PMCCPMCCPMCC

Search tips
Search criteria 

Advanced

 
Logo of medicineHomeSearchSubmit a ManuscriptMedicine
 
Medicine (Baltimore). 2015 November; 94(44): e1965.
Published online 2015 November 6. doi:  10.1097/MD.0000000000001965
PMCID: PMC4915908

Physical Activity, Study Sitting Time, Leisure Sitting Time, and Sleep Time Are Differently Associated With Obesity in Korean Adolescents

A Population-Based Study
Monitoring Editor: Vijayaprasad Gopichandran.

Abstract

Low physical activity, long leisure sitting time, and short sleep time are risk factors for obesity, but the association with study sitting time is unknown. The objective of this study was to evaluate the association between these factors and obesity.

We analyzed the association between physical activity, study sitting time, leisure sitting time, and sleep time and subject weight (underweight, healthy weight, overweight, and obese), using data from a large population-based survey, the 2013 Korea Youth Risk Behavior Web-based Survey. Data from 53,769 participants were analyzed using multinomial logistic regression analyses with complex sampling. Age, sex, region of residence, economic level, smoking, stress level, physical activity, sitting time for study, sitting time for leisure, and sleep time were adjusted as the confounders.

Low physical activity (adjusted odds ratios [AORs] = 1.03, 1.12) and long leisure sitting time (AORs = 1.15, 1.32) were positively associated with overweight and obese. Low physical activity (AOR = 1.33) and long leisure sitting time (AOR = 1.12) were also associated with underweight. Study sitting time was negatively associated with underweight (AOR = 0.86) but was unrelated to overweight (AOR = 0.97, 95% confidence interval [CI] = 0.91–1.03) and obese (AOR = 0.94, 95% CI = 0.84–1.04). Sleep time (<6 hours; ≥6 hours, <7 hours; ≥7 hours, <8 hours) was adversely associated with underweight (AORs = 0.67, 0.79, and 0.88) but positively associated with overweight (AORs = 1.19, 1.17, and 1.08) and obese (AORs = 1.33, 1.36, and 1.30) in a dose–response relationship.

In adolescents, increasing physical activity, decreasing leisure sitting time, and obtaining sufficient sleep would be beneficial in maintaining a healthy weight. However, study sitting time was not associated with overweight or obese.

INTRODUCTION

In the United States, childhood and adolescent obesity has tripled from 5% in 1971 to 1974 to 17% in 2009 to 2010.1 In Korea, childhood and adolescent obesity has increased from 5.8% in 1997 to 9.7% in 2005.2 In a modernized society, the need for physical activity decreases.3 The development of television and the personal computer has increased the likelihood of long sitting times.4,5 Moreover, chronic sleep deprivation is becoming epidemic worldwide.6 Many studies have shown that these risk factors contribute to increasing obesity in adults and adolescents.

Physical activity is associated with obesity in a dose–response relationship.7,8 Sedentary behavior, such as sitting or reclining, is associated with obesity in adolescents.3,9,10 Moreover, sedentary behavior is associated with obesity independent of physical activity.11 Sleep deprivation is another risk factor for obesity.12 The increasing prevalence of sleep deprivation coincides with an increased incidence of obesity.13 Physical activity, sedentary behavior, and sleep time are distributed in a 24-hour day. Therefore, these factors are associated with one another.14

In the present study, we evaluated 4 different types of behaviors (physically active day, study sitting time, leisure sitting time, and sleep time) and their association with adolescent weight using a large, nationwide, population-based sample. We hypothesized that lower physical activity, higher sitting time for study or leisure, and short sleep time would be associated with obesity. To the best of our knowledge, this study is the first to differentiate between types of sitting time (ie, study and leisure) and to evaluate their association with obesity.

MATERIALS AND METHODS

Study Population and Data Collection

The ethics committee of the Korean Centers for Disease Control and Prevention (KCDC) approved the survey. Written informed consent was obtained from each student's parents for use in the survey.

