Association between Post-Diagnosis Particulate Matter Exposure among 5-Year Cancer Survivors and Cardiovascular Disease Risk in Three Metropolitan Areas from South Korea

Air Pollution in Cardio-Oncology and Unraveling the Environmental Nexus: JACC: CardioOncology State-of-the-Art Review

Although recent advancements in cancer therapies have extended the lifespan of patients with cancer, they have also introduced new challenges, including chronic health issues such as cardiovascular disease arising from pre-existing risk factors or cancer therapies. Consequently, cardiovascular disease has become a leading cause of non-cancer-related death among cancer patients, driving the rapid evolution of the cardio-oncology field. Environmental factors, particularly air pollution, significantly contribute to deaths associated with cardiovascular disease and specific cancers, such as lung cancer. Despite these statistics, the health impact of air pollution in the context of cardio-oncology has been largely overlooked in patient care and research. Notably, the impact of air pollution varies widely across geographic areas and among individuals, leading to diverse exposure consequences. This review aims to consolidate epidemiologic and preclinical evidence linking air pollution to cardio-oncology while also exploring associated health disparities and environmental justice issues.

Effect of inflammation on association between cancer and coronary artery disease

BACKGROUND

Cancer and coronary artery disease (CAD) is reported to often co-exist in same individuals, however, whether cancer is directly associated with anatomical severity of CAD is rarely studied. The present study aimed to observe the relationship between newly diagnosed cancer and anatomical severity of CAD, moreover, to investigate effect of inflammation on the relationship of cancer with CAD.

METHODS

374 patients with newly diagnosed cancer who underwent coronary angiography (CAG) were enrolled. Through 1:3 propensity score matching (PSM) to cancer patients based on the age and gender among 51,106 non-cancer patients who underwent CAG, 1122 non-cancer patients were selected as control patients. Anatomical severity of CAD was assessed using SYNTAX score (SXscore) based on coronary angiographic image. SXscore ≤ 22 (highest quartile) was defined as SX-low, and SXscore > 22 as SX-high. The ratio of neutrophil to lymphocyte count (NLR) was used to describe inflammation level. Association between cancer and the anatomical severity of CAD was investigated using logistic regression.

RESULTS

Univariate logistic regression analysis showed a correlation between cancer and anatomical severity of CAD (OR: 1.419, 95% CI: 1.083-1.859; P = 0.011). Cancer was associated with increased risk of SX-high after adjusted for common risk factors of CAD (OR: 1.598, 95% CI: 1.172-2.179, P = 0.003). Significant association between cancer and SX-high was revealed among patients with high inflammation (OR: 1.656, 95% CI: 1.099-2.497, P = 0.016), but not among patients with low inflammation (OR: 1.530, 95% CI: 0.973-2.498, P = 0.089).

CONCLUSIONS

Cancer was associated with severity of CAD, however, the association between the two diseases was significant among patients with high inflammation rather than among patients with low inflammation.

Health behavior changes and mortality among South Korean cancer survivors

Considering the rapid growth in the number of cancer survivors, the successful management of their health behaviors requires further attention. However, there are lack of information about cancer survivors’ health behaviors and the risk of mortality using Korean cohort data. This study aimed to examine the effects of health behavior changes on mortality among cancer survivors and to develop a validated nomogram. This cohort study was conducted using claims data. Data from adult cancer survivors from the National Health Insurance Service–National Sample Cohort, conducted between 2002 and 2015, were included. Individuals who were alive for five years after their cancer diagnosis were defined as cancer survivors. Cox proportional-hazards regression was used to estimate the target associations. Discrimination (Harrell’s C-index) and calibration (Hosmer–Lemeshow test) were employed to validate the nomogram. Data from 9300 cancer survivors were used for analysis. Compared to non-smokers, those who started or quit smoking had a higher risk of all-cause mortality. Those who were physically inactive had a higher risk of all-cause mortality than those who were continuously active. In the nomogram, the C-index value was 0.79 in the training data and 0.81 in the testing data. Hosmer–Lemeshow test was not significant, demonstrating a good fit. We found that individuals with unhealthy behaviors had a higher risk of mortality, thereby highlighting the importance of managing health behaviors among cancer survivors. The development of a validated nomogram may provide useful insights regarding official policies and existing practices in healthcare systems, which would benefit cancer survivors. Our study could provide the evidence to inform the priority of guideline for managing the health behavior among cancer survivors.

