Abstract Background The associations between short- and long-term exposure to ambient fine particulate matter with an aerodynamic diameter ≤ 2.5 µm (PM2.5) and allergic symptoms in middle-aged and elderly populations remain unclear, particularly in China, where most cities have severe air pollution. Methods Participants (n = 10,142; age = 40–75 years) were recruited from ten regions in China from 2018 to 2021 for the Predictive Value of Inflammatory Biomarkers and Forced Expiratory Volume in 1 s (FEV1) for Chronic Obstructive Pulmonary Disease (PIFCOPD) study. Short-term (lag0 and lag0–7 day) and long-term (1-, 3- and 5-year) PM2.5 concentrations at residences were extracted from the air pollutant database known as Tracking Air Pollution (TAP) in China. Multivariate logistic regression models were used to estimate associations for short- and long-term PM2.5 exposure concentrations and long-term exposure models were additionally adjusted for short-term deviations. Results A 10 µg/m3 increase in PM2.5 on the day the allergic symptoms questionnaire was administered (lag0 day) was associated with higher odds of allergic nasal (1.09, 95% CI 1.05, 1.12) and eye symptoms (1.08, 95% CI 1.05, 1.11), worsening dyspnea caused by allergens (1.06, 95% CI 1.02, 1.10), and ≥ 2 allergic symptoms (1.07, 95% CI 1.03, 1.11), which was similar in the lag0–7 day concentrations. A 10 µg/m3 increase in the 1-year average PM2.5 concentration was associated with an increase of 23% for allergic nasal symptoms, 22% for eye symptoms, 20% for worsening dyspnea caused by allergens, and 21% for ≥ 2 allergic symptoms, similar to the 3- and 5-year average PM2.5 concentrations. These associations between long-term PM2.5 concentration and allergic symptoms were generally unchanged after adjustment for short-term deviations. Conclusions Short- and long-term exposure to ambient PM2.5 was associated with an increased risk of allergic nasal and eye symptoms, worsening dyspnea caused by allergens, and ≥ 2 allergic symptoms. Trial registration Clinical trial ID: NCT03532893 (29 Mar 2018).

Background: We aimed to determine whether depressive, anxiety, stress symptoms were associated with the risk of elevated blood pressure by performing longitudinal cohort and Mendelian Randomization (MR) analyses.Methods: We used data from the Cohort Study on Chronic Disease of Community Natural Population in the Beijing-Tianjin-Hebei region (CHCN-BTH) from 2017 to 2021. The Depression-Anxiety-Stress Scale was used to evaluate the depressive, anxiety, stress symptoms. The longitudinal associations between depressive, anxiety, stress symptoms and elevated blood pressure were estimated using Cox proportional regression models. Two-sample MR analysis was performed using the Inverse-variance weighted (IVW), weighted median, and MR-Eg-ger to explore the causal relationships between depressive, anxiety, stress symptoms and elevated blood pressure. Results: In total, 5624 participants were included. The risk of SBP & GE; 140 mmHg or DBP & GE; 90 mmHg was significantly higher in participants with baseline anxiety symptoms (HR = 1.48, 95 % CI: 1.03 to 2.12, P = 0.033; HR = 1.56, 95 % CI: 1.05 to 2.32, P = 0.028), especially in men and individuals with higher educational levels, independent of baseline depression and anxiety at the two-year follow-up. The two-sample MR analysis showed positive associations between depressive, anxiety, stress symptoms and elevated blood pressure.Limitation: Self-reported mental health symptoms, relatively shorter follow-up duration and the European-derived genome-wide association study data for MR analysis.Conclusions: Anxiety symptoms were positively associated with elevated blood pressures in the longitudinal analysis independent of depression, stress, and other confounders. The results were verified in MR analysis, providing evidence for causal effects of anxiety symptoms on the risk of elevated blood pressure.

