International study of objectively measured physical activity and sedentary time with body mass index and obesity: IPEN adult study
Jazyk angličtina Země Anglie, Velká Británie Médium print-electronic
Typ dokumentu časopisecké články, multicentrická studie, pozorovací studie, Research Support, N.I.H., Extramural, práce podpořená grantem
Grantová podpora
R01 CA127296
NCI NIH HHS - United States
R01 CA127296.
NCI NIH HHS - United States
PubMed
24984753
PubMed Central
PMC4282619
DOI
10.1038/ijo.2014.115
PII: ijo2014115
Knihovny.cz E-zdroje
- MeSH
- akcelerometrie statistika a číselné údaje MeSH
- dospělí MeSH
- index tělesné hmotnosti MeSH
- lékařská praxe založená na důkazech statistika a číselné údaje MeSH
- lidé středního věku MeSH
- lidé MeSH
- obezita epidemiologie etiologie MeSH
- podpora zdraví * MeSH
- pohybová aktivita * MeSH
- průřezové studie MeSH
- průzkumy a dotazníky MeSH
- sedavý životní styl * MeSH
- Check Tag
- dospělí MeSH
- lidé středního věku MeSH
- lidé MeSH
- mužské pohlaví MeSH
- ženské pohlaví MeSH
- Publikační typ
- časopisecké články MeSH
- multicentrická studie MeSH
- pozorovací studie MeSH
- práce podpořená grantem MeSH
- Research Support, N.I.H., Extramural MeSH
BACKGROUND: Physical activity (PA) has been consistently implicated in the etiology of obesity, whereas recent evidence on the importance of sedentary time remains inconsistent. Understanding of dose-response associations of PA and sedentary time with overweight and obesity in adults can be improved with large-scale studies using objective measures of PA and sedentary time. The purpose of this study was to examine the strength, direction and shape of dose-response associations of accelerometer-based PA and sedentary time with body mass index (BMI) and weight status in 10 countries, and the moderating effects of study site and gender. METHODS: Data from the International Physical activity and the Environment Network (IPEN) Adult study were used. IPEN Adult is an observational multi-country cross-sectional study, and 12 sites in 10 countries are included. Participants wore an accelerometer for seven consecutive days, completed a socio-demographic questionnaire and reported height and weight. In total, 5712 adults (18-65 years) were included in the analyses. Generalized additive mixed models, conducted in R, were used to estimate the strength and shape of the associations. RESULTS: A curvilinear relationship of accelerometer-based moderate-to-vigorous PA and total counts per minute with BMI and the probability of being overweight/obese was identified. The associations were negative, but weakened at higher levels of moderate-to-vigorous PA (>50 min per day) and higher counts per minute. No associations between sedentary time and weight outcomes were found. Complex site- and gender-specific findings were revealed for BMI, but not for weight status. CONCLUSIONS: On the basis of these results, the current Institute of Medicine recommendation of 60 min per day of moderate-to-vigorous PA to prevent weight gain in normal-weight adults was supported. No relationship between sedentary time and the weight outcomes was present, calling for further examination. If moderator findings are confirmed, the relationship between PA and BMI may be country- and gender-dependent, which could have important implications for country-specific health guidelines.
Centre for Research and Action in Public Health University of Canberra ACT Australia
Department of Family and Preventive Medicine University of California San Diego La Jolla CA USA
Department of Health Sciences Public University of Navarra Pamplona Spain
Department of Public Health School of Medicine Universidad de los Andes Carrera Bogotá Colombia
Faculty of Health and Environmental Sciences Auckland University of Technology Auckland New Zealand
Graduate Division of Biological and Biomedical Sciences Emory University Atlanta GA USA
Institute of Human Performance Hong Kong University Hong Kong
Zobrazit více v PubMed
Finucane MM, Stevens GA, Cowan MJ, Goodarz D, Lin JK, Paciorek CJ, et al. on behalf of the Global Burden of Metabolic Risk Factors of Chronic Diseases Collaborating Group. National, regional, and global trends in body-mass index since 1980: systematic analysis of health examination surveys and epidemiological studies with 960 country-years and 9.1 million participants. Lancet. 2011;377:557–567. PubMed PMC
Wyatt SB, Winters KP, Dubbert PM. Overweight and obesity: prevalence, consequences, and causes of a growing public health problem. Am J Med Sci. 2006;331:166–174. PubMed
World Health Organization. Global recommendations on physical activity for health. Geneva, Switzerland: WHO press; 2010. PubMed
Hamilton MT, Healy GN, Dunstan DW, Zderic TW, Owen N. Too little exercise and too much sitting: inactivity physiology and the need for new recommendations on sedentary behavior. Curr Cardiov Risk Rep. 2008;2:292–298. PubMed PMC
Hu F, Li T, Colditz G, Willett W, Manson J. Television watching and other sedentary behaviors in relation to risk of obesity and type 2 diabetes mellitus in women. JAMA. 2003;289:1758–1791. PubMed
Proper KI, Singh AS, van Mechelen W, Chinapaw MJM. Sedentary behaviors and health outcomes among adults: a systematic review of prospective studies. Am J Prev Med. 2011;40:174–182. PubMed
Thorp AA, Owen N, Neuhaus M, Dunstan DW. Sedentary behaviors and subsequent health outcomes in adults: a systematic review of longitudinal studies, 1996–2011. Am J Prev Med. 2011;41:207–215. PubMed
U.S. Department of Health and Human Services. Physical activity guidelines advisory committee report. Washington DC: ODPHP publication no U0049; 2008. Available from http://www.health.gov/paguidelines/Report/pdf/CommitteeReport.pdf.
