1,243 research outputs found

    Associations among neighborhood socioeconomic deprivation, physical activity facilities, and physical activity in youth during the transition from childhood to adolescence

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    BACKGROUND: This study aims to examine the longitudinal association of neighborhood socioeconomic deprivation (SED) with physical activity in youth during the transition from elementary to middle school, and to determine if access to physical activity facilities moderates this relationship. METHODS: Data were obtained from the Transitions and Activity Changes in Kids (TRACK) study, which was a multilevel, longitudinal study designed to identify the factors that influence changes in physical activity as youth transition from elementary to middle school. The analytic sample for the current study included 660 youth with complete data in grades 5 (baseline) and 7 (follow-up). A repeated measures multilevel framework was employed to examine the relationship between SED and physical activity over time and the potential moderating role of elements of the built environment. RESULTS: Decreases in physical activity varied by the degree of neighborhood SED with youth residing in the most deprived neighborhoods experiencing the greatest declines in physical activity. Access to supportive physical activity facilities did not moderate this relationship. CONCLUSION: Future research studies are needed to better understand how neighborhood SED influences youth physical activity over time

    Distribution of physical activity facilities in Scotland by small area measures of deprivation and urbanicity.

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    BACKGROUND: The aim of this study was to examine the distribution of physical activity facilities by area-level deprivation in Scotland, adjusting for differences in urbanicity, and exploring differences between and within the four largest Scottish cities. METHODS: We obtained a list of all recreational physical activity facilities in Scotland. These were mapped and assigned to datazones. Poisson and negative binomial regression models were used to investigate associations between the number of physical activity facilities relative to population size and quintile of area-level deprivation. RESULTS: The results showed that prior to adjustment for urbanicity, the density of all facilities lessened with increasing deprivation from quintiles 2 to 5. After adjustment for urbanicity and local authority, the effect of deprivation remained significant but the pattern altered, with datazones in quintile 3 having the highest estimated mean density of facilities. Within-city associations were identified between the number of physical activity facilities and area-level deprivation in Aberdeen and Dundee, but not in Edinburgh or Glasgow. CONCLUSIONS: In conclusion, area-level deprivation appears to have a significant association with the density of physical activity facilities and although overall no clear pattern was observed, affluent areas had fewer publicly owned facilities than more deprived areas but a greater number of privately owned facilities.RIGHTS : This article is licensed under the BioMed Central licence at http://www.biomedcentral.com/about/license which is similar to the 'Creative Commons Attribution Licence'. In brief you may : copy, distribute, and display the work; make derivative works; or make commercial use of the work - under the following conditions: the original author must be given credit; for any reuse or distribution, it must be made clear to others what the license terms of this work are

    Public open spaces and physical activity: disparities of resources in Florianópolis

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    ABSTRACT OBJECTIVE: To analyze the association between sociodemographic characteristics of census tracts and the presence/quality of public open spaces and physical activity facilities. METHODS: A cross-sectional study was conducted in 643 census tracts in Florianópolis, Brazil, the presence and quality of public open spaces and physical activity facilities were objectively analyzed and the data by census tracts using Geographic Information Systems was treated. Outcomes were analyzed considering the census tracts as having: ≥ 1 public open spaces; ≥ 1 public open spaces with high quality; ≥ 2 physical activity facilities and high-quality physical activity facilities. Sociodemographic characteristics were the independent variables. Logistic regression analysis was performed. RESULTS: Census tracts with a medium-income (OR = 1.8; 95%CI 1.1–3.0) and high-income (OR = 2.4; 95%CI 1.4–4.0), in those with medium (OR = 1.7; 95%CI 1.0–2.7) and high residential density (OR = 2.0; 95%CI 1,2–3.3), and with higher proportions of older adults (OR = 3.3; 95%CI 1.9–5.7) had a higher proportion of public open spaces. Census tracts with higher proportions of children/adolescents (OR = 0.3; 95%CI 0.2–0.6) and non-white residents (OR= 0.6; 95%CI 0.3–0.9) were less likely to contain public open spaces. The tracts with medium (OR = 4.0; 95%CI 1.4–11.3) and high-income (OR = 3.6; 95%CI 1.2–10.2) were more likely to contain public open spaces with ≥ 2 structures for physical activity, compared with those with low-income. We observed the inverse in sectors with a high proportion of non-white residents (OR = 0.3; 95%CI 0.1–0.9). CONCLUSIONS: Census tracts with higher proportions of children or adolescents, non-white individuals and those in the low-income strata had lower odds of containing public open spaces and physical activity facilities

    Do Physical Activity Facilities near Schools Affect Physical Activity in High School Girls?

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    Objective - To investigate associations between the number of physical activity facilities within walking distance of school and physical activity behavior in 12th grade girls during after-school hours. Methods - Girls (N=1394) from 22 schools completed a self-report to determine physical activity after 3:00 pm. The number of physical activity facilities within a 0.75-mile buffer of the school was counted with a Geographic Information System. Associations between the number of facilities and girls\u27 physical activity were examined using linear mixed-model analysis of variance. Results - Overall, girls who attended schools with ≥ 5 facilities within the buffer reported more physical activity per day than girls in schools with \u3c 5 facilities. In addition, girls who attended rural schools with ≥ 5 facilities reported ~12% more physical activity per day than girls who attended rural schools with \u3c 5 facilities. No difference existed for girls in urban/suburban schools with ≥ 5 vs. \u3c 5 facilities. Conclusion - When school siting decisions are made, the number of physical activity facilities surrounding the school should be considered to encourage physical activity in 12th grade girls

    Genetic risk of obesity as a modifier of associations between neighbourhood environment and body mass index. An observational study of 335 046 UK Biobank participants

