Health status of the advanced elderly in six European countries: results from a representative survey using EQ-5D and SF-12.
Identifieur interne : 001865 ( Main/Exploration ); précédent : 001864; suivant : 001866Health status of the advanced elderly in six European countries: results from a representative survey using EQ-5D and SF-12.
Auteurs : Hans-Helmut König [Allemagne] ; Dirk Heider ; Thomas Lehnert ; Steffi G. Riedel-Heller ; Matthias C. Angermeyer ; Herbert Matschinger ; Gemma Vilagut ; Ronny Bruffaerts ; Josep M. Haro ; Giovanni De Girolamo ; Ron De Graaf ; Viviane Kovess ; Jordi AlonsoSource :
- Health and quality of life outcomes [ 1477-7525 ] ; 2010.
Descripteurs français
- KwdFr :
- Analyse de variance (MeSH), Analyse multifactorielle (MeSH), Enquêtes de santé (MeSH), Enquêtes et questionnaires (MeSH), Europe (MeSH), Facteurs socioéconomiques (MeSH), Femelle (MeSH), Humains (MeSH), Mâle (MeSH), Psychométrie (MeSH), Qualité de vie (MeSH), Sujet âgé (MeSH), Sujet âgé de 80 ans ou plus (MeSH), Surveillance sentinelle (MeSH), Vieillissement (physiologie), Vieillissement (psychologie), État de santé (MeSH).
- MESH :
- physiologie : Vieillissement.
- psychologie : Vieillissement.
- Analyse de variance, Analyse multifactorielle, Enquêtes de santé, Enquêtes et questionnaires, Europe, Facteurs socioéconomiques, Femelle, Humains, Mâle, Psychométrie, Qualité de vie, Sujet âgé, Sujet âgé de 80 ans ou plus, Surveillance sentinelle, État de santé.
English descriptors
- KwdEn :
- Aged (MeSH), Aged, 80 and over (MeSH), Aging (physiology), Aging (psychology), Analysis of Variance (MeSH), Europe (MeSH), Female (MeSH), Health Status (MeSH), Health Surveys (MeSH), Humans (MeSH), Male (MeSH), Multivariate Analysis (MeSH), Psychometrics (MeSH), Quality of Life (MeSH), Sentinel Surveillance (MeSH), Socioeconomic Factors (MeSH), Surveys and Questionnaires (MeSH).
- MESH :
- geographic : Europe.
- physiology : Aging.
- psychology : Aging.
- Aged, Aged, 80 and over, Analysis of Variance, Female, Health Status, Health Surveys, Humans, Male, Multivariate Analysis, Psychometrics, Quality of Life, Sentinel Surveillance, Socioeconomic Factors, Surveys and Questionnaires.
Abstract
BACKGROUND
Due to demographic change, the advanced elderly represent the fastest growing population group in Europe. Health problems tend to be frequent and increasing with age within this cohort.
AIMS OF THE STUDY
To describe and compare health status of the elderly population in six European countries and to analyze the impact of socio-demographic variables on health.
METHODS
In the European Study of the Epidemiology of Mental Disorders (ESEMeD), representative non-institutionalized population samples completed the EQ-5D and Short Form-12 (SF-12) questionnaires as part of personal computer-based home interviews in 2001-2003. This study is based on a subsample of 1659 respondents aged ≥ 75 years from Belgium (n = 194), France (n = 168), Germany (n = 244), Italy (n = 317), the Netherlands (n = 164) and Spain (n = 572). Descriptive statistics, bivariate- (chi-square tests) and multivariate methods (linear regressions) were used to examine differences in population health.
RESULTS
68.8% of respondents reported problems in one or more EQ-5D dimensions, most frequently pain/discomfort (55.2%), followed by mobility (50.0%), usual activities (36.6%), self-care (18.1%) and anxiety/depression (11.6%). The proportion of respondents reporting any problems increased significantly with age in bivariate analyses (age 75-79: 65.4%; age 80-84: 69.2%; age ≥ 85: 81.1%) and differed between countries, ranging from 58.7% in the Netherlands to 72.3% in Italy. The mean EQ VAS score was 61.9, decreasing with age (age 75-79: 64.1; age 80-84: 59.8; age ≥ 85: 56.7) and ranging from 60.0 in Italy to 72.9 in the Netherlands. SF-12 derived Physical Component Summary (PCS) and Mental Component Summary (MCS) scores varied little by age and country. Age and low educational level were associated with lower EQ VAS and PCS scores. After controlling for socio-demographic variables and reported EQ-5D health states, mean EQ VAS scores were significantly higher in the Netherlands and Belgium, and lower in Germany than the grand mean.
