Effects of PM2.5 on Skeletal Muscle Mass and Body Fat Mass of the Elderly in Taipei, Taiwan.
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ABSTRACT:
SUBMITTER: Chen CH
PROVIDER: S-EPMC6671961 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Major components of suspended particulate matter (PM) are inorganic ions, organic matter (OM), elemental carbon (EC), geological minerals, salt, non-mineral elements, and water. Since oxygen (O) and hydrogen (H) are not directly measured in chemical speciation networks, more than ten weighting equations have been applied to account for their presence, thereby approximating gravimetric mass. Assumptions for these weights are not the same under all circumstances. OM is estimated from an organic carbon (OC) multiplier (f) that ranges from 1.4 to 1.8 in most studies, but f can be larger for highly polar compounds from biomass burning and secondary organic aerosols. The mineral content of fugitive dust is estimated from elemental markers, while the water-soluble content is accounted for as inorganic ions or salt. Part of the discrepancy between measured and reconstructed PM mass is due to the measurement process, including: (1) organic vapors adsorbed on quartz-fiber filters; (2) evaporation of volatile ammonium nitrate and OM between the weighed Teflon-membrane filter and the nylon-membrane and/or quartz-fiber filters on which ions and carbon are measured; and (3) liquid water retained on soluble constituents during filter weighing. The widely used IMPROVE equations were developed to characterize particle light extinction in U.S. national parks, and variants of this approach have been tested in a large variety of environments. Important factors for improving agreement between measured and reconstructed PM mass are the f multiplier for converting OC to OM and accounting for OC sampling artifacts.
| S-EPMC4449935 | biostudies-literature
Project description:While studies on ambient fine particulate matter (PM2.5) exposure effect on child health are available, the differential effects, if any, of exposure to PM2.5 species are unexplored in lower and middle-income countries. Using multiple logistic regression, we showed that for every 10 μg m-3 increase in PM2.5 exposure, anaemia, acute respiratory infection, and low birth weight prevalence increase by 10% (95% uncertainty interval, UI: 9-11), 11% (8-13), and 5% (4-6), respectively, among children in India. NO3-, elemental carbon, and NH4+ were more associated with the three health outcomes than other PM2.5 species. We found that the total PM2.5 mass as a surrogate marker for air pollution exposure could substantially underestimate the true composite impact of different components of PM2.5. Our findings provide key indigenous evidence to prioritize control strategies for reducing exposure to more toxic species for greater child health benefits in India.
| S-EPMC10618175 | biostudies-literature
Project description:With emission control efforts, the PM2.5 concentrations and PM2.5 exceedance days (daily mean PM2.5 concentrations >35?µg?m-3) show an apparent declining trend from 2006-2017. The PM2.5 concentrations increase from the northern to southern part of western Taiwan, and reductions in the PM2.5 concentration generally decrease from northern to southern part of western Taiwan. Thus, mitigation of the PM2.5 problem is less effective in southwestern Taiwan than in other regions in Taiwan. Analysis of a 39-year ERA-interim reanalysis dataset (1979-2017) reveals a weakening of the East Asian winter monsoon, a reduction in northeasterly (NE) monsoonal flow, and a tendency of enhanced stably stratified atmospheric structures in Taiwan and the surrounding area. The observed surface wind speed also presents a long-term decline. We can conclude that the long-term PM2.5 variations in Taiwan are mainly associated with changes in local anthropogenic emissions and modulated by short-term yearly variations due to strong haze events in China. In southwestern Taiwan, the long-term trend of PM2.5 reductions is possibly offset by worsening weather conditions, as this region is situated on the leeside of the mountains and often subject to stagnant wind when under the influence of NE monsoonal flow.
