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Sitting time and health outcomes among Mexican origin adults: obesity as a mediator
© de Heer et al.; licensee BioMed Central Ltd. 2012
Received: 6 January 2012
Accepted: 16 October 2012
Published: 23 October 2012
Sitting time and sedentary behaviors have been associated with adverse health outcomes including obesity, diabetes and cardiovascular disease (CVD) within non- Hispanic White populations. Similar associations have not been described within Hispanic populations despite their high CVD risk profile. This study aimed to assess the association between sitting time and obesity, self-reported diagnosed diabetes, hypertension and high cholesterol among a large cohort (N=11,268) of Mexican origin adults and to assess whether obesity mediated these associations.
Using a cross-sectional design, data collected between 2004 and 2010 were analyzed in late 2010. Regression analyses evaluated associations between self-reported daily sitting hours and disease outcomes, controlling for demographics, employment status, family disease history, and light, moderate and strenuous physical activity.
Participants were mostly female (81.1%) Mexican origin adults. Sitting time was associated with increased odds of being obese, having diabetes and having hypertension, but not high cholesterol. Adjusted odds ratios of participants who reported sitting > 4 hours/day compared to those sitting 1-2 hours/day were for obesity OR=1.55 (95% CI 1.39, 1.73), p<.001, for diabetes OR=1.29 (95% CI, 1.09, 1.52), p=.003, for hypertension OR=1.17 (95% CI, 1.01, 1.37), p=.041. Associations controlled for physical activity and employment status. Effects on hypertension and diabetes were mediated by obesity.
Sitting time was significantly associated with detrimental health outcomes, independent of physical activity. Obesity mediated these relationships for diabetes and hypertension. Future research should assess whether interventions addressing sitting time are feasible and effective among Mexican origin populations.
Most adults in the U.S. do not meet daily recommended amounts of physical activity and engage in large amounts of sedentary behaviors, such as commuting by automobile, sitting at work and watching TV at home . Several studies have documented the association between sedentary behaviors including time spent sitting and obesity, and between sitting time and cardiovascular risk factors including hypertension, high cholesterol and diabetes [2–26]. While the associations between sitting time and health outcomes have been moderately well described in non-Hispanic White populations, to date, there is very limited research describing these associations within minority populations. Hispanics represent the largest and fastest growing U.S. minority population . Investigating these associations among Hispanic populations is particularly important given their higher mean Body Mass Index (BMI) relative to national averages  and increased risk of developing diabetes  despite spending less time in sedentary activities than non-Hispanic Whites .
Recently, sitting time has been shown to be associated with chronic disease risk factors independently of engagement in physical activity and a number of other covariates including diet and smoking status [12, 21]. Thus, time spent sitting may be associated with adverse health outcomes, even when recommendations for physical activity are being met [14, 15]. In other words, “too much sitting is distinct from too little exercise” .
Hamilton and colleagues  further reported that associations of sedentary behaviors and cardiovascular or metabolic outcomes are independent of indicators of excess adiposity, suggesting that health consequences of too much sitting are not simply a result of changes in body composition. A number of studies evaluating these associations controlled for an indicator of obesity (BMI or waist circumference) [2–6, 8–12]. Several of these studies found evidence that obesity status attenuated the association between sitting time and health outcomes, [2, 3, 8, 16] although some reported the effects were small. Gaining more insight into whether obesity is an intermediate variable in the pathway between sedentary behaviors and detrimental health outcomes will be important for primary prevention efforts.
In this context, the current study aimed to evaluate the association between sitting time and obesity, and between sitting time and chronic disease outcomes including diabetes, hypertension and high cholesterol among a large cohort (N=11,268) of the largest subgroup of Hispanics: Mexican Americans. It was hypothesized that increased sitting hours per day would be associated with increased odds of being obese and having diabetes, hypertension and high cholesterol, independent of engagement in physical activity and employment status. The second aim was to assess whether obesity mediates the association between sitting time and diabetes, hypertension and high cholesterol.