This cross-sectional study relied on data from the Korea Youth Risk Behavior Web-based Survey (KYRBWS). The study focused on 1 nation using statistical methods based on complex sampling and adjusted, weighted values. The KYRBWS conducted in 2013 were analyzed. These data were collected by the KCDC. Korean adolescents from the 7th through 12th grades voluntarily and anonymously completed the self-administered questionnaire. The survey response rate was 96.4%. The validity and reliability of the KYRBWS were documented by other studies.15,16 The surveys evaluated the data using stratified, 2-stage (schools and classes) clustered sampling based on data from the Education Ministry. The sample was weighted by statisticians who performed poststratification and considered nonresponse rates and extreme values.

Of a total of 72,435 participants, the following participants were excluded from the study: participants who did not complete the sleep time question or who slept fewer than 2 hours (n = 14,933 participants); participants who did not record the study sitting time or leisure sitting time (n = 2403 participants); and participants who did not record their height or weight (n = 1330 participants). A total of 53,769 participants (n = 26,819 males; n = 26,950 females), ranging in age from 12 to 18 years, were included in the study (Figure (Figure11).

FIGURE 1
A schematic illustration of participant selection in the present study. Among a total of 72,435 participants ages 12 to 18 years, individuals with incomplete survey data were excluded from the study. The data of the 53,769 participants from whom complete ...

SURVEY

Independent Variables

Days of physical activity was measured by the number of days of exercise that lasted more than 60 min, a sufficient time to increase the heart rate or respiration, in the last 7 days. Because the mean days of physical activity was 1.9, physical activity was divided into 2 days or less (low physical activity group) and more than 2 days (high physical activity group). Study sitting time and leisure sitting time in the last 7 days were also recorded. Study sitting time included sitting time while at school or a private institution, while using a computer for studying and while watching educational broadcasting. Leisure sitting time included watching TV, playing videogames, surfing the internet for nonstudy purposes, and interacting with friends. Study sitting time was measured in hours and minutes. The mean daily sitting time was calculated by adding the week-day and weekend sitting times with 5/7 and 2/7 weights, respectively. The mean study sitting time and mean leisure sitting time were 6.3 and 3.0 hours, respectively. Thus, study sitting time was divided into 6 hours or less (short study sitting group) and more than 6 hours (long study sitting group), and leisure sitting time was divided into 3 hours or less (short leisure sitting group) and more than 3 hours (long leisure sitting group). Sleep time in the last 7 days was also evaluated. The times to fall asleep and wake up were measured to within 10 min. Duration of sleep time was calculated by subtracting the falling asleep time from the wake-up time. The mean daily sleep time was calculated by adding week-day and weekend sleep times with 5/7 and 2/7 weights, respectively. Sleep time was divided into 4 groups: <6 hours; ≥6 hr, <7 hr; ≥7 hr, <8 hr; and ≥8 hr.

Dependent Variables

The obesity levels were categorized into 4 groups according to the Centers for Disease Control and Prevention guidelines regarding body mass index (kg/m2) for children and teens17: obese ≥95th percentile; overweight ≥85th percentile and <95th percentile; healthy weight ≥5th percentile and <85th percentile; and underweight <5th percentile.

Confounding Variables

Region of residence was divided into 3 groups according to administrative district: large city; small city; and rural area. Economic level was categorized into 5 levels from highest to lowest. Participants were asked how many days they had smoked in the last month, and the question was categorized into the following 4 groups: 0 days a month; 1 to 5 days a month; 6 to 19 days a month; and ≥20 days a month. The stress level of the participants was divided into 5 groups: severe, moderate, mild, a little, and no stress.

Statistical Analysis

Differences in mean age, physical exercise day, study sitting time, and leisure sitting time among underweight, healthy weight, overweight, and obese subjects were compared using linear regression analysis with complex sampling. The rate differences in sleep time, sex, region of residence, economic level, smoking, and stress level were compared using chi-squared tests with Rao–Scott correction.

Odd ratios (ORs) were calculated for days of physical exercise, study sitting time, leisure sitting time, and sleep time using the following methods: simple multinomial logistic regression with complex sampling (unadjusted); multinomial logistic regression with complex sampling adjusted for age and sex (model 1); multinomial logistic regression with complex sampling adjusted for model 1 plus region of residence, economic level, smoking, and stress level (model 2); and multinomial logistic regression with complex sampling adjusted for model 2 plus physical activity, study sitting time, leisure sitting time, and sleep time (model 3).

