Ana Isabel Ribeiro1,2, Ana Cristina Santos1,2, Verónica M Vieira3, Henrique Barros1,2. 1. EPIUnit-Instituto de Saúde Pública, Universidade do Porto, Porto, Portugal. 2. Department of Public Health, Forensic Sciences and Medical Education, University of Porto Medical School, Porto, Portugal. 3. Program in Public Health, Susan and Henry Samueli College of Health Sciences, University of California, Irvine, CA, USA.
Abstract
BACKGROUND: Effective place-based interventions for childhood obesity call for the recognition of the high-risk neighbourhoods and an understanding of the determinants present locally. However, such an approach is uncommon. In this study, we identified neighbourhoods with elevated prevalence of childhood obesity ('hotspots') in the Porto Metropolitan Area and investigated to what extent the socio-economic and built environment characteristics of the neighbourhoods explained such hotspots. METHODS: We used data on 5203 7-year-old children from a population-based birth cohort, Generation XXI. To identify hotspots, we estimated local obesity odds ratios (OR) and 95% confidence intervals (95%CI) using generalized additive models with a non-parametric smooth for location. Measures of the socio-economic and built environment were determined using a Geographic Information System. Associations between obesity and neighbourhood characteristics were expressed as OR and 95%CI after accounting for individual-level variables. RESULTS: At 7 years of age, 803 (15.4%) children were obese. The prevalence of obesity varied across neighbourhoods and two hotspots were identified, partially explained by individual-level variables. Adjustment for neighbourhood characteristics attenuated the ORs and further explained the geographic variation. This model revealed an association between neighbourhood socio-economic deprivation score and obesity (OR = 1.014, 95%CI 1.004-1.025), as well as with the presence of fast-food restaurants at a walkable distance from the residence (OR = 1.37, 1.06-1.77). CONCLUSIONS: In our geographic area it was possible to identify neighbourhoods with elevated prevalence of childhood obesity and to suggest that targeting such high-priority neighbourhoods and their environmental characteristics may help reduce childhood obesity.
BACKGROUND: Effective place-based interventions for childhood obesity call for the recognition of the high-risk neighbourhoods and an understanding of the determinants present locally. However, such an approach is uncommon. In this study, we identified neighbourhoods with elevated prevalence of childhood obesity ('hotspots') in the Porto Metropolitan Area and investigated to what extent the socio-economic and built environment characteristics of the neighbourhoods explained such hotspots. METHODS: We used data on 5203 7-year-old children from a population-based birth cohort, Generation XXI. To identify hotspots, we estimated local obesity odds ratios (OR) and 95% confidence intervals (95%CI) using generalized additive models with a non-parametric smooth for location. Measures of the socio-economic and built environment were determined using a Geographic Information System. Associations between obesity and neighbourhood characteristics were expressed as OR and 95%CI after accounting for individual-level variables. RESULTS: At 7 years of age, 803 (15.4%) children were obese. The prevalence of obesity varied across neighbourhoods and two hotspots were identified, partially explained by individual-level variables. Adjustment for neighbourhood characteristics attenuated the ORs and further explained the geographic variation. This model revealed an association between neighbourhood socio-economic deprivation score and obesity (OR = 1.014, 95%CI 1.004-1.025), as well as with the presence of fast-food restaurants at a walkable distance from the residence (OR = 1.37, 1.06-1.77). CONCLUSIONS: In our geographic area it was possible to identify neighbourhoods with elevated prevalence of childhood obesity and to suggest that targeting such high-priority neighbourhoods and their environmental characteristics may help reduce childhood obesity.
Authors: Andrey I Egorov; Shannon M Griffin; Reagan R Converse; Jennifer N Styles; Elizabeth Klein; James Scott; Elizabeth A Sams; Edward E Hudgens; Timothy J Wade Journal: Environ Res Date: 2020-04-07 Impact factor: 6.498
Authors: Inês Paciência; André Moreira; João Cavaleiro Rufo; Ana Cristina Santos; Henrique Barros; Ana Isabel Ribeiro Journal: J Urban Health Date: 2022-01-23 Impact factor: 5.801