Do associations between objectively-assessed physical activity and neighbourhood environment attributes vary by time of the day and day of the week? IPEN adult study
Language English Country England, Great Britain Media electronic
Document type Journal Article
Grant support
R01 CA127296
NCI NIH HHS - United States
75376
Medical Research Council - United Kingdom
PubMed
28320422
PubMed Central
PMC5359924
DOI
10.1186/s12966-017-0493-z
PII: 10.1186/s12966-017-0493-z
Knihovny.cz E-resources
- Keywords
- Accelerometry, Built environment, Exercise, Geographic Information Systems, International health,
- MeSH
- Accelerometry statistics & numerical data MeSH
- Time MeSH
- Residence Characteristics statistics & numerical data MeSH
- Exercise physiology MeSH
- Adult MeSH
- Middle Aged MeSH
- Humans MeSH
- Adolescent MeSH
- Young Adult MeSH
- Periodicity * MeSH
- Cross-Sectional Studies MeSH
- Reproducibility of Results MeSH
- Sex Distribution MeSH
- Aged MeSH
- Cities statistics & numerical data MeSH
- Employment statistics & numerical data MeSH
- Environment Design statistics & numerical data MeSH
- Check Tag
- Adult MeSH
- Middle Aged MeSH
- Humans MeSH
- Adolescent MeSH
- Young Adult MeSH
- Male MeSH
- Aged MeSH
- Female MeSH
- Publication type
- Journal Article MeSH
- Geographicals
- Cities statistics & numerical data MeSH
BACKGROUND: To more accurately quantify the potential impact of the neighbourhood environment on adults' physical activity (PA), it is important to compare environment-PA associations between periods of the day or week when adults are more versus less likely to be in their neighbourhood and utilise its PA resources. We examined whether, among adults from 10 countries, associations between objectively-assessed neighbourhood environment attributes and moderate-to-vigorous physical activity (MVPA) varied by time of the day and day of the week. The secondary aim was to examine whether such associations varied by employment status, gender and city. METHODS: This cross-sectional study included 6,712 adults from 14 cities across 10 countries with ≥1 day of valid accelerometer-assessed MVPA and complete information on socio-demographic and objectively-assessed environmental characteristics within 0.5 and 1 km street-network buffers around the home. Accelerometer measures (MVPA min/h) were created for six time periods from early morning until late evening/night, for weekdays and weekend days separately. Associations were estimated using generalized additive mixed models. RESULTS: Time of the day, day of week, gender and employment status were significant moderators of environment-MVPA associations. Land use mix was positively associated with MVPA in women who were employed and in men irrespective of their employment status. The positive associations between MVPA and net residential density, intersection density and land use mix were stronger in the mornings of weekdays and the afternoon/evening periods of both weekdays and weekend days. Associations between number of parks and MVPA were stronger in the mornings and afternoon/evenings irrespective of day of the week. Public transport density showed consistent positive associations with MVPA during weekends, while stronger effects on weekdays were observed in the morning and early evenings. CONCLUSIONS: This study suggests that space and time constraints in adults' daily activities are important factors that determine the impact of neighbourhood attributes on PA. Consideration of time-specific associations is important to better characterise the magnitude of the effects of the neighbourhood environment on PA. Future research will need to examine the contribution of built environment characteristics of areas surrounding other types of daily life centres (e.g., workplaces) to explaining adults' PA at specific times of the day.
Baker IDI Heart and Diabetes Institute Melbourne Australia
Department of Family Medicine and Public Health University of California San Diego USA
Department of Sports Science and Clinical Biomechanics University of Southern Denmark Odense Denmark
Faculty of Health and Environmental Sciences AUT University Auckland New Zealand
Ghent University Ghent Belgium
Graduate Program on Physical Education Federal University of Parana Curitiba Brazil
Institute of Active Lifestyle Faculty of Physical Culture Palacký University Olomouc Czech Republic
Prevention Research Center Brown School Washington University in St Louis St Louis USA
Public University of Navarra Navarra Pamplona Spain
Research Foundation Flanders Brussels Belgium
School of Medicine Universidad de los Andes Bogotá Colombia
School of Public Health The University of Hong Kong Hong Kong China
See more in PubMed
Sallis JF, Cervero RB, Ascher W, Henderson KA, Kraft MK, Kerr J. An ecological approach to creating active living communities. Annu Rev Public Health. 2006;27:297–322. doi: 10.1146/annurev.publhealth.27.021405.102100. PubMed DOI
Sallis JF, Owen N. In: Health behavior: Theory, research and practice. 5. Glanz K, Rimer B, Viswanath K, editors. San Francisco: Jossey-Bass/Pfeiffer; 2015. pp. 43–64.
