title: Best-practice interventions to reduce socioeconomic inequalities of coronary heart disease mortality in UK: a prospective occupational cohort study.
abstract: BACKGROUND
  How much the successful implementation of the most effective (ie, best-practice) interventions could reduce socioeconomic inequalities of coronary heart disease mortality is not known. We assessed this issue in an occupational cohort study comparing low with high socioeconomic groups.
  
  
  METHODS
  We undertook a prospective cohort study on 17 186 male civil servants aged 40-69 years between 1967 and 1970 in the UK (the Whitehall study). Socioeconomic position was based on employment grade. We compared the potential reduction in excess coronary heart disease mortality in men of low with those of high socioeconomic position with either best-practice interventions (reduction of systolic blood pressure by 10 mm Hg, of total cholesterol by 2 mmol/L, and of blood glucose by 1 mmol/L in pre-diabetic people; halving the prevalence of non-insulin-dependent diabetes; and complete cessation of cigarette smoking) or primordial prevention.
  
  
  RESULTS
  15-year absolute risk of death due to coronary heart disease per 100 men, standardised to age 55 years, was 11.0 for men in the low employment grade group and 7.5 for those in the high grade group. Population-wide best-practice interventions would reduce coronary heart disease mortality by 57%, and the difference in mortality between socioeconomic groups by 69%. For primordial prevention, the corresponding reductions would be 73% and 86%, respectively.
  
  
  CONCLUSIONS
  Our results suggest that current best-practice interventions to reduce classic coronary risk factors, if successfully implemented in both high and low socioeconomic groups, could eliminate most of the socioeconomic differences in coronary heart disease mortality. Modest further benefits would result if the classic coronary risk factors could be reduced to primordial levels for the whole population.
authors.affiliation: Department of Epidemiology and Public Health, University College London, London, UK.
authors.forename: Mika
authors.initials: M
authors.lastname: Kivimäki
authors.forename: Martin J
authors.initials: MJ
authors.lastname: Shipley
authors.forename: Jane E
authors.initials: JE
authors.lastname: Ferrie
authors.forename: Archana
authors.initials: A
authors.lastname: Singh-Manoux
authors.forename: G David
authors.initials: GD
authors.lastname: Batty
authors.forename: Tarani
authors.initials: T
authors.lastname: Chandola
authors.forename: Michael G
authors.initials: MG
authors.lastname: Marmot
authors.forename: George Davey
authors.initials: GD
authors.lastname: Smith
mesh_terms: D000328:Adult; D000368:Aged; D019985:Benchmarking; D015331:Cohort Studies; D003327:Coronary Disease / Q000209:etiology* / Q000401:mortality* / Q000517:prevention & control; D048909:Diabetes Complications; D004651:Employment / Q000145:classification; D006801:Humans; D006937:Hypercholesterolemia / Q000150:complications* / Q000188:drug therapy; D006973:Hypertension / Q000150:complications* / Q000188:drug therapy; D016014:Linear Models; D008297:Male; D008875:Middle Aged; D012042:Registries; D012307:Risk Factors; D012907:Smoking / Q000009:adverse effects*; D012923:Social Class; D006113:United Kingdom / Q000453:epidemiology