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Kentros PA, Huang Y, Wylie BJ, Khoury-Collado F, Hou JY, de Meritens AB, St Clair CM, Hershman DL, Wright JD. Ambient particulate matter air pollution exposure and ovarian cancer incidence in the USA: An ecological study. BJOG 2024; 131:690-698. [PMID: 37840233 DOI: 10.1111/1471-0528.17689] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/10/2023] [Revised: 09/09/2023] [Accepted: 09/21/2023] [Indexed: 10/17/2023]
Abstract
OBJECTIVE To investigate associations between air particulate matter of ≤2.5 μm in diameter (PM2.5 ) and ovarian cancer. DESIGN County-level ecological study. SETTING Surveillance, epidemiology, and end results from a collection of state-level cancer registries across 744 counties. Data from the Environmental Protection Agency's network for PM2.5 monitoring was used to calculate trailing 5- and 10-year PM2.5 county-level values. County-level data on demographic characteristics were obtained from the American Community Survey. POPULATION A total of 98 751 patients with histologically confirmed ovarian cancer as a primary malignancy from 2000 to 2016. METHODS Generalised linear regression models were developed to estimate the association between PM2.5 and PM10 levels, over 5- and 10-year periods of exposure, and ovarian cancer risk, after accounting for county-level covariates. MAIN OUTCOME MEASURES Risk ratios for associations between ovarian cancer (both overall and specifically epithelial ovarian cancer) and PM2.5 levels. RESULTS For the 744 counties included, the average PM2.5 level from 1990 through 2018 was 11.75 μg/m3 (SD = 3.7) and the average PM10 level was 22.7 μg/m3 (SD = 5.7). After adjusting for county-level covariates, the overall annualised ovarian cancer incidence was significantly associated with increases in 5-year PM2.5 (RR = 1.11 per 10 units (μg/m3 ) increase, 95% CI 1.06-1.16). Similarly, when the analysis was limited to epithelial cell tumours and adjusted for county-level covariates there was a significant association with trailing 5-year PM2.5 exposure models (RR = 1.12 per 10 units increase, 95% CI 1.08-1.17). Likewise, 10-year PM2.5 exposure was associated with ovarian cancer overall and with epithelial ovarian cancer. CONCLUSIONS Higher county-level ambient PM2.5 levels are associated with 5- and 10-year incidences of ovarian cancer, as measurable in an ecological study.
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Affiliation(s)
| | - Yongmei Huang
- Columbia University College of Physicians and Surgeons, New York, New York, USA
- Joseph L. Mailman School of Public Health, Columbia University, New York, New York, USA
| | - Blair J Wylie
- Columbia University College of Physicians and Surgeons, New York, New York, USA
- New York Presbyterian Hospital, New York, New York, USA
| | - Fady Khoury-Collado
- Columbia University College of Physicians and Surgeons, New York, New York, USA
- New York Presbyterian Hospital, New York, New York, USA
- Herbert Irving Comprehensive Cancer Center, New York, New York, USA
| | - June Y Hou
- Columbia University College of Physicians and Surgeons, New York, New York, USA
- New York Presbyterian Hospital, New York, New York, USA
- Herbert Irving Comprehensive Cancer Center, New York, New York, USA
| | - Alexandre Buckley de Meritens
- Columbia University College of Physicians and Surgeons, New York, New York, USA
- New York Presbyterian Hospital, New York, New York, USA
- Herbert Irving Comprehensive Cancer Center, New York, New York, USA
| | - Caryn M St Clair
- Columbia University College of Physicians and Surgeons, New York, New York, USA
- New York Presbyterian Hospital, New York, New York, USA
- Herbert Irving Comprehensive Cancer Center, New York, New York, USA
| | - Dawn L Hershman
- Columbia University College of Physicians and Surgeons, New York, New York, USA
- Joseph L. Mailman School of Public Health, Columbia University, New York, New York, USA
- New York Presbyterian Hospital, New York, New York, USA
- Herbert Irving Comprehensive Cancer Center, New York, New York, USA
| | - Jason D Wright
- Columbia University College of Physicians and Surgeons, New York, New York, USA
- Joseph L. Mailman School of Public Health, Columbia University, New York, New York, USA
- New York Presbyterian Hospital, New York, New York, USA
- Herbert Irving Comprehensive Cancer Center, New York, New York, USA
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2
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Jayasekera J, El Kefi S, Fernandez JR, Wojcik KM, Woo JMP, Ezeani A, Ish JL, Bhattacharya M, Ogunsina K, Chang CJ, Cohen CM, Ponce S, Kamil D, Zhang J, Le R, Ramanathan AL, Butera G, Chapman C, Grant SJ, Lewis-Thames MW, Dash C, Bethea TN, Forde AT. Opportunities, challenges, and future directions for simulation modeling the effects of structural racism on cancer mortality in the United States: a scoping review. J Natl Cancer Inst Monogr 2023; 2023:231-245. [PMID: 37947336 PMCID: PMC10637025 DOI: 10.1093/jncimonographs/lgad020] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/10/2023] [Revised: 05/23/2023] [Accepted: 07/03/2023] [Indexed: 11/12/2023] Open
