Residential mobility in early childhood and the impact on misclassification in pesticide exposures
Open accessAbstract
Studies of environmental exposures and childhood cancers that rely on records often only use maternal address at birth or address at cancer diagnosis to assess exposures in early childhood, possibly leading to exposure misclassification and questionable validity due to residential mobility during early childhood. Our objective was to assess patterns and identify factors that may predict residential mobility in early childhood, and examine the impact of mobility on early childhood exposure assessment for agriculturally applied pesticides and childhood cancers in California. We obtained the addresses at diagnosis of all childhood cancer cases born in 1998-2011 and diagnosed at 0-5 years of age (n = 6478) from the California Cancer Registry (CCR), and their birth addresses from linked birth certificates. Controls were randomly selected from California birth records and frequency matched (20:1) to all cases by year of birth. We obtained residential histories from a public-record database LexisNexis for both case (n = 3877 with age at diagnosis 1-5 years) and control (n = 99,262) families. Logistic regression analyses were conducted to assess the socio-demographic factors in relation to residential mobility in early childhood. We employed a Geographic Information System (GIS)-based system to estimate children's first year of life exposures to agriculturally applied pesticides based on birth vs diagnosis address or residential histories based upon Lexis-Nexis Public Records and assessed agreement between exposure measures using Spearman correlations and kappa statistics. Over 20% of case and control children moved in their first year of life, and 55% of children with cancer moved between birth and diagnosis. Older age at diagnosis, younger maternal age, lower maternal education, not having a Hispanic ethnic background, use of public health insurance, and non-metropolitan residence at birth were predictors of higher residential mobility. There was moderate to strong correlation (Spearman correlation = 0.76-0.83) and good agreement (kappa = 0.75-0.81) between the first year of life exposure estimates for agricultural pesticides applied within 2 km of a residence relying on an address at birth or at diagnosis or LexisNexis addresses; this did not differ by outcome status, but agreement decreased with decreasing buffer size, and increasing distance moved or age at diagnosis. These findings suggest that residential addresses collected at one point in time may represent residential history in early childhood to a reasonable extent; nevertheless, they exposure misclassification in the first year of life remains an issue. Also, the highest proportion of women not captured by LexisNexis were Hispanic women born in Mexico and those living in the lowest SES neighborhoods, i.e. possibly those with the higher environmental exposures, as well as younger women and those with less than high school education. Though LexisNexis only captures a sub-population, its data may be useful for augmenting address information and assessing the extent of exposure misclassification when estimating environmental exposures in large record linkage studies. Future research should investigate how to correct for exposure misclassification introduced by residential mobility that is not being captured by records.
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Two studies concluded that address at birth was adequate for research on the effect of early exposures.
“while the other 2 concluded that address at birth was adequate for research on the effect of early exposures.15,57”
From The quality of social determinants data in the electronic health record: a systematic review (2021) · cites this paper as [57]
The Discussion conclusion says that a single residential address should be used with caution to estimate early-childhood exposures, especially after the first year of life. Although it reports moderate-to-good agreement for pesticide exposures assessed around birth and alternative addresses, it does not conclude that the birth address is adequate for the stated research purpose. (LLM, conf=0.86)
Checked by a reasoning model — may be wrong.
Experimental — accuracy not yet measuredThree studies concluded that a single patient address was sufficient when patients may have moved several times over the study period.
“When confronted with data from patients who may have moved several times over the study period, 3 studies concluded that a single patient address was sufficient;15,56,57”
From The quality of social determinants data in the electronic health record: a systematic review (2021) · cites this paper as [57]
The Discussion (page unavailable) reports moderate-to-strong agreement between pesticide exposure estimates based on a single address and residential histories, and says misclassification may be acceptable for the first year of life. It does not conclude that one address is generally sufficient when patients have moved several times: agreement varied with distance moved and buffer size, and the paper cautions that misclassification remains an issue. (LLM, conf=0.86)
Experimental — accuracy not yet measuredFour (80%) of the included articles explored the impact of residential mobility on exposure assessment.
