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Continuous operating reference station (CORS) networks, underpinned by GNSS technology, support various technological services including comprehensive surveying, navigation, and remote sensing. The stability of these CORS networks is crucial for maintaining the high accuracy and reliability of data services. In this paper, we focus on analyzing the GPS deformation array of Vancouver Island, Canada, and present a thorough stability analysis scheme for CORS networks that is adaptable to other areas with frequent tectonic activity. For this study, we first conducted a data quality assessment based on three primary indices — namely, multipath effect on L1 and L2 frequency, signal-to-noise ratio in both frequency and cycle slip ratio — using the Transfer Edit Quality Check (TEQC) software. Then, we achieved high-precision data processing using the GAMIT/GLOBK software, in order to quantify the changes at each station over the specific periods. Seasonality analysis was also incorporated into the pipeline. Considering the potential variances affecting the deformation array over time, the coordinates were transformed under a unified reference frame, enabling the study of changes with station coordinates from different epochs under the same systematic conditions. Additionally, the impact of plate tectonic was examined through correlation analysis. The results showed that, while the observation data from the QUAD station in the island deformation array are of poor quality, relative stability was maintained within the deformation array. The PTRF and CLRS stations exhibited vertical instability in the fall season, while the QUAD station showed a weaker instability trend. The remaining stations maintained good stability with closer stations demonstrating stronger consistency in their displacement. In terms of plate tectonic, the deformation array stations exhibit a similar southwestward displacement trend as the North American Plate in the horizontal direction, but no significant trend in the vertical direction.

Background: The association of specific PM2.5 chemical constituents with childhood overweight or obesity (OWOB) remain unclear. Furthermore, the long-term impacts of PM2.5 exposure on the trajectory of children's body mass index (BMI) have not been explored. Methods: We conducted a longitudinal study among 1,450,830 Chinese children aged 6–19 years from Beijing and Zhongshan in China during 2005–2018 to examine the associations of PM2.5 and its chemical constituents with incident OWOB risk. We extracted PM2.5 mass and five main component exposure from Tracking Air Pollution in China (TAP) dataset. Cox proportional hazards models were applied to quantify exposure–response associations. We further performed principal component analysis (PCA) to handle the multi-collinearity and used quantile g-computation (QGC) approach to analyze the impacts of exposure mixtures. Additionally, we selected 125,863 children with at least 8 physical examination measurements and combined group-based trajectory models (GBTM) with multinomial logistic regression models to explore the impacts of exposure to PM2.5 mass and five constituents on BMI and BMI Z-score trajectories during 6–19 years. Results: We observed each interquartile range increment in PM2.5 exposure was significantly associated with a 5.1 % increase in the risk of incident OWOB (95 % confidence Interval [CI]: 1.036–1.066). We also found black carbon, sulfate, organic matter, often linked to fossil combustion, had comparable or larger estimates of the effect (HR = 1.139–1.153) than PM2.5. Furthermore, Exposure to PM2.5 mass, sulfate, nitrate, ammonium, organic matter and black carbon was significantly associated with an increased odds of being in a larger BMI trajectory and being assigned to persistent OWOB trajectory. Conclusions: Our findings provide evidence that the constituents mainly from fossil fuel combustion may have a perceptible influence on increased OWOB risk associated with PM2.5 exposure in China. Moreover, long-term exposure to PM2.5 contributes to an increased odds of being in a lager BMI and a persistent OWOB trajectories.

Background: Although there is evidence of long-term effects of particulate matter (PM) on cardiovascular diseases (CVD), researches about long-term effects of PM1 on CVD are limited. We aimed to examine the long-term effects and magnitude of PM, especially PM1, on incident CVD in China. Methods: We included 6016 participants aged ≥ 45 years without CVD at baseline in 2011 from the China Health and Retirement Longitudinal Study. Personal PM (PM1, PM2.5, and PM10) concentrations were estimated using geocoded residential address. Generalized linear mixed models and SHapley Additive exPlanation were utilized to calculate the impacts and contributions of PM on CVD. Sensitivity analyses were used to check the robustness. Results: After a follow up of 4-year, 481 (7.99 %) participants developed CVD. Per 10 μg/m3 uptick in 1-year average concentrations of PM1, PM2.5 and PM10 was associated with a 1.20 [95 % confidence interval (CI): 1.05–1.37], 1.13 (95 % CI: 1.11–1.15), and 1.10 (95 % CI: 1.06–1.13) fold risk of incident CVD, respectively. The 2-year average concentrations of PM1, PM2.5 and PM10 were associated with incident CVD, corresponding to a 1.03 (95 % CI: 0.96–1.10), 1.11 (95 % CI: 1.02–1.21), and 1.09 (95 % CI: 1.03–1.15) fold risk, respectively. The SHapley Additive exPlanation values of PM1, PM2.5, and PM10 were 0.170, 0.153, and 0.053, respectively, corresponding to the first, second, and fifth among all air pollutants. Effects of PM1, PM2.5 and PM10 on CVD remained statistically significant in two-pollutant models. The elderly, males, smokers and alcohol drinkers tended to have slightly higher effects, while the differences were not statistically significant (all P-values > 0.05) between subgroups. Conclusion: Long-term exposure to PM1, PM2.5, and PM10 was associated with an increased incidence of CVD. The smaller the particle size, the more important it was for incident CVD indicating that emphasis should be placed on small size of PM.

