No CrossRef data available.
Article contents
Las repercusiones de la depresión se distribuyen desigualmente en la población
Published online by Cambridge University Press: 12 May 2020
Resumen
Propósitos.
El propósito de este estudio era evaluar las repercusiones de la depresión en la calidad de vida en la población general estudiando sus efectos sobre i) la calidad de vida relacionada con la salud (CdVRS), ii) las utilidades del estado de salud y iii) la carga de la enfermedad en la población según la edad, el sexo, el estado civil, el nivel educativo, la situación económica y el empleo.
Métodos.
Estudio transversal en el Condado de Uppsala, Suecia. Se utilizó una muestra estadística de la población general de 20-64 años de edad (n =4.506). Se obtuvo información sobre el estado actual de la depresión por autoinforme. La CdVRS se midió utilizando la Forma Breve 36 (SF-36). Se usó el método de transacción temporal (TT) para medir las utilidades del estado de salud. La disminución de las utilidades totales del estado de salud asociada con la depresión en la población se utilizó como medida de la carga de la enfermedad.
Resultados.
Un 4% de la población comunicó depresión. Los sujetos con depresión puntuaron significativamente más bajo (P <0,001) que los sujetos sin ella en los ocho dominios del cuestionario SF-36. Además, el grupo deprimido evaluó las utilidades de su estado de salud significativamente más bajo que los otros: 0,796 frente a 0,933 (P <0,001). En el análisis multivariante de la disminución en las utilidades con diversos trastornos médicos, la depresión se asoció con la mayor disminución (-0,090, P< 0,001). Las personas con depresión daban cuenta del 10,9% de la disminución total en las utilidades en toda la población, pero esta proporción variaba según el subgrupo específico. Por ejemplo, el 16,4% y el 8,6% de la carga total de la enfermedad se vinculaban con la depresión entre las personas solteras y casadas, respectivamente. Las cifras correspondientes para las personas con los ingresos más bajos y más altos fueron 15% y 7,9%, respectivamente. Entre los desempleados, los que comunicaron depresión daban cuenta del 15,3% de la disminución en las utilidades, a diferencia del 4,9% entre los que tenían empleo.
Conclusiones.
La depresión tiene fuertes repercusiones en la calidad de vida y la discapacidad total en la población general. Además, las repercusiones de la depresión se distribuyen desigualmente en la población.
Keywords
- Type
- Artículo original
- Information
- Copyright
- Copyright © European Psychiatric Association 2005
References
Bibliografía
[1] Bennet, KJ, Torrance, GW, Boyle, MH, Guscott, R, Morgan, LA. Development and testing of a utility measure for major unipolar depression (McSad). Qual Life Res 2000;9:109–20.CrossRefGoogle Scholar
[2] Bingefors, K, Isacson, D, Von Knorring, L, Smedby, B. Prescription drug use and health care utilization among patients treated with antidepressants in a Swedish community. Ann Pharmacother 1995;29:566–72.CrossRefGoogle Scholar
[3] Bleichrodt, H, Johannesson, M. An experimental test of a theoretic al foundation for rating scale valuations. Med Decis Making 1997;17:208–16.Google Scholar
[4] Blumenschein, K, Johannesson, M. Relationship between quality of life instruments, health state utilities and willingness to pay in patients with asthma. Ann Allergy Asthma Immunol 1998;80:1989–94.CrossRefGoogle ScholarPubMed
[5] Burvill, P. Recent progress in the epidemiology of major depression. Epidemiol Rev 1995;17:21–31.CrossRefGoogle ScholarPubMed
[6] Drummond, M, O'Brien, B, Stoddart, G, Torrance, G. Methods for economic evaluation of health care programmes, 2nd ed. Oxford, New York, Toronto: Oxford University Press; 1997.Google Scholar
[7] Froberg, D, Kane, R. Methodology for measuring health-state preferences I: measurement strategies. J Clin Epidemiol 1989;42:345–54.Google ScholarPubMed
