2017
DOI: 10.1186/s12940-017-0309-2
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Lung cancer mortality of residents living near petrochemical industrial complexes: a meta-analysis

Abstract: Background: Lung cancer, as the leading cause of cancer mortality worldwide, has been linked to environmental factors, such as air pollution. Residential exposure to petrochemicals is considered a possible cause of lung cancer for the nearby population, but results are inconsistent across previous studies. Therefore, we performed a metaanalysis to estimate the pooled risk and to identify possible factors leading to the heterogeneity among studies. Methods: The standard process of selecting studies followed the… Show more

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Cited by 38 publications
(21 citation statements)
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“…8 Further to that, cancer has been associated with living near oil refinery but the results are not consistent. [11][12][13] There is limited data from the Middle East on health impact of living near an oil refinery.…”
Section: Introductionmentioning
confidence: 99%
“…8 Further to that, cancer has been associated with living near oil refinery but the results are not consistent. [11][12][13] There is limited data from the Middle East on health impact of living near an oil refinery.…”
Section: Introductionmentioning
confidence: 99%
“…Still, the debate remains largely disjointed with few studies using a consistent approach to measure petrochemical exposure, or to control for lifestyle and socioeconomic influences. Lin et al's (2017) meta-analysis provides the first attempt to pool some of this knowledge base, identifying no significant increase in the rate of lung cancer mortalities along fence-line communities. A revised meta-analysis found that individuals living near petrochemical facilities have a 19% higher risk of developing lung cancer (Lin et al, 2018).…”
Section: Introductionmentioning
confidence: 99%
“…However, note that plants with missing control data amount to less than 1% of the total global coal capacity, so different assumptions about these missing data are not expected to have a meaningful impact on the analysis. (4) The study did not adjust for meteorological, geographical and/or other covariates 26 . If we assume the lack of considering meteorological effect misclassified our exposure, we might underestimate the true effect as well.…”
Section: Discussionmentioning
confidence: 99%