title: Future declines of coronary heart disease mortality in England and Wales could counter the burden of population ageing.
abstract: BACKGROUND
  Coronary Heart Disease (CHD) remains a major cause of mortality in the United Kingdom. Yet predictions of future CHD mortality are potentially problematic due to population ageing and increase in obesity and diabetes. Here we explore future projections of CHD mortality in England & Wales under two contrasting future trend assumptions.
  
  
  METHODS
  In scenario A, we used the conventional counterfactual scenario that the last-observed CHD mortality rates from 2011 would persist unchanged to 2030. The future number of deaths was calculated by applying those rates to the 2012-2030 population estimates. In scenario B, we assumed that the recent falling trend in CHD mortality rates would continue. Using Lee-Carter and Bayesian Age Period Cohort (BAPC) models, we projected the linear trends up to 2030. We validate our methods using past data to predict mortality from 2002-2011. Then, we computed the error between observed and projected values.
  
  
  RESULTS
  In scenario A, assuming that 2011 mortality rates stayed constant by 2030, the number of CHD deaths would increase 62% or approximately 39,600 additional deaths. In scenario B, assuming recent declines continued, the BAPC model (the model with lowest error) suggests the number of deaths will decrease by 56%, representing approximately 36,200 fewer deaths by 2030.
  
  
  CONCLUSIONS
  The decline in CHD mortality has been reasonably continuous since 1979, and there is little reason to believe it will soon halt. The commonly used assumption that mortality will remain constant from 2011 therefore appears slightly dubious. By contrast, using the BAPC model and assuming continuing mortality falls offers a more plausible prediction of future trends. Thus, despite population ageing, the number of CHD deaths might halve again between 2011 and 2030. This has implications for how the potential benefits of future cardiovascular strategies might best be calculated and presented.
authors.affiliation: Department of Public Health and Policy, University of Liverpool, Liverpool, United Kingdom.
authors.forename: Maria
authors.initials: M
authors.lastname: Guzman Castillo
authors.affiliation: Department of Public Health and Policy, University of Liverpool, Liverpool, United Kingdom.
authors.forename: Duncan O S
authors.initials: DO
authors.lastname: Gillespie
authors.affiliation: Department of Public Health and Policy, University of Liverpool, Liverpool, United Kingdom.
authors.forename: Kirk
authors.initials: K
authors.lastname: Allen
authors.affiliation: Department of Public Health and Policy, University of Liverpool, Liverpool, United Kingdom.
authors.forename: Piotr
authors.initials: P
authors.lastname: Bandosz
authors.affiliation: Department of Statistics, Ludwig-Maximilians-University, Munich, Germany.
authors.forename: Volker
authors.initials: V
authors.lastname: Schmid
authors.affiliation: Department of Public Health and Policy, University of Liverpool, Liverpool, United Kingdom.
authors.forename: Simon
authors.initials: S
authors.lastname: Capewell
authors.affiliation: Department of Public Health and Policy, University of Liverpool, Liverpool, United Kingdom.
authors.forename: Martin
authors.initials: M
authors.lastname: O'Flaherty
mesh_terms: D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D003327:Coronary Disease / Q000401:mortality*; D004739:England / Q000453:epidemiology; D005260:Female; D006801:Humans; D008297:Male; D008875:Middle Aged; D008962:Models, Theoretical; D011157:Population Dynamics; D014852:Wales / Q000453:epidemiology