Spatial Analysis of Ambient PM2.5 Exposure and Bladder Cancer Mortality in Taiwan

Ambient air pollution and urological cancer risk: A systematic review and meta-analysis of epidemiological evidence

Exposure to ambient air pollution has significant adverse health effects; however, whether air pollution is associated with urological cancer is largely unknown. We conduct a systematic review and meta-analysis with epidemiological studies, showing that a 5 μg/m3 increase in PM2.5 exposure is associated with a 6%, 7%, and 9%, increased risk of overall urological, bladder, and kidney cancer, respectively; and a 10 μg/m3 increase in NO2 is linked to a 3%, 4%, and 4% higher risk of overall urological, bladder, and prostate cancer, respectively. Were these associations to reflect causal relationships, lowering PM2.5 levels to 5.8 μg/m3 could reduce the age-standardized rate of urological cancer by 1.5 ~ 27/100,000 across the 15 countries with the highest PM2.5 level from the top 30 countries with the highest urological cancer burden. Implementing global health policies that can improve air quality could potentially reduce the risk of urologic cancer and alleviate its burden.

Traffic-Related Air Pollution and Risk of Lung, Breast, and Urinary Tract Cancer in Halifax, Nova Scotia

OBJECTIVES

We assessed the association of traffic-related air pollution (TRAP) with the incidence of lung, breast, and urinary tract cancer in Halifax, Nova Scotia.

METHODS

Our case-control study included 2315 cancers and 8501 age-sex-matched controls. Land-use regression was used to estimate TRAP concentrations. Logistic regression was used to assess cancer risk in relation to TRAP, adjusting for community social and material deprivation.

RESULTS

There was no association between the risk of lung, breast, or urinary tract cancer in relation to TRAP. Lung cancer risk was significantly increased in the most deprived communities, whereas breast cancer risk was highest in the least deprived communities.

CONCLUSIONS

In a city characterized by low levels of ambient air pollution, there was no evidence of a linear increased lung, breast, or urinary tract cancer risk in relation to TRAP.

Impacts of Mir146a Genotypes on Bladder Cancer Risk in Taiwan

The aim of this study was to investigate the association between single-nucleotide polymorphisms (SNPs) in mir146a and mir196a and bladder cancer (BLCA) risk in Taiwan. The genotypes of mir146a rs2910164 and mir196a rs11614913 were determined in 375 BLCA patients and 375 healthy controls using PCR-RFLP methodology, and their associations with BLCA risk were evaluated. The study also measured the serum expression level of mir146a using quantitative RT-PCR. The results showed that the distributions of CC, CG and GG genotypes of mir146a rs2910164 were 31.7%, 45.6% and 22.7% in the control group, and 21.9%, 44.3% and 33.8% in the case group, respectively. In logistic regression analyses, the heterozygous variant genotype CG carriers showed a marginally significant association with increased BLCA risk (OR = 1.41, 95% CI = 0.99-2.01), while the homozygous variant genotype GG carriers had a 2.17-fold increased risk of BLCA (OR = 2.17, 95%CI = 1.46-3.21). Moreover, carriers of the GG/CG genotypes had significantly higher serum levels of mir146a than those with the CC genotype (p < 0.0001), indicating a genotype-phenotype correlation. In contrast, mir196a rs11614913 was not associated with BLCA risk. Therefore, the genotypes of mir146a rs2910164 may serve as a useful biomarker for predicting the risk of BLCA.

Long-term exposure to fine particulate matter and site-specific cancer mortality: A difference-in-differences analysis in Jiangsu province, China

BACKGROUND

Accumulating studies have reported that chronic exposure to ambient fine particulate matter (PM_2.5) can lead to adverse effects on lung cancer mortality; however, such chronic effects are less clear for mortality from other site-specific cancers.

OBJECTIVE

To explore the causal effect of long-term PM_2.5 exposure on mortality from all-site and a variety of site-specific cancers in Jiangsu province, China during 2015-2020 using a difference-in-differences analysis.

METHODS

For each of 53 county-based spatial units in Jiangsu province, we calculated annual death counts for all-site cancer and 23 site-specific cancers. Using a validated high-resolution PM_2.5 grid dataset, long-term PM_2.5 exposure of a spatial unit within a given year was evaluated as the average of population-weighted annual concentrations during recent 10 years. Conditional Poisson regression models were employed to evaluate exposure-response associations adjusting for spatial and temporal variables, seasonal temperatures, relative humidity, and gross domestic product (GDP).

RESULTS

During the study period, we identified 947,337 adult cancer deaths in Jiangsu province. Each 1 μg/m³ increment in PM_2.5 exposure was significantly associated with a 2.7% increase in the risk of all-site cancer mortality. PM_2.5-mortality associations were also observed in cancer of lip, oral cavity and pharynx, stomach, colorectum, pancreas, lung, bone and joints, ovary, prostate, and lymphoma (all adjusted P < 0.05), with the relative risks ranging from 1.028 (95% confidence interval [CI]: 1.011, 1.046) for stomach cancer to 1.201 (95% CI: 1.120, 1.308) for bone and joints cancers. Exposure-response curves showed that these associations were close to linearity, though most of them had increasing slopes at high exposure levels. Overall, women and subjects in low GDP regions were more vulnerable to PM_2.5 exposures.

CONCLUSIONS

Long-term exposure to ambient PM_2.5 contributes to a higher risk of mortality from multiple site-specific cancers.

