title: The longitudinal prediction of costs due to health care uptake and productivity losses in a cohort of employees with and without depression or anxiety.
abstract: OBJECTIVE
  To examine how various predictors and subgroups of respondents contribute to the prediction of health care and productivity costs in a cohort of employees.
  
  
  METHODS
  We selected 1548 employed people from a cohort study with and without depressive and anxiety symptoms or disorders. Prediction rules, using the RuleFit program, were applied to identify predictors and subgroups of respondents, and to predict estimations of subsequent 1-year health care and productivity costs.
  
  
  RESULTS
  Symptom severity and diagnosis of depression and anxiety were the most important predictors of health care costs. Depressive symptom severity was the most important predictor for productivity costs. Several demographic, social, and work predictors did not predict economic costs.
  
  
  CONCLUSIONS
  Our data suggest that from a business perspective it can be beneficial to offer interventions aimed at prevention of depression and anxiety.
authors.affiliation: From the Department of Clinical Psychology (Ms Geraedts, Ms Fokkema, and Drs Kleiboer, Smit, and Cuijpers), VU University; EMGO Institute for Health and Care Research (Ms Geraedts and Drs Kleiboer, Smit, van Mechelen, Cuijpers, and Penninx), VU University Amsterdam and VU University Medical Center Amsterdam; Body@Work (Ms Geraedts and Drs Kleiboer, Wiezer, van Mechelen, and Cuijpers), Research Center Physical Activity, Work and Health, TNO-VU-VUmc, Amsterdam; Trimbos Institute (Netherlands Institute of Mental Health and Addiction) (Dr Smit), Utrecht; TNO (Dr Wiezer), Hoofddorp; Departments of Public and Occupational Health (Dr van Mechelen) and Psychiatry (Dr Penninx), VU University Medical Center, Amsterdam; Department of Psychiatry (Dr Penninx), Leiden University Medical Centre; and Department of Psychiatry (Dr Penninx), University Medical Centre Groningen, University of Groningen, the Netherlands.
authors.forename: Anna S
authors.initials: AS
authors.lastname: Geraedts
authors.forename: Marjolein
authors.initials: M
authors.lastname: Fokkema
authors.forename: Annet M
authors.initials: AM
authors.lastname: Kleiboer
authors.forename: Filip
authors.initials: F
authors.lastname: Smit
authors.forename: Noortje W
authors.initials: NW
authors.lastname: Wiezer
authors.forename: Maria Cristina
authors.initials: MC
authors.lastname: Majo
authors.forename: Willem
authors.initials: W
authors.lastname: van Mechelen
authors.forename: Pim
authors.initials: P
authors.lastname: Cuijpers
authors.forename: Brenda W J H
authors.initials: BW
authors.lastname: Penninx
mesh_terms: D000041:Absenteeism; D000293:Adolescent; D000328:Adult; D000368:Aged; D001008:Anxiety Disorders / Q000191:economics*; D003866:Depressive Disorder / Q000191:economics*; D017598:Efficiency, Organizational; D005260:Female; D017048:Health Care Costs / Q000706:statistics & numerical data* / Q000639:trends; D006296:Health Services / Q000706:statistics & numerical data; D006801:Humans; D008297:Male; D008875:Middle Aged; D009426:Netherlands; D016272:Occupational Health / Q000191:economics*; D055815:Young Adult