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6 th Meeting of the Task Force on Health Expectancies 2 nd June 2008

6 th Meeting of the Task Force on Health Expectancies 2 nd June 2008. Validating the GALI Question. Carol Jagger and Clare Gillies, University of Leicester. Validating the GALI. HLY (based on the GALI) from SILC 2005 shows considerable differences between countries

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6 th Meeting of the Task Force on Health Expectancies 2 nd June 2008

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  1. 6th Meeting of the Task Force on Health Expectancies2nd June 2008 Validating the GALI Question Carol Jagger and Clare Gillies, University of Leicester

  2. Validating the GALI • HLY (based on the GALI) from SILC 2005 shows considerable differences between countries • Are these differences ‘real’ or due to the GALI • Data from the Survey of Health and Retirement in Europe (SHARE) study, was used to investigate • How the GALI relates to other health measures • Does the GALI reflect similar levels of ill health in different countries

  3. SHARE data • Data on a range of health expectancies • covering 11 European countries and over 12,569 individuals of 65 years of age or more. • GALI, ADL, IADL, self-perceived health, European depression score, which can be converted into health expectancies and compared across countries.

  4. GALI health expectancy at 65 years of age

  5. Other health measures in SHARE • Self-reported • Number of chronic conditions • Number of symptoms • Euro-d (depression score) • Self-perceived health • ADL • IADL • Objective? • Maximum grip strength • Walking speed

  6. How do other health measures relate to the GALI? Adjusted for age and gender, and the clustering effect of country. The odds ratios are for a one unit increase in the health measure, except self-perceived health which was dichotomized to compare good or very good health to fair, bad or very bad.

  7. Grip strength *probabilities estimated by logistic regression and adjusted for age and gender

  8. Walking speed *probabilities estimated by logistic regression and adjusted for age and gender

  9. Number of chronic conditions *probabilities estimated by logistic regression and adjusted for age and gender

  10. Number of ADL limitations *probabilities estimated by logistic regression and adjusted for age and gender

  11. Number of IADL limitations *probabilities estimated by logistic regression and adjusted for age and gender

  12. Conclusions • GALI appears to reflect self-reported functional limitation, chronic morbidity, depression and objectively measured physical function • Does it do this similarly across countries?

  13. For a given level of a health measure are countries equally likely to say they are limited? • Odds ratios calculated for each country, for a number of health indicators, adjusted for age using logistic regression • Meta-analysis carried out to assess heterogeneity between countries in terms of the predicted odds ratios

  14. Are the odds of being limited, by different health indicators, significantly different between countries

  15. Odds ratio of being limited if have 2 or more chronic diseases compared to less than 2 P=0.001

  16. Why do the odds ratios differ between countries?

  17. Odds ratio of being limited if in the lowest third for maximum grip strength compared to others P=0.121

  18. Odds ratio of being limited if have a walking speed of <=0.4m/sec compared to >0.4m/sec P=0.573

  19. Odds ratio of being limited if have 1 or more ADLs compared to none P=0.166

  20. Odds ratio of being limited if have 1 or more IADLs compared to none P=0.075

  21. Conclusions 1 • Odds ratios for number of chronic conditions, number of symptoms and self-perceived health all showed significant heterogeneity between countries • All countries showed a significant association between being limited and each of these three indicators (ORs>1) but for some countries the association was of a greater magnitude

  22. Conclusions 2 • Odds ratios for three significant subjective health measures were additionally adjusted for walking speed and maximum grip strength, heterogeneity between countries was no longer significant. • This suggeststhat the classification of individuals as limited or not limited by the GALI differed between countries in terms of individuals’ self-reporting of their health but not in terms of their actual (objectively measured) health.

  23. Additional Slides

  24. Number of symptoms *probabilities estimated by logistic regression and adjusted for age and gender

  25. European depression score *probabilities estimated by logistic regression and adjusted for age and gender

  26. Self-perceived health *probabilities estimated by logistic regression and adjusted for age and gender

  27. Odds ratio of being limited if have 2 or more symptoms compared to less than 2 P=0.002

  28. Odds ratios of being limited if have a European depression score of >=4, compared to <4 P=0.093

  29. Odds ratio of being limited if self-perceived health is less than good, compared to good or very good P=0.001

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