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BACKGROUND: Benzene exposure has been associated with increased leukemia and other cancer risk; however, epidemiological evidence is inconsistent for the latter and confounding from smoking and alcohol was rarely adjusted. METHODS: We investigated associations of occupational benzene exposure and risk of leukemia, lymphoma, myeloma, lung, stomach, liver, and kidney cancers in a population-based cohort of 61,377 men ages 40-74. A job-exposure matrix, constructed by industrial hygienists specifically for the study population, was used to derive cumulative benzene exposure from all jobs held. Cox regressions were performed to estimate adjusted hazard ratios (aHR) and 95% confidence intervals (CI) for benzene-cancer risk associations with adjustment for potential confounders. RESULTS: Over 15-years of follow-up, 1,145 lung, 656 stomach, 445 liver, 243 kidney cancer cases, 100 leukemia, 124 lymphoma, and 46 myeloma cases were identified. Benzene exposure >550mg/m3 was associated with increased leukemia (aHR=2.3, 95%CI=1.1-4.5), lung (aHR=1.2, 95%CI=1.0-1.6), and stomach (aHR=1.4, 95%CI=1.0-1.9) cancer risk; benzene-exposure was associated with early cancer diagnosis age. The benzene-leukemia and -stomach cancer associations followed a linear dose-response pattern (Plinear=0.016 and 0.023), whereas benzene-lung cancer association was evident at higher exposure levels (Pnon-linear=0.027). Alcohol consumption modified the benzene-leukemia association (HR=3.0, 95%CI=1.1-8.3 for drinkers, aHR=0.9, 95%CI=0.4-2.0 for non-drinkers, Pinteraction=0.047). CONCLUSIONS: Benzene exposure was associated with increased leukemia, stomach, and lung cancer risk. Alcohol consumption may modify the benzene-leukemia association, although estimates are imprecise. IMPACT: Our study provides additional evidence that benzene exposure increases cancer risk beyond leukemia, information important for policymakers to develop programs to mitigate cancer risk among benzene-exposed workers.
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The domestic combustion of locally sourced smoky (bituminous) coal in Xuanwei and Fuyuan counties, China, is responsible for some of the highest lung cancer rates in the world. Recent research has pointed to methylated PAHs (mPAHs), particularly 5-methylchrysene (5MC), within coal combustion products as a driving factor. Here we describe measurements of mPAHs in Xuanwei and Fuyuan derived from controlled burnings (i.e., water boiling tests, WBT, n = 27) representing exposures during stove use, and an exposure assessment (EA) study (n=116) representing 24 h weighted exposures. Using smoky coal leads to significantly higher concentrations of known and likely human carcinogens than using smokeless coal, including 5MC (3.7 ng/m3 vs. 1.0 ng/m3 for EA samples and 100.8 ng/m3 vs. 2.2 ng/m3 for WBT samples), benzo[a]pyrene (38.0 ng/m3 vs. 7.9 ng/m3 for EA samples and 455.3 ng/m3 vs. 12.0 ng/m3 for WBT samples), and 7,12-dimethylbenz[a]anthracene (1.9 ng/m3 vs. 0.2 ng/m3 for EA samples and 47.7 ng/m3 vs. 0.6 ng/m3 for WBT samples). Mixed effect models for both EA samples and WBT samples revealed clear variation in mPAHs concentrations depending on smoky coal source while stove ventilation was consistently found to reduce measured concentrations (by up to nine fold and 65 fold for EA and WBT samples respectively when using smoky coal). Fuel type had a larger influence on mPAHs concentrations than stove type. These findings indicate that users of smoky coal experience exposure to many PAHs, including known and suspected human carcinogens (especially during cooking activities), many of which are not routinely tested for. Collectively, this provides insights into the potential etiologies of lung cancer in the region and further highlights the importance of clean fuel transitions and stove refinements as the final goal for reducing household air pollution and its associated health risks.