Abstract Background Arterial stiffness, glycemic control and blood pressure are risk factors of macrovascular complications in type 2 diabetes. This study aimed to investigate the combined association of arterial stiffness, glycemic control and hypertension status with the occurrence of diabetic macrovascular complication. Methods A total of 1870 patients of diabetes were enrolled from Beijing Health Management Cohort between 2008 and 2018 as baseline, and then followed for macrovascular complication onset. We proposed a composite risk score (0–4) by arterial stiffness severity, pool glycemic control and hypertension status. Cox model was used to estimate the hazard ratio (HR) and 95% confidence interval (CI). Results The mean age (SD) of this population was 59.90 (12.29) years. During a median follow-up of 4.0 years, 359 (19.2%) patients developed macrovascular complication. Compared to the normal arterial stiffness and good glycemic control group, patients with severe arterial stiffness and pool glycemic control had the highest risk of macrovascular complications (HR: 2.73; 95% CI: 1.42–5.25). Similarly, those of severe arterial stiffness and hypertension had the highest risk (HR: 2.69; 95% CI: 1.61–4.50). Patients of the composite score > 2 had a significantly increased risk of macrovascular complication. Conclusion This study suggested the clinical importance of combined evaluation of arterial stiffness, glycemic control and hypertension status for the risk stratification and management of macrovascular complication of type 2 diabetes.

Abstract Extensive researches have linked air pollutants with cardiovascular disease (CVD) and respiratory diseases (RD), however, there is limited evidence on causal effects of air pollutants on morbidity of CVD or RD with comorbidities, particularly diabetes mellitus in elder patients. We included hospital admissions for CVD or RD among elder (≥65 years) diabetic patients between 2014 and 2019 in Beijing. A time‐stratified case‐crossover design based on negative‐control exposure was used to assess causal associations of short‐term exposure to air pollutants with CVD and RD among diabetic patients with the maximum lag of 7 days. A random forest regression model was used to calculate the contribution magnitude of air pollutants. A total of 493,046 hospital admissions were recorded. Per 10 μg/m3 uptick in PM1, PM2.5, PM10, SO2, NO2, O3, and 1 mg/m3 in CO was associated with 0.29 (0.05, 0.53), 0.14 (0.02, 0.26), 0.06 (0.00, 0.12), 0.36 (0.01, 0.70), 0.21 (0.02, 0.40), −0.08 (−0.25, 0.09), and 4.59 (0.56, 8.61) causal effect estimator for admission of CVD among diabetic patients, corresponding to 0.12 (0.05, 0.18), 0.09 (0.05, 0.13), 0.05, 0.23 (0.06, 0.41), 0.10 (0.02, 0.19), −0.04 (−0.06, −0.01), and 3.91(1.81, 6.01) causal effect estimator for RD among diabetic patients. The effect of gaseous pollutants was higher than particulate pollutants in random forest model. Short‐term exposure to air pollution was causally associated with increased admission of CVD and RD among elder diabetic patients. Gaseous pollutants had a greater contribution to CVD and RD among elder diabetic patients.

IntroductionWe aimed to investigate the association between greenness around schools, long-term gaseous air pollution exposure (SO2 and CO), and blood pressure in children and adolescents.MethodsFrom 2006 to 2018, a total of 219,956 Chinese children and adolescents aged 7–17 years in Beijing and Zhongshan were included in this longitudinal study. Annual average concentrations of SO2 and CO and the mean values of normalized difference vegetation index around schools were calculated. We used the generalized estimation equation model, restricted cubic spline model, and Cox model to analyze the health effects.ResultsAmong all the subjects, 52,515 had the first onset of HBP. During the follow-up, HBP's cumulative incidence and incidence density were 23.88% and 7.72 per 100 person-year respectively. Exposures to SO2 and CO were significantly associated with SBP [β = 1.30, 95% CI: (1.26, 1.34) and 0.78 (0.75, 0.81)], DBP [β = 0.81 (0.79, 0.84) and 0.46 (0.44, 0.48)] and HBP [HR = 1.58 (1.57, 1.60) and 1.42 (1.41, 1.43)]. The risks of HBP attributed to SO2 and CO pollution would be higher in school-aged children in the low greenness group: the attributable fractions (AFs) were 26.31% and 20.04%, but only 13.90% and 17.81% in the higher greenness group. The AFs were also higher for normal-BMI children and adolescents in the low greenness group (AFs = 30.90% and 22.64%, but 14.41% and 18.65% in the high greenness group), while the AFs were not as high as expected for obese children in the low greenness group (AFs = 10.64% and 8.61%), nor was it significantly lower in the high greenness group (AFs = 9.60% and 10.72%).DiscussionGreenness could alleviate the damage effects of SO2/CO exposure on the risks of HBP among children and adolescents, and the benefit is BMI sensitivity. It might offer insights for policymakers in making effective official interventions to prevent and control the prevalence of childhood HBP and the future disease burden caused by air pollution.