The impact of social and environmental factors on cancer biology in Black Americans

Low socioeconomic status (SES) is associated with early onset of chronic diseases and reduced life expectancy. The involvement of neighborhood-level factors in defining cancer risk and outcomes for marginalized communities has been an active area of research for decades. Yet, the biological processes that underlie the impact of SES on chronic health conditions, such as cancer, remain poorly understood. To date, limited studies have shown that chronic life stress is more prevalent in low SES communities and can affect important molecular processes implicated in tumor biology such as DNA methylation, inflammation, and immune response. Further efforts to elucidate how neighborhood-level factors function physiologically to worsen cancer outcomes for disadvantaged communities are underway. This review provides an overview of the current literature on how socioenvironmental factors within neighborhoods contribute to more aggressive tumor biology, specifically in Black U.S. women and men, including the impact of environmental pollutants, neighborhood deprivation, social isolation, structural racism, and discrimination. We also summarize commonly used methods to measure deprivation, discrimination, and structural racism at the neighborhood-level in cancer health disparities research. Finally, we offer recommendations to adopt a multi-faceted intersectional approach to reduce cancer health disparities and develop effective interventions to promote health equity.

Ambient Fine Particulate Matter and Cancer: Current Evidence and Future Perspectives

The high incidence of cancer has placed an enormous health and economic burden on countries around the world. In addition to evidence of epidemiological studies, conclusive evidence from animal experiments and mechanistic studies have also shown that morbidity and mortality of some cancers can be attributed to ambient fine particulate matter (PM_2.5) exposure, especially in lung cancer. However, the underlying carcinogenetic mechanisms of PM_2.5 remain unclear. Furthermore, in terms of risks of other types of cancer, both epidemiological and mechanistic evidence are more limited and scattered, and the results are also inconsistent. In order to sort out the carcinogenic effect of PM_2.5, this paper reviews the association of cancers with PM_2.5 based on epidemiological and biological evidence including genetic, epigenetic, and molecular mechanisms. The limitations of existing researches and the prospects for the future are also well clarified in this paper to provide insights for future studies.

The spatial association between environmental pollution and long-term cancer mortality in Italy

Tumours are nowadays the second world‑leading cause of death after cardiovascular diseases. During the last decades of cancer research, lifestyle and random/genetic factors have been blamed for cancer mortality, with obesity, sedentary habits, alcoholism, and smoking contributing as supposed major causes. However, there is an emerging consensus that environmental pollution should be considered one of the main triggers. Unfortunately, all this preliminary scientific evidence has not always been followed by governments and institutions, which still fail to pursue research on cancer's environmental connections. In this unprecedented national-scale detailed study, we analyzed the links between cancer mortality, socio-economic factors, and sources of environmental pollution in Italy, both at wider regional and finer provincial scales, with an artificial intelligence approach. Overall, we found that cancer mortality does not have a random or spatial distribution and exceeds the national average mainly when environmental pollution is also higher, despite healthier lifestyle habits. Our machine learning analysis of 35 environmental sources of pollution showed that air quality ranks first for importance concerning the average cancer mortality rate, followed by sites to be reclaimed, urban areas, and motor vehicle density. Moreover, other environmental sources of pollution proved to be relevant for the mortality of some specific cancer types. Given these alarming results, we call for a rearrangement of the priority of cancer research and care that sees the reduction and prevention of environmental contamination as a priority action to put in place in the tough struggle against cancer.

Long-term ambient hydrocarbon exposure and incidence of urinary bladder cancer

Particulate matter and volatile organic compounds, including total hydrocarbons (THCs), are major ambient air pollutants. Primary nonmethane hydrocarbons (NMHCs) originate from vehicle emissions. The association between air pollution and urinary bladder cancer (UBC) is debatable. We investigated whether long-term exposure to ambient hydrocarbons increases UBC risk among people aged ≥ 20 years in Taiwan. Linkage dataset research with longitudinal design was conducted among 589,135 initially cancer-free individuals during 2000-2013; 12 airborne pollutants were identified. Several Cox models considering potential confounders were employed. The study outcomes were invasive or in situ UBC incidence over time. The targeted pollutant concentration was divided into three tertiles: T1/T2/T3. The mean age of individuals at risk was 42.5 (SD 15.7), and 50.5% of the individuals were men. The mean daily average over 10 years of airborne THC concentration was 2.25 ppm (SD 0.13), and NMHC was 0.29 ppm (SD 0.09). Both pollutants show long-term monotonic downward trend over time using the Mann-Kendall test. There was a dose-dependent increase in UBC at follow-up. UBC incidence per 100,000 enrollees according to T1/T2/T3 exposure to THC was 60.9, 221.2, and 651.8, respectively; it was 170.0/349.5/426.7 per 100,000 enrollees, corresponding to T1/T2/T3 exposure to NMHC, respectively. Without controlling for confounding air pollutants, the adjusted hazard ratio (adj.HR) was 1.83 (95% CI 1.75-1.91) per 0.13-ppm increase in THC; after controlling for PM_2.5, adj.HR was even higher at 2.09 (95% CI 1.99-2.19). The adj.HR was 1.37 (95% CI 1.32-1.43) per 0.09-ppm increase in ambient NMHC concentration. After controlling for SO₂ and CH₄, the adj.HR was 1.10 (95% CI 1.06-1.15). Sensitivity analyses showed that UBC development risk was not sex-specific or influenced by diabetes status. Long-term exposure to THC and NMHC may be a risk factor for UBC development. Acknowledging pollutant sources can inform risk management strategies.

