A study on road traffic noise exposure and prevalence of insomnia

The sound of safety: exploring the determinants of prevention intention in noisy industrial workplaces

Occupational noise exposure is a pervasive issue in many industries, leading to a range of health issues and sleep disturbances among workers. Additionally, there is a strong desire among these workers to prevent industrial accidents. This study, aimed at enhancing worker health and well-being, utilized a survey distributed by the Korean Confederation of Trade Unions to field workers. Data from 1285 workers were collected and analyzed using partial least squares structural equation modeling (PLS-SEM) to identify and understand the factors affecting prevention intention in noisy work environments. Our findings indicate that health problems resulting from occupational noise exposure significantly influence insomnia, perceived severity of potential accidents, perceived benefits of preventive measures, and perceived barriers. Perceived severity was significantly correlated with prevention intention, emphasizing the role of risk perception in motivating preventive behaviors. Perceived benefits were also significantly associated with prevention intention, highlighting the importance of positive outcomes in influencing workers' behaviors. Additionally, perceived barriers showed a significant relationship with prevention intention, suggesting that overcoming these barriers is crucial in promoting preventive behaviors. Demographic factors such as gender displayed a significant association with prevention intention, while age did not. This study provides valuable insights into the multifaceted factors influencing workers' intention to prevent industrial accidents in noisy environments, underlining the importance of comprehensive data collection tools in understanding these dynamics.

The effect of traffic at speed bumps in residential areas on noise and air pollution

Although transportation systems are an increasing necessity in today's connected world, the over-reliance on internal combustion engine vehicles has caused an increase in air and noise pollution. Air and noise pollutions are among the negative environmental factors that contribute to disease occurrence due to their negative health consequences. Literature has showed that air and noise pollutions were responsible for thousands of premature deaths in Europe. This has pushed scientists to search for models to calculate the effect of traffic on air and noise pollution, to help predict future scenarios, and to work on ways to mitigate that increase in pollution. In this paper, a statistical model is done by using data measured for 25 speed bump locations in Kuwait, which included traffic flow data in the form of vehicle count and classification, as well as noise level measurements taken through an Amprobe SM20 sound meter, in addition to air pollutant data obtained from the Environment Public Authority (EPA) in Kuwait. The results of the multivariate linear regression model showed that high traffic counts resulted in significantly higher noise levels, reaching more than 70 decibels in certain locations, which is considered unhealthy for extended time periods. The model also showed that sulfur dioxide levels were impacted by both light and heavy vehicles, while particulate matter less than 10 µm was affected mainly by heavy vehicles. An online survey on speed bumps was completed by 803 participants to understand the behavior of people at speed bumps in Kuwait and understand if age and gender might be a predictor of how people would behave, and this was done by doing Pearson's chi-squared correlation tests on the results obtained from the survey.

A study on the impact of road traffic noise exposure on work efficiency of housewives

Housewives are individuals who take on the caregiving role in the family in virtually every society and while discharging their duties experience serious psychological difficulties due to external environmental pollutants like air, noise, etc., which influences their efficiency of performing household activities. This study hypothesizes a causal association between perception of traffic noise and the reduction in performance of housewives in their daily household activities. A simple mediation model was utilized for the study with traffic noise perception as the exposure variable. The sensitivity to traffic noise, annoyance caused due to traffic noise, and the effect of traffic noise on housewives were evaluated using questionnaire survey. Of the respondents, 57.33% reported high level of traffic noise perception, while 65.81% reported high annoyance due to traffic noise perception. Of the respondents, 88.69% reported higher levels of agreement with regard to negative effect of traffic noise on their household activities. The results supported the hypothesis with respondents belonging to high and moderate noise perception groups reporting a higher reduction in performance as compared to those belonging to the low noise perception group at higher values of sensitivity. There was no significant direct effect among those who perceived traffic noise as high and moderate. However, the indirect path revealed that there was a significantly higher reduction in performance among those belonging to the high and moderate noise perception group as compared to those belonging to the low noise perception group while those who perceived traffic noise as high and moderate did not differ significantly only at higher levels of sensitivity. Using OGRS computational tool, a sensitivity value of 5.586 was identified as the Johnson-Neyman boundary of significance for the direct effect. The results from the study highlight the need for including environmental noise related regulations with regard to residential structures by the concerned authorities and also the need for undertaking more rigorous studies by health authorities and organizations so that the effects are minimized if not eliminated completely.

Circulatory health risks from additive multi-pollutant models: short-term exposure to three common air pollutants in Canada

Numerous studies have reported adverse health effects of ambient air pollution on circulatory health outcomes mainly based on single-pollutant models. However, limited studies have focused on adjusted effect of multi-pollutant exposures on public health. This study aimed to examine short-term effects of three common air pollutants-ground-level ozone (ozone), nitrogen dioxide (NO2), and fine particulate matter (PM2.5)-through multi-pollutant models for mixed effect of adjustment. Daily data (circulatory hospitalization and mortality) and hourly data (air pollutants and temperature) were collected for 24 Canadian cities for 2001-2012. We applied generalized additive over-dispersion Poisson regression models with 1, 2, or 3 pollutants for city-specific risks, and Bayesian hierarchical models for national risks. This study found little mixed effect of adjustment through multi-pollutant models (ozone and/or NO2 and/or PM2.5) for circulatory hospitalization or mortality in Canada for 2001-2012, indicating that the 1-pollutant model did not result in considerable under- or over-estimates. It seemed weak-to-moderate correlations among air pollutants did not change the significant effect of one air pollutant after accounting for others. Inconsistent findings between other previous studies and this study indicate the need of comparable study design for multi-pollutant effect analysis.

Association between air pollution exposure and gestational diabetes mellitus in pregnant women: a retrospective cohort study

The global prevalence of gestational diabetes mellitus (GDM) is increasing annually, and previous research reports on the relationship between exposure to air pollutants and GDM are not completely consistent. We investigated the association between air pollutant exposure and GDM in pregnant women in a retrospective cohort study in Guangzhou. We found that in the first trimester, exposure to PM_2.5 and CO showed a significant association with GDM. In the second trimester, exposure to PM₁₀ was significantly associated with GDM. In the third trimester, exposure to PM_2.5, PM₁₀, NO₂, SO₂, and CO at IQR4 (odds ratio [OR] = 1.271, 95% confidence interval [CI]: 1.179-1.370; OR = 1.283, 95% CI: 1.191-1.383; OR = 1.230, 95% CI: 1.145-1.322; OR = 1.408, 95% CI: 1.303-1.522; OR = 1.150, 95% CI: 1.067-1.240, respectively) compared with IQR1 was positively associated with GDM. However, exposure to NO₂ was negatively associated with GDM in the first and second trimesters, and O₃ was negatively associated with GDM in the second and third trimesters. We found that the correlation between air pollutants and GDM in different trimesters of pregnancy was not completely consistent in this retrospective cohort study. During pregnancy, there may be an interaction between air pollutant exposure and other factors, such as pregnant women's age, occupation, anemia status, pregnancy-induced hypertension status, and pregnancy season.