title: Prevention of late-life depression in primary care: do we know where to begin?
abstract: OBJECTIVE
  This study attempted to compare two models for selective (people at elevated risk) and indicated (those with subsyndromal depressive symptoms) prevention and to determine the optimal strategy for prevention of late-life depression.
  
  
  METHODS
  Onset was assessed at 3 years with the Geriatric Mental State AGECAT in a randomly selected cohort of 1,940 nondepressed and nondemented older people in Amsterdam. Risk factors that can easily be identified in primary care were used.
  
  
  RESULTS
  The association of risk factors with depression incidence was expressed in absolute and relative risk estimates, number needed to treat, and population-attributable fractions. Prevention models were identified with classification and regression tree analyses. In the indicated prevention model, subsyndromal symptoms of depression were associated with a risk of almost 40% of developing depression and a number needed to treat of 5.8, accounting for 24.6% of new cases. Adding more risk factors raised the absolute risk to 49.3%, with a lower number needed to treat but also lower attributable fraction values. In the selective prevention model, spousal death showed the highest risk, becoming even higher if the subjects also had a chronic illness. Overall, the attributable fraction values in the indicated model were higher, identifying more people at risk.
  
  
  CONCLUSIONS
  Consideration of the costs and benefits of both models in the context of the availability of evidence-based preventative interventions indicated that prevention aimed at elderly people with depressive symptoms is preferred. The focus on treatment should be readdressed; a new approach is needed, with a stronger emphasis on prevention.
authors.affiliation: Mentrum Mental Health Care, 2e Constantijn Huijgensstraat 37, 1054 AG Amsterdam, the Netherlands. robert.schoevers@mentrum.nl
authors.forename: Robert A
authors.initials: RA
authors.lastname: Schoevers
authors.forename: Filip
authors.initials: F
authors.lastname: Smit
authors.forename: Dorly J H
authors.initials: DJ
authors.lastname: Deeg
authors.forename: Pim
authors.initials: P
authors.lastname: Cuijpers
authors.forename: Jack
authors.initials: J
authors.lastname: Dekker
authors.forename: Willem
authors.initials: W
authors.lastname: van Tilburg
authors.forename: Aartjan T F
authors.initials: AT
authors.lastname: Beekman
mesh_terms: D000367:Age Factors; D000368:Aged; D000369:Aged, 80 and over; D001601:Bereavement; D002908:Chronic Disease / Q000453:epidemiology / Q000523:psychology; D015331:Cohort Studies; D015897:Comorbidity; D003865:Major Depressive Disorder / Q000175:diagnosis / Q000453:epidemiology / Q000517:prevention & control*; D005260:Female; D015577:Geriatric Assessment; D006801:Humans; D015994:Incidence; D008297:Male; D008393:Marriage / Q000523:psychology; D008960:Models, Psychological; D015233:Models, Statistical; D009426:Netherlands / Q000453:epidemiology; D011314:Preventive Health Services; D011320:Primary Health Care / Q000379:methods*; D011379:Prognosis; D012044:Regression Analysis; D012307:Risk Factors; D012494:Sampling Studies