Quantifying self-rated age.
Level 4 - case-series / case-control
Cross-sectional observational analysis of population survey cohorts
PubMed 35164652 · doi:10.1080/00324728.2022.2030490
What was done
Authors formulated a subjective indicator termed self-rated age and evaluated its concurrent validity against subjective survival probabilities, subjective age, and biological age. They analyzed cross-sectional survey data from Wave 6 of the Survey of Health, Ageing and Retirement in Europe (SHARE), Wave 12 of the Health and Retirement Study (HRS) in the United States, and life tables from the Human Mortality Database using multinomial regression models.
What was found
The abstract reports no numerical values, effect sizes, or confidence intervals. It notes qualitatively that health status and frequency of physical activities showed similar association patterns across self-rated age, subjective survival probabilities, subjective age, and biological age, while the effect of cognitive function differed by geographic region.
Why it matters
Self-rated age provides a subjective demographic measure that may help adjust traditional chronological life tables by capturing perceived health and functional status.
Limits
The abstract omits sample sizes, specific effect estimates, and statistical significance levels. The design is cross-sectional across single survey waves, preventing longitudinal evaluation, and relies on self-reported survey indicators.