Effects of Coexposure to Air Pollution from Vegetation Fires and Extreme Heat on Mortality in Upper Northern Thailand.

Background: understanding the effects of coexposure to compound extreme events, such as air pollution and extreme heat, is important for reducing current and future health burdens. This study investigated the independent and synergistic effects of exposure to air pollution from vegetation fires and extreme heat on all-cause mortality in Upper Northern Thailand. Methods: we used a time-stratified case-crossover study design with a conditional quasi-Poisson model to examine the association between mortality and coexposure to air pollution due to vegetation fire events (fire-PM2.5) and extreme heat. Extreme heat days were defined using the 90th and 99th percentile thresholds for daily maximum temperature. Results: we observed a significant positive excess risk of mortality due to independent exposure to fire-PM2.5 and extreme heat, but not an interactive effect. All-cause mortality risk increased by 0.9% (95% confidence interval (CI): 0.1, 1.8) for each 10 µg/m3 increase in fire-PM2.5 on the same day and by 12.8% (95% CI: 10.5, 15.1) on extreme heat days (90th percentile) relative to nonextreme heat days. Conclusion: this study showed that exposure to PM2.5 from vegetation fires and extreme heat independently increased all-cause mortality risk in UNT. However, there was no evidence of a synergistic effect of these events.

Impact of Climate on the Incidence of Acute Coronary Syndrome　- Differences Between Japan and Thailand.

Background: Although there are many reports of temperature being associated with the onset of acute coronary syndrome (ACS), few studies have examined differences in ACS due to climatic differences between Japan and Thailand. The aim of this joint Japan-Thailand study was to compare patients with myocardial infarction in Japanese and Thai hospitals in different climates. Methods and Results: We estimated the climate data in 2021 for the Wakayama Prefecture and Chonburi Province, two medium-sized cities in Japan and Thailand, respectively, and ACS patients who were treated at the Wakayama Medical University (WMU) and Burapha University Hospital (BUH), the two main hospitals in these provinces (ACS patient numbers: WMU, n=177; BUH, n=93), respectively. In the Chonburi Province, although the average temperature was above 25℃, the number of ACS cases in BUH varied up to threefold between months (minimum: July, 4 cases; maximum: October, 14 cases). In Japan and Thailand, there was a mild to moderate negative correlation between temperature-atmospheric pressure at the onset of ACS, but different patterns for temperature-humidity (temperature-atmospheric pressure, temperature-humidity, and atmospheric pressure-humidity: correlation index; r=-0.561, 0.196, and -0.296 in WMU vs. r=-0.356, -0.606, and -0.502 in BUH). Conclusions: The present study suggests that other climatic conditions and factors, not just temperature, might be involved in the mechanism of ACS.

History of Changes in the Protocol of Clinical Trial of Zinc Supplementation in Treatment of COVID-19 by Hydroxychloroquine.

An article published in this journal used a randomized controlled trial to evaluate the efficacy of combining chloroquine/hydroxychloroquine (CQ/HCQ) and zinc in the treatment of COVID-19 patients. Findings from this study indicate that zinc supplements did not enhance the clinical efficacy of hydroxychloroquine in improving COVID-19 treatment. Although this finding is consistent with many previous studies, several concerns regarding study protocol and trial registration, including interventions and primary outcomes, have been raised in which the protocol has been changed after the completion of the recruitment.

Associations between residential greenness and air pollution and the incident metabolic syndrome in a Thai worker cohort.

