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Background This study aims to explore issues, such as (i) whether there is a difference in quality of life (QoL) among subgroups of the work mode (working from home (WFH) vs. working in the office (WIO)), social contact quantity, and face contact ratio; (ii) whether employees' QoL is moderated by the social contact quantity and face contact ratio given their work mode; (iii) whether the three-way interaction effect of work mode, social contact quantity, and face contact ratio on employee's QoL is significant; and (iv) whether the WHOQOL-BREF invariantly measures for the subgroups of the work mode, social contact quantity, and face contact ratio. Methods We assessed the QoL of 803 WFH employees and 588 WIO employees during the same time period and divided them into sixteen groups resulting from the levels of work mode, social contact quantity, and face contact ratio, forming a case-control study. A differential item functioning (DIF) analysis was used for analyzing the responses on the WHOQOL-BREF under the 4-dimensional rating scale model fitting. Results Our results indicated that WFH employees’ QoL was superior to that of WIO employees [χ2(1) = 8.52, p = 0.0035]. However, since the work mode was moderated by the social contact quantity [χ2(3) = 10.89, p = .012] and face contact ratio [χ2(1) = 11.39, p < .001], WFH employees’ QoL was worse than that of WIO employees if their amount of social contact was low and if most social contacts were not face-to-face. Moreover, WFH employees’ QoL was better than WIF employees’ QoL when most contacts were not face-to-face and the number of social contacts was high [χ2(3) = 9.07, p = .028]. Besides, the WHOQOL-BREF measured employees’ QoL biasedly as many facets of the WHOQOL-BREF were found to diverge among subgroups of the work mode and social contact quantity.Conclusions The WFH mode was practical in the COVID-19 pandemic. However, maintaining social connections is equally important so that employees can maintain good performance in jobs. The facets detected as DIF items provided implications for QoL research methodology and insight into factors affecting employees' QoL.

Additional file 1: Table S1. Hazard ratios of different kinds of mortality. Table S2. Hazard ratios of variables and mortality by multivariate Cox proportional hazards model (baseline). Table S3. Hazard ratios of variables and mortality by multivariate Cox frailty model

ObjectivesEnvironmental exposure to chemicals has been considered a potential factor contributing to deteriorated semen quality. However, previous literature on exposure to air pollution and semen quality is inconsistent. We therefore investigated the health effects of short-term and long-term exposure to fine particulate matter (PM2.5) on semen quality in Taiwanese men from the general population.MethodsA cross-sectional study was conducted among 6475 male participants aged 15–49 years who participated in a standard medical examination programme in Taiwan between 2001 and 2014. Semen quality was assessed according to the WHO 1999 guidelines, including sperm concentration, total motility, progressive motility and morphology. Three-month and 2-year average PM2.5concentrations were estimated at each participant’s address using a spatiotemporal model based on satellite-derived aerosol optical depth data. Multivariable linear and logistic regressions were used to examine the associations between PM2.5and semen quality.ResultsA robust association was observed between exposure to PM2.5and decreased normal morphology. Every increment of 5 µg/m3in 2-year average PM2.5was significantly associated with a decrease of 1.29% in sperm normal morphology and a 26% increased risk of having the bottom 10% of sperm normal morphology, after adjusting for a wide range of potential confounders (p3in 2-year average PM2.5was associated with an increase of 1.03×106/mL in sperm concentration and a 10% decreased risk of being the bottom 10% of sperm concentration (both p2.5.ConclusionsExposure to ambient PM2.5air pollution is associated with a lower level of sperm normal morphology and a higher level of sperm concentration.

BACKGROUND: Chronic kidney disease (CKD) is a serious global public health challenge, but there is limited information on the connection between air pollution and risk of CKD. OBJECTIVE: The aim of this study was to investigate the association between long-term exposure to particulate matter (PM) with an aerodynamic diameter of less than [Formula: see text] ([Formula: see text]) and the development of CKD in a large cohort. METHODS: A total of 100,629 nonCKD Taiwanese residents age 20 y or above were included in this study between 2001 and 2014. Ambient [Formula: see text] concentration was estimated at each participant's address using a satellite-based spatiotemporal model. Incident CKD cases were identified by an estimated glomerular filtration rate (eGFR) of less than [Formula: see text]. We collected information on a wide range of potential confounders/modifiers during the medical examinations. Cox proportional hazard regression was applied to calculate hazard ratios (HRs). RESULTS: During the follow-up, 4,046 incident CKD cases were identified, and the incidence rate was 6.24 per 1,000 person-years. In contrast with participants with the first quintile exposure of [Formula: see text], participants with the fourth and fifth quintiles exposure of [Formula: see text] had increased risk of CKD development, adjusting for age, sex, educational level, smoking, drinking, body mass index, systolic blood pressure, fasting glucose, total cholesterol, and self-reported heart disease or stroke, with an HR [95% confidence interval (CI)] of 1.11 (1.02, 1.22) and 1.15 (1.05, 1.26), respectively. A significant concentration-response trend was observed ([Formula: see text]). Every [Formula: see text] increment in the [Formula: see text] concentration was associated with a 6% higher risk of developing CKD (HR: 1.06, 95% CI: 1.02, 1.10). Sensitivity and stratified analyses yielded similar results. CONCLUSIONS: Long-term exposure to ambient [Formula: see text] was associated with an increased risk of CKD development. Our findings reinforce the urgency to develop global strategies of air pollution reduction to prevent CKD. https://doi.org/10.1289/EHP3304.