Abstract The association between CO and chronic obstructive pulmonary disease (COPD) has been widely reported; however, the association among patients with type 2 diabetes mellitus (T2DM) or hypertension has remained largely unknown in China. Over‐dispersed generalized additive model was adopted to quantity the associations between CO and COPD with T2DM or hypertension. Based on principal diagnosis, COPD cases were identified according to the International Classification of Diseases (J44), and a history of T2DM and hypertension was coded as E12 and I10‐15, O10‐15, P29, respectively. A total of 459,258 COPD cases were recorded from 2014 to 2019. Each interquartile range uptick in CO at lag 03 corresponded to 0.21% (95%CI: 0.08%–0.34%), 0.39% (95%CI: 0.13%–0.65%), 0.29% (95%CI: 0.13%–0.45%) and 0.27% (95%CI: 0.12%–0.43%) increment in admissions for COPD, COPD with T2DM, COPD with hypertension and COPD with both T2DM and hypertension, respectively. The effects of CO on COPD with T2DM (Z = 0.77, P = 0.444), COPD with hypertension (Z = 0.19, P = 0.234) and COPD with T2DM and hypertension (Z = 0.61, P = 0.543) were insignificantly higher than that on COPD. Stratification analysis showed that females were more vulnerable than males except for T2DM group (COPD: Z = 3.49, P

IntroductionAltered Immunoglobulin G (IgG) N-glycosylation is associated with aging, inflammation, and diseases status, while its effect on esophageal squamous cell carcinoma (ESCC) remains unknown. As far as we know, this is the first study to explore and validate the association of IgG N-glycosylation and the carcinogenesis progression of ESCC, providing innovative biomarkers for the predictive identification and targeted prevention of ESCC.MethodsIn total, 496 individuals of ESCC (n=114), precancerosis (n=187) and controls (n=195) from the discovery population (n=348) and validation population (n=148) were recruited in the study. IgG N-glycosylation profile was analyzed and an ESCC-related glycan score was composed by a stepwise ordinal logistic model in the discovery population. The receiver operating characteristic (ROC) curve with the bootstrapping procedure was used to assess the performance of the glycan score.ResultsIn the discovery population, the adjusted OR of GP20 (digalactosylated monosialylated biantennary with core and antennary fucose), IGP33 (the ratio of all fucosylated monosyalilated and disialylated structures), IGP44 (the proportion of high mannose glycan structures in total neutral IgG glycans), IGP58 (the percentage of all fucosylated structures in total neutral IgG glycans), IGP75 (the incidence of bisecting GlcNAc in all fucosylated digalactosylated structures in total neutral IgG glycans), and the glycan score are 4.03 (95% CI: 3.03-5.36, P

Abstract Background The association between visceral adiposity index (VAI) and diabetic complications has been reported in cross-sectional studies, while the effect of VAI on complication development remains unclear. This study aims to evaluate the longitudinal association of VAI and Chinese VAI (CVAI) with the incidence of diabetic nephropathy and retinopathy using a Chinese cohort. Methods A total of 8 948 participants with type 2 diabetes from Beijing Health Management Cohort were enrolled during 2013–2014, and followed until December 31, 2019. Nephropathy was confirmed by urine albumin/creatinine ratio and estimated glomerular filtration rate; retinopathy was diagnosed using fundus photograph. Results The mean (SD) age was 53.35 (14.66) years, and 6 154 (68.8%) were men. During a median follow-up of 4.82 years, 467 participants developed nephropathy and 90 participants developed retinopathy. One-SD increase in VAI and CVAI levels were significantly associated with an increased risk of nephropathy, and the adjusted hazard ratios (HR) were 1.127 (95% CI 1.050–1.210) and 1.165 (95% CI 1.003–1.353), respectively. On contrary, VAI and CVAI level were not associated with retinopathy after adjusting confounding factors. Conclusion VAI and CVAI are independently associated with the development of nephropathy, but not retinopathy in Chinese adults with diabetes.

Objectives: This study aimed to examine the association of solid fuel use for cooking and heating with the progression of multimorbidity.Methods: A total of 5,437 participants from the China Health and Retirement Longitudinal Study were included. Multivariate logistic regression models were used to estimate the odds ratios (ORs) and 95% confidence intervals (CIs) for the associations of the independent and joint effects of solid fuel use for cooking and heating with the progression of multimorbidity.Results: The proportion of participants reporting solid fuel use for both cooking and heating was 59.0% at baseline. Solid fuel use for both cooking and heating was associated with the progression of multimorbidity (adjusted OR: 1.42, 95% CI: 1.19–1.70), compared with clean fuel use for both.Conclusion: Solid fuel use for cooking and heating play an important role in the progression of multimorbidity. Therefore, solid fuel reduction should be considered in developing multimorbidity control and prevention programmes.

Abstract Background To evaluate the association of physical activity (PA) intensity with cognitive performance at baseline and during follow-up. Methods A total of 4039 participants aged 45 years or above from the China Health and Retirement Longitudinal Study were enrolled in visit 1 (2011–2012) and followed for cognitive function in visit 2 (2013–2014), visit 3 (2015–2016), and visit 4 (2017–2018). We analyzed the association of PA intensity with global cognition, episodic memory, and mental intactness at baseline using adjusted regression methods and evaluated the long-term effect of PA intensity using multiple measures of cognition scores by mixed effect model. Results In cross-sectional analysis, mild and moderate PA, rather than vigorous PA, was associated with better cognitive performance. The results remained consistent in multiple sensitivity analyses. During the follow-up, participant with mild PA had a 0.56 (95% CI 0.12–0.99) higher global cognition, 0.23 (95% CI 0.01–0.46) higher episodic memory, and 0.33 (95% CI 0.01–0.64) higher mental intactness, while those with moderate PA had a 0.74 (95% CI 0.32–1.17) higher global score, 0.32 (95% CI 0.09–0.54) higher episodic memory, and 0.43 (95% CI 0.12–0.74) higher mental intactness, compared with individuals without PA. Vigorous PA was not beneficial to the long-term cognitive performance. Conclusions Our study indicates that mild and moderate PA could improve cognitive performance, rather than the vigorous activity. The targeted intensity of PA might be more effective to achieve the greatest cognition improvement considering age and depressive status.

