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Do self-perceived health changes predict longevity?
Esen Erdogan-Ciftci1, Eddy van Doorslaer, Teresa Bago d'Uva
1Applied Economics, Erasmus University, Burgemeester Oudlaan 50, 3062 PA, Rotterdam, The Netherlands. erdoganc@ese.eur.nl
Social Science & Medicine (1982)
|October 15, 2010
Summary
Prospective health change measures predict longevity better than retrospective ones. Longitudinal data collection offers advantages over easier, cheaper retrospective health reporting for predicting mortality.
Area of Science:
- Epidemiology
- Health Services Research
- Biostatistics
Background:
- Self-assessed health (SAH) changes are crucial for understanding health status.
- Researchers use retrospective or prospective methods to measure SAH changes.
- These methods often yield different results, impacting health outcome predictions.
Purpose of the Study:
- To compare the validity of prospective versus retrospective SAH change measures.
- To investigate their predictive power for subsequent mortality.
- To determine the optimal method for collecting health change data.
Main Methods:
- Utilized data from a Dutch cohort study (1991-2004).
- Compared retrospective and prospective SAH changes using three waves of data (1991, 1993, 1995).
- Employed proportional hazard models, controlling for covariates and unobserved heterogeneity.
Main Results:
- A significant proportion (39.8%) of prospective and retrospective SAH change reports disagreed.
- Both measures predicted mortality when controlling only for SAH levels and socioeconomic factors.
- Prospectively measured health changes remained a significant predictor of longevity after controlling for chronic conditions and unobserved factors, unlike retrospective measures.
Conclusions:
- Prospective measurement of health changes provides more valid predictions of mortality than retrospective reports.
- Longitudinal data collection on health changes is advantageous despite higher costs.
- Future research should prioritize prospective data collection for accurate health status assessment and mortality prediction.
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