CONCLUSIONS
More than two thirds of the advanced elderly report impairment of health status. Impairment increases rapidly with age but differs considerably between countries. In all countries, health status is significantly associated with socio-demographic variables.
DOI: 10.1186/1477-7525-8-143
PubMed: 21114833
PubMed Central: PMC3009699
Affiliations:
Links toward previous steps (curation, corpus...)
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Riedel-Heller</name></author><author><name sortKey="Angermeyer, Matthias C" sort="Angermeyer, Matthias C" uniqKey="Angermeyer M" first="Matthias C" last="Angermeyer">Matthias C. Angermeyer</name></author><author><name sortKey="Matschinger, Herbert" sort="Matschinger, Herbert" uniqKey="Matschinger H" first="Herbert" last="Matschinger">Herbert Matschinger</name></author><author><name sortKey="Vilagut, Gemma" sort="Vilagut, Gemma" uniqKey="Vilagut G" first="Gemma" last="Vilagut">Gemma Vilagut</name></author><author><name sortKey="Bruffaerts, Ronny" sort="Bruffaerts, Ronny" uniqKey="Bruffaerts R" first="Ronny" last="Bruffaerts">Ronny Bruffaerts</name></author><author><name sortKey="Haro, Josep M" sort="Haro, Josep M" uniqKey="Haro J" first="Josep M" last="Haro">Josep M. Haro</name></author><author><name sortKey="De Girolamo, Giovanni" sort="De Girolamo, Giovanni" uniqKey="De Girolamo G" first="Giovanni" last="De Girolamo">Giovanni De Girolamo</name></author><author><name sortKey="De Graaf, Ron" sort="De Graaf, Ron" uniqKey="De Graaf R" first="Ron" last="De Graaf">Ron De Graaf</name></author><author><name sortKey="Kovess, Viviane" sort="Kovess, Viviane" uniqKey="Kovess V" first="Viviane" last="Kovess">Viviane Kovess</name></author><author><name sortKey="Alonso, Jordi" sort="Alonso, Jordi" uniqKey="Alonso J" first="Jordi" last="Alonso">Jordi Alonso</name></author></analytic><series><title level="j">Health and quality of life outcomes</title><idno type="eISSN">1477-7525</idno><imprint><date when="2010" type="published">2010</date></imprint></series></biblStruct></sourceDesc></fileDesc><profileDesc><textClass><keywords scheme="KwdEn" xml:lang="en"><term>Aged (MeSH)</term><term>Aged, 80 and over (MeSH)</term><term>Aging (physiology)</term><term>Aging (psychology)</term><term>Analysis of Variance (MeSH)</term><term>Europe (MeSH)</term><term>Female (MeSH)</term><term>Health Status (MeSH)</term><term>Health Surveys (MeSH)</term><term>Humans (MeSH)</term><term>Male (MeSH)</term><term>Multivariate Analysis (MeSH)</term><term>Psychometrics (MeSH)</term><term>Quality of Life (MeSH)</term><term>Sentinel Surveillance (MeSH)</term><term>Socioeconomic Factors (MeSH)</term><term>Surveys and Questionnaires (MeSH)</term></keywords><keywords scheme="KwdFr" xml:lang="fr"><term>Analyse de variance (MeSH)</term><term>Analyse multifactorielle (MeSH)</term><term>Enquêtes de santé (MeSH)</term><term>Enquêtes et questionnaires (MeSH)</term><term>Europe (MeSH)</term><term>Facteurs socioéconomiques (MeSH)</term><term>Femelle (MeSH)</term><term>Humains (MeSH)</term><term>Mâle (MeSH)</term><term>Psychométrie (MeSH)</term><term>Qualité de vie (MeSH)</term><term>Sujet âgé (MeSH)</term><term>Sujet âgé de 80 ans ou plus (MeSH)</term><term>Surveillance sentinelle (MeSH)</term><term>Vieillissement (physiologie)</term><term>Vieillissement (psychologie)</term><term>État de santé (MeSH)</term></keywords><keywords scheme="MESH" type="geographic" xml:lang="en"><term>Europe</term></keywords><keywords scheme="MESH" qualifier="physiologie" xml:lang="fr"><term>Vieillissement</term></keywords><keywords scheme="MESH" qualifier="physiology" xml:lang="en"><term>Aging</term></keywords><keywords scheme="MESH" qualifier="psychologie" xml:lang="fr"><term>Vieillissement</term></keywords><keywords scheme="MESH" qualifier="psychology" xml:lang="en"><term>Aging</term></keywords><keywords scheme="MESH" xml:lang="en"><term>Aged</term><term>Aged, 80 and over</term><term>Analysis of Variance</term><term>Female</term><term>Health Status</term><term>Health Surveys</term><term>Humans</term><term>Male</term><term>Multivariate Analysis</term><term>Psychometrics</term><term>Quality of Life</term><term>Sentinel Surveillance</term><term>Socioeconomic Factors</term><term>Surveys and Questionnaires</term></keywords><keywords