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OBJECTIVES: To summarise the rationale, workflow and recommendations for the conduct of exposure assessment critiques in key human studies evaluated for International Agency for Research on Cancer (IARC) Monographs on the Identification of Carcinogenic Hazards. METHODS: Approaches to evaluating exposure assessment quality in human cancer and mechanistic studies were reviewed according to the precepts outlined in the IARC Monographs Preamble, using two agents as case studies. Exposure assessment 'domains', that is, salient aspects of exposure assessment for the agent under evaluation, were selected for review across the key human studies. RESULTS: The case studies of night shift work (volume 124) and 1,1,1-trichloroethane (volume 130) used a common approach, tailored to the agents' specific exposure scenarios, to evaluate exposure assessment quality. Based on the experiences of IARC Working Groups to date, the implementation of exposure assessment critique requires the need for agent-specific knowledge, consideration of the validity of time-varying exposure metrics related to duration and intensity, and transparent, concise reviews that prioritise the most important strengths and limitations of exposure assessment methods used in human studies. CONCLUSIONS: Exposure assessment has not historically been a fully appreciated component for evaluating the quality of epidemiological studies in cancer hazard identification. Exposure assessment critique in key human cancer and mechanistic studies is now an integral part of IARC Monographs evaluations and its conduct will continue to evolve as new agents are evaluated. The approaches identified here should be considered as a potential framework by others when evaluating the exposure assessment component of epidemiological studies for systematic reviews.
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Advanced glycation end-products (AGEs), formed endogenously or obtained exogenously from diet, may contribute to chronic inflammation, intracellular signaling alterations, and pathogenesis of several chronic diseases including colorectal cancer (CRC). However, the role of AGEs in CRC survival is less known. The associations of pre-diagnostic circulating AGEs and their soluble receptor (sRAGE) with CRC-specific and overall mortality were estimated using multivariable-adjusted Cox proportional hazards regression among 1369 CRC cases in the European Prospective Investigation into Cancer and Nutrition (EPIC) study. Concentrations of major plasma AGEs, Nε-[carboxy-methyl]lysine (CML), Nε-[carboxy-ethyl]lysine (CEL) and Nδ-[5-hydro-5-methyl-4-imidazolon-2-yl]-ornithine (MG-H1), were measured using ultra-performance liquid chromatography mass-spectrometry. sRAGE was assessed by enzyme-linked immunosorbent assay. Over a mean follow-up period of 96 months, 693 deaths occurred of which 541 were due to CRC. Individual and combined AGEs were not statistically significantly associated with CRC-specific or overall mortality. However, there was a possible interaction by sex for CEL (Pinteraction = .05). Participants with higher sRAGE had a higher risk of dying from CRC (HRQ5vs.Q1 = 1.67, 95% CI: 1.21-2.30, Ptrend = .02) or any cause (HRQ5vs.Q1 = 1.38, 95% CI: 1.05-1.83, Ptrend = .09). These associations tended to be stronger among cases with diabetes (Pinteraction = .03) and pre-diabetes (Pinteraction <.01) before CRC diagnosis. Pre-diagnostic AGEs were not associated with CRC-specific and overall mortality in individuals with CRC. However, a positive association was observed for sRAGE. Our findings may stimulate further research on the role of AGEs and sRAGE in survival among cancer patients with special emphasis on potential effect modifications by sex and diabetes.
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BACKGROUND: Long-term exposure to ambient air pollution has been linked with all-cause mortality and cardiovascular and respiratory diseases. Suggestive associations between ambient air pollutants and neurodegeneration have also been reported, but due to the small effect and relatively rare outcomes evidence is yet inconclusive. Our aim was to investigate the associations between long-term air pollution exposure and mortality from neurodegenerative diseases. METHODS: A Dutch national cohort of 10.8 million adults aged ≥30 years was followed from 2013 until 2019. Annual average concentrations of air pollutants (ultra-fine particles (UFP), nitrogen dioxide (NO2), fine particles (PM2.5 and PM10) and elemental carbon (EC)) were estimated at the home address at baseline, using land-use regression models. The outcome variables were mortality due to amyotrophic lateral sclerosis (ALS), Parkinson's disease, non-vascular dementia, Alzheimer's disease, and multiple sclerosis (MS). Hazard ratios (HR) were estimated using Cox models, adjusting for individual and area-level socio-economic status covariates. RESULTS: We had a follow-up of 71 million person-years. The adjusted HRs for non-vascular dementia were significantly increased for NO2 (1.03; 95% confidence interval (CI) 1.02-1.05) and PM2.5 (1.02; 95%CI 1.01-1.03) per interquartile range (IQR; 6.52 and 1.47 µg/m3, respectively). The association with PM2.5 was also positive for ALS (1.02; 95%CI 0.97-1.07). These associations remained positive in sensitivity analyses and two-pollutant models. UFP was not associated with any outcome. No association with air pollution was found for Parkinson's disease and MS. Inverse associations were found for Alzheimer's disease. CONCLUSION: Our findings, using a cohort of more than 10 million people, provide further support for associations between long-term exposure to air pollutants (PM2.5 and particularly NO2) and mortality of non-vascular dementia. No associations were found for Parkinson and MS and an inverse association was observed for Alzheimer's disease.
