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García-Pérez J, Fernández de Larrea-Baz N, Lope V, Domínguez-Castillo A, Espinosa A, Dierssen-Sotos T, Contreras-Llanes M, Sierra MÁ, Castaño-Vinyals G, Tardón A, Jiménez-Moleón JJ, Molina-Barceló A, Aragonés N, Kogevinas M, Pollán M, Pérez-Gómez B. Risk of prostate cancer in the proximity of industrial installations: A multicase-control study in Spain (MCC-Spain). THE SCIENCE OF THE TOTAL ENVIRONMENT 2024; 946:174347. [PMID: 38944307 DOI: 10.1016/j.scitotenv.2024.174347] [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: 03/13/2024] [Revised: 06/11/2024] [Accepted: 06/26/2024] [Indexed: 07/01/2024]
Abstract
BACKGROUND Prostate cancer (PC) is the second most frequent tumor in men worldwide; however, its etiology remains largely unknown, with the exception of age and family history. The wide variability in incidence/mortality across countries suggests a certain role for environmental exposures that has not yet been clarified. OBJECTIVE To evaluate the association between risk of PC (by clinical profile) and residential proximity to pollutant industrial installations (by industrial groups, groups of carcinogens, and specific pollutants released), within the context of a Spanish population-based multicase-control study of incident cancer (MCC-Spain). METHODS This study included 1186 controls and 234 PC cases, frequency matched by age and province of residence. Distances from participants' residences to the 58 industries located in the study area were calculated and categorized into "near" (considering different limits between ≤1 km and ≤ 3 km) or "far" (>3 km). Odds ratios (ORs) and 95 % confidence intervals (95%CIs) were estimated using mixed and multinomial logistic regression models, adjusted for potential confounders and matching variables. RESULTS No excess risk was detected near the overall industries, with ORs ranging from 0.66 (≤2 km) to 1.11 (≤1 km). However, positive associations (OR; 95%CI) were found, by industrial group, near (≤3 km) industries of ceramic (2.54; 1.28-5.07), food/beverage (2.18; 1.32-3.62), and disposal/recycling of animal waste (2.67; 1.12-6.37); and, by specific pollutant, near plants releasing fluorine (4.65; 1.45-14.91 at ≤1.5 km) and chlorine (5.21; 1.56-17.35 at ≤1 km). In contrast, inverse associations were detected near industries releasing ammonia, methane, dioxins+furans, polycyclic aromatic hydrocarbons, trichloroethylene, and vanadium to air. CONCLUSIONS The results suggest no association between risk of PC and proximity to the overall industrial installations. However, some both positive and inverse associations were detected near certain industrial groups and industries emitting specific pollutants.
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Affiliation(s)
- Javier García-Pérez
- Cancer and Environmental Epidemiology Unit, Department of Epidemiology of Chronic Diseases, National Center for Epidemiology, Instituto de Salud Carlos III (Carlos III Institute of Health), Avda. Monforte de Lemos, 5, 28029 Madrid, Spain; Consortium for Biomedical Research in Epidemiology & Public Health (CIBER en Epidemiología y Salud Pública - CIBERESP), Avda. Monforte de Lemos, 3-5, 28029 Madrid, Spain.
| | - Nerea Fernández de Larrea-Baz
- Cancer and Environmental Epidemiology Unit, Department of Epidemiology of Chronic Diseases, National Center for Epidemiology, Instituto de Salud Carlos III (Carlos III Institute of Health), Avda. Monforte de Lemos, 5, 28029 Madrid, Spain; Consortium for Biomedical Research in Epidemiology & Public Health (CIBER en Epidemiología y Salud Pública - CIBERESP), Avda. Monforte de Lemos, 3-5, 28029 Madrid, Spain.
| | - Virginia Lope
- Cancer and Environmental Epidemiology Unit, Department of Epidemiology of Chronic Diseases, National Center for Epidemiology, Instituto de Salud Carlos III (Carlos III Institute of Health), Avda. Monforte de Lemos, 5, 28029 Madrid, Spain; Consortium for Biomedical Research in Epidemiology & Public Health (CIBER en Epidemiología y Salud Pública - CIBERESP), Avda. Monforte de Lemos, 3-5, 28029 Madrid, Spain.
