Associations between short-term exposure to air pollution and thyroid function in a representative sample of the Korean population.

BACKGROUND: Disruption of thyroid function can profoundly affect various organ systems. However, studies on the association between air pollution and thyroid function are relatively scarce and most studies have focused on the long-term effects of air pollution among pregnant women. OBJECTIVES: This study aimed to explore the associations between short-term exposure to air pollution and thyroid function in the general population. METHODS: Data from the Korea National Health and Nutrition Examination Survey (2013-2015) were analyzed (n = 5,626). Air pollution concentrations in residential addresses were estimated using Community Multiscale Air Quality models. The moving averages of air pollution over 7 days were set as exposure variables through exploratory analyses. Linear regression and quantile g-computation models were constructed to assess the effects of individual air pollutants and air pollution mixture, respectively. RESULTS: A 10-ppb increase in NO2 (18.8-µg/m3 increase) and CO (11.5-µg/m3 increase) was associated with 2.43% [95% confidence interval (CI): 0.42, 4.48] and 0.19% (95% CI: 0.01, 0.36) higher thyroid-stimulating hormone (TSH) levels, respectively. A 10-µg/m3 increase in PM2.5 and a 10-ppb increase in O3 (19.6-µg/m3 increment) were associated with 0.87% (95% CI: 1.47, -0.27) and 0.59% (95% CI: 1.18, -0.001) lower free thyroxine (fT4) levels, respectively. A simultaneous quartile increase in PM2.5, NO2, O3, and CO levels was associated with lower fT4 but not TSH levels. CONCLUSIONS: As the subtle changes in thyroid function can affect various organ systems, the present results may have substantial public health implications despite the relatively modest effect sizes. Because this was a cross-sectional study, it is necessary to conduct further experimental or repeated-measures studies to consolidate the current results.

Association Between Instant Coffee Consumption and the Development of Chronic Obstructive Pulmonary Disease: Results From a Community-Based Prospective Cohort.

BACKGROUND: A poor diet is a risk factor for chronic obstructive pulmonary disease (COPD). The interaction between dietary factors and cigarette smoking in the development of COPD is unclear. We investigated the interactions between dietary patterns and smoking status on COPD-related outcomes. METHODS: We used data from the Anseong-Ansan cohort that has been followed for 20 years. A total of 6,221 individuals without COPD in the baseline survey were analyzed. Five dietary patterns were identified using a semi-quantitative food frequency questionnaire. Associations of dietary patterns with COPD and forced expiratory volume in 1 second (FEV1)/forced vital capacity (FVC) ratio in different strata of smoking status were evaluated using Cox regression and linear mixed models, respectively. RESULTS: The highest quartile of the "coffee" pattern (high coffee consumption) was associated with COPD (hazard ratio, 1.46; 95% confidence interval [CI], 1.03-2.08) and lower FEV1/FVC ratio (ß = -1.2%; 95% CI, -1.9% to -0.6%) using the lowest quartile as a reference for heavy smokers, but not light or never smokers (P value for interaction = 0.035 for COPD). Regarding the associations between various consumption levels of black coffee, combined coffee, and instant coffee and COPD, an association with COPD was only observed for instant coffee in heavy smokers. CONCLUSION: High instant coffee consumption is associated with COPD development in heavy smokers, but not in light or never smokers. This may be attributed to sugar and cream in instant coffee mixes.

Association Between Eight Autoimmune Diseases and Thyroid Cancer: A Nationwide Cohort Study.

