Lee Y, et al. Yonsei Med J. 2023 May;64(5):301-308. https://doi.org/10.3349/ymj.2023.0048

Land-use regression (LUR) has emerged as a promising technique for air pollution modeling to obtain the spatial distribution of air pollutants for epidemiological studies. LUR uses traffic, geographic, and monitoring data to develop regression models and then predict the concentration of air pollutants in the same area. To identify the spatial distribution of nitrogen dioxide (NO₂), benzene, toluene, and m-p-xylene, we developed LUR models in Pohang City, one of the largest industrialized areas in Korea. Passive samplings were conducted during two 2-week integrated sampling periods in September 2010 and March 2011, at 50 sampling locations. For LUR model development, predictor variables were calculated based on land use, road lengths, point sources, satellite remote sensing, and population density. The averaged mean concentrations of NO₂, benzene, toluene, and m-p-xylene were 28.4 µg/m³, 2.40 µg/m³, 15.36 µg/m³, and 0.21 µg/m³, respectively. In terms of model-based R² values, the model for NO₂ included four independent variables, showing R² = 0.65. While the benzene and m-p-xylene models showed the same R² values (0.43), toluene showed a lower R² value (0.35). We estimated long-term concentrations of NO₂ and VOCs at 167,057 addresses in Pohang. Our study could hold particular promise in an epidemiological setting having significant health effects associated with small area variations and encourage the extended study using LUR modeling in Asia.

While epidemiological studies have examined the effects of exposure to particulate matter with diameter ≤2.5 μm (PM_2.5) on heart rate variability (HRV) on a daily basis, there is a need for more granular data to better understand the ultrashort-term effects of PM_2.5 on HRV. This study aimed to investigate the minute-level association between PM_2.5 exposure and HRV using real-time personal monitoring data, focusing on time-lagged effects in vulnerable populations. We collected minute-by-minute data of PM_2.5 and HRV using a wearable device from 73 individuals, with 3 days of continuous observations per participant (total 315,360 observations). PM_2.5 and electrocardiogram (ECG)-derived HRV indices, including the standard deviation of normal-to-normal intervals (SDNN) and the root mean square of successive differences (RMSSD), were continuously measured for five days using wearable devices. Distributed lag non-linear and linear mixed-effects models were used to evaluate exposure-response relationships. PM_2.5 exposure was significantly associated with acute HRV reductions within 180 min. SDNN decreased by -8.04 % (95 % CI: 11.10 % to -4.88 %) at the initial lag following exposure, peaking at approximately 49 min and gradually attenuating thereafter, and RMSSD decreased by -4.17 % (95 % CI: 7.23 % to -1.00 %) at the initial lag, with a similar attenuation pattern beyond 38 min. More pronounced effects occurred during nighttime (18:00-06:00), with SDNN decreasing by -13.9 % (95 % CI: 17.81 % to -9.80 %) and RMSSD by -7.43 % (95 % CI: 11.13 % to -3.57 %). Females exhibited a more immediate HRV decline at the initial lag (SDNN: 10.24 %, RMSSD: 6.39 %) compared to males (SDNN: 4.44 %, RMSSD: 8.61 %). Patients with arrhythmia showed the greatest reductions at the initial lag (SDNN: 11.42 %, RMSSD: 15.95 %). This study highlights the immediate autonomic impact of PM_2.5 exposure, emphasizing its differential effects by time of day, sex, and health status. Findings underscore the importance of personal air pollution monitoring and targeted interventions for high-risk populations.

Whether personal heating tools can reduce cold stress and stabilize cardiovascular autonomic responses in motorcycle delivery riders remains unclear. This single-group pre–post intervention study evaluated heated-vest use among 35 male motorcycle delivery riders in Seoul during a winter cold-wave period. Participants completed a field-based protocol consisting of a baseline period with the heated vest powered off and an intervention period with the vest powered on. Wearable sensors attached to the chest measured core body temperature and cardiovascular indices, including heart rate, RR interval, SDNN, RMSSD, and pNN50. Subjective cold perception was assessed by interview before and after the intervention. Distributed lag non-linear models within a linear mixed-effects framework were used to examine lagged associations between participant-centered core body temperature deviations and cardiovascular indices. Participant-specific model-derived lag-response metrics were further evaluated in relation to subjective cold perception. Heated-vest use significantly increased core body temperature. In lag-response analyses, the association between core body temperature deviation and SDNN was significantly attenuated after heated-vest use, with a significant interaction effect (β = 0.213, 95% CI: 0.043 to 0.384). In addition, narrower confidence interval widths of participant-specific lag-response estimates after the intervention were consistently associated with higher subjective cold perception scores across cardiovascular indices. These findings suggest that heated vests may provide a practical personal thermal adaptation strategy that supports physiological stability and subjective thermal protection among motorcycle delivery riders working in cold environments.