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Xue M, Xu Z, Wang X, Chen J, Kong X, Zhou S, Wu J, Zhang Y, Li Y, Christiani DC, Chen F, Zhao Y, Zhang R. ARTEMIS: An independently validated prognostic prediction model of breast cancer incorporating epigenetic biomarkers with main effects and gene-gene interactions. J Adv Res 2024:S2090-1232(24)00358-8. [PMID: 39137864 DOI: 10.1016/j.jare.2024.08.015] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/07/2024] [Revised: 08/05/2024] [Accepted: 08/09/2024] [Indexed: 08/15/2024] Open
Abstract
INTRODUCTION Breast cancer, a heterogeneous disease, is influenced by multiple genetic and epigenetic factors. The majority of prognostic models for breast cancer focus merely on the main effects of predictors, disregarding the crucial impacts of gene-gene interactions on prognosis. OBJECTIVES Using DNA methylation data derived from nine independent breast cancer cohorts, we developed an independently validated prognostic prediction model of breast cancer incorporating epigenetic biomarkers with main effects and gene-gene interactions (ARTEMIS) with an innovative 3-D modeling strategy. ARTEMIS was evaluated for discrimination ability using area under the receiver operating characteristics curve (AUC), and calibration using expected and observed (E/O) ratio. Additionally, we conducted decision curve analysis to evaluate its clinical efficacy by net benefit (NB) and net reduction (NR). Furthermore, we conducted a systematic review to compare its performance with existing models. RESULTS ARTEMIS exhibited excellent risk stratification ability in identifying patients at high risk of mortality. Compared to those below the 25th percentile of ARTEMIS scores, patients with above the 90th percentile had significantly lower overall survival time (HR = 15.43, 95% CI: 9.57-24.88, P = 3.06 × 10-29). ARTEMIS demonstrated satisfactory discrimination ability across four independent populations, with pooled AUC3-year = 0.844 (95% CI: 0.805-0.883), AUC5-year = 0.816 (95% CI: 0.775-0.857), and C-index = 0.803 (95% CI: 0.776-0.830). Meanwhile, ARTEMIS had well calibration performance with pooled E/O ratio 1.060 (95% CI: 1.038-1.083) and 1.090 (95% CI: 1.057-1.122) for 3- and 5-year survival prediction, respectively. Additionally, ARTEMIS is a clinical instrument with acceptable cost-effectiveness for detecting breast cancer patients at high risk of mortality (Pt = 0.4: NB3-year = 19‰, NB5-year = 62‰; NR3-year = 69.21%, NR5-year = 56.01%). ARTEMIS has superior performance compared to existing models in terms of accuracy, extrapolation, and sample size, as indicated by the systematic review. ARTEMIS is implemented as an interactive online tool available at http://bigdata.njmu.edu.cn/ARTEMIS/. CONCLUSION ARTEMIS is an efficient and practical tool for breast cancer prognostic prediction.
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Affiliation(s)
- Maojie Xue
- Department of Biostatistics, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, Jiangsu 211166, China
| | - Ziang Xu
- State Key Laboratory Cultivation Base of Research, Prevention and Treatment for Oral Diseases, Nanjing Medical University, Nanjing, Jiangsu 210029, China; Department of Oral Special Consultation, Affiliated Stomatological Hospital of Nanjing Medical University, Nanjing, Jiangsu 210029, China
| | - Xiang Wang
- Department of Biostatistics, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, Jiangsu 211166, China
| | - Jiajin Chen
- Department of Biostatistics, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, Jiangsu 211166, China; Institute of Cardiovascular Diseases, Xiamen Cardiovascular Hospital of Xiamen University, Xiamen, Fujian 361006, China
| | - Xinxin Kong
- Department of Biostatistics, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, Jiangsu 211166, China
| | - Shenxuan Zhou
- Department of Biostatistics, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, Jiangsu 211166, China
| | - Jiamin Wu
- Department of Biostatistics, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, Jiangsu 211166, China
| | - Yuhao Zhang
- Department of General Biology, Eberly College of Science, Pennsylvania State University, Pennsylvania 16802, USA
| | - Yi Li
- Department of Biostatistics, University of Michigan, Ann Arbor, MI 48109, USA
| | - David C Christiani
- Pulmonary and Critical Care Division, Department of Medicine, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02114, USA; Department of Environmental Health, Harvard T.H. Chan School of Public Health, Boston, MA 02115, USA
| | - Feng Chen
- Department of Biostatistics, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, Jiangsu 211166, China; China International Cooperation Center for Environment and Human Health, Nanjing Medical University, Jiangsu 211166, China.
| | - Yang Zhao
- Department of Biostatistics, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, Jiangsu 211166, China; China International Cooperation Center for Environment and Human Health, Nanjing Medical University, Jiangsu 211166, China.
| | - Ruyang Zhang
- Department of Biostatistics, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, Jiangsu 211166, China; China International Cooperation Center for Environment and Human Health, Nanjing Medical University, Jiangsu 211166, China; Changzhou Medical Center, Nanjing Medical University, Changzhou, Jiangsu 213164, China.
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Ige O, Ratnayake I, Martinez J, Pepper S, Alsup A, McGuirk M, Gajewski B, Mudaranthakam DP. A Regional Study to Evaluate the Impact of Coal-fired Power Plants on Lung Cancer Incident Rates. PREVENTIVE ONCOLOGY & EPIDEMIOLOGY 2024; 2:2348469. [PMID: 38899318 PMCID: PMC11185817 DOI: 10.1080/28322134.2024.2348469] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/28/2023] [Accepted: 04/24/2024] [Indexed: 06/21/2024]
Abstract
Background Lung cancer is the leading cause of cancer related deaths. In Kansas, where coal-fired power plants account for 34% of power, we investigated whether hosting counties had higher age-adjusted lung cancer incidence rates. We also examined demographics, poverty levels, percentage of smokers, and environmental conditions using spatial analysis. Methods Data from the Kansas Health Matters, and the Behavioral Risk Factor Surveillance System (2010-2014) for 105 counties in Kansas were analyzed. Multiple Linear Regression (MLR) assessed associations between potential risk factors and age-adjusted lung cancer incidence rates while Geographically Weighted Regression (GWR) examined regional risk factors. Results Moran's I test confirmed spatial autocorrelation in age-adjusted lung cancer incidence rates (p<0.0003). MLR identified percentage of smokers, population size, and proportion of elderly population as significant predictors of age-adjusted lung cancer incidence rates (p<0.05). GWR showed positive associations between percentage of smokers and age-adjusted lung cancer incidence rates in over 50% of counties. Conclusion Contrary to our hypothesis, proximity to a coal-fired power plant was not a significant predictor of age-adjusted lung cancer incidence rates. Instead, percentage of smokers emerged as a consistent global and regional risk factor. Regional lung cancer outcomes in Kansas are influenced by wind patterns and elderly population.