Neighbourhood. (n.d.) In: Cambridge advanced learner’s dictionary & thesaurus. http://dictionary.cambridge.org/dictionary/english/neighbourhood. Accessed 3 Mar 2017.
Chaix B, Kestens Y, Perchoux C, Karusisi N, Merlo J, Labadi K. An interactive mapping tool to assess individual mobility patterns in neighborhood studies. Am J Prev Med. 2012;43(4):440–50. doi: 10.1016/j.amepre.2012.06.026. PubMed DOI
Bauman AE, Reis RS, Sallis JF, Wells JC, Loos RJF, Martin BW. Correlates of physical activity: why are some people physically active and others not? Lancet. 2012;380(9838):258–71. doi: 10.1016/S0140-6736(12)60735-1. PubMed DOI
Hallal PC, Andersen LB, Bull FC, Guthold R, Haskell W, Ekelund U. Global physical activity levels: surveillance progress, pitfalls, and prospects. Lancet. 2012;380(9838):247–57. doi: 10.1016/S0140-6736(12)60646-1. PubMed DOI
Kohl HW, Craig CL, Lambert EV, Inoue S, Alkandari JR, Leetongin G, et al. The pandemic of physical inactivity: global action for public health. Lancet. 2012;380(9838):294–305. doi: 10.1016/S0140-6736(12)60898-8. PubMed DOI
Sallis JF, Bull F, Guthold R, Heath GW, Inoue S, Kelly P, et al. Progress in physical activity over the Olympic quadrennium. Lancet. 2016;388(10051):1325–36. doi: 10.1016/S0140-6736(16)30581-5. PubMed DOI
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(4):581–601. doi: 10.1123/jpah.10.4.581. PubMed DOI
Sallis JF, Cerin E, Conway TL, Adams MA, Frank LD, Pratt M, et al. Physical activity in relation to urban environments in 14 cities worldwide: a cross-sectional study. Lancet. 2016;387(10034):2207–17. doi: 10.1016/S0140-6736(15)01284-2. PubMed DOI 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. Med Sci Sports Exerc. 2014;46(12):2253–64. doi: 10.1249/MSS.0000000000000367. PubMed DOI PMC
Cerin E, Cain KL, Oyeyemi AL, Owen N, Conway TL, Cochrane T, et al. Correlates of agreement between accelerometry and self-reported physical activity. Med Sci Sports Exerc. 2016;48(6):1075–84. doi: 10.1249/MSS.0000000000000870. PubMed DOI PMC
Owen N, Cerin E, Leslie E, Du Toit L, Coffee N, Frank LD, et al. Neighborhood walkability and the walking behavior of Australian adults. Am J Prev Med. 2007;33(5):387–95. doi: 10.1016/j.amepre.2007.07.025. PubMed DOI
Christiansen LB, Cerin E, Badland H, Kerr J, Davey R, Troelsen J, et al. International comparisons of the associations between objective measures of the built environment and transport-related walking and cycling: IPEN adult study. J Transp Health. 2016;3:467–78. doi: 10.1016/j.jth.2016.02.010. PubMed DOI PMC
Kerr J, Emond J, Badland H, Reis R, Sarmiento O, Carlson J, et al. Perceived neighborhood environmental attributes associated with walking and cycling for transport among adult residents of 17 cities in 12 countries: The IPEN study. Environ Health Perspect. 2016;124(3):290–8. PubMed PMC
Arvidsson D, Eriksson U, Lönn SL, Sundquist K. Neighborhood walkability, income, and hour-by-hour physical activity patterns. Med Sci Sports Exerc. 2013;45(4):698–705. doi: 10.1249/MSS.0b013e31827a1d05. PubMed DOI
Kwan MP. The uncertain geographic context problem. Ann Assoc Am Geogr. 2012;102:958–68. doi: 10.1080/00045608.2012.687349. DOI
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(13):924–33. doi: 10.1136/bjsm.2009.058701. PubMed DOI
Adams M, Frank L, Schipperijn J, Smith G, Chapman J, Christiansen L, et al. International variation in neighborhood walkability, transit, and recreation environments using geographic information systems: the IPEN adult study. Int J Health Geogr. 2014;13:43. doi: 10.1186/1476-072X-13-43. PubMed DOI PMC
Freedson PS, Melanson EL, Sirard J. Calibration of the Computer Science and Applications, Inc. accelerometer. Med Sci Sports Exerc. 1998;30(5):777–81. doi: 10.1097/00005768-199805000-00021. PubMed DOI
Cain K. Accelerometer Scoring Protocol for the IPEN-Adult Study. University California San Diego, CA. San Diego, CA; 2013. http://www.ipenproject.org/documents/methods_docs/IPEN_Protocol.pdf. Accessed 13 Dec 2016.