Increasing air pollution and decreasing exposure to greenness may contribute to the metabolic syndrome (MetS). We examined associations between long-term exposure to residential greenness and air pollution and MetS incidence in the Bangkok Metropolitan Region, Thailand. Data from 1369 employees (aged 52-71 years) from the Electricity Generating Authority of Thailand cohort from 2002 to 2017 were analyzed. The greenness level within 500 m of each participant's residence was measured using the satellite-derived Normalized Difference Vegetation Index (NDVI) and Enhanced Vegetation Index (EVI). The kriging approach was used to generate the average concentration of each air pollutant (PM10, CO, SO2, NO2, and O3) at the sub-district level. The average long-term exposure to air pollution and greenness for each participant was calculated over the same period of person-time. Cox proportional hazards models were used to analyze the greenness-air pollution-MetS associations. The adjusted hazard ratio of MetS was 1.42 (95% confidence interval (CI): 1.32, 1.53), 1.22 (95% CI: 1.15, 1.30), and 2.0 (95% CI: 1.82, 2.20), per interquartile range increase in PM10 (9.5 µg/m3), SO2 (0.9 ppb), and CO (0.3 ppm), respectively. We found no clear association between NDVI or EVI and the incidence of MetS. On the contrary, the incident MetS was positively associated with NDVI and EVI for participants exposed to PM10 at concentrations more than 50 µg/m3. In summary, the incidence of MetS was positively associated with long-term exposure to air pollution. In areas with high levels of air pollution, green spaces may not benefit health outcomes.

Application of satellite remote sensing data and random forest approach to estimate ground-level PM2.5 concentration in Northern region of Thailand.

Numerous epidemiological studies have shown that particulate matter with aerodynamic diameter up to 2.5 µm (PM2.5) is associated with many health consequences, where PM2.5 concentration obtained from the monitoring station was normally applied as the exposure level, so that the concentration of PM2.5 in unmonitored areas has not been captured. The satellite-derived aerosol optical depth (AOD) product is then used to spatially predict ground truth of PM2.5 concentration that covers the locations with no air quality monitoring station, but this method has seldom been developed in Thailand. This study aimed at estimating ground-level PM2.5 concentration at 3 km × 3 km spatial resolution over Northern region of Thailand in 2021 using the random forest model integrating the Moderate Resolution Imaging Spectroradiometer (MODIS) AOD products from Terra and Aqua satellites, meteorological factors, and land use data. A random forest model contained 100 decision trees was utilized to train the model, and 10-fold cross-validation approach was implemented to validate the model performance. The good consistency between actual (observed) and predicted concentrations of PM2.5 in Northern region of Thailand was observed, where a coefficient of determination (R2) and root mean square error (RMSE) of the model fitting were 0.803 and 14.30 µg/m3, respectively, and those of 10-fold cross-validation approach were 0.796 and 14.64 µg/m3, respectively. The three most important predictors for estimating the ground-level concentrations of PM2.5 in this study were normalized difference vegetation index (NDVI), relative humidity, and number of fire hotspot, respectively. Findings from this study revealed that integrating the MODIS AOD, meteorological variables, and land use data into the random forest model precisely and accurately estimated ground-level PM2.5 concentration over Northern region of Thailand that can be further used to investigate the effects of PM2.5 exposure on health consequences, even in unmonitored locations, in epidemiological studies.

Effects of the lockdown measure amid COVID-19 pandemic on outpatient department visits associated with air pollution reduction in Thailand.

We investigated the effects of COVID-19 lockdown on air quality and its consequences health and economic benefits in Thailand. The conditional Poisson regression model was applied to examine the association between air pollution and outpatient department (OPD) visits in each province and pooled the province-specific estimates using the random-effects meta-analysis to derive the national estimates. We then applied a random forest model with meteorological normalization approach to predict the concentration of air pollutants by means of business as usual during the lockdown period (April 3-May 3) in 2020 and further calculated the changes in the number of OPD visits and their consequent expenditure attributable to air pollution reduction using the obtained risk function performed earlier. The number of cardiovascular OPD visits attributed to PM10, PM2.5 and NO2 decreased by 4,414 (95% CI 982, 8,401), 4,040 (95% CI 326, 7,770), and 13,917 (95% CI 1,675, 27,278) cases, respectively, leading to reduced medical expenditure by 14,7180.21, 13,4708.31, and 46,4025.04 USD, respectively. The number of respiratory OPD visits attributed to PM10, PM2.5, NO2, and O3 reduction decreased by 2,298 (95% CI 1,223, 3,375), 2,056 (95% CI 740, 3,252), 3,326 (95% CI 542, 6,295), and 1,160 (95% CI 5,26, 1,804) cases, respectively, where the consequent medical expenditure was reduced by 76,618.48, 68,566.36, 11,0908.31, and 38,685.50 USD, respectively. Finding from this study showed that air quality during the lockdown period in Thailand was improved, contributing to the reduction of cardiovascular and respiratory OPD visits, and consequent medical service costs attributable to air pollution.

