title: Birth cohort appeared to confound effect estimates of guideline changes on statin utilization.
abstract: OBJECTIVE
  To investigate how birth cohorts can confound population-based intervention effect estimates.
  
  
  METHODS
  Interrupted time series design was applied to study the prevalence of statin use in Dutch diabetes patients over the period 1998-2011. Effects of guideline changes on the outcome were estimated using a Poisson regression model with and without the birth cohort dimension modeled through random intercepts.
  
  
  RESULTS
  Both models estimated a stronger increase in prevalence of statin use after influential studies were published in 2003 for patients aged below 50 and above 70 years. The model that controlled for birth cohort also estimated an effect for patients aged 50-70 years from 2003 onward. The magnitude of the intervention effect for patients aged above 70 years when we controlled for birth cohort was reduced from 0.078 [95% confidence interval (CI): 0.065, 0.091] to 0.027 (95% CI: 0.013, 0.041). Similarly, for patients aged below 50 years, the estimated guideline effect was reduced from 0.070 (95% CI: 0.048, 0.092) to 0.055 (95% CI: 0.035, 0.075).
  
  
  CONCLUSIONS
  In this case study, the birth cohort dimension appeared to confound population-level effect estimates of guideline changes on prevalence of statin use in patients with diabetes.
authors.affiliation: Unit PharmacoEpidemiology & PharmacoEconomics (PE2), Department of Pharmacy, University of Groningen, A. Deusinglaan 1, Groningen 9713 AV, The Netherlands. Electronic address: maarten.bijlsma@rug.nl.
authors.forename: Maarten J
authors.initials: MJ
authors.lastname: Bijlsma
authors.affiliation: Unit PharmacoEpidemiology & PharmacoEconomics (PE2), Department of Pharmacy, University of Groningen, A. Deusinglaan 1, Groningen 9713 AV, The Netherlands; Population Research Centre (PRC), Faculty of Spatial Sciences, University of Groningen, P.O. Box 800, 9700 AV Groningen, The Netherlands.
authors.forename: Fanny
authors.initials: F
authors.lastname: Janssen
authors.affiliation: Unit PharmacoEpidemiology & PharmacoEconomics (PE2), Department of Pharmacy, University of Groningen, A. Deusinglaan 1, Groningen 9713 AV, The Netherlands.
authors.forename: René
authors.initials: R
authors.lastname: Lub
authors.affiliation: Unit PharmacoEpidemiology & PharmacoEconomics (PE2), Department of Pharmacy, University of Groningen, A. Deusinglaan 1, Groningen 9713 AV, The Netherlands.
authors.forename: Jens H J
authors.initials: JH
authors.lastname: Bos
authors.affiliation: Unit PharmacoEpidemiology & PharmacoEconomics (PE2), Department of Pharmacy, University of Groningen, A. Deusinglaan 1, Groningen 9713 AV, The Netherlands.
authors.forename: Folgerdiena M
authors.initials: FM
authors.lastname: De Vries
authors.affiliation: Department of Applied Mathematics, Computer Science and Statistics, Ghent University, Krijgslaan 281, S9, 9000 Gent, Belgium.
authors.forename: Stijn
authors.initials: S
authors.lastname: Vansteelandt
authors.affiliation: Unit PharmacoEpidemiology & PharmacoEconomics (PE2), Department of Pharmacy, University of Groningen, A. Deusinglaan 1, Groningen 9713 AV, The Netherlands.
authors.forename: Eelko
authors.initials: E
authors.lastname: Hak
mesh_terms: D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D015331:Cohort Studies; D015986:Confounding Factors, Epidemiologic; D003920:Diabetes Mellitus / Q000188:drug therapy* / Q000453:epidemiology; D005260:Female; D006801:Humans; D019161:Hydroxymethylglutaryl-CoA Reductase Inhibitors / Q000627:therapeutic use*; D065186:Interrupted Time Series Analysis; D008297:Male; D008875:Middle Aged; D009426:Netherlands / Q000453:epidemiology; D017410:Practice Guidelines as Topic; D015995:Prevalence
chemical_list: D019161:Hydroxymethylglutaryl-CoA Reductase Inhibitors
keywords: Birth cohort; Confounding; Diabetes; Effect estimation; Intervention; Statins