Neighbourhood effects in health behaviours: a test of social causation with repeat-measurement longitudinal data

Eur J Public Health. 2016 Jun;26(3):417-21. doi: 10.1093/eurpub/ckv210. Epub 2015 Nov 14.


Background: Neighbourhood characteristics have been associated with health behaviours of residents. We used longitudinal data to examine whether neighbourhood characteristics (level of urbanization and socioeconomic status) are related to within-individual variations in health behaviours (alcohol consumption, smoking, exercise and self-interest in health) as people live in different neighbourhoods over time.

Methods: Participants were from the Young Finns prospective cohort study (N = 3145) with four repeated measurement times (1992, 2001, 2007 and 2011/2012). Neighbourhood socioeconomic status and level of urbanization were measured on the level of municipality and zip code area. Within-individual (i.e. fixed-effect) regression was used to examine whether these associations were observed within individuals who lived in different neighbourhood in different measurement times.

Results: People living in more urban zip code areas were more likely to smoke (b = 0.06; CI = 0.03-0.09) and drink alcohol (b = 0.11; CI = 0.08-0.14), and these associations were replicated in within-individual analysis-supporting social causation. Neighbourhood socioeconomic status and urbanization were associated with higher interest in maintaining personal health (b = 0.05; CI = 0.03-0.08 and b = 0.05; CI = 0.02-0.07, respectively), and these associations were also similar in within-individual analysis. Physical exercise was not associated with neighbourhood characteristics.

Conclusions: These data lend partial support for the hypothesis that neighbourhood differences influence people's health behaviours.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Adolescent
  • Adult
  • Child
  • Child, Preschool
  • Cohort Studies
  • Female
  • Finland
  • Health Behavior*
  • Humans
  • Longitudinal Studies
  • Male
  • Prospective Studies
  • Residence Characteristics / statistics & numerical data*
  • Risk Factors
  • Social Class
  • Social Environment*
  • Socioeconomic Factors