Residential greenness and kidney function: A cohort study of Thai employees.

Higher residential greenness is associated with a lower risk of chronic kidney disease, but evidence on the association between greenness exposure and kidney function has not been conducted. Using cohort data from Electricity Generating Authority of Thailand (EGAT) employees, we investigated the association between long-term exposure to greenness and kidney function using estimated glomerular filtration rate (eGFR) in Bangkok Metropolitan Region (BMR), Thailand. We analyzed data from 2022 EGAT workers (aged 25-55 years at baseline) from 2009 to 2019. The level of greenness was calculated using the satellite-derived Enhanced Vegetation Index (EVI) and Normalized Difference Vegetation Index (NDVI). From 2008 to 2019, the average concentration of each air pollutant (PM10, O3, NO2, SO2, and CO) at the sub-district level in BMR was generated using the Kriging method. Long-term exposure for each participant was defined as the 1-year average concentrations before the date of the physical examination in 2009, 2014, and 2019. We employed linear mixed effects models to evaluate associations of NDVI and EVI with eGFR. The robustness of the results was also tested by including air pollutants in the models. After relevant confounders were controlled, the interquartile range increase in NDVI was associated with higher eGFR [1.03% (95%CI: 0.33, 1.74)]. After PM10 and SO2 were included in the models, the associations between NDVI and eGFR became weaker. The additions of O3, NO2, and CO strengthened the associations between them. In contrast, we did not find any association between EVI and eGFR. In conclusion, there was a positive association between NDVI and eGFR, but not for EVI. Air pollutants had a significant impact on the relationship between NDVI and eGFR. Additional research is needed to duplicate this result in various settings and populations to confirm our findings.

Association between greenness and cardiovascular risk factors: Results from a large cohort study in Thailand.

BACKGROUND: The risk of cardiovascular diseases may be reduced by residing in green environments. However, there are relatively few longitudinal cohort studies, especially in Southeast Asia, that focused on the health benefits of long-term greenness exposure in young adults. The present study examined the association between long-term exposure to residential greenness and self-reported morbidities in participants of the Thai Cohort Study (TCS) in Thailand from 2005 to 2013. METHODS: The self-reported outcomes, including high blood pressure, high blood cholesterol, and diabetes, were reported in 2005, 2009, and 2013, where the study participants provided the exact year of disease occurrence. Greenness was assessed by the satellite-based Normalized Difference Vegetation Index (NDVI) and Enhanced Vegetation Index (EVI), with a spatial resolution of 250 m. Long-term exposure to NDVI and EVI of each participant's sub-district was averaged over the period of person-time. We used Cox proportional hazards models to examine the association between greenness and health outcomes. Associations with self-reported morbidity were measured using hazard ratios (HRs) per interquartile range (IQR) increase in NDVI and EVI. RESULTS: After adjusting for potential confounders, we observed that an IQR increase in NDVI was associated with lower incidence of high blood pressure (HR = 0.92, 95% CI: 0.89, 0.97) and high blood cholesterol (HR = 0.89, 95%CI: 0.87, 0.92), but not significantly associated with diabetes (HR = 0.93, 95%CI: 0.85, 1.01). EVI was also inversely associated with self-reported high blood pressure (HR = 0.92, 95%CI: 0.88, 0.96), high blood cholesterol (HR = 0.89, 95%CI: 0.87, 0.91), and diabetes (HR = 0.92, 95%CI: 0.85, 0.99). CONCLUSIONS: Long-term exposure to residential greenness was inversely associated with self-reported high blood pressure, high blood cholesterol, and diabetes in participants of TCS. Our study provides evidence that greenness exposure may reduce cardiovascular disease risk factors in adult population.

