratios of elevated percent body fat according to leisure type PA and housework-related PA in a sample of university students (n ¼ 221). OR
Model 1a Housework-related PA 600 vs < 600 MET.min/week Eating Out 1e4 times/week vs < once a week 4 times/week vs < once a week Family history of obesity Presence vs Absence Model 2a Leisure type PA Walking vs vigorous PA Moderate PA vs vigorous PA Housework-related PA 600 vs < 600 MET.min/week Eating Out 1e4 times/week vs < once a week 4 times/week vs < once a week Family history of obesity Presence vs Absence Model 3a Leisure type PA Walking vs vigorous PA Moderate PA vs vigorous PA Housework-related PA 600 vs < 600 MET.min/week Eating Out 1e4 times/week vs < once a week 4 times/week vs < once a week Family history of obesity Presence vs Absence Energy intake (Kcal) 2000/2500 kcal vs < 2000/2500 kcal Sitting time (hours/day) 10.15 hours/day vs < 10.15 hours/day
95% CI
p-value
Lower bound
Upper bound
2.91
1.09
7.81
0.034
1.49 5.05
0.80 0.92
2.77 27.68
NS 0.062
2.07
1.17
3.68
0.013
0.52 0.50
0.21 0.27
1.29 0.94
NS 0.031
2.68
0.97
7.40
0.057
1.38 4.22
0.74 0.74
2.60 24.03
NS NS
2.11
1.18
3.79
0.012
0.53 0.50
0.21 0.26
1.31 0.94
NS 0.032
2.62
0.95
7.27
0.064
1.35 4.14
0.71 0.71
2.56 24.29
NS NS
2.18
1.21
3.95
0.01
0.87
0.45
1.68
NS
0.69
0.38
1.24
NS
NS ¼ non-significant (p > 0.10); p < 0.05 was considered as significant. Percent body fat took into consideration gender; Moderate and Vigorous Leisure PA correspond to the type of leisure PA reported in the IPAQ. a Percent body fat was adjusted for Model 1 eating out and family history of obesity; Model 2 housework-related PA, eating out and family history of obesity; Model 3: energy intake and sitting time in addition to Model 2.
presence of domestic helpers in Lebanese houses [42]. Previous studies provided mixed findings [25,43,44]; in a study on Flemish adults, household chores appeared to be the most important predictors of percent body fat in both genders [25]. However, a crosssectional study among 4563 adults in the United Kingdom showed that even though domestic PA accounted for a significant proportion of daily PA level, it was negatively associated with leanness, suggesting that “it may not be sufficient to provide all of the benefits normally associated with meeting the physical activity guidelines” [44]. Several studies have suggested that occupational PA was inversely associated with percent body fat [25,45]. In a recent interventional study, percent body fat was inversely associated with occupational short bouts of moderate-vigorous PA only among workers who did not meet PA guidelines [45]. Furthermore, an inverse association was observed between occupational PA and percent body fat [25]. In contrast, other studies did not show similar associations with job-related PA [17,46], similarly to the current study. Transportation-related PA was not associated with percent body fat. Previous data reported an inverse association with adiposity [43]. In a cross-sectional study conducted in the United Kingdom, “commuting via active or public transport was significantly associated with lower percent body fat than commuting via private transport” [47]. Nevertheless, many other studies did not show similar associations with transportation-related PA [17,25,46],
which is in line with our study. An explanation might be the inconsistent use of active transportation among Lebanese in favor of private cars [48]. Other factors influencing active transportation are time-related barriers and students’ living conditions [49]; most of the students in the present sample live relatively far from the campus and not in nearby dormitories. Sedentary behavior, a major independent factor, correlated with percent body fat. Current evidence suggests that sitting for eight hours or more per day was associated with 62% of higher odds of obesity than sitting for less than four hours/day, after adjustment for confounding variables [13]. In the current study, sitting time did not affect the association between moderate leisure PA and percent body fat. A systematic review of the correlates of sedentary behaviors among university students concluded that the association between sedentary behavior and obesity is inconsistent [50]. Previous data also suggested that PA seems more important than sedentary behavior in relation to obesity [17,25]. Nevertheless, this does not deny the negative impact of sedentary behavior on students’ health. In the present study, a considerably high level of sitting time was observed among university students, exceeding the level associated with high mortality rate (seven hours) [12]. A previous study revealed that replacing long sedentary bouts with brief sedentary bouts or moderate to vigorous PA among workers had beneficial effects on obesity indicators, including percent body fat [51].