Abstract
PURPOSE Structural racism could contribute to racial and ethnic disparities in cancer mortality via its broad effects on housing, economic opportunities, and health care. However, there has been limited focus on incorporating structural racism into simulation models designed to identify practice and policy strategies to support health equity. We reviewed studies evaluating structural racism and cancer mortality disparities to highlight opportunities, challenges, and future directions to capture this broad concept in simulation modeling research. METHODS We used the Preferred Reporting Items for Systematic Reviews and Meta-Analyses-Scoping Review Extension guidelines. Articles published between 2018 and 2023 were searched including terms related to race, ethnicity, cancer-specific and all-cause mortality, and structural racism. We included studies evaluating the effects of structural racism on racial and ethnic disparities in cancer mortality in the United States. RESULTS A total of 8345 articles were identified, and 183 articles were included. Studies used different measures, data sources, and methods. For example, in 20 studies, racial residential segregation, one component of structural racism, was measured by indices of dissimilarity, concentration at the extremes, redlining, or isolation. Data sources included cancer registries, claims, or institutional data linked to area-level metrics from the US census or historical mortgage data. Segregation was associated with worse survival. Nine studies were location specific, and the segregation measures were developed for Black, Hispanic, and White residents. CONCLUSIONS A range of measures and data sources are available to capture the effects of structural racism. We provide a set of recommendations for best practices for modelers to consider when incorporating the effects of structural racism into simulation models.
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Affiliation(s)
- Jinani Jayasekera
- Division of Intramural Research at the National Institute on Minority Health and Health Disparities, National Institutes of Health, Bethesda, MD, USA
| | - Safa El Kefi
- NYU Langone Health, New York University, New York, NY, USA
| | - Jessica R Fernandez
- Division of Intramural Research at the National Institute on Minority Health and Health Disparities, National Institutes of Health, Bethesda, MD, USA
| | - Kaitlyn M Wojcik
- Division of Intramural Research at the National Institute on Minority Health and Health Disparities, National Institutes of Health, Bethesda, MD, USA
| | - Jennifer M P Woo
- Epidemiology Branch at the National Institute of Environmental Health Sciences at the National Institutes of Health, Bethesda, MD, USA
| | - Adaora Ezeani
- Health Behaviors Research Branch of the Behavioral Research Program, Division of Cancer Control and Population Sciences, National Cancer Institute, Rockville, MD, USA
| | - Jennifer L Ish
- Epidemiology Branch at the National Institute of Environmental Health Sciences at the National Institutes of Health, Bethesda, MD, USA
| | - Manami Bhattacharya
- Cancer Prevention Fellowship Program, Division of Cancer Prevention, and the Surveillance Research Program, Division of Cancer Control and Population Sciences, National Cancer Institute, Rockville, MD, USA
| | - Kemi Ogunsina
- Epidemiology Branch at the National Institute of Environmental Health Sciences at the National Institutes of Health, Bethesda, MD, USA
| | - Che-Jung Chang
- Epidemiology Branch at the National Institute of Environmental Health Sciences at the National Institutes of Health, Bethesda, MD, USA
| | - Camryn M Cohen
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Rockville, MD, USA
| | - Stephanie Ponce
- Division of Intramural Research at the National Institute on Minority Health and Health Disparities, National Institutes of Health, Bethesda, MD, USA
| | - Dalya Kamil
- Division of Intramural Research at the National Institute on Minority Health and Health Disparities, National Institutes of Health, Bethesda, MD, USA
| | - Julia Zhang
- Division of Intramural Research at the National Institute on Minority Health and Health Disparities, National Institutes of Health, Bethesda, MD, USA
- Sophomore at Williams College, Williamstown, MA, USA
| | - Randy Le
- Division of Intramural Research at the National Institute on Minority Health and Health Disparities, National Institutes of Health, Bethesda, MD, USA
| | - Amrita L Ramanathan
- Diabetes, Endocrinology, & Obesity Branch, National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, Bethesda, MD, USA
| | - Gisela Butera
- Office of Research Services, National Institutes of Health Library, Bethesda, MD, USA
| | - Christina Chapman
- Department of Radiation Oncology, Baylor College of Medicine, and the Center for Innovations in Quality, Effectiveness, and Safety in the Department of Medicine, Baylor College of Medicine and the Houston Veterans Affairs, Houston, TX, USA
| | - Shakira J Grant
