期刊
HEALTH & PLACE
卷 74, 期 -, 页码 -出版社
ELSEVIER SCI LTD
DOI: 10.1016/j.healthplace.2022.102771
关键词
Residential mobility; Exposure misclassification; Selection bias; Epidemiology
资金
- NIH/NIEHS [R01ES029509]
- National Heart, Lung, and Blood Institute, National Institutes of Health, Depart-ment of Health and Human Services [HHSN268201700001I, HHSN268201700002I, HHSN268201700003I, HHSN268201700004I, HHSN268201700005I]
- NIH (NHLBI) [U01 2U01HL096812, 2U01HL096814, 2U01HL096899, 2U01HL096902, 2U01HL096917]
- NIH (NINDS) [U01 2U01HL096812, 2U01HL096814, 2U01HL096899, 2U01HL096902, 2U01HL096917]
- NIH (NIA) [U01 2U01HL096812, 2U01HL096814, 2U01HL096899, 2U01HL096902, 2U01HL096917]
- NIH (NIDCD) [U01 2U01HL096812, 2U01HL096814, 2U01HL096899, 2U01HL096902, 2U01HL096917]
- NHLBI [R01-HL70825]
Current research on the characteristics and predictors of movers is limited. In this study, we analyzed the ARIC cohort to identify important predictors of moving for different types of movers, and found that interaction between characteristics plays a crucial role. This work has important implications for epidemiological research and studies focusing on residential mobility as an exposure.
Current efforts to characterize movers and identify predictors of moving have been limited. We used the ARIC cohort to characterize non-movers, short-distance movers, and long-distance movers, and employed best subset algorithms to identify important predictors of moving, including interactions between characteristics. Short-and long-distance movers were notably different from non-movers, and important predictors of moving differed based on the distance of the residential move. Importantly, systematic inclusion of interaction terms enhanced model fit and was substantively meaningful. This work has important implications for epidemiologic studies of contextual exposures and those treating residential mobility as an exposure.
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