title: Aging of the population may not lead to an increase in the numbers of acute coronary events: a community surveillance study and modelled forecast of the future.
abstract: OBJECTIVE
  To examine the incidence, mortality and case fatality of acute coronary syndrome (ACS) in Finland during 1993-2007 and to create forecasts of the absolute numbers of ACS cases in the future, taking into account the aging of the population.
  
  
  METHODS
  Community surveillance study and modelled forecasts of the future.
  
  
  METHODS
  Two sets of population-based coronary event register data from Finland (FINAMI and the National Cardiovascular Disease Register (CVDR)). Bayesian age-period-cohort (APC) modelling.
  
  
  METHODS
  24 905 observed ACS events in the FINAMI register and 364 137 in CVDR.
  
  
  METHODS
  Observed trends of ACS events during 1993-2007, forecasted numbers of ACS cases, and the prevalence of ACS survivors until the year 2050.
  
  
  RESULTS
  In the FINAMI register, the average annual declines in age-standardised incidence of ACS were 1.6% (p<0.001) in men and 1.8% (p<0.001) in women. For 28-day case fatality of incident ACS, the average annual declines were 4.1% (p<0.001) in men and 6.7% (p<0.001) in women. Findings in the country-wide CVDR data were consistent with the FINAMI register. The APC model, based on the CVDR data, suggested that both the absolute numbers of ACS events and the prevalence of ACS survivors reached their peak in Finland around 1990, have declined since then, and very likely will continue to decline until 2050.
  
  
  CONCLUSIONS
  The ACS event rates and absolute numbers of cases have declined steeply in Finland. The declining trends are likely to continue in the future despite the aging of the population.
authors.affiliation: Department of Chronic Disease Prevention, THL-National Institute for Health and Welfare, PO Box 30, Helsinki FI-00271, Finland. veikko.salomaa@thl.fi
authors.forename: Veikko
authors.initials: V
authors.lastname: Salomaa
authors.forename: Aki S
authors.initials: AS
authors.lastname: Havulinna
authors.forename: Heli
authors.initials: H
authors.lastname: Koukkunen
authors.forename: Päivi
authors.initials: P
authors.lastname: Kärjä-Koskenkari
authors.forename: Arto
authors.initials: A
authors.lastname: Pietilä
authors.forename: Juha
authors.initials: J
authors.lastname: Mustonen
authors.forename: Matti
authors.initials: M
authors.lastname: Ketonen
authors.forename: Aapo
authors.initials: A
authors.lastname: Lehtonen
authors.forename: Pirjo
authors.initials: P
authors.lastname: Immonen-Räihä
authors.forename: Seppo
authors.initials: S
authors.lastname: Lehto
authors.forename: Juhani
authors.initials: J
authors.lastname: Airaksinen
authors.forename: Y Antero
authors.initials: YA
authors.lastname: Kesäniemi
mesh_terms: D054058:Acute Coronary Syndrome / Q000453:epidemiology* / Q000401:mortality; D000367:Age Factors; D017668:Age of Onset; D000368:Aged; D000375:Aging; D001499:Bayes Theorem; D015897:Comorbidity; D003198:Computer Simulation; D004813:Epidemiology / Q000639:trends; D005260:Female; D005387:Finland / Q000453:epidemiology; D005544:Forecasting; D006801:Humans; D015994:Incidence; D016015:Logistic Models; D008297:Male; D008390:Markov Chains; D008875:Middle Aged; D015233:Models, Statistical; D009010:Monte Carlo Method; D012042:Registries; D017741:Survivors / Q000706:statistics & numerical data; D013997:Time Factors
keywords: CORONARY ARTERY DISEASE