Two-tailed analyses were conducted, and P values <0.05 were considered to indicate statistical significance. Adjusted odd ratios (AORs) and 95% confidence intervals (CIs) were calculated. After applying the weighted values recommended by the KYRBWS, all of the results were recorded as weighted values. The results were statistically analyzed using SPSS v. 21.0 (IBM, Armonk, NY).

RESULTS

Of total 53,769 participants, there were 3169 (5.9%) underweight, 42,682 (79.4%) healthy weight, 6062 (11.3%) overweight, and 1856 (3.5%) obese subjects. The mean age, physical activity, and sitting time for study and leisure were different among the weight categories. In the obese group, the proportion of subjects with at least 8 hours of sleep was highest, and the proportion with <6 hours of sleep was lowest. The obese group showed the highest male rate. The proportion of the highest and middle-high economic level was highest in the obese group. The smoking rate was highest in the underweight group (all P < 0.001; Table Table11).

TABLE 1
General Characteristics of Participants According to Obesity

In the unadjusted model, compared with the healthy weight group, low physical activity (≤2 days) was positively associated with underweight (OR = 1.28) and negatively associated with overweight (OR = 0.86) and obese (OR = 0.72). Study sitting time (>6 hours) was negatively associated with underweight (OR = 0.88), overweight (OR = 0.82), and obese (OR = 0.61). Leisure sitting time (>3 hours) was positively associated with underweight (OR = 1.09), overweight (OR = 1.12), and obese (OR = 1.21). Obtaining <6 hours (OR = 0.63) or between 6 and 7 hours of sleep (OR = 0.79) was negatively associated with the obese group (both P < 0.001; Table Table22).

TABLE 2
Odds Ratios of Physical Activity (d), Sitting Time for Study (h), Sitting Time for Leisure (h), and Sleep Time (h) for Underweight, Overweight, and Obesity Using Simple Multinomial Logistic Regression Analysis With Complex Sampling (Reference = Healthy ...

To adjust for likely confounding factors, we calculated AORs. In model 3 (full adjusted model), low physical activity (≤2 days) was clearly associated with underweight (AOR = 1.33) and obese (AOR = 1.12). Study sitting time (>6 hours) was negatively associated with underweight (AOR = 0.86). However, study sitting time was not associated with overweight (AOR = 0.97, 95% CI = 0.91–1.03) and obese (AOR = 0.94, 95% CI = 0.84–1.04). Leisure sitting time (>3 hours) was positively associated with underweight (AOR = 1.12), overweight (AOR = 1.15), and obese (AOR = 1.32). Compared with receiving at least 8 hours of sleep, less sleep was negatively associated with underweight in a dose–response relationship (<6 hours AOR = 0.67; ≥6 hours, <7 hours AOR = 0.79; ≥7 hours, <8 hours AOR = 0.88); receiving <8 hours of sleep was also positively associated with overweight (<6 hours AOR = 1.19; ≥6 hours, <7 hours AOR = 1.17; ≥7 hours, <8 hours AOR = 1.08) and obese (<6 hours AOR = 1.33; ≥6 hours, <7 hours AOR = 1.36; ≥7 hours, <8 hours AOR = 1.30) in a dose–response relationship (Table (Table33).

TABLE 3
Adjusted Odds Ratios of Physical Activity (d), Sitting Time for Study (h), Sitting Time for Leisure (h), and Sleep Time (h) for Underweight, Overweight, and Obesity Using Multinomial Logistic Regression Analysis With Complex Sampling (Reference = Healthy ...

DISCUSSION

Consistent with previous studies,7,8 low physical activity (≤2 days) was positively associated with obese. Low physical activity was also positively associated with underweight. Other studies have supported these results, finding that underweight adolescents were 1.2 to 1.6 times more likely to be physically inactive than healthy weight subjects.18,19 In another study, the healthy weight group exhibited higher physical activity than the underweight, overweight, and obese groups.20 Low income and nutritional status could explain the low physical activity in underweight subjects.19 However, the low economic level could not be explained in this study because we adjusted the economic level of each participant, and economic level was not associated with underweight (Table (Table1).1). Nutritional status and other factors that were not considered in the present study could explain the findings, as physical activity and weight status may be affected by various confounders. Nevertheless, there were no noticeable changes in the AORs among models 1, 2, and 3 (Supplements 1 and 2; Table S3, http://links.lww.com/MD/A494), which applied different levels of confounders. Thus, unconsidered confounders could provide an explanation.

