Association of perceived and objective neighborhood walkability with accelerometer-measured physical activity and sedentary time in the Maastricht Study.
accelerometry
built environment
physical activity
sedentary behavior
walkability
Journal
Scandinavian journal of medicine & science in sports
ISSN: 1600-0838
Titre abrégé: Scand J Med Sci Sports
Pays: Denmark
ID NLM: 9111504
Informations de publication
Date de publication:
Nov 2023
Nov 2023
Historique:
revised:
11
07
2023
received:
08
04
2023
accepted:
12
07
2023
medline:
23
10
2023
pubmed:
25
7
2023
entrez:
25
7
2023
Statut:
ppublish
Résumé
We investigated the association of neighborhood walkability with accelerometer-measured physical activity (PA) and sedentary behavior (SB) and examined whether objective and subjective measures of walkability resulted in similar findings. PA and SB from the first 7689 Maastricht Study participants ages 40-75 from 2010 to 2017 were measured using accelerometers for 7 days. Mean daily step count, light-intensity PA, moderate- to vigorous- intensity PA (MVPA), and SB were calculated. Objective walkability was measured by the 7-component Dutch Walkability Index within 500 m Euclidean buffers around residential addresses of participants. Subjective walkability was obtained from the Abbreviated Neighborhood Environment Walkability Scale. Linear regression models analyzed the associations of walkability with PA and SB, controlling for potential confounders. Objective walkability was negatively associated with light intensity PA in the most walkable quartile (b = -14.58, 95% CI = -20.94, -8.23). Compared to participants living in the least walkable neighborhoods, those in the most walkable quartile had statistically significantly higher SB levels (b = 11.64, 95% CI = 4.95, 18.32). For subjective walkability, mean daily step count was significantly higher in the most walkable quartile (b = 509.60, 95% CI = 243.38, 775.81). Higher subjective walkability was positively associated with MVPA (b = 4.40, 95% CI = 2.56, 6.23). Living in a neighborhood with higher objective walkability was associated with lower levels of PA and higher SB levels while higher subjective walkability was associated with higher levels of PA. These results show discordant findings and thus, the effect of walkability on participant PA and SB within our sample is to be determined.
Sections du résumé
BACKGROUND
BACKGROUND
We investigated the association of neighborhood walkability with accelerometer-measured physical activity (PA) and sedentary behavior (SB) and examined whether objective and subjective measures of walkability resulted in similar findings.
METHODS
METHODS
PA and SB from the first 7689 Maastricht Study participants ages 40-75 from 2010 to 2017 were measured using accelerometers for 7 days. Mean daily step count, light-intensity PA, moderate- to vigorous- intensity PA (MVPA), and SB were calculated. Objective walkability was measured by the 7-component Dutch Walkability Index within 500 m Euclidean buffers around residential addresses of participants. Subjective walkability was obtained from the Abbreviated Neighborhood Environment Walkability Scale. Linear regression models analyzed the associations of walkability with PA and SB, controlling for potential confounders.
RESULTS
RESULTS
Objective walkability was negatively associated with light intensity PA in the most walkable quartile (b = -14.58, 95% CI = -20.94, -8.23). Compared to participants living in the least walkable neighborhoods, those in the most walkable quartile had statistically significantly higher SB levels (b = 11.64, 95% CI = 4.95, 18.32). For subjective walkability, mean daily step count was significantly higher in the most walkable quartile (b = 509.60, 95% CI = 243.38, 775.81). Higher subjective walkability was positively associated with MVPA (b = 4.40, 95% CI = 2.56, 6.23).
CONCLUSION
CONCLUSIONS
Living in a neighborhood with higher objective walkability was associated with lower levels of PA and higher SB levels while higher subjective walkability was associated with higher levels of PA. These results show discordant findings and thus, the effect of walkability on participant PA and SB within our sample is to be determined.
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
2313-2322Subventions
Organisme : Cardiovascular Center (CVC, Maastricht, the Netherlands)
Organisme : Cardiovascular Research Institute Maastricht (CARIM, Maastricht, the Netherlands)
Organisme : Dutch Ministry of Economic Affairs (grant 31O.041)
Organisme : European Regional Development Fund
Organisme : Health Foundation Limburg (Maastricht, the Netherlands)
Organisme : Janssen-Cilag B.V. (Tilburg, the Netherlands)
Organisme : Novo Nordisk Farma B.V. (Alphen aan den Rijn, the Netherlands)
Organisme : Pearl String Initiative Diabetes (Amsterdam, the Netherlands)
Organisme : Province of Limburg
Organisme : Sanofi-Aventis Netherlands, B.V. (Gouda, the Netherlands)
Organisme : School for Nutrition, Toxicology and Metabolism (NUTRIM, Maastricht, the Netherlands)
Organisme : School for Public Health and Primary Care (CAPHRI, Maastricht, the Netherlands)
Organisme : Stichting Annadal (Maastricht, the Netherlands)
Organisme : Stichting De Weijerhorst (Maastricht, the Netherlands)
Informations de copyright
© 2023 The Authors. Scandinavian Journal of Medicine & Science In Sports published by John Wiley & Sons Ltd.