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Affiliation(s)
- Oluwatobiloba Ige
- Department of Biostatistics & Data Science, The University of Kansas Medical Center, Mail Stop 1026, 3901 Rainbow Blvd., Kansas City, KS 66160 USA
| | - Isuru Ratnayake
- Department of Biostatistics & Data Science, The University of Kansas Medical Center, Mail Stop 1026, 3901 Rainbow Blvd., Kansas City, KS 66160 USA
| | - Joshua Martinez
- Department of Biostatistics & Data Science, The University of Kansas Medical Center, Mail Stop 1026, 3901 Rainbow Blvd., Kansas City, KS 66160 USA
| | - Sam Pepper
- Department of Biostatistics & Data Science, The University of Kansas Medical Center, Mail Stop 1026, 3901 Rainbow Blvd., Kansas City, KS 66160 USA
- The University of Kansas Cancer Center, The University of Kansas Medical Center, 3901 Rainbow Blvd., Kansas City, KS 66160 USA
| | - Alexander Alsup
- Department of Biostatistics & Data Science, The University of Kansas Medical Center, Mail Stop 1026, 3901 Rainbow Blvd., Kansas City, KS 66160 USA
| | - Matthew McGuirk
- Department of Biostatistics & Data Science, The University of Kansas Medical Center, Mail Stop 1026, 3901 Rainbow Blvd., Kansas City, KS 66160 USA
| | - Byron Gajewski
- Department of Biostatistics & Data Science, The University of Kansas Medical Center, Mail Stop 1026, 3901 Rainbow Blvd., Kansas City, KS 66160 USA
- The University of Kansas Cancer Center, The University of Kansas Medical Center, 3901 Rainbow Blvd., Kansas City, KS 66160 USA
| | - Dinesh Pal Mudaranthakam
- Department of Biostatistics & Data Science, The University of Kansas Medical Center, Mail Stop 1026, 3901 Rainbow Blvd., Kansas City, KS 66160 USA
- The University of Kansas Cancer Center, The University of Kansas Medical Center, 3901 Rainbow Blvd., Kansas City, KS 66160 USA
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Boonhat H, Guo YL, Chan CC, Lin RT. Estimates of the global burden of cancer-related deaths attributable to residential exposure to petrochemical industrial complexes from 2020 to 2040. ENVIRONMENTAL POLLUTION (BARKING, ESSEX : 1987) 2024; 350:123955. [PMID: 38631450 DOI: 10.1016/j.envpol.2024.123955] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/18/2023] [Revised: 02/23/2024] [Accepted: 04/09/2024] [Indexed: 04/19/2024]
Abstract
The petrochemical industry is a major industrial emitter of greenhouse gas (CO2) and environmental pollution, posing health risks to nearby communities. Although previous studies have indicated that residents living near petrochemical industrial complexes are at a higher risk of cancer, they have focused on local or regional burdens. This study aimed to estimate the global cancer burden attributable to residential exposure to petrochemical industrial complexes. The geographical coordinates of petrochemical plants and oil refineries were retrieved and verified from published sources. The ArcGIS software and global population data were used to estimate the number of people living within specific distances (exposed population). The exposure time window was framed as ranging from 1992 to 2035, extending to the latest period of the exposure time window for all cancer types to estimate the attributable deaths between 2020 and 2040. The relative risk of cancer was estimated from 15 published studies. Population attributable fraction (PAF) method was used to estimate the risk of cancer attributable to residential exposure and calculate the number of cancer-related deaths. Our findings indicate that >300 million people worldwide will be estimated to live near petrochemical industrial complexes by 2040. The overall global burden of cancer-related deaths was 19,083 in 2020, and it is estimated to increase to 27,366 deaths by 2040. The region with the highest attributable cancer deaths due to exposure is the high-income region, which had 10,584 deaths in 2020 and is expected to reach 13,414 deaths by 2040. Residential exposure to petrochemical industrial complexes could contribute to global cancer deaths, even if the proportion is relatively small, and proactive measures are required to mitigate the cancer burdens among these residents. Enforcing emissions regulations, improving monitoring, educating communities, and fostering collaboration are vital to protecting residents' health.
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Affiliation(s)
- Hathaichon Boonhat
- Graduate Institute of Public Health, College of Public Health, China Medical University, Taichung, 406040, Taiwan; Department of Epidemiology, Faculty of Public Health, Mahidol University, Bangkok, 10400, Thailand.
| | - Yue Leon Guo
- Environmental and Occupational Medicine, National Taiwan University (NTU) College of Medicine and NTU Hospital, Taiwan; Institute of Environmental and Occupational Health Sciences, College of Public Health, National Taiwan University, Taipei, 100025, Taiwan.
| | - Chang-Chuan Chan
- Institute of Environmental and Occupational Health Sciences, College of Public Health, National Taiwan University, Taipei, 100025, Taiwan.
| | - Ro-Ting Lin
- Department of Occupational Safety and Health, College of Public Health, China Medical University, Taichung, 406040, Taiwan.
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Mahlangeni N, Kapwata T, Laban T, Wright CY. Health risks of exposure to air pollution in areas where coal-fired power plants are located: protocol for a scoping review. BMJ Open 2024; 14:e084074. [PMID: 38508645 PMCID: PMC10952927 DOI: 10.1136/bmjopen-2024-084074] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/08/2024] [Accepted: 03/04/2024] [Indexed: 03/22/2024] Open
Abstract
INTRODUCTION Coal-fired power plants are major sources of air pollution which impact human health. Coal combustion byproducts released into the air include particulate matter, nitrogen oxides and sulphur dioxide. Exposure to fine particulate matter is associated with increased risk of mortality. This scoping review will examine and summarise the current literature on the health risks of exposure to air pollution in areas in which coal-fired power plants exist. METHODS AND ANALYSIS This scoping review will be conducted according to the Joanna Briggs Institute methodological framework and reported in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews guidelines. Five electronic databases (PubMed, ScienceDirect, Scopus, Web of Science and Google Scholar) will be searched for relevant articles. Studies will be included up until 31 January 2024. There will be no restriction on geographical area. The searches will be limited to studies published in English. Title, abstract, full-text screening and data extraction of relevant articles will be done by two independent reviewers. Discrepancies will be resolved by group discussion. The findings will be presented in tables with a narrative summary. This review will consider epidemiological studies and grey literature that report on the health risks of exposure to air pollution in areas where coal-fired power plants exist. ETHICS AND DISSEMINATION All data will be collected from published and grey literature. Ethics approval is therefore not required. We will submit our findings for publication in a peer-reviewed journal.
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Affiliation(s)
- Nomfundo Mahlangeni
- Environment and Health Research Unit, South African Medical Research Council, Cape Town, South Africa
- Department of Environmental Health, University of Johannesburg - Doornfontein Campus, Johannesburg, South Africa
| | - Thandi Kapwata
- Environment and Health Research Unit, South African Medical Research Council, Johannesburg, South Africa
- Department of Environmental Health, University of Johannesburg - Doornfontein Campus, Johannesburg, South Africa
| | - Tracey Laban
- Environment and Health Research Unit, South African Medical Research Council, Pretoria, South Africa
- Department of Environmental Health, University of Johannesburg - Doornfontein Campus, Johannesburg, South Africa
| | - Caradee Yael Wright
- Environment and Health Research Unit, South African Medical Research Council, Pretoria, South Africa
- Department of Geography, Geoinformatics and Meteorology, University of Pretoria, Pretoria, South Africa
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Aubourg MA, Sawtell G, Deanes L, Fabricant N, Thomas M, Spicer K, Wagar C, Campbell S, Ulman A, Heaney CD. Community-driven research and capacity building to address environmental justice concerns with industrial air pollution in Curtis Bay, South Baltimore. FRONTIERS IN EPIDEMIOLOGY 2023; 3:1198321. [PMID: 38099060 PMCID: PMC10720608 DOI: 10.3389/fepid.2023.1198321] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/01/2023] [Accepted: 07/20/2023] [Indexed: 12/17/2023]
Abstract
Introduction Curtis Bay (CB) is an environmental justice (EJ) community in South Baltimore. With a high concentration of industrial polluters and compounding non-chemical stressors, CB has experienced socioeconomic, quality of life, and health burdens for over 100 years. Today, these polluters include the open-air CSX Coal Terminal, waste-to-energy incinerators, and heavy diesel traffic through residential areas. The Community of Curtis Bay Association, Free Your Voice, and South Baltimore Community Land Trust are local organizations enacting a vision for equitable, healthy, and community-led development without industrial encroachment. In response to community-identified EJ concerns and an explosion at the CSX Coal Terminal, CB community groups partnered with academic researchers to develop a community-driven hyperlocal air monitoring and capacity building approach. This paper describes this approach to characterizing hyperlocal air quality in CB, building bridges between community residents and regulatory agencies, and nurturing a cohesive and effective community-academic partnership toward EJ. Methods Using hyperlocal air monitoring, we are collecting real-time air pollution (particulate matter, black carbon, and ground-level gas species) and meteorological data from 15 low-cost sensors in residential and industrial areas of CB. We also use trail cameras to record activities at the CSX Coal Terminal. We merge air pollution and industrial activity data to evaluate the following: overall air quality in CB, multi-air pollutant profiles of elevated events, spatiotemporal changes in air quality in the community, patterns of industrial activity, and potential correlations between air quality and observed industrial activity. Members of our partnership also lead a high school course educating students about the history and ongoing efforts of the EJ movement in their community. Students in this course learn how to employ qualitative and quantitative data collection and analysis methods to bring scientific support to community EJ concerns. Results and Discussion Our hyperlocal air monitoring network and community-academic partnership are continuing to evolve and have already demonstrated the ability to respond to community-identified EJ issues with real-time data while developing future EJ leaders. Our reflections can assist other community and academic groups in developing strong and fruitful partnerships to address similar EJ issues.