In many reports, sedentary time was associated with obesity independent of physical activity.3,9,10 Moreover, in a randomized controlled study, reducing sedentary time decreased body weight.21 Sedentary behavior can be divided into mentally active or passive sedentary time and may affect weight status differently. However, few studies have categorized types of sedentary time for this purpose. Previously, mentally passive sedentary time was associated with overweight, whereas mentally active sedentary time was not associated with overweight in the elderly.22 Therefore, we evaluated the 2 types of sedentary behavior in adolescents: study sitting time and leisure sitting time. Leisure but not study sitting time was related to overweight and obese (Table (Table3).3). This finding suggests that these 2 sitting times act differently. One explanation is that leisure sitting time such as watching television increases caloric intake with the advertisement of food,5 whereas study sitting time may not affect caloric intake. In another study among working adults, leisure sitting time displayed a stronger association with obesity than occupational sittingtime.23 Like occupational sitting time among adults, study sitting time among adolescents may have a weak relationship with obesity. The implication is that studies should focus on leisure sedentary time rather than study sedentary time to solve the adolescent obesity problem.

Study sitting time was adversely associated with underweight, whereas leisure sitting time was positively associated with underweight in this study. Increased sedentary behavior was associated with underweight in several previous reports24 but not in others.25 These inconsistent results may be a consequence of failing to categorize types of sedentary behavior. The present study demonstrated that sedentary time was associated differently with underweight, depending on how it was categorized. Leisure sedentary time was associated with underweight as well as overweight and obese, whereas study sitting time was not. These results suggest the importance of focusing on leisure sedentary time rather than study sitting time even in underweight adolescent groups. Study sitting time has no apparent harmful effect on obese, overweight, and underweight subjects.

In previous reports, sleep was associated with obesity in a U-shaped relationship. Both short sleep (<7 hours) and long sleep (more than 8 hours) increased the likelihood of obesity.26,27 Consistent with these studies, short sleep was progressively related to overweight and obese in the present study. Previous reports regarding the relationship between underweight and sleep are controversial.2830 In this study, short sleep was negatively associated with underweight, which suggests that short sleep may increase weight gain even in underweight subjects. The reference sleep time was set to 8 hours or more because the mean sleep time was 7 hours. In Korea, 77.3% of adolescents sleep <8 hours, and only 5.0% of adolescents sleep more than 9 hours. Therefore, we could not evaluate the U-shaped association between excessive sleep and obesity.

This study has several advantages over previous studies. This study simultaneously evaluated physical activity, sedentary behavior, and sleep time. These behaviors should be evaluated simultaneously because increasing 1 behavior implicates a decrease in another.14 The long sleep group (≥8 hours) showed the highest physical activity and the shortest study time (Supplement 3, http://links.lww.com/MD/A494). When adjusting sleep time, physical activity and leisure sedentary time were still related to obesity. This study distinguished sitting time between study and leisure, and these 2 sitting types were differently associated with obesity. This finding helps us to understand the relationship between sedentary behavior and obesity. This study used a large population-based sample, and statisticians weighted the sample to reflect the population.

Despite these advantages, this study has several limitations. First, this study used self-reported measurements of sedentary behavior and moderate physical activity. The self-reported measures could be influenced by recall bias. However, the objective measurement using an accelerometer also has a bias related to incomplete data and measurement error.31 In several reports,32 self-reported sedentary behavior showed a better association with obesity than the objective measurement. Second, we measured a physically active day rather than daily physical activity time; in contrast, sitting time and sleep time were assessed as daily time. Therefore, we could not calculate the summation of daily activity. Furthermore, we did not separately measure moderate and vigorous physical activity. Third, the study was subject to the same limitations that affect all cross-sectional studies, including the potential for reverse causality; therefore, our calculated ORs should be interpreted with caution.