scheme="MESH" xml:lang="fr"><term>Analyse de variance</term><term>Analyse multifactorielle</term><term>Enquêtes de santé</term><term>Enquêtes et questionnaires</term><term>Europe</term><term>Facteurs socioéconomiques</term><term>Femelle</term><term>Humains</term><term>Mâle</term><term>Psychométrie</term><term>Qualité de vie</term><term>Sujet âgé</term><term>Sujet âgé de 80 ans ou plus</term><term>Surveillance sentinelle</term><term>État de santé</term></keywords></textClass></profileDesc></teiHeader><front><div type="abstract" xml:lang="en"><p><b>BACKGROUND</b></p><p>Due to demographic change, the advanced elderly represent the fastest growing population group in Europe. Health problems tend to be frequent and increasing with age within this cohort.</p></div><div type="abstract" xml:lang="en"><p><b>AIMS OF THE STUDY</b></p><p>To describe and compare health status of the elderly population in six European countries and to analyze the impact of socio-demographic variables on health.</p></div><div type="abstract" xml:lang="en"><p><b>METHODS</b></p><p>In the European Study of the Epidemiology of Mental Disorders (ESEMeD), representative non-institutionalized population samples completed the EQ-5D and Short Form-12 (SF-12) questionnaires as part of personal computer-based home interviews in 2001-2003. This study is based on a subsample of 1659 respondents aged ≥ 75 years from Belgium (n = 194), France (n = 168), Germany (n = 244), Italy (n = 317), the Netherlands (n = 164) and Spain (n = 572). Descriptive statistics, bivariate- (chi-square tests) and multivariate methods (linear regressions) were used to examine differences in population health.</p></div><div type="abstract" xml:lang="en"><p><b>RESULTS</b></p><p>68.8% of respondents reported problems in one or more EQ-5D dimensions, most frequently pain/discomfort (55.2%), followed by mobility (50.0%), usual activities (36.6%), self-care (18.1%) and anxiety/depression (11.6%). The proportion of respondents reporting any problems increased significantly with age in bivariate analyses (age 75-79: 65.4%; age 80-84: 69.2%; age ≥ 85: 81.1%) and differed between countries, ranging from 58.7% in the Netherlands to 72.3% in Italy. The mean EQ VAS score was 61.9, decreasing with age (age 75-79: 64.1; age 80-84: 59.8; age ≥ 85: 56.7) and ranging from 60.0 in Italy to 72.9 in the Netherlands. SF-12 derived Physical Component Summary (PCS) and Mental Component Summary (MCS) scores varied little by age and country. Age and low educational level were associated with lower EQ VAS and PCS scores. After controlling for socio-demographic variables and reported EQ-5D health states, mean EQ VAS scores were significantly higher in the Netherlands and Belgium, and lower in Germany than the grand mean.</p></div><div type="abstract" xml:lang="en"><p><b>CONCLUSIONS</b></p><p>More than two thirds of the advanced elderly report impairment of health status. Impairment increases rapidly with age but differs considerably between countries. In all countries, health status is significantly associated with socio-demographic variables.</p></div></front></TEI><pubmed><MedlineCitation Status="MEDLINE" Owner="NLM"><PMID Version="1">21114833</PMID><DateCompleted><Year>2013</Year><Month>02</Month><Day>14</Day></DateCompleted><DateRevised><Year>2018</Year><Month>11</Month><Day>13</Day></DateRevised><Article PubModel="Electronic"><Journal><ISSN IssnType="Electronic">1477-7525</ISSN><JournalIssue CitedMedium="Internet"><Volume>8</Volume><PubDate><Year>2010</Year><Month>Nov</Month><Day>29</Day></PubDate></JournalIssue><Title>Health and quality of life outcomes</Title><ISOAbbreviation>Health Qual Life Outcomes</ISOAbbreviation></Journal><ArticleTitle>Health status of the advanced elderly in six European countries: results from a representative survey using EQ-5D and SF-12.</ArticleTitle><Pagination><MedlinePgn>143</MedlinePgn></Pagination><ELocationID EIdType="doi" ValidYN="Y">10.1186/1477-7525-8-143</ELocationID><Abstract><AbstractText Label="BACKGROUND" NlmCategory="BACKGROUND">Due to demographic change, the advanced elderly represent the fastest growing population group in Europe. Health problems tend to be frequent and increasing with age within this cohort.