PM2.5 exposure and cervical cancer survival in Liaoning Province, northeastern China

Particulate matter with a diameter of 2.5 μm or less (PM_2.5) has frequently been reported to be associated with an increased incidence of cancer, but few studies have explored the association between PM_2.5 exposure and cancer survival. We retrospectively analyzed the association between PM_2.5 exposure and the overall survival (OS) of cervical cancer patients residing in 14 urban areas of Liaoning Province, northeastern China, during January 2014-October 2021. Patients from urban areas who completed the recommended treatments with complete follow-up information were included. The PM_2.5 monitoring data of each urban area of Liaoning Province were retrieved, and individual exposure to PM_2.5 after diagnosis was calculated as the average daily concentration in the city of residence from the date of discharge to the date of death or the last follow-up. Log-rank tests and Cox regression were performed to examine the relationship between PM_2.5 exposure and cervical cancer survival. A total of 1753 cervical cancer patients were finally included, among whom 804 (45.9%) were from Shenyang City, the capital of Liaoning Province. The median average daily concentration of PM_2.5 to which the patients were exposed was 45.0 (interquartile range 38.2-50.0) μg/m³. Both log-rank tests (grouped by quartiles, p < 0.001) and Cox regression (continuous, HR = 1.06, 95% CI 1.04-1.08) indicated that PM_2.5 was significantly associated with shorter OS. Sensitivity analysis also confirmed the robustness of our findings. From the subgroup analysis, only the OS of stage II and stage III patients was associated with PM exposure. Our findings provide the insight that PM_2.5 exposure might be associated with shorter OS of cervical cancer patients.

The impact of size-segregated particle properties on daily mortality in Seoul, Korea

To investigate the causative component for certain health outcomes, the associations between the properties of ambient particles and cause-specific mortality (all-cause, cardiovascular, and respiratory-related mortality) measured in Seoul, Korea, from January 1, 2013, to December 31, 2016, were evaluated with a quasi-Poisson generalized additive model (GAM). The total mass of PM₁₀ and PM_2.5 moderately affected respiratory-related mortality but had almost no impact on all-cause and cardiovascular-related mortality. Among PM_2.5 mass compositions, ammonium sulfate, which is in generally 300-500 nm as a secondary species, showed the most statistically significant effect on respiratory-related mortality at lag 4 (p < 0.1) but not for other mortalities. However, from the size-selective investigations, cardiovascular-related mortality was impacted by particle number concentrations (PNCs), particle surface concentrations (PSCs), and particle volume concentrations (PVCs) in the size range from 50 to 200 nm with a statistically significant association, particularly at lag 1, suggesting that mass is not the only way to examine mortality, which is likely because mass and chemical composition concentrations are generally controlled by larger-sized particles. Our study suggests that the size-specific mortality and/or impacts of size-resolved properties on mortalities need to be evaluated since smaller particles get into the body more efficiently, and therefore, more diverse size-dependent causes and effects can occur.

Modeling the Determinants of PM2.5 in China Considering the Localized Spatiotemporal Effects: A Multiscale Geographically Weighted Regression Method

Many studies have identified the influences of PM2.5. However, very little research has addressed the spatiotemporal dependence and heterogeneity in the relationships between impact factors and PM2.5. This study firstly utilizes spatial statistics and time series analysis to investigate the spatial and temporal dependence of PM2.5 at the city level in China using a three-year (2015–2017) dataset. Then, a new local regression model, multiscale geographically weighted regression (MGWR), is introduced, based on which we measure the influence of PM2.5. A spatiotemporal lag is constructed and included in MGWR to account for spatiotemporal dependence and spatial heterogeneity simultaneously. Results of MGWR are comprehensively compared with those of ordinary least square (OLS) and geographically weighted regression (GWR). Experimental results show that PM2.5 is autocorrelated in both space and time. Compared with existing approaches, MGWR with a spatiotemporal lag (MGWRL) achieves a higher goodness-of-fit and a more significant effect on eliminating residual spatial autocorrelation. Parameter estimates from MGWR demonstrate significant spatial heterogeneity, which traditional global models fail to detect. Results also indicate the use of MGWR for generating local spatiotemporal dependence evaluations which are conditioned on various covariates rather than being simple descriptions of a pattern. This study offers a more accurate method to model geographic events.

The impacts of long-term exposure to PM2.5 on cancer hospitalizations in Brazil

BACKGROUND

Long-term exposure to PM_2.5 has been linked to cancer incidence and mortality. However, it was unknown whether there was an association with cancer hospitalizations.

METHODS

Data on cancer hospitalizations and annual PM_2.5 concentrations were collected from 1,814 Brazilian cities during 2002-2015. A difference-in-difference approach with quasi-Poisson regression was applied to examine State-specific associations. The State-specific associations were pooled at a national level using random-effect meta-analyses. PM_2.5 attributable burden were estimated for cancer hospitalization admissions, inpatient days and costs.

RESULTS

We included 5,102,358 cancer hospitalizations (53.8% female). The mean annual concentration of PM_2.5 was 7.0 μg/m³ (standard deviation: 4.0 μg/m³). With each 1 μg/m³ increase in two-year-average (current year and previous one year) concentrations of PM_2.5, the relative risks (RR) of hospitalization were 1.04 (95% confidence interval [CI]: 1.02 to 1.07) for all-site cancers from 2002 to 2015 without sex and age differences. We estimated that 33.82% (95%CI: 14.97% to 47.84%) of total cancer hospitalizations could be attributed to PM_2.5 exposure in Brazil during the study time. For every 100,000 population, 1,190 (95%CI: 527 to 1,836) cancer hospitalizations, 8,191 (95%CI: 3,627 to 11,587) inpatient days and US$788,775 (95%CI: $349,272 to $1,115,825) cost were attributable to PM_2.5 exposure.

