CONTEXT: Clinically relevant late-life depression has a prevalence of 16% and is associated with substantial societal costs through its disease burden and unfavorable prognosis. From the public health perspective, depression prevention may be an attractive, if not imperative, means to generate health gains and reduce future costs. OBJECTIVE: To target high-risk groups for depression prevention such that maximum health gains are generated against the lowest cost. DESIGN: Population-based cohort study over 3 years. SETTING: General population in the Netherlands. PARTICIPANTS: Twenty-two hundred community residents aged 55 to 85 years. Of these, 1925 were not depressed at baseline. MAIN OUTCOME MEASURE: The onset of clinically relevant depression was measured with the Center for Epidemiological Studies Depression Scale. For each of the risk factors (and their combinations), we calculated indices of potential health gain and the effort (costs) required to generate those health gains. RESULTS: One in every 5 cases of clinically relevant late-life depression is a new case. Consequently, depression prevention has to play a key role in reducing the influx of new cases. This is best done by directing prevention efforts toward elderly people who have depressive symptoms, experience functional impairment, and have a small social network, in particular women, as well as people who have attained only a low educational level or who suffer from chronic diseases. CONCLUSIONS: Directing prevention efforts toward selected high-risk groups could help reduce the incidence of depression and is likely to be more cost-effective than alternative approaches. This article further shows that we have the methodology at our disposal to conduct ante hoc cost-benefit analysis in preventive psychiatry. This helps set a rational research and development agenda before testing the cost-effectiveness of interventions in time-consuming and expensive trials.
CONTEXT: Clinically relevant late-life depression has a prevalence of 16% and is associated with substantial societal costs through its disease burden and unfavorable prognosis. From the public health perspective, depression prevention may be an attractive, if not imperative, means to generate health gains and reduce future costs. OBJECTIVE: To target high-risk groups for depression prevention such that maximum health gains are generated against the lowest cost. DESIGN: Population-based cohort study over 3 years. SETTING: General population in the Netherlands. PARTICIPANTS: Twenty-two hundred community residents aged 55 to 85 years. Of these, 1925 were not depressed at baseline. MAIN OUTCOME MEASURE: The onset of clinically relevant depression was measured with the Center for Epidemiological Studies Depression Scale. For each of the risk factors (and their combinations), we calculated indices of potential health gain and the effort (costs) required to generate those health gains. RESULTS: One in every 5 cases of clinically relevant late-life depression is a new case. Consequently, depression prevention has to play a key role in reducing the influx of new cases. This is best done by directing prevention efforts toward elderly people who have depressive symptoms, experience functional impairment, and have a small social network, in particular women, as well as people who have attained only a low educational level or who suffer from chronic diseases. CONCLUSIONS: Directing prevention efforts toward selected high-risk groups could help reduce the incidence of depression and is likely to be more cost-effective than alternative approaches. This article further shows that we have the methodology at our disposal to conduct ante hoc cost-benefit analysis in preventive psychiatry. This helps set a rational research and development agenda before testing the cost-effectiveness of interventions in time-consuming and expensive trials.
Authors: Karlijn J Joling; Filip Smit; Harm W J van Marwijk; Henriëtte E van der Horst; Philip Scheltens; Richard Schulz; Hein P J van Hout Journal: Int Psychogeriatr Date: 2011-09-01 Impact factor: 3.878
Authors: Charles F Reynolds; Pim Cuijpers; Vikram Patel; Alex Cohen; Amit Dias; Neerja Chowdhary; Olivia I Okereke; Mary Amanda Dew; Stewart J Anderson; Sati Mazumdar; Frank Lotrich; Steven M Albert Journal: Annu Rev Public Health Date: 2012-04 Impact factor: 21.981
Authors: Charles F Reynolds; Stephen B Thomas; Jennifer Q Morse; Stewart J Anderson; Steven Albert; Mary Amanda Dew; Amy Begley; Jordan F Karp; Ariel Gildengers; Meryl A Butters; Jacqueline A Stack; John Kasckow; Mark D Miller; Sandra C Quinn Journal: Psychiatr Serv Date: 2014-06-01 Impact factor: 3.084
Authors: Jeffrey M Lyness; Benjamin P Chapman; Joanne McGriff; Rebecca Drayer; Paul R Duberstein Journal: Int Psychogeriatr Date: 2008-09-12 Impact factor: 3.878