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Jarquin-Yañez L, Martinez-Acuña MI, Lopez-Arevalo I, Calderon Hernandez J. "Characterization of residential proximity to sources of environmental carcinogens in clusters of Acute Lymphoblastic Leukemia in San Luis Potosi, Mexico". ENVIRONMENTAL RESEARCH 2024; 252:118790. [PMID: 38555983 DOI: 10.1016/j.envres.2024.118790] [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: 12/21/2023] [Revised: 03/21/2024] [Accepted: 03/23/2024] [Indexed: 04/02/2024]
Abstract
BACKGROUND Acute Lymphoblastic Leukemia (ALL) is the most prevalent neoplasia in children and teenagers in Mexico. Although epidemiological data supports that children's residence close to emissions from vehicular traffic or industrial processes increases the risk of ALL; and the IARC states that benzene, PAHs, and PM 2.5 are well-known environmental carcinogens, there is a gap in linking these carcinogenic hazards with the sources and their distribution from scenario perspective. AIM To identify ALL clusters in the population under 19 years of age and characterize the environment at the neighborhood level by integrating information on sources of carcinogenic exposure using spatial analysis techniques in the Metropolitan Area of San Luis Potosi, Mexico. METHODS Using the Kernel Density test, we designed an ecological study to identify ALL clusters from incident cases in the population under 19 years of age. A multicriteria analysis was conducted to characterize the risk at the community level from carcinogenic sources. A hierarchical cluster analysis was performed to characterize risk at the individual level based on carcinogenic source count within 1 km for each ALL case. RESULTS Eight clusters of carcinogenic sources were located within the five identified ALL clusters. The multicriteria analysis showed high-risk areas (by density of carcinogenic source) within ALL clusters. CONCLUSIONS This study has a limited source and amount of available data on ALL cases, so selection bias is present as well as the inability to rule out residual confounding factors, since covariates were not included. However, in this study, children living in environments with high vehicular density, gas stations, brick kilns, incinerators, commercial establishments burning biomass, or near industrial zones may be at higher risk for ALL.
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Affiliation(s)
- Lizet Jarquin-Yañez
- Academic Unit of Chemical Sciences, Autonomous University of Zacatecas, Jardín Juárez 147, Centro, 98000 Zacatecas, Zac, Mexico; National Council of Humanities, Sciences and Technologies (CONAHCYT), Mexico, Mexico City
| | - Monica Imelda Martinez-Acuña
- Academic Unit of Chemical Sciences, Autonomous University of Zacatecas, Jardín Juárez 147, Centro, 98000 Zacatecas, Zac, Mexico
| | - Ivan Lopez-Arevalo
- Cinvestav Tamaulipas, Science and Technology Park TecnoTam, 87130, Victoria, Tamaulipas, Mexico
| | - Jaqueline Calderon Hernandez
- Center for Applied Research in Environment and Health, CIACYT-Faculty of Medicine, Autonomous University of San Luis Potosí, Avenida Sierra Leona No. 550, Lomas 2nd Section, 78210, San Luis Potosí, SLP, Mexico; Global Public Health Program, Boston College, Boston, MA, United States.
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Wei T, Jiao R, Nakyeyune R, Zang Z, Shao Y, Shen Y, Niu C, Zhu L, Ruan X, Liu F. Exposure to outdoor air pollution at different periods and the risk of leukemia: a meta-analysis. ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH INTERNATIONAL 2021; 28:35376-35391. [PMID: 34009571 DOI: 10.1007/s11356-021-14053-8] [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: 01/05/2021] [Accepted: 04/19/2021] [Indexed: 06/12/2023]
Abstract
The causes of leukemia remain largely unknown; our aims were to examine the association between the exposure to outdoor air pollution and leukemia risk and to explore the effect of this exposure during different periods of pregnancy and early life. We searched for all case-control and cohort studies published before February 20, 2021, which measured the risk of leukemia in relation to exposure to the air pollutants: particulate matter, benzene, nitrogen dioxide (NO2), and nitrogen oxides (NOx). We then carried out a meta-analysis and calculated the summary relative risks (RRs) of leukemia by using a random-effects model. The potential dose-response relationship was further explored. The results showed that the highest exposure to benzene (RR: 1.20, 95%CI: 1.06-1.35) and NO2 (RR: 1.04, 95%CI; 1.02-1.08) were positively correlated with leukemia risk when compared to the lowest exposure categories for each air pollutant. During pregnancy, exposure to benzene in the third trimester, as well as exposure to NO2 in the second trimester and entire pregnancy, could also increase the risk of leukemia. In the dose-response analysis, benzene exposure and NO2 exposure were linearly associated with the risk of leukemia. Other air pollutants did not have a statistical correlation with leukemia risk. There was a certain degree of publication bias in studies on benzene. Overall, our results support a link between outdoor air pollution and leukemia risk, particularly due to benzene and NO2. Prospero Registration Number: PROSPERO CRD42020207025.
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Affiliation(s)
- Tong Wei
- Department of Epidemiology and Health Statistics, School of Public Health, Beijing Municipal Key Laboratory of Clinical Epidemiology, Capital Medical University, 10# Xitoutiao, Youanmenwai Street, Beijing, 100069, China
| | - Rong Jiao
- Department of Epidemiology and Health Statistics, School of Public Health, Beijing Municipal Key Laboratory of Clinical Epidemiology, Capital Medical University, 10# Xitoutiao, Youanmenwai Street, Beijing, 100069, China
| | - Rena Nakyeyune
- Department of Epidemiology and Health Statistics, School of Public Health, Beijing Municipal Key Laboratory of Clinical Epidemiology, Capital Medical University, 10# Xitoutiao, Youanmenwai Street, Beijing, 100069, China
| | - Zhaoping Zang
- Department of Epidemiology and Health Statistics, School of Public Health, Beijing Municipal Key Laboratory of Clinical Epidemiology, Capital Medical University, 10# Xitoutiao, Youanmenwai Street, Beijing, 100069, China
| | - Yi Shao
- Department of Epidemiology and Health Statistics, School of Public Health, Beijing Municipal Key Laboratory of Clinical Epidemiology, Capital Medical University, 10# Xitoutiao, Youanmenwai Street, Beijing, 100069, China
| | - Yi Shen
- Department of Epidemiology and Health Statistics, School of Public Health, Beijing Municipal Key Laboratory of Clinical Epidemiology, Capital Medical University, 10# Xitoutiao, Youanmenwai Street, Beijing, 100069, China
| | - Chen Niu
- Department of Epidemiology and Health Statistics, School of Public Health, Beijing Municipal Key Laboratory of Clinical Epidemiology, Capital Medical University, 10# Xitoutiao, Youanmenwai Street, Beijing, 100069, China
| | - Lingyan Zhu
- Department of Epidemiology and Health Statistics, School of Public Health, Beijing Municipal Key Laboratory of Clinical Epidemiology, Capital Medical University, 10# Xitoutiao, Youanmenwai Street, Beijing, 100069, China
| | - Xiaoli Ruan
- Department of Epidemiology and Health Statistics, School of Public Health, Beijing Municipal Key Laboratory of Clinical Epidemiology, Capital Medical University, 10# Xitoutiao, Youanmenwai Street, Beijing, 100069, China
| | - Fen Liu
- Department of Epidemiology and Health Statistics, School of Public Health, Beijing Municipal Key Laboratory of Clinical Epidemiology, Capital Medical University, 10# Xitoutiao, Youanmenwai Street, Beijing, 100069, China.
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