CONCLUSION

Increasing physical activity, decreasing leisure sitting time, and increasing sleep time appear to be helpful for adolescents in maintaining a healthy weight. Additionally, these factors are associated with underweight. Study sitting time was not associated with overweight and obese.

ACKNOWLEDGMENTS

We gratefully acknowledge the participants and examiners of the Division of Chronic Disease Surveillance at the Korean Centers for Disease Control and Prevention for participating in this survey and for the dedicated work they provided.

Footnotes

Abbreviations: AORs = adjusted odd ratio, CI = confidence interval, KCDC = the Korean Centers for Disease Control and Prevention, KYRBWS = the Korea Youth Risk Behavior Web-based Survey, OR = odd ratio.

IGK and H-JL have equally contributed in this study.

The manuscript was edited for proper English language, grammar, punctuation, spelling, and overall style by highly qualified native English-speaking editors at American Journal Experts.

This work was supported, in part, by a research grant (HURF-2013-02; HURF-2015-06) funded by Hallym University Sacred Heart Hospital. We have no conflicts of interest.

Supplemental Digital Content is available for this article.

The authors have no conflicts of interest to disclose.

Supplemental digital content is available for this article. Direct URL citations appear in the printed text and are provided in the HTML and PDF versions of this article on the journal's Website (www.md-journal.com).