Effect modification by temperature on the association between O3 and emergency ambulance dispatches in Japan: A multi-city study.

Numerous epidemiological studies have reported that ozone (O3) and temperature are independently associated with health outcomes, but modification of the effects of O3 on health outcomes by temperature, and vice versa, has not been fully described. This study aimed to investigate effect modification by temperature on the association between O3 and emergency ambulance dispatches (EADs) in Japan. Data on daily air pollutants, ambient temperature, and EADs were obtained from eight Japanese cities from 2007 to 2015. A distributed lag non-linear model combined with Poisson regression was performed with temperature as a confounding factor and effect modifier to estimate the effects of O3 on EADs at low (<25th percentile), moderate (25th-75th percentile), and high (>75th percentile) temperature for each city. The estimates obtained from each city were pooled by random-effects meta-analysis. When temperature was entered as a confounder, the estimated effects of O3 on EADs for all acute, cardiovascular, and respiratory illnesses were largest at lag 0 (current-day lag). Therefore, this lag was used to further estimate the effects of O3 on EADs in each temperature category. The estimated effects of O3 on EADs for all acute, cardiovascular, and respiratory illnesses in all eight Japanese cities increased with increasing temperature. Specifically, a 10 ppb increase in O3 was associated with 0.80 % (95 % CI: 0.25 to 1.35), 0.19 % (95 % CI: -0.85 to 1.25), and 1.14 % (95 % CI: -0.01 to 2.31) increases in the risk of EADs for all acute, cardiovascular, and respiratory illnesses, respectively, when city-specific daily temperature exceeded the 75th percentile. Our findings suggest that the association between O3 and EADs for all acute, cardiovascular, and respiratory illnesses is the highest during high temperature. Finding of this study can be used to develop potential mitigation measures against O3 exposure in high temperature environment to reduce its associated adverse health effects.

Estimating ground-level PM2.5 over Bangkok Metropolitan Region in Thailand using aerosol optical depth retrieved by MODIS.

A number of previous studies have shown that statistical model with a combination of satellite-derived aerosol optical depth (AOD) and PM2.5 measured by the monitoring stations could be applied to predict spatial ground-level PM2.5 concentration, but few studies have been conducted in Thailand. This study aimed to estimate ground-level PM2.5 over the Bangkok Metropolitan Region in 2020 using linear regression model that incorporates the Moderate Resolution Imaging Spectroradiometer (MODIS) AOD measurements and other air pollutants, as well as various meteorological factors and greenness indicators into the model. The 12-fold cross-validation technique was used to examine the accuracy of model performance. The annual mean (standard deviation) concentration of observed PM2.5 was 22.37 (± 12.55) µg/m3 and the mean (standard deviation) of PM2.5 during summer, winter, and rainy season was 18.36 (± 7.14) µg/m3, 33.60 (± 14.48) µg/m3, and 15.30 (± 4.78) µg/m3, respectively. The cross-validation yielded R 2 of 0.48, 0.55, 0.21, and 0.52 with the average of predicted PM2.5 concentration of 22.25 (± 9.97) µg/m3, 21.68 (± 9.14) µg/m3, 29.43 (± 9.45) µg/m3, and 15.74 (± 5.68) µg/m3 for the year round, summer, winter, and rainy season, respectively. We also observed that integrating NO2 and O3 into the regression model improved the prediction accuracy significantly for a year round, summer, winter, and rainy season over the Bangkok Metropolitan Region. In conclusion, estimating ground-level PM2.5 concentration from the MODIS AOD measurement using linear regression model provided the satisfactory model performance when incorporating many possible predictor variables that would affect the association between MODIS AOD and PM2.5 concentration. Supplementary Information: The online version contains supplementary material available at 10.1007/s11869-022-01238-4.

