Including information about co-morbidity in estimates of disease burden: Results from the World Health Organization World Mental Health Surveys

J. Alonso, G. Vilagut, S. Chatterji, S. Heeringa, M. Schoenbaum, T. Bedirhan Üstün, S. Rojas-Farreras, M. Angermeyer, E. Bromet, R. Bruffaerts, G. De Girolamo, O. Gureje, J. M. Haro, A. N. Karam, V. Kovess, D. Levinson, Z. Liu, M. E. Medina-Mora, J. Ormel, J. Posada-VillaH. Uda, R. C. Kessler

Research output: Contribution to journalArticle

32 Citations (Scopus)

Abstract

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.

Original languageEnglish
Pages (from-to)873-886
Number of pages14
JournalPsychological Medicine
Volume41
Issue number4
DOIs
Publication statusPublished - Apr 2011

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Health Surveys
Mental Health
Morbidity
Visual Analog Scale
Social Adjustment
Sleep Initiation and Maintenance Disorders
Self Report
Developing Countries
Regression Analysis
Global Health
Interviews
Depression
Health

Keywords

  • Co-morbidity
  • epidemiology
  • global burden of disease
  • mental health
  • visual analog scale

ASJC Scopus subject areas

  • Psychiatry and Mental health
  • Applied Psychology

Cite this

Alonso, J., Vilagut, G., Chatterji, S., Heeringa, S., Schoenbaum, M., Bedirhan Üstün, T., ... Kessler, R. C. (2011). Including information about co-morbidity in estimates of disease burden: Results from the World Health Organization World Mental Health Surveys. Psychological Medicine, 41(4), 873-886. https://doi.org/10.1017/S0033291710001212

Including information about co-morbidity in estimates of disease burden : Results from the World Health Organization World Mental Health Surveys. / Alonso, J.; Vilagut, G.; Chatterji, S.; Heeringa, S.; Schoenbaum, M.; Bedirhan Üstün, T.; Rojas-Farreras, S.; Angermeyer, M.; Bromet, E.; Bruffaerts, R.; De Girolamo, G.; Gureje, O.; Haro, J. M.; Karam, A. N.; Kovess, V.; Levinson, D.; Liu, Z.; Medina-Mora, M. E.; Ormel, J.; Posada-Villa, J.; Uda, H.; Kessler, R. C.

In: Psychological Medicine, Vol. 41, No. 4, 04.2011, p. 873-886.

Research output: Contribution to journalArticle

Alonso, J, Vilagut, G, Chatterji, S, Heeringa, S, Schoenbaum, M, Bedirhan Üstün, T, Rojas-Farreras, S, Angermeyer, M, Bromet, E, Bruffaerts, R, De Girolamo, G, Gureje, O, Haro, JM, Karam, AN, Kovess, V, Levinson, D, Liu, Z, Medina-Mora, ME, Ormel, J, Posada-Villa, J, Uda, H & Kessler, RC 2011, 'Including information about co-morbidity in estimates of disease burden: Results from the World Health Organization World Mental Health Surveys', Psychological Medicine, vol. 41, no. 4, pp. 873-886. https://doi.org/10.1017/S0033291710001212
Alonso, J. ; Vilagut, G. ; Chatterji, S. ; Heeringa, S. ; Schoenbaum, M. ; Bedirhan Üstün, T. ; Rojas-Farreras, S. ; Angermeyer, M. ; Bromet, E. ; Bruffaerts, R. ; De Girolamo, G. ; Gureje, O. ; Haro, J. M. ; Karam, A. N. ; Kovess, V. ; Levinson, D. ; Liu, Z. ; Medina-Mora, M. E. ; Ormel, J. ; Posada-Villa, J. ; Uda, H. ; Kessler, R. C. / Including information about co-morbidity in estimates of disease burden : Results from the World Health Organization World Mental Health Surveys. In: Psychological Medicine. 2011 ; Vol. 41, No. 4. pp. 873-886.
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AU - Alonso, J.

AU - Vilagut, G.

AU - Chatterji, S.

AU - Heeringa, S.

AU - Schoenbaum, M.

AU - Bedirhan Üstün, T.

AU - Rojas-Farreras, S.

AU - Angermeyer, M.

AU - Bromet, E.

AU - Bruffaerts, R.

AU - De Girolamo, G.

AU - Gureje, O.

AU - Haro, J. M.

AU - Karam, A. N.

AU - Kovess, V.

AU - Levinson, D.

AU - Liu, Z.

AU - Medina-Mora, M. E.

AU - Ormel, J.

AU - Posada-Villa, J.

AU - Uda, H.

AU - Kessler, R. C.

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N2 - 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.

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KW - epidemiology

KW - global burden of disease

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KW - visual analog scale

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