Detecting survival effects of socioeconomic status: problems in the use of aggregate measures.
Direct measures of SES are seldom included in medical records or large databases on disease incidence or survival, forcing researchers to infer the SES characteristics of individuals from aggregate data (e.g. census tract-level income, education, etc.). This paper assesses the degree of error that results from such inference and the impact this error may have on reported relationships between SES and survival. The authors obtained both individual and census tract-level data on 536 persons diagnosed with cancer between 1980 and 1982 and monitored their survival through 1992. Pearson correlations between individual-level and census tract-level SES variables ranged between 0.2 and 0.4. Statistically significant relationships between SES and survival were observed in the models based on individual-level but not census tract-level SES data. The authors computed the degree to which inference of individual-level from census tract-level SES reduces estimates of risk ratios across SES. It appears likely that much larger numbers of observations than have been used in published studies will be needed to better understand the relationship of SES to survival and other disease outcomes.
Greenwald
H P
HP
Sacramento Center, School of Public Administration, University of Southern California 95814-2919, USA.
Polissar
N L
NL
Borgatta
E F
EF
McCorkle
R
R
D000367:Age Factors; D004522:Educational Status; D005260:Female; D006801:Humans; D008137:Longitudinal Studies; D008297:Male; D015233:Models, Statistical; D009369:Neoplasms / Q000401:mortality*; D012737:Sex Factors; D012959:Socioeconomic Factors; D016019:Survival Analysis