Background: It has often been reported that thyroid-specific autoimmune diseases (ADs), such as Hashimoto's thyroiditis and Graves' disease, could increase the risk of thyroid cancer, but the association between other ADs beyond thyroid and thyroid cancer has not been well investigated. This study aimed to examine the risk of thyroid cancer in patients with eight ADs compared with those without ADs. Methods: This nationwide retrospective matched cohort study was conducted to investigate the relationship of eight ADs (Hashimoto's thyroiditis, Graves' disease, type 1 diabetes mellitus, Sjogren's disease, inflammatory bowel disease [IBD], vitiligo, systemic lupus erythematosus, and rheumatoid arthritis [RA]) with the risk of incident thyroid cancer using the National Health Insurance Service-National Sample Cohort. The Cox-proportional hazard model was used to estimate the adjusted hazard ratio (HR) and confidence intervals (CI) for thyroid cancer in relation to each of AD compared with control group without AD. Results: During the average follow-up of 9.49 years, 138 thyroid cancer cases were newly developed in control group and 268 cases were occurred in group with 8 ADs. For all of study participants, the risk of thyroid cancer was significantly increased in patients with Hashimoto's thyroiditis (HR = 2.10 [1.57-2.81]), Graves' disease (HR = 2.67 [1.99-3.62]), IBD (HR = 2.06 [1.50-2.83]), vitiligo (HR = 1.71 [1.13-2.59]), RA (HR = 1.76 [1.07-2.90]), and total of 8 ADs (HR = 1.97 [1.60-2.42]) compared with control group without ADs. When ADs were divided into three types, thyroid-specific ADs (HR = 2.37 [1.85-3.03]) showed the strongest and significant association with thyroid cancer, followed by local ADs (HR = 1.83 [1.41-2.38]), and systemic ADs (HR = 1.77 [1.14-2.74]). Conclusions: Specific ADs-especially for thyroid-specific AD, vitiligo, IBD, and RA-were associated with increased risk for thyroid cancer.

Association of Infant Feeding Characteristics With Dietary Patterns and Obesity in Korean Childhood.

OBJECTIVES: Young children's feeding characteristics can play an important role in eating habits and health during later childhood. This study was conducted to examine the associations of feeding characteristics with dietary patterns and obesity in children. METHODS: This study utilized data from the Korea National Health and Nutrition Examination Survey conducted between 2013 and 2017. In total, 802 toddlers were included, with information on their demographic characteristics, feeding practices and duration, and 24-hour recall obtained from their parents. Feeding characteristics were categorized into feeding type, duration of total breastfeeding, duration of total formula feeding, duration of exclusive breastfeeding, and age when starting formula feeding. Dietary patterns were identified based on factor loadings for the food groups for 3 major factors, with "vegetables & traditional," "fish & carbohydrates," and "sweet & fat" patterns. Overweight/obesity was defined as ≥85th percentile in body mass index based on the 2017 Korean National Growth charts for children and adolescents. Multiple regression analysis was conducted to examine associations between feeding characteristics and dietary patterns. The association between dietary patterns and obesity was analyzed using multivariable logistic regression analysis. RESULTS: The early introduction of formula feeding was inversely associated with the "vegetables & traditional" pattern (ß=-0.18; 95% confidence interval [CI], -0.34 to -0.02). A higher "vegetables & traditional" intake was associated with a lower risk of obesity (odds ratio, 0.48; 95% CI, 0.24 to 0.95). CONCLUSIONS: Feeding characteristics are associated with dietary patterns in later childhood, and dietary patterns were shown to have a potential protective association against obesity.

Sex-specific Associations between Body Mass Index and Thyroid Cancer Incidence among Korean Adults.

BACKGROUND: The potential differences by sex in the association between body mass index (BMI) and thyroid cancer risk remain unconfirmed. METHODS: Data from the National Health Insurance Service-National Health Screening Cohort (NHIS-HEALS; 2002-2015; population size = 510,619) and the Korean Multi-center Cancer Cohort (KMCC) data (1993-2015; population size = 19,026) were used. We constructed Cox regression models, adjusted for potential confounders, to evaluate the association between BMI and thyroid cancer incidence in each cohort, and assessed the consistency of the results. RESULTS: In the NHIS-HEALS, 1,351 and 4,609 incident thyroid cancer cases occurred during the follow-up among men and women, respectively. Compared with BMI of 18.5-22.9 kg/m2, BMI of 23.0-24.9 [no. of cases = 410; HR, 1.25; 95% confidence interval (CI), 1.08-1.44], 25.0-29.9 (no. of cases = 522; HR, 1.32; 95% CI, 1.15-1.51), and ≥30.0 kg/m2 (no. of cases = 48; HR, 1.93; 95% CI, 1.42-2.61) were associated with an increased risk of incident thyroid cancer among males. Among females, BMI of 23.0-24.9 (no. of cases = 1,300; HR, 1.17; 95% CI, 1.09-1.26) and 25.0-29.9 (no. of cases = 1,406; HR, 1.20; 95% CI, 1.11-1.29) were associated with incident thyroid cancer. The analyses using the KMCC demonstrated results consistent with wider CIs. CONCLUSIONS: Sex differences in the associations between BMI and thyroid cancer incidence were observed in Korean cohorts. IMPACT: BMI <23 kg/m2 may help prevent incident thyroid cancer, especially among men.