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Addressing the challenge of mapping hyperlocal air pollution in areas without local monitoring, we evaluated unsupervised transfer learning-based land-use regression (LUR) models developed using mobile monitoring data from other cities: CORrelation ALignment (Coral) and its inverse distance-weighted modification (IDW_Coral). These models mitigated domain shifts and transferred patterns learned from mobile air quality monitoring campaigns in Copenhagen and Rotterdam to estimate annual average air pollution levels in Amsterdam (50m road segments) without involving any Amsterdam measurements in model development. For nitrogen dioxide (NO2), IDW_Coral outperformed Copenhagen and Rotterdam LUR models directly applied to Amsterdam, achieving MAE (4.47 µg/m3) and RMSE (5.36 µg/m3) comparable to a locally fitted LUR model (AMS_SLR) developed using Amsterdam mobile measurements collected for 160 days. IDW_Coral yielded an R2 of 0.35, similar to that of the AMS_SLR based on 20 collection days, suggesting a minimum requirement of 20-day mobile monitoring to capture city-specific insights. For ultrafine particles (UFP), IDW_Coral's citywide predictions strongly correlated with previously published mixed-effect models fitted with 160-day Amsterdam measurements (Pearson correlation of 0.71 for UFP and 0.72 for NO2). IDW_Coral demands no direct measurements in the target area, showcasing its potential for large-scale applications and offering significant economic efficiencies in executing mobile monitoring campaigns.
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Air Pollutants , Air Pollution , Environmental Monitoring , Environmental Monitoring/methods , Particulate Matter , Nitrogen Dioxide/analysis , CitiesABSTRACT
Per- and polyfluoroalkyl substances (PFAS) exposure is a potential risk factor for thyroid cancer and may be a contributor to the increasing thyroid cancer incidence rates. A systematic review and meta-analysis was performed to summarize all human studies to date investigating the association between PFAS exposure and thyroid cancer. A search of the National Library of Medicine and National Institutes of Health PubMed and Scopus databases was done to identify relevant articles published in English through January 2024. Studies reporting the association between PFAS exposure and thyroid cancer using odds ratios (OR) were included in the meta-analysis with summary estimate calculated using a random effects model (n=5). Perfluorooctanoic acid (PFOA) was the most investigated PFAS. Results of the included studies varied, ranging from significant positive to significant negative associations with thyroid cancer incidence for different PFAS. Meta-analyses of PFOA, Perfluorooctanesulfonic acid (PFOS), perfluorononanoic acid (PFNA), perfluorohexanesulfonic acid (PFHxS) were not significant. This comprehensive review of the current literature highlights the limited knowledge and inconsistent results of this association. Large longitudinal cohort studies with varying time between sample collection and thyroid cancer diagnosis are needed to better understand the role of PFAS exposure on thyroid carcinogenesis.
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Air pollution exposure is typically assessed at the front door where people live in large-scale epidemiological studies, overlooking individuals' daily mobility out-of-home. However, there is limited evidence that incorporating mobility data into personal air pollution assessment improves exposure assessment compared to home-based assessments. This study aimed to compare the agreement between mobility-based and home-based assessments with personal exposure measurements. We measured repeatedly particulate matter (PM2.5) and black carbon (BC) using a sample of 41 older adults in the Netherlands. In total, 104 valid 24 h average personal measurements were collected. Home-based exposures were estimated by combining participants' home locations and temporal-adjusted air pollution maps. Mobility-based estimates of air pollution were computed based on smartphone-based tracking data, temporal-adjusted air pollution maps, indoor-outdoor penetration, and travel mode adjustment. Intraclass correlation coefficients (ICC) revealed that mobility-based estimates significantly improved agreement with personal measurements compared to home-based assessments. For PM2.5, agreement increased by 64% (ICC: 0.39-0.64), and for BC, it increased by 21% (ICC: 0.43-0.52). Our findings suggest that adjusting for indoor-outdoor pollutant ratios in mobility-based assessments can provide more valid estimates of air pollution than the commonly used home-based assessments, with no added value observed from travel mode adjustments.
