The Use of Carbonaceous Particle Exposure Metrics in Health Impact Calculations.
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ABSTRACT:
SUBMITTER: Olstrup H
PROVIDER: S-EPMC4808912 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:BACKGROUND:Epidemiological evidence on the health effects of ultrafine particles (UFP) remains insufficient to infer a causal relationship that is largely due to different size ranges and exposure metrics examined across studies. Moreover, evidence regarding the association between UFP and cardiovascular disease at a sub-daily timescale is lacking. OBJECTIVE:We investigated the relationship between different particle metrics, including particle number (PNC), length (PLC), and surface area (PSC) concentrations, and myocardial infarction (MI) at an hourly timescale. METHODS:We collected hourly air pollution and meteorological data from fixed urban background monitoring sites and hourly nonfatal MI cases from a MI registry in Augsburg, Germany, during 2005-2015. We conducted a time-stratified case-crossover analysis with conditional logistic regression to estimate the association between hourly particle metrics and MI cases, adjusted for air temperature and relative humidity. We also examined the independent effects of a certain particle metric in two-pollutant models by adjusting for copollutants, including particulate matter (PM) with an aerodynamic diameter of ?10?m or 2.5?m (PM10 and PM2.5, respectively), nitrogen dioxide, ozone, and black carbon. RESULTS:Overall, a total of 5,898 cases of nonfatal MI cases were recorded. Exploratory analyses showed similar associations across particle metrics in the first 6-12 h. For example, interquartile range increases in PNC within the size range of 10-100?nm, PLC, and PSC were associated with an increase of MI 6 h later by 3.27% [95% confidence interval (CI): 0.27, 6.37], 5.71% (95% CI: 1.79, 9.77), and 5.84% (95% CI: 1.04, 10.87), respectively. Positive, albeit imprecise, associations were observed for PNC within the size range of 10-30?nm and 100-500?nm. Effect estimates for PLC and PSC remained similar after adjustment for PM and gaseous pollutants. CONCLUSIONS:Transient exposure to particle number, length, and surface area concentrations or other potentially related exposures may trigger the onset of nonfatal myocardial infraction. https://doi.org/10.1289/EHP5478.
| S-EPMC7015564 | biostudies-literature
Project description:A health impact assessment (HIA) is an important tool for making informed decisions regarding the design and evaluation of environmental interventions. In this study, we performed a quantitative HIA for the population of Scania (1,247,993), the southernmost county in Sweden, in 2016. The impact of annual mean concentrations of particulate matter with an aerodynamic diameter <2.5 µm (PM2.5), modeled at their home residences for the year 2011, on mortality, asthma, dementia, autism spectrum disorders, preeclampsia and low birth weight (LBW) was explored. Concentration-response (C-R) functions were taken from epidemiological studies reporting meta-analyses when available, and otherwise from single epidemiological studies. The average level of PM2.5 experienced by the study population was 11.88 µg/m3. The PM2.5 exposure was estimated to cause 9-11% of cases of LBW and 6% of deaths from natural causes. Locally produced PM2.5 alone contributed to 2-9% of the cases of diseases and disorders investigated. Reducing concentrations to a maximum of 10 µg/m3 would, according to our estimations, reduce mortality by 3% and reduce cases of LBW by 2%. Further analyses of separate emission sources' distinct effects were also presented. Reduction of air pollution levels in the study area would, as expected, have a substantial effect on both mortality and adverse health outcomes. Reductions should be aimed for by local authorities and on national and even international levels.
