Obesity and Control Received: May 14, 2015 Accepted: Jun 15, 2015 Open Access Published: Jun 18, 2015 http://dx.doi.org/10.14437/2378-7805-2-106 Research Peter D Hart, Obes Control Open Access 2015, 2:1 * Peter D Hart 1, 2 Body Mass Index (BMI) and Sedentary Time in Adults 1 Associate Professor, Health Promotion, Montana State University - Northern, Havre, Montana, USA 2 Research and Statistical Consultant, Health Demographics, Havre, Montana, USA Abstract Background: Physical activity is an important behaviour associated with positive health benefits as well as an increase in longevity. Time spent sedentary throughout the waking hour s leads to physical inactivity and is now being considered its own risk factor related to metabolic disorders such as obesity. Purpose: The purpose of this study was to examine the association between BMI-determined weight status and sedentary time in a representative sample of U.S. adults. A secondary purpose was to examine this relationship while controlling for physical activity. Methods: Data from the 2011-2012 National Health and Nutrition Examination Survey (NHANES) were used for the study. Three weight categories were created from BMI: normal weight (BMI < 25 kg/m 2 ), overweight (BMI 25-29.9 kg/m 2 ), and obese (BMI 30 kg/m 2 ). Sedentary time was assessed by asking respondents how much time they usually spend sitting on a typical day. Respondents were placed into one of four sedentary time Quartiles. Multinomial logistic regression was used to obtain odds ratios and 95% confidence intervals adjusted for confounding variables. Results: Adults who were the least sedentary, as compared to the most sedentary, were significantly more likely (OR = 1.80, 95% CI: 1.35 2.41) to be normal weight than obese, while controlling for confounding variables. This same relationship was significant in adults who did not meet recommended levels of physical activity (OR = 1.62, 95% CI: 1.08 2.41). This relationship was suggestive, however not significant, among adults who met recommended levels of physical activity (OR = 1.75, 95% CI: 0.98 3.14). Conclusion: Results from this study show that sedentary time and BMI are related to each other and remain so after controlling for confounding variables. Health promotion interventions that focus on decreasing sedentary time as well as increasing physical activity may have positive effects on body weight. Keywords: Obesity; Sedentary Time; Physical Activity; Population Health * Corresponding Author: Peter D Hart, Associate Professor, Health Promotion, College of Education, Arts & Sciences and Nursing, Montana State University Northern, P.O. Box 7751, Havre, Montana; 59501-7751, Tel: 406.265.3719; Fax: 406.265.4129; E-mail: peter.hart@msun.edu Introduction Obesity is a condition resulting from the interactions between genetic factors and health behaviour [1]. By definition, obesity is an abnormal accumulation (> 25 and 35% of body weight for men and women, respectively) of body fat [2]. However, population-based studies as well as clinical examinations often utilize the Body Mass Index (BMI) measure of body composition which only requires the measurement (or self-report) of one s height and weight [3]. Obesity is linked to Copyright: 2015 OCOA. This is an open-access article distributed under the terms of the Creative Commons Attribution License, Version 3.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
http://dx.doi.org/10.14437/2378-7805-2-106 Page 2 of 7 many chronic diseases such as heart disease, diabetes, hypertension, stroke, and some cancers [4]. The prevalence of obesity has almost tripled in the U.S. during the last five decades from a low of 13% in the early 1960 s to a high of 36% in 2009-10 [5]. Over one-quarter of adults are considered obese using self-reported methods, with rates as high as 36.8% among non-hispanic blacks and 30.7% among Hispanic populations [6]. Physical inactivity is a health-risk behavior independently linked to premature death, coronary heart disease, stroke, diabetes, and some cancers [7]. Sedentary time is a unit measure of sedentary behavior and can lead to physical inactivity [8]. Specifically, sedentary behavior typically does not increase energy expenditure above resting levels and includes activities such as sitting, sleeping, lying down, and screen-based activities [9]. Sedentary behavior can also be defined as activities within a metabolic equivalent (MET) range of 1.0 to 1.5 where a MET of 1.0 is equal to rest [10]. Time spent in sedentary behavior has been shown to be related to cardio-metabolic profiles in adult populations, including body weight characteristics such as waist circumference [11]. However, few studies have examined the relationship between BMI and sedentary time, while controlling for confounding variables. Therefore, the purpose of this study was to examine the association between BMI and sedentary time in a representative sample of U.S. adults. A secondary purpose was to examine this relationship while controlling for physical activity. Methods Sample Data from the 2011-12 National Health and Nutrition Examination Survey (NHANES) were used for this study. NHANES is a continuous annual survey of approximately 5,000 individuals across all ages. The survey methodology uses a multistage, stratified sampling design to represent the non-institutionalized U.S. citizen population [12]. Three components of the survey (demographic, questionnaire and examination) were used for