Références
Guthold R , Stevens GA , Riley LM , Bull FC . Worldwide trends in insufficient physical activity from 2001 to 2016: a pooled analysis of 358 population-based surveys with 1·9 million participants. Lancet Glob Health. 2018;6(10):e1077-e1086.
Lavie CJ , Ozemek C , Carbone S , Katzmarzyk PT , Blair SN . Sedentary behavior, exercise, and cardiovascular health. Circ Res. 2019;124(5):799-815.
WHO. Global Status Report on Noncommunicable Diseases 2014 [Internet]. World Health Organization; 2014. Available from: http://www.who.int/nmh/publications/ncd-status-report-2014/en
Forsyth A , Oakes JM , Schmitz KH , Hearst M . Does residential density increase walking and other physical activity? Urban Stud. 2007;44(4):679-697.
Rodriguez D . Carolina transportation program white paper series the measurement of the level of mixed land uses: a synthetic approach. 2022.
Faulkner GEJ , Buliung RN , Flora PK , Fusco C . Active school transport, physical activity levels and body weight of children and youth: a systematic review. Prev Med. 2009;48(1):3-8.
Giles-Corti B , Kelty SF , Zubrick SR , Villanueva KP . Encouraging walking for transport and physical activity in children and adolescents: how important is the built environment? Sports Med Auckl NZ. 2009;39(12):995-1009.
Braza M , Shoemaker W , Seeley A . Neighborhood design and rates of walking and biking to elementary school in 34 California communities. Am J Health Promot AJHP. 2004;19(2):128-136.
Harris V , Kendal D , Hahs AK , Threlfall CG . Green space context and vegetation complexity shape people's preferences for urban public parks and residential gardens. Landsc Res. 2018;43(1):150-162.
Hunter RF , Christian H , Veitch J , Astell-Burt T , Hipp JA , Schipperijn J . The impact of interventions to promote physical activity in urban green space: a systematic review and recommendations for future research. Soc Sci Med. 2015;1982(124):246-256.
Ewing R , Cervero R . Travel and the built environment. J Am Plann Assoc. 2010;76(3):265-294.
Liao B , van den Berg PEW , van Wesemael PJV , Arentze TA . Empirical analysis of walkability using data from The Netherlands. Transp Res Part Transp Environ. 2020;(85):102390.
Tobin M , Hajna S , Orychock K , et al. Rethinking walkability and developing a conceptual definition of active living environments to guide research and practice. BMC Public Health. 2022;22(1):450.
Cerin E , Nathan A , van Cauwenberg J , Barnett DW , Barnett A . The neighbourhood physical environment and active travel in older adults: a systematic review and meta-analysis. Int J Behav Nutr Phys Act. 2017;14(1):15.
Sallis JF , Floyd MF , Rodríguez DA , Saelens BE . Role of built environments in physical activity, obesity, and cardiovascular disease. Circulation. 2012;125(5):729-737.
Peters M , Muellmann S , Christianson L , et al. Measuring the association of objective and perceived neighborhood environment with physical activity in older adults: challenges and implications from a systematic review. Int J Health Geogr. 2020;19(1):47.
Davison KK , Lawson CT . Do attributes in the physical environment influence children's physical activity? A review of the literature. Int J Behav Nutr Phys Act. 2006;3:19.
Barnett DW , Barnett A , Nathan A , Van Cauwenberg J , Cerin E . Built environmental correlates of older adults' total physical activity and walking: a systematic review and meta-analysis. Int J Behav Nutr Phys Act. 2017;14(1):103.
Van Cauwenberg J , De Bourdeaudhuij I , De Meester F , et al. Relationship between the physical environment and physical activity in older adults: a systematic review. Health Place. 2011;17(2):458-469.
Liao Y , Lin CY , Lai TF , Chen YJ , Kim B , Park JH . Walk score(®) and its associations with older Adults' health behaviors and outcomes. Int J Environ Res Public Health. 2019;16(4). doi:10.3390/ijerph16040622
Van Dyck D , Cardon G , Deforche B , Owen N , Sallis JF , De Bourdeaudhuij I . Neighborhood walkability and sedentary time in Belgian adults. Am J Prev Med. 2010;39(1):25-32.
Learnihan V , Kp VN , Giles-Corti B , Knuiman M . Effect of scale on the links between walking and Urban Design. Geogr Res. 2011;49(2):183-191.
Lam TM , Wang Z , Vaartjes I , et al. Development of an objectively measured walkability index for The Netherlands. Int J Behav Nutr Phys Act. 2022;19(1):50.