| S-EPMC7400131 | biostudies-literature
Project description:BackgroundSemen quality parameters are potentially affected by nanomaterials in several ways: Inhaled nanosized particles are potent inducers of pulmonary inflammation, leading to the release of inflammatory mediators. Small amounts of particles may translocate from the lungs into the lung capillaries, enter the systemic circulation and ultimately reach the testes. Both the inflammatory response and the particles may induce oxidative stress which can directly affect spermatogenesis. Furthermore, spermatogenesis may be indirectly affected by changes in the hormonal milieu as systemic inflammation is a potential modulator of endocrine function. The aim of this study was to investigate the effects of pulmonary exposure to carbonaceous nanomaterials on sperm quality parameters in an experimental mouse model.MethodsEffects on sperm quality after pulmonary inflammation induced by carbonaceous nanomaterials were investigated by intratracheally instilling sexually mature male NMRI mice with four different carbonaceous nanomaterials dispersed in nanopure water: graphene oxide (18 μg/mouse/i.t.), Flammruss 101, Printex 90 and SRM1650b (0.1 mg/mouse/i.t. each) weekly for seven consecutive weeks. Pulmonary inflammation was determined by differential cell count in bronchoalveolar lavage fluid. Epididymal sperm concentration and motility were measured by computer-assisted sperm analysis. Epididymal sperm viability and morphological abnormalities were assessed manually using Hoechst 33,342/PI flourescent and Spermac staining, respectively. Epididymal sperm were assessed with regard to sperm DNA integrity (damage). Daily sperm production was measured in the testis, and testosterone levels were measured in blood plasma by ELISA.ResultsNeutrophil numbers in the bronchoalveolar fluid showed sustained inflammatory response in the nanoparticle-exposed groups one week after the last instillation. No significant changes in epididymal sperm parameters, daily sperm production or plasma testosterone levels were found.ConclusionDespite the sustained pulmonary inflammatory response, an eight week exposure to graphene oxide, Flammruss 101, Printex 90 and the diesel particle SRM1650b in the present study did not appear to affect semen parameters, daily sperm production or testosterone concentration in male NMRI mice.
| S-EPMC5793436 | biostudies-literature
Project description:MotivationParticle tracking is an important step of analysis in a variety of scientific fields and is particularly indispensable for the construction of cellular lineages from live images. Although various supervised machine learning methods have been developed for cell tracking, the diversity of the data still necessitates heuristic methods that require parameter estimations from small amounts of data. For this, solving tracking as a linear assignment problem (LAP) has been widely applied and demonstrated to be efficient. However, there has been no implementation that allows custom connection costs, parallel parameter tuning with ground truth annotations, and the functionality to preserve ground truth connections, limiting the application to datasets with partial annotations.ResultsWe developed LapTrack, a LAP-based tracker which allows including arbitrary cost functions and inputs, parallel parameter tuning and ground-truth track preservation. Analysis of real and artificial datasets demonstrates the advantage of custom metric functions for tracking score improvement from distance-only cases. The tracker can be easily combined with other Python-based tools for particle detection, segmentation and visualization.Availability and implementationLapTrack is available as a Python package on PyPi, and the notebook examples are shared at https://github.com/yfukai/laptrack. The data and code for this publication are hosted at https://github.com/NoneqPhysLivingMatterLab/laptrack-optimisation.Supplementary informationSupplementary data are available at Bioinformatics online.
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Project description:Heat waves have been linked to excess mortality and morbidity, and are projected to increase in frequency and intensity with a warming climate. This study compares exposure metrics to trigger heat wave and health warning systems (HHWS), and introduces a novel multi-level hybrid clustering method to identify potential dangerously hot days. Two-level and three-level hybrid clustering analysis as well as common indices used to trigger HHWS, including spatial synoptic classification (SSC), and the 90th, 95th, and 99th percentiles of minimum and relative minimum temperature (using a 10 day reference period), were calculated using a summertime weather dataset in Detroit from 1976 to 2006. The days classified as 'hot' with hybrid clustering analysis, SSC, minimum and relative minimum temperature methods differed by method type. SSC tended to include the days with, on average, 2.5 °C lower daily minimum temperature and 5.3 °C lower dew point than days identified by other methods. These metrics were evaluated by comparing their performance in predicting excess daily mortality. The 99th percentile of minimum temperature was generally the most predictive, followed by the three-level hybrid clustering method, the 95th percentile of minimum temperature, SSC and others. Our proposed clustering framework has more flexibility and requires less substantial meteorological prior information than the synoptic classification methods. Comparison of these metrics in predicting excess daily mortality suggests that metrics thought to better characterize physiological heat stress by considering several weather conditions simultaneously may not be the same metrics that are better at predicting heat-related mortality, which has significant implications in HHWSs.
