1. Ecologic studies JF Boivin Version 8 October 2010

2. 2 Outline 1.Examples 2.Definition 3.Ecologic fallacy Definition Valid ecologic study Rate difference varies Reference rate varies 4.Contextual effects 5.Rationale for ecologic studies 6.Ecologic confounders

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6. 6 Figure 1. Statistical (empirical Bayes) estimates of county-specific adjusted annual suicide rates in the United States. A Bayes estimate of 1.0 indicates that the rate for the county was equal to the national rate of 12 per 100 000 population, a Bayes estimate of 2.0 represents a doubling of the national rate, and a Bayes estimate of 0.5 represents half the national rate. The estimates are based on all data from 1996 to 1998, adjusted for age, sex, and race.

7. Example: Time-trend studies Time Trends in Autism and in MMR Immunization Coverage in California 7 Percentage of Children Receiving Measles-Mumps-Rubella (MMR) Immunization in Second Year of Life and Caseload of Children With Autism, by Year of Birth, California, 1980-1994 JAMA. 2001;285:1183-1185

8. Émile Durkheim Émile Durkheim (1858 –1917) was a famous French sociologist and pioneer in the development of modern sociology and anthropology. In a groundbreaking book published in 1897, entitled Le Suicide, Durkheim explored the differing suicide rates among Protestants and Catholics. In 19th century Europe, suicide rates were higher in countries that were more heavily Protestant. Durkheim found that suicide rates were highest in provinces that were heavily Protestant. He concluded that stronger social control among Catholics resulted in lower suicide rates. However, Durkheim's study of suicide was criticized as an example of the logical error termed the "ecological fallacy." 8

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10. 10 Using ordinary least-squares linear regression on Durkheim's data, Morgenstern (1995) found a strong positive correlation (Figure below) between proportion protestant and suicide rates. The estimated rate ratio, comparing Protestants with other religions, was 7.6 (i.e. suicide rates among protestants was about 8 fold higher than other religions).

11. 11 Outline 1.Examples 2.Definition 3.Ecologic fallacy Definition Valid ecologic study Rate difference varies Reference rate varies 4.Contextual effects 5.Rationale for ecologic studies 6.Ecologic confounders

12. 12 Ecologic study A study in which the units of analysis are populations or groups of people, rather than individuals. (Last. 2001)

13. 13 Structure of an ecologic study: Counts E+E- M 1+ M 1- N 1- N 1+ D+ D- ? ? ? ? Group 1 E+E- M 2+ M 2- N 2- N 2+ D+ D- ? ? ? ? Group 2

14. 14 Person-years E+E- M 1+ PY 1T D+ PY ? PY 1+ ? PY 1- Group 1 E+E- M 2+ PY 2T D+ PY ? PY 2+ ? PY 2- Group 2

15. 15 Gibbons’ study 20 1,000,000 Suicide PY ? 200,000 ? 800,000 County i YesNo 10 1,000,000 Suicide PY ? 100,000 ? 900,000 County 1 Antidepressant

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17. 17 Outline 1.Examples 2.Definition 3.Ecologic fallacy Definition Valid ecologic study Rate difference varies Reference rate varies 4.Contextual effects 5.Rationale for ecologic studies 6.Ecologic confounders

18. 18 Ecologic fallacy “…the mistaken assumption that a statistical association observed between two ecologic (group-level) variables… is equal to the association between the corresponding variables at the individual level…” (Encyclopedia of epidemiologic methods. 2000)

19. 19 Ecologic fallacy “…arises when the disease rate in the unexposed (reference) population is correlated with exposure prevalence across groups or when the difference in rates between exposed and unexposed populations (biologic effect) varies across groups.” (Encyclopedia of epidemiologic methods. 2000)

20. 20 No ecologic bias E+E- 32 20,000 D+ PY 24 12,000 8 8,000 Group 2 (Ontario) IEIE = 200/100,000 IoIo =100/100,000 RD =100/100,000 RR =2 Group rate = 32/20,000 = 160/100,000 % exposure =12,000/20,000=60% Adapted from Rothman-Greenland Table 23-2 E+ E- 28 20,000 D+ PY 16 8,000 12 12,000 Group 1 (Québec) IEIE = 200/100,000 IoIo =100/100,000 RD =100/100,000 RR =2 Group rate = 28/20,000 = 140/100,000 % exposure =8,000/20,000=40%

21. 21 No ecologic bias 110 120 140 130 150 160 170 180 190 200 10090 80 70605040302010 RATE (per 100,000) % EXPOSURE IRR==2 = IEIE IoIo 100/100,000 200/100,000 Québec Ontario