CONCLUSIONS

Long-term exposure to ambient PM_2.5 was positively associated with hospitalization for many cancer types in Brazil. Inpatient days and cost would be saved if the annual PM_2.5 exposure was reduced.

Cohort studies of long-term exposure to outdoor particulate matter and risks of cancer: A systematic review and meta-analysis

Robust evidence is needed for the hazardous effects of outdoor particulate matter (PM) on mortality and morbidity from all types of cancers. To summarize and meta-analyze the association between PM and cancer, published articles reporting associations between outdoor PM exposure and any type of cancer with individual outcome assessment that provided a risk estimate in cohort studies were identified via systematic searches. Of 3,256 records, 47 studies covering 13 cancer sites (30 for lung cancer, 12 for breast cancer, 11 for other cancers) were included in the quantitative evaluation. The pooled relative risks (RRs) for lung cancer incidence or mortality associated with every 10-μg/m³ PM_2.5 or PM₁₀ were 1.16 (95% confidence interval [CI], 1.10–1.23; I² = 81%) or 1.22 (95% CI, 1.02–1.45; I² = 96%), respectively. Increased but non-significant risks were found for breast cancer. Other cancers were shown to be associated with PM exposure in some studies but not consistently and thus warrant further investigation.

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Updated evidence for the association between PM and lung cancer risk has been provided

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Associations between PM and cancer risks from 13 sites were summarized

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Further studies should be conducted to fill the research gaps

Why We Will Continue to Lose Our Battle with Cancers If We Do Not Stop Their Triggers from Environmental Pollution

Besides our current health concerns due to COVID-19, cancer is a longer-lasting and even more dramatic pandemic that affects almost a third of the human population worldwide. Most of the emphasis on its causes has been posed on genetic predisposition, chance, and wrong lifestyles (mainly, obesity and smoking). Moreover, our medical weapons against cancers have not improved too much during the last century, although research is in progress. Once diagnosed with a malignant tumour, we still rely on surgery, radiotherapy, and chemotherapy. The main problem is that we have focused on fighting a difficult battle instead of preventing it by controlling its triggers. Quite the opposite, our knowledge of the links between environmental pollution and cancer has surged from the 1980s. Carcinogens in water, air, and soil have continued to accumulate disproportionally and grow in number and dose, bringing us to today's carnage. Here, a synthesis and critical review of the state of the knowledge of the links between cancer and environmental pollution in the three environmental compartments is provided, research gaps are briefly discussed, and some future directions are indicated. New evidence suggests that it is relevant to take into account not only the dose but also the time when we are exposed to carcinogens. The review ends by stressing that more dedication should be put into studying the environmental causes of cancers to prevent and avoid curing them, that the precautionary approach towards environmental pollutants must be much more reactionary, and that there is an urgent need to leave behind the outdated petrochemical-based industry and goods production.

Social Determinants of Diabetes-Related Preventable Hospitalization in Taiwan: A Spatial Analysis

Diabetes-Related Preventable Hospitalization (DRPH) has been identified as an important indicator of efficiency and quality of the health system and can be modified by social determinants. However, the spatial disparities, clustering, and relationships between DRPH and social determinants have rarely been investigated. Accordingly, this study examined the association of DRPH with area deprivation, densities of certificated diabetes health-promoting clinics (DHPC) and hospitals (DHPH), and the presence of elderly social services (ESS) using both statistical and spatial analyses. Data were obtained from the 2010-2016 National Health Insurance Research Database (NHIRD) and government open data. Township-level ordinary least squares (OSL) and geographically weighted regression (GWR) were conducted. DRPH rates were found to be negatively associated with densities of DHPC (β = -66.36, p = 0.029; 40.3% of all townships) and ESS (β = -1.85, p = 0.027; 28.4% of all townships) but positively associated with area deprivation (β = 2.96, p = 0.002; 25.6% of all townships) in both OLS and GWR models. Significant relationships were found in varying areas in the GWR model. DRPH rates are high in townships of Taiwan that have lower DHPC densities, lower ESS densities, and greater socioeconomic deprivation. Spatial analysis could identify areas of concern for potential intervention.

Air pollution exposure and bladder, kidney and urinary tract cancer risk: A systematic review

BACKGROUND

Exposure to outdoor air pollution has been linked to lung cancer, and suspicion arose regarding bladder, kidney, and urinary tract cancer (urological cancers). However, most of evidence comes from occupational studies; therefore, little is known about the effect of exposure to air pollution on the risk of urological cancers in the general population.

METHOD

We systematically searched Medline, Scopus, and Web of Science for articles investigating the associations between long-term exposure to air pollution and the risk of urological cancer (incidence or mortality). We included articles using a specific air pollutant (PM₁₀, PM_2.5, …) or proxies (traffic, proximity index …). We assessed each study's quality with the Newcastle-Ottawa scale and rated the quality of the body of evidence for each pollutant-outcome with the GRADE approach. The different study methodologies regarding exposure or outcome prevented us to perform a meta-analysis.