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Affiliation(s)
- Matthew A. Aubourg
- Community Science and Innovation for Environmental Justice (CSI EJ) Initiative, Center for a Livable Future, Department of Environmental Health and Engineering, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, United States
| | - Greg Sawtell
- Community of Curtis Bay Association, Curtis Bay, Baltimore, MD, United States
- South Baltimore Community Land Trust, Curtis Bay, Baltimore, MD, United States
| | - Lauren Deanes
- Community Science and Innovation for Environmental Justice (CSI EJ) Initiative, Center for a Livable Future, Department of Environmental Health and Engineering, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, United States
| | - Nicole Fabricant
- Department of Anthropology, Sociology, and Criminal Justice, Towson University, Towson, MD, United States
| | - Meleny Thomas
- Community of Curtis Bay Association, Curtis Bay, Baltimore, MD, United States
- South Baltimore Community Land Trust, Curtis Bay, Baltimore, MD, United States
| | - Kristoffer Spicer
- Community Science and Innovation for Environmental Justice (CSI EJ) Initiative, Center for a Livable Future, Department of Environmental Health and Engineering, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, United States
| | - Caila Wagar
- Community Science and Innovation for Environmental Justice (CSI EJ) Initiative, Center for a Livable Future, Department of Environmental Health and Engineering, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, United States
| | - Shashawnda Campbell
- Community of Curtis Bay Association, Curtis Bay, Baltimore, MD, United States
- South Baltimore Community Land Trust, Curtis Bay, Baltimore, MD, United States
| | - Abigail Ulman
- Community Science and Innovation for Environmental Justice (CSI EJ) Initiative, Center for a Livable Future, Department of Environmental Health and Engineering, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, United States
| | - Christopher D. Heaney
- Community Science and Innovation for Environmental Justice (CSI EJ) Initiative, Center for a Livable Future, Department of Environmental Health and Engineering, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, United States
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, United States
- Department of International Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, United States
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León-Mejía G, Rueda RA, Pérez Pérez J, Miranda-Guevara A, Moreno OF, Quintana-Sosa M, Trindade C, De Moya YS, Ruiz-Benitez M, Lemus YB, Rodríguez IL, Oliveros-Ortiz L, Acosta-Hoyos A, Pacheco-Londoño LC, Muñoz A, Hernández-Rivera SP, Olívero-Verbel J, da Silva J, Henriques JAP. Analysis of the cytotoxic and genotoxic effects in a population chronically exposed to coal mining residues. ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH INTERNATIONAL 2023; 30:54095-54105. [PMID: 36869947 PMCID: PMC10119205 DOI: 10.1007/s11356-023-26136-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 08/19/2022] [Accepted: 02/21/2023] [Indexed: 06/18/2023]
Abstract
During coal mining activities, many compounds are released into the environment that can negatively impact human health. Particulate matter, polycyclic aromatic hydrocarbons (PAHs), metals, and oxides are part of the complex mixture that can affect nearby populations. Therefore, we designed this study to evaluate the potential cytotoxic and genotoxic effects in individuals chronically exposed to coal residues from peripheral blood lymphocytes and buccal cells. We recruited 150 individuals who lived more than 20 years in La Loma-Colombia and 120 control individuals from the city of Barranquilla without a history of exposure to coal mining. In the cytokinesis-block micronucleus cytome (CBMN-Cyt) assay, significant differences in the frequency of micronucleus (MN), nucleoplasmic bridge (NPB), nuclear bud (NBUD), and apoptotic cells (APOP) were observed between the two groups. In the buccal micronucleus cytome (BM-Cyt) assay, a significant formation of NBUD, karyorrhexis (KRX), karyolysis (KRL), condensed chromatin (CC), and binucleated (BN) cells was observed in the exposed group. Considering the characteristics of the study group, a significant correlation for CBMN-Cyt was found between NBUD and vitamin consumption, between MN or APOP and meat consumption, and between MN and age. Moreover, a significant correlation for BM-Cyt was found between KRL and vitamin consumption or age, and BN versus alcohol consumption. Using Raman spectroscopy, a significant increase in the concentration of DNA/RNA bases, creatinine, polysaccharides, and fatty acids was detected in the urine of individuals exposed to coal mining compared to the control group. These results contribute to the discussion on the effects of coal mining on nearby populations and the development of diseases due to chronic exposure to these residues.
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Affiliation(s)
- Grethel León-Mejía
- Centro de Investigaciones en Ciencias de La Vida (CICV), Universidad Simón Bolívar, Cra 53 Calle 64-51, 080002, Barranquilla, Colombia.
| | - Robinson Alvarez Rueda
- Centro de Investigaciones en Ciencias de La Vida (CICV), Universidad Simón Bolívar, Cra 53 Calle 64-51, 080002, Barranquilla, Colombia
| | - Jose Pérez Pérez
- Centro de Investigaciones en Ciencias de La Vida (CICV), Universidad Simón Bolívar, Cra 53 Calle 64-51, 080002, Barranquilla, Colombia
| | - Alvaro Miranda-Guevara
- Centro de Investigaciones en Ciencias de La Vida (CICV), Universidad Simón Bolívar, Cra 53 Calle 64-51, 080002, Barranquilla, Colombia
| | - Ornella Fiorillo Moreno
- Centro de Investigaciones en Ciencias de La Vida (CICV), Universidad Simón Bolívar, Cra 53 Calle 64-51, 080002, Barranquilla, Colombia
| | - Milton Quintana-Sosa
- Centro de Investigaciones en Ciencias de La Vida (CICV), Universidad Simón Bolívar, Cra 53 Calle 64-51, 080002, Barranquilla, Colombia
| | - Cristiano Trindade
- Centro de Investigaciones en Ciencias de La Vida (CICV), Universidad Simón Bolívar, Cra 53 Calle 64-51, 080002, Barranquilla, Colombia
| | - Yurina Sh De Moya
- Centro de Investigaciones en Ciencias de La Vida (CICV), Universidad Simón Bolívar, Cra 53 Calle 64-51, 080002, Barranquilla, Colombia
| | - Martha Ruiz-Benitez
- Centro de Investigaciones en Ciencias de La Vida (CICV), Universidad Simón Bolívar, Cra 53 Calle 64-51, 080002, Barranquilla, Colombia
| | - Yesit Bello Lemus
- Centro de Investigaciones en Ciencias de La Vida (CICV), Universidad Simón Bolívar, Cra 53 Calle 64-51, 080002, Barranquilla, Colombia
| | - Ibeth Luna Rodríguez
- Centro de Investigaciones en Ciencias de La Vida (CICV), Universidad Simón Bolívar, Cra 53 Calle 64-51, 080002, Barranquilla, Colombia
| | - Ludis Oliveros-Ortiz
- Centro de Investigaciones en Ciencias de La Vida (CICV), Universidad Simón Bolívar, Cra 53 Calle 64-51, 080002, Barranquilla, Colombia
| | - Antonio Acosta-Hoyos
- Centro de Investigaciones en Ciencias de La Vida (CICV), Universidad Simón Bolívar, Cra 53 Calle 64-51, 080002, Barranquilla, Colombia
| | - Leonardo C Pacheco-Londoño
- Centro de Investigaciones en Ciencias de La Vida (CICV), Universidad Simón Bolívar, Cra 53 Calle 64-51, 080002, Barranquilla, Colombia
| | - Amner Muñoz
- Grupo de Investigación en Química Y Biología, Universidad del Norte, Barranquilla, Colombia
| | - Samuel P Hernández-Rivera
- ALERT DHS Center of Excellence for Explosives Research, Department of Chemistry, University of Puerto Rico, Mayagüez, PR, 00681, USA
| | - Jesús Olívero-Verbel
- Environmental and Computational Chemistry Group, School of Pharmaceutical Sciences, Zaragocilla Campus, University of Cartagena, Cartagena, Colombia
| | - Juliana da Silva
- Laboratório de Genética Toxicológica, Universidade Luterana Do Brasil (ULBRA), Canoas-RS, Brazil
| | - João Antonio Pêgas Henriques
- Departamento de Biofísica, Centro de Biotecnologia, Universidade Federal Do Rio Grande Do Sul (UFRGS), Porto Alegre, RS, Brazil
- Programa de Pós-Graduação Em Biotecnologia E Em Ciências Médicas, Universidade Do Vale Do Taquari - UNIVATES, Lajeado, RS, Brazil
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Cheng I, Yang J, Tseng C, Wu J, Shariff-Marco S, Park SSL, Conroy SM, Inamdar PP, Fruin S, Larson T, Setiawan VW, DeRouen MC, Gomez SL, Wilkens LR, Le Marchand L, Stram DO, Samet J, Ritz B, Wu AH. Traffic-related Air Pollution and Lung Cancer Incidence: The California Multiethnic Cohort Study. Am J Respir Crit Care Med 2022; 206:1008-1018. [PMID: 35649154 PMCID: PMC9801994 DOI: 10.1164/rccm.202107-1770oc] [Citation(s) in RCA: 20] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/28/2021] [Accepted: 05/31/2022] [Indexed: 01/07/2023] Open
Abstract
Rationale: Although the contribution of air pollution to lung cancer risk is well characterized, few studies have been conducted in racially, ethnically, and socioeconomically diverse populations. Objectives: To examine the association between traffic-related air pollution and risk of lung cancer in a racially, ethnically, and socioeconomically diverse cohort. Methods: Among 97,288 California participants of the Multiethnic Cohort Study, we used Cox proportional hazards regression to examine associations between time-varying traffic-related air pollutants (gaseous and particulate matter pollutants and regional benzene) and lung cancer risk (n = 2,796 cases; average follow-up = 17 yr), adjusting for demographics, lifetime smoking, occupation, neighborhood socioeconomic status (nSES), and lifestyle factors. Subgroup analyses were conducted for race, ethnicity, nSES, and other factors. Measurements and Main Results: Among all participants, lung cancer risk was positively associated with nitrogen oxide (hazard ratio [HR], 1.15 per 50 ppb; 95% confidence interval [CI], 0.99-1.33), nitrogen dioxide (HR, 1.12 per 20 ppb; 95% CI, 0.95-1.32), fine particulate matter with aerodynamic diameter <2.5 μm (HR, 1.20 per 10 μg/m3; 95% CI, 1.01-1.43), carbon monoxide (HR, 1.29 per 1,000 ppb; 95% CI, 0.99-1.67), and regional benzene (HR, 1.17 per 1 ppb; 95% CI, 1.02-1.34) exposures. These patterns of associations were driven by associations among African American and Latino American groups. There was no formal evidence for heterogeneity of effects by nSES (P heterogeneity > 0.21), although participants residing in low-SES neighborhoods had increased lung cancer risk associated with nitrogen oxides, and no association was observed among those in high-SES neighborhoods. Conclusions: These findings in a large multiethnic population reflect an association between lung cancer and the mixture of traffic-related air pollution and not a particular individual pollutant. They are consistent with the adverse effects of air pollution that have been described in less racially, ethnically, and socioeconomically diverse populations. Our results also suggest an increased risk of lung cancer among those residing in low-SES neighborhoods.
