Characterization and exposure assessment of household fine particulate matter pollution in China

Geographical Distribution of Dietary Patterns and Their Association with T2DM in Chinese Adults Aged 45 y and Above: A Nationwide Cross-Sectional Study

BACKGROUND

This study aimed to investigate the geographical distribution of dietary patterns and their association with T2DM among Chinese adults aged 45 years and above.

METHODS

Data was from the China Adults Chronic Diseases and Nutrition Surveillance (2015). Dietary intake for each participant was determined through a combination of 3-day 24-h dietary recall interviews and food frequency questionnaires. Principal component analysis was used to extract dietary patterns and spatial analysis was employed to investigate the geographic distribution of them. T2DM was diagnosed using criteria of ADA 2018, and binary logistic regression was employed to examine the relationship between dietary patterns and T2DM.

RESULTS

A total of 36,648 participants were included in the study; 10.9% of them were diagnosed as T2DM. Three dietary patterns were identified with the name of plant-based pattern, animal-based pattern, and oriental traditional pattern, which were represented located in northern, northwest, and southern regions, respectively. After adjusting for potential confounders, participants in the highest quartile of the plant-based pattern were associated with lower T2DM odds (OR = 0.82, 95% CI: 0.74, 0.90) when comparing with the lowest quartile. However, participants inclined to higher quartiles of animal-based pattern had a higher risk of T2DM (OR = 1.15, 95% CI: 1.04, 1.27) compared with those in the lower quartiles. No significant association was found between the oriental traditional pattern and T2DM (OR = 1.03, 95% CI: 0.93, 1.14).

CONCLUSION

Dietary patterns of Chinese population revealed geographical disparities, with plant-based dietary pattern showing protective effects and animal-based pattern carrying high risks for T2DM. Regional dietary variations and food environment are paramount in T2DM prevention and management.

Quantifying the dynamic characteristics of indoor air pollution using real-time sensors: Current status and future implication

People generally spend most of their time indoors, making indoor air quality be of great significance to human health. Large spatiotemporal heterogeneity of indoor air pollution can be hardly captured by conventional filter-based monitoring but real-time monitoring. Real-time monitoring is conducive to change air assessment mode from static and sparse analysis to dynamic and massive analysis, and has made remarkable strides in indoor air evaluation. In this review, the state of art, strengths, challenges, and further development of real-time sensors used in indoor air evaluation are focused on. Researches using real-time sensors for indoor air evaluation have increased rapidly since 2018, and are mainly conducted in China and the USA, with the most frequently investigated air pollutants of PM_2.5. In addition to high spatiotemporal resolution, real-time sensors for indoor air evaluation have prominent advantages in 3-dimensional monitoring, pollution peak and source identification, and short-term health effect evaluation. Huge amounts of data from real-time sensors also facilitate the modeling and prediction of indoor air pollution. However, challenges still remain in extensive deployment of real-time sensors indoors, including the selection, performance, stability, as well as calibration of sensors. In future, sensors with high performance, long-term stability, low price, and low energy consumption are welcomed. Furthermore, more target air pollutants are also expected to be detected simultaneously by real-time sensors in indoor air monitoring.

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.

Household PM2.5 pollution in rural Chinese homes: Levels, dynamic characteristics and seasonal variations

Humans generally spend most of their time indoors, and fine particulate matter (PM_2.5) in indoor air can have seriously adverse effects on human health due to the long exposure time. This study conducted field measurements to explore seasonal variations of PM_2.5 concentrations in household air by revisiting the same rural homes in southern China and factors influencing indoor PM_2.5 concentrations were explored mainly by one-way ANOVA. The PM_2.5 concentrations of outdoor, kitchen and living room air were 38.9 ± 12.2, 47.1 ± 20.3 and 50.8 ± 24.1 μg/m³ in summer, respectively, which were 2.3 to 2.9 times lower than those in winter (p < 0.05). The lower indoor PM_2.5 pollution in summer was attributed to the transition to clean household energy and better ventilation. Fuel type can significantly affect PM_2.5 concentrations in the kitchen, with greater PM_2.5 pollution associated with wood combustion than electricity. Our study firstly found mosquito coil emission was an important contributor to PM_2.5 in the living room of rural households, which should be investigated further. Dynamic variations of PM_2.5 suggested that cooking, heating and mosquito coil emission can rapidly increase indoor PM_2.5 concentrations (up to one order of magnitude higher than baseline values), as well as the indoor/outdoor PM_2.5 ratios. This study had the first insight of seasonal differences of household PM_2.5 in the same rural homes using real-time monitors, confirming the different patterns and characteristics of household PM_2.5 pollution in different seasons.

