Introduction to the Active Living Research Reference List January – July 2008



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C. Arambepola, S. Allender, R. Ekanayake and D. Fernando. (2008). Urban living and obesity: is it independent of its population and lifestyle characteristics? Tropical Medicine & International Health. 13, 448-457.

Objectives Living in an urban area influences obesity. However, little is known about whether this relationship is truly independent of, or merely mediated through, the demographic, socio-economic and lifestyle characteristics of urban populations. We aimed to identify and quantify the magnitude of this relationship in a Sri Lankan population. Methods Cross-sectional study of adults aged 20-64 years representing the urban (n = 770) and rural (n = 630) populations, in the district of Colombo in 2004. Obesity was measured as a continuous variable using body mass index (BMI). Demographic, socio-economic and lifestyle factors were assessed. Gender-specific multivariable regression models were developed to quantify the independent effect of urban/ rural living and other variables on increased BMI. Results The BMI (mean; 95% confidence interval) differed significantly between urban (men: 23.3; 22.8-23.8; women: 24.2; 23.7-24.7) and rural (men: 22.3; 21.9-22.7; women: 23.2; 22.7-23.7) sectors (P < 0.01). The observed association remained stable independently of all other variables in the regression models among both men (coefficient = 0.64) and women (coefficient = 0.95). These coefficients equated to 2.2 kg weight for the average man and 1.7 kg for the average woman. Other independent associations of BMI were with income (coefficient = 1.74), marital status (1.48), meal size (1.53) and religion (1.20) among men, and with age (0.87), marital status (2.25) and physical activity (0.96) among women. Conclusions Urban living is associated with obesity independently of most other demographic, socio-economic and lifestyle characteristics of the population. Targeting urban populations may be useful for consideration when developing strategies to reduce the prevalence of obesity.

S. A. Aytur, D. A. Rodriguez, K. R. Evenson, D. J. Catellier and W. D. Rosamond. (2008). The sociodemographics of land use planning: Relationships to physical activity, accessibility, and equity. Health & Place. 14, 367-385.

Little is known about relationships between attributes of land use plans and sociodemographic variations in physical activity (PA). This study evaluates associations between policy-relevant plan attributes, sociodemographic factors, and PA in North Carolina. Results suggest that land use plans that included non-automobile transportation improvements and more comprehensive policies to guide development were positively associated with both leisure and transportation-related PA. However, residents of counties with lower-income levels and higher proportions of non-white residents were less likely to have attributes supportive of PA included in their plans. Implications for transdisciplinary collaboration with respect to reducing health disparities are discussed.

H. M. Badland, G. M. Schofield and N. Garrett. (2008). Travel behavior and objectively measured urban design variables: Associations for adults traveling to work. Health & Place. 14, 85-95.

Mixed land use, residential density, street connectivity, and commute distance have been identified as potential variables affecting transport-related physical activity (TPA) behaviors. In this Study, objectively measured urban design variables and TPA behaviors for adults who commuted to an occupation (n = 364) were examined. Utilitarian walking and cycling for other purposes were not investigated. Commute distance was negatively associated with TPA behaviors. Logistic regression analysis identified respondents who commuted through the most connected streets were more likely to engage in TPA modes to access their occupation (OR = 6.9) when compared to those traveling along the least connected. No other associations between TPA behaviors and urban variables were shown. Improved street connectivity and reduced commute distances will likely support TPA.

E. A. Baker, M. Schootman, C. Kelly and E. Barnidge. (2008). Do Recreational Resources Contribute to Physical Activity? Journal of Physical Activity & Health. 5, 252.

Background: Previous research suggests that access to recreational resources might influence physical activity. Little research, however, has looked at both access to and the characteristics of recreational resources and physical activity. Methods: Access to recreational resources was assessed by counting the number of recreational resources in the geographic area. Resource characteristics were assessed through systematic observation (audits) or telephone interview of each resource. Access and characteristics in 2 counties in the St Louis, MO, metropolitan area with different prevalence rates of physical activity were compared using the critical-ratio (Z) test with P value for the difference between 2 independent proportions, given that the count and sample size were used to assess differences in access to equipment and presence of physical disorder. Financial accessibility was assessed for each facility. Results: Data indicated significant differences in access and characteristics between the 2 areas that mimic differences in levels of physical activity. Conclusion: Our findings suggest that both access to and characteristics of recreational resources can contribute to differential rates of physical activity.

