Evidence map›Paper›PMID 42380543›Full record

ArticleCancer causes & control : CCC2026

Community-level contextual factors associated with lung cancer: a hot spot analysis.

Taylor Jansen, Qian Song, Kristie Long Foley, Elizabeth Dugan

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Article in Cancer causes & control : CCC, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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5 · Who and what money

Authors and funding

4 authors.

Taylor JansenDepartment of Health Sciences, Providence College, Providence, RI, USA. tajanse2@gmail.com.
Qian SongGerontology Department, Donna M. and Robert J. Manning College of Nursing & Health Sciences, University of Massachusetts Boston, Boston, MA, USA.
Kristie Long FoleyDepartment of Implementation Science, Wake Forest University School of Medicine, Winston-Salem, NC, USA.
Elizabeth DuganGerontology Department, Donna M. and Robert J. Manning College of Nursing & Health Sciences, University of Massachusetts Boston, Boston, MA, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeLung cancer is the leading cause of death globally. Geographic disparities in rates of lung cancer may be explained by the variation and intensity of risk factors within a given area. This study aims to advance the literature on how community-level contextual factors (i.e., environmental exposures, lung disease prevalence, and socioeconomic status) contribute to the development of lung cancer. If contextual risk factors for lung cancer can be identified, interventions can be implemented early to reduce geographic disparities of lung cancer.

methodsThis study utilizes town-level lung cancer prevalence data representing 100% of traditional Medicare beneficiaries in Connecticut, Massachusetts, New Hampshire, and Rhode Island to 1) analyze geospatial trends of lung cancer and 2) identify associated community-level risk factors. Following a series of spatial-based analyses (e.g., Moran's I, Getis-Ord Gi*), a series of spatial regression models estimated the association of selected risk factors with lung cancer prevalence. All analyses were conducted in STATA 18 and ArcMap 10.8.

resultsA total of n = 49 towns were identified as lung cancer hot spots at the 95th and 99th percentiles (p < 0.001). In regression modeling, historic releases of chromium from TRI facilities and ozone emissions, prevalence of asthma and chronic obstructive pulmonary disease (COPD), and median house values significantly predicted increased lung cancer prevalence in our sample.

conclusionThis study found that the prevalence of lung cancer across communities can be explained, in part, by levels of environmental emissions, selected health, demographics and socioeconomic indicators.

Indexed as

Environmental ExposureLung NeoplasmsAgedConnecticutFemaleHumansMaleMassachusettsNew HampshirePrevalenceResidence CharacteristicsRhode IslandRisk FactorsSocioeconomic Disparities in HealthSocioeconomic FactorsUnited StatesGeographic information systemsGeographic mappingLung neoplasmsPopulation healthPrevalenceRisk factorsSpatial analysis

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.