RESULTS

twenty articles (four case-control, nine cohort, and seven ecologic) met our inclusion criteria and were included in this review: eighteen reported bladder, six kidney, and two urinary tract. Modeling air pollutants was the most common exposure assessment method. Most of the included studies reported positive associations between air pollution and urological cancer risk. However, only a few reached statistical significance (e.g. for bladder cancer mortality, adjusted odds-ratio of 1.13 (1.03-1.23) for an increase of 4.4 μg.m-3 of PM_2.5). Most studies inadequately addressed confounding, and cohort studies had an insufficient follow-up.

DISCUSSION

Overall, studies suggested positive (even though mostly non-significant) associations between air pollution exposure and bladder cancer mortality and kidney cancer incidence. We need more studies with better confounding control and longer follow-ups.

County-level variation in the long-term association between PM2.5 and lung cancer mortality in China

INTRODUCTION

The relative risk (RR) of long-term exposure to PM_2.5 in lung cancer mortality (LCM) may vary spatially in China. However, previous studies applying global regression have been unable to capture such variation. We aimed to employ a geographically weighted Poisson regression (GWPR) to estimate the RRs of LCM among the elderly (≥65 years) related to long-term exposure to PM_2.5 and the LCM attributable to PM_2.5 at the county level in China.

METHODS

We obtained annual LCM in the elderly between 2013 and 2015 from the National Death Surveillance. We linked annual mean concentrations of PM_2.5 between 2000 and 2004 with LCM using GWPR model at 148 counties across mainland China, adjusting for smoking and socioeconomic covariates. We used county-specific GWPR models to estimate annual average LCM in the elderly between 2013 and 2015 attributable to PM_2.5 exposure between 2000 and 2004.

RESULTS

The magnitude of the association between long-term exposure to PM_2.5 and LCM varied with county. The median of county-specific RRs of LCM among elderly men and women was 1.52 (range: 0.90, 2.40) and 1.49 (range: 0.88, 2.56) for each 10 μg/m³ increment in PM_2.5, respectively. The RRs were positively significant (P < 0.05) at 95% (140/148) of counties among both elderly men and women. Higher RRs of PM_2.5 among elderly men were located at Southwest and South China, and higher RRs among elderly women were located at Northwest, Southwest, and South China. There were 99,967 and 54,457 lung cancer deaths among elderly men and women that could be attributed to PM_2.5, with the attributable fractions of 31.4% and 33.8%, respectively.

CONCLUSIONS

The relative importance of long-term exposure to PM_2.5 in LCM differed by county. The results could help the government design tailored and efficient interventions. More stringent PM_2.5 control is urgently needed to reduce LCM in China.

Cancer mortality risk, fine particulate air pollution, and smoking in a large, representative cohort of US adults

PURPOSE

Air pollution and smoking are associated with various types of mortality, including cancer. The current study utilizes a publicly accessible, nationally representative cohort to explore relationships between fine particulate matter (PM2.5) exposure, smoking, and cancer mortality.

METHODS

National Health Interview Survey and mortality follow-up data were combined to create a study population of 635,539 individuals surveyed from 1987 to 2014. A sub-cohort of 341,665 never-smokers from the full cohort was also created. Individuals were assigned modeled PM2.5 exposure based on average exposure from 1999 to 2015 at residential census tract. Cox Proportional Hazard models were utilized to estimate hazard ratios for cancer-specific mortality controlling for age, sex, race, smoking status, body mass, income, education, marital status, rural versus urban, region, and survey year.

RESULTS

The risk of all cancer mortality was adversely associated with PM2.5 (per 10 µg/m3 increase) in the full cohort (hazard ratio [HR] 1.15, 95% confidence interval [CI] 1.08-1.22) and the never-smokers' cohort (HR 1.19, 95% CI 1.06-1.33). PM2.5-morality associations were observed specifically for lung, stomach, colorectal, liver, breast, cervix, and bladder, as well as Hodgkin lymphoma, non-Hodgkin lymphoma, and leukemia. The PM2.5-morality association with lung cancer in never-smokers was statistically significant adjusting for multiple comparisons. Cigarette smoking was statistically associated with mortality for many cancer types.

CONCLUSIONS

Exposure to PM2.5 air pollution contributes to lung cancer mortality and may be a risk factor for other cancer types. Cigarette smoking has a larger impact on cancer mortality than PM2.5 , but is associated with similar cancer types.

Relationship between atmospheric pollutants and risk of death caused by cardiovascular and respiratory diseases and malignant tumors in Shenyang, China, from 2013 to 2016: an ecological research

Background:

Air pollutants and their pathogenic effects differ among regions and seasons. We aimed to explore the relationship between fine particulate matter (PM_2.5), sulfur dioxide (SO₂), and ozone-8 hours (O₃-8h) concentrations in heating and non-heating seasons and the associated death risk due to cardiovascular diseases (CDs), respiratory diseases (RDs), and malignant tumors.

Methods:

Data were collected in Shenyang, China, from April 2013 to March 2016. We analyzed the correlation or lagged effect of atmospheric pollutant concentration, meteorological conditions, and death risk due to disorders of the circulatory system, respiratory system, and malignant tumor in heating and non-heating seasons. We also used multivariate models to analyze the association of air pollutants during holidays with the death risk due to the evaluated diseases while considering the presence or absence of meteorological factors.