Outpatient Department Visits and Mortality with Various Causes Attributable to Ambient Air Pollution in the Eastern Economic Corridor of Thailand.

The Eastern Economic Corridor in Thailand is undergoing development, but industrial activities are causing serious air pollution. This study aimed to examine the effects of particulate matter (PM10), fine particulate matter (PM2.5), SO2, NO2, O3, and CO on outpatient department (OPD) visits and mortality with various causes in the Eastern Economic Corridor, Thailand between 2013 and 2019 using a case-crossover design and conditional Poisson model. The corresponding burden of disease due to air pollution exposure was calculated. A 1 µg/m3 increase in the PM10 was associated with significant increases in OPD visits for circulatory diseases (0.22, 95% CI 0.01, 0.34), respiratory diseases (0.21, 95% CI 0.13, 0.28), and skin and subcutaneous tissue diseases (0.18, 95% CI 0.10, 0.26). By contrast, a 1 µg/m3 increase in the PM10 was associated with significant increases in mortality from skin and subcutaneous tissue diseases (0.79, 95% CI 0.04, 1.56). A 1 µg/m3 increase in PM2.5 was associated with significant increases in mortality from circulatory diseases (0.75, 95% CI 0.20, 1.34), respiratory diseases (0.82, 95% CI 0.02, 1.63), and skin and subcutaneous tissue diseases (2.91, 95% CI 0.99, 4.86). The highest OPD burden was for circulatory diseases. Respiratory effects were attributed to PM10 exceeding the national ambient air quality standards (NAAQS) of Thailand (120 µg/m3). The highest morbidity burden was for skin and subcutaneous tissue diseases attributed to PM2.5 concentrations that exceeded the NAAQs (50 µg/m3). PM pollution in the EEC could strongly contribute to OPD visits and morbidity from various diseases. Preventing PM10 concentrations from being higher than 60 µg/m3 could decrease OPD visits by more than 33,265 and 29,813 for circulatory and respiratory diseases, respectively. Our study suggests that such pollution increases the risks of OPD visits and mortality in various causes in the Thai EEC. Reducing the ambient air pollution concentration of NAAQSs in Thailand could reduce the health effect on the Thai population.

Effects of rainfall on human leptospirosis in Thailand: evidence of multi-province study using distributed lag non-linear model.

Leptospirosis is a zoonotic bacterial disease that remains an important public health problem, especially in tropical developing countries. Many previous studies in Thailand have revealed the outbreak of human leptospirosis after heavy rainfall, but research determining its quantitative risks associated with rainfall, especially at the national level, remains limited. This study aims to examine the association between rainfall and human leptospirosis across 60 provinces of Thailand. A quasi-Poisson regression framework combined with the distributed lag non-linear model was used to estimate province-specific association between rainfall and human leptospirosis, adjusting for potential confounders. Province-specific estimates were then pooled to derive regional and national estimates using random-effect meta-analysis. The highest risk of leptospirosis associated with rainfall at national level was observed at the same month (lag 0). Using 0 cm/month of rainfall as a reference, the relative risks of leptospirosis associated with heavy (90th percentile), very heavy (95th percentile), and extremely heavy (99th percentile) rainfall at the national level were 1.0994 (95% CI 0.9747, 1.2401), 1.1428 (95% CI 1.0154, 1.2862), and 1.1848 (95% CI 1.0494, 1.3378), respectively. The highest risk of human leptospirosis associated with rainfall was observed in the northern and north-eastern regions. Specifically, the relative risks of leptospirosis associated with extremely heavy rainfall in northern and north-eastern regions were 1.2362 (95% CI 0.9110, 1.6775) and 1.2046 (95% CI 0.9728, 1.4918), respectively. Increasing rainfall was associated with increased risks of leptospirosis, especially in the northern and northeastern regions of Thailand. This finding could be used for precautionary warnings against heavy rainfall. Supplementary Information: The online version contains supplementary material available at 10.1007/s00477-022-02250-x.

Fine particulate matter and daily hospitalizations for mental and behavioral disorders: A time-series study in Ho Chi Minh City, Vietnam.