Use of machine learning to improve the estimation of conductivity and permittivity based on longitudinal relaxation time T1 in magnetic resonance at 7 T.

Electrical property tomography (EPT) is a noninvasive method that uses magnetic resonance imaging (MRI) to estimate the conductivity and permittivity of tissues, and hence, can be used as a biomarker. One branch of EPT is based on the correlation of water and relaxation time T1 with the conductivity and permittivity of tissues. This correlation was applied to a curve-fitting function to estimate electrical properties, it was found to have a high correlation between permittivity and T1 however the computation of conductivity based on T1 requires to estimate the water content. In this study, we developed multiple phantoms with several ingredients that modify the conductivity and permittivity and explored the use of machine learning algorithms to have a direct estimation of conductivity and permittivity based on MR images and the relaxation time T1. To train the algorithms, each phantom was measured using a dielectric measurement device to acquire the true conductivity and permittivity. MR images were taken for each phantom, and the T1 values were measured. Then, the acquired data were tested using curve fitting, regression learning, and neural fit models to estimate the conductivity and permittivity values based on the T1 values. In particular, the regression learning algorithm based on Gaussian process regression showed high accuracy with a coefficient of determination R2 of 0.96 and 0.99 for permittivity and conductivity, respectively. The estimation of permittivity using regression learning demonstrated a lower mean error of 0.66% compared to the curve fitting method, which resulted in a mean error of 3.6%. The estimation of conductivity also showed that the regression learning approach had a lower mean error of 0.49%, whereas the curve fitting method resulted in a mean error of 6%. The findings suggest that utilizing regression learning models, specifically Gaussian process regression, can result in more accurate estimations for both permittivity and conductivity compared to other methods.

Feeding characteristics in infancy affect fruit and vegetable consumption and dietary variety in early childhood.

BACKGROUND/OBJECTIVES: Previous studies have shown an association between breastfeeding and higher fruit and vegetable consumption and the level of dietary variety in children. However, few studies have reported this association on the feeding characteristics. Therefore, this study examined the association of the feeding characteristics with the consumption of fruit and vegetable and dietary variety in children. SUBJECTS/METHODS: This study recruited 802 participants from their parents with information on their feeding, and 24-h dietary recall. The associations of the feeding characteristics with fruit and vegetable consumption and dietary variety score (DVS) were analyzed using a multiple logistic regression model. RESULTS: Compared to the feeding type of exclusive breastfed children, exclusive formula-fed children had a significant association with a lower DVS (odds ratio [OR], 0.42, 95% confidence interval [CI], 0.23-0.77). Fruit and vegetable consumption was classified into 6 groups: non-salted vegetables (NSV), salted vegetables (SV), fruit (F), total vegetables (TV), non-salted vegetables + fruit (NSVF), and total vegetables + fruit (TVF). According to the mean level of fruit and vegetable consumption, compared to the duration of total breastfeeding for 6 month or less, a greater duration of breastfeeding for 12 mon had a significant association with a higher intake of NSVF and TVF (OR, 1.85, 95% CI, 1.20-2.85 and OR, 1.89, 95% CI, 1.22-2.92). On the other hand, the early introduction of formula feeding for 4 mon had a significant association with a lower intake of F and NSVF (OR, 0.59, 95% CI, 0.38-0.91 and OR, 0.63, 95% CI, 0.40-0.99). CONCLUSIONS: These results confirm that breastfeeding is associated with higher fruit and vegetable consumption and dietary variety, whereas formula feeding is associated with lower fruit and vegetable consumption and dietary variety. Therefore, the feeding characteristics in infants may affect fruit and vegetable consumption and dietary variety in children.

Urinary Phthalate Metabolites and Slow Walking Speed in the Korean Elderly Environmental Panel II Study.

