More statistics has many interesting data visualizations – I like them!


A more serious approach for interpreting health statistics can be found in the Lancet. The first of four papers describes the increasing demand for public-health statistics and calls for a rationalisation of measurement strategies. The second paper discusses the poor availability of health statistics for the Millennium Development Goals health indicators. The third articles describes different types of global public-health estimates while the fourth article describes how to enhance the use of health statistics for decisionmaking at the country level. The third paper has a nice panel, please recognize my minor modifications…

1. Broad determinants of health status, including socioeconomic status
2. Risk factors, such as smoking, environmental exposures, diet, or genetic predispositions
3. Underlying causes, frequently undernutrition
4. Direct causes of mortality or morbidity—such as infectious diseases, non-communicable diseases, or injury
5. Indirect causes, whereby one health condition predisposes to another
6. Treatment options, treatment effects
7. Future disease burden
8. Costs and economic consequences of health status, including direct and indirect costs to families for illness care, being orphaned, economic productivity, costs of interventions, costs saved by intervention, and cost-effectiveness