Article Text

Download PDFPDF

Epidemiology and policy
P1-319 A multilevel approach for studying the association between neighbourhood characteristics and self-rated health in the Brazilian PrÓ-saÚde study
  1. S Santos1,
  2. D Chor1,
  3. G Werneck1,2,
  4. C Lopes2,
  5. E Faerstein2
  1. 1National School of Public Health, Oswaldo Cruz Foundation, Rio de Janeiro, Brazil
  2. 2Social Medicine Institute, Rio de Janeiro Satate University, Rio de Janeiro, Brazil


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.

Statistics from

Request Permissions

If you wish to reuse any or all of this article please use the link below which will take you to the Copyright Clearance Center’s RightsLink service. You will be able to get a quick price and instant permission to reuse the content in many different ways.