Participants & recruitment
The Mano a Mano Cohort Study is an ongoing study of over 20,000 Mexican American participants iniated by The University of Texas MD Anderson Cancer Center (UTMDACC) Department of Epidemiology in 2001. The overarching aim of the study is to understand cancer related risk factors as they emerge in this population, and to use this information to facilitate development of cancer prevention strategies. Participants have been recruited through random- digit-dialing, block walking in predominantly Mexican American neighborhoods, from community centers and local health clinics, and networking through currently enrolled participants . Once a household member agrees to participate, a pair of bilingual interviewers visits the home to consent (in English or Spanish), enroll and interview up to three adults.
Procedures are in place to facilitate recruitment and continued contact with the household, which have shown to be successful. Examples include a pre-determined structure of multiple phone calls at different times of the day, which in the case of no response are followed by mailed letters, which are followed by home visits. Due to these efforts, recruitment rates are 150 households a month . The original survey, initiated in 2001, did not include items regarding employment status; these questions were added in September 2004. Due to prior research indicating the importance of employment status on health outcomes , we included only those participants who were asked the employment items. As a result, the current analyses are restricted to participants recruited between September 2004 and June 2010, which included cross-sectional data on a total of 11,268 non-pregnant Mexican American adult (age ≥ 18) cohort participants. Only one participant per household was included. Data were analyzed in the fall of 2010 and in the summer of 2012. All procedures were approved by the Institutional Review Board of The University of Texas MD Anderson Cancer Center.
All data were collected during an in-person interview by a bilingual interviewer, and were self- reported.
Demographic characteristics included age, sex, proportion of life lived in the U.S., educational attainment and employment status. Educational attainment was assessed by asking: “what is the highest level of formal education that you have?” and dichotomized into (0) technical/vocational training or less and (1) at least some college. Employment status was dichotomized into (0) is not currently employed or has never been employed and (1) is currently employed. As a proxy for acculturation, a variable was included describing the proportion of life a participant spent in the United States. This variable was calculated by dividing the answer to the question: “How many years have you lived in the United States?” by the participants’ age.
Hours of sleep was assessed by asking “On average, during the last year, how many hours in a day did you usually sleep, including naps?” with response options (1) 5 hours or less, (2) 6 hours, (3) 7 hours, (4) 8 hours, (5) 9 hours or (6) 10+ hours. Values were recoded to reflect the hours of sleeping (i.e. 6 hours of sleep for option 2).
Family disease history
Family history of diabetes, hypertension and high cholesterol in first-degree relatives was defined by asking: “Please indicate the diseases [your parent, sibling or child] has or has had that were diagnosed by a doctor and for which they are/were taking medications?” Family disease history was included in the analyses as a dichotomized predictor comparing (0) “no” or (1) “yes” for at least one first-degree blood relative with a disease history of the respective condition.
Physical activity was assessed with items adapted from the California Teachers Study, a prospective cohort of female public school teachers and administrators . Participants indicated the average number of hours per week they engaged in light, moderate, and strenuous physical activities. Participants were shown a card with example activities for each category. The activity intensity categorization was based on the Metabolic Equivalent (METs) associated with light activity (<3.0 METs, such as standing, walking at a slow pace or cooking), moderate activity (3-6 METs, such as brisk walking, lifting 10-20 lb. items, mowing or raking the lawn, cycling on a flat surface) and strenuous activity (>6 METs, such as swimming laps, running or cycling on hills) . Response scales for all three levels of physical activity included (1) Never; (2) 0.5 hours; (3) 1 hour; (4) 1.5 hours; (5) 2 hours; (6) 3 hours; (7) 4-6 hours; (8) 7-10 hours; (9) 11+ hours. Values were recoded to reflect the amount of hours the participants engaged in the behavior, using the median value of each interval (e.g. 5 hours for the option 4-6 hours). The hours per week were divided by seven to reflect hours per day for each variable and to make units comparable.
Daily sitting hours were assessed with items adapted from the California Teachers study by asking the participant to “Please estimate the average number of hours [you are] sitting each day either at work, school or home.” The item options used for the current study were (1) 1-2 hours, (2) 2-4 hours, (3) 4-6 hours, (4) 6-8 hours, (5) 8-10 hours, (6) 10-12 hours, (7) 12-14 hours, (8) 14-18 hours or (9) 18+ hours. Similar to procedures used in prior research that divided sitting time hours into categories such as low, moderate and high sitting  or quartiles , participants were categorized into three categories: those participants who reported sitting 1-2 hours/day (27.0%), sitting 2-4 hours/day (41.1%), and sitting more than 4 hours per day (32.0%).