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Affiliation(s)
- Iona Cheng
- Department of Epidemiology and Biostatistics, University of California, San Francisco, San Francisco, California
- University of California, San Francisco Helen Diller Family Comprehensive Cancer Center, San Francisco, California
| | - Juan Yang
- Department of Epidemiology and Biostatistics, University of California, San Francisco, San Francisco, California
| | - Chiuchen Tseng
- Department of Preventive Medicine, Keck School of Medicine, University of Southern California, Los Angeles, California
| | - Jun Wu
- Department of Environmental and Occupational Health, Program in Public Health, Susan and Henry Samueli College of Health Sciences, University of California, Irvine, Irvine, California
| | - Salma Shariff-Marco
- Department of Epidemiology and Biostatistics, University of California, San Francisco, San Francisco, California
- University of California, San Francisco Helen Diller Family Comprehensive Cancer Center, San Francisco, California
| | - Sung-shim Lani Park
- Population Sciences in the Pacific Program (Cancer Epidemiology), University of Hawaii Cancer Center, Honolulu, Hawaii
| | - Shannon M. Conroy
- Department of Public Health Sciences, School of Medicine, University of California, Davis, Davis, California
| | - Pushkar P. Inamdar
- Department of Epidemiology and Biostatistics, University of California, San Francisco, San Francisco, California
| | - Scott Fruin
- Department of Preventive Medicine, Keck School of Medicine, University of Southern California, Los Angeles, California
| | - Timothy Larson
- Department of Civil and Environmental Engineering, University of Washington, Seattle, Washington
| | - Veronica W. Setiawan
- Department of Preventive Medicine, Keck School of Medicine, University of Southern California, Los Angeles, California
| | - Mindy C. DeRouen
- Department of Epidemiology and Biostatistics, University of California, San Francisco, San Francisco, California
- University of California, San Francisco Helen Diller Family Comprehensive Cancer Center, San Francisco, California
| | - Scarlett Lin Gomez
- Department of Epidemiology and Biostatistics, University of California, San Francisco, San Francisco, California
- University of California, San Francisco Helen Diller Family Comprehensive Cancer Center, San Francisco, California
| | - Lynne R. Wilkens
- Population Sciences in the Pacific Program (Cancer Epidemiology), University of Hawaii Cancer Center, Honolulu, Hawaii
| | - Loïc Le Marchand
- Population Sciences in the Pacific Program (Cancer Epidemiology), University of Hawaii Cancer Center, Honolulu, Hawaii
| | - Daniel O. Stram
- Department of Preventive Medicine, Keck School of Medicine, University of Southern California, Los Angeles, California
| | - Jonathan Samet
- Department of Epidemiology and
- Department of Environmental and Occupational Health, Colorado School of Public Health, Aurora, Colorado; and
| | - Beate Ritz
- Department of Epidemiology, School of Public Health, University of California, Los Angeles, Los Angeles, California
| | - Anna H. Wu
- Department of Preventive Medicine, Keck School of Medicine, University of Southern California, Los Angeles, California
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8
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den Braver NR, Lakerveld J, Gozdyra P, van de Brug T, Moin JS, Fazli GS, Rutters F, Brug J, Moineddin R, Beulens JWJ, Booth GL. Development of a neighborhood drivability index and its association with transportation behavior in Toronto. ENVIRONMENT INTERNATIONAL 2022; 163:107182. [PMID: 35306254 DOI: 10.1016/j.envint.2022.107182] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/16/2021] [Revised: 03/08/2022] [Accepted: 03/09/2022] [Indexed: 06/14/2023]
Abstract
BACKGROUND Car driving is a form of passive transport that is associated with an increase in physical inactivity, obesity, air pollution and noise. Built environment characteristics may influence transport mode choice, but comprehensive indices for built environment characteristics that drive car use are still lacking, while such an index could provide tangible policy entry points. OBJECTIVE We developed and validated a neighbourhood drivability index, capturing combined dimensions of the neighbourhood environment in the City of Toronto, and investigated its association with transportation choices (car, public transit or active transport), overall, by trip length, and combined for residential neighbourhood and workplace drivability. METHODS We used exploratory factor analysis to derive distinct factors (clusters of one or more environmental characteristics) that reflect the degree of car dependency in each neighbourhood, drawing from candidate variables that capture density, diversity, design, destination accessibility, distance to transit, and demand management. Area-level factor scores were then combined into a single composite score, reflecting neighbourhood drivability. Negative binomial generalized estimating equations were used to test the association between driveability quintiles (Q) and primary travel mode (>50% of trips by car, public transit, or walking/cycling) in a population-based sample of 63,766 Toronto residents enrolled in the Transportation Tomorrow Survey (TTS) wave 2016, adjusting for individual and household characteristics, and accounting for clustering of respondents within households. RESULTS The drivability index consisted of three factors: Urban sprawl, pedestrian facilities and parking availability. Relative to those living in the least drivable neighbourhoods (Q1), those in high drivability areas (Q5) had a significantly higher rate of car travel (adjusted Risk Ratio (RR): 1.80, 95%CI: 1.77-1.88), and lower rate of public transit use (RR: 0.90, 95%CI: 0.85-0.94) and walking/cycling (RR: 0.22, 95%CI: 0.19-0.25). Associations were strongest for short trips (<3 km) (RR: 2.72, 95%CI: 2.48-2.92), and in analyses where both residential and workplace drivability was considered (RR for car use in high/high vs. low/low residential/workplace drivability: 2.18, 95%CI: 2.08-2.29). CONCLUSION This novel neighbourhood drivability index predicted whether local residents drive or use active modes of transportation and can be used to investigate the association between drivability, physical activity, and chronic disease risk.
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Affiliation(s)
- Nicolette R den Braver
- Amsterdam UMC, Vrije Universiteit Amsterdam, Department of Epidemiology and Data Science, Amsterdam Public Health Research Institute, Amsterdam, the Netherlands; Upstream Team, www.upstreamteam.nl, Amsterdam, the Netherlands.