| S-EPMC6488571 | biostudies-literature
Project description:BackgroundFine particulate matter (PM2.5), one of the most common air pollutants worldwide, has been associated with many adverse birth outcomes in some studies. Pre-pregnancy body mass index (BMI) is an important indicator of maternal obesity that may also contribute to a wide range of birthweight outcomes. Both PM2.5 and maternal obesity have been found associated with issues on neonatal birthweight respectively, and more attentions and interests are focusing on their combined effect on pregnancy outcomes.PurposeTo explore the modifying effect of pre-pregnancy BMI on the association between gestational PM2.5 and birthweight; to investigate the interactive effect between gestational PM2.5 and pre-pregnancy BMI on birthweight among pregnant women during three trimesters and the whole pregnancy.MethodsThis nationwide cohort study used the National Free Preconception Health Examination Project (NFPHEP) data collected from January 1, 2010, to December 31, 2012. A total population of 248,501 Chinese women from 220 counties registered this project. Pre-pregnancy BMI as a common anthropometric examination was collected during preconception investigation, and gestational PM2.5 was derived from a hindcast model for historical PM2.5 estimation from satellite-retrieved aerosol optic depth. Subgroup analysis was conducted to explore a potential modifying effect on the association between PM2.5 and birthweight during pregnancy by four pre-pregnancy BMI subgroups. Interaction analysis by introducing product terms to multivariable linear regression was also used to examine whether there was an interactive relationship between PM2.5 and pre-pregnancy BMI.ResultsTotally, 193,461 participants were included in our study. The average concentration of PM2.5 was 75.33 μg/m3. Higher exposure of PM2.5 during the entire pregnancy was associated with higher birthweight (17.15 g per 10 μg/m3; 95% CI:16.15, 18.17). Each 10 μg/m3 increase in PM2.5 during the first, second, and third trimesters was associated with increases in birthweight by 14.93 g (95%CI: 13.96, 15.89), 13.75 g (95% CI: 12.81, 14.69), and 8.79 g (95% CI: 8.09, 9.49), respectively. Higher pre-pregnancy BMI per kg/m2 was associated with an increase of birthweight by 7.012 g (95% CI: 6.121, 7.902). Product terms between PM2.5 and pre-pregnancy BMI were significant for the first, second trimesters, and the entire duration of pregnancy.ConclusionsOur results found both gestational PM2.5 exposure and pre-pregnancy BMI respectively correlated with the increase of birthweight. A negative interaction between pre-pregnancy BMI and gestational PM2.5 was discovered in term of birthweight gain. Avoidance of high-dose exposure to PM2.5 during the early and middle stages of pregnancy and pre-pregnancy overweight/obesity may help prevent high birthweight.
| S-EPMC9360486 | biostudies-literature
Project description:BackgroundStudies showed that PM2.5 might be associated with various neurogenic diseases such as Alzheimer's Disease (AD). However, this topic had been little studied in Zhejiang province of China. METHODS: In 2018, we established a cohort of AD high-risk population with 1,742 elderly aged 60 and above. In 2020, the cohort was followed up, a total of 1,545 people participated the 2 surveys. Data collection included questionnaires and basic physical examinations. The average residential exposure to PM2.5 for each participant, that in a 5-years period prior to the first survey, was estimated using a satellite-based spatial statistical model. We determined the association between PM2.5 and AD prevalence by cox proportional hazards regression model. RESULTS: This study showed that an increase in the PM2.5 level was an important associated risk factor that contributed to AD. The average PM2.5 exposure levels among the study population ranged from 32.69 μg/m3 to 39.67 μg/m3 from 2013 to 2017, which were much higher than 5 μg/m3 that specified in the WHO air quality guidelines. There was an association between PM2.5 exposure and AD, and the correlations between PM2.5 and Mini-Mental State Examination, Montreal cognitive assessment scale scores were statistically significant. An increase in the PM2.5 level by 10 μg/m3 elevated the risk of AD among residents by 2%-5% (HR model 2-model 4 = 1.02 to 1.05, CI model 2-model 4 = 1.01-1.10). The subgroups of male, with old age, with low education levels, used to work as farmers or blue-collar workers before retirement, overweight and obese were associated with a higher effect of PM2.5.ConclusionsReducing PM2.5 exposure might be a good way to prevent AD.