J. Bjork, M. Albin, P. Grahn, H. Jacobsson, J. Ardo, J. Wadbro, P. O. Ostergren and E. Skarback. (2008). Recreational values of the natural environment in relation to neighbourhood satisfaction, physical activity, obesity and wellbeing. Journal Of Epidemiology And Community Health. 62,

Objectives: The aim of this population-based study was to investigate associations between recreational values of the close natural environment and neighbourhood satisfaction, physical activity, obesity and wellbeing. Methods: Data from a large public health survey distributed as a mailed questionnaire in suburban and rural areas of southern Sweden were used (N = 24 819; 59% participation rate). Geocoded residential addresses and the geographical information system technique were used to assess objectively five recreational values of the close natural environment: serene, wild, lush, spacious and culture. Results: On average, a citizen of the Scania region, inner city areas excluded, only had access to 0.67 recreational values within 300 metres distance from their residence. The number of recreational values near the residence was strongly associated with neighbourhood satisfaction and physical activity. The effect on satisfaction was especially marked among tenants and the presence of recreational values was associated with low or normal body mass index in this group. A less marked positive association with vitality among women was observed. No evident effect on self-rated health was detectable. Conclusions: Immediate access to natural environments with high recreational values was rare in the study population and was distributed in an inequitable manner. Moreover, such access was associated with a positive assessment of neighbourhood satisfaction and time spent on physical activity, which can be expected to reduce obesity and increase vitality by having a buffering effect on stress.

J. L. Black and J. Macinko. (2008). Neighborhoods and obesity. Nutrition Reviews. 66, 2.

This review critically summarizes the literature on neighborhood determinants of obesity and proposes a conceptual framework to guide future inquiry. Thirty-seven studies met all inclusion criteria and revealed that the influence of neighborhood-level factors appears mixed. Neighborhood-level measures of economic resources were associated with obesity in 15 studies, while the associations between neighborhood income inequality and racial composition with obesity were mixed. Availability of healthy versus unhealthy food was inconsistently related to obesity, while neighborhood features that discourage physical activity were consistently associated with increased body mass index. Theoretical explanations for neighborhood-obesity effects and recommendations for strengthening the literature are presented.

M. G. Boarnet, M. Greenwald and T. E. McMillan. (2008). Walking, urban design, and health - Toward a cost-benefit analysis framework. Journal Of Planning Education And Research. 27, 341-358.

The authors examine the magnitude of health benefits from urban design characteristics that are associated with increased walking. Using geocoded travel diary data front Portland, Oregon, regression analyses give information on the magnitude and statistical significance of the link between urban design variables and two-day walking distances. From the coefficient point estimates, the authors link to the health literature to give information on how many persons would realize health benefits, in the form of reductions in mortality risk, from walking increases associated with urban design changes. Using a cost-benefit analysis framework, they give monetized estimates of the health benefits of various urban design changes. The article closes with Suggestions about how the techniques developed can be applied to other cost-benefit analyses of the health benefits of planning projects that are intended to increase walking.

T. D. Bodea, L. A. Garrow, M. D. Meyer and C. L. Ross. (2008). Explaining obesity with urban form: a cautionary tale. Transportation. 35, 179-199.

In recent years, there has been a dramatic increase in studies exploring associations between the built environment and obesity. Many studies have found that built environment characteristics, such as high-density land developments, mixed-land uses, and connected street networks, are associated with lower rates of obesity. However, depending on the research field and the researcher, how one specifies the experimental model and how sociodemographic characteristics of the population are defined and included in the model has led to different policy conclusions and implications. This is not a surprising observation; however, it is one that does seem to have been lost in current discussions. This article highlights several data-processing, model-specification, and model-estimation factors that should be comprehensively considered in studies of the built environment and obesity. Empirical results based on data from Atlanta, GA, USA, illustrate that the association between the built environment and obesity is sensitive to how age, income, and educational attainment are included in the model. Also, a detailed examination of land-use-mix measures shows that it is difficult to create this measure and that results are sensitive to the treatment of missing values. Models that distinguish between overweight and obese individuals are shown to provide richer insights into the associations among obesity, built environment, and sociodemographic characteristics for the Atlanta area. The article concludes by offering modeling recommendations for future studies.

A. L. Brown, A. J. Khattak and D. A. Rodriguez. (2008). Neighbourhood types, travel and body mass: A study of new urbanist and suburban neighbourhoods in the US. Urban Studies. 45, 963-988.

Using an ecological framework, this paper examines the body mass index (BMI), physical activity and travel behaviour of household heads in a US new urbanist neighbourhood relative to household heads of comparable conventional suburban US neighbourhoods. Using a quasi-experimental design, a new urbanist neighbourhood and five conventional suburban neighbourhoods were matched on age of development, assessed property values and regional accessibility. Self-reported height, weight, physical activity and travel behaviours were obtained from the household heads in each neighbourhood type. No direct association was detected between neighbourhood type and BMI. However, household heads of single-family dwellings in the new urbanist neighbourhood have lower BMI partly due to the number of utilitarian trips made by walking or bicycling. This relationship is independent of physical activity time. Although small in magnitude, this association may have appreciable morbidity effects at the population level.