| | - Jeroen Lakerveld
- Amsterdam UMC, Vrije Universiteit Amsterdam, Department of Epidemiology and Data Science, Amsterdam Public Health Research Institute, Amsterdam, the Netherlands
| | - Peter Gozdyra
- MAP Centre for Urban Health Solutions, Li Ka Shing Knowledge Institute, St. Michael's Hospital, Toronto, Canada; ICES, Toronto, Canada
| | - Tim van de Brug
- Amsterdam UMC, Vrije Universiteit Amsterdam, Department of Epidemiology and Data Science, Amsterdam Public Health Research Institute, Amsterdam, the Netherlands
| | - John S Moin
- MAP Centre for Urban Health Solutions, Li Ka Shing Knowledge Institute, St. Michael's Hospital, Toronto, Canada
| | - Ghazal S Fazli
- MAP Centre for Urban Health Solutions, Li Ka Shing Knowledge Institute, St. Michael's Hospital, Toronto, Canada
| | - Femke Rutters
- Amsterdam UMC, Vrije Universiteit Amsterdam, Department of Epidemiology and Data Science, Amsterdam Public Health Research Institute, Amsterdam, the Netherlands
| | - Johannes Brug
- National Institute for Public Health and the Environment, Bilthoven, the Netherlands; Faculty of Social and Behavioural Sciences, University of Amsterdam, Amsterdam, the Netherlands
| | - Rahim Moineddin
- ICES, Toronto, Canada; Department of Family and Community Medicine, Faculty of Medicine, University of Toronto, Toronto, Canada
| | - Joline W J Beulens
- Amsterdam UMC, Vrije Universiteit Amsterdam, Department of Epidemiology and Data Science, Amsterdam Public Health Research Institute, Amsterdam, the Netherlands; Upstream Team, www.upstreamteam.nl, Amsterdam, the Netherlands; Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht, the Netherlands
| | - Gillian L Booth
- MAP Centre for Urban Health Solutions, Li Ka Shing Knowledge Institute, St. Michael's Hospital, Toronto, Canada; ICES, Toronto, Canada; Department of Medicine, University of Toronto, Canada; Institute of Health Policy, Management and Evaluation, University of Toronto, Canada
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9
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Chio CP, Lo WC, Tsuang BJ, Hu CC, Ku KC, Wang YS, Chen YJ, Lin HH, Chan CC. County-Wide Mortality Assessments Attributable to PM 2.5 Emissions from Coal Consumption in Taiwan. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2022; 19:1599. [PMID: 35162624 PMCID: PMC8835574 DOI: 10.3390/ijerph19031599] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 12/15/2021] [Revised: 01/19/2022] [Accepted: 01/28/2022] [Indexed: 12/10/2022]
Abstract
Over one-third of energy is generated from coal consumption in Taiwan. In order to estimate the health impact assessment attributable to PM2.5 concentrations emitted from coal consumption in Taiwan. We applied a Gaussian trajectory transfer-coefficient model to obtain county-wide PM2.5 exposures from coal consumption, which includes coal-fired power plants and combined heat and power plants. Next, we calculated the mortality burden attributable to PM2.5 emitted by coal consumption using the comparative risk assessment framework developed by the Global Burden of Disease study. Based on county-level data, the average PM2.5 emissions from coal-fired plants in Taiwan was estimated at 2.03 ± 1.29 (range: 0.32-5.64) μg/m3. With PM2.5 increments greater than 0.1 μg/m3, there were as many as 16 counties and 66 air quality monitoring stations affected by coal-fired plants and 6 counties and 18 monitoring stations affected by combined heat and power plants. The maximum distances affected by coal-fired and combined heat and power plants were 272 km and 157 km, respectively. Our findings show that more counties were affected by coal-fired plants than by combined heat and power plants with significant increments of PM2.5 emissions. We estimated that 359.6 (95% CI: 334.8-384.9) annual adult deaths and 124.4 (95% CI: 116.4-132.3) annual premature deaths were attributable to PM2.5 emitted by coal-fired plants in Taiwan. Even in six counties without power plants, there were 75.8 (95% CI: 60.1-91.5) deaths and 25.8 (95%CI: 20.7-30.9) premature deaths annually attributable to PM2.5 emitted from neighboring coal-fired plants. This study presents a precise and effective integrated approach for assessing air pollution and the health impacts of coal-fired and combined heat and power plants.
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Affiliation(s)
- Chia-Pin Chio
- Innovation and Policy Center for Population Health and Sustainable Environment, College of Public Health, National Taiwan University, Taipei 10055, Taiwan;
- Institute of Environmental and Occupational Health Science, College of Public Health, National Taiwan University, Taipei 10055, Taiwan
| | - Wei-Cheng Lo
- Graduate Institute of Epidemiology and Preventive Medicine, College of Public Health, National Taiwan University, Taipei 10055, Taiwan; (W.-C.L.); (C.-C.H.)
- Institute of Statistical Science, Academia Sinica, Taipei 11529, Taiwan
- Master Program in Applied Epidemiology, College of Public Health, Taipei Medical University, Taipei 11031, Taiwan
| | - Ben-Jei Tsuang
- Department of Environmental Engineering, Innovation and Development Center of Sustainable Agriculture (IDCSA), National Chung-Hsing University, Taichung 40227, Taiwan; (B.-J.T.); (K.-C.K.); (Y.-S.W.)
| | - Chieh-Chun Hu
- Graduate Institute of Epidemiology and Preventive Medicine, College of Public Health, National Taiwan University, Taipei 10055, Taiwan; (W.-C.L.); (C.-C.H.)
| | - Kai-Chen Ku
- Department of Environmental Engineering, Innovation and Development Center of Sustainable Agriculture (IDCSA), National Chung-Hsing University, Taichung 40227, Taiwan; (B.-J.T.); (K.-C.K.); (Y.-S.W.)
| | - Yi-Sheng Wang
- Department of Environmental Engineering, Innovation and Development Center of Sustainable Agriculture (IDCSA), National Chung-Hsing University, Taichung 40227, Taiwan; (B.-J.T.); (K.-C.K.); (Y.-S.W.)
| | | | - Hsien-Ho Lin
- Innovation and Policy Center for Population Health and Sustainable Environment, College of Public Health, National Taiwan University, Taipei 10055, Taiwan;
- Graduate Institute of Epidemiology and Preventive Medicine, College of Public Health, National Taiwan University, Taipei 10055, Taiwan; (W.-C.L.); (C.-C.H.)
| | - Chang-Chuan Chan
- Innovation and Policy Center for Population Health and Sustainable Environment, College of Public Health, National Taiwan University, Taipei 10055, Taiwan;
- Institute of Environmental and Occupational Health Science, College of Public Health, National Taiwan University, Taipei 10055, Taiwan
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10
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Zhang CH, Sears L, Myers JV, Brock GN, Sears CG, Zierold KM. Proximity to coal-fired power plants and neurobehavioral symptoms in children. JOURNAL OF EXPOSURE SCIENCE & ENVIRONMENTAL EPIDEMIOLOGY 2022; 32:124-134. [PMID: 34257388 PMCID: PMC8275639 DOI: 10.1038/s41370-021-00369-7] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/09/2020] [Revised: 06/30/2021] [Accepted: 07/01/2021] [Indexed: 05/15/2023]
Abstract
BACKGROUND Coal-fired power plants are a major source of air pollution that can impact children's health. Limited research has explored if proximity to coal-fired power plants contributes to children's neurobehavioral disorders. OBJECTIVE This community-based study collected primary data to investigate the relationships of residential proximity to power plants and neurobehavioral problems in children. METHODS 235 participants aged 6-14 years who lived within 10 miles of two power plants were recruited. Exposure to particulate matter ≤10 μm (PM10) was measured in children's homes using personal modular impactors. Neurobehavioral symptoms were assessed using the Child Behavior Checklist (CBCL). Multiple regression models were performed to test the hypothesized associations between proximity/exposure and neurobehavioral symptoms. Geospatial statistical methods were used to map the spatial patterns of exposure and neurobehavioral symptoms. RESULTS A small proportion of the variations of neurobehavioral problems (social problems, affective problems, and anxiety problems) were explained by the regression models in which distance to power plants, traffic proximity, and neighborhood poverty was statistically associated with the neurobehavioral health outcomes. Statistically significant hot spots of participants who had elevated levels of attention deficit hyperactivity disorder, anxiety, and social problems were observed in the vicinity of the two power plants. SIGNIFICANCE Results of this study suggest an adverse impact of proximity to power plants on children's neurobehavioral health. Although coal-fired power plants are being phased out in the US, health concern about exposure from coal ash storage facilities remains. Furthermore, other countries in the world are increasing coal use and generating millions of tons of pollutants and coal ash. Findings from this study can inform public health policies to reduce children's risk of neurobehavioral symptoms in relation to proximity to power plants.
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Affiliation(s)
- Charlie H Zhang
- Department of Geography & Geosciences, University of Louisville, Louisville, KY, USA
| | - Lonnie Sears
- Department of Pediatrics, University of Louisville, Louisville, KY, USA
| | - John V Myers
- Department of Biomedical Informatics and Center for Biostatistics, The Ohio State University, Columbus, OH, USA
| | - Guy N Brock
- Department of Biomedical Informatics and Center for Biostatistics, The Ohio State University, Columbus, OH, USA
| | - Clara G Sears
- Department of Epidemiology, Brown University, Providence, RI, USA
| | - Kristina M Zierold
- Department of Environmental Health Sciences, University of Alabama at Birmingham, Birmingham, AL, USA.