“Four (80%) of the included articles explored the impact of residential mobility on exposure assessment; that is, whether patients’ moving impacted the results of studies looking at environmental outcomes.15,16,56,57”
From The quality of social determinants data in the electronic health record: a systematic review (2021) · cites this paper as [57]
Ling et al noticed significant differences between patients with complete address information and those who were missing information; Hispanic women born in Mexico and people living in poor neighborhoods were more likely to have missing addresses.
“In a study on using patient addresses to determine pesticide exposures, Ling et al57 noticed that there were significant differences between patients with complete address information and those who were missing information. In particular, Hispanic women born in Mexico and people living in poor neighborhoods were more likely to have missing addresses.”
From The quality of social determinants data in the electronic health record: a systematic review (2021) · cites this paper as [57]
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Cites
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“To our knowledge, only a couple of studies examined the post-partum residential mobility either in a statewide sample of California women (Margerison-Zilko et al., 2016) or in enrolled childhood leukemia cases of a Northern California Study (Urayama et al., 2009) but both focused on factors associated with residential…”
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BackgroundDeterminants of Agricultural Pesticide Concentrations in Carpet Dust
Gunier, R. B., Ward, M. H., Airola, M., Bell, E. M., Colt, J. S., NISHIOKA, M. G., Buffler, P. A., Reynolds, P., Rull, R. P., Hertz, A., et al. (2011) · Environmental Health Perspectives · doi:10.1289/ehp.1002532 · Cited by 145 · cited 1× · see citing works
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“5 Pesticide Exposures We estimated agricultural pesticide exposures using a GIS-based Residential Ambient Pesticide Estimation System, as previously described (Cockburn et al., 2011; Rull and Ritz, 2003).”
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“…exposures based upon one maternal residential address, which is readily available from birth certificates (Carozza et al., 2009; Heck et al., 2014; Lavigne et al., 2017; Reynolds et al., 2005; von Ehrenstein et al., 2016) and/or residential address at diagnosis, as was done in some childhood…”
BackgroundResidential Exposure to Traffic in California and Childhood Cancer
Reynolds, P., Behren, J. V., Gunier, R., Goldberg, D. E., & Hertz, A. (2004) · Epidemiology · doi:10.1097/01.ede.0000101749.28283.de · Cited by 115 · cited 1× · see citing works
“For more than 50% of childhood cancer cases under age 5 diagnosed in California between 1988 and 2005, address at birth differed from the address at cancer diagnosis (Reynolds et al., 2004; Urayama et al., 2009), which raises concerns about using residence at birth to assess exposures in early childhood.”
BackgroundProstate cancer and ambient pesticide exposure in agriculturally intensive areas in California.
Cockburn, M., Mills, P., Zhang, X.-B., Zadnick, J., Goldberg, D., & Ritz, B. (2011) · American Journal of Epidemiology · doi:10.1093/aje/kwr003 · Cited by 110 · cited 2× · see citing works
“5 Pesticide Exposures We estimated agricultural pesticide exposures using a GIS-based Residential Ambient Pesticide Estimation System, as previously described (Cockburn et al., 2011; Rull and Ritz, 2003).”
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Reynolds, P., Behren, J. V., Gunier, R., Goldberg, D. E., Harnly, M., & Hertz, A. (2005) · Epidemiology · doi:10.1097/01.ede.0000147119.32704.5c · Cited by 100 · cited 1× · see citing works
“However, they often need to assign exposures based upon one maternal residential address, which is readily available from birth certificates (Carozza et al., 2009; Heck et al., 2014; Lavigne et al., 2017; Reynolds et al., 2005; von Ehrenstein et al., 2016) and/or residential address at diagnosis, as was done in some c…”
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“In contrast, individual-level measures of proximity to pesticide applications or crops as a proxy within a ~800–1000 m buffer of a child’s residence (Cockburn et al., 2011; Gómez-Barroso et al., 2016; Rull et al., 2009) may be subject to considerable misclassification due to residential mobility.”
