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      Walkable Urban Design Attributes and Japanese Older Adults’ Body Mass Index: Mediation Effects of Physical Activity and Sedentary Behavior

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          Abstract

          Purpose:

          The purposes of this study were to examine associations between objectively measured walkable urban design attributes with Japanese older adults’ body mass index (BMI) and to test whether objectively assessed physical activity and sedentary behavior mediated such associations.

          Design:

          Cross-sectional.

          Setting:

          Matsudo City, Chiba Prefecture, Japan.

          Participants:

          Participants were 297 older residents (aged 65-84 years) randomly selected from the registry of residential addresses.

          Measures:

          Walkable urban design attributes, including population density, availability of physical activity facilities, intersection density, and access to public transportation stations, were calculated using geographic information systems. Physical activity, sedentary behavior, and BMI were measured objectively.

          Analysis:

          The relationships of walkable urban design attributes, Walk Score®, and BMI were examined by multiple linear regression with adjustment for covariates in all models. Mediation effects of the physical activity and sedentary behavior variables in these relationships were tested using a product-of-coefficients test.

          Results:

          Higher population density and Walk Score® were associated with lower BMI. Light and moderate-to-vigorous physical activities partially mediated the relationships between these walkable urban design attributes and BMI.

          Conclusions:

          Developing active-friendly environmental policies to (re)design neighborhoods may not only promote active transport behaviors but also help in improving residents’ health status in non-Western contexts.

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          Most cited references15

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          Obesity relationships with community design, physical activity, and time spent in cars.

          Obesity is a major health problem in the United States and around the world. To date, relationships between obesity and aspects of the built environment have not been evaluated empirically at the individual level. To evaluate the relationship between the built environment around each participant's place of residence and self-reported travel patterns (walking and time in a car), body mass index (BMI), and obesity for specific gender and ethnicity classifications. Body Mass Index, minutes spent in a car, kilometers walked, age, income, educational attainment, and gender were derived through a travel survey of 10,878 participants in the Atlanta, Georgia region. Objective measures of land use mix, net residential density, and street connectivity were developed within a 1-kilometer network distance of each participant's place of residence. A cross-sectional design was used to associate urban form measures with obesity, BMI, and transportation-related activity when adjusting for sociodemographic covariates. Discrete analyses were conducted across gender and ethnicity. The data were collected between 2000 and 2002 and analysis was conducted in 2004. Land-use mix had the strongest association with obesity (BMI >/= 30 kg/m(2)), with each quartile increase being associated with a 12.2% reduction in the likelihood of obesity across gender and ethnicity. Each additional hour spent in a car per day was associated with a 6% increase in the likelihood of obesity. Conversely, each additional kilometer walked per day was associated with a 4.8% reduction in the likelihood of obesity. As a continuous measure, BMI was significantly associated with urban form for white cohorts. Relationships among urban form, walk distance, and time in a car were stronger among white than black cohorts. Measures of the built environment and travel patterns are important predictors of obesity across gender and ethnicity, yet relationships among the built environment, travel patterns, and weight may vary across gender and ethnicity. Strategies to increase land-use mix and distance walked while reducing time in a car can be effective as health interventions.
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            Real-time estimation of daily physical activity intensity by a triaxial accelerometer and a gravity-removal classification algorithm.

            We have recently developed a simple algorithm for the classification of household and locomotive activities using the ratio of unfiltered to filtered synthetic acceleration (gravity-removal physical activity classification algorithm, GRPACA) measured by a triaxial accelerometer. The purpose of the present study was to develop a new model for the immediate estimation of daily physical activity intensities using a triaxial accelerometer. A total of sixty-six subjects were randomly assigned into validation (n 44) and cross-validation (n 22) groups. All subjects performed fourteen activities while wearing a triaxial accelerometer in a controlled laboratory setting. During each activity, energy expenditure was measured by indirect calorimetry, and physical activity intensities were expressed as metabolic equivalents (MET). The validation group displayed strong relationships between measured MET and filtered synthetic accelerations for household (r 0·907, P < 0·001) and locomotive (r 0·961, P < 0·001) activities. In the cross-validation group, two GRPACA-based linear regression models provided highly accurate MET estimation for household and locomotive activities. Results were similar when equations were developed by non-linear regression or sex-specific linear or non-linear regressions. Sedentary activities were also accurately estimated by the specific linear regression classified from other activity counts. Therefore, the use of a triaxial accelerometer in combination with a GRPACA permits more accurate and immediate estimation of daily physical activity intensities, compared with previously reported cut-off classification models. This method may be useful for field investigations as well as for self-monitoring by general users.
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              Neighborhood Food Environment and Walkability Predict Obesity in New York City