Combined Associations of Physical Activity and Particulate Matter With Subsequent Cardiovascular Disease Risk Among 5‐Year Cancer Survivors

Background

The combined associations of physical activity and particulate matter (PM) with subsequent cardiovascular disease (CVD) risk is yet unclear.

Methods and Results

The study population consisted of 18 846 cancer survivors who survived for at least 5 years after initial cancer diagnosis from the Korean National Health Insurance Service database. Average PM levels for 4 years were determined in administrative district areas, and moderate‐to‐vigorous physical activity (MVPA) information was acquired from health examination questionnaires. A multivariable Cox proportional hazards model was used to evaluate the risk for CVD. Among patients with low PM with particles ≤2.5 µm (PM2.5; (19.8–25.6 μg/m³) exposure, ≥5 times per week of MVPA was associated with lower CVD risk (adjusted hazard ratio [aHR], 0.77; 95% CI, 0.60–0.99) compared with 0 times per week of MVPA. Also, a higher level of MVPA frequency was associated with lower CVD risk (P for trend=0.028) among cancer survivors who were exposed to low PM2.5 levels. In contrast, ≥5 times per week of MVPA among patients with high PM2.5 (25.8–33.8 μg/m³) exposure was not associated with lower CVD risk (aHR, 0.98; 95% CI, 0.79–1.21). Compared with patients with low PM2.5 and MVPA ≥3 times per week, low PM2.5 and MVPA ≤2 times per week (aHR, 1.26; 95% CI, 1.03–1.55), high PM2.5 and MVPA ≥3 times per week (aHR, 1.34; 95% CI, 1.07–1.67), and high PM2.5 and MVPA ≤2 times per week (aHR, 1.38; 95% CI, 1.12–1.70) was associated with higher CVD risk.

Conclusions

Cancer survivors who engaged in MVPA ≥5 times per week benefited from lower CVD risk upon low PM2.5 exposure. High levels of PM2.5 exposure may attenuate the risk‐reducing effects of MVPA on the risk of CVD.

Association of particulate matter with autoimmune rheumatic diseases among adults in South Korea

OBJECTIVE

The primary objective of this study was to investigate adverse effects of ambient particulate matter of various sizes on the incidence of the prevalent autoimmune rheumatic diseases (AIRDs): RA, AS and SLE.

METHODS

We investigated 230 034 participants in three metropolitan cities of South Korea from the National Health Insurance Service-National Sample Cohort (NHIS-NSC). Starting from January 2010, subjects were followed up until the first event of prevalent AIRDs, death, or December 2013. The 2008-2009 respective averages of particulate matter2.5 (<2.5 μm) and particulate mattercoarse (2.5 μm to 10 μm) were linked with participants' administrative district codes. Adjusted hazard ratios (aHRs) and 95% CIs were estimated using Cox regression analysis in one- and two-pollutant models.

RESULTS

Adjusted for age, sex, region, and household income, in the two-pollutant model, RA incidence was positively associated with the 10 μg/m³ increment of particulate matter2.5 (aHR = 1.74, 95% CI: 1.06, 2.86), but not with particulate mattercoarse (aHR = 1.27, 95% CI: 0.87, 1.85). In the one-pollutant model, the elevated incidence rate of RA was slightly attenuated (particulate matter2.5 aHR = 1.61, 95% CI: 0.99, 2.61; particulate mattercoarse aHR = 1.13, 95% CI: 0.80, 1.61), with marginal statistical significance for particulate matter2.5. The RA incidence was also higher in the 4th quartile group of particulate matter2.5 compared with the first quartile group (aHR = 1.83, 95% CI: 1.07, 3.11). Adverse effects from particulate matter were not found for AS or SLE in either the one- or two-pollutant models.