- Department of Medicine, Division of Hematology, University of North Carolina, Chapel Hill, NC, USA
| | - Marquita W Lewis-Thames
- Department of Medical Social Science, Center for Community Health at Northwestern University Feinberg School of Medicine, Chicago, IL, USA
| | - Chiranjeev Dash
- Office of Minority Health and Health Disparities Research at the Georgetown-Lombardi Comprehensive Cancer Center, Washington, DC, USA
| | - Traci N Bethea
- Office of Minority Health and Health Disparities Research at the Georgetown-Lombardi Comprehensive Cancer Center, Washington, DC, USA
| | - Allana T Forde
- Division of Intramural Research at the National Institute on Minority Health and Health Disparities, National Institutes of Health, Bethesda, MD, USA
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Sheridan P, Chen C, Thompson CA, Benmarhnia T. Immortal Time Bias With Time-Varying Exposures in Environmental Epidemiology: A Case Study in Lung Cancer Survival. Am J Epidemiol 2023; 192:1754-1762. [PMID: 37400995 PMCID: PMC10558188 DOI: 10.1093/aje/kwad135] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/22/2022] [Revised: 01/19/2023] [Accepted: 06/04/2023] [Indexed: 07/05/2023] Open
Abstract
Immortal time bias is a well-recognized bias in clinical epidemiology but is rarely discussed in environmental epidemiology. Under the target trial framework, this bias is formally conceptualized as a misalignment between the start of study follow-up (time 0) and treatment assignment. This misalignment can occur when attained duration of follow-up is encoded into treatment assignment using minimums, maximums, or averages. The bias can be exacerbated in the presence of time trends commonly found in environmental exposures. Using lung cancer cases from the California Cancer Registry (2000-2010) linked with estimated concentrations of particulate matter less than or equal to 2.5 μm in aerodynamic diameter (PM2.5), we replicated previous studies that averaged PM2.5 exposure over follow-up in a time-to-event model. We compared this approach with one that ensures alignment between time 0 and treatment assignment, a discrete-time approach. In the former approach, the estimated overall hazard ratio for a 5-μg/m3 increase in PM2.5 was 1.38 (95% confidence interval: 1.36, 1.40). Under the discrete-time approach, the estimated pooled odds ratio was 0.99 (95% confidence interval: 0.98, 1.00). We conclude that the strong estimated effect in the former approach was likely driven by immortal time bias, due to misalignment at time 0. Our findings highlight the importance of appropriately conceptualizing a time-varying environmental exposure under the target trial framework to avoid introducing preventable systematic errors.
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Affiliation(s)
- Paige Sheridan
- Correspondence to Dr. Paige Sheridan, Herbert Wertheim School of Public Health, University of California, San Diego, 9500 Gilman Drive, La Jolla, CA 92093 (e-mail: )
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Gomez SL, Chirikova E, McGuire V, Collin LJ, Dempsey L, Inamdar PP, Lawson-Michod K, Peters ES, Kushi LH, Kavecansky J, Shariff-Marco S, Peres LC, Terry P, Bandera EV, Schildkraut JM, Doherty JA, Lawson A. Role of neighborhood context in ovarian cancer survival disparities: current research and future directions. Am J Obstet Gynecol 2023; 229:366-376.e8. [PMID: 37116824 PMCID: PMC10538437 DOI: 10.1016/j.ajog.2023.04.026] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/06/2022] [Revised: 04/01/2023] [Accepted: 04/20/2023] [Indexed: 04/30/2023]
Abstract
Ovarian cancer is the fifth leading cause of cancer-associated mortality among US women with survival disparities seen across race, ethnicity, and socioeconomic status, even after accounting for histology, stage, treatment, and other clinical factors. Neighborhood context can play an important role in ovarian cancer survival, and, to the extent to which minority racial and ethnic groups and populations of lower socioeconomic status are more likely to be segregated into neighborhoods with lower quality social, built, and physical environment, these contextual factors may be a critical component of ovarian cancer survival disparities. Understanding factors associated with ovarian cancer outcome disparities will allow clinicians to identify patients at risk for worse outcomes and point to measures, such as social support programs or transportation aid, that can help to ameliorate such disparities. However, research on the impact of neighborhood contextual factors in ovarian cancer survival and in disparities in ovarian cancer survival is limited. This commentary focuses on the following neighborhood contextual domains: structural and institutional context, social context, physical context represented by environmental exposures, built environment, rurality, and healthcare access. The research conducted to date is presented and clinical implications and recommendations for future interventions and studies to address disparities in ovarian cancer outcomes are proposed.
