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Spatial clusters of cancer incidence: analyzing 1940 census data linked to 1966-2017 cancer records.
Leiser, Claire L; Taddie, Marissa; Hemmert, Rachael; Richards Steed, Rebecca; VanDerslice, James A; Henry, Kevin; Ambrose, Jacob; O'Neil, Brock; Smith, Ken R; Hanson, Heidi A.
Affiliation
  • Leiser CL; Population Sciences, Huntsman Cancer Institute, University of Utah, Salt Lake City, UT, USA. cleiser@uw.edu.
  • Taddie M; Department of Epidemiology, University of Washington, Seattle, WA, USA. cleiser@uw.edu.
  • Hemmert R; Department of Family and Preventive Medicine, University of Utah, Salt Lake City, UT, USA.
  • Richards Steed R; Department of Obstetrics and Gynecology, University of Utah, Salt Lake City, UT, USA.
  • VanDerslice JA; Population Sciences, Huntsman Cancer Institute, University of Utah, Salt Lake City, UT, USA.
  • Henry K; Department of Geography, University of Utah, Salt Lake City, UT, USA.
  • Ambrose J; Department of Family and Preventive Medicine, University of Utah, Salt Lake City, UT, USA.
  • O'Neil B; Department of Geography and Urban Studies, Temple University, Philadelphia, PA, USA.
  • Smith KR; Population Sciences, Huntsman Cancer Institute, University of Utah, Salt Lake City, UT, USA.
  • Hanson HA; Department of Surgery, University of Utah, Salt Lake City, UT, USA.
Cancer Causes Control ; 31(7): 609-615, 2020 Jul.
Article in En | MEDLINE | ID: mdl-32323050
ABSTRACT

PURPOSE:

A life course perspective to cancer incidence is important for understanding effects of the environment during early life on later cancer risk. We assessed spatial clusters of cancer incidence based on early life location defined as 1940 US Census Enumeration District (ED).

METHODS:

A cohort of 260,585 individuals aged 0-40 years in 1940 was selected. Individuals were followed from 1940 to cancer diagnosis, death, or last residence in Utah. We geocoded ED centroids in Utah for the 1940 Census. Spatial scan statistics with purely spatial elliptic scanning window were used to identify spatial clusters of EDs with excess cancer rates across 26 cancer types, assuming a discrete Poisson model.

RESULTS:

Cancer was diagnosed in 66,904 (25.67%) individuals during follow-up across 892 EDs. Average follow-up was 50.9 years. We detected 15 clusters of excess risk for bladder, breast, cervix, colon, lung, melanoma, oral, ovary, prostate, and soft tissue cancers. An urban area had dense overlap of multiple cancer types, including two EDs at increased risk for five cancer types each.

CONCLUSIONS:

Early environments may contribute to cancer risk later in life. Life course perspectives applied to the study of cancer incidence can provide insights for increasing understanding of cancer etiology.
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Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Neoplasms Type of study: Etiology_studies / Incidence_studies / Observational_studies / Prognostic_studies / Risk_factors_studies Limits: Adolescent / Adult / Child / Child, preschool / Female / Humans / Infant / Male / Newborn Country/Region as subject: America do norte Language: En Journal: Cancer Causes Control Journal subject: EPIDEMIOLOGIA / NEOPLASIAS Year: 2020 Document type: Article Affiliation country: Estados Unidos

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Neoplasms Type of study: Etiology_studies / Incidence_studies / Observational_studies / Prognostic_studies / Risk_factors_studies Limits: Adolescent / Adult / Child / Child, preschool / Female / Humans / Infant / Male / Newborn Country/Region as subject: America do norte Language: En Journal: Cancer Causes Control Journal subject: EPIDEMIOLOGIA / NEOPLASIAS Year: 2020 Document type: Article Affiliation country: Estados Unidos