Despite growing evidence that links long-term air pollution exposure to cardiovascular disease (CVD), the combined effects of air pollutants and particulate matter with an aerodynamic diameter of less than 2.5 μm (PM2.5) components are still limited. A prospective cohort study was performed based on the Cohort Study on Chronic Disease of the Community Natural Population in the Beijing-Tianjin-Hebei Region (CHCN-BTH) to assess the association of long-term air pollutants with incident CVD and the combined effect of the air pollutants mixture among 26,851 adults. Three-year residential exposure to air pollutants (PM2.5, O3, PM10, PM1, NO2, SO2 and CO) and PM2.5 components [black carbon (BC), NH4+, SO42-, NO3- and organic matter (OM)] were calculated based on well-validated models. Proportional hazard models were applied to assess the association of air pollutants with incident CVD. Quantile g-Computation was used to examine the combined effect of the pollutant mixture. During the 56,090 person-years follow-up, 629 participants reported incident CVD. Adjusted hazard ratios with 95% confidence intervals (CIs) of CVD per interquartile range increase in O3, PM2.5, PM1, NO2, BC, and OM concentrations were 4.52 (95%CI: 2.61, 7.83), 2.39 (95%CI: 1.83, 3.13), 2.37 (95%CI: 1.20, 4.70), 1.36 (95%CI: 1.19, 1.56), 3.84 (95%CI: 2.38, 6.18), and 3.07 (95%CI: 2.01, 4.69), respectively. In multi-pollutant models, the combined effect of air pollutant mixture on incident CVD was 2.37 (95%CI: 2.30, 2.44). PM2.5 and O3 contributed 54.3% and 44.5% of the combined effect of the air pollutant mixture, respectively. After using PM2.5 components instead of PM2.5 as part of the mixture, OM drove 55.2% of the combined effect. The findings indicated associations of air pollutant mixtures with CVD incidence. PM2.5 (especially OM) and O3 might strongly contribute to air pollutant mixtures that lead to incident CVD.

Abstract Background The application of artificial intelligence (AI) and large language models (LLMs) in the medical sector has become increasingly common. The widespread adoption of electronic health record (EHR) platforms has created demand for the efficient extraction and analysis of unstructured data, which are known as real-world data (RWD). The rapid increase in free-text data in the medical context has highlighted the significance of natural language processing (NLP) with regard to extracting insights from EHRs, identifying this process as a crucial tool in clinical research. The development of LLMs that are specifically designed for biomedical and clinical text mining has further enhanced the capabilities of NLP in this domain. Despite these advancements, the utilization of LLMs specifically in clinical research remains limited. Objective This study aims to assess the feasibility and impact of the implementation of an LLM for RWD extraction in hospital settings. The primary focus of this research is on the effectiveness of LLM-driven data extraction as compared to that of manual processes associated with the electronic source data repositories (ESDR) system. Additionally, the study aims to identify challenges emerging in the context of LLM implementation and to obtain practical insights from the field. Methods The researchers developed the ESDR system, which integrates LLMs, electronic case report forms (eCRFs) and EHRs. The Paroxysmal Atrial Tachycardia Project, a single-center retrospective cohort study, served as a pilot case. This study involved deploying the ESDR system on the hospital local area network (LAN). Localized LLM deployment utilized the Chinese open-source ChatGLM model. The research design compared the AI-assisted process with manual processes associated with the ESDR in terms of accuracy rates and time allocation. Five eCRF forms, predominantly including free-text content, were evaluated; the relevant data focused on 630 subjects, in which context a 10% sample (63 subjects) was used for assessment. Data collection involved electronic medical and prescription records collected from 13 departments. Results While the discharge medication form achieved 100% data completeness, some free-text forms exhibited data completeness rates below 20%. The AI-assisted process was associated with an estimated efficiency improvement of 80.7% in eCRF data transcription time. The AI data extraction accuracy rate was 94.84%, and errors were related mainly to localized Chinese clinical terminology. The study identified challenges pertaining to prompt design, prompt output consistency, and prompt output verification. Addressing limitations in terms of clinical terminology and output inconsistency entails integrating local terminology libraries and offering clear examples of output format. Output verification can be enhanced by probing the model's reasoning, assessing confidence on a scale, and highlighting relevant text snippets. These measures mitigate challenges that can impede our understanding of the model's decision-making process with regard to extensive free-text documents. Conclusions This research enriches academic discourse on LLMs in the context of clinical research and provides actionable recommendations for the practical implementation of LLMs for RWD extraction. By offering insights into LLM integration in the context of clinical research systems, the study contributes to the task of establishing a secure and efficient framework for digital clinical research. The continuous evolution and optimization of LLM technology are crucial for its seamless integration into the broader landscape of clinical research.