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Affiliation(s)
- Scarlett L Gomez
- Department of Epidemiology and Biostatistics, University of California, San Francisco, San Francisco, CA; Helen Diller Family Comprehensive Cancer Center, University of California, San Francisco, San Francisco, CA.
| | - Ekaterina Chirikova
- Department of Epidemiology and Biostatistics, University of California, San Francisco, San Francisco, CA
| | - Valerie McGuire
- Department of Epidemiology and Biostatistics, University of California, San Francisco, San Francisco, CA
| | - Lindsay J Collin
- Department of Population Health Sciences, Huntsman Cancer Institute, University of Utah, Salt Lake City, UT
| | - Lauren Dempsey
- Department of Epidemiology, Rollins School of Public Health, Emory University, Atlanta, GA
| | - Pushkar P Inamdar
- Department of Epidemiology and Biostatistics, University of California, San Francisco, San Francisco, CA
| | - Katherine Lawson-Michod
- Department of Population Health Sciences, Huntsman Cancer Institute, University of Utah, Salt Lake City, UT
| | - Edward S Peters
- Department of Epidemiology, University of Nebraska Medical Center College of Public Health, Omaha, NE
| | - Lawrence H Kushi
- Division of Research, Kaiser Permanente Northern California, Oakland, CA
| | - Juraj Kavecansky
- Department of Hematology and Oncology, Kaiser Permanente Northern California, Antioch, CA
| | - Salma Shariff-Marco
- Department of Epidemiology and Biostatistics, University of California, San Francisco, San Francisco, CA; Helen Diller Family Comprehensive Cancer Center, University of California, San Francisco, San Francisco, CA
| | - Lauren C Peres
- Department of Cancer Epidemiology, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL
| | - Paul Terry
- Department of Medicine, University of Tennessee, Knoxville, TN
| | - Elisa V Bandera
- Cancer Epidemiology and Health Outcomes, Rutgers Cancer Institute of New Jersey, Robert Wood Johnson Medical School, New Brunswick, NJ
| | - Joellen M Schildkraut
- Department of Epidemiology, Rollins School of Public Health, Emory University, Atlanta, GA
| | - Jennifer A Doherty
- Department of Population Health Sciences, Huntsman Cancer Institute, University of Utah, Salt Lake City, UT
| | - Andrew Lawson
- Department of Public Health Sciences, College of Medicine, Medical University of South Carolina, Charleston, SC; Usher Institute, School of Medicine, University of Edinburgh, Edinburgh, United Kingdom
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5
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Gao S, Zou BJ, Shi S, Wei YF, Du ZD, Zheng G, Wang R, Yin JL, Zhao JQ, Yan S, Qin X, Xiao Q, Gong TT, Chen RJ, Zhao YH, Wu QJ. PM 2.5 exposure and its interaction of oxidative balance score on ovarian cancer survival: A prospective cohort study. ECOTOXICOLOGY AND ENVIRONMENTAL SAFETY 2023; 256:114877. [PMID: 37037107 DOI: 10.1016/j.ecoenv.2023.114877] [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: 12/11/2022] [Revised: 03/24/2023] [Accepted: 04/04/2023] [Indexed: 06/19/2023]
Abstract
Recent evidence advises particles with a diameter of 2.5 µm or less (PM2.5) might be a prognostic factor for ovarian cancer (OC) survival. The oxidative balance score (OBS) incorporates diet-lifestyle factors to estimate individuals' anti-oxidant exposure status which may be relevant to cancer prognosis. We aimed to investigate the roles of PM2.5, and OBS and their interaction in OC prognosis. 663 patients with OC were enrolled in the current study. Satellite-derived annual average exposures to PM2.5 based on patients' residential locations. The OBS was calculated based on 16 different diet-lifestyle components derived using an acknowledged self-reported questionnaire. The Cox regression model was performed to estimate the hazard ratios (HRs) and 95% confidence intervals (CIs) for overall survival (OS). We also assessed the effect of modification between PM2.5 and OS by OBS via interaction terms. During a median follow-up of 37.57 (interquartile:35.27-40.17) months, 123 patients died. Compared to low-concentration PM2.5 exposure, high PM2.5 during 1 year before diagnosis was associated with worse OC survival (HR= 1.19, 95% CI = 1.01-1.42). We observed an improved OS with the highest compared with the lowest OBS (HR = 0.46, 95% CI = 0.27-0.79, P for trend < 0.05). Notably, we also found an additive interaction between low OBS and high exposure to PM2.5, with the corresponding associations of PM2.5 being more pronounced among participants with lower OBS (HR = 1.42, 95% CI = 1.09-1.86). PM2.5 may blunt OC survival, but high OBS represented an antioxidative performance that could alleviate the adverse association of PM2.5 and OS.
