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https://hdl.handle.net/10216/143203Full metadata record
| DC Field | Value | Language |
|---|---|---|
| dc.creator | Ribeiro, AI | |
| dc.creator | Santos, AC | |
| dc.creator | Vieira, VM | |
| dc.creator | Barros, H | |
| dc.date.accessioned | 2022-08-23T14:45:39Z | - |
| dc.date.available | 2022-08-23T14:45:39Z | - |
| dc.date.issued | 2020 | |
| dc.identifier.issn | 0300-5771 | |
| dc.identifier.issn | 1464-3685 | |
| dc.identifier.uri | https://hdl.handle.net/10216/143203 | - |
| dc.description.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. | |
| dc.description.sponsorship | This study was funded by the European Regional Development Fund (FEDER) through the Operational Programme Competitiveness and Internationalization and national funding from the Foundation for Science and Technology–FCT (Portuguese Ministry of Science, Technology and Higher Education) under the Unidade de Investigação em Epidemiologia-Instituto de Saúde Pública da Universidade do Porto (EPIUnit) (POCI-01-0145-FEDER-006862; Ref. UID/DTP/04750/2013) and under the scope of the projects ‘EXALAR 21—The influence of exposure to urban air pollutants, green and blue spaces, and biodiversity on the development of allergic diseases and asthma in children: a life-course and eco-social approach’ (POCI-01-0145-FEDER-030193—PTDC/GES-AMB/30193/2017), ‘Pathways from early life to cardiometabolic risk during childhood’ (POCI-01-0145-FEDER-016837 - PTDC/DTP-EPI/3306/2014) and ‘How childhood social adversity shapes health: The biology of social adversity. ‘(POCI-01-0145-FEDER-016838 - PTDC/DTP-EPI/1687/2014). G21 was funded by Programa Operacional de Saúde – Saúde XXI, Quadro Comunitário de Apoio III and Administração Regional de Saúde Norte (Regional Department of Ministry of Health). It has also support from the Portuguese Foundation for Science and Technology and from the Calouste Gulbenkian Foundation. V.M.V. was supported by the US National Institute of Environmental Health Sciences (NIEHS), National Institutes of Health (NIH) under grant number P42 ES007381. Its contents are solely the responsibility of the authors and do not necessarily represent the views of NIH. A.C.S. was supported by the FCT Investigator contract IF/01060/2015. | |
| dc.language.iso | eng | |
| dc.publisher | Oxford University Press | |
| dc.relation | info:eu-repo/grantAgreement/FCT/6817 - DCRRNI ID/UID/DTP/04750/2013/PT | |
| dc.relation | info:eu-repo/grantAgreement/FCT/9471 - RIDTI/PTDC/GES-AMB/30193/2017/PT | |
| dc.relation | info:eu-repo/grantAgreement/FCT/9471 - RIDTI/PTDC/DTP-EPI/3306/2014/PT | |
| dc.relation | info:eu-repo/grantAgreement/FCT/9471 - RIDTI/PTDC/DTP-EPI/1687/2014/PT | |
| dc.relation | info:eu-repo/grantAgreement/FCT/Investigador FCT/IF/01060/2015/CP1319/FCT0001/PT | |
| dc.relation.ispartof | Int J Epidemiol. 2020 Jun 1;49(3):934-943 | |
| dc.rights | openAccess | |
| dc.rights.uri | https://creativecommons.org/licenses/by/4.0/ | |
| dc.subject | Spatial analysis | |
| dc.subject | childhood obesity | |
| dc.subject | built environment | |
| dc.subject | socio-economic factors | |
| dc.subject | neighbourhoods | |
| dc.title | Hotspots of childhood obesity in a large metropolitan area: does neighbourhood social and built environment play a part? | |
| dc.type | Artigo em Revista Científica Internacional | |
| dc.contributor.uporto | Instituto de Saúde Pública da Universidade do Porto | |
| dc.identifier.doi | 10.1093/ije/dyz205 | |
| dc.relation.publisherversion | https://academic.oup.com/ije/article/49/3/934/5585655#206048780 | |
| Appears in Collections: | ISPUP - Artigo em Revista Científica Internacional | |
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|---|---|---|---|---|
| ribeiro-ije-2020.pdf | 520.42 kB | Adobe PDF | ![]() View/Open |
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