Please cite this article as: Harmouche-Karaki M et al., Combined effect of physical activity and sedentary behavior on body composition in university students, Clinical Nutrition, https://doi.org/10.1016/j.clnu.2019.06.015
M. Harmouche-Karaki et al. / Clinical Nutrition xxx (xxxx) xxx
Interestingly, there was no association between energy and macronutrients intakes with percent body fat. It has been recently outlined that even though energy intake is an important factor of weight gain, reducing it might not be enough to lose body weight [52]. Moreover, in line with the J-shaped association between energy expenditure and energy intake reported by Mayer et al, “energy intake matches energy expenditure at higher levels of energy expenditure. However, at low levels of energy expenditure, this tight association is disrupted and high levels of energy intake persist, resulting in weight gain” [53]. One limitation of the present study is the cross-sectional design, which prohibits causal inference, but enables the evaluation of associations. In the future, we plan to implement suitable interventions and re-assess PA levels and domains as well as sedentary behavior. Another limitation is that we did not study whether percent body fat correlates with disease risk, e.g. metabolic syndrome, diabetes, arterial hypertension, etc. Moreover, the relatively small sample size might have affected the power in the analyses. In addition, participants were selected from one university only, which does not permit for the generalizability of the results. The use of a questionnaire instead of a more objective measure (such as accelerometer) to assess PA is an additional limitation. This is due to recall bias and because the last seven days may not represent the habitual PA level. Hence, this was accounted for in this study by repeating the IPAQ twice, within one-month interval. Leisure PA might be more accurately reported by respondents while filling out the IPAQ, given that it has a more planned and structured nature. The absence of associations with occupational and transportationrelated PA may be because the majority of the students had low levels of non-leisure-related activities. A major strength was the assessment of domain-specific PA and its correlates using an internationally validated questionnaire; to our knowledge, this is the first study in Lebanon that used the long form of the IPAQ. Moreover, data on PA domain is lacking especially among university students in Lebanon and the Middle East. Therefore, sufficient data was provided in this study for the formulation of PA promotion strategies. Lastly, the BIA that was used to measure body composition is the most cost-effective method, with high precision and feasibility. Even though BMI was mostly used as the adiposity parameter in previous studies, it was shown to have low sensitivity to identify excess body fat [29,30]. In conclusion, we found that although university students spend long hours sitting, they can compensate for the negative effects of this behavior by practicing moderate leisure PA. This is the first study to shed the light on the effect of moderate activities vs. vigorous in a student community even with long sitting hours. It is also the first to provide a unique insight on patterns of PA and sedentary behavior in a sample of Lebanese university students. This may allow us to properly implement adequate interventions focusing on reducing the long periods spent sitting on campuses, as well as increasing PA level of moderate leisure PA and common daily activities across occupational and transportation-related PA domains. Formatting of funding sources This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors. CRediT author statement Mireille Harmouche-Karaki: Conceptualization, Methodology, Data curation, Software, Writing- Reviewing and Editing, Supervision. Maya Mahfouz: Data curation, Software, Writing- Original draft preparation. Yara Mahfouz: Software, Writing- Original draft