BACKGROUND: Previous epidemiological studies have suggested that phthalate exposure may contribute to neurocognitive and neurobehavioral disorders and decreased muscle strength and bone mass, all of which may be associated with reduced physical performance. Walking speed is a reliable assessment tool for measuring physical performance in adults age 60 y and older. OBJECTIVE: We investigated associations between urinary phthalate metabolites and slowness of walking speed in community-dwelling adults ages 60-98 y. METHODS: We analyzed 1,190 older adults [range, 60-98 y of age; mean±standard deviation (SD) , 74.81±5.99] from the Korean Elderly Environmental Panel II study and measured repeatedly up to three times between 2012 and 2014. Phthalate exposure was estimated using the following phthalate metabolites in urine samples: mono-(2-ethyl-5-hydroxyhexyl) phthalate (MEHHP), mono-(2-ethyl-5-oxohexyl) phthalate (MEOHP), mono-n-butyl phthalate (MnBP), mono-(2-ethyl-5-carboxypentyl) phthalate (MECPP), and mono-benzyl phthalate (MBzP). Slowness was defined as a walking speed of <1.0meter/second. We used logistic and linear regression models to evaluate the association between each urinary phthalate metabolite and slowness or walking-speed change. We also used Bayesian kernel machine regression (BKMR) to examine overall mixture effects on walking speed. RESULTS: At enrollment, MBzP levels were associated with an increased odds of slowness [odds ratio (OR) per doubling increase: 1.15, 95% confidence interval (CI): 1.02, 1.30; OR for the highest vs. lowest quartile: 2.20 (95% CI: 1.12, 4.35) with p-trend across quartiles=0.031]. In longitudinal analyses, MEHHP levels showed an increased risk of slowness [OR per doubling increase: 1.15 (95% CI: 1.02, 1.29), OR for the highest vs. lowest quartile: 1.47 (95% CI: 1.04, 2.06), p- trend=0.035]; whereas those with higher MnBP showed a reduced risk of slowness [OR per doubling increase: 0.84 (95% CI: 0.74, 0.96), OR in the highest (vs. lowest) quartile: 0.64 (95% CI: 0.47, 0.87), p-trend=0.006]. For linear regression models, MBzP quartiles were associated with slower walking speed (p-trend=0.048) at enrollment, whereas MEHHP quartiles were associated with slower walking speed, and MnBP quartiles were associated with faster walking speed in longitudinal analysis (p-trend=0.026 and <0.001, respectively). Further, the BKMR analysis revealed negative overall trends between the phthalate metabolite mixtures and walking speed and DEHP group (MEHHP, MEOHP, and MECPP) had the main effect of the overall mixture. DISCUSSION: Urinary concentrations of prevalent phthalates exhibited significant associations with slow walking speed in adults ages 60-98 y. https://doi.org/10.1289/EHP10549.

Association between long-term air pollution exposure and development of diabetes among community-dwelling adults: Modification of the associations by dietary nutrients.

BACKGROUND: Studies on the modifying effects of dietary factors on the association between air pollution and diabetes-related outcomes are limited. We examined whether dietary nutrients could modify the association between long-term air pollution exposure and the development of diabetes. METHODS: We used data from the Cardiovascular Disease Association Study, which enrolled adults aged 40-69 years in Korea between 2005 and 2011 and followed them up until 2016 (n = 14,667). Annual concentrations of fine particulate matter (PM2.5) and nitrogen dioxide (NO2) at each participant's residence(s) were estimated using community multiscale air quality models. Intake of 22 dietary nutrients was assessed using a validated food frequency questionnaire during the baseline survey. We examined the product terms between air pollution levels (continuous) and each dietary nutrient (quartile) using Cox regression models, adjusted for potential confounders. RESULTS: PM2.5 [hazard ratio (HR) = 1.49, 95 % confidence interval (CI): 1.11, 2.00] and NO2 (HR = 1.29, 95 % CI: 1.12, 1.49) concentrations were found to be associated with incident diabetes. NO2 levels interacted with dietary intake of retinol, vitamin A, and cholesterol (p-values for interaction < 0.05). Stronger associations were observed between NO2 levels and the occurrence of diabetes among individuals with a lower intake of these nutrients compared to those with a higher intake. No interaction was found between PM2.5 and the 22 investigated dietary nutrients. CONCLUSIONS: Adequate intake of dietary nutrients, such as retinol, vitamin A, and cholesterol, from various food items in a balanced diet may prevent the occurrence of diabetes in a setting wherein reduction of air pollution levels cannot be achieved in a short time frame.