Background and Objectives: Lung cancer remains a leading cause of cancer mortality worldwide. Accurately classifying benign pulmonary nodules and malignant ones is crucial for early diagnosis and improved patient outcomes. The purpose of this study is to explore the deep-learning model of ResNet combined with a convolutional block attention module (CBAM) for the differentiation between benign and malignant lung cancer, based on computed tomography (CT) images, morphological features, and clinical information. Methods and materials: In this study, 8241 CT slices containing pulmonary nodules were retrospectively included. A random sample comprising 20% (n = 1647) of the images was used as the test set, and the remaining data were used as the training set. ResNet combined CBAM (ResNet-CBAM) was used to establish classifiers on the basis of images, morphological features, and clinical information. Nonsubsampled dual-tree complex contourlet transform (NSDTCT) combined with SVM classifier (NSDTCT-SVM) was used as a comparative model. Results: The AUC and the accuracy of the CBAM-ResNet model were 0.940 and 0.867, respectively, in test set when there were only images as inputs. By combining the morphological features and clinical information, CBAM-ResNet shows better performance (AUC: 0.957, accuracy: 0.898). In comparison, a radiomic analysis using NSDTCT-SVM achieved AUC and accuracy values of 0.807 and 0.779, respectively. Conclusions: Our findings demonstrate that deep-learning models, combined with additional information, can enhance the classification performance of pulmonary nodules. This model can assist clinicians in accurately diagnosing pulmonary nodules in clinical practice.

Abstract Background Cross-sectional studies have reported that insulin resistance (IR) is associated with arterial stiffness. However, the relationship between IR and arterial stiffness progression remains unclear. This study aims to evaluate the association of triglyceride glucose (TyG) index and triglyceride to high-density lipoprotein cholesterol (TG/HDL-C) ratio with arterial stiffness progression in a non-normotensive population. Methods A total of 1895 prehypertensive (systolic pressure 120–139 mmHg or diastolic pressure 80–90 mmHg) or hypertensive (systolic pressure ≥ 140 mmHg or diastolic pressure ≥ 90 mmHg or using antihypertensive medication) participants were enrolled in 2013 and 2014, and followed until December 31, 2019. Arterial stiffness progression was measured by brachial-ankle pulse wave velocity (baPWV) change (absolute difference between baseline and last follow-up), baPWV change rate (change divided by following years), and baPWV slope (regression slope between examination year and baPWV). Results During a median follow-up of 4.71 years, we observed an increasing trend of baPWV in the population. There were linear and positive associations of the TyG index and TG/HDL-C ratio with the three baPWV parameters. The difference (95% CI) in baPWV change (cm/s) comparing participants in the highest quartile versus the lowest of TyG index and TG/HDL-C ratio were 129.5 (58.7–200.0) and 133.4 (52.0–214.9), respectively. Similarly, the evaluated baPWV change rates (cm/s/year) were 37.6 (15.3–60.0) and 43.5 (17.8–69.2), while the slopes of baPWV were 30.6 (9.3–51.8) and 33.5 (9.0–58.0). The observed association was stronger in the hypertensive population. Conclusion Our study indicates that the TyG index and TG/HDL-C ratio are significantly associated with arterial stiffness progression in hypertensive population, not in prehypertensive population.

Background: Evidence on the effects of the air pollutants on the hospital admissions, hospital cost and length of stay (LOS) among patients with comorbidities remains limited in China, particularly for patients with cardiovascular diseases and comorbid diabetes mellitus (CVD-DM). Methods: We collected daily data on CVD-DM patients from 242 hospitals in Beijing between 2014 and 2019. Generalized additive model was employed to quantify the associations between admissions, LOS, and hospital cost for CVD-DM patients and air pollutants. We further evaluated the attributable risk posed by air pollutants to CVD-DM patients, using both Chinese and WHO air quality guidelines as reference. Results: Per 10 ug/m3 increase of particles with an aerodynamic diameter

Abstract Background Associations between the frequency of social and intellectual activities and cognitive trajectories are understudied in Chinese middle-aged and older adults. We aimed to examine this association in a nationally representative longitudinal study. Methods The China Health and Retirement Longitudinal Study (CHARLS) is a nationally representative sample of Chinese middle-aged and older participants. The frequency of social and intellectual activities was measured at baseline. Interview-based cognitive assessments of orientation and attention, episodic memory, and visuospatial skills and the calculation of combined global scores were assessed every 2 years from 2011 to 2016. Cognitive aging trajectories over time were analyzed using group-based trajectory modeling, and the associations of the trajectory memberships with social and intellectual activities were analyzed using multinomial logistic regression. Odds ratios (OR) and 95% confidence intervals (CI) were reported. Results Among 8204 participants aged 50–75 years at baseline, trajectory analysis identified three longitudinal patterns of cognitive function based on the global cognitive scores: “persistently low trajectory” (n = 1550, 18.9%), “persistently moderate trajectory” (n = 3194, 38.9%), and “persistently high trajectory” (n = 3460, 42.2%). After adjustment for sociodemographic variables, lifestyles, geriatric symptoms, and health conditions, more frequent intellectual activities (OR 0.54, 95% CI 0.38–0.77) and social activities (OR 0.79, 95% CI 0.65–0.95) were both associated with a lower likelihood of being in the “persistently low trajectory” for global cognitive function. Conclusions These findings suggested that more frequent social and intellectual activities were associated with more favorable cognitive aging trajectories.