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preparation. Nicole Sayegh: Data curation, Software. Khalil Helou: Conceptualization, Supervision. Conflict of interest The authors declare that they have no conflict of interest. Acknowledgements The authors would like to gratefully thank Pr. Pascale Salameh (Lebanese University, Lebanon) for proofreading the manuscript. Appendix A. Supplementary data Supplementary data to this article can be found online at https://doi.org/10.1016/j.clnu.2019.06.015. References [1] Mehio Sibai A, Nasreddine L, Mokdad AH, Adra N, Tabet M, Hwalla N. Nutrition transition and cardiovascular disease risk factors in Middle East and North Africa countries: Reviewing the evidence. Ann Nutr Metab 2010;57:193e203. https://doi.org/10.1159/000321527. [2] World Health Organization. Obesity and overweight. 2018. http://www.who. int/news-room/fact-sheets/detail/obesity-and-overweight. [Accessed 11 October 2018]. [3] National research council, Institute of Medicine. U.S. Health in International perspective: shorter lives, poorer health. 2013. https://doi.org/10.17226/ 13497. [4] El-Kassas G, Ziade F. Exploration of the dietary and lifestyle behaviors and weight status and their self-perceptions among Health Sciences university students in North Lebanon. BioMed Res Int 2016. https://doi.org/10.1155/ 2016/9762396. J, Zeidan N, et al. Assessment of [5] Salameh P, Jomaa L, Issa C, Farhat G, Salame dietary intake patterns and their correlates among university students in Lebanon. Front Public Health 2014;2. https://doi.org/10.3389/fpubh.2014. 00185. [6] Golzarand M, Mirmiran P, Jessri M, Toolabi K, Mojarrad M, Azizi F. Dietary trends in the Middle East and North Africa: an ecological study (1961 to 2007). Public Health Nutr 2012;15:1835e44. https://doi.org/10.1017/S13689 80011003673. [7] Popkin BM, Adair LS, Ng SW. Global nutrition transition and the pandemic of obesity in developing countries. Nutr Rev 2012;70:3e21. https://doi.org/ 10.1111/j.1753-4887.2011.00456.x. [8] Rahim HFA, Sibai A, Khader Y, Hwalla N, Fadhil I, Alsiyabi H, et al. Noncommunicable diseases in the Arab world. Lancet 2014;383:356e67. https:// doi.org/10.1016/S0140-6736(13)62383-1. M, Parent-Massin D. Food consump[9] Nasreddine L, Hwalla N, Sibai A, Hamze tion patterns in an adult urban population in Beirut, Lebanon. Public Health Nutr 2006;9. https://doi.org/10.1079/PHN2005855. [10] Naja F, Nasreddine L, Itani L, Adra N, Sibai AM, Hwalla N. Association between dietary patterns and the risk of metabolic syndrome among Lebanese adults. Eur J Nutr 2013;52:97e105. https://doi.org/10.1007/s00394-011-0291-3. [11] Mansoubi M, Pearson N, Clemes SA, Biddle SJ, Bodicoat DH, Tolfrey K, et al. Energy expenditure during common sitting and standing tasks: examining the 1.5 MET definition of sedentary behaviour. BMC Public Health 2015;15. https://doi.org/10.1186/s12889-015-1851-x. [12] Biddle SJH, Bennie JA, Bauman AE, Chau JY, Dunstan D, Owen N, et al. Too much sitting and all-cause mortality: is there a causal link? BMC Public Health 2016;16:635. https://doi.org/10.1186/s12889-016-3307-3. [13] Bullock VE, Griffiths P, Sherar LB, Clemes SA. Sitting time and obesity in a sample of adults from Europe and the USA. Ann Hum Biol 2017;44:230e6. https://doi.org/10.1080/03014460.2016.1232749. [14] Al-Hariri M, Alkahtani S, Abdelgayed A M. Impact of life behaviour on students physical fitness at university of dammam in Saudi Arabia. Acad Res Int 2014;5:87e93. [15] Musaiger AO, Awadhalla MS, Al-Mannai M, AlSawad M, Asokan GV. Dietary habits and sedentary behaviors among health science university students in Bahrain. Int J Adolesc Med Health 2015;29. https://doi.org/10.1515/ijamh2015-0038. [16] Mabry R, Koohsari MJ, Bull F, Owen N. A systematic review of physical activity and sedentary behaviour research in the oil-producing countries of the Arabian Peninsula. BMC Public Health 2016;16. https://doi.org/10.1186/ s12889-016-3642-4. [17] Wanner M, Martin BW, Autenrieth CS, Schaffner E, Meier F, Brombach C, et al. Associations between domains of physical activity, sitting time, and different measures of overweight and obesity. Prev Med Rep 2016;3:177e84. https:// doi.org/10.1016/j.pmedr.2016.01.007.
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Please cite this article as: Harmouche-Karaki M et al., Combined effect of physical activity and sedentary behavior on body composition in university students, Clinical Nutrition, https://doi.org/10.1016/j.clnu.2019.06.015