Can individual protective measures safeguard cardiopulmonary health from air pollution? A systematic review and meta-analysis.

Evidence supporting the effect of individual protective measures (IPMs) on air pollution is relatively scarce. In this study, we performed a systematic review and meta-analysis to investigate the effects of air purifiers, air-purifying respirators, and cookstove changes on cardiopulmonary health outcomes. We searched PubMed, Scopus, and Web of Science until December 31, 2022, 90 articles and 39,760 participants were included. Two authors independently searched and selected the studies, extracted information, and assessed each study's quality and risk of bias. We performed meta-analyses when three or more studies were available for each IPMs, with comparable intervention and health outcome. Systematic review showed that IPMs were beneficial in children and elderly with asthma along with healthy individuals. Meta-analysis results showed a reduction in cardiopulmonary inflammation using air purifiers than in control groups (with sham/no filter) with a decrease in interleukin 6 by -0.247 µg/mL (95% confidence intervals [CI] = -0.413, -0.082). A sub-group analysis for air purifier as an IPMs in developing counties reduced fractional exhaled nitric oxide by -0.208 ppb (95% confidence intervals [CI] = -0.394, -0.022). However, evidence describing the effects of air purifying respirator and cook stove changes on cardiopulmonary outcomes remained insufficient. Therefore, air purifiers can serve as efficient IPMs against air pollution. The beneficial effect of air purifiers is likely to have a greater effect in developing countries than in developed countries.

Associations of cold exposure with hospital admission and mortality due to acute kidney injury: A nationwide time-series study in Korea.

BACKGROUND: Emerging evidence supports an association between heat exposure and acute kidney injury (AKI). However, there is a paucity of studies on the association between cold exposure and AKI. OBJECTIVE: We aimed to investigate the associations of cold exposure with hospital admission and mortality due to AKI and to explore whether these associations were influenced by age and sex. METHODS: Information on daily counts of hospital admission and mortality due to AKI in 16 regions of Korea during the cold seasons (2010-2019) was obtained from the National Health Insurance Service (a single national insurer providing universal health coverage) and Statistics Korea. Daily mean temperature and relative humidity were calculated from hourly data obtained from 94 monitoring systems operated by the Korean Meteorological Administration. Associations of low temperatures (<10th percentile of daily mean temperature) and cold spells (≥2 consecutive days with <5th percentile of daily mean temperature) up to 21 days with AKI were estimated using quasi-Poisson regression models adjusted for potential confounders (e.g., relative humidity and air pollutants) with distributed lag models and univariate meta-regression models. RESULTS: Low temperatures were associated with hospital admission due to AKI [relative risk (RR) = 1.12, 95 % confidence interval (CI): 1.09, 1.16]. Cold spells were associated with hospital admission (RR = 1.87, 95 % CI: 1.46, 2.39) and mortality due to AKI (RR = 4.84, 95 % CI: 1.30, 17.98). These associations were stronger among individuals aged ≥65 years than among those aged <65 years. CONCLUSION: Our results underscore the need for the general population, particularly the elderly, physicians, and other healthcare providers to be more vigilant to cold exposure, given the risk of AKI. Government agencies need to develop specific strategies for the prevention and early detection of cold exposure-related AKI.

Study on the Effect of Non-Symmetrical Current Distribution Controlled by Capacitor Placement in Radio-Frequency Coils for 7T MRI.

In this paper, we present a study on the effects of varying the position of a single tuning capacitor in a circular loop coil as a mechanism to control and produce non-symmetric current distribution, such that could be used for magnetic resonance imaging (MRI) operating at ultra-high frequency (UHF). This study aims to demonstrate that the position of the tuning capacitor of a circular loop could improve the coupling between adjacent coils, used to optimize transmission field uniformity or intensity, improve signal-to-noise ratio (SNR) or specific absorption rate (SAR). A typical loop coil used in MRI consists of symmetrically distributed capacitors along the coil; this design is able to produce uniform current distributions inside the coil. However, in UHF conditions, the magnetic flux density (|B1+|) field produced by this setup may exhibit field distortion, requiring a method of controlling the field distribution and improving the field intensity of the circular loop coil. The control mechanism investigated in this study is based on the position of the tuning capacitor in the circular coil, the capacitor position was varied from 15° to 345°, in steps of 15°. We performed electromagnetic (EM) simulations, fabricated the coils, and performed MRI experiments at 7T, with each of the coils with capacitor position from 15° to 345° to determine the effects on field intensity, coupling between adjacent coils, SAR, and applications for field uniformity optimization. For the case of free space, a coil with capacitor position at 15° showed higher field intensity compared to the reference coil; while an improved decoupling was achieved when a coil had the capacitor placed at 180° and the other coil at 90°; in a similar matter, we discuss the results for SAR, field uniformity and an application with an array coil for the spinal cord.