The outcomes consisted of obesity, diabetes status, high cholesterol and hypertension. Obesity was dichotomized based on participant BMI with obesity defined as having a BMI ≥ 30 kg/m2. BMI was calculated from self-reported height and weight. More than half of the participants (n=6,206) also had their height and weight measured in addition to self-report. The correlation between reported and measured BMI among participants was high (r=0.93). Disease status of the participants was assessed by asking: “Have you ever been told by a health professional that you had diabetes/ high blood pressure/ high cholesterol” Participants reported only those conditions diagnosed by a doctor for which they currently take, or previously took medications.
T-tests and Analysis of Variance (for continuous variables) and chi-square tests (for categorical variables) were used to assess differences across sex and across time spent sitting. The sitting time variable was split into three categories: (1) 1-2 hours of sitting, (2) 2-4 hours of sitting and (3) more than 4 hours of sitting. Logistic regression analyses were conducted to assess whether sitting time (as a categorical variable) was associated with increased odds of obesity, diabetes, hypertension and high cholesterol, controlling for strenuous, moderate and light physical activity and other covariates. Covariates in the logistic regression models included age, sex, proportion of life spent in the U.S., educational attainment, employment status, hours of sleep and family history of diabetes, hypertension and high cholesterol.
Demographic characteristics, Body Mass Index, sitting time and physical activity by sex among a cohort of Mexican American adults over age 18 (N=11,268)
Age in Years (Mean, SD)
Proportion of life lived in the U.S. (%)
Currently Employed (%)
High school or less (%)
BMI (Mean, SD)
Overweight, not obese (%)
Sitting hrs/day (Mean, SD)
Sitting mins/day (Mean, SD)
Strenuous PA min/day (Mean, SD)
Moderate PA min/day (Mean, SD)
Light PA min/day (Mean, SD)
Demographic characteristics, Body Mass Index and physical activity by sitting time among a cohort of Mexican American adults (N=11,268)
more than 4 hours
Proportion of participants (%)
Age in Years (Mean, SD)
Proportion of life lived in the U.S.
Currently employed (%)
High school or less (%)
Hours of Sleep/day (Mean, SD)
BMI (Mean, SD)
Overweight, not obese (%)
Strenuous PA min/day (Mean, SD)
Moderate PA min/day (Mean, SD)
Light PA min/day (Mean, SD)
Sitting time and health outcomes
Logistic regression predicting obesity, diabetes and hypertension from sitting time and other covariates among a cohort of Mexican origin adults (Final model N=10,688) a
Obesityb OR (95% CI)
Diabetes OR (95% CI)
Hypertension OR (95% CI)
High cholesterol OR (95% CI)
Proportion of life in U.S.
Hours of sleep
Family history (yes vs no)
Strenuous hrs/day PA
Moderate hrs/ day PA
Light hrs/ day PA
1-2 hours sitting/day
2-4 hours sitting/day
> 4 hours sitting/day
Sitting time was associated with greater odds of having been diagnosed with diabetes. Participants sitting more than four hours per day had significantly higher odds (OR=1.29, 95% CI; 1.09, 1.52) of diabetes compared to participants who reported sitting 1-2 hours a day (see Table 3). Strenuous physical activity and currently being employed were associated with lower odds of having diabetes. Older age was associated with higher odds, as was having lived a larger proportion of one’s life in the U.S. Having a family history of diabetes was strongly (OR=2.59, 95% CI; 2.28, 2.96, p<.001) associated with diabetes.
Sitting time was associated with greater odds of having reported a diagnosis of hypertension. Participants who reported sitting more than four hours per day had significantly higher odds of having hypertension compared to participants sitting 1-2 hours per day (OR=1.17, 95% CI=1.01, 1.37, p=.041) (see Table 3). Again, older age, living a larger portion of one’s life in the U.S., and having a family history of hypertension were associated with increased odds of having hypertension. Engaging in more moderate physical activity and currently being employed were associated with lower odds of hypertension.
Sitting time was not associated with increased odds of having high cholesterol (see Table 3).