Various adverse health outcomes caused by particulate matter (PM) exposure has been documented, while the evidence for the adverse effects of PM exposure on mental and behavioral disorders (MBDs) is limited. To date, few epidemiological studies, especially in developing countries, have focused on these adverse effects. In the past decade, air pollution sources in Vietnam have noticeably increased, resulting to the elevated concentrations of ambient air pollutants particularly fine PM or PM with an aerodynamic diameter ≤2.5 µm (PM2.5). Hence, investigating the short-term association between PM2.5 and MBDs is worthwhile. In this study, a quasi-Poisson time-series regression analysis was used to investigate the association between PM2.5 exposure and daily hospitalizations for MBDs to the Ho Chi Minh City Mental Health Hospital during 2017-2020. A natural cubic spline smooth function for time was used to screen out long-term and seasonality trends. Stratified analyses were also performed by sex, age, and season. During study period, 9,986 hospitalizations for MBDs were recorded and included in the analysis. Results suggested that a 10 µg/m3 daily increase in PM2.5 concentration was associated with a statistically significant 2.96% (95% confidence interval: 0.23%-5.76%) increase in hospitalizations for MBDs. The effects of PM2.5 exposure on hospital admissions were more pronounced in female patients and the middle-age group (35-59 years). This finding could increase awareness regarding prevention and minimization of MBDs on the public.

Long-term air pollution exposure and decreased kidney function: A longitudinal cohort study in Bangkok Metropolitan Region, Thailand from 2002 to 2012.

BACKGROUND: Kidney dysfunction is considered a cardiovascular risk factor. However, few longitudinal studies have examined the effects of air pollution on kidney function. We evaluated associations between long-term air pollution exposure and estimated glomerular filtration rate (eGFR) using data from a cohort of the Electricity Generating Authority of Thailand (EGAT) study in Bangkok Metropolitan Region, Thailand. METHODS: This longitudinal study included 1839 subjects (aged 52-71 years in 2002) from the EGAT1 cohort study during 2002-2012. eGFR, based on creatinine, was measured in 2002, 2007, and 2012. Annual mean concentrations of air pollutants (i.e., particulate matter with an aerodynamic diameter ≤10 µm (PM10), ozone (O3), nitrogen dioxide (NO2), sulfur dioxide (SO2), and carbon monoxide (CO)) prior to a measurement of creatinine were assessed with the ordinary kriging method. Mixed-effect linear regression models were used to assess associations between air pollutants and eGFR, while controlling for potential covariates. eGFR values are expressed as percent change per interquartile range (IQR) increments of each pollutant. RESULTS: Lower eGFR was associated with higher concentrations of PM10 (-1.99%, 95% confidence interval (CI): -3.33, -0.63), SO2 (-4.89%, 95%CI: -6.69, -3.07), and CO (-0.97%, 95%CI: -1.96, 0.03). However, after adjusting for temperature, relative humidity, PM10, and SO2, no significant association was observed between CO and eGFR. CONCLUSIONS: Our findings support the hypothesis that long-term exposure to high concentrations of PM10 and SO2 is associated with the progression of kidney dysfunction in subjects of the EGAT cohort study.

Daily ambient temperature and mortality in Thailand: Estimated effects, attributable risks, and effect modifications by greenness.

