Evidence map›Paper›PMID 36395001›Full record

ArticlePreventing chronic disease2022

Creation and Evaluation of the Illinois Cancer Risk Index as a Predictor of Four Common Cancers.

Lei Guo, Margaret E Wright, Meredith C Osias, Mahdi Vaezi, M Courtney Hughes

Abstract read
In one paragraph

Article in Preventing chronic disease, 2022. 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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0citing papers in PubMed
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1 · What the graph read from it

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

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3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

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5 · Who and what money

Authors and funding

5 authors.

Lei GuoLei Guo, MA, MS, School of Interdisciplinary Health Professions, Northern Illinois University, Wirtz Hall 323, DeKalb, IL 60115. Email: rguo@niu.edu.
Margaret E WrightUniversity of Illinois Cancer Center, Chicago, Illinois.
Meredith C OsiasSchool of Health Studies, Northern Illinois University, DeKalb, Illinois.
Mahdi VaeziDepartment of Engineering Technology, Northern Illinois University, DeKalb, Illinois.
M Courtney HughesSchool of Health Studies, Northern Illinois University, DeKalb, Illinois.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionNearly half of all cancer deaths in the US are attributed to 4 common cancers: lung, colorectal, breast, and prostate. Illinois residents experience higher rates of cancer death from all 4 cancers compared with the US overall. We developed the Illinois Cancer Risk Index (ICRI), which incorporates many predictors of these cancers into a single summary measure, to identify Illinois counties that would benefit most from public health intervention.

methodsWe identified 90 county-level predictors of 4 common cancers, used multicollinearity testing to reduce this number to 61, and applied factor analysis to extract and analyze 4 factors representing 25 variables. Next, we created the ICRI by regressing the 4 factors on our outcome of interest - an age-adjusted common cancers mortality rate (CCMR), incorporating the direction of the β-coefficients from regression models to sum factor scores. Finally, we mapped and assessed the geographic distributions of both ICRI and CCMR by county across the state.

resultsThe ICRI was positively associated with the CCMR (r = 0.59, P < .001) and explained 32.2% of the variance in the CCMR across Illinois. The ICRI showed distinct geospatial patterns across the state, with the highest risk counties located in the east-central, far northern, and southern regions. The CCMR showed similar geospatial patterns.

conclusionOur study identifies counties in Illinois that may benefit most from interventions that target multiple cancer risk factors simultaneously. The ICRI may be adapted for use in other geographic locations where data are available.

Indexed as

NeoplasmsFactor Analysis, StatisticalHumansIllinoisMalePublic HealthRisk Factors

Identifiers

PMID36395001
PMCPMC9673961

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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.