[目的]探讨胰岛素抵抗的替代标志物甘油三酯葡萄糖乘积(TyG)指数与脑卒中患病风险的关联.[方法]数据来源于2017-2018年"京津冀地区生活社区自然人群慢性病队列研究"天津现场基线调查.通过问卷调查、体格检查与实验室检查的方式收集数据,病例组与对照组根据性别相同、年龄±2岁进行1:1匹配.采用条件Logistic回归模型分析TyG指数与脑卒中患病风险的关联.[结果]共536例研究对象纳入分析,病例组TyG指数比对照组升高(P＜0.0001).多因素条件Logistic回归模型分析结果显示,与TyG指数＜8.38相比,8.38≤TyG指数＜8.67、8.67≤TyG指数＜9.10和TyG指数≥9.10时,脑卒中的风险[O R(95％CI)]分别为1.13(0.61,2.10)、1.47(0.78,2.74)和2.24(1.06,4.72).[结论]TyG指数是脑卒中患病的独立危险因素,随着TyG指数水平的升高,脑卒中患病风险逐渐增加.

目的 探索北京市密云区大气污染物短期暴露与呼吸系统疾病住院人数的关联.方法 收集北京市密云区医院2014年4月10日—2019年8月10日呼吸内科病房住院病例数据,北京市生态环境监测中心的每日大气污染物监测数据和中国气象数据网的每日气象数据.运用广义相加模型,调整星期几效应、节假日效应、温度、湿度、风速和时间长期趋势变量,分析密云区大气PM2.5、PM10、SO2、NO2、CO和O3-8 h与呼吸系统疾病住院人数的关联性.通过双污染物模型和敏感性分析,评价各污染物模型的稳健性.结果 PM10质量浓度在lag 7 d每上升1个四分位间距(IQR)时,呼吸系统疾病住院人数增加2.29％(95％CI:0.04％～4.60％);O3-8 h质量浓度在lag 0 d每上升1个IQR时,呼吸系统疾病住院人数增加5.80％(95％CI:0.06％～11.86％).在亚组分析中PM10在lag 3 d与男性的关联高于女性(P交互=0.006);CO在lag 3 d与80岁及以上人群的关联高于65～79岁人群(P交互=0.047).在双污染物模型中,O3-8 h在lag 0 d与呼吸系统疾病住院人数的关联在调整PM2.5、PM10、NO2、CO后仍存在统计学意义,提示O3暴露与呼吸系统疾病住院人数增加的正向关联具有稳健性.结论 O3-8 h短期暴露与呼吸系统疾病住院人数增加相关;PM10污染与呼吸系统疾病住院人数增加存在关联,且存在滞后效应.

目的 为优化医用耗材本市医疗保障信息业务编码贯标工作(无论医保内外均要对照核定国家医保编码),解决同一耗材医保编码、物价编码、耗材管理编码三码不统一问题.方法 我院以此次医用耗材贯标工作为契机,通过数据的分类对比、同类耗材关键词提取,收费价格及入库价格匹配,依托已有的耗材管理信息系统,使用一物三码合一的管理办法进行实践.结果 在不增加信息系统升级改造成本的前提下,完成现用的可单独收费医用耗材的国家医保编码贯标工作.结论 医用耗材种类多、用量大、对医保资金占用明显,在不增加信息系统升级成本的前提下,一物三码合一后,工作效率提高,没有附加人力成本投入,且更便于医院对医用耗材管控工作持续改进.增加医院收费环节的准确率,降低医保收费项目错收、漏收现象的发生,为医院有效节流.

目前大气污染日趋严重,已成为全球共同关注的环境问题.据世界卫生组织(WHO)估算,全球92％的人口生活处于空气质量超标地区.2015年,全球疾病、伤害和危险因素负担研究(GBD)已将空气污染确定为增加全球疾病负担的第4位危险因素.近30年来,随着我国城市化和工业化的快速推进,能源消耗飞速增加,我国已成为全球大气污染最严重的国家之一.

