Evidence map›Paper›PMID 40333936›Full record

ArticleJournal of public health (Oxford, England)2025

Spatial analysis of colorectal cancer outcomes: investigating the impact of place-specific factors using causal inference methods for spatial data.

Dajana Draganic, Knut R Wangen

Abstract read
In one paragraph

Article in Journal of public health (Oxford, England), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors.

Dajana DraganicDepartment of Health Management and Health Economics, Institute of Health and Society, University of Oslo, Forskningsveien 3A, Oslo 0373, Norway.
Knut R WangenDepartment of Health Management and Health Economics, Institute of Health and Society, University of Oslo, Forskningsveien 3A, Oslo 0373, Norway.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundDisparities in health outcomes across regions may arise from place-specific factors, encompassing both contextual elements such as healthcare accessibility and compositional factors tied to the unique population characteristics. This study seeks to investigate the impact of various place-specific factors on late-stage incidence and mortality rates within Norwegian municipalities.

methodMunicipality-level data on colorectal cancer (CRC) late-stage diagnosis and mortality rates were acquired from the Cancer Registry of Norway and the Norwegian Cause of Death Registry. Screening utilization rates were obtained from the Norwegian Patient Registry. To explore the region-level effects of place-specific factors on CRC outcomes, a causal inference method for spatial data-neighborhood adjustment method via spatial smoothing (NA approach)-was employed.

resultsThe findings indicate that a one-unit increase in screening rates (or a 1% rise in screening uptake) corresponds to a 2.9% decrease in late-stage incidence, with a 95% credible interval ranging from -0.055 to -0.003. However, no significant relationship between screening rates and mortality rates was observed.

conclusionThis study underscores the importance of maximizing the utilization of screening services to prevent advance-stage diagnosis. Moreover, the research underscores the significance of improving access to screening services, particularly in rural and medically underserved areas.

Indexed as

Colorectal NeoplasmsResidence CharacteristicsSpatial AnalysisAgedEarly Detection of CancerFemaleHealth Services AccessibilityHumansIncidenceMaleMiddle AgedNorwayRegistriescausal methods for spatial datacolorectal cancerplace-specific factorsregional disparitiesscreening rates

Identifiers

PMID40333936
PMCPMC12395940

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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.