The study's purpose was to examine age, gender, and education as potential moderators of the associations of perceived neighborhood environment variables with accelerometer-based moderate-to-vigorous physical activity (MVPA). Data were from 7273 adults from 16 sites (11 countries) that were part of a coordinated multi-country cross-sectional study. Age moderated the associations of perceived crime safety, and perceiving no major physical barriers to walking, with MVPA: positive associations were only found in older adults. Perceived land use mix-access was linearly (positive) associated with MVPA in men, and curvilinearly in women. Perceived crime safety was related to MVPA only in women. No moderating relationships were found for education. Overall the associations of adults' perceptions of environmental attributes with MVPA were largely independent of the socio-demographic factors examined. These findings are encouraging, suggesting that efforts to optimize the perceived built and social environment may act in a socially-equitable manner to facilitate MVPA.

Auckland University of Technology Human Potential Centre Auckland New Zealand

Baker IDI Heart and Diabetes Institute Melbourne Australia

Center for Nutrition and Health Research National Institute of Public Health Cuernavaca Morelos Mexico; Stanford Prevention Research Center Stanford University School of Medicine Palo Alto CA USA; Nutrition and Health Sciences Program Graduate Division of Biological and Biomedical Sciences Emory University Atlanta GA USA

Centre for Research and Action in Public Health Canberra University Canberra ACT Australia

Centre of Physical Activity and Nutrition Research School of Exercise and Nutrition Sciences Deakin University Burwood Victoria Australia; School of Public Health The University of Hong Kong Hong Kong China

Department of Family and Preventive Medicine University of California San Diego CA USA

Department of Health Sciences Public University of Navarra Pamplona Spain

Department of Movement and Sport Sciences Ghent University Ghent Belgium

Department of Sports Science and Clinical Biomechanics University of Southern Denmark Denmark

Institute of Active Lifestyle Faculty of Physical Culture Palacky University Olomouc Czech Republic

Institute of Human Performance The University of Hong Kong Hong Kong China

Research Foundation Flanders Brussels Belgium; Department of Movement and Sport Sciences Ghent University Ghent Belgium

Research Group of Physical Activity and Quality of Life School of Health and Biosciences Pontificia Universidade Catolica do Parana Curitiba Brazil; Department of Physical Education Universidade Federal do Parana Curitiba Brazil

Universidad de los Andes Department of Public Health School of Medicine Bogota Colombia

Zobrazit více v PubMed

Arango CM, Paez DC, Reis RS, Brownson RC, Parra DC. Association between the perceived environment and physical activity among adults in Latin America: a systematic review. International Journal of Behavioral Nutrition and Physical Activity. 2013;10:122. PubMed PMC

Bauman AE, Reis RS, Sallis JF, Wells JC, Loos RF, Martin BW, for the Lancet Physical Activity Series Working Group Correlates of physical ativity: why are some people physically active and others not? Lancet. 2012;380:258–271. PubMed

Berrigan D, Troiano RP. The association between urban form and physical activity in U.S. adults. American Journal of Preventive Medicine. 2002;23(2 Suppl):74–79. PubMed

Boone-Heinonen J, Gordon-Larsen P. Life stage and sex specificity in relationships between the built and socioeconomic environments and physical activity. Journal of Epidemiology and Community Health. 2011;65:847–852. PubMed PMC

Burnham KP, Anderson DR. Model selection and multimodel inference: a practical information-theoretic approach. 2nd ed Springer; New York, NY: 2002.

Cain K. Accelerometer scoring protocol for the IPEN-adult study. University of California; San Diego, CA: 2013. Available for download at: http://www.ipenproject.org/documents/methods_docs/IPEN_Protocol.pdf.

Carlson JA, Bracy NL, Sallis JF, Millstein RA, Saelens BE, Kerr J, et al. Sociodemographic moderators of relations of neighborhood safety to physical activity. Medicine and Science in Sports and Exercise. 2014;46:1554–1563. PubMed PMC

Cerin E, Cain KL, Conway TL, Van Dyck D, Hinckson E, Schipperijn J, et al. Neighborhood environments and objectively measured physical activity in 11 countries. Medicine and Science in Sports and Exercise. 2014;46:2253–2264. PubMed PMC

Cerin E, Conway TL, Cain KL, Kerr J, De Bourdeaudhuij I, Owen N, et al. Sharing good NEWS across the world: developing comparable scores across 12 countries for the Neighborhood Environment Walkability Scale (NEWS) BMC Public Health. 2013;13:309. PubMed PMC

Cerin E, Saelens BE, Sallis JF, Frank LD. Neighborhood environment walkability scale: validity and development of a short form. Medicine and Science in Sports and Exercise. 2006;38:1682–1691. PubMed

Ding D, Gebel K. Built environment, physical activity, and obesity: what have we learned from reviewing the literature? Health & Place. 2012;18:100–105. PubMed

Forsyth A, Oakes JM, Lee B, Schmitz KH. The built environment, walking, and physical activity: Is the environment more important to some people than others? Transportation Research Part D. 2009;14:42–49.

