title: A comparison of SF-36 summary measures of physical and mental health for women across the life course.
abstract: BACKGROUND
  Physical and mental component summary scores (PCS and MCS, respectively) are often used to summarise SF-36 quality of life subscales. This paper investigates PCS and MCS across the life course and compares the trajectories obtained from two different methods of calculation.
  
  
  METHODS
  The Australian Longitudinal Study on Women's Health is a population-based study with three cohorts of women and SF-36 surveys taken at multiple time points. Scoring coefficients for each component score were determined using factor analysis with uncorrelated (orthogonal) and correlated (oblique) rotation at the baseline survey, which were then used to compute correlated and uncorrelated PCS and MCS scores at each survey (scaled to have mean of 50 and standard deviation of 10 at baseline).
  
  
  RESULTS
  For both methods, PCS declined progressively across the lifespan, while MCS rose in young and mid-age women to a peak and subsequently declined in later life. Differences were apparent between correlated and uncorrelated scores, most notably for MCS in the older cohort, where correlated MCS reached 54.6 but still less than uncorrelated MCS, with a random effects model indicating 1.63 (95% confidence intervals 1.58-1.67) units difference; it then declined to a score of 51.2 by the last survey and the difference widened to 3.44 (3.38-3.50) units compared with the uncorrelated MCS.
  
  
  CONCLUSIONS
  PCS and MCS have distinct trajectories through life, with differences in results from correlated and uncorrelated component summary scores. The divergence is most notable with MCS, especially for older women, suggesting that correlated MCS and PCS should be used when examining change in health over time in this age group.
authors.affiliation: School of Population Health, The University of Queensland, Herston Road, Herston, QLD, 4006, Australia, g.mishra@sph.uq.edu.au.
authors.forename: Gita D
authors.initials: GD
authors.lastname: Mishra
authors.forename: Richard
authors.initials: R
authors.lastname: Hockey
authors.forename: Annette J
authors.initials: AJ
authors.lastname: Dobson
mesh_terms: D000293:Adolescent; D000328:Adult; D017677:Age Distribution; D000368:Aged; D001315:Australia; D015331:Cohort Studies; D005163:Factor Analysis, Statistical; D005260:Female; D005500:Follow-Up Studies; D006306:Health Surveys; D006801:Humans; D008137:Longitudinal Studies; D008603:Mental Health / Q000706:statistics & numerical data*; D008875:Middle Aged; D017063:Outcome Assessment, Health Care; D011446:Prospective Studies; D011788:Quality of Life / Q000523:psychology*; D012044:Regression Analysis; D018434:Sickness Impact Profile; D012959:Socioeconomic Factors; D011795:Surveys and Questionnaires / Q000592:standards*; D016387:Women's Health; D055815:Young Adult