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P1-319 A multilevel approach for studying the association between neighbourhood characteristics and self-rated health in the Brazilian PrÓ-saÚde study

Bibliographic Data

ID11176928
AuthorsSimone C Dos Santos (0000-0002-7903-9981, Fundação Oswaldo Cruz), S Santos (0000-0003-2637-3449), Dóra Chor (0000-0002-3941-5786, Fundação Oswaldo Cruz), Guilherme Loureiro Werneck (0000-0003-1169-1436, Universidade do Estado do Rio de Janeiro), G Werneck, C Lopes (0000-0002-8635-5675), Claudia De Souza Lopes (0000-0002-0401-689X, Universidade do Estado do Rio de Janeiro), Eduardo Faerstein (0000-0002-4027-4896, Universidade do Estado do Rio de Janeiro)
Year2011
Volume65
IssueSuppl 1
PagesA156.1-A156
Publication date2011-08-01
Open AccessNo
TypeARTICLE
VenueJournal of Epidemiology and Community Health (JOURNAL)
Journal identifiersISSN: 0143-005X • E-ISSN: 1470-2738
PublisherBMJ (PUBLISHER • GB)
DOI10.1136/jech.2011.142976f.11
OpenAlexW2313739097
LanguageEN

Introduction Few studies examine the influence of neighbourhood characteristics on self-rated health (SRH), particularly in middle-income countries such as Brazil. We examine the association between neighbourhood of residence indicators of socioeconomic position and individual self-rated health in the Pró-Saúde cohort study, adjusting for group and individual characteristics. Methods A multilevel approach using hierarchical modelling was applied to analyse the relationship between neighbourhood indicators of socioeconomic position and self-rated health in 3054 University employees living in Rio de Janeiro city who participate in the Pró-Saúde study. Neighbourhoods (n=621) were created using the SKATER algorithm, a tool for area regionalisation to group small areas (TerraView software). Census tracts were grouped based on four census tract indicators and a minimum population of 5000 living in the delimited neighbourhood. Results Adjusting for individual factors, such as individual income per capita, educational level, age, sex, ethnicity, health related behaviours and the presence of chronic diseases, low neighbourhood income level and a higher number of inhabitants per residence were significantly associated with poor SRH. Subjects living in neighbourhoods with medium income level were 34% more likely to rated their health as poor. Those living in areas with a higher density of persons per household were 50% more likely to report poor SRH. Conclusion Following adjustment for individuals factors neighbourhood context influenced SRH in this study; poor neighbourhood socioeconomic conditions are associated with poor SRH

Census tract · Environmental health · Geography · Multilevel model · Neighbourhood (mathematics) · Population · Residence · Self-rated health · Socioeconomic status · Sociology · Demography · Global Public Health Policies and Epidemiology · Health disparities and outcomes · Medicine · Gerontology

Highly citedNo

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