BACKGROUND: In recent years, many previous studies have examined the association between ambient temperature and mortality in different parts of the world. However, very few studies have explored the mortality burden attributable to temperature, especially those in developing countries. This study aimed to quantify the burden of mortality attributable to non-optimum temperature in Thailand and explore whether greenness, using normalized difference vegetation index (NDVI) as indicator, alleviates the mortality contributed by non-optimum ambient temperature. METHODS: Daily number of mortality (i.e., all-cause, cardiovascular and respiratory diseases) and daily meteorological data were obtained over 65 provinces in Thailand during 2010 to 2017. The two-stage statistical approach was applied to estimate the association between temperature and mortality. First, the time-stratified case-crossover analysis was performed to examine province-specific temperature-mortality association. Second, province-specific association was pooled to derive national estimates using multivariate meta-regression. Mortality burden attributable to temperature was then estimated, and the association between attributed mortality and NDVI was explored using multivariate meta-regression models. RESULTS: A total of 2,891,407 all-cause of death was included over the study period, in which 403,450 and 264,672 deaths were accounted for cardiovascular and respiratory diseases, respectively. The temperature-mortality association at cumulative lag 0-7 days was non-linear with J-shaped curve for all-cause and respiratory mortality, whereas V-shaped curve was observed for cardiovascular mortality. Using minimum mortality temperature (MMT) as optimum temperature, 3.72% (95% empirical CI: 2.18, 5.21) of all-cause, 2.92% (0.55, 5.10) of cardiovascular and 3.00% (0.27, 5.49) of respiratory mortality were attributable to non-optimum temperature (both hot and cold effects). Higher level of NDVI was associated with alleviated impacts of non-optimum temperature, especially hot temperature. CONCLUSION: Exposure to non-optimum temperature was associated with increased risks of mortality in Thailand. This finding is useful for planning the public health interventions to reduce health effects of non-optimum ambient temperature.

Effects of long-term air pollution exposure on ankle-brachial index and cardio-ankle vascular index: A longitudinal cohort study using data from the Electricity Generating Authority of Thailand study.

BACKGROUND: Ankle-brachial index (ABI) and cardio-ankle vascular index (CAVI) are surrogate measures of atherosclerosis based on the functional performance of vessels, and are highly related to cardiovascular events. However, only a few longitudinal studies have been conducted on their associations with long-term air pollution exposure. OBJECTIVE: This study aimed to examine whether long-term air pollution exposure is associated with ABI and CAVI in workers of the Electricity Generating Authority of Thailand (EGAT) in the Bangkok Metropolitan Region (BMR). METHODS: This longitudinal study included 1261 participants (age range, 57-76 years as of 2007) of the EGAT study (2007-2017). ABI and CAVI were measured in 2007, 2012, and 2017. Annual mean concentrations of particulate matter ≤10 µm in diameter (PM10), sulfur dioxide (SO2), nitrogen dioxide (NO2), ozone (O3), and carbon monoxide (CO) were estimated by ordinary kriging using data from 22 background and 7 traffic monitoring stations in BMR between 2002 and 2017. Linear mixed-effects models were used to assess associations between air pollution (expressed as 1-year, 3-year, and 5-year average concentration) and ABI and CAVI (expressed as percent changes per interquartile range (IQR) increase in PM10, O3, NO2, SO2, and CO). We also applied the mixed-effect ordinal logistic models to calculate odds ratios (ORs) of having high or moderate CAVI per an IQR increase in air pollution. RESULTS: After controlling for potential confounders, 1-year average CO was negatively associated with ABI, but not significantly (-0.48%, 95% CI: -1.03, 0.07). Three-year average NO2 was positively associated with CAVI (6.67%, 95% CI: 0.21, 13.1). In contrast, 1-year average PM10 was inversely associated with CAVI although the association was not significant. Although not significantly, 1-year average NO2 and CO were positively associated with prevalence of high or moderate CAVI. CONCLUSIONS: Although not statistically significant, long-term NO2 and CO exposure was associated with ABI and CAVI in the participants of the EGAT study.

Socio-economic factors do also matter: comments on the article "Can climatic factors explain the differences in COVID-19 incidence and severity across the spanish regions?: an ecological study".

A report published in this journal showed an inversely significant association between ultraviolet radiation (UVR) before the pandemic and cumulative COVID-19 cases in Spain. The analyses employed several meteorological factors, but socio-economic factors were not included. We examined the associations of COVID-19 cases with selected factors and found a significance on gross domestic product per capita (p = 0.037 by Spearman's correlation). Hence, simple regression analyses of UVR would be confounded with regional difference in economic activities. In addition, we raised several questions for limitations due to the study design and analyses.