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Affiliation(s)
- Song Gao
- Department of Obstetrics and Gynecology, Shengjing Hospital of China Medical University, Shenyang, China
| | - Bing-Jie Zou
- Department of Clinical Epidemiology, Shengjing Hospital of China Medical University, Shenyang, China; Clinical Research Center, Shengjing Hospital of China Medical University, Shenyang, China
| | - Su Shi
- School of Public Health, Key Lab of Public Health Safety of the Ministry of Education and NHC Key Lab of Health Technology Assessment, Fudan University, Shanghai, China
| | - Yi-Fan Wei
- Department of Clinical Epidemiology, Shengjing Hospital of China Medical University, Shenyang, China; Clinical Research Center, Shengjing Hospital of China Medical University, Shenyang, China; Liaoning Key Laboratory of Precision Medical Research on Major Chronic Disease, Shengjing Hospital of China Medical University, Shenyang, China
| | - Zong-Da Du
- Department of Clinical Epidemiology, Shengjing Hospital of China Medical University, Shenyang, China; Clinical Research Center, Shengjing Hospital of China Medical University, Shenyang, China; Liaoning Key Laboratory of Precision Medical Research on Major Chronic Disease, Shengjing Hospital of China Medical University, Shenyang, China
| | - Gang Zheng
- Department of Clinical Epidemiology, Shengjing Hospital of China Medical University, Shenyang, China; Clinical Research Center, Shengjing Hospital of China Medical University, Shenyang, China; Liaoning Key Laboratory of Precision Medical Research on Major Chronic Disease, Shengjing Hospital of China Medical University, Shenyang, China
| | - Rang Wang
- Department of Clinical Epidemiology, Shengjing Hospital of China Medical University, Shenyang, China; Clinical Research Center, Shengjing Hospital of China Medical University, Shenyang, China; Liaoning Key Laboratory of Precision Medical Research on Major Chronic Disease, Shengjing Hospital of China Medical University, Shenyang, China
| | - Jia-Li Yin
- Department of Clinical Epidemiology, Shengjing Hospital of China Medical University, Shenyang, China; Clinical Research Center, Shengjing Hospital of China Medical University, Shenyang, China; Liaoning Key Laboratory of Precision Medical Research on Major Chronic Disease, Shengjing Hospital of China Medical University, Shenyang, China
| | - Jun-Qi Zhao
- Department of Clinical Epidemiology, Shengjing Hospital of China Medical University, Shenyang, China; Clinical Research Center, Shengjing Hospital of China Medical University, Shenyang, China; Liaoning Key Laboratory of Precision Medical Research on Major Chronic Disease, Shengjing Hospital of China Medical University, Shenyang, China
| | - Shi Yan
- Department of Clinical Epidemiology, Shengjing Hospital of China Medical University, Shenyang, China; Clinical Research Center, Shengjing Hospital of China Medical University, Shenyang, China; Liaoning Key Laboratory of Precision Medical Research on Major Chronic Disease, Shengjing Hospital of China Medical University, Shenyang, China
| | - Xue Qin
- Department of Obstetrics and Gynecology, Shengjing Hospital of China Medical University, Shenyang, China
| | - Qian Xiao
- Department of Clinical Epidemiology, Shengjing Hospital of China Medical University, Shenyang, China; Department of Obstetrics and Gynecology, Shengjing Hospital of China Medical University, Shenyang, China
| | - Ting-Ting Gong
- Department of Obstetrics and Gynecology, Shengjing Hospital of China Medical University, Shenyang, China.
| | - Ren-Jie Chen
- School of Public Health, Key Lab of Public Health Safety of the Ministry of Education and NHC Key Lab of Health Technology Assessment, Fudan University, Shanghai, China
| | - Yu-Hong Zhao
- Department of Clinical Epidemiology, Shengjing Hospital of China Medical University, Shenyang, China; Clinical Research Center, Shengjing Hospital of China Medical University, Shenyang, China; Liaoning Key Laboratory of Precision Medical Research on Major Chronic Disease, Shengjing Hospital of China Medical University, Shenyang, China
| | - Qi-Jun Wu
- Department of Clinical Epidemiology, Shengjing Hospital of China Medical University, Shenyang, China; Clinical Research Center, Shengjing Hospital of China Medical University, Shenyang, China; Liaoning Key Laboratory of Precision Medical Research on Major Chronic Disease, Shengjing Hospital of China Medical University, Shenyang, China; Department of Obstetrics and Gynecology, Shengjing Hospital of China Medical University, Shenyang, China; Key Laboratory of Reproductive and Genetic Medicine (China Medical University), National Health Commission, Shenyang, China.
