Do socioeconomic gradients in women's health widen over time and with age?
A population-based study was conducted to investigate changes over time in women's well-being and health service use by socio-economic status and whether these varied by age. Data from 12,328 mid-age women (aged 45-50 years in 1996) and 10,430 older women (aged 70-75 years) from the Australian Longitudinal Study on Women's Health were analysed. The main outcome measures were changes in the eight dimensions of the Short Form General Health Survey (SF-36) adjusted for baseline scores, lifestyle and behavioural factors; health care utilisation at Survey 2; and rate of deaths (older cohort only). Cross-sectional analyses showed clear socioeconomic differentials in well-being for both cohorts. Differential changes in health across tertiles of socioeconomic status (SES) were more evident in the mid-age cohort than in the older cohort. For the mid-aged women in the low SES tertile, declines in physical functioning (adjusted mean change of -2.4, standard error (SE) 1.1) and general health perceptions (-1.5, SE 1.1) were larger than the high SES group (physical functioning -0.8 SE 1.1, general health perceptions -0.8 SE 1.2). In the older cohort, changes in SF-36 scores over time were similar for all SES groups but women in the high SES group had lower death rates than women in the low SES group (relative risk: 0.79, 95% confidence interval 0.64-0.98). Findings suggest that SES differentials in physical health seem to widen during women's mid-adult years but narrow in older age. Nevertheless, SES remains an important predictor of health, health service use and mortality in older Australian women.
MRC-Human Nutrition Research, Elsie Widdowson Laboratory, Fulbourn Road, Cambridge CB1 9NL, UK. gita.mishra@mrc-hnr.cam.ac.uk
Gita D
GD
Mishra
Kylie
K
Ball
Annette J
AJ
Dobson
Julie E
JE
Byles
D017677:Age Distribution; D000367:Age Factors; D000368:Aged; D000375:Aging / Q000502:physiology; D000553:Ambulatory Care / Q000706:statistics & numerical data; D001315:Australia / Q000453:epidemiology; D015988:Cohort Effect; D005260:Female; D006305:Health Status Indicators; D006801:Humans; D008137:Longitudinal Studies; D008875:Middle Aged; D012044:Regression Analysis; D012959:Socioeconomic Factors; D016387:Women's Health; D014932:Women's Health Services / Q000706:statistics & numerical data