| S-EPMC9706836 | biostudies-literature
Project description:Although exposure to particulate matter with aerodynamic diameters ≤ 2.5 µm (PM2.5) influences cardiovascular disease (CVD), its association with CVD-related hospitalizations of super-aged patients in Japan remains uncertain. We investigated the relationship between short-term PM2.5 exposure and CVD-related hospitalizations, lengths of hospital stays, and medical expenses. We analyzed the Japanese national database of patients with CVD (835,405) admitted to acute-care hospitals between 2012 and 2014. Patients with planned hospitalizations and those with missing PM2.5 exposure data were excluded. We classified the included patients into five quintiles based on their PM2.5 exposure: PM-5, -4, -3, -2, and -1 groups, in descending order of concentration. Compared with the PM-1 group, the other groups had higher hospitalization rates. The PM-3, -4, and -5 groups exhibited increased hospitalization durations and medical expenses, compared with the PM-1 group. Interestingly, the hospitalization period was longer for the ≥ 90-year-old group than for the ≤ 64-year-old group, yet the medical expenses were lower for the former group. Short-term PM2.5 exposure is associated with increased CVD-related hospitalizations, hospitalization durations, and medical expenses. The effects of incident CVDs were more marked in elderly than in younger patients. National PM2.5 concentrations should be reduced and the public should be aware of the risks.
| S-EPMC8110517 | biostudies-literature
Project description:IntroductionDespite the London Underground (LU) handling on average 2.8 million passenger journeys per day, the characteristics and potential health effects of the elevated concentrations of metal-rich PM2.5 found in this subway system are not well understood.MethodsSpatial monitoring campaigns were carried out to characterise the health-relevant chemical and physical properties of PM2.5 across the LU network, including diurnal and day-to-day variability and spatial distribution (above ground, depth below ground and subway line). Population-weighted station PM2.5 rankings were produced to understand the relative importance of concentrations at different stations and on different lines.ResultsThe PM2.5 mass in the LU (mean 88??g?m-3, median 28??g?m-3) was greater than at ambient background locations (mean 19??g?m-3, median 14??g?m-3) and roadside environments in central London (mean 22??g?m-3, median 14??g?m-3). Concentrations varied between lines and locations, with the deepest and shallowest submerged lines being the District (median 4??g?m-3) and Victoria (median 361??g?m-3 but up to 885??g?m-3). Broadly in agreement with other subway systems around the world, sampled LU PM2.5 comprised 47% iron oxide, 7% elemental carbon, 11% organic carbon, and 14% metallic and mineral oxides. Although a relationship between line depth and air quality inside the tube trains was evident, there were clear influences relating to the distance from cleaner outside air and the exchange with cabin air when the doors open. The passenger population-weighted exposure analysis demonstrated a method to identify stations that should be prioritised for remediation to improve air quality.ConclusionPM2.5 concentrations in the LU are many times higher than in other London transport Environments. Failure to include this environment in epidemiological studies of the relationship between PM2.5 and health in London is therefore likely to lead to a large exposure misclassification error. Given the significant contribution of underground PM2.5 to daily exposure, and the differences in composition compared to urban PM2.5, there is a clear need for well-designed studies to better understand the health effects of underground exposure.
| S-EPMC6902242 | biostudies-literature
Project description:This study aimed to find the characteristics of polychlorinated dibenzo-p-dioxins and dibenzofurans (PCDD/Fs) in fine particulate matter from different stationary emission sources (coal-fired boiler, CFB; municipal waste incinerator, MWI; electric arc furnace, EAF) in Taiwan and the relationship between PM2.5 and PM2.5-bound PCDD/Fs with Taiwanese mortality risk. PM2.5 was quantified using gravimetry and corresponding chemical analyses were done for PM2.5-bound chemicals. Mortality risks of PM2.5 exposure and PCDD/Fs exposure were calculated using Poisson regression. The highest concentration of PM2.5 (0.53 ± 0.39 mg/Nm3) and PCDD/Fs (0.206 ± 0.107 ng I-TEQ/Nm3) was found in CFB and EAF, respectively. Higher proportions of PCDDs over PCDFs were observed in the flue gases of CFB and MWI whereas it was reversed in EAF. For ambient air, PCDD/F congeners around the stationary sources were dominated by PCDFs in vapor phase. Positive matrix factorization (PMF) analysis found that the sources of atmosphere PCDD/Fs were 14.6% from EAF (r = 0.81), 52.6% from CFB (r = 0.74), 18.0% from traffic (r = 0.85) and 14.8% from MWI (r = 0.76). For the dioxin congener distribution, PCDDs were dominant in flue gases of CFB and MWI, PCDFs were dominant in EAF. It may be attributed to the different formation mechanisms among wastes incineration, steel-making, and coal-burning processes.
