Factors associated with residential mobility in children with leukemia: implications for assigning exposures.
OBJECTIVE
In epidemiologic studies, neighborhood characteristics are often assigned to individuals based on a single residence despite the fact that people frequently move and, for most cancer outcomes, the relevant time-window of exposure is not known. The authors evaluated residential mobility patterns for a population-based series of childhood leukemia cases enrolled in the Northern California Childhood Leukemia Study.


METHODS
Complete residential history from 1 year before birth to date of diagnosis was obtained for 380 cases diagnosed between 1995 and 2002. All residences were assigned U.S. Census block group designations using a geographic information system.


RESULTS
Overall, two-thirds (65.8%) of children had moved between birth and diagnosis, and one-third (34.5%) moved during the first year of life. Approximately 25% of the mothers had moved during the year before the child's birth. Multivariable analysis indicated greater residential mobility to be associated with older age of the child at diagnosis, younger age of the mother at child's birth, and lower household income. Among those who had moved, residential urban/rural status for birth and diagnosis residences changed for about 20% of subjects, and neighborhood socioeconomic status for 35%.


CONCLUSIONS
These results suggest that neighborhood attribute estimates in health studies should account for patterns of residential mobility. Estimates based on a single residential location at a single point in time may lead to different inferences.
Urayama
Kevin Y
KY
School of Public Health, University of California, Berkeley, CA 94704, USA. kurayama@berkeley.edu
Von Behren
Julie
J
Reynolds
Peggy
P
Hertz
Andrew
A
Does
Monique
M
Buffler
Patricia A
PA
D000293:Adolescent; D002140:California / Q000453:epidemiology; D016022:Case-Control Studies; D002648:Child; D002675:Child, Preschool; D004781:Environmental Exposure / Q000706:statistics & numerical data*; D005260:Female; D040362:Geographic Information Systems; D006801:Humans; D007223:Infant; D007407:Interviews as Topic; D007938:Leukemia / Q000453:epidemiology*; D011157:Population Dynamics / Q000706:statistics & numerical data*; D011247:Pregnancy; D011297:Prenatal Exposure Delayed Effects / Q000453:epidemiology; D015995:Prevalence; D012424:Rural Population / Q000706:statistics & numerical data; D012923:Social Class; D014505:Urban Population / Q000706:statistics & numerical data