this study. The majority of the data came from the demographic and questionnaire components of the survey. Heights and weights for BMI were retrieved from the examination component of the survey. Therefore, these values were measured by trained health care technicians. Measures BMI was measured from technician-derived measurements and computed as the ratio of weight in kilograms divided by height in meters squared (BMI = kg/m 2 ) [3]. Continuous BMI was then recoded into BMIdetermined weight classifications as follows: Normal (BMI < 25 kg/m2), Overweight (BMI 25-29.9 kg/m2), and Obese (BMI 30 kg/m2) [13]. Sedentary time was assessed (in minutes per day) by the self-reported response to the question How much time do you usually spend sitting on a typical day? Continuous sedentary time was then recoded into quartiles as follows: Q1 = 0 to 180 min/day, Q2 = 181 to 300 min/day, Q3 = 301 to 480 min/day, Q4 = 481+ min/day. These coding shows that adults placed in the fourth quartile (Q4) are the most sedentary. A recreational physical activity variable was also computed from constructed variables of minutes of moderate physical activity (MMPA) per week and minutes of vigorous physical activity (MVPA) per week. MVPA was assessed from the responses to two questions. The first question asked respondents how many days they participated in vigorousintensity sports, fitness, or recreational activities. The second question asked respondents how much time they spend doing vigorous-intensity activity on a typical day. Multiplying days with minutes yielded MVPA measured per week. The same two questions were asked regarding moderate-intensity activities to assess MMPA per week. These two physical activity variables were then used to compute minutes of moderate-to-vigorous physical activity (MMVPA) per week. Finally, the MMVPA variable was used to classify participants as either meeting current physical activity guidelines ( 150 MMVPA) or not meeting guidelines (< 150 MMVPA) [14].
http://dx.doi.org/10.14437/2378-7805-2-106 Page 3 of 7 Statistical Analysis Prevalence estimates, 95% confidence intervals (95% CI), and Rao-Scott chi-square tests of independence were used to describe BMI categories (Normal, Overweight, Obese) across demographic characteristics. The general linear model was used to form analysis of covariance models (ANCOVA) to test for adjusted mean BMI differences across sedentary time quartiles. Finally, multinomial logistic regression models were used to calculate the adjusted odds ratios (ORs) and 95% CIs of being normal weight (and overweight) as opposed to being obese for each sedentary time quartile, while adjusting for age, race, gender, and income. Multinomial logistic models were run for all adults, those meeting recommended levels of physical activity, and for those not meeting recommended levels of physical activity. All analyses were performed using the complex samples module of SPSS version 16. All p-values are reported as 2-sided and statistical significance was set at 0.05. Results A total of 5,525 adults were included in the analysis (see Table 1), of which, 34.6% (95% CI: 31.7, 37.5) were obese, 33.5% (95% CI: 30.7, 36.4) were overweight, and 31.9% (95% CI: 28.4, 35.8) were normal weight (p =.587). In males and females, 33.2% (95% CI: 30.5, 36.0) and 35.9% (95% CI: 32.3, 39.6) were obese, respectively. The prevalence of obesity generally increased as age group increased, with a low of 23.9% (95% CI: 19.1, 29.5) among the 18-24 year old group to a high of 39.5% (95% CI: 34.0, 45.4) among the 45-54 year old group. Non-Hispanic white adults had the greatest prevalence of obesity, 46.7% (95% CI: 43.2, 50.2). Those adults with monthly household income between $1250-2099 had the greatest prevalence of obesity at 38.4% (95% CI: 33.4, 43.6). Finally, prevalence of obesity increased proportionately with ratings of perceived health, with a low of 17.9% (95% CI: 14.2, 22.4) among those reporting excellent health to a high of 55.1% (95% CI: 42.8, 66.8) among those reporting poor health. Figure 1 displays age-adjusted mean BMI by sedentary time quartile. Female adults had significantly different mean BMI across sedentary time quartiles (Q1 = 27.9, Q2 = 28.4, Q3 = 28.9, Q4 = 30.2, p =.025). Adjusted mean BMI also showed a significant linear trend (p =.033) across sedentary time quartiles among females. Male adults had significantly different mean BMI across sedentary time quartiles (Q1 = 27.9, Q2 = 27.9, Q3 = 28.3, Q4 = 29.6, p =.049). The linear trend test was however not significant for male adults. Table 2 contains results from the multinomial logistic regression models, controlling for age, race, gender, and income. Overall, adults in the least sedentary quartile (Q1) were 1.80 (95% CI: 1.35, 2.41) times more likely to be normal weight (vs. obese) than those in the most sedentary quartile (Q4). Furthermore, adults in the second lowest sedentary quartile (Q2) were 1.45 (95% CI: 1.10, 1.92) times more likely to be normal weight (vs. obese) than those in the most sedentary quartile (Q4). Among adults who did not meet recommended levels of physical activity (< 150 MMVPA per week), those in the least sedentary quartile (Q1) were 1.62 (95% CI: 1.08, 2.41) times more likely to be normal weight (vs. obese) than those in the most sedentary quartile (Q4). Furthermore, less active adults in the least sedentary quartile (Q1) were 1.69 (95% CI: 1.30, 2.19) times more likely to be overweight (vs. obese) than