CONCLUSION

The important components of particulate matter10 associated with RA incidence were the fine fractions (particulate matter2.5); no positive association was found between particulate matter and AS or SLE.

Association of the combined effects of air pollution and changes in physical activity with cardiovascular disease in young adults

AIMS

Little is known about the trade-off between the health benefits of physical activity (PA) and the potential harmful effects of increased exposure to air pollution during outdoor PA. We examined the association of the combined effects of air pollution and changes in PA with cardiovascular disease (CVD) in young adults.

METHODS AND RESULTS

This nationwide cohort study included 1 469 972 young adults aged 20-39 years. Air pollution exposure was estimated by the annual average cumulative level of particulate matter (PM). PA was calculated as minutes of metabolic equivalent tasks per week (MET-min/week) based on two consecutive health examinations from 2009 to 2012. Compared with the participants exposed to low-to-moderate levels of PM2.5 or PM10 who continuously engaged in ≥1000 MET-min/week of PA, those who decreased their PA from ≥1000 MET-min/week to 1-499 MET-min/week [PM10 adjusted hazard ratio (aHR) 1.22; 95% confidence interval (CI) 1.00-1.48] and to 0 MET-min/week (physically inactive; PM10 aHR 1.38; 95% CI 1.07-1.78) had an increased risk of CVD (P for trend <0.01). Among participants exposed to high levels of PM2.5 or PM10, the risk of CVD was elevated with an increase in PA above 1000 MET-min/week.

CONCLUSION

Reducing PA may lead to subsequent elevation of CVD risk in young adults exposed to low-to-moderate levels of PM2.5 or PM10, whereas a large increase in PA in a high-pollution environment may adversely affect cardiovascular health.

Association of Short-Term Particulate Matter Exposure among 5-Year Cancer Survivors with Incident Cardiovascular Disease: A Time-Stratified Case-Crossover Study

The association of short-term particulate matter concentration with cardiovascular disease (CVD) among cancer survivors is yet unclear. Using the National Health Insurance Service database from South Korea, the study population consisted of 22,864 5-year cancer survivors with CVD events during the period 2015-2018. Using a time-stratified case-crossover design, each case date (date of incident CVD) was matched with three or four referent dates, resulting in a total of 101,576 case and referent dates. The daily average particulate matter 10 (PM10), 2.5 (PM2.5), and 2.5-10 (PM2.5-10) on the day of case or referent date (lag0), 1-3 days before the case or referent date (lag1, lag2, and lag3), and the mean value 0-3 days before the case or referent date (lag0-3) were determined. Conditional logistic regression was conducted to calculate the adjusted odds ratios (aORs) and 95% confidence intervals (CIs) for CVD according to quartiles of PM10, PM2.5, and PM2.5-10. Compared to the 1st (lowest) quartile of lag0-3 PM10, the 4th (highest) quartile of lag0-3 PM10 was associated with higher odds for CVD (aOR 1.13, 95% CI 1.06-1.21). The 4th quartiles of lag1 (aOR 1.12, 95% CI 1.06-1.19), lag2 (aOR 1.09, 95% CI 1.03-1.16), lag3 (aOR 1.06, 95% CI 1.00-1.12), and lag0-3 (aOR 1.11, 95% CI 1.05-1.18) PM2.5 were associated with higher odds for CVD compared to the respective 1st quartiles. Similarly, the 4th quartile of lag0-3 PM2.5-10 was associated with higher CVD events (aOR 1.11, 95% CI 1.03-1.19) compared to the 1st quartile. Short-term exposure to high levels of PM may be associated with increased CVD risk among cancer survivors.