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11
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Kumar A, Patel VS, Harding JN, You D, Cormier SA. Exposure to combustion derived particulate matter exacerbates influenza infection in neonatal mice by inhibiting IL22 production. Part Fibre Toxicol 2021; 18:43. [PMID: 34906172 PMCID: PMC8670221 DOI: 10.1186/s12989-021-00438-7] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/08/2021] [Accepted: 11/29/2021] [Indexed: 01/05/2023] Open
Abstract
Background Particulate matter (PM) containing environmentally persistent free radicals (EPFRs) are formed during various combustion processes, including the thermal remediation of hazardous wastes. Exposure to PM adversely affects respiratory health in infants and is associated with increased morbidity and mortality due to acute lower respiratory tract infections. We previously reported that early-life exposure to PM damages the lung epithelium and suppresses immune responses to influenza virus (Flu) infection, thereby enhancing Flu severity. Interleukin 22 (IL22) is important in resolving lung injury following Flu infection. In the current study, we determined the effects of PM exposure on pulmonary IL22 responses using our neonatal mouse model of Flu infection. Results Exposure to PM resulted in an immediate (0.5–1-day post-exposure; dpe) increase in IL22 expression in the lungs of C57BL/6 neonatal mice; however, this IL22 expression was not maintained and failed to increase with either continued exposure to PM or subsequent Flu infection of PM-exposed mice. This contrasts with increased IL22 expression in age-matched mice exposed to vehicle and Flu infected. Activation of the aryl hydrocarbon receptor (AhR), which mediates the induction and release of IL22 from immune cells, was also transiently increased with PM exposure. The microbiome plays a major role in maintaining epithelial integrity and immune responses by producing various metabolites that act as ligands for AhR. Exposure to PM induced lung microbiota dysbiosis and altered the levels of indole, a microbial metabolite. Treatment with recombinant IL22 or indole-3-carboxaldehyde (I3A) prevented PM associated lung injury. In addition, I3A treatment also protected against increased mortality in Flu-infected mice exposed to PMs. Conclusions Together, these data suggest that exposure to PMs results in failure to sustain IL22 levels and an inability to induce IL22 upon Flu infection. Insufficient levels of IL22 may be responsible for aberrant epithelial repair and immune responses, leading to increased Flu severity in areas of high PM.
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Affiliation(s)
- Avinash Kumar
- Department of Biological Sciences, Louisiana State University, Baton Rouge, LA, USA.,Pennington Biomedical Research Center, 6400 Perkins Road, Baton Rouge, LA, USA
| | - Vivek S Patel
- Department of Biological Sciences, Louisiana State University, Baton Rouge, LA, USA
| | - Jeffrey N Harding
- Department of Biological Sciences, Louisiana State University, Baton Rouge, LA, USA
| | - Dahui You
- Department of Pediatrics, University of Tennessee Health Sciences Center, Memphis, TN, USA
| | - Stephania A Cormier
- Department of Biological Sciences, Louisiana State University, Baton Rouge, LA, USA. .,Pennington Biomedical Research Center, 6400 Perkins Road, Baton Rouge, LA, USA.
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12
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Pakpour AH, Lin CK, Safdari M, Lin CY, Chen SH, Hamilton K. Using an Integrated Social Cognition Model to Explain Green Purchasing Behavior among Adolescents. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2021; 18:ijerph182312663. [PMID: 34886395 PMCID: PMC8656670 DOI: 10.3390/ijerph182312663] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 10/27/2021] [Revised: 11/27/2021] [Accepted: 11/29/2021] [Indexed: 01/03/2023]
Abstract
Strengthening pro-environmental behaviors such as green purchasing behavior is important for environmental sustainability. An integrated social cognition model which incorporates constructs from habit theory, health action process approach (HAPA), and theory of planned behavior (TPB) is adopted to understand Iranian adolescents’ green purchasing behavior. Using a correlational-prospective design, the study recruited Iranian adolescents aged between 14 and 19 years (N = 2374, n = 1362 (57.4%) females, n = 1012 (42.6%) males; Mean (SD) age = 15.56 (1.22)). At baseline (T1), participants self-reported on the following constructs: past behavior; habit strength (from habit theory); action planning and coping planning (from HAPA); and intention, perceived behavioral control, subjective norm, and attitude (from TPB) with respect to green purchasing behavior. Six months later (T2), participants self-reported on their actions in terms of purchasing green goods. Our findings reported direct effects of perceived behavioral control, subjective norms, attitude, and past behavior on intention; intention and perceived behavioral control on green purchase behavior; intention on two types of planning (i.e., action and coping planning); both types of planning on green purchase behavior; and past green purchase behavior and habits on prospectively measured green purchase behavior. These results indicate that adolescent green purchasing behavior is underpinned by constructs representing motivational, volitional, and automatic processes. This knowledge can help inform the development of theory-based behavior change interventions to improve green purchasing in adolescents, a key developmental period where climate change issues are salient and increased independence and demands in making self-guided decisions are needed.
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Affiliation(s)
- Amir H. Pakpour
- Social Determinants of Health Research Center, Research Institute for Prevention of Non-Communicable Diseases, Qazvin University of Medical Sciences, Qazvin 3419759811, Iran;
- Department of Nursing, School of Health and Welfare, Jönköping University, 55111 Jönköping, Sweden
| | - Cheng-Kuan Lin
- Department of Environmental Health, Harvard T.H. Chan School of Public Health, Boston, MA 02115, USA;
| | - Mahdi Safdari
- Department of Environmental Health Engineering, School of Medical Sciences, Tarbiat Modares University, Tehran 1411713116, Iran;
| | - Chung-Ying Lin
- Institute of Allied Health Sciences, College of Medicine, National Cheng Kung University, Tainan 701401, Taiwan
- Biostatistics Consulting Center, National Cheng Kung University Hospital, College of Medicine, National Cheng Kung University, Tainan 701401, Taiwan
- Department of Occupational Therapy, College of Medicine, National Cheng Kung University, Tainan 701401, Taiwan
- Department of Public Health, College of Medicine, National Cheng Kung University, Tainan 701401, Taiwan
- Correspondence: (C.-Y.L.); (S.-H.C.)
| | - Shun-Hua Chen
- School of Nursing, Fooyin University, Kaohsiung 83102, Taiwan
- Correspondence: (C.-Y.L.); (S.-H.C.)
| | - Kyra Hamilton
- School of Applied Psychology, Menzies Health Institute Queensland, Griffith University, Brisbane, QLD 4122, Australia;
- Health Sciences Research Institute, University of California, Merced, CA 95343, USA
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13
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Wang X, Hu W, Zhang S, Kang N, Wang H, Dong Y, Bian H, Meng Y. Occupational Dust Hazards and Risk Assessment of Coal-Fired Thermal Power Plants of Different Capacities - China, 2017-2019. China CDC Wkly 2021; 3:901-905. [PMID: 34745688 PMCID: PMC8563332 DOI: 10.46234/ccdcw2021.221] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/09/2021] [Accepted: 10/19/2021] [Indexed: 01/02/2023] Open
Abstract
What is already known about this topic? Silica dust and coal dust are the main occupational hazards in coal-fired thermal power plants, which mainly exist in coal transportation workplaces, combustion milling workplaces, and ash removal workplaces. What is added by this report? The overall environmental and personal dust exposure levels decrease with an increase in the capacity of coal-fired thermal power plants, the overall dust hazard risk level of the workforce in coal-fired is Medium. What are the implications for public health practice? Dust management should be conducted in the coal-fired thermal power plant in 300 million watt units because it has the highest dust exposure level, and ash removal workplaces and combustion milling workplaces are key control points for dust hazards.
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Affiliation(s)
- Xin Wang
- National Institute of Occupational Health and Poison Control, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Weijiang Hu
- National Institute of Occupational Health and Poison Control, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Siyu Zhang
- National Institute of Occupational Health and Poison Control, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Ning Kang
- National Institute of Occupational Health and Poison Control, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Hongfei Wang
- National Institute of Occupational Health and Poison Control, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Yiwen Dong
- National Institute of Occupational Health and Poison Control, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Hongying Bian
- National Institute of Occupational Health and Poison Control, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Ye Meng
- National Institute of Occupational Health and Poison Control, Chinese Center for Disease Control and Prevention, Beijing, China
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Bikomeye JC, Namin S, Anyanwu C, Rublee CS, Ferschinger J, Leinbach K, Lindquist P, Hoppe A, Hoffman L, Hegarty J, Sperber D, Beyer KMM. Resilience and Equity in a Time of Crises: Investing in Public Urban Greenspace Is Now More Essential Than Ever in the US and Beyond. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2021; 18:8420. [PMID: 34444169 PMCID: PMC8392137 DOI: 10.3390/ijerph18168420] [Citation(s) in RCA: 21] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 06/10/2021] [Revised: 07/31/2021] [Accepted: 08/01/2021] [Indexed: 01/14/2023]
Abstract
The intersecting negative effects of structural racism, COVID-19, climate change, and chronic diseases disproportionately affect racial and ethnic minorities in the US and around the world. Urban populations of color are concentrated in historically redlined, segregated, disinvested, and marginalized neighborhoods with inadequate quality housing and limited access to resources, including quality greenspaces designed to support natural ecosystems and healthy outdoor activities while mitigating urban environmental challenges such as air pollution, heat island effects, combined sewer overflows and poor water quality. Disinvested urban environments thus contribute to health inequity via physical and social environmental exposures, resulting in disparities across numerous health outcomes, including COVID-19 and chronic diseases such as cancer and cardiovascular diseases (CVD). In this paper, we build off an existing conceptual framework and propose another conceptual framework for the role of greenspace in contributing to resilience and health equity in the US and beyond. We argue that strategic investments in public greenspaces in urban neighborhoods impacted by long term economic disinvestment are critically needed to adapt and build resilience in communities of color, with urgency due to immediate health threats of climate change, COVID-19, and endemic disparities in chronic diseases. We suggest that equity-focused investments in public urban greenspaces are needed to reduce social inequalities, expand economic opportunities with diversity in workforce initiatives, build resilient urban ecosystems, and improve health equity. We recommend key strategies and considerations to guide this investment, drawing upon a robust compilation of scientific literature along with decades of community-based work, using strategic partnerships from multiple efforts in Milwaukee Wisconsin as examples of success.