The assessment of the generalization of the strict hypertension definition in the 2017 ACC/AHA Hypertension Guideline from environmental condition remains sparse. The aims of this study are to investigate and compare the associations of ambient air pollution and traffic-related pollution (TRP) with hypertension defined by the different criteria. A total of 32,135 participants were recruited from the baseline survey of the CHCN-BTH in 2017. We defined hypertension as SBP/DBP ≥ 140/90 mmHg according to the hypertension guidelines in China, Japan, Europe and ISH (traditional criteria) and defined as SBP/DBP ≥ 130/80 mmHg according to the 2017 ACC/AHA Hypertension Guideline (strict criteria). A two-level generalized linear mixed models were applied to investigate the associations of air pollutants (i.e. PM2.5, SO2, NO2) and TRP with blood pressure (BP) measures and hypertension. Stratified analyses and two-pollutant models were also performed. The stronger associations of air pollutants were found in the hypertension defined by the strict criteria than that defined by the traditional criteria. The ORs per an IQR increase in PM2.5 were 1.17 (95% CI: 1.09, 1.25) for the strict criteria and 1.14 (95% CI: 1.06, 1.23) for the traditional criteria. The similar conditions were also observed for TRP. The above results were robust in both stratified analyses and two-pollutant models. Our study assessed the significance of the hypertension defined by the strict criteria from environmental aspect and called attention to the more adverse effects of air pollution and TRP on the earlier stage of hypertension.

目的:建立医院一站式女性盆底功能障碍(PFD)诊治中心,简化患者就诊流程,实现对盆底疾病及生殖整形患者的系统化和规范化管理,提高医院诊疗效率.方法:对医院产科和妇科现有医疗设备进行资源整合,对各设备房间重新调整和功能重新定位,通过盆底诊治一站式信息化管理平台,实现对盆底问诊、评估、诊断、治疗及随访的全病程管理.结果:2020年6月一站式女性PFD诊治中心投入使用后,就诊患者整体满意度由2019年的82.20％提升至2020年的91.4％,设备使用率提高.采用盆底诊治一站式信息化管理平台实现了多学科协作(MDT)诊疗模式,为患者制定最优和最科学的治疗方案,利用大数据长期追踪管理患者治疗效果.结论:医院一站式女性PFD诊治中心能够减少患者诊治中间的转科环节,便于PFD患者治疗,有效提升医疗设备使用效率.

Evidence regarding the effects of environmental factors on COVID-19 transmission is mixed. We aimed to explore the associations of air pollutants and meteorological factors with COVID-19 confirmed cases during the outbreak period throughout China. The number of COVID-19 confirmed cases, air pollutant concentrations, and meteorological factors in China from January 25 to February 29, 2020, (36 days) were extracted from authoritative electronic databases. The associations were estimated for a single-day lag as well as moving averages lag using generalized additive mixed models. Region-specific analyses and meta-analysis were conducted in 5 selected regions from the north to south of China with diverse air pollution levels and weather conditions and sufficient sample size. Nonlinear concentration–response analyses were performed. An increase of each interquartile range in PM 2.5 , PM 10 , SO 2 , NO 2 , O 3 , and CO at lag4 corresponded to 1.40 (1.37–1.43), 1.35 (1.32–1.37), 1.01 (1.00–1.02), 1.08 (1.07–1.10), 1.28 (1.27–1.29), and 1.26 (1.24–1.28) ORs of daily new cases, respectively. For 1°C, 1%, and 1 m/s increase in temperature, relative humidity, and wind velocity, the ORs were 0.97 (0.97–0.98), 0.96 (0.96–0.97), and 0.94 (0.92–0.95), respectively. The estimates of PM 2.5 , PM 10 , NO 2 , and all meteorological factors remained significantly after meta-analysis for the five selected regions. The concentration–response relationships showed that higher concentrations of air pollutants and lower meteorological factors were associated with daily new cases increasing. Higher air pollutant concentrations and lower temperature, relative humidity and wind velocity may favor COVID-19 transmission. Controlling ambient air pollution, especially for PM 2.5 , PM 10 , NO 2 , may be an important component of reducing risk of COVID-19 infection. In addition, as winter months are arriving in China, the meteorological factors may play a negative role in prevention. Therefore, it is significant to implement the public health control measures persistently in case another possible pandemic.