Background: Scientific studies have identified various adverse effects of particulate matter (PM) on respiratory disease (RD) and type 2 diabetes (T2D). However, whether short-term exposure to PM triggers the onset of RD with T2D, compared with RD without T2D, has not been elucidated. Methods: A two-stage time-series study was conducted to evaluate the acute adverse effects of PM on admission for RD and for RD with and without T2D in Beijing, China, from 2014 to 2020. District-specific effects of PM2.5 and PM10 were estimated using the over-dispersed Poisson generalized addictive model after adjusting for weather conditions, day of the week, and long-term and seasonal trends. Meta-analyses were applied to pool the overall effects on overall and cause-specific RD, while the exposure-response (E-R) curves were evaluated using a cubic regression spline. Results: A total of 1550,154 admission records for RD were retrieved during the study period. Meta-analysis suggested that per interquartile range upticks in the concentration of PM2.5 corresponded to 1.91% (95% CI: 1.33–2.49%), 2.16% (95% CI: 1.08–3.25%), and 1.92% (95% CI: 1.46–2.39%) increments in admission for RD, RD with T2D, and RD without T2D, respectively, at lag 0–8 days, lag 8 days, and lag 8 days. The effect size of PM2.5 was statistically significantly higher in the T2D group than in the group without T2D (z = 3.98, P

BackgroundThe supervised deep learning approach provides state-of-the-art performance in a variety of fundus image classification tasks, but it is not applicable for screening tasks with numerous or unknown disease types. The unsupervised anomaly detection (AD) approach, which needs only normal samples to develop a model, may be a workable and cost-saving method of screening for ocular diseases. ObjectiveThis study aimed to develop and evaluate an AD model for detecting ocular diseases on the basis of color fundus images. MethodsA generative adversarial network–based AD method for detecting possible ocular diseases was developed and evaluated using 90,499 retinal fundus images derived from 4 large-scale real-world data sets. Four other independent external test sets were used for external testing and further analysis of the model’s performance in detecting 6 common ocular diseases (diabetic retinopathy [DR], glaucoma, cataract, age-related macular degeneration, hypertensive retinopathy [HR], and myopia), DR of different severity levels, and 36 categories of abnormal fundus images. The area under the receiver operating characteristic curve (AUC), accuracy, sensitivity, and specificity of the model’s performance were calculated and presented. ResultsOur model achieved an AUC of 0.896 with 82.69% sensitivity and 82.63% specificity in detecting abnormal fundus images in the internal test set, and it achieved an AUC of 0.900 with 83.25% sensitivity and 85.19% specificity in 1 external proprietary data set. In the detection of 6 common ocular diseases, the AUCs for DR, glaucoma, cataract, AMD, HR, and myopia were 0.891, 0.916, 0.912, 0.867, 0.895, and 0.961, respectively. Moreover, the AD model had an AUC of 0.868 for detecting any DR, 0.908 for detecting referable DR, and 0.926 for detecting vision-threatening DR. ConclusionsThe AD approach achieved high sensitivity and specificity in detecting ocular diseases on the basis of fundus images, which implies that this model might be an efficient and economical tool for optimizing current clinical pathways for ophthalmologists. Future studies are required to evaluate the practical applicability of the AD approach in ocular disease screening.

Background: The health effect of particulate matter pollution on stroke has been widely examined; however, the effect among patients with comorbid type 2 diabetes (T2D) in developing countries has remained largely unknown. Methods: A time-series study was conducted to investigate the short-term effect of fine particulate matter (PM2.5) and inhalable particulate matter (PM10) on hospital admissions for stroke among patients with T2D in Beijing, China, from 2014 to 2018. An over-dispersed Poisson generalized additive model was employed to adjust for important covariates, such as weather conditions and long-term and seasonal trends. Results: A total of 159,298 hospital admissions for stroke comorbid with T2D were reported. Approximately linear exposure-response curves were observed for PM2.5 and PM10 in relation to stroke admissions among T2D patients. A 10 μg/m3 increase in the four-day moving average of PM2.5 and PM10 was associated with 0.14% (95% confidence interval [CI]: 0.05–0.23%) and 0.14% (95% CI: 0.06–0.22%) incremental increases in stroke admissions among T2D patients, respectively. A 10 μg/m3 increase in PM2.5 in the two-day moving average corresponded to a 0.72% (95% CI: 0.02–1.42%) incremental increase in hemorrhagic stroke, and a 10 μg/m3 increase in PM10 in the four-day moving average corresponded to a 0.14% (95% CI: 0.06–0.22%) incremental increase in ischemic stroke. Conclusions: High particulate matter might be a risk factor for stroke among patients with T2D. PM2.5 and PM10 have a linear exposure-response relationship with stroke among T2D patients. The study provided evidence of the risk of stroke due to particulate matter pollution among patients with comorbid T2D.