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Li YZ, Huang SH, Shi S, Chen WX, Wei YF, Zou BJ, Yao W, Zhou L, Liu FH, Gao S, Yan S, Qin X, Zhao YH, Chen RJ, Gong TT, Wu QJ. Association of long-term particulate matter exposure with all-cause mortality among patients with ovarian cancer: A prospective cohort. THE SCIENCE OF THE TOTAL ENVIRONMENT 2023; 884:163748. [PMID: 37120017 DOI: 10.1016/j.scitotenv.2023.163748] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/13/2022] [Revised: 04/19/2023] [Accepted: 04/22/2023] [Indexed: 05/03/2023]
Abstract
BACKGROUND Evidence of the association between particles with a diameter of 2.5 μm or less (PM2.5) in long term and ovarian cancer (OC) mortality is limited. METHODS This prospective cohort study analyzed data collected between 2015 and 2020 from 610 newly diagnosed OC patients, aged 18-79 years. The residential average PM2.5 concentrations 10 years before the date of OC diagnosis were assessed by random forest models at a 1 km × 1 km resolution. Cox proportional hazard models fully adjusted for the covariates (including age at diagnosis, education, physical activity, kitchen ventilation, FIGO stage, and comorbidities) and distributed lag non-linear models were used to estimate the hazard ratios (HRs) and 95 % confidence intervals (CIs) of PM2.5 and all-cause mortality of OC. RESULTS During a median follow-up of 37.6 months (interquartile: 24.8-50.5 months), 118 (19.34 %) deaths were confirmed among 610 OC patients. One-year PM2.5 exposure levels before OC diagnosis was significantly associated with an increase in all-cause mortality among OC patients (single-pollutant model: HR = 1.22, 95 % CI: 1.02-1.46; multi-pollutant models: HR = 1.38, 95 % CI: 1.10-1.72). Furthermore, during 1 to 10 years prior to diagnosis, the lag-specific effect of long-term PM2.5 exposure on the all-cause mortality of OC had a risk increase for lag 1-6 years, and the exposure-response relationship was linear. Of note, significant interactions between several immunological indicators as well as solid fuel use for cooking and ambient PM2.5 concentrations were observed. CONCLUSION Higher ambient PM2.5 concentrations were associated with an increased risk of all-cause mortality among OC patients, and there was a lag effect in long-term PM2.5 exposure.
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Affiliation(s)
- Yi-Zi Li
- Department of Clinical Epidemiology, Shengjing Hospital of China Medical University, Shenyang, China; Clinical Research Center, Shengjing Hospital of China Medical University, Shenyang, China; Key Laboratory of Precision Medical Research on Major Chronic Disease, Shengjing Hospital of China Medical University, Shenyang, China
| | - Shu-Hong Huang
- Department of Clinical Epidemiology, Shengjing Hospital of China Medical University, Shenyang, China; Clinical Research Center, Shengjing Hospital of China Medical University, Shenyang, China; Key Laboratory of Precision Medical Research on Major Chronic Disease, Shengjing Hospital of China Medical University, Shenyang, China
| | - Su Shi
- School of Public Health, Key Lab of Public Health Safety of the Ministry of Education and NHC Key Lab of Health Technology Assessment, Fudan University, Shanghai, China
| | - Wen-Xiao Chen
- Department of Sports Medicine and Joint Surgery, The People's Hospital of Liaoning Province, Shenyang, China
| | - Yi-Fan Wei
- Department of Clinical Epidemiology, Shengjing Hospital of China Medical University, Shenyang, China; Clinical Research Center, Shengjing Hospital of China Medical University, Shenyang, China; Key Laboratory of Precision Medical Research on Major Chronic Disease, Shengjing Hospital of China Medical University, Shenyang, China
| | - Bing-Jie Zou
- Department of Clinical Epidemiology, Shengjing Hospital of China Medical University, Shenyang, China; Clinical Research Center, Shengjing Hospital of China Medical University, Shenyang, China; Key Laboratory of Precision Medical Research on Major Chronic Disease, Shengjing Hospital of China Medical University, Shenyang, China
| | - Wei Yao
- Department of Clinical Epidemiology, Shengjing Hospital of China Medical University, Shenyang, China; Clinical Research Center, Shengjing Hospital of China Medical University, Shenyang, China; Key Laboratory of Precision Medical Research on Major Chronic Disease, Shengjing Hospital of China Medical University, Shenyang, China
