Unit of EPIDEMIOLOGY SCIENTIFIC INSTITUTE OF PUBLIC HEALTH Comparison of HLY from different health...
18
Unit of EPIDEMIOLOGY SCIENTIFIC INSTITUTE OF PUBLIC HEALTH Comparison of HLY from different health surveys 4th Meeting of the Task Force on Health Expectancies Luxembourg, 4 th June 2007 Bianca Cox
-
Upload
carolina-mangold -
Category
Documents
-
view
214 -
download
2
Transcript of Unit of EPIDEMIOLOGY SCIENTIFIC INSTITUTE OF PUBLIC HEALTH Comparison of HLY from different health...
Unit of EPIDEMIOLOGY
SCIENTIFIC INSTITUTE OF PUBLIC HEALTH
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 expectanciescomparison 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
Self-Percieved Health: males age 65SWESPAPORNETLUXITAIREGREGERFRAFINESTDENAUS BEL SWI
0123456789
1011121314151617181920
ES SH SI ES SI ES SH SI ES SI ES SI ES SH SI ES SH ES SH SI ES SI SH SI ES SI ES SH ES SI ES SH SI ES SH SI ES SH
Country/Survey
He
alt
h e
xp
ec
tan
cy
Very good & good Fair Very bad & bad
Self-Percieved Health: males age 85
SWIBELAUS DEN EST FIN FRA GER GRE IRE ITA LUX NET POR SPA SWE
0
1
2
3
4
5
6
ES SH SI ES SI ES SH SI ES SI ES SI ES SH SI ES SH ES SH SI ES SI SH SI ES SI ES SH ES SI ES SH SI ES SH SI ES SH
Country/Survey
Healt
h e
xp
ecta
ncy
Very good & good Fair Very bad & bad
Results : Graphical exploration AL health expectancies
Activity Limitation: males age 65SWIBELAUS DEN EST FIN FRA GER GRE IRE ITA LUX NET POR SPA SWE
0
1
23
4
5
6
78
9
10
1112
13
14
15
1617
18
19
ES SH SI ES SI ES SH SI ES SI ES SI ES SH SI ES SH ES SH SI ES SI SH SI ES SI ES SH ES SI ES SH SI ES SH SI ES SH
Country/Survey
He
alt
h e
xp
ec
tan
cy
Without Moderate Severe
Activity Limitation: males age 85
SWESPAPORNETLUXITAIREGREGERFRAFINESTDENAUS BEL SWI
0
1
2
3
4
5
6
ES SH SI ES SI ES SH SI ES SI ES SI ES SH SI ES SH ES SH SI ES SI SH SI ES SI ES SH ES SI ES SH SI ES SH SI ES SH
Country/Survey
Healt
h e
xp
ecta
ncy
Without Moderate Severe
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
● 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 prevalences
Results : Logistic models on SPH prevalences
+ or - odds ratio > 1 or odds ratio < 1A & B number of models with a significant odds ratioC number of models with a odds ratio > 1
Agegr 50 Agegr 65 Agegr 85
0
1
2
3
4
5
6
SH - ES ES - SI SH - SI SH - ES ES - SI SH - SI SH - ES ES - SI SH - SI
min median max
Agegr 85Agegr 65Agegr 50
0
1
2
3
4
5
6
SH - ES ES - SI SH - SI SH - ES ES - SI SH - SI SH - ES ES - SI SH - SI
min median max
Agegr 85Agegr 65Agegr 50
0
1
2
3
4
5
6
SH - ES ES - SI SH - SI SH - ES ES - SI SH - SI SH - ES ES - SI SH - SI
min median max
Agegr 50 Agegr 65 Agegr 85
0
1
2
3
4
5
6
SH - ES ES - SI SH - SI SH - ES ES - SI SH - SI SH - ES ES - SI SH - SI
min median max
Results : Distribution of odds ratio estimates for SPH
Good SPH males Good SPH females
Bad SPH males Bad SPH females
SH > ES > SI
SH (<) ES < SI
Results : Logistic models on AL prevalences
+ or - odds ratio > 1or odds ratio < 1A & B number of models with a significant odds ratioC number of models with a odds ratio > 1
Results : Distribution of odds ratio estimates for AL
Without AL males Without AL females
Severe AL males Severe AL females
Agegr 85Agegr 65Agegr 50
0
1
2
3
4
5
6
7
8
ES - SI SI - SH ES - SH ES - SI SI - SH ES - SH ES - SI SI - SH ES - SH
min median max
Agegr 50 Agegr 65 Agegr 85
0
1
2
3
4
5
6
7
8
ES - SI SI - SH ES - SH ES - SI SI - SH ES - SH ES - SI SI - SH ES - SH
min median max
Agegr 85Agegr 65Agegr 50
0
1
2
3
4
5
6
7
8
ES - SI SI - SH ES - SH ES - SI SI - SH ES - SH ES - SI SI - SH ES - SH
min median max
Agegr 85Agegr 65Agegr 50
0
1
2
3
4
5
6
7
8
ES - SI SI - SH ES - SH ES - SI SI - SH ES - SH ES - SI SI - SH ES - SH
min median max
ES > SI > SH
ES < SH < SI
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 ? ”