Genome-wide association studies suggest that there is a significant genetic susceptibility to salt sensitivity of blood pressure (SSBP), but it still needs to be verified in varied and large sample populations. We attempted to verify the associations between single-nucleotide polymorphisms (SNPs) in candidate genes and SSBP and to estimate their interaction with potential risk factors. A total of 29 candidate SNPs were genotyped in the 2,057 northern Han Chinese population from the Systems Epidemiology Study on Salt Sensitivity. A modified Sullivan's acute oral saline load and diuresis shrinkage test (MSAOSL-DST) was used to identify SSBP. A generalized linear model was conducted to analyze the association between SNPs and SSBP, and Bonferroni correction was used for multiple testing. Mediation analysis was utilized to explore the mediation effect of risk factors. Eleven SNPs in eight genes (PRKG1, CYBA, BCAT1, SLC8A1, AGTR1, SELE, CYP4A11, and VSNL1) were identified to be significantly associated with one or more SSBP phenotypes (P < 0.05). Four SNPs (PRKG1/rs1904694 and rs7897633, CYP4A11/rs1126742, and CYBA/rs4673) were still significantly associated after Bonferroni correction (P < 0.0007) adjusted for age, sex, fasting blood glucose, total cholesterol, salt-eating habit, physical activity, and hypertension. Stratified analysis showed that CYBA/rs4673 was significantly associated with SSBP in hypertensive subjects (P < 0.0015) and CYP4A11/rs1126742 was significantly associated with SSBP in normotensive subjects (P < 0.0015). Subjects carrying both CYBA/rs4673-AA and AGTR1/rs2638360-GG alleles have a higher genetic predisposition to salt sensitivity due to the potential gene co-expression interaction. Expression quantitative trait loci analysis (eQTL) suggested that the above positive four SNPs showed cis-eQTL effects on the gene expression levels. Mediation analysis suggested that several risk factors were mediators of the relation between SNP and SSBP. This study suggests that the genetic variants in eight genes might contribute to the susceptibility to SSBP, and other risk factors may be the mediators.

Background： The association between long-term air pollutants exposure with blood pressure and hypertension defined by 2017 American College of Cardiology (ACC)/American Heart Association (AHA) Hypertension Guideline is still conflicting. This study was designed to investigate the associations between long-term exposure to air pollutants, blood pressure and hypertension defined by Chinese and ACC/AHA guideline in Chinese adults. Methods: Our study was based on the baseline survey of the Cohort Study on Chronic Disease of Communities Natural Population in Beijing, Tianjin and Hebei (CHCN-BTH) from 2017 to 2019. A spatial statistical model was used to assessed three-year (2014-2016) average pollutant concentrations for PM 2.5 , and other pollutants concentration (PM 10 , SO 2 , NO 2 ) was assessed by data of air monitoring stations. Results: A total of 32,135 adults aged 18-80 years were included, each interquartile range (IQR) increment of PM 2.5 , PM 10 , SO 2 and NO 2 was associated with increases of 0.66mmHg (95%CI: 0.29, 1.03), 040mmHg (0.00, 0.81), 1.38mmHg (0.92, 1.84) and 0.54mmHg (0.16, 0.91) in SBP, respectively. SO 2 was associated with increases 0.42mmHg (0.11, 0.72) in DBP. PM 2.5 , PM 10 , SO 2 and NO 2 was associated with an 14% (Odds ratio [OR]:1.14, 95%CI:1.06-1.23), 6% (1.06, 1.00-1.13), 9% (1.09, 1.02-1.17) and 8% (1.08, 1.01-1.16) increase of hypertension defined by Chinese guideline. PM 2.5 and SO 2 was associated with 16% (1.166, 1.093-1.245) and 10% (1.10, 1.03-1.18) increase of hypertension defined by ACC/AHA guideline. Two-pollutants model, traffic-related pollution model and stratified analysis yielded similar results. Conclusions: We found that long-term exposure to PM 2.5 , NO 2 and SO 2 is associated with increase of blood pressure and hypertension defined by both Chinses and ACC/AHA guideline. PM 10 is associated with higher SBP and risk of hypertension defined by Chinese guideline.