Exploratory subgroup analyses
To assess whether the high proportion of females in the study impacted the association between sitting time and health outcomes, a number of sex-based interactions were conducted. None of these interactions were significant, and there was no evidence that sitting time impacted women differently than men in the current study. Further, approximately 6.1% of participants were over the age of 65. Due to the increased loss of lean muscle mass at older age, effects of sitting time on health outcomes and the impact of BMI may differ among this subgroup. To assess this, analyses were conducted among the subgroup of participants 65 years and older. Among participants over the age of 65, sitting time was significantly associated with obesity (OR=1.66, 95% CI: 1.31, 2.10, p<.001), marginally associated with diabetes (OR=1.55, 95% CI: 0.97, 2.51, p=.068), but not significantly associated with hypertension, despite the similar odds ratio as the total study sample (OR=1.17, 95% CI: 0.75, 1.84, p=.432).
The aim of the current study was to assess whether daily hours of sitting time was an independent risk factor for increased chronic disease risk factors among a large cohort of Mexican origin adults. Daily hours of sitting were associated with increased odds of obesity, diabetes, and hypertension. Moreover, the effects of sitting time on diabetes and hypertension were mediated by obesity. These associations were maintained regardless of levels of light, moderate and strenuous physical activity, employment status, and other covariates.
To our knowledge, this is the first study to describe these associations among a large population of people of Mexican descent. A number of prior studies have assessed or hypothesized how time spent sitting may lead to adverse health outcomes, including biological as well as behavioral pathways (e.g. ). For example, prior research has suggested that leisure sitting time is associated with increased snacking, resulting in an increase in energy intake while energy output levels are decreased . Although it is beyond the scope of the current study to assess these processes, several characteristics specific to this study’s participants may have impacted reported sitting time and the process in which sitting time can lead to adverse health consequences. Most participants were female, were not employed, had spent more than half of their lifetime outside of the U.S., were younger on average and had a higher BMI on average compared to participants in most prior studies (e.g. [8, 24]). Further, it is important to note that the mean hours of daily sitting reported by the current study participants were substantially lower than those observed in prior studies that used objective measures of sitting time. For example, Johanssen and colleagues  found that even lean participants sat more than 10 hours per day on average. The mean hours sitting reported here more closely approximated self-reported leisure time sitting assessed in other studies , suggesting that the sitting time question used for this study may have assessed leisure time sitting rather than total time spent sitting.
Interestingly, we found that the effects of sitting time on diabetes and hypertension were mediated by obesity. Although some prior research has provided preliminary evidence that inclusion of indicators of obesity or adiposity attenuates the effect of sitting time on health outcomes [2, 3, 16], no mediation analyses had been reported to date. For example, Thorp and colleagues  reported that inclusion of an adiposity indicator (waist circumference) impacted the associations between sitting time and cardiovascular and metabolic outcomes. Among women in their study, the associations between sitting time and systolic blood pressure and HDL cholesterol disappeared, and the associations between sitting time and diastolic blood pressure and fasting plasma glucose were weakened. In addition, all associations between hours per day of TV viewing and health outcomes either weakened or disappeared with the inclusion of waist circumference .These findings and the findings of the current study are in contrast with reports that indicators of excess adiposity do not impact the association between sitting time and disease outcomes .
The current study has several limitations. First, the unique characteristics of the participants (i.e. a high proportion of females, immigrants, and the low employment rate) may limit the generalizability of the findings of the current study. Second, only BMI as an indicator of obesity was available, whereas waist circumference has been shown to be a stronger predictor of obesity- related health conditions . Further, the survey is based on self-reported sitting time, although recent research has suggested that self-reported measures of sedentary behaviors may be appropriate for cross-sectional associations with health outcomes (as in the current study) . In addition, the sitting time categories used in the current study are limited, as at the time of the study no uniform recommendations or biological mechanisms were known that could guide categorization of sitting time according to health consequences. Further, while the analyses controlled for employment status, the survey did not distinguish between occupational sitting and leisure time sitting. Also, due to the cross-sectional nature of the current study, our knowledge of temporality of exposure (time spent sitting) and disease occurrence is limited. For example, sitting time may precede disease outcomes, but may also be a consequence of disease onset and development. Finally, the survey items asked about diagnosed disease, and the percentages of undiagnosed disease were unknown in the current sample.
