Bronchitis bei Kindern unter Belastung durch Strassenverkehrslarm und Abgase. Bronchitis in Children Exposed to Road Traffic Noise and Exhaust Fumes

Ising, H; Lange-Asschenfeldt, H; Eilts, Manfred

doi:10.1111/j.1439-054x.2005.00044.x

Cited by 3 publications

(5 citation statements)

References 4 publications

(6 reference statements)

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“…As an initial step, understanding how metabolomic profiles vary by biological matrices in the same individuals may inform future study designs in this exposure science subfield. Non-invasive sampling of exhaled breath (EBC) [12,26] and saliva [27] may serve as viable alternatives to more invasive blood sampling. Comparative metabolomic profiling across the plasma, EBC, and saliva matrices may assist with the identification of the most relevant components of PM exposure for health.…”

Section: Introductionmentioning

confidence: 99%

Metabolomic profiles of plasma, exhaled breath condensate, and saliva are correlated with potential for air toxics detection

et al. 2017

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Introduction Advances in the development of high-resolution metabolomics (HRM) have provided new opportunities for their use in characterizing exposures to environmental air pollutants and air pollution-related disease etiologies. Exposure assessment studies have considered blood, breath, and saliva as biological matrices suitable for measuring responses to air pollution exposures. The current study examines comparability among these three matrices using HRM and explored their potential for measuring mobile source air toxics. Methods Four participants provided saliva, exhaled breath concentrate (EBC), and plasma before and after a 2-hour road traffic exposure. Samples were analyzed on a Thermo Scientific QExactive MS system in positive electrospray ionization (ESI) mode and resolution of 70,000 FHWM with C18 chromatography. Data were processed using apLCMS and xMSanalyzer on the R statistical platform. Results The analysis yielded 7,110, 6,019, and 7,747 reproducible features in plasma, EBC, and saliva, respectively. Correlations were moderate-to-strong (R = 0.41 – 0.80) across all pairwise comparisons of feature intensity within profiles, with the strongest between EBC and saliva. The associations of mean intensities between matrix pairs were positive and significant, controlling for subject and sampling time effects. Six out of 20 features shared in all three matrices putatively matched a list of known mobile-source air toxics. Conclusions Plasma, saliva, and EBC have largely comparable metabolic profiles measurable through HRM. These matrices have the potential to be used in identification and measurement of exposures to mobile source air toxics, though further, targeted study is needed.

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Section: Introductionmentioning

confidence: 99%

Metabolomic profiles of plasma, exhaled breath condensate, and saliva are correlated with potential for air toxics detection

et al. 2017

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“…Some relevant studies, i.e., the study of chronic noise exposure and hypertension in the Netherlands, reported a correlation coefficient of 0.72 between modeled noise and modeled annual average Particulate Matter10 (de Kluizenaar et al, 2007). A study in Germany reported a strong correlation (r=0.84) between measurements of night-time (0:00-6:00) traffic noise and 58-93 h measurements of NO2 at 25 locations (Ising et al, 2004).…”

Section: Correlation Between Air and Noise Pollution Due To Environme...mentioning

confidence: 99%

Investigating the Influence of Environmental Features on Air Pollution and Environmental Noise in Three Cities of Ontario, Canada

Saroar

2024

Preprint

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This thesis examines the impacts of environmental features on air and noise pollution covariance in three different cities of Southern Ontario. More specifically, the objectives of the study were to (1) Evaluate the correlation and spatial relationship between nitrogen dioxide 2NO ), and environmental noise in Mississauga, Hamilton and London; (2) Analyze the influence of environmental features on the covariance of NO and NO2se levels in the study areas. A combination of descriptive and inferential bivariate, and multivariate statistical techniques were performed to develop local and global models of noise and air pollution covariance. This study found a substantial correlation between the NO 2nd environmental noise in Mississauga and Hamilton; however, the correlation in London was very low. According to the final Land Use Regression (LUR) model, variables like traffic volume, road length, and industrial land-use increase the NO a2d environmental noise in different cities, whereas Normalized Difference Vegetation Index (NDVI) helps to reduce the NO a2d environmental noise. This approach could be a good option for LUR modeling of environmental pollution in cities where extensive spatial monitoring is unfeasible, and more specifically, the predicted results of such a study may be applied to further health studies in the cities with the same land-use patterns.