The Exposure of Workers at a Busy Road Node to PM2.5: Occupational Risk Characterisation and Mitigation Measures

The link between air pollution and health burden in urban areas has been well researched. This has led to a plethora of effective policy-induced monitoring and interventions in the global south. However, the implication of pollutant species like PM_2.5 in low middle income countries (LMIC) still remains a concern. By adopting a positivist philosophy and deductive reasoning, this research addresses the question, to what extent can we deliver effective interventions to improve air quality at a building structure located at a busy road node in a LMIC? This study assessed the temporal variability of pollutants around the university environment to provide a novel comparative evaluation of occupational shift patterns and the use of facemasks as risk control interventions. The findings indicate that the concentration of PM_2.5, which can be as high as 300% compared to the WHO reference, was exacerbated by episodic events. With a notable decay period of approximately one-week, adequate protection and/or avoidance of hotspots are required for at-risk individuals within a busy road node. The use of masks with 80% efficiency provides sufficient mitigation against exposure risks to elevated PM_2.5 concentrations without occupational shift, and 50% efficiency with at least ‘2 h ON, 2 h OFF’ occupational shift scenario.

Quantify individual variation of real-time PM2.5 exposure in urban Chinese homes based on a novel method

Fine particulate matter (PM_2.5 ) concentrations show high variations in different microenvironments indoors, which has considerable impact on risk management. However, the real-time variations of PM_2.5 exposure associated with per activity/microenvironment and intra-variation among family members remain undefined. In this study, real-time monitors were used to collect real-time PM_2.5 data in different microenvironments in 32 households in urban community of China. Peak concentrations of PM_2.5 were found in kitchen. The parallel levels of PM_2.5 household indoor and outdoor indicated the benefit of clean energies use. To validly assess the health risk of individuals, we proposed a novel method to estimate the real-time exposure of all residents and firstly investigate the intra-variation of PM_2.5 exposure among family members. The member who is responsible for cooking in the family had the maximum PM_2.5 exposure. The ratios among intraindividual variations demonstrated children usually had lower exposure compared to the adults as they stayed more time in lower polluted microenvironments such as living room and bedroom. The exposure intensity in living room was above 1.0 for most residents, indicating it is warranted to alleviate the air pollution in living room. This study firstly focused on the intra differences of PM_2.5 exposure among family members and provided a new insight for indoor air pollution management. The results suggested when adopting measures to reduce exposure, the microenvironments pattern of each member should be taken into consideration. Future work is welcomed to move another big step on this issue to protect the human health.

Characteristics, distribution, and children exposure assessment of 13 metals in household dust in China: A big data pilot study

To explore the pollution characteristics of metals in household dust in China and their exposure to children, this study searched peer-reviewed papers published during 1980-2020 and analyzed 30 eligible papers screened under the per-decided strategy. We evaluated the sample-weighted concentration (SWC) of each metal, explored the sources of metals, and presented the quantitative description of spatial-temporary characteristics and children exposure to 13 metals with multi-route under a general living scenario. The results showed the concentrations of 13 metals with a range of 0.89-29 090.19 mg/kg. The SWC of Cd in household dust from rural areas was 3.29 times of that from urban areas, while the SWC of Ni from urban areas was 3.71 times of that from rural areas. The results showed that four principal components were extracted, and the cumulative contribution rate reached 79.127%. The exposure dose of 13 metals to children aged 2-3 years was presented with the highest by ingestion. Metals such as Fe, Zn, and Mn posed inevitable health risk to children with high exposure. Countermeasures should be carried out to minimize the children exposure to metals in household dust urgently, such as the establishment of environmental health standard for household dust.