title: Geographic variability in the association between socioeconomic status and BMI in the USA and Canada.
abstract: OBJECTIVE
  Reported associations between socioeconomic status (SES) and obesity are inconsistent depending on gender and geographic location. Globally, these inconsistent observations may hide a variation in the contextual effect on individuals' risk of obesity for subgroups of the population. This study explored the regional variability in the association between SES and BMI in the USA and in Canada, and describes the geographical variance patterns by SES category.
  
  
  METHODS
  The 2009-2010 samples of the Behavioral Risk Factor Surveillance System (BRFSS) and the Canadian Community Health Survey (CCHS) were used for this comparison study. Three-level random intercept and differential variance multilevel models were built separately for women and men to assess region-specific BMI by SES category and their variance bounds.
  
  
  RESULTS
  Associations between individual SES and BMI differed importantly by gender and countries. At the regional-level, the mean BMI variation was significantly different between SES categories in the USA, but not in Canada. In the USA, whereas the county-specific mean BMI of higher SES individuals remained close to the mean, its variation grown as SES decreased. At the county level, variation of mean BMI around the regional mean was 5 kg/m2 in the high SES group, and reached 8.8 kg/m2 in the low SES group.
  
  
  CONCLUSIONS
  This study underlines how BMI varies by country, region, gender and SES. Lower socioeconomic groups within some regions show a much higher variation in BMI than in other regions. Above the BMI regional mean, important variation patterns of BMI by SES and place of residence were found in the USA. No such pattern was found in Canada. This study suggests that a change in the mean does not necessarily reflect the change in the variance. Analyzing the variance by SES may be a good way to detect subtle influences of social forces underlying social inequalities.
authors.affiliation: Evaluation Platform on Obesity Prevention, Quebec Heart and Lung Institute, Laval University, Quebec City, Quebec, Canada; Department of Social and Behavioral Sciences, Harvard School of Public Health, Boston, Massachusetts, United States of America; Graduate School of Land Management and Regional Planning, Laval University, Quebec City, Quebec, Canada.
authors.forename: Alexandre
authors.initials: A
authors.lastname: Lebel
authors.affiliation: CHUM Research Center, Montreal, Canada; Department of Social and Preventive Medicine, University of Montreal, Montreal, Quebec, Canada.
authors.forename: Yan
authors.initials: Y
authors.lastname: Kestens
authors.affiliation: CHUM Research Center, Montreal, Canada; Department of Social and Preventive Medicine, University of Montreal, Montreal, Quebec, Canada.
authors.forename: Christelle
authors.initials: C
authors.lastname: Clary
authors.affiliation: Evaluation Platform on Obesity Prevention, Quebec Heart and Lung Institute, Laval University, Quebec City, Quebec, Canada; Faculty of Nursing Science, Laval University, Quebec City, Quebec, Canada.
authors.forename: Sherri
authors.initials: S
authors.lastname: Bisset
authors.affiliation: Department of Social and Behavioral Sciences, Harvard School of Public Health, Boston, Massachusetts, United States of America.
authors.forename: S V
authors.initials: SV
authors.lastname: Subramanian
mesh_terms: D000293:Adolescent; D000328:Adult; D000368:Aged; D015992:Body Mass Index; D002170:Canada / Q000453:epidemiology; D004522:Educational Status; D005260:Female; D006306:Health Surveys; D006801:Humans; D007182:Income / Q000706:statistics & numerical data; D008297:Male; D008875:Middle Aged; D009765:Obesity / Q000453:epidemiology; D050177:Overweight / Q000453:epidemiology*; D011159:Population Surveillance; D018401:Sample Size; D012494:Sampling Studies; D012923:Social Class; D014481:United States / Q000453:epidemiology; D055815:Young Adult