E. Cerin and E. Leslie. (2008). How socio-economic status contributes to participation in leisure-time physical activity. Social Science & Medicine. 66, 2596-2609.

The aim of this cross-sectional study was to identify individual, social, and environmental contributors (mediators) to individual- and area-level differences in leisure-time physical activity across socio-economic groups. A two-stage stratified sampling design was used to recruit 20-65 year old adults (N = 2194) living in 154 census collection districts of Adelaide, Australia (overall response rate: 12%). Participants completed two surveys six months apart (response rate on the second survey: 83%). Individual-level socio-economic status (SES) was assessed using self-report measures on educational attainment, household income, and household size. Area-level SES was assessed using census data on median household income and household size for each selected census district. Bootstrap generalized linear models were used to examine associations between SES, potential mediators, and leisure-time physical activity. The product-of-coefficient test was used to estimate mediating effects. All SES measures were independently associated with potential individual and social mediators of the SES-activity relationships. Individual- and area-level income was also associated with perceived neighborhood attributes. Self-efficacy and social support for physical activity explained virtually all of the differences in physical activity across educational attainment groups. Physical barriers to walking and access to public open space contributed in part to the explanation of differences in recreational walking across income groups. Yet, self-efficacy and social support were the key mediators of the observed relationships between individual- and area-level income and physical activity. This study suggests that in order to increase physical activity participation in the more disadvantaged segments of the population, comprehensive, multilevel interventions targeting activity-related attitudes and skills as well as social and physical environments are needed.

E. Cerin, C. Vandelanotte, E. Leslie and D. Merom. (2008). Recreational facilities and leisure-time physical activity: An analysis of moderators and self-efficacy as a mediator. Health Psychol. 27, S126-35.

OBJECTIVE: To examine socio-demographic and psychosocial moderators, and self-efficacy as a mediator of the cross-sectional relationships between having access to recreational facilities and leisure-time physical activity (LTPA); to investigate the extent to which the environment-LTPA associations could be explained by self-selection to neighborhoods. DESIGN: A two-stage stratified sampling design was used to recruit 2,650 adults (aged 20-65) from 32 urban communities varying in walkability and socioeconomic status. Participants reported perceived access to facilities and home equipment for LTPA, weekly minutes of LTPA, self-efficacy for and enjoyment of LTPA, reasons for neighborhood selection, and socio-demographic characteristics. MAIN OUTCOME MEASURES: Self-reported recreational walking and other forms of moderate-to-vigorous LTPA expressed in MET-minutes. RESULTS: Specific types of recreational facilities were independently associated with LTPA. Age, education, being overweight/obese, reasons for neighborhood selection, enjoyment of, and self-efficacy for LTPA moderated these relationships. Self-efficacy was not a significant mediator of these cross-sectional associations. CONCLUSION: These findings have potentially significant implications for the planning of environmental interventions aimed at increasing population-level LTPA particularly in those who are less attitudinally inclined to being physically active.

M. A. Colchero and D. Bishai. (2008). Effect of neighborhood exposures on changes in weight among women in Cebu, Philippines (1983-2002). American Journal Of Epidemiology. 167, 615-623.

The authors aimed to identify the contributions of community factors to weight change in a cohort of women from Metropolitan Cebu, Philippines, between 1983 and 2002. The authors created a three-level random-intercept model to see whether mean body mass index (BMI; weight (kg)/height (m)(2)) varied by individual- and cluster-level variables and identified community characteristics associated with changes in BMI among 2,952 nonpregnant women. The average BMI among women living in places with four public amenities (telephones, electricity, mail delivery, and newspapers) was 0.16 kg/m(2) (95% confidence interval: 0.07, 0.26) higher than that of women living in places with fewer than three amenities. An increase in population density of 10,000 persons per km(2) was associated with a BMI increase of 0.09 kg/m(2) (95% confidence interval: 0.05, 0.13). A model with interactions revealed that the effect of population density increased significantly over time. These findings confirm earlier observations that in low-income countries, obesity starts among the wealthiest communities. Secondary and tertiary prevention policies designed to reduce obesity should be implemented in the most economically developed areas first. Primary prevention would be most needed in less developed areas, where the obesity epidemic is just beginning.

C. Coutts. (2008). Greenway accessibility and physical-activity behavior. Environment And Planning B-Planning & Design. 35, 552-563.

Public health initiatives have made important but relatively modest gains through individual-level and nonecological health-promotion efforts aimed at increasing physical activity. The previously overlooked built environment is now being considered as facilitating or hindering one's ability to be active. The multiuse greenway is an example of a facility that can support physical activity, but its level of use may be influenced by the accessibility characteristics of the areas surrounding the greenway. In this study, an unobtrusive methodology using GPS and GIS technology was employed to test whether two variables used to measure accessibility, proximity (population density) and opportunities (land-use mixture), predicted the use of greenway segments. The results presented here allow us to confirm that smaller walking and bicycling scales of analysis are better predictors of physical-activity behavior. The results also suggest that solely bringing environmental support for physical activity closer to concentrated areas of population does not necessarily equate to more use. It is important that areas with increased population density have correspondingly increased levels of land-use mixture if increasing physical activity is the goal.

