1. Towards quantification of impacts The example of income John Kemm 7 th International HIA conference Cardiff April 6th

2. Prediction of outcome Nature Direction of change Magnitude of change

3. The case for quantification “… Quantification of one or more impacts may help to make trade-offs between conflicting impacts, or to make the scale of impacts explicit. Assessments with quantitative estimates may be considered more influential by policy makers ….” Mindell J. et al 2001 Journal of Public Health Medicine 23, 173-178.

4. Quantitating outcomes in HIA Veerman JL, Barendregt JJ, Mackenbach JP J. Epidemiol Comm Hlth 2005; 59:361-370 98 prospective HIA studies 17 quantitative estimates of change in exposure 16 quantitative estimates of health outcome

5. Causal Paths Inter- vention New road New policy etc, etc Intermediate factor Air pollution Income Employment Housing etc, etc. Health Impact Mortality Hospital admissions etc, etc

6. Intermediate factors Air pollution Noise Traffic density Smoking Drinking Income Employment Housing Physical activity Social cohesion Fear of crime

7. Mortality of White US Males by Median Family Income of Zip Code Area 1980 Slope = -1.6 per $1000 Median Family Income

8. Mortality and Income US panel study of income dynamics McDonough et al Am J Public Health 1997: 87; 1476-1483

9. Survival after 65 years and Career Average Earnings Canadian Pension Plan Study Wolfson M et al J Gerontology 1993: 48; S167-179

10. Income and mortality Finnish register study Martikainen P et al Int J Epidemiologu 20001; 30, 1397-1405

11. RR of reporting poor health and current income Benzeval M, Judge K Social Science & Medicine 2001 52; 1371-1379

12. Which measure of income? Disposable income Income after tax and benefits Current income Income at some previous point Average income Income stability Income or wealth

13. The income / health relationship Relationship causal? Reverse causation Confounding Context Reversible Time Lags Misclassification Relative or absolute

14. The income / health relationship Confounders Unemployment Employment conditions Education Ethnicity Lifestyle and environment Etc, etc

15. Income inequality & health Individual states USA 1990 Kaplan GA et al (1996) BMJ 312, 999-1003 r=-0.62

16. Possible mechanisms by which income could effect health More Income Material factors Better housing Better environment Food choice Psychological factors Improved self image Less financial worry

17. RR Mortality and income

18. RR Mortality and Log income RR reduces by about 0.6 for income increase of 0.8 log units ie 3% reduction in risk for 10% increase in income

19. Example Group of 6000 men Equal numbers aged 25,35,45,55 Expect 240 deaths in next 10 years If experience 10% reduction in income Would expect extra 7 deaths in next 10 years on basis of reduced income.