              Background Differences in the neighborhood food environment may contribute to disparities in obesity. Objectives The purpose of this study was to examine the association of neighborhood food environments with body mass index (BMI) and obesity after control for neighborhood walkability. Methods This study employed a cross-sectional, multilevel analysis of BMI and obesity among 13,102 adult residents of New York City. We constructed measures of the food environment and walkability for the neighborhood, defined as a half-mile buffer around the study subject’s home address. Results Density of BMI-healthy food outlets (supermarkets, fruit and vegetable markets, and natural food stores) was inversely associated with BMI. Mean adjusted BMI was similar in the first two quintiles of healthy food density (0 and 1.13 stores/km2, respectively), but declined across the three higher quintiles and was 0.80 units lower [95% confidence interval (CI), 0.27–1.32] in the fifth quintile (10.98 stores/km2) than in the first. The prevalence ratio for obesity comparing the fifth quintile of healthy food density with the lowest two quintiles combined was 0.87 (95% CI, 0.78–0.97). These associations remained after control for two neighborhood walkability measures, population density and land-use mix. The prevalence ratio for obesity for the fourth versus first quartile of population density was 0.84 (95% CI, 0.73–0.96) and for land-use mix was 0.91 (95% CI, 0.86–0.97). Increasing density of food outlets categorized as BMI-unhealthy was not significantly associated with BMI or obesity. Conclusions Access to BMI-healthy food stores is associated with lower BMI and lower prevalence of obesity.
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                Author and article information

                Journal
                Am J Health Promot
                Am J Health Promot
                AHP
                spahp
                American Journal of Health Promotion
                SAGE Publications (Sage CA: Los Angeles, CA )
                0890-1171
                2168-6602
                25 November 2018
                June 2019
                : 33
                : 5
                : 764-767
                Affiliations
                [1 ]Faculty of Sport Sciences, Waseda University, Tokorozawa, Japan
                [2 ]Behavioural Epidemiology Laboratory, Baker Heart and Diabetes Institute, Melbourne, Australia
                [3 ]Mary MacKillop Institute for Health Research, Australian Catholic University, Melbourne, Australia
                [4 ]Department of Health Promotion, Education, and Behavior, Arnold School of Public Health, University of South Carolina, Columbia, SC, USA
                [5 ]Prevention Research Center, University of South Carolina, Columbia, SC, USA
                [6 ]Graduate School of Environmental Studies, Tohoku University, Sendai, Japan
                [7 ]Faculty of Health and Sport Sciences, University of Tsukuba, Tsukuba, Japan
                [8 ]Faculty of Liberal Arts and Sciences, Bunka Gakuen University, Tokyo, Japan
                [9 ]School of International Liberal Studies, Chukyo University, Nagoya, Japan
                Author notes
                [*]Mohammad Javad Koohsari, Faculty of Sport Sciences, Waseda University, 2-579-15 Mikajima, Tokorozawa, Saitama 359-1192, Japan. Email: javad.koohsari@ 123456baker.edu.au
                Article
                10.1177_0890117118814385
                10.1177/0890117118814385
                7323758
                30474377
                0134cfad-bd84-49e5-aefe-e7dfda964b47
                © The Author(s) 2018

                This article is distributed under the terms of the Creative Commons Attribution-NonCommercial 4.0 License ( http://www.creativecommons.org/licenses/by-nc/4.0/) which permits non-commercial use, reproduction and distribution of the work without further permission provided the original work is attributed as specified on the SAGE and Open Access pages ( https://us.sagepub.com/en-us/nam/open-access-at-sage).

                History
                Funding
                Funded by: JSPS KAKENHI;
                Award ID: JP25704018
                Categories
                Applied Research Briefs

                built environment,weight,neighborhood,aging,active behaviors

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