Accumulating evidence suggested that long non-coding RNAs (lncRNAs) could play biological roles in cardiovascular diseases. We investigated whether lncRNAs can serve as biomarkers for salt sensitivity of blood pressure (SSBP). Participants were divided into salt-sensitive (SS) and salt-resistant (SR) ones by oral saline test. LncRNAs were tested by microarray (N = 20) and two-stage qRT-PCR (N = 89 and 228). We identified five differently expressed lncRNAs (lnc-IGSF3-1:1, SCOC-AS1, SLC8A1-AS1, KCNQ1OT1, and lnc-GNG-10–3:1) between SS and SR. In single-lncRNA analyses, lnc-IGSF3-1:1 displayed better diagnostic performance in hypertensive patients (AUC = 0.840), while SCOC-AS1 in normotensive (AUC = 0.810). In multi-lncRNA analyses, lnc-IGSF3-1:1 + SCOC-AS1 + SLC8A1-AS1 combination showed the best diagnostic performance in hypertensive (AUC = 0.853) and normotensive groups (AUC = 0.873). We constructed a lncRNA-mRNA-GO-KEGG-disease network by bioinformatic analysis; lnc-IGSF3-1:1 and SLC8A1-AS1 were identified as hub biomarkers. Our findings suggest that lnc-IGSF3-1:1, SCOC-AS1, and SLC8A1-AS1 may represent as genetic susceptible biomarkers for SSBP, and had different SS diagnostic performance in hypertensive patients and normotensive individuals.

The potential effect of long-term exposure to ambient air pollutants on low-grade systematic inflammation has seldom been evaluated taking indoor air pollution and self-protection behaviors on smog days into account. A total of 24,346 participants at baseline were included to conduct a cross-sectional study. The annual (2016) average pollutant concentrations were assessed by air monitoring stations for PM2.5, PM10, SO2, NO2, O3 and CO. Associations between annual ambient air pollution and low-grade systematic inflammation (hsCRP>3 mg/L) were estimated by generalized linear mixed models. Stratification analysis was also performed based on demographic characteristics, health-related behaviors and disease status. Annual ambient NO2 and O3 were all associated with low-grade systematic inflammation in single-pollutant models after adjusting for age, sex, blood lipids, blood pressure, lifestyle risk factors, cooking fuel, heating fuel and habits during smog days (NO2 per 10 μg/m3: OR = 1.057, P = 0.018; O3 per 10 μg/m3: OR = 0.953, P = 0.012). The 2-year and 3-year ozone concentrations were consistently associated with lower systematic inflammation (2-year O3 per 10 μg/m3: OR = 0.959, P = 0.004; 3-year O3 per 10 μg/m3: OR = 0.961, P = 0.014). In two-pollutant models, the estimated effects of annual NO2 and O3 on low-grade systematic inflammation remained stable. The effect size of annual pollutants on inflammation increased in participants without air-purifier usage (NO2 per 10 μg/m3: OR = 1.079, P = 0.009; O3 per 10 μg/m3: OR = 0.925, P = 0.001), while the association was null in the air-purifier usage group. Thus, long-term exposure to ambient NO2 and O3 was associated with low-grade systemic inflammation, and the results were generally stable after sensitivity analysis. The usage of air purifiers on smog days can modify the association between gaseous pollutants and systematic inflammation.

Background Large-scale epidemiological surveys focusing on characteristic differences in psychological and physical health conditions in Chinese adults are lacking. Objective To investigate the association of noncommunicable chronic diseases (NCDs) with depression, anxiety and stress in the Chinese general population. Methods A total of 13784 participants were recruited from the baseline survey of the Cohort Study on Chronic Disease of Communities Natural Population in Beijing, Tianjin and Hebei (CHCN-BTH) from 2017 to 2019. Sociodemographic characteristics, lifestyle and NCDs were assessed via questionnaire. Stress, anxiety and depression were assessed by the Depression-Anxiety-Stress Scale (DASS-21). The relationship of NCDs with psychological symptoms was determined through logistic regression analysis. Results Multivariate logistic regression analysis revealed that the prevalence of stress (OR = 1.640; 95% CI: 1.381-1.949), anxiety (OR = 1.654; 95% CI: 1.490-1.837) and depression (OR = 1.460; 95% CI: 1.286-1.658) symptoms were all significantly higher in patients with NCDs. Multimorbidities were associated with a higher risk of stress (OR = 2.310; 95% CI: 1.820-2.931), anxiety (OR = 2.119; 95% CI: 1.844-2.436) and depression (OR = 2.785; 95% CI: 1.499-2.126) than single NCDs. A course of disease within 1 year or more than 5 years also was associated with a higher risk. Limitations The cross-sectional design could not examine the causal link between psychological symptoms and NCDs. Conclusion Psychological symptoms were more prevalent among individuals with NCDs in the Chinese general population. This study suggests that more attention should be paid to the mental health problems of patients with NCDs.

