Indoor air quality (IAQ) has a substantial impact on public health. Since the beginning of the COVID-19 pandemic, more employees have worked remotely from home to minimize in-person contacts. This pilot study aims to measure the difference in workplace IAQ before and during the pandemic and its impact on employees’ health. The levels of fine particulate matter (PM2.5) and total volatile organic chemicals (tVOC) were measured in the employees’ offices before the COVID-19 pandemic and at homes while working from home during the pandemic using Foobot air monitors. The frequencies of six sick building syndrome (SBS) symptoms were evaluated at each period of monitoring. The result showed PM2.5 levels in households while working from home were significantly higher than in offices while working at the office for all participants (p < 0.05). The PM2.5 levels in all households exceeded the health-based annual mean standard (12 µg/m3), whereas 90% of offices were in compliance. The tVOC levels were all below the standard (500 µg/m3). We also found a higher frequency of SBS symptoms were observed while working from home as the IAQ was worse at home. This study suggested that working from home might have a detrimental health impact due to poor IAQ and providing interventions to remote employees should be considered.
Objective: Few studies have examined factors affecting the high frequency of hospitalization for pediatric asthma. This study identifies individual and environmental characteristics of children with asthma from a low-income community with a high number of hospitalizations. Methods: The study population included 902 children admitted at least once to a children's hospital in South Texas because of asthma from 2010 to 2016. The population was divided into three groups by utilization frequency (high: !4 times, medium: 2-3 times, or low: 1 time). Individual-level factors at index admission and environmental factors were included for the analysis. Unadjusted and adjusted multivariate ordered logistic regression models were applied to identify significant characteristics of high hospital utilizers. Results: The high utilization group comprised 2.4% of total patients and accounted for substantial hospital resource utilization: 10.8% of all admissions and 13.5% of days stayed in the hospital. Patients in the high utilization group showed longer length of stay (LOS) and shorter time between admissions on average than the other two groups. The multivariate ordered logistic regression models revealed that age of 5-11 years (OR ¼ 0.57, 95%CI ¼ 0.35-0.93), longer LOS (2 days: OR ¼ 1.80, 95%CI ¼ 1.15-2.84; !3 days: OR ¼ 3.38, 95%CI ¼ 2.10-5.46), warm season at index admission (OR ¼ 1.49, 95%CI ¼ 1.01-2.20), and higher average ozone level in children's residential neighborhoods (OR ¼ 1.78, 95%CI ¼ 1.01-3.14) were significantly associated with a higher number of asthma hospitalizations. Conclusions: The findings suggest the importance of monitoring high hospital utilizers and establishing strategies for such patients based on their characteristics to reduce repeated hospitalizations and to increase optimal use of hospital resources.
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