Correlation analysis between the complex electrical permittivity and relaxation time of tissue mimicking phantoms in 7 T MRI.

Dielectric relaxation theory describes the complex permittivity of a material in an alternating field; in particular, Debye theory relates the time it takes for an applied field to achieve the maximum polarization and the electrical properties of the material. Although, Debye's equations were proposed for electrical polarization, in this study, we investigate the correlation between the magnetic longitudinal relaxation time T1 and the complex electrical permittivity of tissue-mimicking phantoms using a 7 T magnetic resonance scanner. We created phantoms that mimicked several human tissues with specific electrical properties. The electrical properties of the phantoms were measured using bench-test equipment. T1 values were acquired from phantoms using MRI. The measured values were fitted with functions based on dielectric estimations, using relaxation times of electrical polarization, and the mixture theory for dielectrics. The results show that, T1 and the real permittivity are correlated; therefore, the correlation can be approximated with a rational function in the case of water-based phantoms. The correlation between index loss and T1 was determined using a fitting function based on the Debye equation and mixture theory equation, in which the fraction of the materials was taken into account. This phantom study and analysis provide an insight into the application relaxation times used for estimating dielectric properties. Currently, the measurement of electrical properties based on dielectric relaxation theory is based on an antenna, sometimes invasive, that irradiates an electric field into a small sample; thus, it is not possible to create a map of electrical properties for a complex structure such as the human body. This study could be further used to compute the electrical properties maps of tissues by scanning images and measuring T1 maps.

Effects of short-term exposure to air pollution on hospital admissions for autism spectrum disorder in Korean school-aged children: a nationwide time-series study.

OBJECTIVES: This study explored the effects of short-term exposure to air pollution on hospital admissions for autism spectrum disorder (ASD), a proxy for symptom aggravation, among Korean children aged 5-14 years. DESIGN: Time-series study. SETTING, PARTICIPANTS AND OUTCOME MEASURES: We used data from the National Health Insurance Service (2011-2015). Daily concentrations of fine particulate matter (PM2.5), nitrogen dioxide (NO2) and ozone (O3) levels in each region were used as exposures. ASD cases were defined based on a principal admission diagnosis of the claims data. We applied distributed lag non-linear models and a generalised difference-in-differences method to the quasi-Poisson models to estimate the causal effects of air pollution for up to 6 days. We also performed weighted quantile sum regression analyses to assess the combined effects of air pollution mixtures. RESULTS: PM2.5 levels at lag day 1, NO2 levels at lag day 5 and O3 levels at lag day 4 increased the risks of hospital admissions for ASD (relative risk (RR)=1.17, 95% CI 1.10 to 1.25 for PM2.5; RR=1.09, 95% CI 1.01 to 1.18 for NO2 and RR=1.03, 95% CI 1.00 to 1.06 for O3). The mean daily count of hospital admissions for ASD was 8.5, and it would be 7.3, 7.8 and 8.3 when the PM2.5 levels would be decreased by 10.0 µg/m3, NO2 by 10 ppb and O3 by 10 ppb, respectively. The weighted quantile sum index, constructed from PM2.5, NO2 and O3 levels, was associated with a higher risk of hospital admissions for ASD (RR 1.29, 95% CI 1.14 to 1.46), where NO2 was found to contribute to the effects most (the weight of 0.80). CONCLUSIONS: These results emphasise that reduction of air pollution exposure should be considered for ASD symptom management, with important implications for the quality of life and economic costs.

Reaction to the COVID-19 pandemic in Seoul with biostatistics.