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Air Pollutants , Air Pollution , Environmental Exposure , Particulate Matter , Humans , Particulate Matter/analysis , Air Pollutants/analysis , Netherlands , Environmental Monitoring/methods , Male , Female , AgedABSTRACT
Background: Many studies reported associations between long-term exposure to environmental factors and mortality; however, little is known on the combined effects of these factors and health. We aimed to evaluate the association between external exposome and all-cause mortality in large administrative and traditional adult cohorts in Europe. Methods: Data from six administrative cohorts (Catalonia, Greece, Rome, Sweden, Switzerland and the Netherlands, totaling 27,913,545 subjects) and three traditional adult cohorts (CEANS-Sweden, EPIC-NL-the Netherlands, KORA-Germany, totaling 57,653 participants) were included. Multiple exposures were assigned at the residential addresses, and were divided into three a priori defined domains: (1) air pollution [fine particulate matter (PM2.5), nitrogen dioxide (NO2), black carbon (BC) and warm-season Ozone (warm-O3)]; (2) land/built environment (Normalized Difference Vegetation Index-NDVI, impervious surfaces, and distance to water); (3) air temperature (cold- and warm-season mean and standard deviation). Each domain was synthesized through Principal Component Analysis (PCA), with the aim of explaining at least 80% of its variability. Cox proportional-hazards regression models were applied and the total risk of the external exposome was estimated through the Cumulative Risk Index (CRI). The estimates were adjusted for individual- and area-level covariates. Results: More than 205 million person-years at risk and more than 3.2 million deaths were analyzed. In single-component models, IQR increases of the first principal component of the air pollution domain were associated with higher mortality [HRs ranging from 1.011 (95% CI: 1.005-1.018) for the Rome cohort to 1.076 (1.071-1.081) for the Swedish cohort]. In contrast, lower levels of the first principal component of the land/built environment domain, pointing to reduced vegetation and higher percentage of impervious surfaces, were associated with higher risks. Finally, the CRI of external exposome increased mortality for almost all cohorts. The associations found in the traditional adult cohorts were generally consistent with the results from the administrative ones, albeit without reaching statistical significance. Discussion: Various components of the external exposome, analyzed individually or in combination, were associated with increased mortality across European cohorts. This sets the stage for future research on the connections between various exposure patterns and human health, aiding in the planning of healthier cities.
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BACKGROUND: Overweight and obesity impose a considerable individual and social burden, and the urban environments might encompass factors that contribute to obesity. Nevertheless, there is a scarcity of research that takes into account the simultaneous interaction of multiple environmental factors. OBJECTIVES: Our objective was to perform an exposome-wide association study of body mass index (BMI) in a multicohort setting of 15 studies. METHODS: Studies were affiliated with the Dutch Geoscience and Health Cohort Consortium (GECCO), had different population sizes (688-141,825), and covered the entire Netherlands. Ten studies contained general population samples, others focused on specific populations including people with diabetes or impaired hearing. BMI was calculated from self-reported or measured height and weight. Associations with 69 residential neighborhood environmental factors (air pollution, noise, temperature, neighborhood socioeconomic and demographic factors, food environment, drivability, and walkability) were explored. Random forest (RF) regression addressed potential nonlinear and nonadditive associations. In the absence of formal methods for multimodel inference for RF, a rank aggregation-based meta-analytic strategy was used to summarize the results across the studies. RESULTS: Six exposures were associated with BMI: five indicating neighborhood economic or social environments (average home values, percentage of high-income residents, average income, livability score, share of single residents) and one indicating the physical activity environment (walkability in 5-km buffer area). Living in high-income neighborhoods and neighborhoods with higher livability scores was associated with lower BMI. Nonlinear associations were observed with neighborhood home values in all studies. Lower neighborhood home values were associated with higher BMI scores but only for values up to 300,000. The directions of associations were less consistent for walkability and share of single residents. DISCUSSION: Rank aggregation made it possible to flexibly combine the results from various studies, although between-study heterogeneity could not be estimated quantitatively based on RF models. Neighborhood social, economic, and physical environments had the strongest associations with BMI. https://doi.org/10.1289/EHP13393.
