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      Neighborhood walkability and 12-year changes in cardio-metabolic risk: the mediating role of physical activity

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          Abstract

          Background

          Living in walkable neighborhoods may provide long-term cardio-metabolic health benefits to residents. Little empirical research has examined the behavioral mechanisms in this relationship. In this longitudinal study, we examined the potential mediating role of physical activity (baseline and 12-year change) in the relationships of neighborhood walkability with 12-year changes in cardio-metabolic risk markers.

          Methods

          The Australian Diabetes, Obesity and Lifestyle study collected data from adults, initially aged 25+ years, in 1999–2000, 2004–05, and 2011–12. We used 12-year follow-up data from 2023 participants who did not change their address during the study period. Outcomes were 12-year changes in waist circumference, weight, systolic and diastolic blood pressure, fasting and 2-h postload plasma glucose, high-density lipoprotein cholesterol, and triglycerides. A walkability index was calculated, using dwelling density, intersection density, and destination density, within 1 km street-network buffers around participants’ homes. Spatial data for calculating these measures were sourced around the second follow-up period. Physical activity was assessed by self-reported time spent in moderate-to-vigorous physical activity (including walking). Multilevel models, adjusting for potential confounders, were used to examine the total and indirect relationships. The joint-significance test was used to assess mediation.

          Results

          There was evidence for relationships of higher walkability with smaller increases in weight ( P = 0.020), systolic blood pressure ( P < 0.001), and high-density lipoprotein cholesterol ( P = 0.002); and, for relationships of higher walkability with higher baseline physical activity ( P = 0.020), which, in turn, related to smaller increases in waist circumference ( P = 0.006), weight ( P = 0.020), and a greater increase in high-density lipoprotein cholesterol ( P = 0.005). There was no evidence for a relationship of a higher walkability with a change in physical activity during the study period ( P = 0.590).

          Conclusions

          Our mediation analysis has shown that the protective effects of walkable neighborhoods against obesity risk may be in part attributable to higher baseline physical activity levels. However, there was no evidence of mediation by increases in physical activity during the study period. Further research is needed to understand other behavioral pathways between walkability and cardio-metabolic health, and to investigate any effects of changes in walkability.

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          Most cited references41

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          Dose response between physical activity and risk of coronary heart disease: a meta-analysis.

          No reviews have quantified the specific amounts of physical activity required for lower risks of coronary heart disease when assessing the dose-response relation. Instead, previous reviews have used qualitative estimates such as low, moderate, and high physical activity. We performed an aggregate data meta-analysis of epidemiological studies investigating physical activity and primary prevention of CHD. We included prospective cohort studies published in English since 1995. After reviewing 3194 abstracts, we included 33 studies. We used random-effects generalized least squares spline models for trend estimation to derive pooled dose-response estimates. Among the 33 studies, 9 allowed quantitative estimates of leisure-time physical activity. Individuals who engaged in the equivalent of 150 min/wk of moderate-intensity leisure-time physical activity (minimum amount, 2008 U.S. federal guidelines) had a 14% lower coronary heart disease risk (relative risk, 0.86; 95% confidence interval, 0.77 to 0.96) compared with those reporting no leisure-time physical activity. Those engaging in the equivalent of 300 min/wk of moderate-intensity leisure-time physical activity (2008 U.S. federal guidelines for additional benefits) had a 20% (relative risk, 0.80; 95% confidence interval, 0.74 to 0.88) lower risk. At higher levels of physical activity, relative risks were modestly lower. People who were physically active at levels lower than the minimum recommended amount also had significantly lower risk of coronary heart disease. There was a significant interaction by sex (P=0.03); the association was stronger among women than men. These findings provide quantitative data supporting US physical activity guidelines that stipulate that "some physical activity is better than none" and "additional benefits occur with more physical activity."
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            City planning and population health: a global challenge

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              Multilevel Analysis

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                Author and article information

                Contributors
                Manoj.Chandrabose@myacu.edu.au
                Ester.Cerin@acu.edu.au
                Suzanne.Mavoa@unimelb.edu.au
                David.Dunstan@baker.edu.au
                Alison.Carver@acu.edu.au
                Gavin.Turrell@rmit.edu.au
                Neville.Owen@baker.edu.au
                Billie.Giles-Corti@rmit.edu.au
                Takemi.Sugiyama@acu.edu.au
                Journal
                Int J Behav Nutr Phys Act
                Int J Behav Nutr Phys Act
                The International Journal of Behavioral Nutrition and Physical Activity
                BioMed Central (London )
                1479-5868
                15 October 2019
                15 October 2019
                2019
                : 16
                : 86
                Affiliations
                [1 ]ISNI 0000 0001 2194 1270, GRID grid.411958.0, Mary MacKillop Institute for Health Research, , Australian Catholic University, ; Melbourne, Australia
                [2 ]ISNI 0000 0004 0409 2862, GRID grid.1027.4, Centre for Urban Transitions, , Swinburne University of Technology, ; Melbourne, Australia
                [3 ]ISNI 0000 0000 9760 5620, GRID grid.1051.5, Baker Heart and Diabetes Institute, ; Melbourne, Australia
                [4 ]ISNI 0000000121742757, GRID grid.194645.b, School of Public Health, , The University of Hong Kong, ; Hong Kong, China
                [5 ]ISNI 0000 0001 2179 088X, GRID grid.1008.9, Melbourne School of Population and Global Health, , University of Melbourne, ; Melbourne, Australia
                [6 ]ISNI 0000 0001 2163 3550, GRID grid.1017.7, Centre for Urban Research, , RMIT University, ; Melbourne, Australia
                [7 ]ISNI 0000000089150953, GRID grid.1024.7, School of Public Health and Social Work, , Queensland University of Technology, ; Brisbane, Australia
                [8 ]ISNI 0000 0000 9320 7537, GRID grid.1003.2, School of Public Health, , The University of Queensland, ; Brisbane, Australia
                [9 ]ISNI 0000 0004 1936 7857, GRID grid.1002.3, Central Clinical School, Faculty of Medicine, Nursing and Health Sciences, , Monash University, ; Melbourne, Australia
                [10 ]ISNI 0000 0004 0473 0844, GRID grid.1048.d, Institute for Resilient Regions, , University of Southern Queensland, ; Toowoomba, Australia
                Author information
                http://orcid.org/0000-0002-5311-3020
                Article
                849
                10.1186/s12966-019-0849-7
                6792258
                31615522
                e492f7a1-89ec-4514-bb78-aaff16839d51
                © The Author(s). 2019

                Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License ( http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

                History
                : 10 May 2019
                : 16 September 2019
                Funding
                Funded by: National Health and Medical Research Council (Australia)
                Award ID: 1061404
                Award ID: 1003960
                Award ID: 1107672
                Award ID: 1121035
                Award ID: 1078360
                Award Recipient :
                Funded by: Australian Research Council
                Award ID: FT3 140100085
                Award Recipient :
                Categories
                Research
                Custom metadata
                © The Author(s) 2019

                Nutrition & Dietetics
                built environment,cardiovascular disease,type 2 diabetes,hypertension,pathways,population health

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