REFERENCES

1. May AL, Freedman D, Sherry B, et al. Obesity—United States, 1999–2010. MMWR Surveill Summ 2013; 62 Suppl 3:120–128.
2. Oh K, Jang MJ, Lee NY, et al. Prevalence and trends in obesity among Korean children and adolescents in 1997 and 2005. Korean J Pediatr 2008; 51:950–955.
3. Byun W, Dowda M, Pate RR. Associations between screen-based sedentary behavior and cardiovascular disease risk factors in Korean youth. J Korean Med Sci 2012; 27:388–394. [PMC free article] [PubMed]
4. Vandewater EA, Shim MS, Caplovitz AG. Linking obesity and activity level with children's television and video game use. J Adolesc 2004; 27:71–85. [PubMed]
5. Saunders TJ, Chaput JP, Tremblay MS. Sedentary behaviour as an emerging risk factor for cardiometabolic diseases in children and youth. Can J Diabetes 2014; 38:53–61. [PubMed]
6. Xi B, He D, Zhang M, et al. Short sleep duration predicts risk of metabolic syndrome: a systematic review and meta-analysis. Sleep Med Rev 2014; 18:293–297. [PubMed]
7. Janssen I, Leblanc AG. Systematic review of the health benefits of physical activity and fitness in school-aged children and youth. Int J Behav Nutr Phys Act 2010; 7:40. [PMC free article] [PubMed]
8. Kesaniemi YK, Danforth E, Jr, Jensen MD, et al. Dose-response issues concerning physical activity and health: an evidence-based symposium. Med Sci Sports Exerc. 2001;33:S351–S358. [PubMed]
9. Eisenmann JC, Bartee RT, Smith DT, et al. Combined influence of physical activity and television viewing on the risk of overweight in US youth. Int J Obes 2008; 32:613–618. [PubMed]
10. Kautiainen S, Koivusilta L, Lintonen T, et al. Use of information and communication technology and prevalence of overweight and obesity among adolescents. Int J Obes 2005; 29:925–933. [PubMed]
11. Staiano AE, Harrington DM, Barreira TV, et al. Sitting time and cardiometabolic risk in US adults: associations by sex, race, socioeconomic status and activity level. Br J Sports Med 2014; 48:213–219. [PMC free article] [PubMed]
12. Vgontzas AN, Lin HM, Papaliaga M, et al. Short sleep duration and obesity: the role of emotional stress and sleep disturbances. Int J Obes 2008; 32:801–809. [PubMed]
13. Iglowstein I, Jenni OG, Molinari L, et al. Sleep duration from infancy to adolescence: reference values and generational trends. Pediatrics 2003; 111:302–307. [PubMed]
14. Buman MP, Winkler EA, Kurka JM, et al. Reallocating time to sleep, sedentary behaviors, or active behaviors: associations with cardiovascular disease risk biomarkers, NHANES 2005–2006. Am J Epidemiol 2014; 179:323–334. [PubMed]
15. Bae J, Joung H, Kim J-Y, et al. Validity of self-reported height, weight, and body mass index of the Korea Youth Risk Behavior Web-based Survey questionnaire. J Prev Med Public Health 2010; 43:396–402. [PubMed]
16. Bae J, Joung H, Kim J-Y, et al. Test-retest reliability of a questionnaire for the Korea Youth Risk Behavior Web-based Survey. J Prev Med Public Health 2010; 43:403–410. [PubMed]
17. Centers for Disease Control and Prevention. About BMI for Children and Teens. 2014. Available at: http://www.cdc.gov/healthyweight/assessing/bmi/childrens_bmi/about_childrens_bmi.html Accessed November, 14, 2014.
18. Baharudin A, Zainuddin AA, Manickam MA, et al. Factors associated with physical inactivity among school-going adolescents: data from the Malaysian School-Based Nutrition Survey 2012. Asia Pac J Public Health 2014; 26:27S–35S. [PubMed]
19. Jones S, Hendricks S, Draper CE. Assessment of physical activity and sedentary behavior at preschools in Cape Town. South Africa Child Obes 2014; 10:501–510. [PubMed]
20. da Silva IC, van Hees VT, Ramires VV, et al. Physical activity levels in three Brazilian birth cohorts as assessed with raw triaxial wrist accelerometry. Int J Epidemiol 2014; 43:1959–1968. [PMC free article] [PubMed]
21. Tremblay MS, LeBlanc AG, Kho ME, et al. Systematic review of sedentary behaviour and health indicators in school-aged children and youth. Int J Behav Nutr Phys Act 2011; 8:98. [PMC free article] [PubMed]
22. Kikuchi H, Inoue S, Sugiyama T, et al. Distinct associations of different sedentary behaviors with health-related attributes among older adults. Prev Med 2014; 67:335–339. [PubMed]
23. Chau JY, van der Ploeg HP, Merom D, et al. Cross-sectional associations between occupational and leisure-time sitting, physical activity and obesity in working adults. Prev Med 2012; 54:195–200. [PubMed]
24. Seo DC, Niu J. Trends in underweight and overweight/obesity prevalence in Chinese youth, 2004–2009. Int J Behav Med 2014; 21:682–690. [PubMed]
25. Kantanista A, Osinski W. Underweight in 14 to 16 year-old girls and boys: prevalence and associations with physical activity and sedentary activities. Ann Agric Environ Med 2014; 21:114–119. [PubMed]
26. Cappuccio FP, Taggart FM, Kandala NB, et al. Meta-analysis of short sleep duration and obesity in children and adults. Sleep 2008; 31:619–626. [PubMed]
27. Knutson KL, Turek FW. The U-shaped association between sleep and health: the 2 peaks do not mean the same thing. Sleep 2006; 29:878–879. [PubMed]
28. Sivertsen B, Pallesen S, Sand L, et al. Sleep and body mass index in adolescence: results from a large population-based study of Norwegian adolescents aged 16 to 19 years. BMC Pediatr 2014; 14:204. [PMC free article] [PubMed]
29. Ohayon MM. Interactions between sleep normative data and sociocultural characteristics in the elderly. J Psychosom Res 2004; 56:479–486. [PubMed]
30. Chaput JP, Brunet M, Tremblay A. Relationship between short sleeping hours and childhood overweight/obesity: results from the “Quebec enForme” project. Int J Obes 2006; 30:1080–1085. [PubMed]
31. Westerterp KR. Assessment of physical activity: a critical appraisal. Eur J Appl Physiol 2009; 105:823–828. [PubMed]
32. Stamatakis E, Davis M, Stathi A, et al. Associations between multiple indicators of objectively-measured and self-reported sedentary behaviour and cardiometabolic risk in older adults. Prev Med 2012; 54:82–87. [PubMed]

Articles from Medicine are provided here courtesy of Wolters Kluwer Health