Hallal PC, Andersen LB, Bull FC, Guthold R, Haskell W, Ekelund U, et al. on behalf of the Lancet Physical Activity Series Working Group Global physical activity levels: surveillance progress, pitfalls, and prospects. Lancet. 2012;380:247–257. PubMed
Bauman A, Bull F, Chey T, Craig CL, Ainsworth BE, Sallis JF, et al. The International Prevalence Study on physical activity: results from 20 countries. Int J Behav Nutr Phys Act. 2009;6:21. PubMed PMC
Craig CL, Marshall AL, Sjöström M, Bauman AE, Booth ML, Ainsworth BE, et al. International Physical Activity Questionnaire: 12-country reliability and validity. Med Sci Sports Exerc. 2003;35:1381–1395. PubMed
Boon RM, Hamlin MJ, Steel GD, Ross JJ. Validation of the New Zealand Physical Activity Questionnaire (NZPAQ-LF) and the International Physical Activity Questionnaire (IPAQ-LF) with accelerometry. Br J Sports Med. 2010;44:741–746. PubMed
Hagströmer M, Oja P, Sjöström M. The International Physical Activity Questionnaire (IPAQ): a study of concurrent and construct validity. Public Health Nutr. 2006;9:755–762. PubMed
Kerr J, Sallis JF, Owen N, De Bourdeaudhuij I, Cerin E, Sugiyama T, et al. Advancing science and policy through a coordinated international study of physical activity and built environments: IPEN Adult methods. J Phys Act Health. 2013;10:581–601. PubMed
Rhodes RE, Mark RS, Temmel CP. Adult sedentary behavior: a systematic review. Am J Prev Med. 2012;42:e3–e28. PubMed
Frank LD, Sallis JF, Saelens BE, Leary L, Cain K, Conway TL, et al. The development of a walkability index: application to the Neighborhood Quality of Life Study. Br J Sports Med. 2010;44:924–933. PubMed
Cerin E, Leslie E, Owen N, Bauman A. An Australian version of the neighborhood environment walkability scale: validity evidence. Meas Phys Educ Exerc Sci. 2008;12:31–51.
Cain K. Accelerometer scoring protocol for the IPEN-adult study. San Diego, CA: University of California; 2013. Available for download at: http://www.ipenproject.org/documents/methods_docs/IPEN_Protocol.pdf.
McAdams MA, Van Dam RM, Hu FB. Comparison of self-reported and measured BMI as correlates of disease markers in US adults. Obesity. 2007;15:188–196. PubMed
Freedson PS, Miller K. Objective monitoring of physical activity using motion sensors and heart rate. Res Q Exerc Sport. 2002;71:S21–S29. PubMed
Freedson PS, Lyden K, Kozey-Keadle S, Staudenmayer J. Evaluation of artificial neural network algorithms for predicting METs and activity type from accelerometer data: Validation on an independent sample. J Appl Physiol. 2011;111:1804–1812. PubMed PMC
Welk GJ. Use of accelerometry-based activity monitors to assess physical activity. In: Welk GJ, editor. Physical activity assessments for health-related research. Champaign, IL: Human Kinetics; 2002. pp. 125–141.
Lee KY, Macfarlane DJ, Cerin E. Comparison of three models of actigraph accelerometers during free living and controlled laboratory conditions. Eur J Sport Sci. 2013;13:332–339. PubMed
John D, Tyo B, Bassett DR. Comparison of four Actigraph accelerometers during walking and running. Med Sci Sports Exerc. 2010;42:368–374. PubMed PMC
Vanhelst J, Mikulovic J, Bui-Xuan G, Dieu O, Blondeau T, Fardy P, et al. Comparison of two ActiGraph accelerometer generations in the assessment of physical activity in free living conditions. BMC Res Notes. 2012;5:187. PubMed PMC
Tanha T, Tornberg A, Dencker M, Wollmer P. Accelerometer measured daily physical activity and sedentary pursuits – comparison between two models of the Actigraph and the importance of data reduction. BMC Res Notes. 2013;6:439. PubMed PMC
Freedson PS, Melanson E, Sirard J. Calibration of the Computer Science and Applications, Inc. accelerometer. Med Sci Sports Exerc. 1998;30:777–781. PubMed
Matthews CE, Chen KY, Freedson PS, Buchowski MS, Beech BM, Pate RR, et al. Amount of time spent in sedentary behaviors in the United States, 2003–2004. Am J Epidemiol. 2008;167:875–881. PubMed PMC
Wood SN. Generalized additive models: an introduction with R. Boca Raton, FL: Chapman & Hall; 2006.