those in the most sedentary quartile (Q4). Finally, less active adults in the second lowest sedentary quartile (Q2) were 1.77 (95% CI: 1.29, 2.43) times more likely to be overweight (vs. obese) than those in the most sedentary quartile (Q4). Sedentary time quartiles were not significantly related to body weight classification among adults who met recommended levels of physical activity ( 150 MMVPA per week). Discussion The primary purpose of this study was to examine the association between BMI and sedentary time in a representative sample of U.S. adults. This relationship was clearly established from the data showing that more sedentary adults had significantly greater BMI than adults who were less sedentary. This relationship was further qualified among female adults by the significant linear trend test. This finding implies a direct dose-response relationship between sedentary time and BMI. The same linear trend approached, but fell shy of, significance in male adults. Furthermore, the BMI and
http://dx.doi.org/10.14437/2378-7805-2-106 Page 4 of 7 sedentary time relationship was further shown by the multivariate analyses. These results clearly showed that adults who were the least sedentary were more likely to be of normal weight status compared to adults who were more sedentary. Similar results to these were found in the Australian Diabetes, Obesity and Lifestyle Study (AUSDiab) [15]. In this study of adults with known diabetes, objectively measured sedentary time was positively associated with waist circumference, after controlling for potential confounding variables. A secondary purpose of this study was to examine the BMI and sedentary time relationship while controlling for physical activity. Results from these analyses showed that only among less active adults (those accumulating < 150 MMVPA per week) were the odds of normal weight greater in the least sedentary than most sedentary. This same finding was not apparent in active (those accumulating 150 MMVPA per week) adults. These findings have the interesting implications of showing that sedentary time may be more of a factor in less active adults than in active adults. Similar findings were found in a study of older adults [16]. This study found that sedentary behavior was associated with a decreased risk of both overweight and obesity after controlling for activity levels meeting recommended guidelines. One limitation of this study is its cross-sectional properties which limits these findings to correlation-type generalizations as opposed to cause-and-effect inferences. However, the test of linear trend in this study, which also tests for dose-response effects, is a valuable attribute that aids in cross-sectional generalizations. Another limitation of this study was the use of self-reporting of sedentary time. Although a respondent s estimate of amounts of sitting time per day may be less complicated than their estimate of amounts and intensities of certain physical activities, estimating sedentary time in this study may still include un-accounted for error. This study also has much strength worth mentioning. First, data for this study are from a representative sample of all U.S. adults 18 years of age and older. The complex multi-stage sampling utilized ensures representations from all subgroups commonly left out of non-probability samples. A second strength is the use of multivariate models to assess the relationship between BMI and sedentary time. These models included commonly known covariates that otherwise could confound certain generalizations. A final strength of this study is its use of physical activity status as a control variable. Specifically, this study used the recommended amounts of physical activity ( 150 MMVPA per week) criteria to stratify its main analysis. In so doing, this study was able to generalize that sedentary time was a more influential factor among less active adults, compared to their active counterparts. Conclusion In conclusion, this study shows that more sedentary adults had significantly greater BMI than adults who were less sedentary. Results from this study also show that less active adults who were less sedentary were more likely to be normal weight than more sedentary adults. These findings suggest that interventions focusing on decreasing sedentary time as well as increasing physical activity may have beneficial effects on body weight. References 1. Chaput, J. P., Pérusse, L., Després, J. P., Tremblay, A., & Bouchard, C. (2014). Findings from the Quebec Family Study on the etiology of obesity: genetics and environmental highlights. Current obesity reports, 3(1), 54-66. 2. Wilmore, J. H. (1994). Exercise, obesity, and weight control. President's Council on Physical Fitness and Sports. 3. Flegal, K. M., Carroll, M. D., Kit, B. K., & Ogden, C. L. (2012). Prevalence of obesity and trends in the distribution of body mass index among US adults, 1999-2010. Jama, 307(5), 491-497. 4. Must, A., Spadano, J., Coakley, E. H., Field, A. E., Colditz, G., & Dietz, W. H. (1999). The disease burden associated with overweight and obesity. Jama, 282(16), 1523-1529. 5. May, A. L., Freedman, D., Sherry, B., & Blanck, H. M. (2013). Obesity: United States, 1999 2010. Morbidity and Mortality Weekly Report, 62(3), 120-128. 6. Centers for Disease Control and Prevention (CDC. (2010). Vital signs: state-specific obesity prevalence among adults-- -United States, 2009. MMWR. Morbidity and mortality weekly report, 59(30), 951.