Results:

An increase in the daily average SO₂ concentration by 10 μg/m³ increased the death risk by CDs, which reached a maximum of 2.0% (95% confidence interval [CI]: 1.3%–2.7%) on lagging day 4 during the non-heating season and 0.2% (95% CI: 0.1%–0.4%) on lagging day 3 during the heating season. The risk of death caused by RDs peaked on lagging day 1 by 0.8% (95% CI: 0.4%–1.2%) during the heating season. An increase in O₃-8h concentration by 10 μg/m³ increased the risk of RD-related death on lagging day 2 by 1.0% (95% CI: 0.4%–1.7%) during the non-heating season, which was significantly higher than the 0.1% (95% CI: 0–0.9%) increase during the heating season. Further, an increase in the daily average PM_2.5 concentration by 10 μg/m³ increased the risk of death caused by RDs by 0.3% and 0.8% during heating and non-heating seasons, respectively, which peaked on lagging day 0. However, air pollution was not significantly associated with the risk of death caused by malignant tumors.

Conclusion:

Short-term exposure to PM_2.5, SO₂, and O₃ during the non-heating season resulted in higher risks of CD-related death, followed by RD-related death.

The interaction of gender and smoking on bladder cancer risks

PURPOSE OF REVIEW

Although smoking and gender are well-established bladder cancer (BCa) risk factors, a significant interaction with other risk factors could help in the identification of patterns for early detection and prevention strategies.

RECENT FINDINGS

Smoking appears to be more strongly associated with BCa risk in women than in men, which could be related to differences in metabolism, smoking behavior, exposure patterns, and DNA repair mechanisms. BMI is associated with a higher risk of BCa with negligible difference between genders. The risk for BCa is increased in postmenopausal women, specifically in women with earlier menopausal age (<45 years). Other potential risk factors such as alcohol, arsenic exposure, and particulate matter inhalation seem to affect the genders differently.Female smokers experience a higher risk of disease recurrence after bacillus Calmette-Guérin therapy than their male counterparts. Lastly, smoking appears to negatively affect the outcome of radiotherapy in women, but not that of men.

SUMMARY

Several lines of evidence point to an interaction between smoking and gender, whereas their impact on other potential risk factors remains to be elucidated. Identifying such differential effects could allow for gender-specific prevention, early detection, and treatment strategies.

microRNA-324 plays an oncogenic role in bladder cancer cell growth and motility

Background

Despite advances in the treatment of bladder cancer (BC), patients with late-stage BC have a high mortality rate. microRNA is a small, nonprotein coding RNA, and a dysfunction in its expression is frequently strongly correlated with the prognosis of patients with cancer. Aberrant expression of miR-324 has been reported to contribute to human carcinogenesis. However, the role of miR-324 in BC remains unclear.

Methods

The expression levels of miR-324-5p and miR-324-3p were analyzed by analyzing The Cancer Genome Atlas (TCGA) database and real-time polymerase chain reaction (PCR) approach. The biological role of miR-324-5p and miR-324-3p were assessed in BFTC950 cells with miR-324-5p or miR-324-3p mimics transfection, respectively.

Results

In this study, we demonstrated that high expression levels of miR-324-5p and miR-324-3p were significantly correlated with poor survival of patients with BC. Furthermore, miR-324-5p expression significantly accelerated BC cell proliferation, colony formation ability, and invasion ability, whereas miR-324-3p expression slightly increased BC cell growth and motility.

Conclusion

Our data indicated that miR-324-5p and miR-324-3p play oncogenic roles in BC cells. This finding provides a new insight into potential therapeutic targets or putative biomarkers of BC.

Comparison of methods for addressing the point-to-area data transformation to make data suitable for environmental, health and socio-economic studies

Soil lead (Pb) provides an important exposure pathway to the human body through soil ingestion and dust inhalation and is closely associated with human health as well as social behaviour. The challenge of transforming different spatial supports arises when linking point data (Pb concentration) to areal data (health status or social behaviour). A detailed review of methodologies for integrating point and areal data has been carried out. Among a number of methodologies, eight methods: (1) average, (2) median, (3) centroids inverse distance weighted (IDW), (4) average block IDW, (5) median block IDW, (6) centroids ordinary kriging (OK), (7) average block OK and (8) median block OK, have been compared using Pb data set in the Greater London Authority (GLA) area. The results indicated that the method of median block IDW was recommended for further investigation of the relationship between Pb concentration and socio-economic factors in the ward-level of the GLA area. The reasons were (i) spatial interpolations were useful for predicting unobserved values when simple average and median could not work in the locations where there were no samples collected in some areal units; (ii) the median value was more suitable than the average value for a skewed data set; (iii) the block method reduced estimation error and provided more representative values of areal units than the centroid method; (iv) IDW reserved more spatial variation than OK, containing more local maxima (hotspot) and local minima. Despite that it is still hard to decide the optimal method, this study has highlighted the point-to-area transformation issue and provided valuable examples to compare the different methods.

Methylation at cg05575921 of a smoking-related gene (AHRR) in non-smoking Taiwanese adults residing in areas with different PM2.5 concentrations

BACKGROUND

DNA methylation is associated with cancer, metabolic, neurological, and autoimmune disorders. Hypomethylation of aryl hydrocarbon receptor repressor (AHRR) especially at cg05575921 is associated with smoking and lung cancer. Studies on the association between AHRR methylation at cg05575921 and sources of polycyclic aromatic hydrocarbon (PAH) other than smoking are limited. The aim of our study was to assess the pattern of blood DNA methylation at cg05575921 in non-smoking Taiwanese adults living in areas with different PM_2.5 levels.