[8] Froberg, D, Kane, R. Methodology for measuring health-state preferences II: scaling measurements. J Clin Epidemiol 1989;42:459–71.CrossRefGoogle Scholar
[9] Goossens, M, Vlaeyen, J, Rutten Van Molken, M, Van der Linden, S. Patient utilities in ctronic musculoskeletal pain: how useful is the standard gamble method. Pain 1999;80:365–75.Google ScholarPubMed
[10] Hagnell, O, Lanke, J, Rorsman, B, Ojesjo, L. Are we entering an age of melancholy? Depressive illnesses in a prospective epidemiological study over 25 years: the Lundby Study, Sweden. Psychol Med 1982;12:279–89.Google Scholar
[11] Hays, RD, Wells, KB, Sherbourne, CD, Rogers, W, Spritzer, K. Functioning and well-being outcomes of patients with depression compared with chronic general medical illness. Arch Gen Psychiatry 1995;52:11–9.Google Scholar
[12] Kessler, RC, McGonagle, KA, Zhao, S, Nelson, CB, Hughes, M, Eshleman, S, et al. Lifetime and 12-month prevalence of DSM-III-R psychiatric disorders in the United States. Results from the National Comorbidity Survey. Arch Gen Psychiatry 1994;51:8–19.Google ScholarPubMed
[13] Lundberg, L, Johannesson, M, Isacson, D, Borgquist, L. The relationship between health-state utilities and the SF-12 in a general population. Med Dec Making 1999;19:128-40.CrossRefGoogle Scholar
[14] Mallon, L, Broman, J, Hetta, J. Relationship between insomnia, depression, and mortality: a 12-year follow-up of older adults in the community. Int Psychoger 2000;12:295–306.CrossRefGoogle Scholar
[15] Melse, JM, Essink-Bot, M-L, Kramers, PGN, Hoeymans, N. A national burden of disease calculation: Dutch disability-adjusted lifeyears. Am J Public Health 2000;90: 1241-7.Google Scholar
[16] Murray, CJL, Acharya, AK. Understanding DALYs. J Health Econ 1996;16:703–30.CrossRefGoogle Scholar
[17] In: Murray, C, Lopez, A, editors. The global burden of disease. Cambridge, MA: Harvard University Press; 1996.Google ScholarPubMed
[18] Murray, CJL, Lopez, AD. Alternative projections of mortality and disability by cause 1990 2020: global burden of disease study. Lancet 1997;349:1498–504.CrossRefGoogle ScholarPubMed
[19] Murray, CJL, Lopez, AD. Mortality by cause for eight regions of the world: global burden of disease study. Lancet 1997;349:1269–76.Google ScholarPubMed
[20] Murray, C, Salomon, J, Mathers, C. A critical examination of summary measures of population health. Bull World Health Org 2000;78:981–94.Google ScholarPubMed
[21] Nord, E. Cost-value analysis in health care. Cambridge: University Press; 1999.CrossRefGoogle ScholarPubMed
[22] Norholm, V, Bech, RThe WHO quality of life (WHOQOL) questionnaire: Danish validation study. Nord J Psychiatry 2001:55:229-35.Google ScholarPubMed
[23] Olsson, G. Adolescent depression. Epidemiology, nosology, life stress, and social network (PhD thesis). Uppsala: Uppsala University; 1998.Google Scholar
[24] Palsson, S, Ostling, S, Skoog, I. The incidence of first-onset depression in a population followed from the age of 70 to 85. Psychol Med 2001;31:1159–68.CrossRefGoogle Scholar
[25] Persson L-O, Karlsson, J, Bengtsson, C, Steen, B, Sullivan, M. The Swedish SF-36 health survey II: evaluation of clinical validity: results from population studies of elderly and women in Gofhenborg. J Clin Epidemiol 1998;51:1095–103.Google Scholar
[26] Peterson, S, Backlund, I, Diderichsen, ESjukdomsbordan i Sverige en svensk DALY-kalkyl (The burden of disease in Sweden—a Swedish DALY-calculation). Stockholm: Folkhalsoinstitutet, Stockolms laus landsting, Socialstyrelsen; 1998.Google Scholar
[27] Pyne, JM, Patterson, TL, Kaplan, RM, Gillin, JC, Koch, WL, Grant, I. Assessment of the quality of life of patients with major depression. Psychiatr Serv 1997;48:224–30.Google ScholarPubMed
[28] Read, J, Quin, R, Berwick, D, Fineberg, H, Weinstein, M. Preference for health outcomes: comparison of assessment methods. Med Decis Making 1984;4:315–29.CrossRefGoogle Scholar
