title: Measuring inequalities in health from survey data using self-assessed social class.
abstract: Asking participants to assess their social class may be an efficient approach to examining inequalities in heath from survey data. The present study investigated this possibility empirically by testing whether subjective class identification is related to overall health.
  
  
  
  I used pooled cross-sectional data from the 2012 and the 2014 General Social Survey, a nationally representative survey carried out among adults in the United States. The association between health and class was estimated separately by gender, race and age.
  
  
  
  The association follows a gradient pattern where health deteriorates with lower class position even after controlling for indicators typically used in research that examines class differences in health-educational attainment, family income and occupational prestige. The results largely hold when the data are stratified by gender, race and age.
  
  
  
  These findings demonstrate the empirical value of subjective class identification for assessing social inequalities in health from survey data.
authors.affiliation: School of Criminal Justice, Rutgers University, 123 Washington Street, Newark, NJ 07102-3094, USA.
authors.forename: Valerio
authors.initials: V
authors.lastname: Bacak
mesh_terms: D000328:Adult; D000368:Aged; D003430:Cross-Sectional Studies; D005260:Female; D006304:Health Status; D054624:Health Status Disparities; D006306:Health Surveys; D006801:Humans; D008297:Male; D008875:Middle Aged; D044469:Racial Groups; D012923:Social Class; D012959:Socioeconomic Factors; D014481:United States