Risk of temperature, humidity and concentrations of air pollutants on the hospitalization of AECOPD.
Ontology highlight
ABSTRACT:
SUBMITTER: Chen C
PROVIDER: S-EPMC6879126 | biostudies-literature | 2019
REPOSITORIES: biostudies-literature
Publications
Risk of temperature, humidity and concentrations of air pollutants on the hospitalization of AECOPD.
Chen Cai C Liu Xuejian X Wang Xianfeng X Li Wei W Qu Wenxiu W Dong Leilei L Li Xiyuan X Rui Zhiqing Z Yang Xueqing X
PloS one 20191126 11
<h4>Aim</h4>To investigate the effect of temperature, humidity and the concentration of ambient air pollution on the hospitalization of AECOPD.<h4>Method</h4>Hospitalization record was obtained from Shenyang Medical Insurance Bureau, concluding patient's age, gender, income hospital time, outcome hospital; Generalized additive model was used to analyze the relationship between temperature, humidity, the concentration of ambient air pollution and the hospitalization of AECOPD.<h4>Result</h4>The e ...[more]
Similar Datasets
Project description:BackgroundStudies have observed associations between long-term air pollution and cardiovascular disease hospitalization. Little is known, however, about effect modification of these associations by greenness, temperature and humidity.MethodsWe constructed an open cohort consisting of all fee-for-service Medicare beneficiaries, aged ≥ 65, living in the contiguous US from 2000 through 2016 (~63 million individuals). We assigned annual average PM2.5, NO2 and ozone zip code concentrations. Cox-equivalent Poisson models were used to estimate associations with first cardiovascular disease (CVD), coronary heart disease (CHD) and cerebrovascular disease (CBV) hospitalization.ResultsPM2.5 and NO2 were both positively associated with CVD, CHD and CBV hospitalization, after adjustment for potential confounders. Associations were substantially stronger at the lower end of the exposure distributions. For CVD hospitalization, the hazard ratio (HR) of PM2.5 was 1.041 (1.038, 1.045) per IQR increase (4.0 µg/m3) in the full study population and 1.327 (1.305, 1.350) per IQR increase for a subgroup with annual exposures always below 10 µg/m3 PM2.5. Ozone was only positively associated with CVD, CHD and CBV hospitalization for the low-exposure subgroup (<40 ppb). Associations of PM2.5 were stronger in areas with higher greenness, lower ozone and Ox, lower summer and winter temperature and lower summer and winter specific humidity.ConclusionPM2.5 and NO2 were positively associated with CVD, CHD and CBV hospitalization. Associations were more pronounced at low exposure levels. Associations of PM2.5 were stronger with higher greenness, lower ozone and Ox, lower temperature and lower specific humidity.
| S-EPMC8380672 | biostudies-literature
Project description:Environmental parameters have a significant impact on the spread of respiratory viral diseases (temperature (T), relative humidity (RH), and air saturation state). T and RH are strongly correlated with viral inactivation in the air, whereas supersaturated air can promote droplet deposition in the respiratory tract. This study introduces a new concept, the dynamic virus deposition ratio (α), that reflects the dynamic changes in viral inactivation and droplet deposition under varying ambient environments. A non-steady-state-modified Wells-Riley model is established to predict the infection risk of shared air space and highlight the high-risk environmental conditions. Findings reveal that a rise in T would significantly reduce the transmission of COVID-19 in the cold season, while the effect is not significant in the hot season. The infection risk under low-T and high-RH conditions, such as the frozen seafood market, is substantially underestimated, which should be taken seriously. The study encourages selected containment measures against high-risk environmental conditions and cross-discipline management in the public health crisis based on meteorology, government, and medical research.