BackgroundAgricultural Pesticides and Risk of Childhood Cancers
Carozza, S. E., Li, B., Wang, Q., Horel, S., & Cooper, S. (2009) · International Journal of Hygiene and Environmental Health · doi:10.1016/j.ijheh.2008.06.002 · Cited by 91 · cited 1× · see citing works
“However, they often need to assign exposures based upon one maternal residential address, which is readily available from birth certificates (Carozza et al., 2009; Heck et al., 2014; Lavigne et al., 2017; Reynolds et al., 2005; von Ehrenstein et al., 2016) and/or residential address at diagnosis, as was done in some c…”
BackgroundPost Office Box Addresses: A Challenge for Geographic Information System-Based Studies
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“, 2011) and other studies using buffer sizes between 500 m and 8 km radius (Bell et al., 2001; Gemmill et al., 2013; Gunier et al., 2011; Shaw et al., 2018; Shelton et al., 2014; Wofford et al., 2013) to estimate exposures to agricultural pesticide applied in proximity to residences.”
BackgroundEpidemiology of Rhabdoid Tumors of Early Childhood
Heck, J., Lombardi, C., Cockburn, M., Meyers, T. J., Wilhelm, M., & Ritz, B. (2012) · Pediatric Blood & Cancer · doi:10.1002/pbc.24141 · Cited by 71 · cited 1×
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“, 2016) and/or residential address at diagnosis, as was done in some childhood cancer studies (Carozza et al., 2008; García-Pérez et al., 2016, 2015).”
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Jacquez, G., Slotnick, M., Meliker, J., Avruskin, G., Copeland, G., & Nriagu, J. (2011) · American Journal of Epidemiology · doi:10.1093/aje/kwq350 · Cited by 65 · cited 1×
“Earlier studies have shown that addresses acquired from LexisNexis are useful for reconstructing residential histories for subjects in epidemiological studies with an overall match rate of ~70–85% when detailed address histories were obtained in interviews (Hurley et al., 2017; Jacquez et al., 2011; Wheeler and Wang,…”
BackgroundUrayama, K., Behren, J. V., Reynolds, P., Hertz, A., Does, M., & Buffler, P. (2009) · Annals of Epidemiology · doi:10.1016/j.annepidem.2009.03.001 · Cited by 65 · cited 12×
“To our knowledge, only a couple of studies examined the post-partum residential mobility either in a statewide sample of California women (Margerison-Zilko et al., 2016) or in enrolled childhood leukemia cases of a Northern California Study (Urayama et al., 2009) but both focused on factors associated with residential…”
BackgroundMethodInfluentialChildhood leukemia and residential proximity to industrial and urban sites.
García-Pérez, J., López-Abente, G., Gómez-Barroso, D., Morales-Piga, A., Romaguera, E. P., Tamayo, I., Fernández-Navarro, P., & Ramis, R. (2015) · Environmental Research · doi:10.1016/j.envres.2015.05.014 · Cited by 63
Exposure misclassification due to residential mobility during pregnancy.
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“While previous studies that examined residential proximity to environmental exposures have referred to exposure misclassification when solely using address at delivery or conception instead of a full residential history (Fell et al., 2004; Hodgson et al., 2015; Pennington et al., 2016; Schulman et al., 1993) and the p…”
BackgroundGómez-Barroso, D., García-Pérez, J., López-Abente, G., Tamayo-Uria, I., Morales-Piga, A., Romaguera, E. P., & Ramis, R. (2016) · International Journal of Health Geographics · doi:10.1186/s12942-016-0047-7 · Cited by 59 · cited 1× · see citing works
“In contrast, individual-level measures of proximity to pesticide applications or crops as a proxy within a ~800–1000 m buffer of a child’s residence (Cockburn et al., 2011; Gómez-Barroso et al., 2016; Rull et al., 2009) may be subject to considerable misclassification due to residential mobility.”
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“, 1993) and the potential bias resulting from residential mobility during pregnancy (Pennington et al., 2016), they rarely focused on early childhood.”
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“These cutoffs were primarily selected for estimating the level of misclassification in buffer-based exposure assessment, adopted by our group (500 m or 2 km) (Costello et al., 2009; Ling et al., 2018; Wang et al., 2011) and other studies using buffer sizes between 500 m and 8 km radius (Bell et al.”
