Modelling the impact of a healthy diet on cardiovascular disease and cancer mortality

J Epidemiol Community Health. 2012 May;66(5):420-6. doi: 10.1136/jech.2010.114520. Epub 2010 Dec 15.

Abstract

Background: Quantifying the potential health benefits of improvements in the nutritional quality of the average diet of a population would provide evidence for resource allocation between population-level interventions aimed at reducing chronic disease.

Methods: A model was built linking consumption of food components with biological risk factors (blood pressure, serum cholesterol and obesity) and subsequent mortality from coronary heart disease, stroke and cancer. Meta-analyses of individual-level studies that quantified the RR of increased consumption/increased risk factor level on disease outcomes were used to build the model. The sensitivity of the model to the results from the meta-analyses was assessed with Monte Carlo simulations. Country-specific estimates of current nutrient intake compared against dietary recommendations for the UK were used to demonstrate the model.

Results: Approximately 33 000 deaths per year would be avoided if UK dietary recommendations were met. The modelled reduction in deaths for coronary heart disease was 20 800 (95% credible interval 17 845-24 069), for stroke 5876 (3856-7364) and for cancer 6481 (4487-8353). Over 15 000 of the avoided deaths would be due to increased consumption of fruit and vegetables.

Conclusions: The developed model estimates the impact of population-level dietary changes and is robust. Achieving UK dietary recommendations for fruit and vegetable consumption (five portions a day) would result in substantial health benefits-equivalent benefits would be achieved if salt intakes were lowered to 3.5 g per day or saturated fat intakes were lowered to 3% of total energy.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Cardiovascular Diseases / mortality*
  • Diet*
  • Humans
  • Models, Biological
  • Neoplasms / mortality*
  • United States / epidemiology