Environment & Health最新文献_第8页

Impact of Climate Change on Indoor Radon Concentrations as a Current Public Health Challenge 气候变化对室内氡浓度的影响是当前的公共卫生挑战。

IF 6.3

Environment & Health Pub Date : 2025-05-01 DOI: 10.1021/envhealth.4c00269

Ala V. Overcenco*, and , Liuba Ş. Coreţchi,

{"title":"Impact of Climate Change on Indoor Radon Concentrations as a Current Public Health Challenge","authors":"Ala V. Overcenco*,  and , Liuba Ş. Coreţchi, ","doi":"10.1021/envhealth.4c00269","DOIUrl":"10.1021/envhealth.4c00269","url":null,"abstract":"Climate change is considered to intensify radon migration into houses, increasing health risks. Energy efficiency strategies can contribute to indoor radon accumulation, particularly in the winter and summer seasons, when buildings are sealed to maintain thermal comfort. Studies in various regions of the world have shown that meteorological factors influence indoor radon concentration either directly or indirectly. Seasonal variations in radon levels have been observed, with winter concentrations exceeding summer levels by 2–5 times, while extreme weather events further impact radon exhalation. Epidemiological data indicate that the increase of indoor radon concentration by 100 Bq/m3 raises lung cancer risk by 16%, with 35–40% of radon-related lung cancers potentially preventable through exposure reduction. Additionally, recent studies suggest a correlation between radon exposure and cardiovascular diseases, contributing to its significance for public health. Collecting meteorological data alongside indoor radon measurements and analyzing their relationship are essential for understanding such interactions as well as developing public health strategies for prevention and adaptation to future climate conditions. Based on international experience, methodological approaches to the study of the assessment of the influence of meteorological factors on the risk of radon exposure in a regional context have been formulated.","PeriodicalId":29795,"journal":{"name":"Environment & Health","volume":"3 7","pages":"705–713"},"PeriodicalIF":6.3,"publicationDate":"2025-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12281206/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144699722","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Evaluating the Vascular Risk of PFCs: An Integrated XGBoost-Driven Structure–Activity Prediction and Experimental Validation Study 评估pfc血管风险：一项综合xgboost驱动的结构-活性预测和实验验证研究。

IF 6.3

Environment & Health Pub Date : 2025-04-29 DOI: 10.1021/envhealth.5c00014

Gan Miao, Chengying Zhou, Liting Xu, Li Zhao, Jingxu Zhang, Ze Zhang, Zhe Kou, Rifat Zubair Ahmed, Dawei Lu, Xiaoting Jin* and Yuxin Zheng,

{"title":"Evaluating the Vascular Risk of PFCs: An Integrated XGBoost-Driven Structure–Activity Prediction and Experimental Validation Study","authors":"Gan Miao, Chengying Zhou, Liting Xu, Li Zhao, Jingxu Zhang, Ze Zhang, Zhe Kou, Rifat Zubair Ahmed, Dawei Lu, Xiaoting Jin* and Yuxin Zheng, ","doi":"10.1021/envhealth.5c00014","DOIUrl":"10.1021/envhealth.5c00014","url":null,"abstract":"Perfluorochemicals (PFCs) are emergent and persistent organic pollutants with widespread application. Their structural similarity and detection in serum raises substantial concerns regarding their toxicological effects. While the endocrine-disrupting effects of PFCs are well-recognized, the structure–activity relationship with respect to vascular function has not been investigated yet. This study addresses this critical gap by investigating the impact of PFCs on endothelial cell function, a key determinant of cardiovascular health. Through a machine learning-based quantitative structure–activity relationship (QSAR) model, we analyzed 16 structural descriptors for 23 environmentally prevalent PFCs with respect to their binding affinities to endothelial cell receptors. The eXtreme Gradient Boosting (XGBoost) algorithm suggested short-chain PFCs with strong acid groups may as particularly detrimental to endothelial cells, a finding substantiated by subsequent cell culture experiments. We also integrated computational and experimental approaches, providing a detailed understanding of the structure–activity and dose–response relationships of PFCs. Furthermore, the population health risk assessment, linking in vitro adverse effect with in vivo exposure data, indicated differences in risks across countries due to the global shift in the fluoride industry; the entire Chinese population is at high risk, with risk varying by gender and industrialization level. This study not only elucidates the structure–activity relationship of PFCs on vascular function but also offers a strategic framework for managing toxic PFCs and proposing the development of safer alternatives.","PeriodicalId":29795,"journal":{"name":"Environment & Health","volume":"3 7","pages":"795–806"},"PeriodicalIF":6.3,"publicationDate":"2025-04-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12281208/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144699721","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Omega-3 Modify the Adverse Effects of Long-Term Exposure to Ambient Air Pollution on the Incidence of Chronic Obstructive Pulmonary Disease: Evidence from a Nationwide Prospective Cohort Study Omega - 3改变长期暴露于环境空气污染对慢性阻塞性肺疾病发病率的不利影响：来自全国前瞻性队列研究的证据