METHODS

Data on blood DNA methylation, smoking, and residence were retrieved from the Taiwan Biobank dataset (2008-2015). Current and former smokers, as well as individuals with incomplete information were excluded from the current study. The final analysis included 708 participants (279 men and 429 women) aged 30-70 years. PM_2.5 levels have been shown to increase as one moves from the northern through central towards southern Taiwan. Based on this trend, the study areas were categorized into northern, north-central, central, and southern regions.

RESULTS

Living in PM_2.5 areas was associated with lower methylation levels: compared with the northern area (reference area), living in north-central, central, and southern areas was associated with lower methylation levels at cg05575921. However, only methylation levels in those living in central and southern areas were significant (β = - 0.01003, P = 0.009 and β = - 0.01480, P < 0.001, respectively. Even though methylation levels in those living in the north-central area were not statistically significant, the test for linear trend was significant (P < 0.001). When PM_2.5 was included in the regression model, a unit increase in PM_2.5 was associated with 0.00115 (P < 0.001) lower cg05575921 methylation levels.

CONCLUSION

Living in PM_2.5 areas was inversely associated with blood AHRR methylation levels at cg05575921. The methylation levels were lowest in participants residing in southern followed by central and north-central areas. Moreover, when PM_2.5 was included in the regression model, it was inversely associated with methylation levels at cg05575921. Blood methylation at cg05575921 (AHRR) in non-smokers might indicate different exposures to PM_2.5 and lung cancer which is a PM_2.5-related disease.

Environmental regulation, economic growth and air pollution: Panel threshold analysis for OECD countries

Particles with a diameter of <2.5 μm (PM_2.5) have serious adverse-effects on human health, which have caused widespread public concern in recent decades. Currently, most of the existing research on PM_2.5 have used linear regression analysis; very few studies on the subject have been conducted using non-linear models. This study adopts a panel threshold model, which is seldom used in environmental studies, to examine the non-linear effects of environmental regulation and economic growth on PM_2.5 in 30 OECD countries, and we also explore the key driving socio-economic factors for PM_2.5 emissions. The results of our analysis show that, along with an increase in environmental policy stringency, PM_2.5 emissions first rise and then show no significant correlations, and thus a reduction in emissions can be expected if current trends continue. As for GDP per capita, significant and negative correlations are found across the three phases divided by the panel threshold model, indicating a promoting effect for PM_2.5 mitigation. In addition, public expenditure on the air sector correlated positively with PM_2.5 concentrations, expanding the share of service economy reward to reduce air pollution, and urban population ratio exhibits an inverted U-shaped pattern. Future studies may shed more light on the regulation-PM_2.5 nexus, and more studies are needed to confirm the existence of bi-directional correlations between economic development and air pollution.

SOX2 promoter hypermethylation in non-smoking Taiwanese adults residing in air pollution areas

BACKGROUND

Both SOX2 promoter methylation and air pollution have been associated with lung cancer risk. However, little has been done to assess SOX2 promoter methylation in individuals living in air pollution areas. The aim of this study was to investigate SOX2 promoter methylation in non-smoking Taiwanese adults living in areas with different levels of air pollution especially particulate matter with diameter < 2.5 μm (PM2.5).

METHODS

A total of 1142 individuals aged 30-70 years were recruited. Data on SOX2 methylation, residence, age, and exposure to second-hand smoke (SHS) among others were extracted from the Taiwan Biobank dataset (2008-2015). After excluding former and current smokers, alongside those with incomplete information, a total of 461 non-smokers comprising 176 men and 285 women were included in the study. Participants' residences were grouped under northern and central/southern areas because air pollution (PM2.5) is lower in northern compared to central and southern areas.

RESULTS

The methylation levels in men (0.16310 ± 0.01230) and women (0.15740 ± 0.01240) were significantly different (P < .0001). In both sexes, the SOX2 promoter region was shown to be significantly hypermethylated in central and southern areas compared with the northern areas. The regression coefficient (β) was 0.00331 (P = 0.0257) in men and 0.00514 (P < .0001) in women.

CONCLUSION

SOX2 was significantly hypermethylated in both men and women residing in central and southern areas. The consistency in the results for both sexes shows that SOX2 promoter methylation could serve as a potential biomarker for industrial air pollution exposure. Moreover, it might reflect predisposition to cancer. Hence, healthy non-smokers at precancerous stages who have not been clinically diagnosed could be identified.

Differential transcriptional changes in human alveolar epithelial A549 cells exposed to airborne PM2.5 collected from Shanghai, China

Fine particulate matters (PM_2.5) are the core pollutants of haze episode, which pose a serious threat to the human health of developing countries. However, the mechanisms involved in PM_2.5-induced hazard influence are not to fully elucidated. In the present study, human lung epithelial cells (A549) were exposed to various concentrations of PM_2.5 samples collected from Shanghai, China. Illumina RNA-Seq method with transcriptome, Gene Ontology (GO), and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis were further employed to identify the detrimental effects of PM_2.5 on A549 cells in vitro. A total of 712 differentially expressed genes were obtained from global transcriptome profiling of A549 cells after PM_2.5 exposure. In addition, GO function enrichment analysis revealed that major differentially expressed genes (DEGs) involved in the biological process of the immune system and the response to the stress. KEGG pathway analysis further proposes that infectious disease, cancers, cardiovascular disease, and immune disease pathway were the key human disease events that occur in A549 cells under PM_2.5 stress. The data obtained here shed light on the related biological process and gene signaling pathways affected by PM_2.5 exposure. This study aids our understanding of the complicated mechanisms related to PM_2.5-induced health effects and is informative for the prevention and treatment of PM_2.5-induced systemic diseases.