This paper discusses our collaboration work with government officers in the health department of Seoul during the COVID-19 pandemic. First, we focus on short-term forecasting for the number of new confirmed cases and severe cases. Second, we focus on understanding how much of the current infections has been affected by external influx from neighborhood areas or internal transmission within the area. This understanding may be important because it is linked to the government policy determining non-pharmaceutical interventions. To obtain the decomposition of the effect, districts of Seoul should be considered simultaneously, and multivariate time series models are used. Third, we focus on predicting the number of new weekly confirmed cases for each district in Seoul. This detailed prediction may be important to the government policy on resource allocation. We consider an ensemble method to overcome poor prediction performance of simple models. This paper presents the methodological details and analysis results of the study.

Association between Blood Glucose Control and Subjective Cognitive Decline in Korean Patients with Diabetes Aged over 50 Years.

This study aimed to investigate the association between blood glucose control and subjective cognitive decline in adult patients with diabetes. Using the 2018 data from the community health survey, we included 18,789 patients with diabetes aged ≥50 years who had complete responses recorded. Blood glucose control was the independent variable, and subjective cognitive decline was the dependent variable. Multivariable logistic regression analysis was used to analyze the association between blood glucose control and subjective cognitive decline. Multivariable logistic regression analysis showed that blood glucose control was inversely associated with subjective cognitive decline in patients with diabetes. Patients with uncontrolled blood glucose levels had higher odds of subjective cognitive decline than those with controlled blood glucose levels (odds ratio = 1.22; 95% confidence interval: 1.10, 1.34). Our findings suggest that patients with diabetes may demonstrate subjective cognitive decline if their blood glucose levels are not well-controlled.

Associations between cold spells and hospital admission and mortality due to diabetes: A nationwide multi-region time-series study in Korea.

BACKGROUND: Climate change is predicted to increase the frequency, intensity, and duration of extreme cold events in the mid-latitudes. However, although diabetes is one of the most critical metabolic diseases due to its high and increasing prevalence worldwide, few studies have investigated the short-term association between cold exposure and diabetes-related outcomes. OBJECTIVE: The aim of this study was to investigate the associations between cold spells and their characteristics (intensity, duration, and seasonal timing) and hospital admission and mortality due to diabetes. METHODS: This study used claims data from the National Health Insurance Service and cause-specific mortality data from Statistics Korea (2010-2019). Cold spells were defined as ≥2 consecutive days with a daily mean temperature lower than the region-specific 5th percentile during the cold season (November-March). Quasi-Poisson regressions combined with distributed lag models were used to assess the associations between exposures and outcomes in 16 regions across the Republic of Korea. Meta-analyses were conducted to pool the region-specific estimates. RESULTS: Exposure to cold spells was associated with an increased risk of hospital admission [relative risk (RR) = 1.45, 95% confidence interval (CI): 1.26, 1.66] and mortality (RR = 2.02, 95% CI: 1.37, 2.99) due to diabetes. The association between cold spells and hospital admission due to diabetes was stronger for cold spells that were more intense, longer, and occurred later during the cold season. The association between cold spells and diabetes-related mortality was stronger for more intense and longer cold spells. CONCLUSION: This study emphasizes the importance of developing effective interventions against cold spells, including education on the dangers of cold spells and early alarm systems. Further studies are needed to create real-world interventions and evaluate their effectiveness in improving diabetes-related outcomes.

Long-term exposure to air pollution and the blood lipid levels of healthy young men.