IF 6.3

Environment & Health Pub Date : 2025-04-28 DOI: 10.1021/envhealth.4c00198

Jixuan Ma, Yuxin Yao, Yujia Xie, Haoyu Yin, Shiyu Yang, Bingxin Shang, Xiaojie You, Yanjun Guo and Weihong Chen*,

{"title":"Omega-3 Modify the Adverse Effects of Long-Term Exposure to Ambient Air Pollution on the Incidence of Chronic Obstructive Pulmonary Disease: Evidence from a Nationwide Prospective Cohort Study","authors":"Jixuan Ma, Yuxin Yao, Yujia Xie, Haoyu Yin, Shiyu Yang, Bingxin Shang, Xiaojie You, Yanjun Guo and Weihong Chen*, ","doi":"10.1021/envhealth.4c00198","DOIUrl":"10.1021/envhealth.4c00198","url":null,"abstract":"We aim to assess the modification effects of omega-3 polyunsaturated fatty acid (PUFA) levels on relationships between long-term air pollutants exposure and chronic obstructive pulmonary disease (COPD) risk. A total of 82,706 nonsmokers were finally included in the UK Biobank. The concentrations of circulating omega-3 PUFA (including total omega-3 and docosahexaenoic acid [DHA]) were measured by using a targeted high-throughput nuclear magnetic resonance metabolomics platform. Land-use regression models were used to estimate concentrations of nitrogen dioxide (NO2) and particulate matter (PM2.5 and PM10) for each individual. Additionally, systemic inflammation levels were assessed using the low-grade inflammation score (INFLA-score) to elucidate the potential mechanism. We noted that the observed effects could be modified by circulating omega-3 PUFA levels (P-interaction < 0.05). Specifically, the significant pollutants-COPD associations were mainly observed in the lower circulating omega-3 PUFA groups. In contrast, there was no statistical evidence for increased COPD risk associated with air pollutants in subjects with higher circulating omega-3 PUFA. Mediation analysis further indicated that circulating omega-3 PUFA modified the air pollution-associated COPD risk might partly by reducing systemic inflammation. In summary, circulating omega-3 PUFA may provide protection against the COPD risk caused by long-term exposure to air pollutants.","PeriodicalId":29795,"journal":{"name":"Environment & Health","volume":"3 7","pages":"787–794"},"PeriodicalIF":6.3,"publicationDate":"2025-04-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12281204/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144699725","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Nationwide Machine Learning-Ensemble PM2.5 Mapping Prediction and Forecasting Models in South Korea with High Spatiotemporal Resolution and Health Risk Estimation-Based Evaluations 基于健康风险评估和高时空分辨率的韩国全国机器学习-集成PM2.5映射预测和预测模型

IF 6.3

Environment & Health Pub Date : 2025-04-23 DOI: 10.1021/envhealth.4c00201

Seoyeong Ahn, Ayoung Kim, Yeonseung Chung, Cinoo Kang, Sooyoung Kim, Dohoon Kwon, Jiwoo Park, Jieun Oh, Jinah Park, Jeongmin Moon, Insung Song, Jieun Min, Hyung Joo Lee, Ho Kim and Whanhee Lee*,

