title: Change in Neighborhood Disadvantage and Change in Smoking Behaviors in Adults: A Longitudinal, Within-individual Study.
abstract: Evidence for an association between neighborhood disadvantage and smoking is mixed and mainly based on cross-sectional studies. To shed light on the causality of this association, we examined whether change in neighborhood socioeconomic disadvantage is associated with within-individual change in smoking behaviors.
  
  
  
  The study population comprised participants of the Finnish Public Sector study who reported a change in their smoking behavior between surveys in 2008/2009 and 2012/2013. We linked participants' residential addresses to a total population database on neighborhood disadvantage with 250 × 250-m resolution. The outcome variables were changes in smoking status (being a smoker vs. not) as well as the intensity (heavy/moderate vs. light smoker). We used longitudinal case-crossover design, a method that accounts for time-invariant confounders by design. We adjusted models for time-varying covariates.
  
  
  
  Of the 3,443 participants, 1,714 quit, while 967 began to smoke between surveys. Smoking intensity increased among 398 and decreased among 364 participants. The level of neighborhood disadvantage changed for 1,078 participants because they moved residence. Increased disadvantage was associated with increased odds of being a smoker (odds ratio of taking up smoking 1.23 [95% confidence interval: 1.2, 1.5] per 1 SD increase in standardized national disadvantage score). Odds ratio for being a heavy/moderate (vs. light) smoker was 1.14 (95% confidence interval: 0.85, 1.52) when disadvantage increased by 1 SD.
  
  
  
  These within-individual results link an increase in neighborhood socioeconomic disadvantage, due to move in residence, with subsequent smoking behaviors.
authors.affiliation: From the aFinnish Institute of Occupational Health, Helsinki, Finland; bDepartment of Public Health, University of Turku, Turku, Finland; cSchool of Health Sciences, University of Tampere, Tampere, Finland; dDepartment of Social and Behavioral Sciences, Harvard School of Public Health, Boston, MA; eDepartment of Epidemiology and Public Health, University College London Medical School, London, United Kingdom; fClinicum, Faculty of Medicine, University of Helsinki, Helsinki, Finland; and gTurku University Hospital, Turku, Finland.
authors.forename: Jaana I
authors.initials: JI
authors.lastname: Halonen
authors.forename: Anna
authors.initials: A
authors.lastname: Pulakka
authors.forename: Sari
authors.initials: S
authors.lastname: Stenholm
authors.forename: Jaana
authors.initials: J
authors.lastname: Pentti
authors.forename: Ichiro
authors.initials: I
authors.lastname: Kawachi
authors.forename: Mika
authors.initials: M
authors.lastname: Kivimäki
authors.forename: Jussi
authors.initials: J
authors.lastname: Vahtera
mesh_terms: D000328:Adult; D000368:Aged; D018592:Cross-Over Studies; D005260:Female; D005387:Finland / Q000453:epidemiology; D006306:Health Surveys; D006801:Humans; D016015:Logistic Models; D008137:Longitudinal Studies; D008297:Male; D008875:Middle Aged; D016017:Odds Ratio; D011204:Poverty Areas; D012111:Residence Characteristics; D012307:Risk Factors; D012907:Smoking / Q000191:economics / Q000453:epidemiology* / Q000523:psychology; D013997:Time Factors