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Project description:Suitable animal models are essential for translational research, especially in the case of complex, multifactorial conditions, such as obesity. The non-inbred mouse (Mus musculus) line Titan, also known as DU6, is one of the world’s longest selection experiments for high body mass and was previously described as a model for metabolic healthy (benign) obesity. The present study further characterizes the geno- and phenotypes of this non-inbred mouse line and testes its suitability as an interventional obesity model. In contrast to previous findings, our data suggest that Titan mice are metabolically unhealthy obese and short-lived. Line-specific patterns of genetic invariability are in accordance with observed phenotypic traits. Titan mice also show modifications in the liver transcriptome, proteome, and epigenome linked to metabolic (dys)regulations. Importantly, dietary intervention partially reversed the metabolic phenotype in Titan mice and significantly extended their life expectancy. Therefore, the Titan mouse line is a valuable resource for translational and interventional obesity research.
2022-05-01 | GSE150073 | GEO
Project description:The present study examines the effects of fuel [an ultralow sulfur diesel (ULSD) versus a 20% v/v soy-based biodiesel-80% v/v petroleum blend (B20)], temperature, load, vehicle, driving cycle, and active regeneration technology on gas- and particle-phase carbon emissions from light and medium heavy-duty diesel vehicles (L/MHDDV). The study is performed using chassis dynamometer facilities that support low-temperature operation (-6.7 °C versus 21.7 °C) and heavy loads up to 12 000 kg. Organic and elemental carbon (OC-EC) composition of aerosol particles is determined using a thermal-optical technique. Gas- and particle-phase semivolatile organic compound (SVOC) emissions collected using traditional filter and polyurethane foam sampling media are analyzed using advanced gas chromatograpy/mass spectrometry methods. Study-wide OC and EC emissions are 0.735 and 0.733 mg/km, on average. The emissions factors for diesel vehicles vary widely, and use of a catalyzed diesel particle filter (CDPF) device generally mutes the carbon particle emissions in the exhaust, which contains ~90% w/w gas-phase matter. Interestingly, replacing ULSD with B20 did not significantly influence SVOC emissions, for which sums range from 0.030 to 9.4 mg/km for the L/MHDDVs. However, both low temperature and vehicle cold-starts significantly increase SVOCs in the exhaust. Real-time particle measurements indicate vehicle regeneration technology did influence emissions, although regeneration effects went unresolved using bulk chemistry techniques. A multistudy comparison of the toxic particle-phase polycyclic aromatic hydrocarbons (PAHs; molecular weight (MW) ≥ 252 amu) in diesel exhaust indicates emission factors that span up to 8 orders of magnitude over the past several decades. This study observes conditions under which PAH compounds with MW ≥ 252 amu appear in diesel particles downstream of the CDPF and can even reach low-end concentrations reported earlier for much larger HDDVs with poorly controlled exhaust streams. This rare observation suggests that analysis of PAHs in particles emitted from modern L/MHDDVs may be more complex than recognized previously.