Mean Body Mass Index (BMI) Citation: Peter D Hart (2015), Body Mass Index (BMI) and Sedentary Time in Adults. Obes Control Open Access 2:106 http://dx.doi.org/10.14437/2378-7805-2-106 Page 5 of 7 7. US Department of Health and Human Services. (2011). Healthy People 2020. Retrieved from: http://www.healthypeople.gov/2020/topicsobjectives/topic/physical-activity 8. Cart, L. R. S. M. (2012). Letter to the editor: standardized use of the terms sedentary and sedentary behaviours. Appl. Physiol. Nutr. Metab., 37, pp. 540 542. 9. Pate RR, O'Neill JR, Lobelo F (2008) The evolving definition of "sedentary". Exerc Sport Sci Rev 36:173 178. 10. Brocklebank, L. A., Falconer, C. L., Page, A. S., Perry, R., & Cooper, A. R. (2015). Accelerometer-measured sedentary time and cardiometabolic biomarkers: a systematic review. Preventive medicine. 11. Healy, G. N., Matthews, C. E., Dunstan, D. W., Winkler, E. A., & Owen, N. (2011). Sedentary time and cardiometabolic biomarkers in US adults: NHANES 2003 06. European heart journal, ehq451. 12. CDC. (2014). National Health and Nutrition Examination Survey. Survey Methods and Analytic Guidelines. Retrieved from: http://www.cdc.gov/nchs/nhanes/survey_methods.htm 13. World Health Organization (WHO). (2015). BMI classification. Retrieved from: http://apps.who.int/bmi/index.jsp?intropage=intro_3.html 14. U.S. Department of Health and Human Services (2008) Physical Activity Guidelines Advisory Committee Report p. A-7. 15. Healy, G. N., Wijndaele, K., Dunstan, D. W., Shaw, J. E., Salmon, J., Zimmet, P. Z., & Owen, N. (2008). Objectively measured sedentary time, physical activity, and metabolic risk the Australian Diabetes, Obesity and Lifestyle Study (AusDiab). Diabetes care, 31(2), 369-371. 16. Inoue, S., Sugiyama, T., Takamiya, T., Oka, K., Owen, N., & Shimomitsu, T. (2012). Television viewing time is associated with overweight/obesity among older adults, independent of meeting physical activity and health guidelines. Journal of Epidemiology, 22(1), 50-56. Figure 1. Age Adjusted Mean BMI Across Sedentary Time Quartiles. 30.5 Male (p =.049) 30 Female (p =.025)* 29.5 29 28.5 28 27.5 27 26.5 Q1 Q2 Q3 Q4 Sedentary Time (min/day) Quartile 30.5 Note. Mean BMI values are ANCOVA adjusted for age. Q1 = 0 to 180 min/day, Q2 = 181 to 300 min/day, Q3 = 301 to 480 min/day, Q4 = 481+ min/day. *Represents a separate significant linear trend (p =.033).
