title: Gender differences in multiple underlying dimensions of health-related quality of life are associated with sociodemographic and socioeconomic status.
abstract: OBJECTIVE
  The purpose of the study was to examine whether gender differences in summary health-related quality of life (HRQoL) are due to differences in specific dimensions of health, and whether they are explained by sociodemographic and socioeconomic (SES) variation.
  
  
  METHODS
  The National Health Measurement Study collected cross-sectional data on a national sample of 3648 black and white noninstitutionalized adults ages 35 to 89 years. Data included the Short Form 36-Item survey, which yielded separate Mental and Physical Component Summary scores (MCS and PCS, respectively), and five HRQoL indexes: Short Form 6 dimension, EuroQol 5 dimension, the Health Utilities Indexes Mark 2 and 3, and the Quality of Well-Being Scale Self-Administered form. Structural equation models were used to explore gender differences in physical, psychosocial, and pain latent dimensions of the 5 indexes, adjusting for sociodemographic and SES indicators. Observed MCS and PCS scores were examined in regression models to judge robustness of latent results.
  
  
  RESULTS
  Men had better estimated physical and psychosocial health and less pain than women with similar trends on the MCS and PCS scores. Adjustments for marital status or income reduced gender differences more than did other indicators. Adjusting results for partial factorial invariance of HRQoL attributes supported the presence of gender differentials, but also indicated that these differences are impacted by dimensions being related to some HRQoL attributes differently by gender.
  
  
  CONCLUSIONS
  Men have better estimated health on 3 latent dimensions of HRQoL-physical, psychosocial, and pain-comparable to gender differences on the observed MCS and PCS scores. Gender differences are partly explained by sociodemographic and SES factors, highlighting the role of socioeconomic inequalities in perpetuating gender differences in health outcomes across multiple domains. These results also emphasize the importance of accounting for measurement invariance for meaningful comparison of group differences in estimated means of self-reported measures of health.
authors.affiliation: Department of Health Services, University of California, School of Public Health, Los Angeles, CA, USA. dgcherepanov@gmail.com
authors.forename: Dasha
authors.initials: D
authors.lastname: Cherepanov
authors.forename: Mari
authors.initials: M
authors.lastname: Palta
authors.forename: Dennis G
authors.initials: DG
authors.lastname: Fryback
authors.forename: Stephanie A
authors.initials: SA
authors.lastname: Robert
authors.forename: Ron D
authors.initials: RD
authors.lastname: Hays
authors.forename: Robert M
authors.initials: RM
authors.lastname: Kaplan
mesh_terms: D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D003430:Cross-Sectional Studies; D004522:Educational Status; D005260:Female; D006304:Health Status; D006801:Humans; D007182:Income; D016018:Least-Squares Analysis; D008297:Male; D017533:Marital Status; D008875:Middle Aged; D010146:Pain / Q000453:epidemiology; D011788:Quality of Life; D012044:Regression Analysis; D012737:Sex Factors; D012959:Socioeconomic Factors; D011795:Surveys and Questionnaires; D014481:United States / Q000453:epidemiology