MethodSelf-citationvon Ehrenstein, O. V., Heck, J., Park, A. S., Cockburn, M., Escobedo, L. A., & Ritz, B. (2015) · Environmental Health Perspectives · doi:10.1289/ehp.1408582 · Cited by 54 · cited 1× · see citing works
“…which is readily available from birth certificates (Carozza et al., 2009; Heck et al., 2014; Lavigne et al., 2017; Reynolds et al., 2005; von Ehrenstein et al., 2016) and/or residential address at diagnosis, as was done in some childhood cancer studies (Carozza et al., 2008; García-Pérez et…”
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“Previous geographic studies suggested that generally 70–80% of the addresses during automated geocoding have a positional error of 100 m or less depending on geocoding platforms, although this could be up to a few kilometers in rural areas (Cayo and Talbot, 2003; Faure et al., 2017).”
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“, 2011) and other studies using buffer sizes between 500 m and 8 km radius (Bell et al., 2001; Gemmill et al., 2013; Gunier et al., 2011; Shaw et al., 2018; Shelton et al., 2014; Wofford et al., 2013) to estimate exposures to agricultural pesticide applied in proximity to residences.”
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“Address information from LexisNexis has several intrinsic issues including multiple unique addresses for the same time period, inaccurate or missing first seen and last seen dates associated with certain addresses (Hurley et al., 2017), disagreement between LexisNexis addresses and registry-obtained addresses at the t…”
BackgroundMethodAssessment of Residential History Generation Using a Public-Record Database
Wheeler, D., & Wang, A. (2015) · International Journal of Environmental Research and Public Health · doi:10.3390/ijerph120911670 · Cited by 47 · cited 2×
“Following previously developed methods (Hurley et al., 2017; Wheeler and Wang, 2015), we cleaned and processed all addresses: first, we removed all post office box (P.”
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“, 2011) and other studies using buffer sizes between 500 m and 8 km radius (Bell et al., 2001; Gemmill et al., 2013; Gunier et al., 2011; Shaw et al., 2018; Shelton et al., 2014; Wofford et al., 2013) to estimate exposures to agricultural pesticide applied in proximity to residences.”
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“While previous studies that examined residential proximity to environmental exposures have referred to exposure misclassification when solely using address at delivery or conception instead of a full residential history (Fell et al., 2004; Hodgson et al., 2015; Pennington et al., 2016; Schulman et al., 1993) and the p…”
BackgroundGarcía-Pérez, J., Morales-Piga, A., Aguaded, I., Gómez-Barroso, D., Tamayo-Uria, I., Romaguera, E. P., Fernández-Navarro, P., López-Abente, G., & Ramis, R. (2016) · Environmental Research · doi:10.1016/j.envres.2016.02.036 · Cited by 30
Residential agricultural pesticide exposures and risks of spontaneous preterm birth
Shaw, G., Yang, W., Roberts, E., Kegley, S., Stevenson, D., Carmichael, S., & English, P. (2018) · Epidemiology · doi:10.1097/ede.0000000000000757 · Cited by 24 · cited 1×
“, 2011) and other studies using buffer sizes between 500 m and 8 km radius (Bell et al., 2001; Gemmill et al., 2013; Gunier et al., 2011; Shaw et al., 2018; Shelton et al., 2014; Wofford et al., 2013) to estimate exposures to agricultural pesticide applied in proximity to residences.”
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Nikkilä, A., Kendall, G., Raitanen, J., Spycher, B., Lohi, O., & Auvinen, A. (2018) · Environmental Research · doi:10.1016/j.envres.2018.06.035 · Cited by 16 · cited 3×
“To date, only a few studies investigated the impact of residential mobility in early childhood on exposure assessment or effect estimates (Brokamp et al., 2016; Danysh et al., 2017; Nikkilä et al., 2018; Tee Lewis et al., 2019).”
BackgroundResidential mobility and childhood leukemia
Amoon, A. T., Oksuzyan, S., Crespi, C. M., Arah, O., Cockburn, M., Vergara, X., & Kheifets, L. (2018) · Environmental Research · doi:10.1016/j.envres.2018.03.016 · Cited by 15 · cited 8×
“To our knowledge, only a couple of studies examined the post-partum residential mobility either in a statewide sample of California women (Margerison-Zilko et al., 2016) or in enrolled childhood leukemia cases of a Northern California Study (Urayama et al., 2009) but both focused on factors associated with residential…”
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Margerison-Zilko, C., Cubbin, C., Jun, J.-N., Marchi, K., & Braveman, P. (2015) · Maternal and Child Health Journal · doi:10.1007/s10995-015-1812-0 · Cited by 6 · cited 16×
“A uthor M anuscript A uthor M anuscript A uthor M anuscript A uthor M anuscript In a 2003–2007 California statewide representative survey, only 14% of women moved in the 2–7 months post-partum (Margerison-Zilko et al., 2016), but the frequency of residential moves increases with a child’s age.”