http://dx.doi.org/10.14437/2378-7805-2-106 Page 6 of 7 Table 1. Prevalence of BMI categories by demographic characteristic, US adults 18+ years of age 2011-12. Weight Classification Obese Overweight Normal Characteristic % 95% CI % 95% CI % 95% CI Overall 34.6 31.7, 37.5 33.5 30.7, 36.4 31.9 28.4, 35.8 Gender Male 33.2 30.5, 36.0 37.2 34.2, 40.4 29.6 26.0, 33.4 Female 35.9 32.3, 39.6 30.0 26.6, 33.6 34.2 30.2, 38.3 Age Group (yr) 18-24 23.9 19.1, 29.5 22.4 17.7, 28.0 53.6 46.2, 60.9 25-34 32.8 28.1, 37.8 31.7 28.3, 35.3 35.5 29.4, 42.1 35-44 35.6 32.6, 38.8 34.9 30.5, 39.5 29.5 24.6, 34.9 45-54 39.5 34.0, 45.4 37.6 33.2, 42.3 22.8 19.2, 26.9 55-64 39.2 31.3, 47.8 35.2 29.7, 41.0 25.6 21.7, 29.9 65+ 33.4 29.2, 37.9 36.3 33.9, 38.7 30.3 26.2, 34.8 Race/Ethnicity Hispanic 40.8 37.0, 44.7 34.9 31.8, 38.1 24.3 20.5, 28.5 Black 32.9 29.2, 36.9 34.7 31.3, 38.3 32.3 28.1, 36.9 White 46.7 43.2, 50.2 28.2 24.9, 31.7 25.2 21.7, 29.0 Asian 10.7 8.1, 14.0 27.2 23.2, 31.5 62.0 57.7, 66.2 Other 33.9 23.4, 46.3 30.4 21.6, 40.9 35.7 27.8, 44.5 Monthly Income (US $) 0-1249 35.0 31.4, 38.7 29.7 24.7, 35.2 35.4 28.7, 42.6 1250-2099 38.4 33.4, 43.6 32.4 28.5, 36.6 29.2 25.8, 32.8 2100-3749 37.2 32.6, 42.0 31.7 26.8, 37.0 31.1 25.8, 37.0 3750-5399 37.2 31.6, 43.2 34.4 28.5, 40.7 28.4 23.9, 33.4 5400-8399 36.9 29.9, 44.5 32.9 26.5, 40.0 30.2 24.6, 36.5 8400+ 23.0 17.2, 30.1 41.5 33.8, 49.7 35.5 30.6, 40.7 General Health Excellent 17.9 14.2, 22.4 33.8 27.9, 40.2 48.3 40.0, 56.7 Very Good 25.5 21.9, 29.5 38.0 33.1, 43.2 36.5 31.4, 41.8 Good 42.1 39.7, 44.5 32.9 29.3, 36.7 25.0 21.2, 29.1 Fair 51.6 44.6, 58.5 23.2 20.7, 26.0 25.2 19.4, 32.1 Poor 55.1 42.8, 66.8 24.1 14.6, 37.0 20.9 14.0, 29.9 Note. p-values are testing independence by Rao-Scott chi-square. Weight Classification: Normal (BMI < 25 kg/m 2 ), Overweight (BMI 25-29.9 kg/m 2 ), and Obese (BMI 30 kg/m 2 ).
http://dx.doi.org/10.14437/2378-7805-2-106 Page 7 of 7 Table 2. Odds of being normal and overweight when comparing less sedentary groups to the most sedentary group (Q4). Normal vs. Obese Overweight vs. Obese Sedentary Group OR 95% CI OR 95% CI Overall Q1 1.80 1.35 2.41 1.37 0.96 1.96 Q2 1.45 1.10 1.92 1.45 1.05 1.99 Q3 1.25 0.98 1.60 1.08 0.83 1.42 Q4 1.00 - - 1.00 - - 150 MMVPA Q1 1.75 0.98 3.14 0.91 0.42 1.96 Q2 1.50 0.87 2.58 1.00 0.60 1.66 Q3 1.55 0.95 2.53 0.99 0.62 1.57 Q4 1.00 - - 1.00 - - < 150 MMVPA Q1 1.62 1.08 2.41 1.69 1.30 2.19 Q2 1.32 0.92 1.88 1.77 1.29 2.43 Q3 1.06 0.75 1.49 1.17 0.84 1.63 Q4 1.00 - - 1.00 - - Note. Values in bold indicate statistical significance. Multinomial logistic regression models adjusted for age, race, income, and gender. Q1 = 0 to 180 min/day, Q2 = 181 to 300 min/day, Q3 = 301 to 480 min/day, Q4 = 481+ min/day. MMVPA represents minutes of moderate to vigorous physical activity (per week). Weight Classification: Normal (BMI < 25 kg/m 2 ), Overweight (BMI 25-30 kg/m 2 ), and Obese (BMI 30 kg/m 2 ).