Subject(s)
Body Mass Index , Environmental Exposure , Exposome , Humans , Netherlands , Environmental Exposure/statistics & numerical data , Residence Characteristics/statistics & numerical data , Male , Female , Obesity/epidemiology , Cohort Studies , Random ForestSubject(s)
Brain Neoplasms , Humans , Prospective Studies , Cell Phone , Cell Phone Use/statistics & numerical dataABSTRACT
BACKGROUND: Small airways obstruction (SAO) has been associated with occupational exposures. Whether exposure to harmful occupational agents impacts the survival of people with SAO is unknown. Our aim was to estimate the mortality risk associated with occupational exposures among people with SAO. METHODS: We used data from UK Biobank participants with SAO, defined as a ratio of forced expiratory volume in three seconds to forced expiratory volume in six seconds (FEV3/FEV6) below the lower limit of normal. We assigned lifetime occupational exposures to participants with available occupational histories using the ALOHA+ Job Exposure Matrix. Mortality data were provided by the National Death Registries. We used Cox regression to assess the association of all-cause mortality with lifetime occupational exposures (vapours, gases, dusts, fumes-VGDF; solvents; pesticides; metals), adjusting for potential confounders. RESULTS: The 13,942 participants with SAO had a mean age of 56±7 years, 59% were females and 94.2% were of White ancestry. Overall, there were 457 deaths over a median follow-up of 12.8 years. A greater mortality risk was associated with exposure to VGDF, with hazard ratios of 1.32 (95%CI: 1.04-1.78) for low levels and 1.41 (95%CI: 1.11-1.78) for moderate levels of cumulative exposure. There was no evidence of association for the other occupational exposures. CONCLUSION: Lifetime occupational exposure to VGDF in people with SAO may have a detrimental effect on their survival. Future respiratory health surveillance programmes of people exposed to VGDF should consider assessment for SAO and focus on primary prevention through adequate exposure control.
Subject(s)
Occupational Exposure , Humans , Occupational Exposure/adverse effects , Female , Male , Middle Aged , Airway Obstruction/mortality , Airway Obstruction/etiology , Airway Obstruction/epidemiology , Risk Factors , Proportional Hazards Models , Aged , Adult , United Kingdom/epidemiology , Forced Expiratory VolumeABSTRACT
OBJECTIVES: Previous studies established a causal relationship between occupational benzene exposure and acute myeloid leukemia (AML). However, mixed results have been reported for associations between benzene exposure and other myeloid and lymphoid malignancies. Our work examined whether occupational benzene exposure is associated with increased mortality from overall lymphohaematopoietic (LH) cancer and major subtypes. METHODS: Mortality records were linked to a Swiss census-based cohort from two national censuses in 1990 and 2000. Cases were defined as having any LH cancers registered in death certificates. We assessed occupational exposure by applying a quantitative benzene job-exposure matrix (BEN-JEM) to census-reported occupations. Exposure was calculated as the products of exposure proportions and levels (P × L). Cox proportional hazards models were used to calculate LH cancer death hazard ratios (HR) and 95% confidence intervals (CI) associated with benzene exposure, continuously and in ordinal categories. RESULTS: Our study included approximately 2.97 million persons and 13 415 LH cancer cases, including 3055 cases with benzene exposure. We observed increased mortality risks per unit (P × L) increase in continuous benzene exposure for AML (HR 1.03, 95% CI 1.00-1.06) and diffuse large B-cell lymphoma (HR 1.09, 95% CI 1.04-1.14). When exposure was assessed categorically, increasing trends in risks were observed with increasing benzene exposure for AML (P=0.04), diffuse large B-cell lymphoma (P=0.02), and follicular lymphoma (P=0.05). CONCLUSION: In a national cohort from Switzerland, we found that occupational exposure to benzene is associated with elevated mortality risks for AML, diffuse large B-cell lymphoma, and possibly follicular lymphoma.