Burnham KP, Anderson DR. Model selection and multimodel inference: a practical information-theoretic approach. 2nd edn. New York, NY: Springer; 2002.
Harrell FE. Regression modeling strategies with applications to linear models, logistic regression, and survival analyses. New York, NY: Springer – Verlag; 2001.
Fox J, Weisberg S. An R companion to applied regression. 2nd edn. Thousand Oaks CA: Sage; 2011.
Warnes GR. gmodels: Various R programming tools for model fitting. R package version 2.15.3. 2012 http://CRAN.R-project.org/package=gmodels.
Carstensen B, Plummer M, Laara E, Hills M. Epi: a package for statistical analysis in epidemiology. R package version 1.1.44. 2013 URL http://CRAN.R-project.org/package=Epi.
Pate RR, Pratt M, Blair SN, Haskell WL, Macera CA, Bouchard C, et al. Physical activity and public health: a recommendation from the Centers for Disease Control and Prevention and the American College of Sports Medicine. JAMA. 1995;273:402–407. PubMed
Haskell WL, Min Lee I, Pate RR, Powell KE, Blaire SN, Franklin BA, et al. Physical activity and public health: updated recommendations for adults from the American College of Sports Medicine and the American Heart Association. Med Sci Sports Exerc. 2007;39:1423–1434. PubMed
Sattelmair J, Pertman J, Ding EL, Kohl HW, Haskell W, Min Lee I. Dose response between physical activity and risk of coronary heart disease: a meta-analysis. Circulation. 2011;124:789–795. PubMed PMC
Seo D, Li C. Leisure-time physical activity dose-response effects on obesity among US adults: results from the 1999–2006 National Health and Nutrition Examination Survey. J Epidemiol Community Health. 2010;64:426–431. PubMed
Institute of Medicine. Dietary reference intakes for energy, carbohydrate, fiber, fat, fatty acids, cholesterol, protein, and amino acids (macronutrients) Washington, DC: National Academies Press; 2002. Food and Nutrition Board, Institute of Medicine. PubMed
Min Lee I, Djoussé L, Sesso HD, Wang L, Buring JE. Physical activity and weight gain prevention. JAMA. 2010;303:1173–1179. PubMed PMC
Haskell WL. Health consequences of physical activity: understanding and challenges regarding dose-response. Med Sci Sports Exerc. 1994;26:649–660. PubMed
Banks E, Lim L, Seubsman S, Bain C, Sleigh A. Relationship of obesity to physical activity, domestic activities, and sedentary behaviours: cross-sectional findings from a national cohort of over 70,000 Thai adults. BMC Public Health. 2011;11:762. PubMed PMC
Meyer AM, Evenson KR, Couper DJ, Stevens J, Pereria MA, Heiss G. Television, physical activity, diet, and body weight status: the ARIC cohort. Int J Behav Nutr Phys Act. 2008;5:68. PubMed PMC
Harnack LJ, Schmitz KH. The role of nutrition and physical activity in the obesity epidemic. In: Crawford D, Jeffery RW, Ball K, Brug J, editors. Obesity epidemiology: from aetiology to public health. New York, NY: Oxford University Press Inc; 2010. pp. 91–104.
Carr LJ, Mahar MT. Accuracy of intensity and inclinometer output of three activity monitors for identification of sedentary behavior and light-intensity activity. J Obes. 2012;2012:460271. PubMed PMC
Kozey-Keadle S, Libertine A, Lyden K, Staudenmayer J, Freedson PS. Validation of wearable monitors for assessing sedentary behavior. Med Sci Sports Exerc. 2011;43:1561–1567. PubMed
Buman MP, Hekler EB, Haskell WL, Pruitt L, Conway TL, Caink K, et al. Objective light-intensity physical activity associations with rated health in older adults. Am J Epidemiol. 2010;172:1155–1165. PubMed PMC
Carson V, Ridgers ND, Howard BJ, Winkler EA, Healy GN, Owen N, et al. Light-intensity physical activity and cardiometabolic biomarkers in US adolescents. PLoS One. 2013;8:e71417. PubMed PMC
Healy GN, Dunstan DW, Salmon J, Cerin E, Shaw JE, Zimmet PZ, et al. Breaks in sedentary time: Beneficial associations with metabolic risk. Diabetes Care. 2008;31:661–666. PubMed
Henson J, Yates T, Biddle SJH, Edwardson CL, Khunti K, Wilmot EG, et al. Associations of objectively measured sedentary behaviour and physical activity with markers of cardiometabolic health. Diabetologica. 2013;56:1012–1020. PubMed
Is Pedometer-Determined Physical Activity Decreasing in Czech Adults? Findings from 2008 to 2013