Census and geographic differences between respondents and nonrespondents in a case-control study of non-Hodgkin lymphoma.
To quantify nonresponse bias and estimate its potential impact, the authors compared census-based socioeconomic and demographic factors and geographic locations among respondents and nonrespondents in a multicenter case-control study of non-Hodgkin lymphoma (1998-2000). Using a geographic information system, the authors mapped current addresses and linked them to the 2000 US Census database to determine group-level demographic and socioeconomic information. They used logistic regression analysis to compute the risk of being a nonrespondent, separately for cases and controls. They used spatial scan methods to evaluate spatial clustering at each study center. Among cases at one or more centers, nonresponse was significantly associated with non-White race, lower household income, a greater proportion of multiple-unit housing, fewer years of education, and living in a more urbanized area. For most factors, the authors observed similar patterns among controls, although findings were mostly nonsignificant. They found two nonrandom elliptical clusters in Los Angeles, California, and Detroit, Michigan, that disappeared after adjustment for the demographic factors. The authors determined the bias in non-Hodgkin lymphoma risk associated with census-tract educational level by comparing risks among respondents and all subjects. The bias was 8%, indicating that the socioeconomic and demographic differences between respondents and nonrespondents did not result in a large bias in the risk estimate for education.
Shen
Min
M
Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD 20892, USA.
Cozen
Wendy
W
Huang
Lan
L
Colt
Joanne
J
De Roos
Anneclaire J
AJ
Severson
Richard K
RK
Cerhan
James R
JR
Bernstein
Leslie
L
Morton
Lindsay M
LM
Pickle
Linda
L
Ward
Mary H
MH
D000328:Adult; D000368:Aged; D015982:Bias; D016022:Case-Control Studies; D019352:Censuses; D003625:Data Collection; D004812:Epidemiologic Methods; D005006:Ethnicity; D005260:Female; D040362:Geographic Information Systems; D005843:Geography; D006801:Humans; D016015:Logistic Models; D008228:Lymphoma, Non-Hodgkin / Q000453:epidemiology*; D008297:Male; D008875:Middle Aged; D044469:Racial Groups; D012307:Risk Factors; D018426:SEER Program; D012959:Socioeconomic Factors; D014481:United States / Q000453:epidemiology