</AbstractText><AbstractText Label="AIMS OF THE STUDY" NlmCategory="OBJECTIVE">To describe and compare health status of the elderly population in six European countries and to analyze the impact of socio-demographic variables on health.</AbstractText><AbstractText Label="METHODS" NlmCategory="METHODS">In the European Study of the Epidemiology of Mental Disorders (ESEMeD), representative non-institutionalized population samples completed the EQ-5D and Short Form-12 (SF-12) questionnaires as part of personal computer-based home interviews in 2001-2003. This study is based on a subsample of 1659 respondents aged ≥ 75 years from Belgium (n = 194), France (n = 168), Germany (n = 244), Italy (n = 317), the Netherlands (n = 164) and Spain (n = 572). Descriptive statistics, bivariate- (chi-square tests) and multivariate methods (linear regressions) were used to examine differences in population health.</AbstractText><AbstractText Label="RESULTS" NlmCategory="RESULTS">68.8% of respondents reported problems in one or more EQ-5D dimensions, most frequently pain/discomfort (55.2%), followed by mobility (50.0%), usual activities (36.6%), self-care (18.1%) and anxiety/depression (11.6%). The proportion of respondents reporting any problems increased significantly with age in bivariate analyses (age 75-79: 65.4%; age 80-84: 69.2%; age ≥ 85: 81.1%) and differed between countries, ranging from 58.7% in the Netherlands to 72.3% in Italy. The mean EQ VAS score was 61.9, decreasing with age (age 75-79: 64.1; age 80-84: 59.8; age ≥ 85: 56.7) and ranging from 60.0 in Italy to 72.9 in the Netherlands. SF-12 derived Physical Component Summary (PCS) and Mental Component Summary (MCS) scores varied little by age and country. Age and low educational level were associated with lower EQ VAS and PCS scores. After controlling for socio-demographic variables and reported EQ-5D health states, mean EQ VAS scores were significantly higher in the Netherlands and Belgium, and lower in Germany than the grand mean.</AbstractText><AbstractText Label="CONCLUSIONS" NlmCategory="CONCLUSIONS">More than two thirds of the advanced elderly report impairment of health status. Impairment increases rapidly with age but differs considerably between countries. In all countries, health status is significantly associated with socio-demographic variables.</AbstractText></Abstract><AuthorList CompleteYN="Y"><Author ValidYN="Y"><LastName>König</LastName><ForeName>Hans-Helmut</ForeName><Initials>HH</Initials><AffiliationInfo><Affiliation>Department of Medical Sociology and Health Economics, University Medical Center Hamburg-Eppendorf, Martinistrasse 52, Hamburg, Germany. h.koenig@uke.uni-hamburg.de</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Heider</LastName><ForeName>Dirk</ForeName><Initials>D</Initials></Author><Author ValidYN="Y"><LastName>Lehnert</LastName><ForeName>Thomas</ForeName><Initials>T</Initials></Author><Author ValidYN="Y"><LastName>Riedel-Heller</LastName><ForeName>Steffi G</ForeName><Initials>SG</Initials></Author><Author ValidYN="Y"><LastName>Angermeyer</LastName><ForeName>Matthias C</ForeName><Initials>MC</Initials></Author><Author ValidYN="Y"><LastName>Matschinger</LastName><ForeName>Herbert</ForeName><Initials>H</Initials></Author><Author ValidYN="Y"><LastName>Vilagut</LastName><ForeName>Gemma</ForeName><Initials>G</Initials></Author><Author ValidYN="Y"><LastName>Bruffaerts</LastName><ForeName>Ronny</ForeName><Initials>R</Initials></Author><Author ValidYN="Y"><LastName>Haro</LastName><ForeName>Josep M</ForeName><Initials>JM</Initials></Author><Author ValidYN="Y"><LastName>de Girolamo</LastName><ForeName>Giovanni</ForeName><Initials>G</Initials></Author><Author ValidYN="Y"><LastName>de Graaf</LastName><ForeName>Ron</ForeName><Initials>R</Initials></Author><Author ValidYN="Y"><LastName>Kovess</LastName><ForeName>Viviane</ForeName><Initials>V</Initials></Author><Author ValidYN="Y"><LastName>Alonso</LastName><ForeName>Jordi</ForeName><Initials>J</Initials></Author><Author ValidYN="Y"><CollectiveName>ESEMeD/MHEDEA 2000 investigators</CollectiveName></Author></AuthorList><Language>eng</Language><PublicationTypeList><PublicationType UI="D003160">Comparative Study</PublicationType><PublicationType UI="D016428">Journal Article</PublicationType><PublicationType UI="D013485">Research Support, Non-U.S. Gov't</PublicationType></PublicationTypeList><ArticleDate