scholarly journals Complex mixtures of air pollutants: characterizing the cancer risk of polycyclic organic matter.

1993 ◽  
Vol 100 ◽  
pp. 211-218 ◽  
Author(s):  
J Lewtas
Keyword(s):  
Organic Matter ◽  
Cancer Risk ◽  
Air Pollutants ◽  
Complex Mixtures

scholarly journals Relationship between Air Pollutant Exposure and Gynecologic Cancer Risk

2021 ◽  
Vol 18 (10) ◽  
pp. 5353
Author(s):  
Qiwei Yu ◽  
Liqiang Zhang ◽  
Kun Hou ◽  
Jingwen Li ◽  
Suhong Liu ◽  
...  
Keyword(s):  
Air Pollution ◽  
Cancer Risk ◽  
Air Pollutants ◽  
Gynecological Cancer ◽  
Gynecologic Cancer ◽  
Ambient Air ◽  
Air Pollutant ◽  
Ambient Air Pollution ◽  
Short Term Exposure ◽  
Increased Risk

Exposure to air pollution has been suggested to be associated with an increased risk of women’s health disorders. However, it remains unknown to what extent changes in ambient air pollution affect gynecological cancer. In our case–control study, the logistic regression model was combined with the restricted cubic spline to examine the association of short-term exposure to air pollution with gynecological cancer events using the clinical data of 35,989 women in Beijing from December 2008 to December 2017. We assessed the women’s exposure to air pollutants using the monitor located nearest to each woman’s residence and working places, adjusting for age, occupation, ambient temperature, and ambient humidity. The adjusted odds ratios (ORs) were examined to evaluate gynecologic cancer risk in six time windows (Phase 1–Phase 6) of women’s exposure to air pollutants (PM2.5, CO, O3, and SO2) and the highest ORs were found in Phase 4 (240 days). Then, the higher adjusted ORs were found associated with the increased concentrations of each pollutant (PM2.5, CO, O3, and SO2) in Phase 4. For instance, the adjusted OR of gynecological cancer risk for a 1.0-mg m−3 increase in CO exposures was 1.010 (95% CI: 0.881–1.139) below 0.8 mg m−3, 1.032 (95% CI: 0.871–1.194) at 0.8–1.0 mg m−3, 1.059 (95% CI: 0.973–1.145) at 1.0–1.4 mg m−3, and 1.120 (95% CI: 0.993–1.246) above 1.4 mg m−3. The ORs calculated in different air pollution levels accessed us to identify the nonlinear association between women’s exposure to air pollutants (PM2.5, CO, O3, and SO2) and the gynecological cancer risk. This study supports that the gynecologic risks associated with air pollution should be considered in improved public health preventive measures and policymaking to minimize the dangerous effects of air pollution.

Estimating Cancer Risk from Outdoor Concentrations of Hazardous Air Pollutants in 1990

2000 ◽  
Vol 82 (3) ◽  
pp. 194-206 ◽  
Author(s):  
Tracey J. Woodruff ◽  
Jane Caldwell ◽  
Vincent J. Cogliano ◽  
Daniel A. Axelrad
Keyword(s):  
Cancer Risk ◽  
Air Pollutants ◽  
Hazardous Air Pollutants

Establishing a Measure of Reproducibility of Ultrahigh-Resolution Mass Spectra for Complex Mixtures of Natural Organic Matter

2012 ◽  
Vol 84 (21) ◽  
pp. 9184-9191 ◽  
Author(s):  
Rachel L. Sleighter ◽  
Hongmei Chen ◽  
Andrew S. Wozniak ◽  
Amanda S. Willoughby ◽  
Paolo Caricasole ◽  
...  
Keyword(s):  
Organic Matter ◽  
Natural Organic Matter ◽  
Mass Spectra ◽  
Complex Mixtures ◽  
Ultrahigh Resolution ◽  
Resolution Mass

Development of a Comparative Potency Method for Cancer Risk Assessment of Complex Mixtures Using Short-Term in Vivo and in Vitro Bioassays

1985 ◽  
Vol 1 (4) ◽  
pp. 193-203 ◽  
Author(s):  
Joellen Lewtas
Keyword(s):  
Risk Assessment ◽  
Cancer Risk ◽  
Data Base ◽  
Complex Mixtures ◽  
Cancer Risk Assessment ◽  
Human Lung Cancer ◽  
Short Term ◽  
Coke Ovens

A comparative potency method for cancer risk assessment has been developed based on a constant relative potency hypothesis. This method was developed and tested using data from a battery of short-term mutagenesis bioassays, animal tumorigenicity data and human lung cancer risk estimations. This data base was developed for a series of complex mixtures including emissions from coke ovens, roofing tar pots, cigarette smoke and automotive engines. The series of automobiles used in this study included both diesel- and gasoline-powered vehicles. The assumptions inherent in this method are discussed, together with the methods and data base used to test these assumptions.

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