Smaller particular matter, larger risk of female lung cancer incidence? Evidence from 436 Chinese counties

How long-term PM exposure may affect all-site cancer mortality: Evidence from a large cohort in southern China

BACKGROUND

Evidence of a potential causal link between long-term exposure to particulate matter (PM) and all-site cancer mortality from large population cohorts remained limited and suffered from residual confounding issues with traditional statistical methods.

AIMS

We aimed to examine the potential causal relationship between long-term PM exposure and all-site cancer mortality in South China using causal inference methods.

METHODS

We used a cohort in southern China that recruited 580,757 participants from 2009 through 2015 and tracked until 2020. Annual averages of PM1, PM2.5, and PM10 concentrations were generated with validated spatiotemporal models. We employed a causal inference approach, the Marginal Structural Cox model, based on observational data to evaluate the association between long-term exposure to PM and all-site cancer mortality.

RESULTS

With an increase of 1 µg/m³ in PM1, PM2.5, and PM10, the hazard ratios (HRs) and 95% confidence interval (CI) for all-site cancer were 1.033 (95% CI: 1.025-1.041), 1.032 (95% CI: 1.027-1.038), and 1.020 (95% CI: 1.016-1.025), respectively. The HRs (95% CI) for digestive system and respiratory system cancer mortality associated with each 1 µg/m³ increase in PM1 were 1.022 (1.009-1.035) and 1.053 (1.038-1.068), respectively. In addition, inactive participants, who never smoked, or who lived in areas of low surrounding greenness were more susceptible to the effects of PM exposure, the HRs (95% CI) for all-site cancer mortality were 1.042 (1.031-1.053), 1.041 (1.032-1.050), and 1.0473 (1.025-1.070) for every 1 µg/m³ increase in PM1, respectively. The effect of PM1 tended to be more pronounced in the low-exposure group than in the general population, and multiple sensitivity analyses confirmed the robustness of the results.

CONCLUSION

This study provided evidence that long-term exposure to PM may elevate the risk of all-site cancer mortality, emphasizing the potential health benefits of improving air quality for cancer prevention.

Using particle dimensionality-based modeling to estimate lung carcinogenicity of 3D printer emissions

The use of 3D printing technologies by industry and consumers is expanding. However, the approaches to assess the risk of lung carcinogenesis from the emissions of 3D printers have not yet been developed. The objective of the study was to demonstrate a methodology for modeling lung cancer risk related to specific exposure levels as derived from an experimental study of 3D printer emissions for various types of filaments (ABS, PLA, and PETG). The emissions of 15 filaments were assessed at varying extrusion temperatures for a total of 23 conditions in a Class 1,000 cleanroom following procedures described by ANSI/CAN/UL 2904. Three approaches were utilized for cancer risk estimation: (a) calculation based on PM2.5 and PM10 concentrations, (b) a proximity assessment based on the pulmonary deposition fraction, and (c) modeling based on the mass-weighted aerodynamic diameter of particles. The combined distribution of emitted particles had the mass median aerodynamic diameter (MMAD) of 0.35 μm, GSD 2.25. The average concentration of PM2.5 was 25.21 μg/m3 . The spline-based function of aerodynamic diameter allowed us to reconstruct the carcinogenic potential of seven types of fine and ultrafine particles (crystalline silica, fine TiO2 , ultrafine TiO2 , ambient PM2.5 and PM10, diesel particulates, and carbon nanotubes) with a correlation of 0.999, P < 0.00001. The central tendency estimation of lung cancer risk for 3D printer emissions was found at the level of 14.74 cases per 10,000 workers in a typical exposure scenario (average cumulative exposure of 0.3 mg/m3 - years), with the lowest risks for PLA filaments, and the highest for PETG type.

Long-term exposure to varying-sized particulate matters and kidney disease in middle-aged and elder adults: A 8-year nationwide cohort study in China

Evidence for the causal relationship of particulate matters (PMs) exposure with kidney disease, especially PM1, PM1-2.5 and PM2.5-10, remained scarce among developing countries with severe pollution. We conducted a longitudinal cohort study involving 13,041 adults with free kidney disease from 150 Chinese counties. PMs concentrations were generated using a well-established satellite-based spatiotemporal model. And the time-varying Cox regression model along with stratified analyses were performed to determine the association and potential modifiers, respectively. We also calculated the population-attributable fraction to evaluate the burden of kidney disease attributable to PMs pollution. Between Jan 2011 and Dec 2018, 985 kidney disease incidents were identified with an incidence rate of 12.69 per 1000 person-years. Significant dose-response relationships were observed for all 5 kinds PMs. Specifically, an increased risk of kidney disease was associated with per 10 μg/m3 increment of PM1 (HR = 1.187, 95%CI: 1.114 to 1.265), PM1-2.5 (1.326, 1.212 to 1.452), PM2.5 (1.197, 1.139 to 1.258), PM2.5-10 (1.297, 1.240 to 1.357), and PM10 (1.137, 1.108 to 1.166). A mixture analysis method of weighted quantile regression model revealed that PM2.5-10 predominated the PMs mixture index (57.1 %), and followed with PM10 (26.4 %). Stratified analyses indicated the elder, overweight persons, smokers, respiratory patients and urban residents were more vulnerable to PMs pollution than their counterparts. Calculated population attributable fractions of kidney disease attributable to PMs pollution was 16.67-39.47 %. Higher PMs pollution was associated with the increased risk of kidney disease development in China. Acceleration of efforts to reduce PMs pollution was therefore urgently needed to alleviate kidney disease burden.

