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Comparative Analysis of Health Expectancies from Various Surveys

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sema
18 diapositives · 290 Views · Oct 12, 2014

This study compares health expectancies across European countries from different health surveys conducted in 2004. It examines self-perceived health and activity limitations data to assess comparability. Various statistical analyses and models are used to evaluate differences across surveys, age groups, and countries. Results show trends in health perceptions and limitations, with discussions on potential survey biases and sampling variations.

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  1. Comparison of HLY according to different health surveys 4th Meeting of the Task Force on Health Expectancies Luxembourg, 4th June 2007 Bianca Cox

  2. Introduction • EHEMU Information System : Health expectancies for 25 European countries • Demographic data Eurostat + national statistical centers • Health data Eurostat, DG SANCO, Mannheim University  from different European surveys

  3. Introduction

  4. Introduction • Are the health expectancies for a given country comparable between the surveys? • Surveys carried out in the same year (2004): ESS, SHARE, SILC  Common health indicators : • Self-Percieved Health (SPH) • Activity Limitation (AL)

  5. Data • Health expectancies comparison WITHIN country : same demographic data • Raw health data (prevalences) • Self-Percieved Health : good, fair, bad  • Activity Limitation : without, moderate, severe • Average over 5-year age groups: 50-54, 55-59,…, 85+

  6. Analyses • Health expectancies : graphical exploration • Prevalences : logistic regression  Separate model for each health state and gender • Overall models : • Main effects : survey, agegr, country • Interactions : survey*agegr, survey*country, agegr*country • Country-specific models : • Main effects : survey, agegr • Interactions : survey*agegr  Odds ratio estimates of one survey vs the other for agegroups 50, 65 and 85+

  7. Results : Graphical exploration SPH health expectancies

  8. Results : Graphical exploration AL health expectancies

  9. Results : Graphical exploration health expectancies • Common trend in some countries : • Self-Perceived Health : • Good : SHARE > ESS > SILC • Bad : SHARE < ESS < SILC • Activity Limitation : • Without : ESS > SILC > SHARE • Severe : ESS < SHARE < SILC • Confidence intervals of health expectancies : SILC << SHARE < ESS

  10. Results : Logistic models on prevalences • Overall models : • Survey*agegr, survey*country, agegr*country • SPH: sign. in all 6 models • AL: sign. in 4 models (not in ♀models for “without” & “severe”) •  Effect of survey different for different age groups and countries • Country-specific models : • Odds ratio estimates of one survey vs the other for age groups 50, 65 and 85+

  11. Results : Logistic models on SPH prevalences + or - odds ratio > 1 or odds ratio < 1 A & B number of models with a significant odds ratio C number of models with a odds ratio > 1

  12. Results : Distribution of odds ratio estimates for SPH Good SPH males SH > ES > SI Good SPH females Bad SPH males SH (<) ES < SI Bad SPH females

  13. Results : Logistic models on AL prevalences + or - odds ratio > 1or odds ratio < 1 A & B number of models with a significant odds ratio C number of models with a odds ratio > 1

  14. Results : Distribution of odds ratio estimates for AL Without AL males ES > SI > SH Without AL females Severe AL males ES < SH < SI Severe AL females

  15. Discussion • Significant effect of survey, different for different age groups and countries • Still : odds ratios show common trend across age groups and countries • Good SPH : SH > ES > SI • Bad SPH : SH (<) ES < SI • Without AL : ES > SI > SH • Severe AL : ES < SH < SI • Significance of odds ratios increases with age but also the variability in the distribution of the odds ratio estimates  chance effects due to smaller sample sizes

  16. Discussion • Possible reasons for differences between surveys : • Different sampling designs : Sr = Simple random sampling Systrs = Systematic random sampling Stratrs = Stratified random sampling Ms = Multi-stage sampling Final sampling units: P = Persons H = Households A = Addresses T = Telephone numbers D = Dwellings But : Sampling design depends more on country than on survey  Survey design often constrained by what is available in the country

  17. Discussion • Possible reasons for differences between surveys : • Different selection bias : e.g. participation / item response • Different sample sizes : SILC > SHARE > ESS • Different position in questionnaire • Differences in wording: • SPH : “ How is your health in general ? ” ESS & SILC general questionnaires : “health” further specified (f.e. including mental health) in footnote or between brackets  Also in country-specific questionnaires or spoken out by interviewer ??

  18. Discussion • AL : - ESS : “ Are you hampered in your daily activities in any way by any longstanding illness, or disability, infirmity or mental health problem ? ” - SHARE & SILC : “ For the past six months at least, to what extent have you been limited because of a health problem in activities people usually do ? ”