Association of Air Pollutants with Incident Chronic Kidney Disease in a Nationally Representative Cohort of Korean Adults

(1) Background: There is limited information regarding association between long-term exposure to air pollutants and risk of chronic kidney disease (CKD) (2). Methods: This study acquired data of 164,093 adults aged at least 40 years who were residing in 7 metropolitan cities between 2002 and 2005 from the Korean National Health Insurance Service National Sample Cohort database. CKD risk was evaluated using the multivariate Cox hazards proportional regression. All participants were followed up with until CKD, death, or 31 December 2013, whichever occurred earliest. (3) Results: Among 1,259,461 person-years of follow-up investigation, CKD cases occurred in 1494 participants. Air pollutant exposures including PM10, SO2, NO2, CO, and O3 showed no significant association with incident CKD after adjustments for age, sex, household income, area of residence, and the Charlson comorbidity index. The results were consistent in the sensitivity analyses including first and last year annual exposure analyses as well as latent periods-washed-out analyses. (4) Conclusions: Long-term exposure to air pollution is not likely to increase the risk of CKD.

Cardiovascular effects of air pollution: current evidence from animal and human studies

Air pollution is a global health concern. Particulate matter (PM)_2.5, a component of ambient air pollution, has been identified by the World Health Organization as one of the pollutants that poses the greatest threat to public health. Cardiovascular health effects have been extensively documented, and these effects are still being researched to provide an overview of recent literature regarding air pollution-associated cardiovascular morbidity and mortality in humans. Additionally, potential mechanisms through which air pollutants affect the cardiovascular system are discussed based on human and additional animal studies. We used the strategy of a narrative review to summarize the scientific literature of studies that were published in the past 7 yr. Searches were carried out on PubMed and Web of Science using predefined search queries. We obtained an initial set of 800 publications that were filtered to 78 publications that were relevant to include in this review. Analysis of the literature showed significant associations between air pollution, especially PM_2.5, and the risk of elevated blood pressure (BP), acute coronary syndrome, myocardial infarction (MI), cardiac arrhythmia, and heart failure (HF). Prominent mechanisms that underlie the adverse effects of air pollution include oxidative stress, systemic inflammation, endothelial dysfunction, autonomic imbalance, and thrombogenicity. The current review underscores the relevance of air pollution as a global health concern that affects cardiovascular health. More rigorous standards are needed to reduce the cardiovascular disease burden imposed by air pollution. Continued research on the health impact of air pollution is needed to provide further insight.

Potential of ARIMA-ANN, ARIMA-SVM, DT and CatBoost for Atmospheric PM2.5 Forecasting in Bangladesh

Atmospheric particulate matter (PM) has major threats to global health, especially in urban regions around the world. Dhaka, Narayanganj and Gazipur of Bangladesh are positioned as top ranking polluted metropolitan cities in the world. This study assessed the performance of the application of hybrid models, that is, Autoregressive Integrated Moving Average (ARIMA)-Artificial Neural Network (ANN), ARIMA-Support Vector Machine (SVM) and Principle Component Regression (PCR) along with Decision Tree (DT) and CatBoost deep learning model to predict the ambient PM2.5 concentrations. The data from January 2013 to May 2019 with 2342 observations were utilized in this study. Eighty percent of the data was used as training and the rest of the dataset was employed as testing. The performance of the models was evaluated by R2, RMSE and MAE value. Among the models, CatBoost performed best for predicting PM2.5 for all the stations. The RMSE values during the test period were 12.39 µg m−3, 13.06 µg m−3 and 12.97 µg m−3 for Dhaka, Narayanganj and Gazipur, respectively. Nonetheless, the ARIMA-ANN and DT methods also provided acceptable results. The study suggests adopting deep learning models for predicting atmospheric PM2.5 in Bangladesh.