| | - Lu Zhou
- School of Public Health, Key Lab of Public Health Safety of the Ministry of Education and NHC Key Lab of Health Technology Assessment, Fudan University, Shanghai, China
| | - Fang-Hua Liu
- Department of Clinical Epidemiology, Shengjing Hospital of China Medical University, Shenyang, China; Clinical Research Center, Shengjing Hospital of China Medical University, Shenyang, China; Key Laboratory of Precision Medical Research on Major Chronic Disease, Shengjing Hospital of China Medical University, Shenyang, China
| | - Song Gao
- Department of Obstetrics and Gynecology, Shengjing Hospital of China Medical University, Shenyang, China
| | - Shi Yan
- Department of Clinical Epidemiology, Shengjing Hospital of China Medical University, Shenyang, China; Clinical Research Center, Shengjing Hospital of China Medical University, Shenyang, China; Key Laboratory of Precision Medical Research on Major Chronic Disease, Shengjing Hospital of China Medical University, Shenyang, China
| | - Xue Qin
- Department of Obstetrics and Gynecology, Shengjing Hospital of China Medical University, Shenyang, China
| | - Yu-Hong Zhao
- Department of Clinical Epidemiology, Shengjing Hospital of China Medical University, Shenyang, China; Clinical Research Center, Shengjing Hospital of China Medical University, Shenyang, China; Key Laboratory of Precision Medical Research on Major Chronic Disease, Shengjing Hospital of China Medical University, Shenyang, China
| | - Ren-Jie Chen
- School of Public Health, Key Lab of Public Health Safety of the Ministry of Education and NHC Key Lab of Health Technology Assessment, Fudan University, Shanghai, China
| | - Ting-Ting Gong
- Department of Obstetrics and Gynecology, Shengjing Hospital of China Medical University, Shenyang, China.
| | - Qi-Jun Wu
- Department of Clinical Epidemiology, Shengjing Hospital of China Medical University, Shenyang, China; Clinical Research Center, Shengjing Hospital of China Medical University, Shenyang, China; Key Laboratory of Precision Medical Research on Major Chronic Disease, Shengjing Hospital of China Medical University, Shenyang, China; Department of Obstetrics and Gynecology, Shengjing Hospital of China Medical University, Shenyang, China; Key Laboratory of Reproductive and Genetic Medicine (China Medical University), National Health Commission, Shenyang, China.
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7
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Lord BD, Harris AR, Ambs S. The impact of social and environmental factors on cancer biology in Black Americans. Cancer Causes Control 2023; 34:191-203. [PMID: 36562901 DOI: 10.1007/s10552-022-01664-w] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/05/2022] [Accepted: 12/16/2022] [Indexed: 12/24/2022]
Abstract
Low socioeconomic status (SES) is associated with early onset of chronic diseases and reduced life expectancy. The involvement of neighborhood-level factors in defining cancer risk and outcomes for marginalized communities has been an active area of research for decades. Yet, the biological processes that underlie the impact of SES on chronic health conditions, such as cancer, remain poorly understood. To date, limited studies have shown that chronic life stress is more prevalent in low SES communities and can affect important molecular processes implicated in tumor biology such as DNA methylation, inflammation, and immune response. Further efforts to elucidate how neighborhood-level factors function physiologically to worsen cancer outcomes for disadvantaged communities are underway. This review provides an overview of the current literature on how socioenvironmental factors within neighborhoods contribute to more aggressive tumor biology, specifically in Black U.S. women and men, including the impact of environmental pollutants, neighborhood deprivation, social isolation, structural racism, and discrimination. We also summarize commonly used methods to measure deprivation, discrimination, and structural racism at the neighborhood-level in cancer health disparities research. Finally, we offer recommendations to adopt a multi-faceted intersectional approach to reduce cancer health disparities and develop effective interventions to promote health equity.