Abstract Background Air pollution and cardiovascular disease are increasing problems in China. However, the short-term association between fine particulate matter (PM2.5) and cardiovascular disease (CVD) is not well documented. The purpose of this study is to estimate the short-term effects of PM2.5 on CVD admissions in Beijing, China. Methods In total, 460,938 electronic hospitalization summary reports for CVD between 2013 and 2017 were obtained. A generalized additive model using a quasi-Poisson distribution was used to investigate the association between exposure to PM2.5 and hospitalizations for total and cause-specific CVD, including coronary heart disease (CHD), atrial fibrillation (AF), and heart failure (HF) after controlling for the season, the day of the week, public holidays, and weather conditions. A stratified analysis was also conducted for age (18–64 and ≥ 65 years), sex and season. Results For every 10 μg/m3 increase in the PM2.5 concentration from the previous day to the current (lag 0–1) there was a significant increase in total CVD admissions (0.30, 95% CI: 0.20, 0.39%), with a strong association for older adults (aged ≥65 years), CHD (0.34, 95% CI: 0.22 to 0.45%) and AF (0.29, 95% CI, 0.03 to 0.55%). However, the observed increased risk was not statistically significant for HF hospitalizations. The associations in the single-pollutant models were robust to the inclusion of other pollutants in a two-pollutant model. No differences were found after stratification by sex and season. Conclusions Exposure to PM2.5 increased the risk of hospitalizations from CVD, especially for CHD, and appeared to have more influence in the elderly. Precautions and protective measures and efforts to reduce exposure to PM2.5 should be strengthened, especially for the elderly.

Abstract Background Evidence of the association between dyslipidemia and its components with commuting mode after adjusting for air pollution is limited. This study aimed to explore the association of dyslipidemia and its components with the modes used to commute to and from work after accounting for air pollution and other potential confounding factors. Methods This cross–sectional study was based on data collected from a working population of 69 functional communities in Beijing in 2016. A final sample of 8090 adults aged 18–65 years (mean age: 38.36 ± 9.75 years) was enrolled in the study. Risk estimates and their corresponding 95% confidence intervals (CIs) for the associations of dyslipidemia and its components with commuting mode were determined using multivariate logistic regression models. Results Of the 8090 subjects, 2419 (29.90%) met the criteria for dyslipidemia. Compared with car or taxi commuters, walking (OR 0.79, 95% CI 0.64 to 0.97), cycling (OR 0.71, 95% CI 0.58 to 0.86) and bus-riding commuters (OR 0.78, 95% CI 0.66 to 0.91) had a lower risk for dyslipidemia. Compared with car or taxi commuting, walking, cycling and bus-riding commuting were also associated with a lower risk for some components of dyslipidemia. Among the walking, cycling and bus-riding commuters, a dose-response trend of the association between dyslipidemia, some of its components and commuting mode by commuting time was also observed. Conclusions Walking, cycling and bus-riding commuting can reduce the risk for dyslipidemia and some of its components. Education on the prevention of dyslipidemia should be emphasized among higher-risk people who usually commute by car or taxi. Population-wide health may be improved by policies that encourage active commuting, particularly cycling and walking.

Landslides constitute a severe environmental problem in Jiangxi, China. This research was aimed at conducting landslide hazard assessment to provide technical support for disaster reduction and prevention action in the province. Fourteen geo-environmental factors, e.g., slope, elevation, road, river, fault, lithology, rainfall, and land cover types, were selected for this study. A test was made in two cases: (1) only based on the main linear features, e.g., main rivers and roads, and (2) with detailed complete linear features including all levels of roads and rivers. After buffering of the linear features, an information value (IV) analysis was applied to quantify the distribution of the observed landslides for each subset of the 14 factors. The results were inputted into the binary logistic regression model (LRM) for landslide risk modeling, taking the known landslide points as a training set (70% of the total 9,525 points). The calculated probability of a landslide was further classified into five grades with an interval of 0.2 for hazard mapping: very high (3.70%), high (4.05%), moderate (18.72%), low (27.17%), and stable zones (46.36%). The accuracy was evaluated by AUC [the area under the receiver operating characteristic (ROC) curve] vs. the validation set (30%, the remaining landslides). The final results show that with increasing the completeness of the linear features, the modeling reliability also significantly increased. We hence concluded that the tested methodology is capable of achieving the landslide hazard prediction at regional scale, and the results may provide technical support for geohazard reduction and prevention in the studied province.

Background. Sleep duration is associated with type 2 diabetes (T2D). However, few T2D risk scores include sleep duration. We aimed to develop T2D scores containing sleep duration and to estimate the additive value of sleep duration. Methods. We used data from 43,404 adults without T2D in the Beijing Health Management Cohort study. The participants were surveyed approximately every 2 years from 2007/2008 to 2014/2015. Sleep duration was calculated from the self-reported usual time of going to bed and waking up at baseline. Logistic regression was employed to construct the risk scores. Integrated discrimination improvement (IDI) and net reclassification improvement (NRI) were used to estimate the additional value of sleep duration. Results. After a median follow-up of 6.8 years, we recorded 2623 (6.04%) new cases of T2D. Shorter (both 6-8 h/night and 8 h/night in the adjusted model. Seven variables, including age, education, waist-hip ratio, body mass index, parental history of diabetes, fasting plasma glucose, and sleep duration, were selected to form the comprehensive score; the C-index was 0.74 (95% CI: 0.71-0.76) for the test set. The IDI and NRI values for sleep duration were 0.017 (95% CI: 0.012-0.022) and 0.619 (95% CI: 0.518-0.695), respectively, suggesting good improvement in the predictive ability of the comprehensive nomogram. The decision curves showed that women and individuals older than 50 had more net benefit. Conclusions. The performance of T2D risk scores developed in the study could be improved by containing the shorter estimated sleep duration, particularly in women and individuals older than 50.