Wood SN. Generalized additive models: An introduction with R. Boca Raton: Chapman and Hall; 2006.
Burnham KP, Anderson DR. Model selection and multimodel inference: A practical information-theoretic approach. 2. New York: Springer; 2002.
R Core Development Team. R: a language and environment for statistical computing, 3.2.1. Available on the internet at: http://www.R-Project.Org. R Foundation for Statistical Computing; 2015. http://doi.org/10.1017/CBO9781107415324.004.
Adams MA, Todd M, Kurka J, Conway TL, Cain KL, Frank LD, et al. Patterns of walkability, transit, and recreation environment for physical activity. Am J Prev Med. 2015;49(6):878–87. doi: 10.1016/j.amepre.2015.05.024. PubMed DOI PMC
Lemoine PD, Sarmiento OL, Pinzón JD, Meisel JD, Montes F, Hidalgo D, et al. TransMilenio, a scalable bus rapid transit system for promoting physical activity. J Urban Health. 2016;93(2):256–70. doi: 10.1007/s11524-015-0019-4. PubMed DOI PMC
Reis RS, Hino AAF, Rech CR, Kerr J, Hallal PP. Walkability and physical activity. Am J Prev Med. 2013;45(3):269–75. doi: 10.1016/j.amepre.2013.04.020. PubMed DOI PMC
Södergren M, Sundquist J, Johansson SE, Sundquist K. Physical activity, exercise and self-rated health: a population-based study from Sweden. BMC Public Health. 2008;8:352. doi: 10.1186/1471-2458-8-352. PubMed DOI PMC
Sjöström M, Yngve A, Ekelund U, Poortvliet E, Hurtig-Wennlöf A, Nilsson A, et al. Physical activity in groups of Swedish adults. Are the recommendations feasible? Scand J Nutr. 2002;46(3):123–30. doi: 10.1080/11026480260363251. DOI
World Health Organisation. Sweden - Physical activity factsheet. World Health Organization, Regional Office for Europe; 2015. http://www.euro.who.int/en/health-topics/disease-prevention/physical-activity/country-work/sweden. Accessed 13 Dec 2016.
US Bureau of Labor Statistics. Time spent in primary activities and percent of the civilian population engaging in each activity, averages per day on weekdays and weekends, 2015 annual averages; 2016. http://www.bls.gov/news.release/atus.t02.htm. Accessed 13 Dec 2016.
Valdez P, Ramírez C, García A. Delaying and extending sleep during weekends: sleep recovery or circadian effect? Chronobiol Intern. 1996;13:191–8. doi: 10.3109/07420529609012652. PubMed DOI
Lemoine PD, Cordovez JM, Zambrano JM, Sarmiento OL, Meisel JD, et al. Using agent based modeling to assess the effect of increased Bus Rapid Transit system infrastructure on walking for transportation. Prev Med. 2016;88:39–45. doi: 10.1016/j.ypmed.2016.03.015. PubMed DOI
Cerin E, Zhang CJ, Barnett A, Sit CH, Cheung MM, Johnston JM, et al. Associations of objectively-assessed neighborhood characteristics with older adults’ total physical activity and sedentary time in an ultra-dense urban environment: Findings from the ALECS study. Health Place. 2016;42:1–10. doi: 10.1016/j.healthplace.2016.08.009. PubMed DOI
Harrison RA, Gemmell I, Heller RF. The population effect of crime and neighbourhood on physical activity: an analysis of 15,461 adults. J Epidemiol Community Health. 2007;61(1):34–9. doi: 10.1136/jech.2006.048389. PubMed DOI PMC
Foster S, Giles-Corti B, Knuiman M. Neighbourhood design and fear of crime: A social-ecological examination of the correlates of residents’ fear in new suburban housing developments. Health Place. 2010;16(6):1156–65. doi: 10.1016/j.healthplace.2010.07.007. PubMed DOI
Leslie E, Cerin E, Kremer P. Perceived neighborhood environment and park use as mediators of the effect of area socio-economic status on walking behaviors. J Phys Act Health. 2010;7(6):802–10. doi: 10.1123/jpah.7.6.802. PubMed DOI