B. de Geus, I. De Bourdeaudhuij, C. Jannes and R. Meeusen. (2008). Psychosocial and environmental factors associated with cycling for transport among a working population. Health Education Research. 23, 697-708.

The aim of this study was to examine psychosocial and environmental predictors of cycling for transportation. A sample of 343 Flemish adults (43% men) living at maximum 10 km from their workplace was surveyed. Self-report measures of cycling, demographic variables, psychosocial variables, self-efficacy, perceived benefits and barriers and environmental attributes (destination, traffic variables and facilities at the workplace) of cycling for transport were obtained by means of a mailing questionnaire. Modeling and social support by accompanying, external self-efficacy, ecological-economic awareness and lack of time and interest were positively associated with the likelihood of cycling for transport and varied in importance between cyclists and non-cyclists. Cyclists estimate the time to destination shorter than non-cyclists and indicate to have more facilities for cyclists at the workplace. The results suggest that when people live in a setting with adequate bicycle infrastructure, individual determinants (psychosocial, self-efficacy, perceived benefits and barriers) outperform the role of environmental determinants in this sample. Promotion campaigns aimed at increasing cycling for transportation should focus on creating social support by encouraging cycling with partners, increasing self-efficacy, raising ecological and economic awareness, decreasing lack of time and interest barriers and providing facilities for cyclists at the workplace.

G. E. Duncan, J. Goldberg, C. Noonan, A. V. Moudon, P. Hurvitz and D. Buchwald. (2008). Unique environmental effects on physical activity participation: a twin study. PLoS ONE. 3, e2019.

BACKGROUND: The health benefits of regular physical activity are well established. However, the relative contribution of heritable and environmental factors to physical activity participation remains controversial. Using a cut-point of 60 minutes of total activity per week, data from the GenomEUtwin project revealed consistent genetic influence on physical activity participation in 37,051 twin pairs from seven countries. We hypothesized that the heritability of physical activity participation would be attenuated using the CDC/ACSM recommended minimum threshold of 150 minutes of moderate intensity activity per week. METHODS: Data were obtained from 1,389 twin pairs from the community-based University of Washington Twin Registry. Twin similarity in physical activity participation using both cut-points was analyzed using tetrachoric correlations and structural equation modeling in all same-sex pairs. RESULTS: Correlations were higher in monozygotic (r(MZ) = 0.43, 95% CI = 0.33-0.54) than dizygotic pairs (r(DZ) = 0.30, 95% CI = 0.12-0.47) using the 60 minute cut-point. However, differences were attenuated using the 150 minute standard (r(MZ) = 0.30, 95% CI = 0.20-0.40; r(DZ) = 0.25, 95% CI = 0.07-0.42). Using the lower cut-point, the best fitting model of twin resemblance only included additive genetics and unique environment, with a heritability of 45%. In contrast, using the higher threshold, the best fitting model included the common and unique environment, with the unique environment contributing 72% of the variance. CONCLUSION: Unique environment factors provide the strongest influence on physical activity participation at levels recommended for health benefits.

M. Z. Dunn. (2008). Psychosocial mediators of a walking intervention among African American women. Journal Of Transcultural Nursing. 19, 40-46.

Many Americans are sedentary and would reduce their disease risk if they increased their levels of physical activity to 30 minutes of moderate activity most days of the week. This descriptive exploratory study addresses how to maximize adherence to a physical activity prescription. A sample of 14 older African American women enrolled in a walking intervention study participated in three focus-group discussions of barriers to and facilitators of walking. Focus groups were audiotaped, transcribed, and examined by three nurse researchers using analytic induction, content analysis, and grounded theory techniques. Women who participated in the focus-group discussions identified lack of family support, perceived or real family obligations, personal health status, and neighborhood safety as factors influencing adherence to physical activity. A necessary component of successful walking maintenance was the confidence and support of the woman's family. The most compelling reason for continued walking in this group was to help others.

J. Eid, H. G. Overman, D. Puga and M. A. Turner. (2008). Fat city: Questioning the relationship between urban sprawl and obesity. Journal Of Urban Economics. 63, 385-404.

We study the relationship between urban sprawl and obesity. Using data that tracks individuals over time, we find no evidence that urban sprawl causes obesity. We show that previous findings of a positive relationship most likely reflect a failure to properly control for the fact the individuals who are more likely to be obese choose to live in more sprawling neighborhoods. Our results indicate that current interest in changing the built environment to counter the rise in obesity is misguided. (C) 2008 Elsevier Inc. All rights reserved.

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