The findings of this study provide relevant information for future programs and studies aimed at decreasing total hours and prolonged periods of sitting among Mexican origin populations. Intervention strategies can be as simple as standing up and briefly walking around while watching television or sitting at work for prolonged periods of time. Recently, Healy and colleagues  found that breaking up long periods of sitting have been associated with beneficial metabolic outcomes, independent of physical activity and total engagement in sedentary behavior.
Although prior research has reported that indicators of excess adiposity did not attenuate the relation between sitting time and adverse health outcomes , the current study found that obesity mediated the associations of sitting time with diabetes and hypertension. Future research should evaluate in greater detail whether obesity mediates the association between sitting time and cardiovascular and metabolic disease outcomes, and whether interventions addressing sitting time are feasible and effective among Mexican origin populations.
We would like to extend our gratitude to our research participants, without whom this project would not have been possible. The Mano a Mano cohort was funded by the Comprehensive Tobacco Settlement of 1998, the Caroline W. Law Fund for Cancer Prevention, and the Dan Duncan Family Institute for Cancer Prevention and Risk Assessment. Anna V. Wilkinson is funded by the National Cancer Institute [CA126988]. This study was supported by the Intramural Research Program of the National Human Genome Research Institute at the National Institutes of Health [Z01HG200335 to LMK].
- Matthews CE, Chen KY, Freedson PS, et al: Amount of time spent in sedentary behaviors in the United States, 2003-2004. Am J Epidemiol. 2008, 167 (7): 875-881. 10.1093/aje/kwm390.View ArticlePubMedPubMed CentralGoogle Scholar
- Hu FB, Li TY, Colditz GA, et al: Television watching and other sedentary behaviors in relation to risk of obesity and type 2 diabetes mellitus in women. JAMA. 2003, 289: 1785-1791. 10.1001/jama.289.14.1785.View ArticlePubMedGoogle Scholar
- Hu FB, Leitzmann MF, Stampfer MJ, et al: Physical activity and TV watching in relation to risk for type 2 diabetes mellitus in men. Arch Intern Med. 2001, 161: 1542-1548. 10.1001/archinte.161.12.1542.View ArticlePubMedGoogle Scholar
- Gao X, Nelson ME, Tucker KL: Television viewing is associated with prevalence of metabolic syndrome in Hispanic elders. Diab Care. 2007, 30: 694-700. 10.2337/dc06-1835.View ArticleGoogle Scholar
- Healy GN, Dunstan DW, Salmon J, et al: Objectively measured light-intensity physical activity is independently associated with 2-h plasma glucose. Diab Care. 2007, 28 (1): 1384-1389.View ArticleGoogle Scholar
- Dunstan DW, Salmon J, Healy GN, et al: The AusDiab Steering Committee: Association of TV viewing with fasting and 2-h postchallenge plasma glucose levels in adults without diagnosed diabetes. Diab Care. 2007, 30: 516-522. 10.2337/dc06-1996.View ArticleGoogle Scholar
- Healy GN, Wijndaele K, Dunstan DW, et al: Objectively measured sedentary time, physical activity, and metabolic risk: the Australian Diabetes, Obesity and Lifestyle Study (AusDiab). Diab Care. 2008, 31: 369-371.View ArticleGoogle Scholar
- Thorp AA, Healy GN, Owen N, et al: Deleterious associations of sitting time and television viewing time with cardiometabolic risk biomarkers: Australian Diabetes, Obesity and Lifestyle (AusDiab) study 2004-2005. Diab Care. 2010, 33: 327-334. 10.2337/dc09-0493.View ArticleGoogle Scholar
- Jakes RW, Day NE, Khaw KT, et al: Television viewing and low participation in vigorous recreation are independently associated with obesity and markers of cardiovascular disease risk: EPIC-Norfolk population-based study. Eur J Clin Nutr. 2003, 57: 1089-1096. 10.1038/sj.ejcn.1601648.View ArticlePubMedGoogle Scholar