{"title":"Nationwide Machine Learning-Ensemble PM2.5 Mapping Prediction and Forecasting Models in South Korea with High Spatiotemporal Resolution and Health Risk Estimation-Based Evaluations","authors":"Seoyeong Ahn, Ayoung Kim, Yeonseung Chung, Cinoo Kang, Sooyoung Kim, Dohoon Kwon, Jiwoo Park, Jieun Oh, Jinah Park, Jeongmin Moon, Insung Song, Jieun Min, Hyung Joo Lee, Ho Kim and Whanhee Lee*, ","doi":"10.1021/envhealth.4c00201","DOIUrl":"https://doi.org/10.1021/envhealth.4c00201","url":null,"abstract":"Several studies developed machine learning-based PM2.5 prediction models; however, nationwide models addressing both mapping prediction and forecasting were limited. Further, although the prediction accuracy is different from PM2.5-related health risk estimation, previous studies solely examined the prediction accuracy. This study suggests a method to assess the statistical properties of PM2.5-health risk estimation, which also can be used as a model selection. We used three machine learning algorithms and an ensemble method to construct PM2.5 mapping prediction (1 km2) and two-day forecasting models majorly using satellite-driven data in South Korea (2015–2022). We performed a simulation study to examine the statistical properties of short-term PM2.5 risk estimation using prediction models. Our ensemble spatial prediction model showed better performance than single algorithms (0.956 test R2). The range of the R2 values was 0.78–0.98 across the monitoring sites. The average % bias was from 1.403%–1.787% when our mapping models for PM2.5-mortality risk estimation, compared to the estimates from monitored PM2.5. The best R2 of our forecasting models was 0.904. This study developed machine learning models for spatial PM2.5 predictions and forecasting in Korea. This study also suggested a method to address risk estimation and model selection concurrently when multiple prediction models were used.","PeriodicalId":29795,"journal":{"name":"Environment & Health","volume":"3 8","pages":"878–887"},"PeriodicalIF":6.3,"publicationDate":"2025-04-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://pubs.acs.org/doi/pdf/10.1021/envhealth.4c00201","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144840464","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Residential Greenness and the Incidence of Dyslipidemia in Chinese Adults: A Large Prospective Cohort Study 住宅绿化与中国成人血脂异常的发病率：一项大型前瞻性队列研究。

IF 6.3

Environment & Health Pub Date : 2025-04-22 DOI: 10.1021/envhealth.4c00278

Jia-Xin Li, Li Li, Shujun Fan, Beibei Li, Hui-Ling Qiu, Aimin Xu, Yu-Ting Xie, Chuanjiang He, Gang-Long Zhou, Xiao-Qi Zhu, Lu Wang, Jian-Cheng Jiang, Hui-Yun Chen, Yan-Zhao He, Qinqin Jiang, Zhou-Bin Zhang, Guang-Hui Dong, Qiansheng Hu*, Xiaoguang Zou* and Bo-Yi Yang*,

{"title":"Residential Greenness and the Incidence of Dyslipidemia in Chinese Adults: A Large Prospective Cohort Study","authors":"Jia-Xin Li, Li Li, Shujun Fan, Beibei Li, Hui-Ling Qiu, Aimin Xu, Yu-Ting Xie, Chuanjiang He, Gang-Long Zhou, Xiao-Qi Zhu, Lu Wang, Jian-Cheng Jiang, Hui-Yun Chen, Yan-Zhao He, Qinqin Jiang, Zhou-Bin Zhang, Guang-Hui Dong, Qiansheng Hu*, Xiaoguang Zou* and Bo-Yi Yang*, ","doi":"10.1021/envhealth.4c00278","DOIUrl":"10.1021/envhealth.4c00278","url":null,"abstract":"Dyslipidemia is a significant risk factor for cardiovascular disease. While cross-sectional studies suggest lower odds of dyslipidemia in greener environments, longitudinal research is limited. This prospective cohort study analyzed data from 3,454,623 adults from January 2017 to December 2021, focusing on dyslipidemia and its subtypes. Residential greenness was assessed using vegetation indices and greenspace percentages. Cox regressions and generalized estimating equation models were used to analyze associations between greenness and dyslipidemia outcomes. Over a median follow-up period of 3.21 years, 744,732 cases of dyslipidemia were observed. Greener environments were associated with a reduced risk of dyslipidemia, hypercholesterolemia, hypertriglyceridemia, and hyperbetalipoproteinemia (hazard ratios ranged from 0.82 to 0.96) and an increased risk of hypoalphalipoproteinemia (hazard ratios were 1.12 to 1.15). Higher greenness levels were linked to lower serum lipids. These associations were stronger among older adults and those with higher education. Mediation analyses showed that lower air pollution, temperature, and higher physical activity accounted for 2.08–33.72% of the associations between greenness and dyslipidemia. Our findings suggest that greenspace exposure can be incorporated into dyslipidemia etiology and prevention strategies. Nature therapies like forest bathing can be supplementary strategies.","PeriodicalId":29795,"journal":{"name":"Environment & Health","volume":"3 7","pages":"777–786"},"PeriodicalIF":6.3,"publicationDate":"2025-04-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12281202/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144699727","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0