| S-EPMC8046994 | biostudies-literature
Project description:Fine particulate matter (PM2.5) mainly originates from combustion emissions. On-road transportation is considered one of the primary sources of PM2.5 emission. The relationship between on-road transportation and PM2.5 concentration varies temporally and spatially, and the estimation for this variation is important for policymaking. Here, we reveal the quantitative association of PM2.5 concentration with on-road transportation by the spatial panel Durbin model and the geographical and temporal weighted regression. We find that 6.17 billion kilometres (km) per km2 on-road transportation increase is associated with a 1-μg/m3 county-level PM2.5 concentration increase in the contiguous United States. On-road transportation marginally contributes to PM2.5, only 1.09% on average. Approximately 3605 premature deaths are attributed to PM2.5 from on-road transportation in 2010, and about a total of 50,223 premature deaths ascribe to PM2.5 taking 6.49% from 2003 to 2016. Our findings shed light on the necessity of the county-level policies considering the temporal and spatial variability of the relationship to further mitigate PM2.5 from on-road transportation.
| S-EPMC8556279 | biostudies-literature
Project description:BackgroundLittle is known about the association of changes in two body components, muscle and fat mass, with the risk of cardiovascular disease (CVD) among young adults. We investigated the association of changes in predicted lean body mass index (LBMI), appendicular skeletal muscle mass index (ASMI), and body fat mass index (BFMI) with the development of CVD among young adults.MethodsThis nationwide, population-based cohort study included 3 727 738 young adults [2 406 046 (64.5%) men and 1 321 692 (35.5%) women] aged 20-39 years without a previous history of CVD who underwent two health screening examinations during 2009-2010 and 2011-2012. Using validated and robust prediction equations, we calculated the changes in predicted LBMI, ASMI, and BFMI from the first to the second examinations.ResultsThe mean (SD) age was 32.2 (4.9) years, and 2 406 046 (64.5%) of the participants were men. A total of 23 344 CVD events were detected during 22 257 632 person-years of follow-up. Each 1 kg/m2 increase in predicted LBMI and ASMI change was associated with a reduced risk of CVD among men [adjusted hazard ratio (aHR): 0.86, 95% confidence interval (CI) 0.82-0.91; aHR: 0.76, 95% CI 0.69-0.82, respectively] and women (aHR: 0.77, 95% CI 0.63-0.95; aHR: 0.75, 95% CI 0.59-0.96). Each 1 kg/m2 increase in predicted BFMI change was associated with an increased risk of CVD among men (aHR: 1.16, 95% CI 1.10-1.22) and women (aHR: 1.32, 95% CI 1.06-1.65). In both sexes, decreases in predicted LBMI and ASMI were associated with greater CVD risk, and decreased predicted BFMI was associated with a reduced CVD risk. Those who maintained their BMI between -1 and +1 kg/m2 also had a decreased risk of CVD per 1 kg/m2 increase in predicted LBMI and ASMI change among men (aHR: 0.86, 95% CI 0.80-0.92; aHR: 0.85, 95% CI 0.76-0.95) and women (aHR: 0.62, 95% CI 0.47-0.83; aHR: 0.59, 95% CI 0.44-0.80) and had a greater risk of CVD per 1 kg/m2 increase in predicted BFMI change among men (aHR: 1.17, 95% CI 1.10-1.25) and women (aHR: 1.64, 95% CI 1.20-2.23). Regardless of changes in weight, such as from normal to obese or vice versa, these results were consistent.ConclusionsAmong young adults, increased predicted muscle mass or decreased predicted fat mass were associated with a reduced risk of development of CVD. Decreased predicted muscle mass or increased predicted fat mass were associated with an elevated risk of development of CVD.
| S-EPMC8978024 | biostudies-literature