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    Background There is growing recognition that recent global increases in obesity are the product of a complex interplay between genetic and environmental factors. However, in gene-environment studies of obesity, ‘environment’ usually refers to individual behavioural factors that influence energy balance, whereas more upstream environmental factors are overlooked. We examined gene-environment interactions between genetic risk of obesity and two neighbourhood characteristics likely to be associated with obesity (proximity to takeaway/ fast-food outlets and availability of physical activity facilities). Methods We used data from 335 046 adults aged 40–70 in the UK Biobank cohort to conduct a populationbased cross-sectional study of interactions between neighbourhood characteristics and genetic risk of obesity, in relation to body mass index (BMI). Proximity to a fast-food outlet was defined as distance from home address to nearest takeaway/fast-food outlet, and availability of physical activity facilities as the number of formal physical activity facilities within 1 km of home address. Genetic risk of obesity was operationalised by weighted Genetic Risk Scores of 91 or 69 single nucleotide polymorphisms (SNP), and by six individual SNPs considered separately. Multivariable, mixed-effects models with product terms for the gene-environment interactions were estimated. Results After accounting for likely confounding, the association between proximity to takeaway/fast-food outlets and BMI was stronger among those at increased genetic risk of obesity, with evidence of an interaction with polygenic risk scores (p=0.018 and p=0.028 for 69- SNP and 91-SNP scores, respectively) and in particular with a SNP linked to MC4R (p=0.009), a gene known to regulate food intake. We found very little evidence of geneenvironment interaction for the availability of physical activity facilities. Conclusions Individuals at an increased genetic risk of obesity may be more sensitive to exposure to the local fast-food environment. Ensuring that neighbourhood residential environments are designed to promote a healthy weight may be particularly important for those with greater genetic susceptibility to obesity

    Validation of a GIS Facilities Database: Quantification and Implications of Error

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    To validate a commercial database of community-level physical activity facilities that can be used in future research examining associations between access to physical activity facilities and individual-level physical activity and obesity

    Associations between access to recreational physical activity facilities and body mass index in Scottish adults.

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    BACKGROUND: The aim of this country-wide study was to link individual health and behavioural data with area-level spatial data to examine whether the body mass index (BMI) of adults was associated with access to recreational physical activity (PA) facilities by different modes of transport (bus, car, walking, cycling) and the extent to which any associations were mediated by PA participation. METHODS: Data on individual objectively-measured BMI, PA (number of days of (a) ≥20 min of moderate-to-vigorous PA, and (b) ≥15 min of sport or exercise, in previous 4 weeks), and socio-demographic characteristics were obtained from a nationally representative sample of 6365 adults. The number of accessible PA facilities per 1,000 individuals in each small area (data zones) was obtained by mapping a representative list of all fixed PA facilities throughout mainland Scotland. A novel transport network was developed for the whole country, and routes on foot, by bike, by car and by bus from the weighted population centroid of each data zone to each facility were calculated. Separate multilevel models were fitted to examine associations between BMI and each of the 24 measures of accessibility of PA facilities and BMI, adjusting for age, gender, longstanding illness, car availability, social class, dietary quality and urban/rural classification. RESULTS: We found associations (p < 0.05) between BMI and 7 of the 24 accessibility measures, with mean BMI decreasing with increasing accessibility of facilities-for example, an estimated decrease of 0.015 BMI units per additional facility within a 20-min walk (p = 0.02). None of these accessibility measures were found to be associated with PA participation. CONCLUSIONS: Our national study has shown that some measures of the accessibility of PA facilities by different modes of transport (particularly by walking and cycling) were associated with BMI; but PA participation, as measured here, did not appear to play a part in this relationship. Understanding the multi-factorial environmental influences upon obesity is key to developing effective interventions to reduce it

    Genetic risk of obesity as a modifier of associations between neighbourhood environment and body mass index: an observational study of 335 046 UK Biobank participants.

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    BackgroundThere is growing recognition that recent global increases in obesity are the product of a complex interplay between genetic and environmental factors. However, in gene-environment studies of obesity, 'environment' usually refers to individual behavioural factors that influence energy balance, whereas more upstream environmental factors are overlooked. We examined gene-environment interactions between genetic risk of obesity and two neighbourhood characteristics likely to be associated with obesity (proximity to takeaway/fast-food outlets and availability of physical activity facilities).MethodsWe used data from 335 046 adults aged 40-70 in the UK Biobank cohort to conduct a population-based cross-sectional study of interactions between neighbourhood characteristics and genetic risk of obesity, in relation to body mass index (BMI). Proximity to a fast-food outlet was defined as distance from home address to nearest takeaway/fast-food outlet, and availability of physical activity facilities as the number of formal physical activity facilities within 1 km of home address. Genetic risk of obesity was operationalised by weighted Genetic Risk Scores of 91 or 69 single nucleotide polymorphisms (SNP), and by six individual SNPs considered separately. Multivariable, mixed-effects models with product terms for the gene-environment interactions were estimated.ResultsAfter accounting for likely confounding, the association between proximity to takeaway/fast-food outlets and BMI was stronger among those at increased genetic risk of obesity, with evidence of an interaction with polygenic risk scores (p=0.018 and p=0.028 for 69-SNP and 91-SNP scores, respectively) and in particular with a SNP linked to MC4R (p=0.009), a gene known to regulate food intake. We found very little evidence of gene-environment interaction for the availability of physical activity facilities.ConclusionsIndividuals at an increased genetic risk of obesity may be more sensitive to exposure to the local fast-food environment. Ensuring that neighbourhood residential environments are designed to promote a healthy weight may be particularly important for those with greater genetic susceptibility to obesity
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