Is neighbourhood obesogenicity associated with body mass index in women? Application of an obesogenicity index in socioeconomically disadvantaged neighbourhoods

Tseng, Marilyn; Thornton, Lukar; Lamb, Karen E.; Ball, Kylie; Crawford, David

doi:10.1016/j.healthplace.2014.07.012

Cited by 23 publications

(28 citation statements)

References 54 publications

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“…This will capture place‐specific dynamics that structure the potential relation between built environment, obesity‐related behaviours and obesity, often oversimplified in existing literature . This corroborates the conclusions of previous studies addressing obesogenic environments in urban contexts and shows the importance of factor and cluster analyses to quantify such multifactorial, complex local contexts .…”

Section: Discussionsupporting

confidence: 82%

“…fast food restaurants) are the most available. These findings suggest that different obesogenic dimensions of the built environment should be considered together, as counteracting features may exist in the same neighbourhood (34). We should therefore recognize the multifaceted spatial interactions between environmental features rather than seeing them in isolation (35).…”

Section: Discussionmentioning

confidence: 99%

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Neighbourhood typology based on virtual audit of environmental obesogenic characteristics

et al. 2016

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SummaryVirtual audit (using tools such as Google Street View) can help assess multiple characteristics of the physical environment. This exposure assessment can then be associated with health outcomes such as obesity. Strengths of virtual audit include collection of large amount of data, from various geographical contexts, following standard protocols. Using data from a virtual audit of obesity-related features carried out in five urban European regions, the current study aimed to (i) describe this international virtual audit dataset and (ii) identify neighbourhood patterns that can synthesize the complexity of such data and compare patterns across regions. Data were obtained from 4,486 street segments across urban regions in Belgium, France, Hungary, the Netherlands and the UK. We used multiple factor analysis and hierarchical clustering on principal components to build a typology of neighbourhoods and to identify similar/dissimilar neighbourhoods, regardless of region. Four neighbourhood clusters emerged, which differed in terms of food environment, recreational facilities and active mobility features, i.e. the three indicators derived from factor analysis. Clusters were unequally distributed across urban regions. Neighbourhoods mostly characterized by a high level of outdoor recreational facilities were predominantly located in Greater London, whereas neighbourhoods characterized by high urban density and large amounts of food outlets were mostly located in Paris. Neighbourhoods in the Randstad conurbation, Ghent and Budapest appeared to be very similar, characterized by relatively lower residential densities, greener areas and a very low percentage of streets offering food and recreational facility items. These results provide multidimensional constructs of obesogenic characteristics that may help target at-risk neighbourhoods more effectively than isolated features.

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Section: Discussionsupporting

confidence: 82%

Section: Discussionmentioning

confidence: 99%

Neighbourhood typology based on virtual audit of environmental obesogenic characteristics

et al. 2016

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“…Furthermore, more geospatial data are becoming available to assess neighborhood environments, although the majority of these data resources are not developed specifically for assessing social and built environments or linking to health outcomes. By using the available data, areas have been characterized with walkability measures, food environment measures, omnidirectional imagery data using Google Street View, and other scores/indices developed by private and public entities . Using scores can require more sophisticated analytical measures that take into consideration spatial autocorrelation, density or exposures, and changes over time (eg, stores opening or closing, changes in zoning) .…”

Section: Discussionmentioning

confidence: 99%

The impact of neighborhood social and built environment factors across the cancer continuum: Current research, methodological considerations, and future directions

Gomez

Shariff‐Marco

DeRouen

et al. 2015

Cancer

244

249

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Neighborhood social and built environments have been recognized as important contexts in which health is shaped. We review the extent to which these neighborhood factors have been addressed in population-level cancer research, with a scan of the literature for research that focuses on specific social and/or built environment characteristics and association with outcomes across the cancer continuum, including incidence, diagnosis, treatment, survivorship, and survival. We discuss commonalities and differences in methodologies across studies, current challenges in research methodology, and future directions in this research area. The assessment of social and built environment factors in relation to cancer is a relatively new field, with 82% of 34 reviewed papers published since 2010. Across the wide range of social and built environment exposures and cancer outcomes considered by the studies, numerous associations were reported. However, the directions and magnitudes of association varied, due in large part to the variation in cancer sites and outcomes being studied, but also likely due to differences in study populations, geographical region, and, importantly, choice of neighborhood measure and geographic scale. We recommend that future studies consider the life course implications of cancer incidence and survival, integrate secondary and self-report data, consider work neighborhood environments, and further develop analytical and statistical approaches appropriate to the geospatial and multilevel nature of the data. Incorporating social and built environment factors into research on cancer etiology and outcomes can provide insights into disease processes, identify vulnerable populations, and generate results with translational impact of relevance for interventionists and policy makers.

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“…Health concerns for this increasingly urban population include sedentary lifestyles that contribute to obesity and associated illnesses (e.g., diabetes, hypertension, cardiovascular disease) (Tamosiunas et al, 2014, Tseng et al, 2014, Groth et al, 2015, Koohsari et al, 2015). Urban greenspaces may influence weight status and are increasingly identified as valuable resources for supporting active lifestyles and enhancing health.…”

Section: Introductionmentioning

confidence: 99%

Varying age-gender associations between body mass index and urban greenspace

Sander

Ghosh

Hodson

2017

Urban Forestry & Urban Greening

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Urban greenspace benefits urbanites in numerous ways ranging from regulating flooding, air quality, and local climate to providing opportunities for exercise and relaxation. These benefits may influence human health. Greenspace, for example, may facilitate exercise, thereby helping to reduce body mass index (BMI) and combat obesity, a current epidemic of great public health concern. Little evidence exists to support this assertion, however, and we lack a full understanding of the mechanisms whereby this relationship operates, the populations for whom greenspace is linked to weight status, and the aspects of urban greenspace that are linked to weight status. This study seeks to identify relationships among the composition and arrangement of greenspace and BMI for different populations using regression models for eight age and gender groups in Cleveland, Ohio, US. We find that several greenspace variables are related to BMI for women under 65 years and males under 51 years, but not for older groups, and that the aspects and types of greenspace that are significantly related to BMI vary among groups. Relationships between greenspace attributes and BMI are generally stronger for female groups and for younger groups. Providing access to greenspace with particular attributes such as greenspaces with water, canopy cover, or connected greenspaces could support a healthy weight status for some populations, but these attributes are not consistent across age and gender groups. These results could help to inform policy aimed at designing urban greenspace to benefit the health of different population subgroups.

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Is neighbourhood obesogenicity associated with body mass index in women? Application of an obesogenicity index in socioeconomically disadvantaged neighbourhoods

Cited by 23 publications

References 54 publications

Neighbourhood typology based on virtual audit of environmental obesogenic characteristics

Neighbourhood typology based on virtual audit of environmental obesogenic characteristics

The impact of neighborhood social and built environment factors across the cancer continuum: Current research, methodological considerations, and future directions

Varying age-gender associations between body mass index and urban greenspace

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