Subject(s)
Benzene , Occupational Exposure , Humans , Benzene/toxicity , Benzene/adverse effects , Occupational Exposure/adverse effects , Switzerland/epidemiology , Male , Female , Middle Aged , Cohort Studies , Adult , Leukemia, Myeloid, Acute/mortality , Leukemia, Myeloid, Acute/epidemiology , Leukemia, Myeloid, Acute/chemically induced , Aged , Occupational Diseases/mortality , Occupational Diseases/epidemiology , Occupational Diseases/chemically induced , Proportional Hazards Models , Risk FactorsABSTRACT
OBJECTIVE: Headache is one of the most prevalent and disabling health conditions globally. We prospectively explored the urban exposome in relation to weekly occurrence of headache episodes using data from the Dutch population-based Occupational and Environmental Health Cohort Study (AMIGO). MATERIAL AND METHODS: Participants (N = 7,339) completed baseline and follow-up questionnaires in 2011 and 2015, reporting headache frequency. Information on the urban exposome covered 80 exposures across 10 domains, such as air pollution, electromagnetic fields, and lifestyle and socio-demographic characteristics. We first identified all relevant exposures using the Boruta algorithm and then, for each exposure separately, we estimated the average treatment effect (ATE) and related standard error (SE) by training causal forests adjusted for age, depression diagnosis, painkiller use, general health indicator, sleep disturbance index and weekly occurrence of headache episodes at baseline. RESULTS: Occurrence of weekly headache was 12.5 % at baseline and 11.1 % at follow-up. Boruta selected five air pollutants (NO2, NOX, PM10, silicon in PM10, iron in PM2.5) and one urban temperature measure (heat island effect) as factors contributing to the occurrence of weekly headache episodes at follow-up. The estimated causal effect of each exposure on weekly headache indicated positive associations. NO2 showed the largest effect (ATE = 0.007 per interquartile range (IQR) increase; SE = 0.004), followed by PM10 (ATE = 0.006 per IQR increase; SE = 0.004), heat island effect (ATE = 0.006 per one-degree Celsius increase; SE = 0.007), NOx (ATE = 0.004 per IQR increase; SE = 0.004), iron in PM2.5 (ATE = 0.003 per IQR increase; SE = 0.004), and silicon in PM10 (ATE = 0.003 per IQR increase; SE = 0.004). CONCLUSION: Our results suggested that exposure to air pollution and heat island effects contributed to the reporting of weekly headache episodes in the study population.
Subject(s)
Air Pollutants , Air Pollution , Environmental Exposure , Exposome , Headache , Humans , Headache/epidemiology , Headache/chemically induced , Male , Female , Netherlands/epidemiology , Middle Aged , Prospective Studies , Adult , Environmental Exposure/statistics & numerical data , Air Pollutants/analysis , Air Pollution/statistics & numerical data , Air Pollution/adverse effects , Environmental Health , Cohort Studies , Surveys and Questionnaires , Particulate Matter/analysis , Urban Population/statistics & numerical dataABSTRACT
OBJECTIVE: Within the scope of the Exposome Project for Health and Occupational Research on applying the exposome concept to working life health, we aimed to provide a broad overview of the status of knowledge on occupational exposures and associated health effects across multiple noncommunicable diseases (NCDs) to help inform research priorities. METHODS: We conducted a narrative review of occupational risk factors that can be considered to have "consistent evidence for an association," or where there is "limited/inadequate evidence for an association" for 6 NCD groups: nonmalignant respiratory diseases; neurodegenerative diseases; cardiovascular/metabolic diseases; mental disorders; musculoskeletal diseases; and cancer. The assessment was done in expert sessions, primarily based on systematic reviews, supplemented with narrative reviews, reports, and original studies. Subsequently, knowledge gaps were identified, e.g. based on missing information on exposure-response relationships, gender differences, critical time-windows, interactions, and inadequate study quality. RESULTS: We identified over 200 occupational exposures with consistent or limited/inadequate evidence for associations with one or more of 60+ NCDs. Various exposures were identified as possible risk factors for multiple outcomes. Examples are diesel engine exhaust and cadmium, with consistent evidence for lung cancer, but limited/inadequate evidence for other cancer sites, respiratory, neurodegenerative, and cardiovascular diseases. Other examples are physically heavy work, shift work, and decision latitude/job control. For associations with limited/inadequate evidence, new studies are needed to confirm the association. For risk factors with consistent evidence, improvements in study design, exposure assessment, and case definition could lead to a better understanding of the association and help inform health-based threshold levels. CONCLUSIONS: By providing an overview of knowledge gaps in the associations between occupational exposures and their health effects, our narrative review will help setting priorities in occupational health research. Future epidemiological studies should prioritize to include large sample sizes, assess exposures prior to disease onset, and quantify exposures. Potential sources of biases and confounding need to be identified and accounted for in both original studies and systematic reviews.