| | - Alejandro Domínguez-Castillo
- Cancer and Environmental Epidemiology Unit, Department of Epidemiology of Chronic Diseases, National Center for Epidemiology, Instituto de Salud Carlos III (Carlos III Institute of Health), Avda. Monforte de Lemos, 5, 28029 Madrid, Spain; Consortium for Biomedical Research in Epidemiology & Public Health (CIBER en Epidemiología y Salud Pública - CIBERESP), Avda. Monforte de Lemos, 3-5, 28029 Madrid, Spain.
| | - Ana Espinosa
- Consortium for Biomedical Research in Epidemiology & Public Health (CIBER en Epidemiología y Salud Pública - CIBERESP), Avda. Monforte de Lemos, 3-5, 28029 Madrid, Spain; Barcelona Institute of Global Health (ISGlobal), Carrer Del Dr. Aiguader, 88, 08003 Barcelona, Spain; University Pompeu Fabra, Plaça de La Mercè, 10-12, 08002 Barcelona, Spain; Hospital Del Mar Medical Research Institute (IMIM), Carrer Del Dr. Aiguader, 88, 08003 Barcelona, Spain.
| | - Trinidad Dierssen-Sotos
- Consortium for Biomedical Research in Epidemiology & Public Health (CIBER en Epidemiología y Salud Pública - CIBERESP), Avda. Monforte de Lemos, 3-5, 28029 Madrid, Spain; Department of Medical and Surgical Sciences, Faculty of Medicine, University of Cantabria, IDIVAL, Avda. Cardenal Herrera Oria s/n, 39011 Santander, Spain.
| | - Manuel Contreras-Llanes
- Research Center on Natural Resources, Health, and Environment (RENSMA), University of Huelva, Campus de El Carmen, Av. del Tres de Marzo, s/n, 21071 Huelva, Spain.
| | - María Ángeles Sierra
- Cancer and Environmental Epidemiology Unit, Department of Epidemiology of Chronic Diseases, National Center for Epidemiology, Instituto de Salud Carlos III (Carlos III Institute of Health), Avda. Monforte de Lemos, 5, 28029 Madrid, Spain; Consortium for Biomedical Research in Epidemiology & Public Health (CIBER en Epidemiología y Salud Pública - CIBERESP), Avda. Monforte de Lemos, 3-5, 28029 Madrid, Spain.
| | - Gemma Castaño-Vinyals
- Consortium for Biomedical Research in Epidemiology & Public Health (CIBER en Epidemiología y Salud Pública - CIBERESP), Avda. Monforte de Lemos, 3-5, 28029 Madrid, Spain; Barcelona Institute of Global Health (ISGlobal), Carrer Del Dr. Aiguader, 88, 08003 Barcelona, Spain; University Pompeu Fabra, Plaça de La Mercè, 10-12, 08002 Barcelona, Spain; Hospital Del Mar Medical Research Institute (IMIM), Carrer Del Dr. Aiguader, 88, 08003 Barcelona, Spain.
| | - Adonina Tardón
- Consortium for Biomedical Research in Epidemiology & Public Health (CIBER en Epidemiología y Salud Pública - CIBERESP), Avda. Monforte de Lemos, 3-5, 28029 Madrid, Spain; Health Research Institute of Asturias (ISPA), University of Oviedo, Av. Del Hospital Universitario, 33011 Oviedo, Spain.
| | - José J Jiménez-Moleón
- Consortium for Biomedical Research in Epidemiology & Public Health (CIBER en Epidemiología y Salud Pública - CIBERESP), Avda. Monforte de Lemos, 3-5, 28029 Madrid, Spain; Department of Preventive Medicine and Public Health, University of Granada, Av. de La Investigación, 11, 18016 Granada, Spain; Institute of Health Research IBS., Granada, Spain.
| | - Ana Molina-Barceló
- Cancer and Public Health Area, The Foundation for the Promotion of Health and Biomedical Research of Valencia Region (FISABIO), Av. de Catalunya, 21, 46020 Valencia, Spain.