Particulate matter and inflammatory skin diseases: From epidemiological and mechanistic studies

Epidemiological and toxicological studies have confirmed that exposure to atmospheric particulate matter (PM) could affect our cardiovascular and respiratory systems. Recent studies have shown that PM can penetrate the skin and cause skin inflammation, but the evidence is limited and contradictory. As the largest outermost surface of the human body, the skin is constantly exposed to the environment. The aim of this study was to assess the relationship between PM and inflammatory skin diseases. Most epidemiological studies have provided positive evidence for outdoor, indoor, and wildfire PM and inflammatory skin diseases. The effects of PM exposure during pregnancy and inflammatory skin diseases in offspring are heterogeneous. Skin barrier dysfunction, Oxidative stress, and inflammation may play a critical role in the underlying mechanisms. Finally, we summarize some interventions to alleviate PM-induced inflammatory skin diseases, which may contribute to public health welfare. Overall, PM is related to inflammatory skin diseases via skin barrier dysfunction, oxidative stress, and inflammation. Appropriate government interventions are beneficial.

Gaps and future directions in research on health effects of air pollution

Despite progress in many countries, air pollution, and especially fine particulate matter air pollution (PM2.5) remains a global health threat: over 6 million premature cardiovascular and respiratory deaths/yr. have been attributed to household and outdoor air pollution. In this viewpoint, we identify present gaps in air pollution monitoring and regulation, and how they could be strengthened in future mitigation policies to more optimally reduce health impacts. We conclude that there is a need to move beyond simply regulating PM2.5 particulate matter mass concentrations at central site stations. A greater emphasis is needed on: new portable and affordable technologies to measure personal exposures to particle mass; the consideration of a submicron (PM1) mass air quality standard; and further evaluations of effects by particle composition and source. We emphasize the need to enable further studies on exposure-health relationships in underserved populations that are disproportionately impacted by air pollution, but not sufficiently represented in current studies.

Long-term effect of submicronic particulate matter (PM1) and intermodal particulate matter (PM1-2.5) on incident dyslipidemia in China: A nationwide 5-year cohort study

BACKGROUND

There is insufficient evidence of associations between incident dyslipidemia with PM₁ (submicronic particulate matter) and PM_1-2.5 (intermodal particulate matter) in the middle-aged and elderly. We aimed to determine the long-term effects of PM₁ and PM_1-2.5 on incident dyslipidemia respectively.

METHODS

We studied 6976 individuals aged ≥45 from the China Health and Retirement Longitudinal Study from 2013 to 2018. The concentrations of particular matter (PM) for every individual's address were evaluated using a satellite-based spatiotemporal model. Dyslipidemia was evaluated by self-reported. The generalized linear mixed model was applied to quantify the correlations between PM and incident dyslipidemia.

RESULTS

After a 5-year follow-up, 333 (4.77%) participants developed dyslipidemia. Per 10 μg/m³ uptick in four-year average concentrations of PMs (PM₁ and PM_1-2.5) corresponded to 1.11 [95% confidence interval (CI): 1.01-1.23)] and 1.23 (95% CI: 1.06-1.43) fold risks of incident dyslipidemia. Nonlinear exposure-response curves were observed between PM and incident dyslipidemia. The effect size of PM₁ on incident dyslipidemia was slightly higher in males [1.14 (95% CI: 0.98-1.32) vs. 1.04 (95% CI: 0.89-1.21)], the elderly [1.23 (95% CI: 1.04-1.45) vs. 1.03 (95% CI: 0.91-1.17)], people with less than primary school education [1.12 (95% CI: 0.94-1.33) vs. 1.08 (95% CI: 0.94-1.23)], and solid cooking fuel users [1.17 (95% CI: 1.00-1.36) vs. 1.06 (95% CI: 0.93-1.21)], however, the difference was not statistically significant (Z = -0.82, P = 0.413; Z = -1.66, P = 0.097; Z = 0.32, P = 0.752; Z = -0.89, P = 0.372).

CONCLUSIONS

Long-term exposure to PM₁ and PM_1-2.5 were linked with an increased morbidity of dyslipidemia in the middle-aged and elderly population. Males, the elderly, and solid cooking fuel users had higher risk. Further studies would be warranted to establish an accurate reference value of PM to mitigate growing dyslipidemia.

Long-Term Exposure to Air Pollution Associates the Risk of Benign Brain Tumor: A Nationwide, Population-Based, Cohort Study in Taiwan

Air pollutants as risk factors for benign brain tumor (BBT) remain unclear. Therefore, we conducted a nationwide retrospective cohort study by integrating the patients’ clinical data and daily air quality data to assess the environmental risk factors of BBT in Taiwan.Daily air quality data were categorized into quartiles (Q1 to Q4). The adjusted hazard ratio (aHR) was evaluated by comparing the BBT incidence rate of the subjects in Q2–Q4 with that of the subjects in Q1 (the lowest concentration of air pollutants). A total of 161,213 subjects were enrolled in the study. Among the air pollutants tested, the aHR of BBT was significantly higher in the subjects who were exposed to the highest level (Q4) of CO (aHR 1.37, 95% CI 1.08–1.74), NO2 (aHR 1.40, 95% CI 1.09–1.78), and PM2.5 (aHR 1.30, 95% CI 1.02–1.65) than that in the subjects who were exposed to the lowest level (Q1). No significant risk association of BBT with SO2 and PM10 exposure was observed. The results revealed that long-term exposure to air pollutants, particularly CO, NO2, and PM2.5, is associated with the risk of BBT.