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Record W2087621972 · doi:10.1289/ehp.1408882

Lung Cancer and Exposure to Nitrogen Dioxide and Traffic: A Systematic Review and Meta-Analysis

2015· review· en· W2087621972 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueEnvironmental Health Perspectives · 2015
Typereview
Languageen
FieldEnvironmental Science
TopicAir Quality and Health Impacts
Canadian institutionsUniversity of British Columbia
FundersWorld Health Organization
KeywordsLung cancerNitrogen dioxideMeta-analysisMedicineEnvironmental healthConfoundingPublication biasToxicologyOncologyInternal medicineChemistryBiology

Abstract

fetched live from OpenAlex

BACKGROUND AND OBJECTIVE: Exposure to traffic-related air pollutants is an important public health issue. Here, we present a systematic review and meta-analysis of research examining the relationship of measures of nitrogen oxides (NOx) and of various measures of traffic-related air pollution exposure with lung cancer. METHODS: We conducted random-effects meta-analyses of studies examining exposure to nitrogen dioxide (NO2) and NOx and its association with lung cancer. We identified 20 studies that met inclusion criteria and provided information necessary to estimate the change in lung cancer per 10-μg/m3 increase in exposure to measured NO2. Further, we qualitatively assessed the evidence of association between distance to roadways and traffic volume associated with lung cancer. RESULTS: The meta-estimate for the change in lung cancer associated with a 10-μg/m3 increase in exposure to NO2 was 4% (95% CI: 1%, 8%). The meta-estimate for change in lung cancer associated with a 10-μg/m3 increase in NOx was similar and slightly more precise, 3% (95% CI: 1%, 5%). The NO2 meta-estimate was robust to different confounding adjustment sets as well as the exposure assessment techniques used. Trim-and-fill analyses suggest that if publication bias exists, the overall meta-estimate is biased away from the null. Forest plots for measures of traffic volume and distance to roadways largely suggest a modest increase in lung cancer risk. CONCLUSION: We found consistent evidence of a relationship between NO2, as a proxy for traffic-sourced air pollution exposure, with lung cancer. Studies of lung cancer related to residential proximity to roadways and NOx also suggest increased risk, which may be attributable partly to air pollution exposure. The International Agency for Research on Cancer recently classified outdoor air pollution and particulate matter as carcinogenic (Group 1). These meta-analyses support this conclusion, drawing particular attention to traffic-sourced air pollution. CITATION: Hamra GB, Laden F, Cohen AJ, Raaschou-Nielsen O, Brauer M, Loomis D. 2015. Lung cancer and exposure to nitrogen dioxide and traffic: a systematic review and meta-analysis. Environ Health Perspect 123:1107-1112; http://dx.doi.org/10.1289/ehp.1408882.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.918
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0060.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.096
GPT teacher head0.409
Teacher spread0.313 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it