| | - Nuria Aragonés
- Consortium for Biomedical Research in Epidemiology & Public Health (CIBER en Epidemiología y Salud Pública - CIBERESP), Avda. Monforte de Lemos, 3-5, 28029 Madrid, Spain; Cancer Surveillance and Registry Unit, Division of Public Health, Department of Health of Madrid, C. López de Hoyos, 35, 28002 Madrid, Spain.
| | - Manolis Kogevinas
- Consortium for Biomedical Research in Epidemiology & Public Health (CIBER en Epidemiología y Salud Pública - CIBERESP), Avda. Monforte de Lemos, 3-5, 28029 Madrid, Spain; Barcelona Institute of Global Health (ISGlobal), Carrer Del Dr. Aiguader, 88, 08003 Barcelona, Spain; University Pompeu Fabra, Plaça de La Mercè, 10-12, 08002 Barcelona, Spain; Hospital Del Mar Medical Research Institute (IMIM), Carrer Del Dr. Aiguader, 88, 08003 Barcelona, Spain.
| | - Marina Pollán
- Cancer and Environmental Epidemiology Unit, Department of Epidemiology of Chronic Diseases, National Center for Epidemiology, Instituto de Salud Carlos III (Carlos III Institute of Health), Avda. Monforte de Lemos, 5, 28029 Madrid, Spain; Consortium for Biomedical Research in Epidemiology & Public Health (CIBER en Epidemiología y Salud Pública - CIBERESP), Avda. Monforte de Lemos, 3-5, 28029 Madrid, Spain.
| | - Beatriz Pérez-Gómez
- Consortium for Biomedical Research in Epidemiology & Public Health (CIBER en Epidemiología y Salud Pública - CIBERESP), Avda. Monforte de Lemos, 3-5, 28029 Madrid, Spain; Department of Epidemiology of Chronic Diseases, National Center for Epidemiology, Instituto de Salud Carlos III (Carlos III Institute of Health), Avda. Monforte de Lemos, 5, 28029 Madrid, Spain.
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Speksnijder JP, van Marion ES, Baart EB, Steegers EA, Laven JS, Bertens LC. Living in a low socioeconomic status neighbourhood is associated with lower cumulative ongoing pregnancy rate after IVF treatment. Reprod Biomed Online 2024; 49:103908. [PMID: 38781882 DOI: 10.1016/j.rbmo.2024.103908] [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: 11/06/2023] [Revised: 02/09/2024] [Accepted: 02/12/2024] [Indexed: 05/25/2024]
Abstract
RESEARCH QUESTION Does an association exist between neighbourhood socioeconomic status (SES) and the cumulative rate of ongoing pregnancies after 2.5 years of IVF treatment? DESIGN A retrospective observational study involving 2669 couples who underwent IVF or IVF and intracytoplasmic sperm injection treatment between 2006 and 2020. Neighbourhood SES for each couple was determined based on their residential postal code. Subsequently, SES was categorized into low ( p80). Multivariable binary logistic regression analyses were conducted, with the cumulative ongoing pregnancy within 2.5 years as the outcome variable. The SES category (reference category: high), female age (reference category: 32-36 years), body mass index (reference category: 23-25 kg/m2), smoking status (yes/no), number of oocytes after the first ovarian stimulation, embryos usable for transfer or cryopreservation after the first cycle, duration of subfertility before treatment and insemination type were used as covariates. RESULTS A variation in ongoing pregnancy rates was observed among SES groups after the first fresh embryo transfer. No difference was found in the median number of IVF treatment cycles carried out. The cumulative ongoing pregnancy rates differed significantly between SES groups (low: 44%; medium: 51%; high: 56%; P < 0.001). Low neighbourhood SES was associated with significantly lower odds for achieving an ongoing pregnancy within 2.5 years (OR 0.66, 95% CI 0.52 to 0.84, P < 0.001). CONCLUSION Low neighbourhood SES compared with high neighbourhood SES is associated with reducing odds of achieving an ongoing pregnancy within 2.5 years of IVF treatment.