Subject(s)
Neoplasms , Noncommunicable Diseases , Occupational Exposure , Humans , Occupational Exposure/adverse effects , Occupational Exposure/statistics & numerical data , Occupational Exposure/analysis , Noncommunicable Diseases/epidemiology , Neoplasms/epidemiology , Neoplasms/etiology , Risk Factors , Cardiovascular Diseases/etiology , Cardiovascular Diseases/epidemiology , Musculoskeletal Diseases/etiology , Musculoskeletal Diseases/epidemiology , Occupational Diseases/epidemiology , Occupational Diseases/etiology , Neurodegenerative Diseases/etiology , Neurodegenerative Diseases/epidemiology , Respiratory Tract Diseases/epidemiology , Respiratory Tract Diseases/etiology , Exposome , Mental Disorders/epidemiology , Mental Disorders/etiologyABSTRACT
This randomized crossover study investigated the metabolic and mRNA alterations associated with exposure to high and low traffic-related air pollution (TRAP) in 50 participants who were either healthy or were diagnosed with chronic pulmonary obstructive disease (COPD) or ischemic heart disease (IHD). For the first time, this study combined transcriptomics and serum metabolomics measured in the same participants over multiple time points (2 h before, and 2 and 24 h after exposure) and over two contrasted exposure regimes to identify potential multiomic modifications linked to TRAP exposure. With a multivariate normal model, we identified 78 metabolic features and 53 mRNA features associated with at least one TRAP exposure. Nitrogen dioxide (NO2) emerged as the dominant pollutant, with 67 unique associated metabolomic features. Pathway analysis and annotation of metabolic features consistently indicated perturbations in the tryptophan metabolism associated with NO2 exposure, particularly in the gut-microbiome-associated indole pathway. Conditional multiomics networks revealed complex and intricate mechanisms associated with TRAP exposure, with some effects persisting 24 h after exposure. Our findings indicate that exposure to TRAP can alter important physiological mechanisms even after a short-term exposure of a 2 h walk. We describe for the first time a potential link between NO2 exposure and perturbation of the microbiome-related pathways.
Subject(s)
Air Pollutants , Air Pollution , Gastrointestinal Microbiome , Humans , Male , London , Female , Middle Aged , Cross-Over Studies , Traffic-Related Pollution , Nitrogen DioxideABSTRACT
The Cohort Study of Mobile Phone Use and Health (COSMOS) has repeatedly collected self-reported and operator-recorded data on mobile phone use. Assessing health effects using self-reported information is prone to measurement error, but operator data were available prospectively for only part of the study population and did not cover past mobile phone use. To optimize the available data and reduce bias, we evaluated different statistical approaches for constructing mobile phone exposure histories within COSMOS. We evaluated and compared the performance of four regression calibration (RC) methods (simple, direct, inverse, and generalized additive model for location, shape, and scale), complete-case (CC) analysis and multiple imputation (MI) in a simulation study with a binary health outcome. We used self-reported and operator-recorded mobile phone call data collected at baseline (2007-2012) from participants in Denmark, Finland, the Netherlands, Sweden, and the UK. Parameter estimates obtained using simple, direct, and inverse RC methods were associated with less bias and lower mean squared error than those obtained with CC analysis or MI. We showed that RC methods resulted in more accurate estimation of the relation between mobile phone use and health outcomes, by combining self-reported data with objective operator-recorded data available for a subset of participants.
