Comparison of hly from different health surveys
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Comparison of HLY from different health surveys. 4th Meeting of the Task Force on Health Expectancies Luxembourg, 4 th June 2007 Bianca Cox. Introduction. EHEMU Information System : Health expectancies for 25 European countries Demographic data Eurostat + national statistical centers

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Comparison of HLY from different health surveys

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Comparison of HLY from different health surveys

4th Meeting of the Task Force on Health Expectancies

Luxembourg, 4th June 2007

Bianca Cox


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


Introduction


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)


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+


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+


Results : Graphical exploration SPH health expectancies


Results : Graphical exploration AL health expectancies


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


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+


Results : Logistic models on SPH prevalences

+ or -odds ratio > 1 or odds ratio < 1

A & Bnumber of models with a significant odds ratio

Cnumber of models with a odds ratio > 1


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


Results : Logistic models on AL prevalences

+ or -odds ratio > 1or odds ratio < 1

A & Bnumber of models with a significant odds ratio

Cnumber of models with a odds ratio > 1


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


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


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


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 ??


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 ? ”


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