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Affiliation(s)
- Jeroen P Speksnijder
- Division of Reproductive Endocrinology and Infertility, Department of Obstetrics and Gynaecology, Erasmus MC, University Medical Center, PO Box 2040, 3000 CA Rotterdam, The Netherlands..
| | - Eva S van Marion
- Division of Reproductive Endocrinology and Infertility, Department of Obstetrics and Gynaecology, Erasmus MC, University Medical Center, PO Box 2040, 3000 CA Rotterdam, The Netherlands
| | - Esther B Baart
- Division of Reproductive Endocrinology and Infertility, Department of Obstetrics and Gynaecology, Erasmus MC, University Medical Center, PO Box 2040, 3000 CA Rotterdam, The Netherlands.; Department of Developmental Biology, Erasmus MC, University Medical Center, PO Box 2040, 3000 CA Rotterdam, The Netherlands
| | - Eric Ap Steegers
- Department of Obstetrics and Gynaecology, Erasmus MC, University Medical Center, PO Box 2040, 3000 CA Rotterdam, The Netherlands
| | - Joop Se Laven
- Division of Reproductive Endocrinology and Infertility, Department of Obstetrics and Gynaecology, Erasmus MC, University Medical Center, PO Box 2040, 3000 CA Rotterdam, The Netherlands
| | - Loes Cm Bertens
- Department of Obstetrics and Gynaecology, Erasmus MC, University Medical Center, PO Box 2040, 3000 CA Rotterdam, The Netherlands
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Huang Y, Li Y, Pan H, Han L. Global, regional, and national burden of neurological disorders in 204 countries and territories worldwide. J Glob Health 2023; 13:04160. [PMID: 38018250 PMCID: PMC10685084 DOI: 10.7189/jogh.13.04160] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2023] Open
Abstract
Background We aimed to determine the incidence and disability-adjusted life-years (DALYs) of neurological disorders worldwide from 1990 to 2019. Methods We obtained age-standardised incidence and DALY rates of neurological disorders in 204 countries and territories from 1990 to 2019 from the Global Burden of Disease (GBD) database. We determined trends stratified by age, sex, region, country, and Social Development Index (SDI) and the risk factors contributing to DALYs associated with these neurological disorders. Results The largest increases in the age-standardised incidence rates of neurological disorders in 1990-2019 occurred in four regions (East Asia: estimated annual percentage change (EAPC) = 0.19, tropical Latin America: EAPC = 0.07, Southern Latin America: EAPC = 0.03, Western Europe: EAPC = 0.03) and three countries (China: EAPC = 0.20, Ecuador: EAPC = 0.13, Italy: EAPC = 0.13). We observed the largest increases in age-standardised incidence rates for Parkinson disease, idiopathic epilepsy, and bipolar disorder, and in age-standardised DALY rates for Alzheimer disease and other dementias. High-SDI regions showed the highest EAPC for age-standardised incidence rates of Parkinson disease, depression, and motor neuron disease, and age-standardised DALY rates of neurological disorders. Conclusions There is a need to control the increase in age-standardised incidence rates of neurological disorders in East Asia, tropical Latin America, Southern Latin America, and Western Europe, particularly in China, Ecuador, and Italy.
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Affiliation(s)
- Yi Huang
- Department of Neurosurgery, The First Affiliated Hospital of Ningbo University, Ningbo, Zhejiang, China
| | - Yongan Li
- Department of Neurology, Suzhou Xiangcheng People's Hospital, Jiangsu, China
| | - Haiyan Pan
- The First Dongguan Affiliated Hospital,Guangdong Medical University
- School of Public Health, Guangdong Medical University, Dongguan, Guangdong, PR China
| | - Liyuan Han
- Center for Cardiovascular and Cerebrovascular Epidemiology and Translational Medicine, Ningbo Institute of Life and Health Industry, University of Chinese Academy of Sciences, Ningbo, China
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Li X, Yu B, Li Y, Meng H, Shen M, Yang Y, Zhou Z, Liu S, Tian Y, Xing X, Yin L. The impact of ambient air pollution on hospital admissions, length of stay and hospital costs for patients with diabetes mellitus and comorbid respiratory diseases in Panzhihua, Southwest China. J Glob Health 2023; 13:04118. [PMID: 37830139 PMCID: PMC10570759 DOI: 10.7189/jogh.13.04118] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/14/2023] Open