| S-EPMC9366825 | biostudies-literature
Project description:We analyzed the ability of particulate matter (PM) and chemicals adsorbed onto it to induce diverse gene expression profiles in subjects living in two regions of the Czech Republic differing in levels and sources of the air pollution. A total of 312 samples from polluted Ostrava region and 154 control samples from Prague were collected in winter 2009, summer 2009 and winter 2010. The highest concentrations of air pollutants were detected in winter 2010 when the subjects were exposed to: PM of aerodynamic diameter < 2.5 µm (PM2.5) (70 vs. 44.9 µg/m3); benzo[a]pyrene (9.02 vs. 2.56 ng/m3) and benzene (10.2 vs. 5.5 µg/m3) in Ostrava and Prague, respectively. Global gene expression analysis of total RNA extracted from leukocytes was performed using Illumina Expression BeadChips microarrays. The expression of selected genes was verified by quantitative real-time PCR (qRT-PCR). Gene expression profiles differed by locations and seasons. Despite lower concentrations of air pollutants a higher number of differentially expressed genes and affected KEGG (Kyoto Encyclopedia of Genes and Genomes) pathways was found in subjects from Prague. In both locations immune response pathways were affected, in Prague also neurodegenerative diseases-related pathways. Over-representation of the latter pathways was associated with the exposure to PM2.5. The qRT-PCR analysis showed a significant decrease in expression of APEX, ATM, FAS, GSTM1, IL1B and RAD21 in subjects from Ostrava, in a comparison of winter 2010 and summer 2009. In Prague, an increase in gene expression was observed for GADD45A and PTGS2. In conclusion, high concentrations of pollutants in Ostrava were not associated with higher number of differentially expressed genes, affected KEGG pathways and expression levels of selected genes. This observation suggests that chronic exposure to air pollution may result in reduced gene expression response with possible negative health consequences.
2014-08-27 | GSE60767 | GEO
Project description:High concentrations of air pollutants on roadways, relative to ambient concentrations, contribute significantly to total personal exposure. Estimation of these exposures requires measurements or prediction of roadway concentrations. Our study develops, compares, and evaluates linear regression and nonlinear generalized additive models (GAMs) to estimate on-road concentrations of four key air pollutants, particle-bound polycyclic aromatic hydrocarbons (PB-PAH), particle number count (PNC), nitrogen oxides (NOx), and particulate matter with diameter <2.5 ?m (PM2.5) using traffic, meteorology, and elevation variables. Critical predictors included wind speed and direction for all the pollutants, traffic-related variables for PB-PAH, PNC, and NOx, and air temperatures and relative humidity for PM2.5. GAMs explained 50%, 55%, 46%, and 71% of the variance for log or square-root transformed concentrations of PB-PAH, PNC, NOx, and PM2.5, respectively, an improvement of 5% to over 15% over the linear models. Accounting for temporal autocorrelation in the GAMs further improved the prediction, explaining 57-89% of the variance. We concluded that traffic and meteorological data are good predictors in estimating on-road traffic-related air pollutant concentrations and GAMs perform better for nonlinear variables, such as meteorological parameters.
| S-EPMC4048198 | biostudies-literature
Project description:BackgroundEstimating the long-term health impact of air pollution in a spatio-temporal ecological study requires representative concentrations of air pollutants to be constructed for each geographical unit and time period. Averaging concentrations in space and time is commonly carried out, but little is known about how robust the estimated health effects are to different aggregation functions. A second under researched question is what impact air pollution is likely to have in the future.MethodsWe conducted a study for England between 2007 and 2011, investigating the relationship between respiratory hospital admissions and different pollutants: nitrogen dioxide (NO2); ozone (O3); particulate matter, the latter including particles with an aerodynamic diameter less than 2.5 micrometers (PM2.5), and less than 10 micrometers (PM10); and sulphur dioxide (SO2). Bayesian Poisson regression models accounting for localised spatio-temporal autocorrelation were used to estimate the relative risks (RRs) of pollution on disease risk, and for each pollutant four representative concentrations were constructed using combinations of spatial and temporal averages and maximums. The estimated RRs were then used to make projections of the numbers of likely respiratory hospital admissions in the 2050s attributable to air pollution, based on emission projections from a number of Representative Concentration Pathways (RCP).ResultsNO2 exhibited the largest association with respiratory hospital admissions out of the pollutants considered, with estimated increased risks of between 0.9 and 1.6% for a one standard deviation increase in concentrations. In the future the projected numbers of respiratory hospital admissions attributable to NO2 in the 2050s are lower than present day rates under 3 Representative Concentration Pathways (RCPs): 2.6, 6.0, and 8.5, which is due to projected reductions in future NO2 emissions and concentrations.ConclusionsNO2 concentrations exhibit consistent substantial present-day health effects regardless of how a representative concentration is constructed in space and time. Thus as concentrations are predicted to remain above limits set by European Union Legislation until the 2030s in parts of urban England, it will remain a substantial health risk for some time.