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Affiliation(s)
- Jean C. Bikomeye
- Institute for Health & Equity, Medical College of Wisconsin, 8701 Watertown Plank Rd., Milwaukee, WI 53226, USA; (J.C.B.); (S.N.); (C.A.)
| | - Sima Namin
- Institute for Health & Equity, Medical College of Wisconsin, 8701 Watertown Plank Rd., Milwaukee, WI 53226, USA; (J.C.B.); (S.N.); (C.A.)
| | - Chima Anyanwu
- Institute for Health & Equity, Medical College of Wisconsin, 8701 Watertown Plank Rd., Milwaukee, WI 53226, USA; (J.C.B.); (S.N.); (C.A.)
| | - Caitlin S. Rublee
- Department of Emergency Medicine, Medical College of Wisconsin, 8701 Watertown Plank Rd., Milwaukee, WI 53226, USA;
| | - Jamie Ferschinger
- Sixteenth Street Community Health Centers, Environmental Health & Community Wellness, 1337 S Cesar Chavez Drive, Milwaukee, WI 53204, USA;
| | - Ken Leinbach
- The Urban Ecology Center, 1500 E. Park Place, Milwaukee, WI 53211, USA;
| | - Patricia Lindquist
- Wisconsin Department of Natural Resources, Division of Forestry, 101 S. Webster Street, P.O. Box 7921, Madison, WI 53707, USA;
| | - August Hoppe
- The Urban Wood Lab, Hoppe Tree Service, 1813 S. 73rd Street, West Allis, WI 53214, USA;
| | - Lawrence Hoffman
- Department of GIS, Groundwork Milwaukee, 227 West Pleasant Street, Milwaukee, WI 53212, USA;
| | - Justin Hegarty
- Reflo—Sustainable Water Solutions, 1100 S 5th Street, Milwaukee, WI 53204, USA;
| | - Dwayne Sperber
- Wudeward Urban Forest Products, N11W31868 Phyllis Parkway, Delafield, WI 53018, USA;
| | - Kirsten M. M. Beyer
- Institute for Health & Equity, Medical College of Wisconsin, 8701 Watertown Plank Rd., Milwaukee, WI 53226, USA; (J.C.B.); (S.N.); (C.A.)
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15
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Energy, Data, and Decision-Making: a Scoping Review-the 3D Commission. J Urban Health 2021; 98:79-88. [PMID: 34374032 PMCID: PMC8440708 DOI: 10.1007/s11524-021-00563-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 05/07/2021] [Indexed: 10/20/2022]
Abstract
Access to energy is an important social determinant of health, and expanding the availability of affordable, clean energy is one of the Sustainable Development Goals. It has been argued that climate mitigation policies can, if well-designed in response to contextual factors, also achieve environmental, economic, and social progress, but otherwise pose risks to economic inequity generally and health inequity specifically. Decisions around such policies are hampered by data gaps, particularly in low- and middle-income countries (LMICs) and among vulnerable populations in high-income countries (HICs). The rise of "big data" offers the potential to address some of these gaps. This scoping review sought to explore the literature linking energy, big data, health, and decision-making.Literature searches in PubMed, Embase, and Web of Science were conducted. English language articles up to April 1, 2020, were included. Pre-agreed study characteristics including geographic location, data collected, and study design were extracted and presented descriptively, and a qualitative thematic analysis was performed on the articles using NVivo.Thirty-nine articles fulfilled eligibility criteria. These included a combination of review articles and research articles using primary or secondary data sources. The articles described health and economic effects of a wide range of energy types and uses, and attempted to model effects of a range of technological and policy innovations, in a variety of geographic contexts. Key themes identified in our analysis included the link between energy consumption and economic development, the role of inequality in understanding and predicting harms and benefits associated with energy production and use, the lack of available data on LMICs in general, and on the local contexts within them in particular. Examples of using "big data," and areas in which the articles themselves described challenges with data limitations, were identified.The findings of this scoping review demonstrate the challenges decision-makers face in achieving energy efficiency gains and reducing emissions, while avoiding the exacerbation of existing inequities. Understanding how to maximize gains in energy efficiency and uptake of new technologies requires a deeper understanding of how work and life is shaped by socioeconomic inequalities between and within countries. This is particularly the case for LMICs and in local contexts where few data are currently available, and for whom existing evidence may not be directly applicable. Big data approaches may offer some value in tracking the uptake of new approaches, provide greater data granularity, and help compensate for evidence gaps in low resource settings.
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Zierold KM, Myers JV, Brock GN, Sears CG, Sears LL, Zhang CH. Nail Samples of Children Living near Coal Ash Storage Facilities Suggest Fly Ash Exposure and Elevated Concentrations of Metal(loid)s. ENVIRONMENTAL SCIENCE & TECHNOLOGY 2021; 55:9074-9086. [PMID: 34132542 PMCID: PMC10725724 DOI: 10.1021/acs.est.1c01541] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/12/2023]
Abstract
Children who live near coal-fired power plants are exposed to coal fly ash, which is stored in landfills and surface impoundments near residential communities. Fly ash has the potential to be released as fugitive dust. Using data collected from 263 children living within 10 miles of coal ash storage facilities in Jefferson and Bullitt Counties, Kentucky, USA, we quantified the elements found in nail samples. Furthermore, using principal component analysis (PCA), we investigated whether metal(loid)s that are predominately found in fly ash loaded together to indicate potential exposure to fly ash. Concentrations of several neurotoxic metal(loid)s, such as chromium, manganese, and zinc, were higher than concentrations reported in other studies of both healthy and environmentally exposed children. From PCA, it was determined that iron, aluminum, and silicon in fly ash were found to load together in the nails of children living near coal ash storage facilities. These metal(loid)s were also highly correlated with each other. Last, results of geospatial analyses partially validated our hypothesis that children's proximity to power plants was associated with elevated levels of concentrations of fly ash metal(loid)s in nails. Taken together, nail samples may be a powerful tool in detecting exposure to fly ash.
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Affiliation(s)
- Kristina M Zierold
- Department of Environmental Health Sciences, University of Alabama at Birmingham, Birmingham 35294, Alabama, United States
| | - John V Myers
- Department of Biomedical Informatics and Center for Biostatistics, The Ohio State University, Columbus 43210, Ohio, United States
| | - Guy N Brock
- Department of Biomedical Informatics and Center for Biostatistics, The Ohio State University, Columbus 43210, Ohio, United States
| | - Clara G Sears
- Department of Epidemiology, Brown University, Providence 02912, Rhode Island, United States
| | - Lonnie L Sears
- Department of Pediatrics, University of Louisville, Louisville 40292, Kentucky, United States
| | - Charlie H Zhang
- Department of Geography & Geosciences, University of Louisville, Louisville 40292, Kentucky, United States
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Bălă GP, Râjnoveanu RM, Tudorache E, Motișan R, Oancea C. Air pollution exposure-the (in)visible risk factor for respiratory diseases. ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH INTERNATIONAL 2021; 28:19615-19628. [PMID: 33660184 PMCID: PMC8099844 DOI: 10.1007/s11356-021-13208-x] [Citation(s) in RCA: 57] [Impact Index Per Article: 19.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/10/2020] [Accepted: 02/24/2021] [Indexed: 04/12/2023]
Abstract
There is increasing interest in understanding the role of air pollution as one of the greatest threats to human health worldwide. Nine of 10 individuals breathe air with polluted compounds that have a great impact on lung tissue. The nature of the relationship is complex, and new or updated data are constantly being reported in the literature. The goal of our review was to summarize the most important air pollutants and their impact on the main respiratory diseases (chronic obstructive pulmonary disease, asthma, lung cancer, idiopathic pulmonary fibrosis, respiratory infections, bronchiectasis, tuberculosis) to reduce both short- and the long-term exposure consequences. We considered the most important air pollutants, including sulfur dioxide, nitrogen dioxide, carbon monoxide, volatile organic compounds, ozone, particulate matter and biomass smoke, and observed their impact on pulmonary pathologies. We focused on respiratory pathologies, because air pollution potentiates the increase in respiratory diseases, and the evidence that air pollutants have a detrimental effect is growing. It is imperative to constantly improve policy initiatives on air quality in both high- and low-income countries.