Abstract
Background There is limited evidence on association between air pollutants and hospital admissions, hospital cost and length of stay (LOS) among patients with diabetes mellitus (DM) and comorbid respiratory diseases (RD), especially in low- and middle-income countries (LMICs) with low levels of air pollution. Methods Daily data on RD-DM patients were collected in Panzhihua from 2016 to 2020. A generalised additive model (GAM) was used to explore the effect of air pollutants on daily hospital admissions, LOS and hospital cost. Attributable risk was employed to estimate RD-DM's burden due to exceeding air pollution exposure, using both 0 microgrammes per cubic metre (μg/m3) and WHO's 2021 air quality guidelines as reference. Results For each 10 ug/m3 increase of particles with an aerodynamic diameter <2.5 micron (μm) (PM2.5), particles with an aerodynamic diameter <10 μm (PM10), sulfur dioxide (SO2), nitrogen dioxide (NO2) and ozone (O3), the admissions of RD-DM patients increased by 7.25% (95% CI = 4.26 to 10.33), 5.59% (95% CI = 3.79 to 7.42), 10.10% (95% CI = 7.29 to 12.98), 12.33% (95% CI = 8.82 to 15.95) and -2.99% (95% CI = -4.08 to -1.90); per 1 milligramme per cubic metre (mg/m3) increase of carbon monoxide (CO) corresponded to a 25.77% (95% CI = 17.88 to 34.19) increment for admissions of RD-DM patients. For LOS and hospital cost, the six air pollutants showed similar effect. Given 0 μg/m3 as the reference, NO2 showed the maximum attributable fraction of 32.68% (95% CI = 25.12 to 39.42%), corresponding to an avoidable burden of 5661 (95% CI = 3611 to 5860) patients with RD-DM. Conclusions There is an association between PM2.5, PM10, SO2, NO2, and CO with increased hospital admissions, LOS and hospital cost in patients with RD-DM. Disease burden of RD-DM may be improved by formulating policies related to air pollutants exposure reduction, especially in LMICs with low levels of air pollution.
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Affiliation(s)
- Xianzhi Li
- Meteorological Medical Research Center, Panzhihua Central Hospital, Panzhihua, Sichuan Province, China
- Clinical Medical Research Center, Panzhihua Central Hospital, Panzhihua, Sichuan Province, China
- Dali University, Dali, Yunnan Province, China
| | - Bin Yu
- Institute for Disaster Management and Reconstruction, Sichuan University - Hong Kong Polytechnic University, Chengdu, Sichuan Province, China
| | - Yajie Li
- Tibet Center for Disease Control and Prevention, Lhasa, Tibet Autonomous Region, China
| | - Haorong Meng
- Yunnan Center for Disease Control and Prevention, Kunming, Yunnan Province, China
| | - Meiying Shen
- Nursing department, Panzhihua Central Hospital, Panzhihua, Sichuan Province, China
| | - Yan Yang
- Meteorological Medical Research Center, Panzhihua Central Hospital, Panzhihua, Sichuan Province, China
- Dali University, Dali, Yunnan Province, China
- Department of Respiratory and Critical Care Medicine, Panzhihua Central Hospital, Panzhihua, Sichuan Province, China
| | - Zonglei Zhou
- Department of Epidemiology, School of Public Health, Fudan University, Shanghai, China
| | - Shunjin Liu
- Meteorological Medical Research Center, Panzhihua Central Hospital, Panzhihua, Sichuan Province, China
- Clinical Medical Research Center, Panzhihua Central Hospital, Panzhihua, Sichuan Province, China
- Dali University, Dali, Yunnan Province, China
| | - Yunyun Tian
- Clinical Medical Research Center, Panzhihua Central Hospital, Panzhihua, Sichuan Province, China
- Dali University, Dali, Yunnan Province, China
| | - Xiangyi Xing
- Meteorological Medical Research Center, Panzhihua Central Hospital, Panzhihua, Sichuan Province, China
- Dali University, Dali, Yunnan Province, China
- Department of Pharmacy, Panzhihua Central Hospital, Panzhihua, Sichuan Province, China
| | - Li Yin
- Meteorological Medical Research Center, Panzhihua Central Hospital, Panzhihua, Sichuan Province, China
- Clinical Medical Research Center, Panzhihua Central Hospital, Panzhihua, Sichuan Province, China
- Dali University, Dali, Yunnan Province, China
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