BackgroundMethodInfluential
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The quality of social determinants data in the electronic health record: a systematic review
Cook, L. A., Sachs, J., & Weiskopf, N. G. (2021) · Journal of the American Medical Informatics Association · doi:10.1093/jamia/ocab199 · Cited by 153 · see citing works
“Four (80%) of the included articles explored the impact of residential mobility on exposure assessment; that is, whether patients’ moving impacted the results of studies looking at environmental outcomes.(15,16,56,57) In all of these articles, bias was characterized as misclassification of exposure to contaminants, an…”
BackgroundClark, C., Johnson, N., Soriano, M., Warren, J., Sorrentino, K. M., Kadan-Lottick, N., Saiers, J., Ma, X.-M., & Deziel, N. (2022) · Environmental Health Perspectives · doi:10.1289/ehp11092 · Cited by 45
“ID2W 2 km Exposed 14 (3) 37 (2) 7 (2) 13 (1) Unexposed 391 (97) 2,043 (98) 398 (98) 2,067 (99) ID2W 5 km Exposed 31 (8) 122 (6) 18 (4) 61 (3) Unexposed 374 (92) 1,958 (94) 387 (96) 2,019 (97) ID2W 10 km Exposed 59 (15) 270 (13) 41 (10) 153 (7) Unexposed 346 (85) 1,810 (87) 364 (89) 1,927 (83) IDups 2 km Exposed 6 (2)…”
Acute lymphoid leukemia etiopathogenesis
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Self-citationPrenatal ambient pesticide exposure and childhood retinoblastoma
Thompson, S., Ritz, B., Cockburn, M., & Heck, J. (2022) · International Journal of Hygiene and Environmental Health · doi:10.1016/j.ijheh.2022.114025 · Cited by 27 · see citing works
Self-citationSocioeconomic Disparities in Colon Cancer Survival
Wiese, D., Stroup, A., Maiti, A., Harris, G., Lynch, S. M., Vucetic, S., & Henry, K. A. (2020) · Epidemiology · doi:10.1097/ede.0000000000001216 · Cited by 21 · see citing works
Liew, Z., Ehrenstein, O. S. V., Ling, C., Yuan, Y., Meng, Q., Cui, X., Park, A. S., Uldall, P. V., Olsen, J., Cockburn, M., et al. (2020) · Toxics · doi:10.3390/toxics8030052 · Cited by 23 · see citing works
“However, our recent study in the same study population compared address on birth records to residential histories from a public-record database (LexisNexis) [77].”
BackgroundSelf-citationThe role of residential history in cancer research: A scoping review.
Namin, S., Zhou, Y., Neuner, J., & Beyer, K. (2020) · Social Science & Medicine (1967) · doi:10.1016/j.socscimed.2020.113657 · Cited by 15 · see citing works
Matching participant address with public records database in a US national longitudinal cohort study
Brooks, M., Bennett, A., Lovasi, G., Hurvitz, P., Colabianchi, N., Howard, V., Manly, J. M., & Judd, S. (2021) · SSM: Population Health · doi:10.1016/j.ssmph.2021.100887 · Cited by 14
“…based on neighborhood socioeconomic characteristics that differ by race and sex (Brown et al., 2011; Grimaud et al., 2011; Hart et al., 2000; Howard et al., 2016; Lisabeth et al., 2007; Pujades-Rodriguez et al., 2014), it is important to have unbiased and comprehensive residential location data.”