Effects of exposure estimation errors on estimated exposure-response relations for PM2.5

Associations between fine particulate matter (PM2.5) exposure concentrations and a wide variety of undesirable outcomes, from autism and auto theft to elderly mortality, suicide, and violent crime, have been widely reported. Influential articles have argued that reducing National Ambient Air Quality Standards for PM2.5 is desirable to reduce these outcomes. Yet, other studies have found that reducing black smoke and other particulate matter by as much as 70% and dozens of micrograms per cubic meter has not detectably affected all-cause mortality rates even after decades, despite strong, statistically significant positive exposure concentration-response (C-R) associations between them. This paper examines whether this disconnect between association and causation might be explained in part by ignored estimation errors in estimated exposure concentrations. We use EPA air quality monitor data from the Los Angeles area of California to examine the shapes of estimated C-R functions for PM2.5 when the true C-R functions are assumed to be step functions with well-defined response thresholds. The estimated C-R functions mistakenly show risk as smoothly increasing with concentrations even well below the response thresholds, thus incorrectly predicting substantial risk reductions from reductions in concentrations that do not affect health risks. We conclude that ignored estimation errors obscure the shapes of true C-R functions, including possible thresholds, possibly leading to unrealistic predictions of the changes in risk caused by changing exposures. Instead of estimating improvements in public health per unit reduction (e.g., per 10 µg/m³ decrease) in average PM2.5 concentrations, it may be essential to consider how interventions change the distributions of exposure concentrations.

A Review of Recent Advances in Research on PM2.5 in China

PM_2.5 pollution has become a severe problem in China due to rapid industrialization and high energy consumption. It can cause increases in the incidence of various respiratory diseases and resident mortality rates, as well as increase in the energy consumption in heating, ventilation, and air conditioning (HVAC) systems due to the need for air purification. This paper reviews and studies the sources of indoor and outdoor PM_2.5, the impact of PM_2.5 pollution on atmospheric visibility, occupational health, and occupants’ behaviors. This paper also presents current pollution status in China, the relationship between indoor and outdoor PM_2.5, and control of indoor PM_2.5, and finally presents analysis and suggestions for future research.

Spatiotemporal influence of temperature, air quality, and urban environment on cause-specific mortality during hazy days

Haze is an extreme weather event that can severely increase air pollution exposure, resulting in higher burdens on human health. Few studies have explored the health effects of haze, and none have investigated the spatiotemporal interaction between temperature, air quality and urban environment that may exacerbate the adverse health effects of haze. We investigated the spatiotemporal pattern of haze effects and explored the additional effects of temperature, air pollution and urban environment on the short-term mortality risk during hazy days. We applied a Poisson regression model to daily mortality data from 2007 through 2014, to analyze the short-term mortality risk during haze events in Hong Kong. We evaluated the adverse effect on five types of cause-specific mortality after four types of haze event. We also analyzed the additional effect contributed by the spatial variability of urban environment on each type of cause-specific mortality during a specific haze event. A regular hazy day (lag 0) has higher all-cause mortality risk than a day without haze (odds ratio: 1.029 [1.009, 1.049]). We have also observed high mortality risks associated with mental disorders and diseases of the nervous system during hazy days. In addition, extreme weather and air quality contributed to haze-related mortality, while cold weather and higher ground-level ozone had stronger influences on mortality risk. Areas with a high-density environment, lower vegetation, higher anthropogenic heat, and higher PM_2.5 featured stronger effects of haze on mortality than the others. A combined influence of haze, extreme weather/air quality, and urban environment can result in extremely high mortality due to mental/behavioral disorders or diseases of the nervous system. In conclusion, we developed a data-driven technique to analyze the effects of haze on mortality. Our results target the specific dates and areas with higher mortality during haze events, which can be used for development of health warning protocols/systems.

PM2.5, Population Exposure and Economic Effects in Urban Agglomerations of China Using Ground-Based Monitoring Data

This paper adopts the PM_2.5 concentration data obtained from 1497 station-based monitoring sites, population and gross domestic product (GDP) census data, revealing population exposure and economic effects of PM_2.5 in four typical urban agglomerations of China, i.e., Beijing-Tianjin-Hebei (BTH), the Yangtze River delta (YRD), the Pearl River delta (PRD), and Chengdu-Chongqing (CC). The Cokriging interpolation method was used to estimate the PM_2.5 concentration from station-level to grid-level. Next, an evaluation was conducted mainly at the grid-level with a cell size of 1 × 1 km, assisted by the urban agglomeration scale. Criteria including the population-weighted mean, the cumulative percent distribution and the correlation coefficient were applied in our evaluation. The results showed that the spatial pattern of population exposure in BTH was consistent with that of PM_2.5 concentration, as well as changes in elevation. The topography was also an important factor in the accumulation of PM_2.5 in CC. Moreover, the most polluted urban agglomeration based on the population-weighted mean was BTH, while the least was PRD. In terms of the cumulative percent distribution, only 0.51% of the population who lived in the four urban agglomerations, and 2.33% of the GDP that was produced in the four urban agglomerations, were associated with an annual PM_2.5 concentration smaller than the Chinese National Ambient Air Quality Standard of 35 µg/m³. This indicates that the majority of people live in the high air polluted areas, and economic development contributes to air pollution. Our results are supported by the high correlation between population exposure and the corresponding GDP in each urban agglomeration.