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Potential differential and non-differential recall error in mobile phone use (MPU) in the multinational MOBI-Kids case-control study were evaluated. We compared self-reported MPU with network operator billing record data up to 3 months, 1 year, and 2 years before the interview date from 702 subjects aged between 10 and 24 years in eight countries. Spearman rank correlations, Kappa coefficients and geometric mean ratios (GMRs) were used. No material differences in MPU recall estimates between cases and controls were observed. The Spearman rank correlation coefficients between self-reported and recorded MPU in the most recent 3 months were 0.57 and 0.59 for call number and for call duration, respectively. The number of calls was on average underestimated by the participants (GMR = 0.69), while the duration of calls was overestimated (GMR = 1.59). Country, years since start of using a mobile phone, age at time of interview, and sex did not appear to influence recall accuracy for either call number or call duration. A trend in recall error was seen with level of self-reported MPU, with underestimation of use at lower levels and overestimation of use at higher levels for both number and duration of calls. Although both systematic and random errors in self-reported MPU among participants were observed, there was no evidence of differential recall error between cases and controls. Nonetheless, these sources of exposure measurement error warrant consideration in interpretation of the MOBI-Kids case-control study results on the association between children's use of mobile phones and potential brain cancer risk.
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INTRODUCTION: Environmental exposures, such as ambient air pollution and household fuel use affect health and under-5 mortality (U5M) but there is a paucity of data in the Global South. This study examined early-life exposure to ambient particulate matter with a diameter of 2.5 µm or less (PM2.5), alongside household characteristics (including self-reported household fuel use), and their relationship with U5M in the Navrongo Health and Demographic Surveillance Site (HDSS) in northern Ghana. METHODS: We employed Satellite-based spatiotemporal models to estimate the annual average PM2.5 concentrations with the Navrongo HDSS area (1998 to 2016). Early-life exposure levels were determined by pollution estimates at birth year. Socio-demographic and household data, including cooking fuel, were gathered during routine surveillance. Cox proportional hazards models were applied to assess the link between early-life PM2.5 exposure and U5M, accounting for child, maternal, and household factors. FINDINGS: We retrospectively studied 48,352 children born between 2007 and 2017, with 1872 recorded deaths, primarily due to malaria, sepsis, and acute respiratory infection. Mean early-life PM2.5 was 39.3 µg/m3, and no significant association with U5M was observed. However, Children from households using "unclean" cooking fuels (wood, charcoal, dung, and agricultural waste) faced a 73 % higher risk of death compared to those using clean fuels (adjusted HR = 1.73; 95 % CI: 1.29, 2.33). Being born female or to mothers aged 20-34 years were linked to increased survival probabilities. INTERPRETATION: The use of "unclean" cooking fuel in the Navrongo HDSS was associated with under-5 mortality, highlighting the need to improve indoor air quality by introducing cleaner fuels.
Subject(s)
Air Pollution, Indoor , Cooking , Particulate Matter , Ghana , Humans , Child, Preschool , Infant , Female , Particulate Matter/analysis , Male , Air Pollution, Indoor/statistics & numerical data , Air Pollution, Indoor/analysis , Air Pollution, Indoor/adverse effects , Environmental Exposure/statistics & numerical data , Child Mortality , Air Pollutants/analysis , Family Characteristics , Retrospective Studies , Infant, Newborn , Air Pollution/statistics & numerical dataABSTRACT
Breast cancer is the second most common cancer globally. Most deaths from breast cancer are due to metastatic disease which often follows long periods of clinical dormancy1. Understanding the mechanisms that disrupt the quiescence of dormant disseminated cancer cells (DCC) is crucial for addressing metastatic progression. Infection with respiratory viruses (e.g. influenza or SARS-CoV-2) is common and triggers an inflammatory response locally and systemically2,3. Here we show that influenza virus infection leads to loss of the pro-dormancy mesenchymal phenotype in breast DCC in the lung, causing DCC proliferation within days of infection, and a greater than 100-fold expansion of carcinoma cells into metastatic lesions within two weeks. Such DCC phenotypic change and expansion is interleukin-6 (IL-6)-dependent. We further show that CD4 T cells are required for the maintenance of pulmonary metastatic burden post-influenza virus infection, in part through attenuation of CD8 cell responses in the lungs. Single-cell RNA-seq analyses reveal DCC-dependent impairment of T-cell activation in the lungs of infected mice. SARS-CoV-2 infected mice also showed increased breast DCC expansion in lungs post-infection. Expanding our findings to human observational data, we observed that cancer survivors contracting a SARS-CoV-2 infection have substantially increased risks of lung metastatic progression and cancer-related death compared to cancer survivors who did not. These discoveries underscore the significant impact of respiratory viral infections on the resurgence of metastatic cancer, offering novel insights into the interconnection between infectious diseases and cancer metastasis.