BackgroundMedgyesi, D., Fisher, J., Flory, A., Hayes, R., Thurston, G., Liao, L. M., Ward, M., Silverman, D., & Jones, R. R. (2021) · Environmental Research · doi:10.1016/j.envres.2021.110986 · Cited by 14 · see citing works
Mupfudze, T., Martinez, A., Noreen, S., Stewart, D. E., Schold, J., & Cartwright, L. (2024) · PLoS ONE · doi:10.1371/journal.pone.0308407 · Cited by 13
Constructing Residential Histories in a General Population-Based Representative Sample
Xu, W., Agnew, M., Kamis, C., Schultz, A., Salas, S., Malecki, K., & Engelman, M. (2023) · American Journal of Epidemiology · doi:10.1093/aje/kwad188 · Cited by 12
“Given the relatively novel and unique nature of Lexis-Nexis data, only a few studies have assessed its accuracy, validity, and potential biases (13, 15–17).”
BackgroundSmall-area estimates from consumer trace data
Acolin, A., Decter-Frain, A., & Hall, M. (2022) · Demographic Research · doi:10.4054/demres.2022.47.27 · Cited by 8 · see citing works
“It is similar to other consumer datasets, such as Infutor and LexisNexis, that have also been used in academic research (Diamond, McQuade, and Qian 2019; Ling et al. 2019; Greenlee 2019; Phillips 2020).”
MethodMupfudze, T., Handarova, D. K., Noreen, S., Stewart, D. E., Mohan, S., & Schold, J. (2024) · Kidney International Reports · doi:10.1016/j.ekir.2024.12.011 · Cited by 7
Namin, S., Zhou, Y., McGinley, E., & Beyer, K. (2021) · SSM: Population Health · doi:10.1016/j.ssmph.2021.100823 · Cited by 6
“…commercially available credit reporting companies such as LexisNexis to construct residential histories for epidemiological studies (Bender et al., 2006; Hurley et al., 2017; Jacquez et al., 2011) as they are becoming more popular in cancer research (Ling et al., 2019; Stinchcomb & Roeser, 2016).”
BackgroundDeriving life‐course residential histories in brain bank cohorts: A feasibility study
Melcher, E. M., Vilen, L. H., Pfaff, A., Lim, S., DeWitt, A., Powell, W. R., Bendlin, B. B., & Kind, A. (2024) · Alzheimer s & Dementia · doi:10.1002/alz.13773 · Cited by 4 · see citing works
Clark, C., Warren, J. L., Saiers, J., Ma, X.-M., Bell, M. L., & Deziel, N. (2023) · Journal of Exposure Science and Environmental Epidemiology · doi:10.1038/s41370-023-00636-9 · Cited by 4 · see citing works
Liu, B., Niu, L., & Lee, F. F. (2023) · Journal of Thoracic Disease · doi:10.21037/jtd-23-533 · Cited by 4
“Residential mobility in the general U.S. population and cancer population before and after diagnosis have been previously documented (34-36,42 ,45 ,55 Extending the existing literature, we further quantified the degree of the exposure misclassification between approaches with and without…”
InfluentialChen, Y.-X., Deventer, D. V., Nianogo, R., Vinceti, M., Kang, W., Cockburn, M., Federman, N., & Heck, J. (2024) · International Journal of Hygiene and Environmental Health · doi:10.1016/j.ijheh.2024.114388 · Cited by 3
Self-citationPrenatal pesticide exposure and neuroblastoma – A statewide case-control study in California
Deventer, D. V., Ritz, B., Cockburn, M. G., & Heck, J. (2025) · Environmental Research · doi:10.1016/j.envres.2025.123027 · Cited by 2
Self-citationMckenzie, L., Allshouse, W., Cockburn, M., & Ghosh, D. (2024) · Cancer Epidemiology · doi:10.1016/j.canep.2024.102561 · Cited by 2
Self-citationAccuracy of LexisNexis-derived retrospective address histories in the Sister Study cohort
Ish, J. L., Daniel, M., Ringwald, P., Niehoff, N., Jones, R. R., & White, A. J. (2025) · Journal of Exposure Science and Environmental Epidemiology · doi:10.1038/s41370-025-00802-1 · Cited by 1
Clustering of Pediatric Brain Tumors in Texas, 2000–2017
Hoang, T. T., Rosales, O., Burgess, E., Lupo, P., Scheurer, M., & Oluyomi, A. (2023) · Toxics · doi:10.3390/toxics11040351 · Cited by 1
“While we cannot rule out the prenatal period as a critical window of exposure, there is some evidence that exposures based on addresses at birth and diagnosis are similar [34,35], so these results may also apply to sources of exposure during pregnancy.”
