Interpreting health statistics for policymaking: the story behind the headlines

Lancet. 2007 Mar 17;369(9565):956-63. doi: 10.1016/S0140-6736(07)60454-1.


Politicians, policymakers, and public-health professionals make complex decisions on the basis of estimates of disease burden from different sources, many of which are "marketed" by skilled advocates. To help people who rely on such statistics make more informed decisions, we explain how health estimates are developed, and offer basic guidance on how to assess and interpret them. We describe the different levels of estimates used to quantify disease burden and its correlates; understanding how closely linked a type of statistic is to disease and death rates is crucial in designing health policies and programmes. We also suggest questions that people using such statistics should ask and offer tips to help separate advocacy from evidence-based positions. Global health agencies have a key role in communicating robust estimates of disease, as do policymakers at national and subnational levels where key public-health decisions are made. A common framework and standardised methods, building on the work of Child Health Epidemiology Reference Group (CHERG) and others, are urgently needed.

Publication types

  • Review

MeSH terms

  • Causality
  • Cost of Illness
  • Data Interpretation, Statistical*
  • Decision Making
  • Global Health
  • Guidelines as Topic
  • Health Policy*
  • Health Status Indicators
  • Humans
  • Risk Factors
  • Uncertainty