Timmermans EJ , Visser M , Wagtendonk AJ , Noordzij JM , Lakerveld J . Associations of changes in neighbourhood walkability with changes in walking activity in older adults: a fixed effects analysis. BMC Public Health. 2021;21(1):1323.
Schram MT , Sep SJS , Van Der Kallen CJ , et al. The Maastricht study: an extensive phenotyping study on determinants of type 2 diabetes, its complications and its comorbidities. Eur J Epidemiol. 2014;29(6):439-451.
van der Berg JD , Willems PJB , van der Velde JHPM , et al. Identifying waking time in 24-h accelerometry data in adults using an automated algorithm. J Sports Sci. 2016;34(19):1867-1873.
Lakerveld J , Wagtendonk A , Vaartjes I , et al. Deep phenotyping meets big data: the geoscience and hEalth cohort COnsortium (GECCO) data to enable exposome studies in The Netherlands. Int J Health Geogr. 2020;19(1):1-16.
Timmermans EJ , Lakerveld J , Beulens JWJ , et al. Cohort profile: the geoscience and health cohort Consortium (GECCO) in The Netherlands. BMJ Open. 2018;8(6):e021597.
Cerin E , Conway TL , Saelens BE , Frank LD , Sallis JF . Cross-validation of the factorial structure of the neighborhood environment walkability scale (NEWS) and its abbreviated form (NEWS-A). Int J Behav Nutr Phys Act. 2009;6:1-10.
Cerin E , Saelens BE , Sallis JF , Frank LD . Neighborhood environment walkability scale: validity and development of a short form. Med Sci Sports Exerc. 2006;38(9):1682-1691.
Kadaster. Transacties en koopsommen 2000-2015. Accessed January, 2022. https://www.cbs.nl/nl-nl/cijfers/detail/83906NED
Inequality - Income Inequality OECD data. Accessed May 19, 2022. https://data.oecd.org/inequality/income-inequality.htm
Braver NR , Rutters F , Wagtendonk AJ , et al. Neighborhood walkability, physical activity and changes in glycemic markers in people with type 2 diabetes: the Hoorn diabetes care system cohort. Health Place. 2021;69:102560.
Hajna S , Brage S , Dalton A , et al. Cross-sectional and prospective associations between active living environments and accelerometer-assessed physical activity in the EPIC-Norfolk cohort. Health Place. 2021;67:102490.
Lam TM , Vaartjes I , Grobbee DE , Karssenberg D , Lakerveld J . Associations between the built environment and obesity: an umbrella review. Int J Health Geogr. 2021;20(1):7.
Satariano WA , Ivey SL , Kurtovich E , et al. Lower-body function, neighborhoods, and walking in an older population. Am J Prev Med. 2010;38(4):419-428.
Mahmood A , Chaudhury H , Michael YL , Campo M , Hay K , Sarte A . A photovoice documentation of the role of neighborhood physical and social environments in older adults' physical activity in two metropolitan areas in North America. Soc Sci Med 1982. 2012;74(8):1180-1192.
Ruijsbroek A , Droomers M , Groenewegen PP , Hardyns W , Stronks K . Social safety, self-rated general health and physical activity: changes in area crime, area safety feelings and the role of social cohesion. Health Place. 2015;31:39-45.
Brantingham PJ , Brantingham PL , Song J , Spicer V . Crime hot spots, crime corridors and the journey to crime: an expanded theoretical model of the generation of crime concentrations. In: Lersch KM , Chakraborty J , eds. Geographies of Behavioural Health, Crime, and Disorder: the Intersection of Social Problems and Place [Internet]. Springer International Publishing; 2020:61-86.
Savard D , Kennedy D . Crime and security liability concerns at shopping centers. Palgrave Macmillan UK; 2014:254-275.
van Doorslaer E , Masseria C , Koolman X . Inequalities in access to medical care by income in developed countries. CMAJ Can Med Assoc J J Assoc Medicale Can. 2006;174(2):177-183.
Schwandt H , Currie J , Bär M , et al. Inequality in mortality between black and white Americans by age, place, and cause and in comparison to Europe, 1990 to 2018. Proc Natl Acad Sci USA. 2021;118(40):e2104684118.
Woolf SH , Aron L , (Eds.) US health in international perspective: shorter lives, poorer health. National Academies Press; 2013.
WHO Guidelines on physical activity and sedentary behaviour [Internet]. World Health Organization; 2020. Available from: https://apps.who.int/iris/bitstream/handle/10665/336656/9789240015128-eng.pdf
Hupin D , Roche F , Gremeaux V , et al. Even a low-dose of moderate-to-vigorous physical activity reduces mortality by 22% in adults aged ≥60 years: a systematic review and meta-analysis. Br J Sports Med. 2015;49(19):1262-1267.