ResultPredictors of maternal residential mobility in a sibling-matched birth cohort in Massachusetts
Legaspi, J. M., & Vieira, V. M. (2026) · Environmental Epidemiology · doi:10.1097/ee9.0000000000000452
“3,7,11 Mothers with higher educational attainment tend to experience housing stability due to greater economic resources and access to stable housing environments.”
InfluentialPidoux, N., de Hoogh, K., Petitpierre, A., Zinsstag, L., & Fuhrimann, S. (2025) · Environmental Challenges · doi:10.1016/j.envc.2025.101337
Prevalence, predictors, and patterns of residential mobility by the parents of preterm infants
Murosko, D. C., Nelin, T. D., Sharma, P., Tam, V. W., Volkova, E., Scott, K. A., Gregory, E. F., & Lorch, S. A. (2025) · Journal of Perinatology · doi:10.1038/s41372-025-02414-x
“Though our analysis was not designed to compare to term infants, we found that preterm mobility rates are aligned with prior estimates that include infants of all gestations [1 – 3 , 5].”
InfluentialBinczewski, N. R., Morimoto, L., Wiemels, J. L., Ma, X.-M., Metayer, C., & Vieira, V. M. (2025) · JNCI Cancer Spectrum · doi:10.1093/jncics/pkaf075
“12 In another California study of childhood cancers diagnosed before age 15, information obtained from LexisNexis showed that two-thirds of cases had moved between their birth and diagnosis date, with higher residential mobility associated with younger maternal age, older child age at diagnosis,…”
InfluentialChildhood cancer risk in Hispanic enclaves in California
Deventer, D. V., Contreras, Z., Li, S.-W., Iwundu, C. N., Ritz, B., Cockburn, M. G., & Heck, J. (2025) · Journal of Immigrant and Minority Health · doi:10.1007/s10903-025-01675-0
Self-citation
- Authors
- Ling, C., Heck, J. E., Cockburn, M., Liew, Z., Marcotte, E., & Ritz, B.
- Affiliations
- University of California, Los Angeles (US)
- University of Southern California (US)
- Yale University (US)
- University of Minnesota (US)
- Corresponding author
- Ritz, Beate
- Venue
- Environmental Research
- Publisher
- Elsevier BV
- Published
- 2019-06
- Volume
- 173
- Pages
- 212-220
- ISSN
- 0013-9351 (ISSN-L)
- PMC
- PMC6553500
- OpenAlex
- W2923518022
- Cited by
- 31
- References
- 44
- Citations by year
- 2026: 2 · 2025: 6 · 2024: 6 · 2023: 5 · 2022: 3 · 2021: 6 · 2020: 3
- FWCI
- 2.21
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- Environmental Research (publishedVersion)
- PubMed (publishedVersion)
- PubMed Central (acceptedVersion)
- eScholarship (California Digital Library) (submittedVersion)
- Funders
- National Institutes of Health (R01ES10544, R21ES019986, R21ES018960, R01CA195218)
- Alex's Lemonade Stand Foundation (17-01882)
- Topics
- Life Sciences › Agricultural and Biological Sciences › Plant Science › Pesticide Exposure and Toxicity
- Health Sciences › Medicine › Oncology › Global Cancer Incidence and Screening
- Physical Sciences › Environmental Science › Health, Toxicology and Mutagenesis › Health, Environment, Cognitive Aging
- Keywords
- residential mobility, early childhood, pesticide exposure, childhood cancer, exposure misclassification, agricultural pesticides, exposure assessment, maternal factors, Hispanic children, California Cancer Registry, birth certificates, residential history, socioeconomic factors, age at diagnosis, maternal education, maternal age, public health insurance, buffer distance
- MeSH terms
- Adult, Aged, California, Child, Child, Preschool, Environmental Exposure, Female, Humans, Infant, Infant, Newborn, Mexico, Pesticides, Population Dynamics, Pregnancy, Young Adult
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