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Affiliation(s)
- Gabriel-Petrică Bălă
- Department of Pulmonology, University of Medicine and Pharmacy "Victor Babeș", P-ța Eftimie Murgu nr.2, Timișoara, 300041, Timiș, Romania
| | | | - Emanuela Tudorache
- Department of Pulmonology, University of Medicine and Pharmacy "Victor Babeș", P-ța Eftimie Murgu nr.2, Timișoara, 300041, Timiș, Romania
| | | | - Cristian Oancea
- Department of Pulmonology, University of Medicine and Pharmacy "Victor Babeș", P-ța Eftimie Murgu nr.2, Timișoara, 300041, Timiș, Romania
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18
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Zierold KM, Odoh C. A review on fly ash from coal-fired power plants: chemical composition, regulations, and health evidence. REVIEWS ON ENVIRONMENTAL HEALTH 2020; 35:401-418. [PMID: 32324165 DOI: 10.1515/reveh-2019-0039] [Citation(s) in RCA: 33] [Impact Index Per Article: 8.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/13/2019] [Accepted: 03/09/2020] [Indexed: 05/29/2023]
Abstract
Throughout the world, coal is responsible for generating approximately 38% of power. Coal ash, a waste product, generated from the combustion of coal, consists of fly ash, bottom ash, boiler slag, and flue gas desulfurization material. Fly ash, which is the main component of coal ash, is composed of spherical particulate matter with diameters that range from 0.1 μm to >100 μm. Fly ash is predominately composed of silica, aluminum, iron, calcium, and oxygen, but the particles may also contain heavy metals such as arsenic and lead at trace levels. Most nations throughout the world do not consider fly ash a hazardous waste and therefore regulations on its disposal and storage are lacking. Fly ash that is not beneficially reused in products such as concrete is stored in landfills and surface impoundments. Fugitive dust emissions and leaching of metals into groundwater from landfills and surface impoundments may put people at risk for exposure. There are limited epidemiological studies regarding the health effects of fly ash exposure. In this article, the authors provide an overview of fly ash, its chemical composition, the regulations from nations generating the greatest amount of fly ash, and epidemiological evidence regarding the health impacts associated with exposure to fly ash.
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Affiliation(s)
- Kristina M Zierold
- Environmental Health Sciences, University of Alabama at Birmingham, Birmingham, AL, USA
| | - Chisom Odoh
- Rehabilitation and Health Services, University of North Texas, Denton, TX, USA
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Saatchi M, Mansournia MA, Khalili D, Daroudi R, Yazdani K. Estimation of Generalized Impact Fraction and Population Attributable Fraction of Hypertension Based on JNC-IV and 2017 ACC/AHA Guidelines for Cardiovascular Diseases Using Parametric G-Formula: Tehran Lipid and Glucose Study (TLGS). Risk Manag Healthc Policy 2020; 13:1015-1028. [PMID: 32848484 PMCID: PMC7431169 DOI: 10.2147/rmhp.s265887] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/09/2020] [Accepted: 07/21/2020] [Indexed: 11/23/2022] Open
Abstract
Purpose An area of interest to health policymakers is the effect of interventions aimed at risk factors on decreasing the number of new cardiovascular disease (CVD) cases. The aim of this study was to estimate the generalized impact fraction (GIF) and population attributable fraction (PAF) of hypertension (HTN) for CVD in Tehran. Patients and Methods In this population-based cohort study, 8071 participants aged ≥30 years were followed for a median of 16 years. A survival model was used to estimate the 10- and 18-year risk of CVD. JNC-IV and 2017 ACC/AHA guidelines were used to categorize blood pressure (BP). PAF and GIF were estimated in different scenarios using the parametric G-formula. Results Of 7378 participants included in analyses, 22.7% and 52.3% were classified as hypertensive according to the JNC-IV and 2017 ACC/AHA guidelines, respectively. According to the 2017 ACC/AHA, the 10-year risk of CVD was 5.1% (4.3–6.0%), 8.9% (6.7–12.0%), and 7.1% (6.1–8.4%) for normal BP, elevated BP, and stage 1 HTN, respectively, and 20.8% (18.8–23.0%) for stage 2 of the 2017 ACC/AHA and JNC-IV. The PAF of stage 2 vs stage 1 and vs normal BP for CVD was 17.4% (11.5–21.8%) and 20.4% (14.6–26.4%), respectively. The GIF of 30% reduction in the prevalence of stage 2 HTN to stage 1 and to normal BP for CVD was 5.1% (3.4–6.6%) and 6.1% (4.4–8.0%), respectively. Based on JNC-IV, the PAF and GIF of 30% for CVD were 17.8% (12.7–22.9%) and 5.4% (4.0–6.9%), respectively. Conclusion By reducing the prevalence of HTN by 30%, a remarkable number of new CVD cases would be prevented. In an Iranian population, the comparison of HTN cases with normal BP showed no association between stage 1 HTN and CVD, whereas elevated BP was a significant risk factor for the incidence of CVD.
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Affiliation(s)
- Mohammad Saatchi
- Department of Epidemiology and Biostatistics, School of Public Health, Tehran University of Medical Sciences, Tehran, Iran
| | - Mohammad Ali Mansournia
- Department of Epidemiology and Biostatistics, School of Public Health, Tehran University of Medical Sciences, Tehran, Iran
| | - Davood Khalili
- Prevention of Metabolic Disorders Research Center, Research Institute for Endocrine Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran
| | - Rajabali Daroudi
- Department of Health Management and Economics, School of Public Health, Tehran University of Medical Sciences, Tehran, Iran
| | - Kamran Yazdani
- Department of Epidemiology and Biostatistics, School of Public Health, Tehran University of Medical Sciences, Tehran, Iran
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20
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Lipfert FW, Wyzga RE. Longitudinal relationships between lung cancer mortality rates, smoking, and ambient air quality: a comprehensive review and analysis. Crit Rev Toxicol 2020; 49:790-818. [DOI: 10.1080/10408444.2019.1700210] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
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21
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Lin CK, Chen ST. Estimation and application of population attributable fraction in ecological studies. Environ Health 2019; 18:52. [PMID: 31196209 PMCID: PMC6567453 DOI: 10.1186/s12940-019-0492-4] [Citation(s) in RCA: 17] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/03/2019] [Accepted: 05/21/2019] [Indexed: 05/04/2023]
Abstract
Estimation of population attributable fraction (PAF) requires unbiased relative risk (RR) by using either Levin's or Miettinen's formula, on which decision depends on the available exposure information in reference group, not the types of studies. For ecological studies and studies with aggregated outcomes, once having unbiased RRs, Levin's and Miettinen's formulae would provide identical PAF estimates. PAF could also be applied to compare relative burdens of disease between countries across time, which is an additional information in consideration of country-level policies.
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Affiliation(s)
- Cheng-Kuan Lin
- Department of Environmental Health, Harvard T.H. Chan School of Public Health, 665 Huntington Avenue, Boston, MA, 02115, USA.
| | - Szu-Ta Chen
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, 667 Huntington Avenue, Boston, MA, 02115, USA
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22
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Khosravi A, Mansournia MA. Issues with incorrect computing of population attributable fraction (PAF) in a global perspective on coal-fired power plants and burden of lung cancer. Environ Health 2019; 18:54. [PMID: 31196121 PMCID: PMC6567379 DOI: 10.1186/s12940-019-0490-6] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/12/2019] [Accepted: 05/07/2019] [Indexed: 05/21/2023]
Abstract
All observational studies are liable to confounding and Levin's formula becomes useless in practice for unbiasedly estimating PAF. With respect to causal interpretation of PAF in public health setting, unbiased estimation of PAF requires several assumptions which are ignored in practice. We recommend using Miettinen PAF formula with careful consideration about possibility of bias in study design and analysis.
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Affiliation(s)
- Ahmad Khosravi
- Department of Epidemiology, School of Public Health, Shahroud University of Medical Sciences, Shahroud, Iran
| | - Mohammad Ali Mansournia
- Department of Epidemiology and Biostatistics, Tehran University of Medical Sciences, Tehran, Iran
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