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Publication Details
AFRICAN RESEARCH NEXUS
SHINING A SPOTLIGHT ON AFRICAN RESEARCH
medicine
Including information about co-morbidity in estimates of disease burden: Results from the World Health Organization World Mental Health Surveys
Psychological Medicine, Volume 41, No. 4, Year 2011
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Description
Background The methodology commonly used to estimate disease burden, featuring ratings of severity of individual conditions, has been criticized for ignoring co-morbidity. A methodology that addresses this problem is proposed and illustrated here with data from the World Health Organization World Mental Health Surveys. Although the analysis is based on self-reports about one's own conditions in a community survey, the logic applies equally well to analysis of hypothetical vignettes describing co-morbid condition profiles.Method Face-to-face interviews in 13 countries (six developing, nine developed; n=31 067; response rate=69.6%) assessed 10 classes of chronic physical and nine of mental conditions. A visual analog scale (VAS) was used to assess overall perceived health. Multiple regression analysis with interactions for co-morbidity was used to estimate associations of conditions with VAS. Simulation was used to estimate condition-specific effects.Results The best-fitting model included condition main effects and interactions of types by numbers of conditions. Neurological conditions, insomnia and major depression were rated most severe. Adjustment for co-morbidity reduced condition-specific estimates with substantial between-condition variation (0.24-0.70 ratios of condition-specific estimates with and without adjustment for co-morbidity). The societal-level burden rankings were quite different from the individual-level rankings, with the highest societal-level rankings associated with conditions having high prevalence rather than high individual-level severity.Conclusions Plausible estimates of disorder-specific effects on VAS can be obtained using methods that adjust for co-morbidity. These adjustments substantially influence condition-specific ratings. © 2010 Cambridge University Press.
Authors & Co-Authors
Alonso Caballero, J. L.
Spain, Barcelona
Institut Municipal D'investigacio Medica
Spain, Madrid
Centro de Investigación Biomédica en Red de Epidemiología y Salud Pública
Vilagut, Gemma
Spain, Barcelona
Institut Municipal D'investigacio Medica
Spain, Madrid
Centro de Investigación Biomédica en Red de Epidemiología y Salud Pública
Chatterji, Somnath
Switzerland, Geneva
Organisation Mondiale de la Santé
Heeringa, Steven G.
United States, Ann Arbor
University of Michigan, Ann Arbor
Schoenbaum, M.
United States, Bethesda
Instituto Nacional de la Salud Mental
Bedirhan Üstün, T.
Switzerland, Geneva
Organisation Mondiale de la Santé
Rojas-Farreras, S.
Spain, Barcelona
Institut Municipal D'investigacio Medica
Angermeyer, Matthias Claus
Austria
Centre for Public Mental Health
Bromet, Evelyn J.
United States, Stony Brook
Stony Brook University
Bruffaerts, Ronny
Belgium, Leuven
Ku Leuven– University Hospital Leuven
de Girolamo, Giovanni
Italy, Brescia
Irccs Centro San Giovanni Di Dio Fatebenefratelli
Gureje, Oye
Nigeria, Ibadan
University College Hospital, Ibadan
Haro, Josep Maria
Spain, Madrid
Centro de Investigación Biomédica en Red de Salud Mental
Karam, Aimée Nasser
Lebanon, Beirut
Saint George Hospital University Medical Center
Kovess - Masfety, Viviane
France, Paris
Université Paris Cité
Levinson, Daphna
Israel, Jerusalem
Mental Health Services Ministry of Health
Liu, Zhaourui
China, Beijing
Peking University Sixth Hospital
Medina-Mora, M. E.
Mexico, Mexico
Instituto Nacional de Psiquiatría Ramon de la Fuente
Ormel, Johan Hans
Netherlands, Groningen
Universitair Medisch Centrum Groningen
Posada-Villa, J. A.
Colombia, Bogota
Universidad Colegio Mayor de Cundinamarca
Uda, Hidenori
Japan, Kagoshima Prefecture
Osumi Regional Promotion Bureau
Kessler, Ronald C.
United States, Boston
Harvard Medical School
Statistics
Citations: 51
Authors: 22
Affiliations: 20
Identifiers
Doi:
10.1017/S0033291710001212
ISSN:
00332917
e-ISSN:
14698978
Research Areas
Mental Health
Study Design
Cross Sectional Study
Study Approach
Quantitative