22. 22 Ecologic bias (rate difference varies across groups) E+E- 27 20,000 D+ PY 20 13,000 7 7,000 Group 2 (Ontario) IEIE = 154/100,000 IoIo =100/100,000 RD =54/100,000 RR =1.54 Group rate = 27/20,000 = 135/100,000 % exposure =13,000/20,000=65% E+ E- 33 20,000 D+ PY 20 7,000 13 13,000 Group 1 (Québec) IEIE = 286/100,000 IoIo =100/100,000 RD =186/100,000 RR =2.86 Group rate = 33/20,000 = 165/100,000 % exposure =7,000/20,000=35%

23. 23 Ecologic bias 110 120 140 130 150 160 170 180 190 200 10090 80 70605040302010 RATE (per 100,000) % EXPOSURE IRR==0.5 = IEIE IoIo 200/100,000 100/100,000

24. 24 Ecologic bias (reference rate varies across groups) E+E- 46 20,000 D+ PY 40 16,000 6 4,000 Group 2 (Ontario) IEIE = 250/100,000 IoIo =150/100,000 RD =100/100,000 RR =1.67 Group rate = 46/20,000 = 230/100,000 % exposure =16,000/20,000=80% E+ E- 28 20,000 D+ PY 16 8,000 12 12,000 Group 1 (Québec) IEIE = 200/100,000 IoIo =100/100,000 RD =100/100,000 RR =2 Group rate = 28/20,000 = 140/100,000 % exposure =8,000/20,000=40%

25. 25 Ecologic bias 0 100 150 200 250 10090 80 70605040302010 RATE (per 100,000) % EXPOSURE IRR==5.5 = IEIE IoIo 275/100,000 50/100,000

26. 26 (Koepsell & Weiss)

27. 27 Outline 1.Examples 2.Definition 3.Ecologic fallacy Definition Valid ecologic study Rate difference varies Reference rate varies 4.Contextual effects 5.Rationale for ecologic studies 6.Ecologic confounders

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29. 29 Neighborhood social class as aggregate of individual social classes Can differ from study subjects’ social class Neighborhood social class as contextual variable Same contextual variable for all subjects

30. Example: ecologic effect 30

31. 31 Outline 1.Examples 2.Definition 3.Ecologic fallacy Definition Valid ecologic study Rate difference varies Reference rate varies 4.Contextual effects 5.Rationale for ecologic studies 6.Ecologic confounders

32. 32 1.Low cost and convenience 2.Measurement limitation of individual-level studies 3.Design limitations of individual-level studies Koepsell and Weiss, Figure 12.1 4.Simplicity of analysis and presentation 5.Instrumental variables Rationale for ecologic studies

33. 33 (Koepsell & Weiss)

34. 34 Outline 1.Examples 2.Definition 3.Ecologic fallacy Definition Valid ecologic study Rate difference varies Reference rate varies 4.Contextual effects 5.Rationale for ecologic studies 6.Ecologic confounders

35. 35 No ecologic bias Country 1Country 2Country 3 CovariateExposurePYRatePYRatePYRate Yes 300060040006004000600 No1200050080005006000500 RR 1.2 NoYes200060040006006000600 No800050080005009000500 RR 1.2 SumYes5000600800060010000600 No200005001600050015000500 RR 1.2 (rates per 100,000 person-year) (Note: no individual-level confounding) Ecologic analysis % exposed20%33%40% % covariate60%50%40% Overall disease rate520533540 Crude RR = 1.2 Adjusted RR = 1.2 Crude is valid!

36. 36 Country 1Country 2Country 3 CovariateExposurePYRatePYRatePYRate Yes 300060040006004000600 No1200050080005006000500 RR 1.2 NoYes200020040002006000200 No800010080001009000100 RR 2 2 2 SumYes5000440800040010000360 No200003401600030015000260 RR 1.3 1.4 (rates per 100,000 person-year) (Note: no individual-level confounding) Ecologic analysis % exposed20%33%40% % covariate60%50%40% Overall disease rate360333300 Crude RR = 0.3 Adjusted RR = 1.3 Adjusted is valid! Crude ecologic bias No stratum-specific ecologic bias

37. 37 Country 1Country 2Country 3 CovariateExposurePYRatePYRatePYRate Yes 8000500130001500140001000 No1200050012000150060001000 RR 1 1 1 NoYes200010020003006000200 No280001002300030024000200 RR 1 1 1 SumYes1000042015000134020000760 No400002203500071130000360 RR 1.9 2.1 (rates per 100,000 person-year) Ecologic analysis % exposed20%30%40% % covariate40%50%40% Overall disease rate260900520 Crude RR = 8.6 Adjusted RR = 8.6 No valid estimate available! Ecologic bias (crude and stratum-specific)

38. 38 Another example

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