[29] Revicki, D, Wood, M. Patient-assigned health state utilities for depression-related outcomes: differences by severity and antidepressant medications. J Affect Dis 1998;48:25–36.CrossRefGoogle ScholarPubMed
[30] Rorsman, B, Grasbeck, A, Hagnell, O, Lanke, J, Ohman, R, Ojesjo, L, et al. A prospective study of first-incidence depression. The Lundby study, 1957-72. Br J Psychol 1990;156:336–42.Google ScholarPubMed
[31] Rutz, W, Walinder, J, Von Knorring, L, Pihlgren, H, Rihmer, Z. Is depression in men under-treated? High frequency of sudden, unexpected suicides (in Swedish). Lakartidningen 1995;92:3893–4.Google Scholar
[32] SAS Institute Inc. The SAS system for Windows, Release 6.12. USA: Cary, NC; 1996.Google Scholar
[33] Schopper, D, Pereira, J, Torres, A, Cuende, N, Alonso, M, Baylin, A, et al. Estimating the burden of disease in one Swiss canton: what do disability adjusted life years (DALY) tell us? Int J Epidemiol 2000;29:871–7.CrossRefGoogle ScholarPubMed
[34] Sherbourne, C, Unutzer, J, Schoenbaum, M, Duan, N, Lenert, L, Sturm, R, et al. Can utility-weighted health-related quality-of-life estimates capture health effects of quality improvement for depression? Med Care 2001;39:1246–59.CrossRefGoogle Scholar
[35] Spitzer, RL, Kroenke, K, Linzer, M, Hahn, SR, Williams, JBW, deGniy, FV, et al. Health-related quality of life in primary care patients with mental disorders. J Am Med Assoc 1995;274:1511–7.CrossRefGoogle ScholarPubMed
[36] Statistics Sweden. Living Conditions. Appendix 13. Technical report for 1984-85, 1986-87 and 1988-89 years surveys of living conditions. Örebro: SCB-Tryck; 1991.Google Scholar
[37] Statistics Sweden. Living Conditions. Report no 76. Health and medical care 1980 1989. Orebro: SCB-Tryck; 1992.Google Scholar
[38] Strand, B, Dalgard, O, Tambs, K, Rognerud, M. Measuring the mental health status of the Norwegian population: a comparison of the instruments SCL-25, SCL-10, SCL-5 and MHI-5 (SF-36). Nord J Psychiatry 2003;57: 113-8.Google Scholar
[39] Sullivan, M, Karlsson, J. The Swedish SF-36 health survey III. Evaluation of criterion-based validity: results from normative population. J Clin Epidemiol 1998;51:1105–13.Google ScholarPubMed
[40] Thorslund, M, Warneryd, B. Methodological research in the Swedish surveys of living conditions. Problems of measurements and data collection. Soc Ind Res 1985;16:77–95.Google Scholar
[41] Torrance, G. Social preferences for health states. Socioecon Plana Sci 1976;10:129–36.CrossRefGoogle Scholar
[42] Tsevat, J, Keck, PE, Hornung, RW, McElroy, SL. Health values of patients with bipolar disorder. Qual Life Res 2000;9:579–86.Google ScholarPubMed
[43] Von Knorring, L. Depressive syndromes in patients with physical disorders. In: Treatment of depression. Workshop, vol. 1. Uppsala: Lakemedelsverket (Medical Products Agency); 1992. p. 205-15.Google Scholar
[44] Ware, J, Sherbourne, C. The MOS 36 item short form health survey (SF-36). Med Care 1992;30:473–83.CrossRefGoogle Scholar
[45] Ware, J, Snow, K, Kosinski, M, Gandek, B. SF-36 health survey manual and interpretation guide. Boston: New England Medical Center; 1993.Google Scholar
[46] Watkins, C, Daniels, L, Jack, C, Dickinson, H, Van den Broek, M. Accuracy of a single question in screening for depression in a cohort of patients after stroke: comparative study. Br Med J 2001;323: 1159.CrossRefGoogle Scholar
[47] Wells, KB, Sherbourne, CD. Functioning and utility for current health of patients with depression or chronical medical conditions in managed, primary care practices. Arch Gen Psychiatry 1999;56:897–904.CrossRefGoogle ScholarPubMed
[48] Wells, KB, Stewart, A, Hays, RD, Burnan, MA, Rogers, W, Daniels, M, et al. The functioning and well-being of depressed patients. Results of the Medical Outcomes Study. J Am Med Assoc 1989;262:914–9.CrossRefGoogle ScholarPubMed
[49] Williams, J, Mulrow, C, Kroenke, K, Dhanda, R, Badgett, R, Omori, D, et al. Case-finding for depression in primary care: a randomized trial. Am J Med 1999;106:36–43.CrossRefGoogle ScholarPubMed