Background The protective effects of physical activity (PA) against chronic disease can be partially ascribed to its anti-inflammatory effects. On the other hand, long-term exposure to particulate matter with an aerodynamic diameter less than 2.5 μm (PM 2.5 ) may induce systemic inflammation. Objective To investigate the joint effects of habitual PA and long-term exposure to PM 2.5 on systemic inflammation in a large cohort of Taiwanese adults. Methods We studied 359,067 adult participants from a cohort consisting of Taiwanese residents who participated in a standard medical examination program from 2001 to 2014. Peripheral white blood cell (WBC) and differential counts were measured as indicators of systemic inflammation. Two-year average concentration of PM 2.5 was estimated at each participant‘s address using a satellite-based spatio-temporal model. Habitual PA level was assessed by questionnaire (inactive, low, moderate and high). Mixed-effects linear regression model was used to examine the associations of WBC counts with PM 2.5 and PA. Results Compared with inactive participants, those with low, moderate or high PA levels had 0.36% [95% confidence interval (CI): 0.31%, 0.41%], 0.70% (95%CI: 0.65%, 0.76%) and 1.16% (95%CI: 1.11%, 1.22%) lower WBC counts, respectively, after adjusting for PM 2.5 exposure and a wide range of confounders. Long-term PM 2.5 exposure was associated with increased WBC counts at all PA levels. Analyses for differential counts generated similar results. No significant interaction was observed between PA and PM 2.5 exposure ( P for interaction = 0.59). Conclusions Habitual PA was associated with statistically significant lower markers of systemic inflammation across different levels of PM 2.5 . Effects of PA and PM 2.5 exposure on systemic inflammation are independent.

In the control of infectious diseases, epidemiologic information and useful clustering algorithms can be integrated to garner key indicators from huge amounts of daily surveillance information for the need of early intervention. This chapter first introduces the temporal, spatial and spatio-temporal clustering algorithms commonly used in surveillance systems–the key concepts behind the algorithms and the criteria for appropriate use. This description is followed by an introduction to different statistical methods that can be used to analyze the clustering patterns which occur in different epidemics and epidemic stages. Research methods such as flexible analysis of irregular spatial and temporal clusters, adjustment of personal risk factors, and Bayesian approaches to disease mapping and better prediction all will be needed to understand the epidemiologic characteristics of infectious diseases in the future.

Background Particulate matter (PM) air pollution is associated with the risk of cardiovascular morbidity and mortality. However, the biological mechanism underlying the associations remains unclear. Atherosclerosis, the underlying pathology of cardiovascular disease, is a chronic inflammatory process. We therefore investigated the association of long-term exposure to fine PM (PM2.5) with C-reactive protein (CRP), a sensitive marker of systemic inflammation, in a large Taiwanese population. Methods Participants were from a large cohort who participated in a standard medical examination programme with measurements of high-sensitivity CRP between 2007 and 2014. We used a spatiotemporal model to estimate 2-year average PM2.5 exposure at each participant’s address, based on satellite-derived aerosol optical depth data. General regression models were used for baseline data analysis and mixed-effects linear regression models were used for repeated data analysis to investigate the associations between PM2.5 exposure and CRP, adjusting for a wide range of potential confounders. Results In this population of 30 034 participants with 39 096 measurements, every 5 μg/m3 PM2.5 increment was associated with a 1.31% increase in CRP [95% confidence interval (CI): 1.00%, 1.63%) after adjusting for confounders. For those participants with repeated CRP measurements, no significant changes were observed between the first and last measurements (0.88 mg/l vs 0.89 mg/l, P = 0.337). The PM2.5 concentrations remained stable over time between 2007 and 2014. Conclusions Long-term exposure to PM2.5 is associated with increased level of systemic inflammation, supporting the biological link between PM2.5 air pollution and deteriorating cardiovascular health. Air pollution reduction should be an important strategy to prevent cardiovascular disease.