| S-EPMC5368918 | biostudies-literature
Project description:New findingsWhat is the central question of this study? What are the independent effects of air temperature and humidity on performance, physiological and perceptual responses during endurance exercise? What is the main finding and its importance? When examined independently, elevated air temperature increased heat strain and impaired aerobic exercise performance, but to a lesser extent than has been reported previously. These findings highlight the importance of absolute humidity relative to temperature when exercising or working under severe heat stress.AbstractMany studies have reported that ambient heat stress increases physiological and perceptual strain and impairs endurance exercise, but effects of air temperature per se remain almost unexamined. Most studies have used matched relative humidity, thereby exponentially increasing absolute humidity (water content in air) concurrently with temperature. Absolute (not relative) humidity governs evaporative rate and is more important at higher work rates and air temperatures. Therefore, we examined the independent effects of air temperature and humidity on performance, thermal, cardiovascular and perceptual measures during endurance exercise. Utilizing a crossover design, 14 trained participants (7 females) completed 45 min fixed-intensity cycling (70% V̇O2peak${\dot V_{{{\rm{O}}_{\rm{2}}}{\rm{peak}}}}$ ) followed by a 20-km time trial in each of four environments: three air temperatures at matched absolute humidity (Cool, 18°C; Moderate, 27°C; and Hot, 36°C; at 1.96 kPa, air velocity ∼4.5 m/s), and one at elevated humidity (Hot Humid, 36°C at 3.92 kPa). Warmer air caused warmer skin (0.5°C/°C; P < 0.001), higher heart rate (1 bpm/°C; P < 0.001), sweat rate (0.04 l/h/°C; P < 0.001) and thermal perceptions during fixed-intensity exercise, but minimally affected core temperature (<0.01°C/°C; P = 0.053). Time-trial performance was comparable between Cool and Moderate (95% CI: -1.4, 5.9%; P = 0.263), but 3.6-6% slower in Hot (95% CI: ±2.4%; P ≤ 0.006). Elevated humidity increased core temperature (P < 0.001), perceived temperature and discomfort but not skin temperature or heart rate, and reduced mean blood pressure (P = 0.046) during fixed-intensity exercise. Elevated humidity impaired time-trial performance by 3.4% (95% CI: ±2.2%; P = 0.006). In conclusion, these findings quantify the importance of absolute humidity alongside air temperature when exercising under severe heat stress.
| S-EPMC10103870 | biostudies-literature
Project description:BACKGROUND:Extreme ambient temperatures and air quality have been directly associated with various human diseases from several studies around the world. However, few analyses involving the association of these environmental circumstances with mental and behavioral disorders (MBD) have been carried out, especially in developing countries such as Brazil. METHODS:A time series study was carried out to explore the associations between daily air pollutants (SO2, NO2, O3, and PM10) concentrations and meteorological variables (temperature and relative humidity) on hospital admissions for mental and behavioral disorders for Curitiba, Brazil. Daily hospital admissions from 2010 to 2016 were analyzed by a semi-parametric generalized additive model (GAM) combined with a distributed lag non-linear model (DLNM). RESULTS:Significant associations between environmental conditions (10??g/m3 increase in air pollutants and temperature °C) and hospitalizations by MBD were found. Air temperature was the environmental variable with the highest relative risk (RR) at 0-day lag for all ages and sexes analyzed, with RR values of 1.0182 (95% CI: 1.0009-1.0357) for men, and 1.0407 (95% CI: 1.0230-1.0587) for women. Ozone exposure was a risk for all women groups, being higher for the young group, with a RR of 1.0319 (95% CI: 1.0165-1.0483). Elderly from both sexes were more susceptible to temperature variability, with a RR of 1.0651 (95% CI: 1.0213-1.1117) for women, and 1.0215 (95% CI: 1.0195-1.0716) for men. CONCLUSIONS:This study suggests that temperatures above and below the thermal comfort threshold, in addition to high concentrations of air pollutants, present significant risks on hospitalizations by MBD; besides, there are physiological and age differences resulting from the effect of this exposure.