Background. The relationship between the IgG glycan panel and type 2 diabetes remains unclear in Chinese population. We aimed to investigate the association of the IgG glycan profile and glycan score with type 2 diabetes. Methods. In the discovery population, 162 individuals diagnosed with type 2 diabetes and 162 matched controls from Beijing health management cohort were included. We analyzed the IgG glycan profile and composed a glycan score for type 2 diabetes. Findings were validated in the replication population from Beijing Xuanwu community cohort (280 cases and 508 controls). Area under curve (AUC) using 10-fold and bootstrap validation, net reclassification index (NRI), and integrated discrimination index (IDI) were calculated for the glycan score. Results. In the discovery population, 5 initial IgG glycans and 7 derived traits were significantly associated with type 2 diabetes after Bonferroni correction and Lasso selection, which were validated in the replication population subsequently. The glycan score composed of these IgG glycans and traits showed a strong association with type 2 diabetes (combined odds ratio (OR): 3.78) and its risk factors. In the replication population, AUC of the model involving clinical traits improved from 0.74 to above 0.90, and the values of NRI and IDI were 0.35 and 0.42, respectively, with the glycan score added. Conclusions. IgG glycosylation profiles were associated with type 2 diabetes and the glycan score may be a novel indicator for diabetes which reflected a proinflammatory status.

Abstract Background Research on the relationship between metabolic syndrome (MetS), its components and eating speed is limited in China. The present study aimed to clarify the association between MetS, its components and eating speed in a Beijing adult population. Methods This cross-sectional study included 7972 adults who were 18–65 years old and who received health check-ups at the Beijing Physical Examination Center in 2016. Logistic regression was conducted to explore the associations between MetS, its components and eating speed. Results The prevalence of MetS in this population was 24.65% (36.02% for males and 10.18% for females). Eating speed was significantly associated with a high risk for MetS, elevated blood pressure, and central obesity for both genders. Eating speed was associated with a high risk for elevated triglycerides and with a reduction in high-density lipoprotein in males, and eating speed was associated with a high risk for elevated fasting plasma glucose in females. Compared with slow eating speed, the multivariate-adjusted odds ratios of medium eating speed and fast eating speed for MetS were 1.65 (95% confidence interval 1.32–2.07) and 2.27 (95% confidence interval 1.80–2.86) for all subjects, 1.58 (95% confidence interval 1.21–2.07) and 2.21 (95% confidence interval 1.69–2.91) for males, and 1.75 (95% confidence interval 1.15–2.68) and 2.27 (95% confidence interval 1.46–3.53) for females, respectively. Conclusions Eating speed is positively associated with MetS and its components. Future recommendations aiming to prevent MetS and its components may focus on eating speed.

Background: Coronavirus disease 2019 (COVID-19), a global pandemic, has caused over 216 million cases and 4.50 million deaths as of 30 August 2021. Vaccines can be regarded as one of the most powerful weapons to eliminate the pandemic, but the impact of vaccines on daily COVID-19 cases and deaths by country is unclear. This study aimed to investigate the correlation between vaccines and daily newly confirmed cases and deaths of COVID-19 in each country worldwide. Methods: Daily data on firstly vaccinated people, fully vaccinated people, new cases and new deaths of COVID-19 were collected from 187 countries. First, we used a generalized additive model (GAM) to analyze the association between daily vaccinated people and daily new cases and deaths of COVID-19. Second, a random effects meta-analysis was conducted to calculate the global pooled results. Results: In total, 187 countries and regions were included in the study. During the study period, 1,011,918,763 doses of vaccine were administered, 540,623,907 people received at least one dose of vaccine, and 230,501,824 people received two doses. For the relationship between vaccination and daily increasing cases of COVID-19, the results showed that daily increasing cases of COVID-19 would be reduced by 24.43% [95% CI: 18.89, 29.59] and 7.50% [95% CI: 6.18, 8.80] with 10,000 fully vaccinated people per day and at least one dose of vaccine, respectively. Daily increasing deaths of COVID-19 would be reduced by 13.32% [95% CI: 3.81, 21.89] and 2.02% [95% CI: 0.18, 4.16] with 10,000 fully vaccinated people per day and at least one dose of vaccine, respectively. Conclusions: These findings showed that vaccination can effectively reduce the new cases and deaths of COVID-19, but vaccines are not distributed fairly worldwide. There is an urgent need to accelerate the speed of vaccination and promote its fair distribution across countries.