Foster S, Giles-Corti B. The built environment, neighborhood crime and constrained physical activity: an exploration of inconsistent findings. Preventive Medicine. 2008;47:241–251. PubMed

Fox J, Weisberg S. An R companion to applied regression. 2nd ed Sage; Thousand Oaks, CA: 2011.

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. British Journal of Sports Medicine. 2010;44:924–933. PubMed

Freedson PS, Melanson E, Sirard J. Calibration of the Computer Science and Applications, Inc. accelerometer. Medicine and Science in Sports and Exercise. 1998;30:777–781. PubMed

Gordon-Larsen P, Popkin B. Understanding socioeconomic and racial/ethnic status disparities in diet, exercise, and weight: underlying contextual factors and pathways. Journal of the American Dietetic Association. 2011;111:1816–1819. PubMed PMC

Institute of Medicine . Dietary reference intakes for energy, carbohydrate, fiber, fat, fatty acids, cholesterol, protein, and amino acids (macronutrients) National Academies Press; Washington, DC: 2002. Food and Nutrition Board, Institute of Medicine. 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. Journal of Physical Activity and Health. 2013;10:581–601. PubMed

Lee IM, Djoussé L, Sesso HD, Wang L, Buring JE. Physical activity and weight gain prevention. Journal of the American Medical Association. 2010;303:1173–1179. PubMed PMC

McCormack GR, Shiell A, Doyle-Baker PK, Friedenreich CM, Sandalack BA. Subpopulation differences in the association between neighborhood urban form and neighborhood-based physical activity. Health & Place. 2014;28:109–115. PubMed

McCormack GR, Cerin E, Leslie E, Du Toit L, Owen N. Objective versus perceived distances to destinations: correspondence and predictive validity. Environment and Behavior. 2008;40:401–425.

McGinn AP, Evenson KR, Herrin AH, Huston SL, Rodriguez DA. Exploring associations between physical activity and perceived and objective measures of the built environment. Journal of Urban Health. 2007;84:162–184. PubMed PMC

Owen N, Cerin E, Leslie E, duToit L, Coffee N, Frank LD, et al. Neighborhood walkability and the walking behavior of Australian adults. American Journal of Preventive Medicine. 2007;33:387–395. PubMed

Pearce JR, Maddison R. Do enhancements to the urban built environment improve physical activity levels among socially disadvantaged populations? International Journal of Equity in Health. 2011;10:28. PubMed PMC

R Core Team . R: A language and environment for statistical computing. R Foundation for Statistical Computing; Vienna, Austria: 2013. ISBN 3-900051-07-0, URL http://www.R-project.org/

Roman CG, Chalfin A. Fear of walking outdoors: a multilevel ecologic analysis of crime and disorder. American Journal of Preventive Medicine. 2008;34:306–312. PubMed

Saelens BE, Sallis JF, Black JB, Chen D. Neigborhood-based differences in physical activity: an environment scale evaluation. American Journal of Public Health. 2003;93:1552–1558. PubMed PMC

Sallis JF. Environmental and policy research on physical activity is going global. Research in Exercise Epidemiology. 2011;13:111–117.

Sallis JF, Owen N, Fisher EB. Ecological models of health behavior. In: Glanz K, Rimer BK, Viswanath K, editors. Health Behavior and Health Education: Theory, Research and Practice. fourth ed Jossey-Bass; San Francisco: 2008. pp. 465–486.

Sallis JF, Saelens BE, Frank LD, Conway TL, Slymen DJ, Cain K, et al. Neighborhood built environment and income: examining multiple health outcomes. Social Science & Medicine. 2009;68:1285–1293. PubMed PMC

Trost SG, Owen N, Bauman AE, Sallis JF, Brown W. Correlates of adults’ participation in physical activity: review and update. Medicine and Science in Sports and Exercise. 2002;34:1996–2001. PubMed

Van Dyck D, Deforche B, Cardon G, De Bourdeaudhuij I. Neighbourhood walkability and its particular importance for adults with a preference for passive transport. Health & Place. 2009;15:496–504. PubMed

Van Holle V, Deforche B, Van Cauwenberg J, Goubert L, Maes L, Van de Weghe N, et al. Relationship between the physical environment and different domains of physical activity in European adults: a systematic review. BMC Public Health. 2012;12:807. PubMed PMC

Villanueva K, Knuiman M, Nathan A, Giles-Corti B, Christian H, Foster S, et al. The impact of neighborhood walkability on walking: does it differ across adult life stage and does neighborhood buffer size matter? Health & Place. 2008;25:43–46. 2008. PubMed

Warnes GR. Gmodels: Various R programming tools for model fitting. (R package version 2.15.3) 2012 http://CRAN.R-project.org/package=gmodels.

Welk GJ. Use of accelerometry-based activity monitors to assess physical activity. In: Welk GJ, editor. Physical activity assessments for health-related research. Human Kinetics; Champaign, IL: 2002. pp. 125–141.

Wood SN. Generalized additive models: an introduction with R. Chapman & Hall; Boca Raton, FL: 2006.

World Cancer Research Fund and American Institute for Cancer Research . Food, nutrition, physical activity and the prevention of cancer: a global perspective. American Institute for Cancer Research; Washington, DC: 2007.