2020
DOI: 10.1186/s12889-020-09509-4
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Cross-sectional associations between the neighborhood built environment and physical activity in a rural setting: the Bogalusa Heart Study

Abstract: Background Insufficient physical activity (PA) is a common health risk and more prevalent in rural populations. Few studies have assessed relationships between the built environment and PA in rural settings, and community policy guidance to promote PA through built environment interventions is primarily based on evidence from urban studies. Methods Participants in the Bogalusa Heart Study, a longitudinal study in rural Louisiana, with International Physical Activity Questionnaire data from 2012 to 2013 and a… Show more

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Cited by 8 publications
(12 citation statements)
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References 30 publications
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“…We evaluated cross-sectional and longitudinal associations between structural features of the rural built environment and depressive symptoms among participants in the Bogalusa Heart Study. Previous research in this population identified significant associations between scores for features of the neighborhood built environment and physical activity ( 11 ). We hypothesized that higher scores (environments more conducive to physical activity) would be associated with lower baseline prevalence of depression and lower depression incidence and that these associations would be mediated by physical activity.…”
Section: Introductionmentioning
confidence: 84%
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“…We evaluated cross-sectional and longitudinal associations between structural features of the rural built environment and depressive symptoms among participants in the Bogalusa Heart Study. Previous research in this population identified significant associations between scores for features of the neighborhood built environment and physical activity ( 11 ). We hypothesized that higher scores (environments more conducive to physical activity) would be associated with lower baseline prevalence of depression and lower depression incidence and that these associations would be mediated by physical activity.…”
Section: Introductionmentioning
confidence: 84%
“…We developed scales for built environment overall in 6 domains of street segment features identified a priori and refined following principal components analysis. This process has been reported in detail elsewhere ( 11 ). Briefly, scales were developed by creating 1 variable for features that were assessed across multiple RALA variables (eg, sidewalks, paths), with all variables coded so higher values indicated features that promote physical activity.…”
Section: Methodsmentioning
confidence: 96%
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“…In the majority of existing studies, the evaluation of living street space is conducted from two perspectives. The primary objective is to develop an evaluation system based on semantic segmentation of street physical environment elements extracted from street view images (SVIs) [11][12][13]. The second objective is to quantify the subjective human reaction to SVIs using measurements derived from deep learning technology [14][15][16].…”
Section: Introductionmentioning
confidence: 99%