Evidence map›Paper›PMID 31344779›Full record

ArticleInternational journal of environmental research and public health2019

Spatial Analysis of Industrial Benzene Emissions and Cancer Incidence Rates in Texas.

Chinmay Mungi, Dejian Lai, Xianglin L Du

Abstract read
In one paragraph

Article in International journal of environmental research and public health, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed, 2 pooled it
–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

5 citing papers in PubMed, 2 syntheses or guidelines pooled it.

  1. Impact of Pollution on Cancer: A Systematic Review and Meta-Analysis with Focus on Air Pollution.International journal of environmental research and public health · 2026
    Pooled it
  2. Pooled it
  3. Article
  4. Article
  5. Review
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

3 authors.

Chinmay MungiDepartment of Biostatistics and Data Science, The University of Texas Health Science Center at Houston School of Public Health, 1200 Pressler St., Room 1008, Houston, TX 77030, USA.
Dejian LaiDepartment of Biostatistics and Data Science, The University of Texas Health Science Center at Houston School of Public Health, 1200 Pressler St., Room 1008, Houston, TX 77030, USA. Dejian.lai@uth.tmc.edu.
Xianglin L DuDepartment of Epidemiology, Human Genetics and Environmental Sciences, The University of Texas Health Science Center at Houston, 1200 Pressler St., Room 1008, Houston, TX 77030, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This paper presents a spatial analysis of the association between industrial benzene emissions and the 10-year incidence rates of cancers likely to be associated with benzene exposure (Lymphohematopoietic, lung and lip cancers) at the county level in Texas. The spatial distribution of incident cases of the above cancers between 2004 and 2013 was assessed at the county level and found to have positive spatial auto-correlation. Subsequently, point pattern analysis was performed on industrial emissions of benzene reported to the Toxic Release Inventory (TRI), revealing a non-random spatial pattern. Universal kriging was performed using the industrial emissions data to derive estimates of ambient benzene levels at the county level. An ordinary linear regression model was fitted using the incidence rates as the outcome and the estimated benzene level along with chosen covariates and the residuals were assessed for lingering spatial auto-correlation. As the residuals showed that spatial auto-correlation persists, a spatial conditional auto-regression (CAR) model was fitted instead. In the spatial CAR linear regression model, estimated levels of ambient benzene were not found to be significantly associated with the 10-year incidence rates of lymphohematopoietic, lung and lip cancers at the county level.

Indexed as

Air PollutantsBenzeneHumansIncidenceIndustryLinear ModelsNeoplasmsSpatial AnalysisTexasAir PollutantsBenzenebenzene emissioncancer incidencekrigingSpatial Linear ModelsSpatial Pattern Analysis

Identifiers

PMID31344779
PMCPMC6696035

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Registered trials

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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.