Parra DC, Gomez LF, Fleischer NL, David PJ. Built environment characteristics and perceived active park use among older adults: Results from a multilevel study in Bogota. Health Place. 2010;16(6):1174–81. doi: 10.1016/j.healthplace.2010.07.008. PubMed DOI
Salvo D, Reis RS, Stein AD, Rivera J, Martorell R, Pratt M. Characteristics of the built environment in relation to objectively measured physical activity among Mexican adults, 2011. Prev Chronic Dis. 2014;11:E147. doi: 10.5888/pcd11.140047. PubMed DOI PMC
Dunton GF, Berrigan D, Ballard-Barbash R, Graubard BI, Atienza AA. Social and physical environments of sports and exercise reported among adults in the American Time Use Survey. Prev Med. 2008;47(5):519–24. doi: 10.1016/j.ypmed.2008.07.001. PubMed DOI
Díaz Del Castillo A, González SA, Ríos AP, Páez DC, Torres A, Díaz MP, et al. Start small, dream big: Experiences of physical activity in public spaces in Colombia. Prev Med. 2016 PubMed
Bostock L. Pathways of disadvantage? Walking as a mode of transport amongst low-income mothers. Health Soc Care Comm. 2001;9(1):11–8. doi: 10.1046/j.1365-2524.2001.00275.x. PubMed DOI
Carver A, Timperio A, Crawford D. Parental chauffeurs: what drives their transport choice? J Transp Geogr. 2013;26:72–7. doi: 10.1016/j.jtrangeo.2012.08.017. DOI
McGuckin N, Murakami E. Examining trip-chaining behavior: Comparison of travel by men and women. Transport Res Rec. 1999;1693:79–85. doi: 10.3141/1693-12. DOI
Raley S, Bianchi SM, Wang W. When do fathers care? Mothers’ economic contribution and fathers’ involvement in child care. Am J Sociol. 2012;117(5):1422–59. doi: 10.1086/663354. PubMed DOI PMC
Sugiyama T, Cerin E, Owen N, Oyeyemi AL, Conway TL, Van Dyck D, et al. Perceived neighbourhood environmental attributes associated with adults recreational walking: IPEN Adult study in 12 countries. Health Place. 2014;28:22–30. doi: 10.1016/j.healthplace.2014.03.003. PubMed DOI PMC
Van Dyck D, Cerin E, De Bourdeaudhuij I, Hinckson E, Reis RS, Davey R, et al. International study of objectively measured physical activity and sedentary time with body mass index and obesity: IPEN adult study. Int J Obes. 2015;39(2):199–207. doi: 10.1038/ijo.2014.115. PubMed DOI PMC
Morton KL, Corder K, Suhrcke M, Harrison F, Jones AP, van Sluijs EM, et al. School polices, programmes and facilities, and objectively measured sedentary time, LPA and MVPA: associations in secondary school and over the transition from primary to secondary school. Int J Behav Nutr Phys Act. 2016;13:54. doi: 10.1186/s12966-016-0378-6. PubMed DOI PMC
Cochrane T, Davey RC, Gidlow C, Smith GR, Fairburn J, Armitage CJ, et al. Small area and individual level predictors of physical activity in urban communities: a multi-level study in Stoke on Trent, England. Int J Environ Res Public Health. 2009;6(2):654–77. doi: 10.3390/ijerph6020654. PubMed DOI PMC
Kavanagh AM, Goller JL, King T, Jolley D, Crawford D, Turrell G. Urban area disadvantage and physical activity: a multilevel study in Melbourne, Australia. J Epidemiol Community Health. 2005;59(11):934–40. doi: 10.1136/jech.2005.035931. PubMed DOI PMC
Van Lenthe FJ, Brug J, MacKenbach JP. Neighbourhood inequalities in physical inactivity: The role of neighbourhood attractiveness, proximity to local facilities and safety in the Netherlands. Soc Sci Med. 2005;60(4):763–75. doi: 10.1016/j.socscimed.2004.06.013. PubMed DOI
Jankowska MM, Schipperijn J, Kerr J. A framework for using GPS data in physical activity and sedentary behavior studies. Exerc Sport Sci Rev. 2015;43(1):48–56. doi: 10.1249/JES.0000000000000035. PubMed DOI PMC
Salvo D, Sarmiento OL, Reis RS, Hino AA, Bolivar MA, Lemoine PD, et al. Where Latin Americans are physically active, and why does it matter? Findings from the IPEN-adult study in Bogota, Colombia; Cuernavaca, Mexico; and Curitiba, Brazil. Prev Med. 2016 PubMed PMC