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OP08 Explaining trends in coronary heart disease mortality and socioeconomic inequalities in denmark 1991–2007: impactsec model analysis using routine data
  1. AM Joensen1,
  2. T Joergensen2,3,4,
  3. S Lundbye-Christensen5,
  4. MB Johansen5,
  5. M Guzmán-Castillo6,
  6. P Bandosz6,
  7. J Hallas7,
  8. EIB Prescott8,
  9. S Capewell6,
  10. M O’Flaherty6
  1. 1Department of Cardiology, Aalborg University Hospital, Aalborg, Denmark
  2. 2Research Centre for Prevention and Health, The Capital Region, Glostrup, Denmark
  3. 3Department of Public Health, University of Copenghagen, Copenhagen, Denmark
  4. 4Department of Clinical Medicine, Aalborg University, Aalborg, Denmark
  5. 5Unit of Clinical Biostatistics and Bioinformatics, Aalborg University Hospital, Aalborg, Denmark
  6. 6Department of Public Health and Policy, University of Liverpool, Liverpool, UK
  7. 7Clinical Pharmacology, Department of Public Health, University of Southern Denmark, Odense, Denmark
  8. 8Bispebjerg University Hospital, Capital Region of Denmark, Copenhagen, Denmark


Background Coronary heart disease (CHD) mortality has declined substantially during recent decades but is still one of the leading causes of death, morbidity and healthcare costs in Denmark. Furthermore, socioeconomic inequalities persist. Quantifying the contributions of prevention and treatment to these recent declines might help to identify the most successful health policies, particularly for reducing inequalities.

Methods We used IMPACTSEC, a previously validated policy model, to apportion the recent decline in Danish CHD mortality to changes in major cardiovascular risk factors, and to increases in treatments in nine non-overlapping patient groups. Participants: All Danish adults aged 25–84 years, stratified by gender, age group and quintiles of financial income. Main outcome measure: Deaths prevented or postponed (DPP), stratified by socio-economic circumstance (SEC).

Results There were 11 110 fewer CHD deaths in 2007 than would be expected if the 1991 mortality rates had persisted. This reflected a dramatic 74% fall in CHD mortality rates (from 433 to 113 deaths per 100,000). Improved treatments accounted for approximately 24% (95% confidence interval=21%–28%). This contribution was higher in more affluent quintiles (approximately 26%) and least in the most deprived group (19%). The biggest contributions came from the treatment of congestive heart failure in the community (630 DPPs=5.7% of all DPPs) and in hospital (410 DPPs=3.7%).

Risk factor improvements accounted for approximately 40% (37%–44%) of the mortality fall. This contribution was higher in the central quintiles -approximately 51% (47%–58%) and least in the most deprived quintile – approximately 36% (29%–39%). The largest contribution came from population falls in cholesterol levels approximately 24% (22.7%–25.4%) of all DPPs; and decreases in smoking, some 10% (8.4%–12.2%).

Overall, the IMPACTSEC model could explain two thirds of the mortality fall. The 36% gap most likely reflects deficiencies in data, notably in population blood pressure and income.

Conclusion Denmark has benefited from one of biggest falls in CHD mortality in high income countries. The treatment uptake rate in Denmark was comparable with that in other countries and treatments accounted for approximately one third of the total mortality fall, much as in other, comparable populations. The largest contributions came from population-wide, non-phamacological reductions in major risk factors, notably cholesterol and smoking. Future strategies should therefore prioritise population-wide prevention policies.

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