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“…A total of 25 studies were identified that reported on the impact of noise exposure on cortisol levels [Table S5][ 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 ]; however the majority of studies ( n = 21) could not be pooled into a meta-analysis due to differences in populations, measurement of exposures, measurement of outcomes, and reporting of outcomes. Therefore, the results are presented narratively in the summary of findings table.…”

Section: R Esultsmentioning

confidence: 99%

“…Therefore, the results are presented narratively in the summary of findings table. [ 19 20 21 22 23 24 25 26 27 28 29 31 32 33 34 35 36 40 41 42 43 ] Concerns with risk of bias due to confounding, exposure assessment, missing data, and measurement of outcomes were identified [Tables S6 and S7]. As shown in Table 3 , there was very low CoE for the effects of increased noise exposure on cortisol levels.…”

Section: R Esultsmentioning

confidence: 99%

“…Four studies examined the relationship between road traffic noise and cortisol. [ 22 31 32 42 ] Among cohort studies that assessed road traffic noise and cortisol, it was reported that an increase in road traffic noise may have little to no effect on cortisol levels. Among cross-sectional studies exploring road traffic noise, one study reported that increased road traffic noise may increase cortisol levels (MD: 1.70; 95% confidence interval, CI: 1.20–2.20); however, the certainty in the evidence was very low [ Table 3 ].…”

Section: R Esultsmentioning

confidence: 99%

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Impact of Noise Exposure on Risk of Developing Stress-Related Metabolic Effects: A Systematic Review and Meta-Analysis

et al. 2022

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Background: Exposure to noise can increase biological stress reactions, which may increase adverse health effects, including metabolic disorders; however, the certainty in the association between exposure to noise and metabolic outcomes has not been widely explored. The objective of this review is to evaluate the evidence between noise exposures and metabolic effects. Materials and Methods: A systematic review of English and comparative studies available in PubMed, Cochrane Central, EMBASE, and CINAHL databases between January 1, 1980 and December 29, 2021 was performed. Risk of Bias of Nonrandomized Studies of Exposures was used to assess risk of bias of individual studies and certainty of the body of evidence for each outcome was assessed using the Grading of Recommendations Assessment, Development and Evaluation (GRADE) approach. Results: Fifty-six primary studies reporting on cortisol, cholesterol levels, waist circumference, glucose levels, and adrenaline and/or noradrenaline were identified. Although meta-analyses suggested that there may be an increase in waist circumference and adrenaline with increased noise exposure, the certainty in the evidence is very low. Overall, the certainty in the evidence of an effect of increased noise on all the outcomes were low to very low due to concerns with risk of bias, inconsistency across exposure sources, populations, and studies, and imprecision in the estimates of effects. Conclusions: The certainty of the evidence of increased noise on metabolic effects was low to very low, which likely reflects the inability to compare across the totality of the evidence for each outcome. The findings from this review may be used to inform policies involving noise reduction and mitigation strategies, and to direct further research in areas that currently have limited evidence available.

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Bronchitis bei Kindern unter Belastung durch Strassenverkehrslarm und Abgase. Bronchitis in Children Exposed to Road Traffic Noise and Exhaust Fumes

Cited by 3 publications

References 4 publications

Metabolomic profiles of plasma, exhaled breath condensate, and saliva are correlated with potential for air toxics detection

Metabolomic profiles of plasma, exhaled breath condensate, and saliva are correlated with potential for air toxics detection

Investigating the Influence of Environmental Features on Air Pollution and Environmental Noise in Three Cities of Ontario, Canada

Impact of Noise Exposure on Risk of Developing Stress-Related Metabolic Effects: A Systematic Review and Meta-Analysis

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