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Affiliation(s)
- Brittany D Lord
- Laboratory of Human Carcinogenesis, Center for Cancer Research, National Cancer Institute (NCI), National Institutes of Health (NIH), Bldg. 37/Room 3050, Bethesda, MD, 20892-4258, USA.
| | - Alexandra R Harris
- Laboratory of Human Carcinogenesis, Center for Cancer Research, National Cancer Institute (NCI), National Institutes of Health (NIH), Bldg. 37/Room 3050, Bethesda, MD, 20892-4258, USA
| | - Stefan Ambs
- Laboratory of Human Carcinogenesis, Center for Cancer Research, National Cancer Institute (NCI), National Institutes of Health (NIH), Bldg. 37/Room 3050, Bethesda, MD, 20892-4258, USA
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Cancer status in the Occupied Palestinian Territories: types; incidence; mortality; sex, age, and geography distribution; and possible causes. J Cancer Res Clin Oncol 2022:10.1007/s00432-022-04430-2. [PMID: 36350411 PMCID: PMC9645346 DOI: 10.1007/s00432-022-04430-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/13/2022] [Accepted: 10/16/2022] [Indexed: 11/11/2022]
Abstract
Cancer is a disease in which some cells of the body grow uncontrollably and occasionally spread to other parts of the body. With a group of more than 100 different types, cancer can start almost anywhere in the body. Defective cells may form a mass called a tumor which can be cancerous (malignant), which grows and spreads to other parts of the body, or benign that can grow but not spread throughout the body. In 2021, more than 10 million people died of cancer worldwide (1 out of 6 deaths). This paper has thoroughly investigated the cancer status in the Occupied Palestinian Territories (OPT), in terms of its various types; incidence; mortality; sex, age, and geography distribution; and potential causes. In the OPT, with a population of 5.35 million, cancer mortality was 14% in 2016, being the second cause of death after cardiovascular diseases accounting 30.6% of all causes of death. Cancer mortality in the OPT increased by 136% from 2000 to 2016, and by 14% from 2016 to 2020. In addition to other types of cancer in the OPT, its main types are lung (highest in males), breast (highest in females), colorectal (highest in both sexes), and leukemia (highest in children). The high rates of different types of cancer in the OPT can be attributed to various causes, including those related to environmental pollution, nutrition, stress, and lifestyle factors (smoking, lack of activity, increased dependence on technologies, etc.), whereas only 10–30% of cancer cases are attributed to genetics.
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Liu G, Yang Z, Wang C, Wang D. PM 2.5 exposure and cervical cancer survival in Liaoning Province, northeastern China. ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH INTERNATIONAL 2022; 29:74669-74676. [PMID: 35641744 DOI: 10.1007/s11356-022-20597-0] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/10/2022] [Accepted: 04/29/2022] [Indexed: 06/15/2023]
Abstract
Particulate matter with a diameter of 2.5 μm or less (PM2.5) has frequently been reported to be associated with an increased incidence of cancer, but few studies have explored the association between PM2.5 exposure and cancer survival. We retrospectively analyzed the association between PM2.5 exposure and the overall survival (OS) of cervical cancer patients residing in 14 urban areas of Liaoning Province, northeastern China, during January 2014-October 2021. Patients from urban areas who completed the recommended treatments with complete follow-up information were included. The PM2.5 monitoring data of each urban area of Liaoning Province were retrieved, and individual exposure to PM2.5 after diagnosis was calculated as the average daily concentration in the city of residence from the date of discharge to the date of death or the last follow-up. Log-rank tests and Cox regression were performed to examine the relationship between PM2.5 exposure and cervical cancer survival. A total of 1753 cervical cancer patients were finally included, among whom 804 (45.9%) were from Shenyang City, the capital of Liaoning Province. The median average daily concentration of PM2.5 to which the patients were exposed was 45.0 (interquartile range 38.2-50.0) μg/m3. Both log-rank tests (grouped by quartiles, p < 0.001) and Cox regression (continuous, HR = 1.06, 95% CI 1.04-1.08) indicated that PM2.5 was significantly associated with shorter OS. Sensitivity analysis also confirmed the robustness of our findings. From the subgroup analysis, only the OS of stage II and stage III patients was associated with PM exposure. Our findings provide the insight that PM2.5 exposure might be associated with shorter OS of cervical cancer patients.
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Affiliation(s)
- Guangcong Liu
- Cancer Hospital of China Medical University, Liaoning Cancer Hospital and Institute Shenyang, Shenyang, People's Republic of China
| | - Zhuo Yang
- Cancer Hospital of China Medical University, Liaoning Cancer Hospital and Institute Shenyang, Shenyang, People's Republic of China
| | - Chenyu Wang
- Cancer Hospital of China Medical University, Liaoning Cancer Hospital and Institute Shenyang, Shenyang, People's Republic of China
| | - Danbo Wang
- Cancer Hospital of China Medical University, Liaoning Cancer Hospital and Institute Shenyang, Shenyang, People's Republic of China.
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