| S-EPMC7336420 | biostudies-literature
Project description:The aging rate in Taiwan is the second highest in the world. As the population ages quickly, the prevalence of dementia increases rapidly. There are some studies that have explored the association between air pollution and cognitive decline, but the association between air pollution and dementia has not been directly evaluated.This was a case-control study comprising 249 Alzheimer's disease (AD) patients, 125 vascular dementia (VaD) patients, and 497 controls from three teaching hospitals in northern Taiwan from 2007 to 2010. Data of particulate matter <10 ?m in diameter (PM10) and ozone were obtained from the Taiwan Environmental Protection Administration for 12 and 14 years, respectively. Blood samples were collected to determine the apolipoprotein E (APOE) ?4 haplotype. Bayesian maximum entropy was used to estimate the individual exposure level of air pollutants, which was then tertiled for analysis. Conditional logistic regression models were used to estimate adjusted odds ratios (AORs) and 95% confidence intervals between the association of PM10 and ozone exposure with AD and VaD risk.The highest tertile of PM10 (?49.23 ?g/m(3)) or ozone (?21.56 ppb) exposure was associated with increased AD risk (highest vs. lowest tertile of PM10: AOR = 4.17; highest vs. lowest tertile of ozone: AOR = 2.00). Similar finding was observed for VaD. The association with AD and VaD risk remained for the highest tertile PM10 exposure after stratification by APOE ?4 status and gender.Long-term exposure to the highest tertile of PM10 or ozone was significantly associated with an increased risk of AD and VaD.
| S-EPMC4876896 | biostudies-other
Project description:Weather conditions affect the incidence of acute myocardial infarction (AMI). However, little is known on the association of weather temperature and humidity with AMI hospitalizations in a super-aging society. This study sought to examine this association. We included 87,911 consecutive patients with AMI admitted to Japanese acute-care hospitals between April 1, 2012 and March 31, 2015. The primary outcome was the number of AMI hospitalizations per day. Multilevel mixed-effects linear regression models were used to estimate the association of the average temperature and humidity, 1 day before hospital admission, with AMI hospitalizations, after adjusting for weather, hospital, and patient demographics.Lower temperature and humidity were associated with an increased number of AMI hospitalizations (coefficient - 0.500 [- 0.524 to - 0.474] per °C change, p < 0.001 and coefficient - 0.012 [- 0.023 to - 0.001] per % change, p = 0.039, respectively). The effects of temperature and humidity on AMI hospitalization did not differ by age and sex (all interaction p > 0.05), but differed by season. However, higher temperatures in spring (coefficient 0.089 [0.025 to 0.152] per °C change, p = 0.010) and higher humidity in autumn (coefficient 0.144 [0.121 to 0.166] per % change, p < 0.001) were risk factors for AMI hospitalization. Increased average temperatures and humidity, 1 day before hospitalization, are associated with a decreased number of AMI hospitalizations.
| S-EPMC8613245 | biostudies-literature
Project description:Respiratory syncytial virus (RSV) contributes significantly to pediatric hospitalizations. An association between air pollution and an increased number of RSV cases has been suggested. We sought to evaluate the short-term impact of air pollutants on RSV hospitalizations in Polish children in the period 2010-2019. Daily concentrations of PM10 and PM2.5 (particulate matter with an aerodynamic diameter less than or equal to 10 μm and 2.5 μm, respectively) and nitrogen dioxide (NO2) were analyzed in general regression models (GRM) to establish their influence and full interaction scheme. Significant seasonal and annual periodicity among 53,221 hospitalizations was observed; finally, data from the 2012-2019 RSV high-risk seasons created models for seven agglomerations. The addition of PM2.5, PM10, and NO2 to the basic model for RSV seasonality explained 23% (4.9-31%, univariate model) to 31.4% (8.4-31%, multivariate model) of the variance in RSV hospitalizations. A 10 μg/m3 increase in PM2.5, PM10, and NO2 concentrations was associated with 0.134 (0.087-0.16), 0.097 (0.031-0.087), and 0.212 (0.04-0.29) average increases in hospitalizations, respectively. In the multivariate models, PM2.5, PM10, and NO2 alone, as well as PM2.5-NO2, PM2.5-PM10, and PM10-NO2 interactions, were associated with hospitalizations in some of the locations, while the metaregression showed statistically significant interactions between each of the pollutants, and between the pollutants and the year of the study. The inclusion of PM2.5, PM10, and NO2 in GRM explains a significant number of RSV hospitalizations. The pollutants act alone and interact together in a varied manner. Reducing air contamination might decrease the costs of hospital healthcare.
| S-EPMC8348891 | biostudies-literature