- Dunstan DW, Salmon J, Owen N, et al: Associations of TV viewing and physical activity with the metabolic syndrome in Australian adults. Diabetologia. 2005, 48: 2254-2261. 10.1007/s00125-005-1963-4.View ArticlePubMedGoogle Scholar
- Healy GN, Dunstan DW, Salmon J, et al: Television time and continuous metabolic risk in physically active adults. Med Sci Sports Exec. 2008, 40: 639-645. 10.1249/MSS.0b013e3181607421.View ArticleGoogle Scholar
- Dunstan DW, Barr ELM, Healy GN, et al: Television viewing time and mortality: The Australian Diabetes, Obesity and Lifestyle Study (AusDiab). Circulation. 2010, 121: 384-391. 10.1161/CIRCULATIONAHA.109.894824.View ArticlePubMedGoogle Scholar
- Dunstan DW, Salmon J, Owen N, et al: Physical activity and television viewing in relation to risk of undiagnosed abnormal glucose metabolism in adults. Diab Care. 2004, 27 (11): 2603-2609. 10.2337/diacare.27.11.2603.View ArticleGoogle Scholar
- Owen N, Healy GN, Matthews CE, et al: Too much sitting: the population health science of sedentary behavior. Exerc Sport Sci Rev. 2010, 38 (3): 105-113. 10.1097/JES.0b013e3181e373a2.View ArticlePubMedPubMed CentralGoogle Scholar
- Owen N, Bauman A, Brown W: Too much sitting: a novel and important predictor of chronic disease risk?. Br J Sports Med. 2009, 43 (2): 81-View ArticlePubMedGoogle Scholar
- Fung TT, Hu FB, Yu J, et al: Leisure-time physical activity, TV watching, and plasma biomarkers of obesity and cardiovascular disease risk. Am J Epidemiol. 2000, 152: 1171-1178. 10.1093/aje/152.12.1171.View ArticlePubMedGoogle Scholar
- van Uffelen JGZ, Wong J, Chau JY, et al: Occupational sitting and health risks: a systematic review. Am J Prev Med. 2010, 39 (4): 379-388. 10.1016/j.amepre.2010.05.024.View ArticlePubMedGoogle Scholar
- Owen N, Leslie E, Salmon J, et al: Environmental determinants of physical activity and sedentary behaviour. Exerc Sport Sci Rev. 2000, 28 (4): 165-170.Google Scholar
- Levine JA, Eberhardt NL, Jensen MD: Role of non- exercise activity thermogenesis in resistance to fat gain in humans. Science. 1999, 283: 212-214. 10.1126/science.283.5399.212.View ArticlePubMedGoogle Scholar
- Mummery WK, Schofield GM, Steele R, et al: Occupational sitting time and overweight and obesity in Australian workers. Am J Prev Med. 2005, 29 (2): 91-97. 10.1016/j.amepre.2005.04.003.View ArticlePubMedGoogle Scholar
- Hamilton MT, Hamilton DG, Zderic TW: Role of low energy expenditure and sitting in obesity, metabolic syndrome, type 2 diabetes, and cardiovascular disease. Diabetes. 2007, 56 (11): 2655-2667. 10.2337/db07-0882.View ArticlePubMedGoogle Scholar
- Katzmarzyk PT, Church TS, Craig CL, et al: Sitting time and mortality from all causes, cardiovascular disease, and cancer. Med Sci Sport Exerc. 2009, 41 (5): 998-1005. 10.1249/MSS.0b013e3181930355.View ArticleGoogle Scholar
- Brown WJ, Williams L, Ford JH, et al: Identifying the energy gap: magnitude and determinants of 5-year weight gain in midage women. Obes Res. 2005, 13: 1431-1441. 10.1038/oby.2005.173.View ArticlePubMedGoogle Scholar
- Proper KI, Cerin E, Brown WJ, et al: Sitting time and socio-economic differences in overweight and obesity. Int J Obesity. 2007, 31 (1): 169-176. 10.1038/sj.ijo.0803357.View ArticleGoogle Scholar
- Hamilton MT, Healy GN, Dunstan DW, et al: Too little exercise and too much sitting: inactivity physiology and the need for new recommendations on sedentary behavior. Curr Cardiovasc Risk Rep. 2008, 2: 292-298. 10.1007/s12170-008-0054-8.View ArticlePubMedPubMed CentralGoogle Scholar
- Stamatakis E, Hamer M, Dunstan DW: Screen-Based Entertainment Time, All-Cause Mortality, and Cardiovascular Events. J Am Coll of Cardiol. 2011, 57: 292-299. 10.1016/j.jacc.2010.05.065.View ArticleGoogle Scholar
