Field-based longitudinal study design for measuring the association between indoor air quality and occupant health status in residential buildings.

There has been a growing interest in the association between indoor air quality (IAQ) with an increase in the time spent at home. However, there is still a lack of evidence on the impact of IAQ on occupants' health and well-being in the long term. This study aimed to develop a field-based longitudinal study design to evaluate the IAQ level and daily symptoms of adults and children living in different types of buildings over one year. We proposed vital principles to be considered when recruiting the study participants so that potential confounders, such as age, underlying diseases, and the geographic area would be either removed in advance or matched between different building types. We suggested collecting exposure and outcome data in three categories: lifestyle and housing environment, IAQ measurement, and occupants' health. We presented web-based survey tools for collecting housing and health data, and the frequency of data collection varied from weekly to six-month intervals. We developed two different models using a generalized mixed model for modeling the association between housing environment, IAQ, and human health. The current study design could be applied for future studies on the association between built environment and health, regardless of the type of buildings.•A real-time indoor air quality monitor was used to monitor indoor air parameters every 5 mins over one year.•A simple web-based survey tool was developed to collect data for occupants' daily symptoms in the long term.•A binomial generalized linear mixed model and a Poisson generalized linear mixed model was developed to evaluate the association between indoor air parameters, and building types and daily symptoms.

Population Response to Air Pollution and the Risk of Coronavirus Disease in Chinese Cities during the Early Pandemic Period.

Health behavior is a critical measure in controlling the coronavirus disease 2019 (COVID-19) pandemic. We estimated the effect of health behaviors against air pollution on reducing the risk of COVID-19 during the initial phase of the pandemic. The attack rates of COVID-19 in 159 mainland Chinese cities during the first 2 weeks after the closure of major cities was estimated; air pollution level as a surrogate indicator of the mask-wearing rate. Data on air pollution levels and meteorologic factors 2 weeks prior to the closure were obtained. The attack rate was compared with the level of air pollution using a generalized linear model after adjusting for confounders. When fine particulates (PM2.5) and nitrogen dioxide (NO2) levels increased by one unit of air quality index (AQI), the infection risk decreased by 0.7% and 3.4%, respectively. When PM2.5 levels exceeded 150 (level 4), the infection risk decreased (relative risk, RR = 0.635, 95% confidence interval, CI: 0.442 to 0.912 for level 4; RR = 0.529, 95% CI: 0.337 to 0.830 for level 5; respectively). After controlling for the number of high-speed railway routes, when PM2.5 and NO2 levels increased by one AQI, relative risk for PM2.5 and NO2 was 0.990 (95% CI, 0.984 to 0.997) and 0.946 (95% CI, 0.911 to 0.982), respectively, demonstrating a consistently negative association. It is postulated that, during the early phase of the pandemic, the cities with higher air pollution levels may represent the higher practice of mask-wearing to protect from air pollution, which could have acted as a barrier to the transmission of the virus. This study highlights the importance of health behaviors, including mask-wearing for preventing infections.

Effects of mechanical ventilation on indoor air quality and occupant health status in energy-efficient homes: A longitudinal field study.

Despite the growing interest in energy-efficient homes (EEHs), there is still a lack of evidence regarding whether the mechanical ventilation system of an EEH positively or negatively impacts indoor air quality (IAQ) and the health and wellbeing of occupants. This study aimed to evaluate the IAQ level and daily health symptoms of adults and children living in EEHs compared to conventional buildings over the course of one year. A two-way mixed analysis of variance was conducted to compare the level of IAQ between the two housing types. A binomial generalized linear mixed model (GLMM) and generalized additive mixed model was developed to investigate the association between IAQ and daily risks of symptoms. Differences in the daily prevalence of symptoms between the two housing types were assessed using a Poisson GLMM model. Overall, the indoor concentrations of particulate matter (PM10 and PM2.5), carbon dioxide (CO2), and volatile organic compounds (VOCs) were lower in EEH after controlling for seasonality. The indoor temperature and relative humidity level were relatively constant in the EEH. We also found that an increased level of indoor air quality parameters, particularly CO2, which is closely related to the indoor ventilation rate, was associated with the daily risk of eye fatigue, allergic rhinitis, and atopic dermatitis symptoms. Considering that EEH effectively reduced indoor air pollutants and IAQ improvement was associated with a reduction in the risk of individual symptoms, the IAQ improvement of EEH may have positively impacted occupants' health. Symptoms such as eye fatigue and skin dryness, which have been reported in previous studies as potential side effects of mechanical ventilation, were reported in this study; however, they were not found to be statistically significantly different from those reported in the conventional building.

Establishment of the Korea National Health and Nutrition Examination Survey air pollution study dataset for the researchers on the health impact of ambient air pollution.

To provide a nationwide representative dataset for the study on health impact of air pollution, we combined the data from the Korea National Health and Nutrition Examination Survey with the daily air quality and weather data by matching the date of examination and the residential address of the participants. The database of meteorological factors and air quality as sources of exposure data were estimated using the Community Multiscale Air Quality model. The linkage dataset was merged by three ways; administrative district, si-gun-gu (city, county, and district), and geocode (in latitude and longitude coordinate units) based on the participants' residential address, respectively. During the study period, the exposure dataset of 85,018 individuals (38,306 men and 46,712 women) whose examination dates were recorded were obtained. According to the definition of exposure period, the dataset was combined with the data on short-term, mid-term, and long-term exposure to air pollutants and the meteorological indices. Calculation of the daily merged dataset's average air pollution linked by si-gun-gu and geocode units showed similar results. This study generated a daily average of meteorological indices and air pollution exposure dataset for all regions including rural and remote areas in Korea for 11 years. It is expected to provide a platform for the researchers studying the health impact of air pollution and climate change on the representative population and area, which may facilitate the establishment of local health care plans by understanding the residents' health status at the local as well as national level.