BACKGROUND: There is insufficient evidence of an association between long-term exposure to air pollution and changes in blood lipid levels, and assessments may be influenced by residual confounding factors, such as socioeconomic status. OBJECTIVES: To investigate the associations between long-term exposure to air pollution and blood lipid profiles while controlling for the risk of residual confounding factors. METHODS: We conducted a study involving conscripted Korean soldiers to assess the associations between air pollution and blood lipid levels. The soldiers, who were randomly distributed among military units throughout the country, led homogenous lives and were subjected to health checkups 8-12 months post-enlistment. We analyzed data pertaining to those who enlisted and underwent health checkups in 2019 (n = 12,778) using linear mixed models. Additionally, we evaluated quantile-specific associations using quantile regression models. We also assessed interactions based on body mass index (BMI) at the time of enlistment (≥25.0 vs. < 25.0 kg/m2). RESULTS: The linear mixed models revealed that a 10-µg/m3 increase in fine particulate matter ≤ 2.5 µm (PM2.5) decreased high-density lipoprotein cholesterol (HDL-C) levels by -0.66% (95% confidence interval [CI]: -1.21, -0.10), and a 10-ppb increase in nitrogen dioxide (NO2) increased total cholesterol (TC) levels by 1.04% (95% CI: 0.24, 1.84). In the quantile regression models, associations were also found at specific deciles. PM2.5 exposure contributed to higher TC, NO2 resulted in higher triglycerides and lower HDL-C, and ozone (O3) led to lower HDL-C. The association between O3 and TC differed according to BMI (p-value for interaction = 0.03); among those with a BMI ≥ 25.0 kg/m2, a 10-ppb increase in O3 increased TC by 1.09% (95% CI: 0.20, 1.09). DISCUSSION: These results shed new light on the importance of controlling air pollution, which can contribute to abnormal blood lipid levels, an independent risk factor for cardiovascular disease.

Prevalence and Premature Mortality Statistics of Autism Spectrum Disorder Among Children in Korea: A Nationwide Population-Based Birth Cohort Study.

BACKGROUND: The aim of this study was to estimate the 8-year prevalence and mortality statistics of autism spectrum disorder (ASD) according to birth year (2002-2012). METHODS: We used the National Health Insurance Service database with 4,989,351 children born from 2002 to 2012 including 35,529 children diagnosed with ASD until 8 years of age. The 8-year cumulative prevalence of ASD was calculated annually (2010-2020) with 8 years of follow-up. The 8-year mortality was estimated using Cox models adjusted for sex, household income, area of residence, and year of birth. RESULTS: Of the 473,494 children born in 2002, 2,467 (5.2 per 1,000 births) were diagnosed with ASD until 2010. The ASD prevalence was 2.6 times higher among boys (1,839; 7.4 per 1,000 boy births) than girls (628; 2.8 per 1,000 girl births). Of the 467,360 children born in 2012, 4,378 (9.4 per 1,000 births) were diagnosed with ASD until 2020. The ASD prevalence was 2.7 times higher among boys (3,246; 13.5 per 1,000 boy births) than girls (1,132; 5.0 per 1,000 girl births). The risk of all-cause mortality was higher among children with ASD than those without (hazard ratio [HR], 2.340; 95% confidence interval [CI], 2.063-2.654), which is substantially higher among girls (HR, 4.223; 95% CI, 3.472-5.135) than boys (HR, 1.774; 95% CI, 1.505-2.090). CONCLUSION: The present study demonstrated that national-level prevalence and mortality statistics of ASD can be estimated effectively using claims data comprising newborns born each year and followed up for to the age of interest. Because this information is essential to establish evidence-based policies, health authorities need to consider producing epidemiological information of ASD continuously using the same methodology.

Age-specific effects of ozone on pneumonia in Korean children and adolescents: a nationwide time-series study.

OBJECTIVES: The aim of this study was to estimate the age-specific effects of 8-hour maximum ozone levels on pneumonia in children and adolescents. METHODS: We performed quasi-Poisson regression analyses for individuals of 0-4 years, 5-9 years, 10-14 years, and 15-19 years of age using nationwide time-series data from the Korea (2011-2015). We constructed distributed lag linear models employing a generalized difference-in-differences method and controlling for other air pollutants. RESULTS: A 10.0-parts per billion increase in 8-hour maximum ozone levels was associated with a higher risk of hospital admissions due to pneumonia at 0-4 (relative risk [RR], 1.02; 95% confidence interval [CI], 1.01 to 1.03) and 5-9 years of age (RR, 1.06; 95% CI, 1.04 to 1.08), but not at 10-14 (RR, 1.01; 95% CI, 0.98 to 1.04) or 15-19 years of age (RR, 1.01; 95% CI, 0.97 to 1.06). The association between ozone and hospital admissions due to pneumonia was stronger in cool seasons (from November to April) than in warm seasons (from May to October), but was similar between boys and girls. CONCLUSIONS: Short-term exposure to ozone was associated with a higher risk of pneumonia at 0-4 years and 5-9 years of age, but not at 10-14 years or 15-19 years of age. Our findings can help identify vulnerable periods, determine the target populations for public health interventions, and establish air pollution standards.