TY - JOUR
T1 - Residential Mobility and Geospatial Disparities in Colon Cancer Survival
AU - Wiese, Daniel
AU - Stroup, Antoinette M.
AU - Maiti, Aniruddha
AU - Harris, Gerald
AU - Lynch, Shannon M.
AU - Vucetic, Slobodan
AU - Henry, Kevin A.
N1 - Publisher Copyright:
©2020 American Association for Cancer Research.
PY - 2020/11/1
Y1 - 2020/11/1
N2 - Background: Identifying geospatial cancer survival disparities is critical to focus interventions and prioritize efforts with limited resources. Incorporating residential mobility into spatial models may result in different geographic patterns of survival compared with the standard approach using a single location based on the patient's residence at the time of diagnosis. Methods: Data on 3,949 regional-stage colon cancer cases diagnosed from 2006 to 2011 and followed until December 31, 2016, were obtained from the New Jersey State Cancer Registry. Geographic disparity based on the spatial variance and effect sizes from a Bayesian spatial model using residence at diagnosis was compared with a time-varying spatial model using residential histories [adjusted for sex, gender, substage, race/ethnicity, and census tract (CT) poverty]. Geographic estimates of risk of colon cancer death were mapped. Results: Most patients (65%) remained at the same residence, 22% changed CT, and 12% moved out of state. The time-varying model produced a wider range of adjusted risk of colon cancer death (0.85–1.20 vs. 0.94–1.11) and resulted in greater geographic disparity statewide after adjustment (25.5% vs. 14.2%) compared with the model with only the residence at diagnosis. Conclusions: Including residential mobility may allow for more precise estimates of spatial risk of death. Results based on the traditional approach using only residence at diagnosis were not substantially different for regional stage colon cancer in New Jersey. Impact: Including residential histories opens up new avenues of inquiry to better understand the complex relationships between people and places, and the effect of residential mobility on cancer outcomes.
AB - Background: Identifying geospatial cancer survival disparities is critical to focus interventions and prioritize efforts with limited resources. Incorporating residential mobility into spatial models may result in different geographic patterns of survival compared with the standard approach using a single location based on the patient's residence at the time of diagnosis. Methods: Data on 3,949 regional-stage colon cancer cases diagnosed from 2006 to 2011 and followed until December 31, 2016, were obtained from the New Jersey State Cancer Registry. Geographic disparity based on the spatial variance and effect sizes from a Bayesian spatial model using residence at diagnosis was compared with a time-varying spatial model using residential histories [adjusted for sex, gender, substage, race/ethnicity, and census tract (CT) poverty]. Geographic estimates of risk of colon cancer death were mapped. Results: Most patients (65%) remained at the same residence, 22% changed CT, and 12% moved out of state. The time-varying model produced a wider range of adjusted risk of colon cancer death (0.85–1.20 vs. 0.94–1.11) and resulted in greater geographic disparity statewide after adjustment (25.5% vs. 14.2%) compared with the model with only the residence at diagnosis. Conclusions: Including residential mobility may allow for more precise estimates of spatial risk of death. Results based on the traditional approach using only residence at diagnosis were not substantially different for regional stage colon cancer in New Jersey. Impact: Including residential histories opens up new avenues of inquiry to better understand the complex relationships between people and places, and the effect of residential mobility on cancer outcomes.
KW - Bayes Theorem
KW - Colonic Neoplasms/epidemiology
KW - Humans
KW - New Jersey/epidemiology
KW - Population Dynamics
KW - Residence Characteristics
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UR - https://www.webofscience.com/api/gateway?GWVersion=2&SrcApp=purepublist2023&SrcAuth=WosAPI&KeyUT=WOS:000585070300003&DestLinkType=FullRecord&DestApp=WOS
U2 - 10.1158/1055-9965.EPI-20-0772
DO - 10.1158/1055-9965.EPI-20-0772
M3 - Article
C2 - 32759382
SN - 1055-9965
VL - 29
SP - 2119
EP - 2125
JO - Cancer Epidemiology Biomarkers and Prevention
JF - Cancer Epidemiology Biomarkers and Prevention
IS - 11
ER -