A comparison of SF-36 summary measures of physical and mental health for women across the life course
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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.
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).
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.
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.
KeywordsPhysical component summary scores Mental component summary scores Uncorrelated scores Oblique rotation Varimax rotation Australian women Life course SF-36
The Australian Longitudinal Study on Women’s Health is funded by the Australian Department of Health and Ageing, and GDM is supported by the Australian National Health and Medical Research Council (APP1000986).
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