| S-EPMC7252512 | biostudies-literature
Project description:Peak exposures are of concern because they can potentially overwhelm normal defense mechanisms and induce adverse health effects. Metrics of peak exposure have been used in epidemiologic and exposure studies, but consensus is lacking on its definition. The relevant characteristics of peak exposure are dependent upon exposure patterns, biokinetics of exposure, and disease mechanisms. The objective of this review was to summarize the use of peak metrics in epidemiologic and exposure studies. A comprehensive search of Medline, Embase, Web of Science, and NIOSHTIC-2 databases was conducted using keywords related to peak exposures. The retrieved references were reviewed and selected for indexing if they included a peak metric and met additional criteria. Information on health outcomes and peak exposure metrics was extracted from each reference. A total of 1,215 epidemiologic or exposure references were identified, of which 182 were indexed and summarized. For the 72 epidemiologic studies, the health outcomes most frequently evaluated were: chronic respiratory effects, cancer and acute respiratory symptoms. Exposures were frequently assessed using task-based and full-shift time-integrated methods, qualitative methods, and real-time instruments. Peak exposure summary metrics included the presence or absence of a peak event, highest exposure intensity and frequency greater than a target. Peak metrics in the 110 exposure studies most frequently included highest exposure intensity, average short-duration intensity, and graphical presentation of the real-time data (plots). This review provides a framework for considering biologically relevant peak exposure metrics for epidemiologic and exposure studies to help inform risk assessment and exposure mitigation.
| S-EPMC7820770 | biostudies-literature
Project description:IntroductionThe American Heart Association created "Life's Simple Seven" metrics to estimate progress toward improving US cardiovascular health in a standardized manner. Given the widespread use of federally funded Diabetes Prevention Program (DPP)-based lifestyle interventions such as the Group Lifestyle Balance (DPP-GLB), evaluation of change in health metrics within such a program is of national interest. This study examined change in cardiovascular health metric scores during the course of a yearlong DPP-GLB intervention.MethodsData were combined from 2 similar randomized trials offering a community based DPP-GLB lifestyle intervention to overweight/obese individuals with prediabetes and/or metabolic syndrome. Pre/post lifestyle intervention participation changes in 5 of the 7 cardiovascular health metrics were examined at 6 and 12 months (BMI, blood pressure, total cholesterol, fasting plasma glucose, physical activity). Smoking was rare and diet was not measured.ResultsAmong 305 participants with complete data (81.8% of 373 eligible adults), significant improvements were demonstrated in all 5 risk factors measured continuously at 6 and 12 months. There were significant positive shifts in the "ideal" and "total" metric scores at both time points. Also noted were beneficial shifts in the proportion of participants across categories for BMI, activity, and blood pressure.ConclusionAHA-metrics could have clinical utility in estimating an individual's cardiovascular health status and in capturing improvement in cardiometabolic/behavioral risk factors resulting from participation in a community-based translation of the DPP lifestyle intervention.
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Project description:Most studies of short-term particulate matter (PM) exposure use 24-hour averages. However, other pollutants have stronger effects at shorter timeframes, which has influenced policy (e.g., ozone 8-hour maximum). Selecting appropriate exposure timeframes is important for effective regulation. The U.S. EPA identified health effects for sub-daily PM exposures as a critical research need. Unlike most areas, Seoul, Korea has hourly measurements of PM10, although not PM2.5. We investigated PM10 and mortality (total, cardiovascular, respiratory) in Seoul (1999-2009) considering sub-daily exposures: 24-hour, daytime (7am-8pm), morning (7-10am), nighttime (8pm-7am), and 1-hour daily maximum. We applied Poisson generalized linear modeling adjusting for temporal trends and meteorology. All PM10 metrics were significantly associated with total mortality. Compared to other exposure timeframes, morning exposure had the most certain effect with total mortality (based on statistical significance). A 10µg/m3 increase in 24-hour, daytime, morning, nighttime, and 1-hour maximum PM10 was associated with a 0.15% (95% confidence interval 0.02-0.28%), 0.14% (0.01-0.27%), 0.10% (0.03-0.18%), 0.12% (0.03-0.22%), and 0.10% (0.00-0.21%) increase in total mortality, respectively. PM10 was significantly associated with cardiovascular mortality for 24-hour, morning, and nighttime exposures. We did not identify significant associations with respiratory mortality. Results support use of a 24-hour averaging time as an appropriate metric for health studies and regulation, particularly for PM10 and mortality.
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