Association of indoor noise level with depression in hotel workers: A multicenter study from 111 China's cities.

Several studies have elucidated the link between outdoor noise and depression, but the relationship between indoor noise levels and depression symptoms in residential and public places remains unclear. This study was a multicenter observational study with a cross-sectional design. In 2019, a total of 10 545 indoor noise levels on-site and 26 018 health data from practitioners were collected from 2402 hotels in 111 cities. Indoor daily noise data levels were detected, and PHQ-9 questionnaires were used to collect health data. Logistic analysis was used to determine the association between depression score and noise level, negative binomial regression was used to determine potential risks. The geometric mean indoor noise level was 38.9 dB (A), with approximately 40.9% of hotels exceeding the 45 dB value (A). Approximately 19.1% of hotel workers exhibited mild and above depressive symptoms. In addition to functional zoning, geographic location, central air conditioner, decoration status, and other factors had an impact on noise levels (p < 0.05). Results of logistic and negative binomial regression showed the following: (1) there was significantly positive association between indoor noise and high depression scores above 2 (OR = 1.007, 95% CI: 1.002, 1.012) and (2) some sub-groups were more susceptible to this effect, especially for the younger female workers working in the first-tier cities, having higher education level, lower level of income, smoking, and longer working hours. This study confirms an early potential effect of indoor noise on depression. It is recommended to implement evidence-based measures to control noise sources in hotels.

The relationship of residential formaldehyde pollution in 11 Chinese cities to schoolchildren pneumonia prevalence in actual living condition.

Residential formaldehyde pollution is one of the leading residential harmful pollutants with a large production and consumption globally and remains much uncertainty in Chinese families with huge health burden for children worldwide. A multi-center observation study from 11 cities was conducted to investigate residential formaldehyde pollution levels measured by phenol reagent spectrophotometry. Data on household characteristics and schoolchildren's health were collected by questionnaire. The median concentration of residential formaldehyde was 0.025 (0.002-0.281) mg/m3 among 11 cities with the total exceeding standard rate of 7.40% according to the reference value of 0.10 mg/m3 (1-h average). Residential formaldehyde pollution in warm season, bedrooms and northern cities was more serious than that in cold season, living rooms and southern cities, respectively. The potential influencing factors of residential formaldehyde included household characteristics (distance from a traffic road, building history, residence duration, window glass layers, decoration and furniture) and use of air conditioner. The positive regulation effect of temperature on residential formaldehyde was explored with the approximately turning-point temperature of 28.9 °C for peak concentration. Long-term exposure to residential formaldehyde of low concentrations (0.010-0.090 mg/m3) would increase the prevalence of childhood pneumonia and a more stringent criteria value for residential formaldehyde should be discussed cautiously.

Source, Characterization of Indoor Dust PAHs and the Health Risk on Chinese Children.

Polycyclic aromatic hydrocarbons (PAHs) in indoor dust are one of the common exposure sources for children worldwide. The aim of this study is to explore PAHs pollution status in indoor dust and estimate health risk on Chinese children with big data. Weighted average concentration was used to analyze source and characterization of PAHs in indoor dust based on peer-reviewed literature. According to specific inclusion criteria, 17 studies were included finally to analyze weighted average concentration. The national average concentration of Σ16PAHs was approximately 25.696 µg/g. The highest concentration of Σ16PAHs was in Shanxi (2111.667 µg/g), and the lowest was in Hong Kong (1.505 µg/g). The concentrations in Shanxi and Guangdong were higher than national level and the over standard rate was 18.18%. The concentrations of individual PAHs varied greatly across the country, and Flu in Shanxi was the highest (189.400 µg/g). The sources of PAHs varied in different regions and combustion processes played a leading role. PAHs exposure through ingestion and dermal contact was more carcinogenic than inhalation. The incremental lifetime cancer risk model indicated that children lived in Shanxi were found in the highest health risk coupled with the highest BaPE concentration (54.074 µg/g). Although PAHs concentrations of indoor dust showed a downward trend from 2005 to 2018, indoor environmental sanitation should be improved with multidisciplinary efforts. Health standard should be possibly established to minimize children exposure to PAHs in indoor dust in China.

Construction of a nomogram for predicting the risk of allergic rhinitis among employees of long-distance bus stations in China.

This study examined indoor air pollutants and their health effects on allergic rhinitis in 3194 employees of 226 bus station halls and then constructed a nomogram model to predict allergic rhinitis risk in those employees. Indoor air temperature, relative humidity, PM10 , PM2.5 , total bacteria, and total fungi were measured, and questionnaires were used to collect basic station information and employee health information. The results revealed that the over-standard rates of PM10 , PM2.5 , total bacteria, and total fungi were 18.16%, 31.13%, 2.22%, and 55.89%, respectively. Seasonal variations were found in temperature, relative humidity, and PM2.5 . Passenger flow could affect temperature, and total bacteria. Central air conditioning could affect total bacteria. A total of 15.90% of the employees were diagnosed as allergic rhinitis by physicians. Relative humidity, fungi, self-reported allergic rhinitis symptoms, and exposure to smoking were the influencing factors for allergic rhinitis. These four variables were incorporated to construct a nomogram. The concordance index of the nomogram was 0.775 (95% CI: 0.745-0.806) and 0.749 (95% CI: 0.715-0.783) for the training cohort and test cohort, respectively. The calibration plot revealed that the nomogram model exhibited good discrimination and consistency. This nomogram model may help predict the occurrence of allergic rhinitis.