Re: Cohen data suspect at best

["Rad health" <healthrad@HOTMAIL.COM>]

Ruth, I think you are wrong.  Can you document your statement concerning the 

accuracy of census information?



Dr. Field emailed me this reference below as an example of a factor that 

would not be linear between counties and could not be corrected for using 

Cohen's stratifications.  As Dr. Field put it to me, we know both smoking 

and lung cancer rates are higher for blacks than whites.  If you have data 

like Cohen's that under report blacks, Cohen will not be able to adjust for 

it between counties and for sure not within counties.  This misreporting of 

SES and smoking along with other covariates asssociated with SES is enough 

to explain the inverse association alone.  Dr. Cohen, I think this warrants 

the $5000.00 don't you, please donate the money to the American Lung 

Association.



Don



Annals of  Epidemiology  2001 Apr 11:171-193



The use of census data for determining race and education as SES indicators: 

a validation study.



Kwok RK, Yankaskas BC.



Department of Epidemiology, School of Public Health, University of North 

Carolina at Chapel Hill, Chapel Hill, NC 27599-7515, USA.



PURPOSE: Little research has examined the validity of using census data to 

determine an individual's socio-economic status (SES), as measured by race 

and

educational level. This study assessed the accuracy of using aggregate level 

data from United States Census Block Groups in determining race and 

education

SES indicators in a cohort of women from North Carolina. METHODS: The study 

analyzed patient data from the Carolina Mammography Registry and 1990 United

States Census in 21 North Carolina counties. Women (n = 39,546) were 

geocoded to their census block group and their block group characteristics 

(surrogate

measures) were validated with their self-reported values on race and 

education.



An analysis was performed to explore whether using these surrogate measures 

would affect measured associations with the self-reported values. RESULTS:

Whites were accurately identified (84.8%) more consistently than Blacks 

(14.1%) regardless of their urban/rural status. Women without a high school 

diploma or equivalent were accurately identified (56.2%) more often than 

those with higher education levels (45.9%). Analyses using the surrogate 

measures were significantly different than the true values according to 

chi-square statistics.



CONCLUSIONS: Use of census data to derive SES indicators tends to be more 

accurate for the majority than the minority population. Researchers must be

sensitive to the ecologic fallacy when using aggregate level data such as 

the census to determine individual level characteristics.







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