- United States Bureau of the Census: The Hispanic Population. 2010, Available at: http://www.census.gov/prod/cen2010/briefs/c2010br-04.pdf,Google Scholar
- Centers for Disease Control and Prevention (CDC): Differences in Prevalence of Obesity Among Black, White, and Hispanic Adults - United States, 2006- 2008. MMWR. 2009, 58 (27): 740-744.Google Scholar
- Centers for Disease Control and Prevention: National diabetes fact sheet: national estimates and general information on diabetes and pre-diabetes in the United States, 2011. 2011, Atlanta: Department of Health and Human Services, Centers for Disease Control and PreventionGoogle Scholar
- Wilkinson AV, Spitz MR, Strom SS, et al: Effects of nativity, age at migration, and acculturation on smoking among adult Houston residents of Mexican descent. Am J Public Health. 2005, 95: 1043-1049. 10.2105/AJPH.2004.055319.View ArticlePubMedPubMed CentralGoogle Scholar
- The University of Texas MD Anderson Cancer Center: Tobacco Settlement Proceeds Program. 2009, Available from: http://www.mdanderson.org/about-us/university-of-texas-system-reports/files/tobacco-planned-expenditures-fy-2009.pdf,Google Scholar
- Rogot E, Sorlie PD, Johnson NJ: Life expectancy by employment status, income, and education in the National Longitudinal Mortality Study. Public Health Rep. 1992, 107 (4): 457-461.PubMedPubMed CentralGoogle Scholar
- Mai PL, Sullivan-Halley J, Ursin G, et al: Physical activity and colon cancer risk among women in the California Teachers Study. Cancer Epidemiol Biomarkers Prev. 2007, 16: 517-525. 10.1158/1055-9965.EPI-06-0747.View ArticlePubMedGoogle Scholar
- Ainsworth B, Haskell WL, White MC, et al: Compendium of physical activities: an update of activity codes and MET intensities. Med Sci Sports Exerc. 2000, 32 (suppl): S498-S504. 10.1097/00005768-200009001-00009.View ArticlePubMedGoogle Scholar
- Herr NR: Mediation with dichotomous outcomes. 2011, Retrieved March 15th, 2011 from: http://nrherr.bol.ucla.edu/Mediation/logmed.html,Google Scholar
- Sobel ME: Asymptotic confidence intervals for indirect effects in structural equation models. Sociological Methodology. Edited by: Leinhardt S. 1982, San Fransisco: Jossey-Bass, 290-312.Google Scholar
- Baron RM, Kenny DA: The moderator–mediator variable distinction in social psychological research: Conceptual, strategic, and statistical considerations. J Pers Soc Psych. 1986, 51: 1173-1182.View ArticleGoogle Scholar
- Zderic TW, Hamilton MT: Physical inactivity amplifies the sensitivity of skeletal muscle to the lipid-induced downregulation of lipoprotein lipase activity. J Appl Physiol. 2006, 100: 249-257. 10.1152/japplphysiol.00925.2005.View ArticlePubMedGoogle Scholar
- Bowman SA: Television-viewing characteristics of adults: correlations to eating practices and overweight and health status. Prev Chr Dis. 2006, 3 (2): 1-11.Google Scholar
- Johannsen DL, Welk G, Sharp RL, et al: Differences in daily energy expenditure in lean and obese women: the role of posture allocation. Obesity. 2008, 16: 34-39. 10.1038/oby.2007.15.View ArticlePubMedGoogle Scholar
- Healy GN, Clark BK, Winkler EAH, et al: measurement of adults sedentary time in population-based studies. Am J Prev Med. 2011, 41 (2): 216-227. 10.1016/j.amepre.2011.05.005.View ArticlePubMedPubMed CentralGoogle Scholar
- Janssen I, Katzmarzyk P, Ross R: Waist circumference and not body mass index explains obesity-related health risk. Am J Clin Nutr. 2004, 79: 379-84.PubMedGoogle Scholar
- Healy GN, Dunstan DW, Salmon J, et al: Breaks in sedentary time: beneficial associations with metabolic risk. Diab Care. 2008, 31: 661-666. 10.2337/dc07-2046.View ArticleGoogle Scholar
- The pre-publication history for this paper can be accessed here:http://www.biomedcentral.com/1471-2458/12/896/prepub
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