DateType="Electronic"><Year>2010</Year><Month>11</Month><Day>29</Day></ArticleDate></Article><MedlineJournalInfo><Country>England</Country><MedlineTA>Health Qual Life Outcomes</MedlineTA><NlmUniqueID>101153626</NlmUniqueID><ISSNLinking>1477-7525</ISSNLinking></MedlineJournalInfo><CitationSubset>IM</CitationSubset><MeshHeadingList><MeshHeading><DescriptorName UI="D000368" MajorTopicYN="N">Aged</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D000369" MajorTopicYN="N">Aged, 80 and over</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D000375" MajorTopicYN="Y">Aging</DescriptorName><QualifierName UI="Q000502" MajorTopicYN="N">physiology</QualifierName><QualifierName UI="Q000523" MajorTopicYN="N">psychology</QualifierName></MeshHeading><MeshHeading><DescriptorName UI="D000704" MajorTopicYN="N">Analysis of Variance</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D005060" MajorTopicYN="N" Type="Geographic">Europe</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D005260" MajorTopicYN="N">Female</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D006304" MajorTopicYN="Y">Health Status</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D006306" MajorTopicYN="N">Health Surveys</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D006801" MajorTopicYN="N">Humans</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D008297" MajorTopicYN="N">Male</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D015999" MajorTopicYN="N">Multivariate Analysis</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D011594" MajorTopicYN="N">Psychometrics</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D011788" MajorTopicYN="Y">Quality of Life</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D018571" MajorTopicYN="N">Sentinel Surveillance</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D012959" MajorTopicYN="N">Socioeconomic Factors</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D011795" MajorTopicYN="Y">Surveys and Questionnaires</DescriptorName></MeshHeading></MeshHeadingList><InvestigatorList><Investigator ValidYN="Y"><LastName>Alonso</LastName><ForeName>Jordi</ForeName><Initials>J</Initials></Investigator><Investigator ValidYN="Y"><LastName>Angermeyer</LastName><ForeName>Matthias</ForeName><Initials>M</Initials></Investigator><Investigator ValidYN="Y"><LastName>Bernert</LastName><ForeName>Sebastian</ForeName><Initials>S</Initials></Investigator><Investigator ValidYN="Y"><LastName>Bruffaerts</LastName><ForeName>Ronny</ForeName><Initials>R</Initials></Investigator><Investigator ValidYN="Y"><LastName>Brugha</LastName><ForeName>Traolach S</ForeName><Initials>TS</Initials></Investigator><Investigator ValidYN="Y"><LastName>Bryson</LastName><ForeName>Heather</ForeName><Initials>H</Initials></Investigator><Investigator ValidYN="Y"><LastName>de Girolamo</LastName><ForeName>Giovanni</ForeName><Initials>G</Initials></Investigator><Investigator ValidYN="Y"><LastName>de Graaf</LastName><ForeName>Ron</ForeName><Initials>R</Initials></Investigator><Investigator ValidYN="Y"><LastName>Demyttenaere</LastName><ForeName>Koen</ForeName><Initials>K</Initials></Investigator><Investigator ValidYN="Y"><LastName>Gasquet</LastName><ForeName>Isabelle</ForeName><Initials>I</Initials></Investigator><Investigator ValidYN="Y"><LastName>Haro</LastName><ForeName>Josep M</ForeName><Initials>JM</Initials></Investigator><Investigator ValidYN="Y"><LastName>Katz</LastName><ForeName>Steven J</ForeName><Initials>SJ</Initials></Investigator><Investigator ValidYN="Y"><LastName>Kessler</LastName><ForeName>Ronald C</ForeName><Initials>RC</Initials></Investigator><Investigator ValidYN="Y"><LastName>Kovess</LastName><ForeName>Viviane</ForeName><Initials>V</Initials></Investigator><Investigator ValidYN="Y"><LastName>Lépine</LastName><ForeName>Jean P</ForeName><Initials>JP</Initials></Investigator><Investigator ValidYN="Y"><LastName>Ormel</LastName><ForeName>Johan</ForeName><Initials>J</Initials></Investigator><Investigator ValidYN="Y"><LastName>Polidori</LastName><ForeName>Gabriella</ForeName><Initials>G</Initials></Investigator><Investigator ValidYN="Y"><LastName>Russo</LastName><ForeName>Leo J</ForeName><Initials>LJ</Initials></Investigator><Investigator 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