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Geographic variation in incidence of coronary heart disease in Britain: the contribution of established risk factors

Abstract

OBJECTIVE To determine the extent to which geographic variation in the incidence of major coronary heart disease (CHD) in Great Britain may be explained by established risk factors.

DESIGN Prospective study.

SETTING 24 British towns with widely differing CHD mortality.

SUBJECTS 7735 men followed up from screening in 1978–80 for 15 years.

MAIN OUTCOME MEASURES Percentage of variance between the towns in major CHD incidence that can be explained by individual characteristics of men in the towns.

RESULTS Age standardised incidence rates over a 15 year period varied from 0.52% per annum in Maidstone to 1.07% per annum in Dewsbury and tended to follow the known pattern of higher rates in Scottish and northern English towns and lower rates in southern English towns (“north-south gradient”). Higher town incidence rates were related to prevalence of current cigarette smoking, low physical activity, and low alcohol consumption, and to mean body mass index, mean systolic blood pressure, low mean height, and prevalence of manual social class, but not to mean serum total cholesterol. The 95% range for true age adjusted CHD incidence (over 15 years) was estimated as 0.58–1.03% per annum among British towns. After adjustment for baseline smoking status, physical activity, body mass index, alcohol consumption, systolic blood pressure, serum total cholesterol, occupational social class, and height, this variation was reduced by 50%. A model based on these eight variables accounted for the major part of the north-south gradient.

CONCLUSIONS Much of the variation in CHD incidence among British towns was accounted for by established risk variables. The remaining unexplained variation may be related to measurement error in the established risk variables, to environmental factors such as climate, or to the combined effect of a wide range of minor risk factors.

  • geographic variation
  • established risk factors
  • coronary heart disease
  • multilevel modelling

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