Urban infrastructures have become imperative to human life. Any damage to these infrastructures as a result of detrimental activities would accrue huge economical costs and severe casualties. War in particular is a major anthropogenic calamity with immense collateral effects on the social and economic fabric of human nations. Therefore, damaged buildings assessment plays a prominent role in post-war resettlement and reconstruction of urban infrastructures. The data-analysis process of this assessment is essential to any post-disaster program and can be carried out via different formats. Synthetic Aperture Radar (SAR) data and Interferometric SAR (InSAR) techniques help us to establish a reliable and fast monitoring system for detecting post-war damages in urban areas. Along this thread, the present study aims to investigate the feasibility and mode of implementation of Sentinel-1 SAR data and InSAR techniques to estimate post-war damage in war-affected areas as opposed to using commercial high-resolution optical images. The study is presented in the form of a survey to identify urban areas damaged or destroyed by war (Islamic State of Iraq and the Levant, ISIL, or ISIS occupation) in the city of Mosul, Iraq, using Sentinel-1 (S1) data over the 2014–2017 period. Small BAseline Subset (SBAS), Persistent Scatterer Interferometry (PSI) and coherent-intensity-based analysis were also used to identify war-damaged buildings. Accuracy assessments for the proposed SAR-based mapping approach were conducted by comparing the destruction map to the available post-war destruction map of United Nations Institute for Training and Research (UNITAR); previously developed using optical very high-resolution images, drone imagery, and field visits. As the findings suggest, 40% of the entire city, the western sectors, especially the Old City, were affected most by ISIS war. The findings are also indicative of the efficiency of incorporating Sentinel-1 SAR data and InSAR technique to map post-war urban damages in Mosul. The proposed method could be widely used as a tool in damage assessment procedures in any post-war reconstruction programs.

Background Cognitive impairment may increase the risk of all‐cause and cardiovascular disease (CVD) mortality. This study examined the association between cognitive function and risk of all‐cause and CVD mortality among the elderly in Beijing, China. Methods and Results A total of 1996 participants aged ≥55 years at baseline were enrolled from the BLSA (Beijing Longitudinal Study of Aging). Cognitive function was assessed using the Mini‐Mental State Examination (MMSE), and participants were categorized as:

Limited information is available regarding spatiotemporal variations of particles with median aerodynamic diameter < 2.5 μm (PM2.5) at high resolutions, and their relationships with meteorological factors in Beijing, China. This study aimed to detect spatiotemporal change patterns of PM2.5 from August 2013 to July 2014 in Beijing, and to assess the relationship between PM2.5 and meteorological factors.Daily and hourly PM2.5 data from the Beijing Environmental Protection Bureau (BJEPB) were analyzed separately. Ordinary kriging (OK) interpolation, time-series graphs, Spearman correlation coefficient and coefficient of divergence (COD) were used to describe the spatiotemporal variations of PM2.5. The Kruskal-Wallis H test, Bonferroni correction, and Mann-Whitney U test were used to assess differences in PM2.5 levels associated with spatial and temporal factors including season, region, daytime and day of week. Relationships between daily PM2.5 and meteorological variables were analyzed using the generalized additive mixed model (GAMM).Annual mean and median of PM2.5 concentrations were 88.07 μg/m3 and 71.00 μg/m3, respectively, from August 2013 to July 2014. PM2.5 concentration was significantly higher in winter (P < 0.0083) and in the southern part of the city (P < 0.0167). Day to day variation of PM2.5 showed a long-term trend of fluctuations, with 2-6 peaks each month. PM2.5 concentration was significantly higher in the night than day (P < 0.0167). Meteorological factors were associated with daily PM2.5 concentration using the GAMM model (R2 = 0.59, AIC = 7373.84).PM2.5 pollution in Beijing shows strong spatiotemporal variations. Meteorological factors influence the PM2.5 concentration with certain patterns. Generally, prior day wind speed, sunlight hours and precipitation are negatively correlated with PM2.5, whereas relative humidity and air pressure three days earlier are positively correlated with PM2.5.

To determine the value of contourlet textural features obtained from solitary pulmonary nodules in two dimensional CT images used in diagnoses of lung cancer.A total of 6,299 CT images were acquired from 336 patients, with 1,454 benign pulmonary nodule images from 84 patients (50 male, 34 female) and 4,845 malignant from 252 patients (150 male, 102 female). Further to this, nineteen patient information categories, which included seven demographic parameters and twelve morphological features, were also collected. A contourlet was used to extract fourteen types of textural features. These were then used to establish three support vector machine models. One comprised a database constructed of nineteen collected patient information categories, another included contourlet textural features and the third one contained both sets of information. Ten-fold cross-validation was used to evaluate the diagnosis results for the three databases, with sensitivity, specificity, accuracy, the area under the curve (AUC), precision, Youden index, and F-measure were used as the assessment criteria. In addition, the synthetic minority over-sampling technique (SMOTE) was used to preprocess the unbalanced data.Using a database containing textural features and patient information, sensitivity, specificity, accuracy, AUC, precision, Youden index, and F-measure were: 0.95, 0.71, 0.89, 0.89, 0.92, 0.66, and 0.93 respectively. These results were higher than results derived using the database without textural features (0.82, 0.47, 0.74, 0.67, 0.84, 0.29, and 0.83 respectively) as well as the database comprising only textural features (0.81, 0.64, 0.67, 0.72, 0.88, 0.44, and 0.85 respectively). Using the SMOTE as a pre-processing procedure, new balanced database generated, including observations of 5,816 benign ROIs and 5,815 malignant ROIs, and accuracy was 0.93.Our results indicate that the combined contourlet textural features of solitary pulmonary nodules in CT images with patient profile information could potentially improve the diagnosis of lung cancer.