BACKGROUND:The emergence of promising compounds to lower lipoprotein(a) [Lp(a)] has increased the need for a precise characterisation and comparability assessment of Lp(a)-associated cardiometabolic disease risk. This study aimed to evaluate the distribution of Lp(a) levels in a Chinese population and characterise the association with cardiometabolic diseases.METHODS:We assessed data from individuals from the Cohort Study on Chronic Diseases of the General Community Population in the Beijing-Tianjin-Hebei Region project. All Lp(a) measurements were performed in the same hospital. The cardiometabolic diseases considered were coronary heart disease (CHD), stroke, hypertension and type 2 diabetes (T2DM).RESULTS:A total of 25343 individuals were included in the study. The median level of Lp(a) was 11.9 mg/dl (IQR 5.9 to 23.7 mg/dl), and higher Lp(a) levels showed a significant concentration-dependent association with CHD risk. Individuals with Lp(a) levels lower than the 25th percentile were at increased risk of hypertension (OR: 1.15, 95% CI: 1.06-1.25) and T2DM (OR: 1.15, 95% CI: 1.03-1.28); however, Lp(a) levels were not significantly associated with stroke. The addition of Lp(a) levels to the prognostic model led to a marginal but significant C-index, integrated discrimination improvement and net reclassification improvement.CONCLUSIONS:In this large sample size study, we observed that elevated Lp(a) levels were significantly associated with CHD. Furthermore, we found that the lowest Lp(a) levels were also significantly associated with hypertension and T2DM. These results provide evidence for differential approaches to higher levels of Lp(a) in individuals with different cardiometabolic diseases.

Background: To evaluate the contributions of elevated lipoprotein(a) [Lp(a)] to the risk of coronary heart disease (CHD) in the general Chinese community population according to different lipid profiles. Methods: We recruited individuals aged over 18 years from the baseline survey of the Cohort Study on Chronic Disease of Communities Natural Population in Beijing, Tianjin and Hebei (CHCN-BTH) using a stratified, multistage cluster sampling method. Data were collected through questionnaire surveys, anthropometric measures and laboratory tests. Restricted cubic spline (RCS) functions, multivariate logistic regression, sensitivity analyses and stratified analyses were used to evaluate the association between Lp(a) and CHD. Results: A total of 25,343 participants were included, with 1,364 (5.38%) identified as having CHD. Elevated Lp(a) levels were linearly related to an increased risk of CHD (Poverall-association<0.0001 and Pnonlinear-association=0.8468). Multivariate logistic regression analysis indicated that subjects with Lp(a) >= 300 mg/L had a higher risk of CHD [OR (95% CI): 1.36 (1.17, 1.57)] than did individuals with Lp(a) <300 mg/L. Compared with individuals with Lp(a) <119.0 mg/L (<50th percentile), the ORs (95% CI) for CHD in the 51st-80th, 81st-95th and >95th percentiles were 1.07 (0.93, 1.23), 1.26 (1.07, 1.50) and 1.68 (1.30, 2.17), respectively (P for trend <0.0001). This association was also found among the subgroup of subjects without dyslipidemia, including those with normal total cholesterol (TC) (<6.2 mmol/L), triglycerides (TG) (<2.3 mmol/L), high-density lipoprotein cholesterol (HDL-C) (>= 1.0 mmol/L) and low-density lipoprotein cholesterol (LDL-C) (<4.1 mmol/L). Elevated Lp(a) and dyslipidemia significantly contributed to a higher risk of CHD with synergistic effects. Stratified analyses showed that elevated Lp(a) concentrations were significantly associated with an increased risk of CHD in the subgroups of individuals who were noncurrent drinkers, overweight individuals, individuals with hypertension, individuals who engaged in moderate physical activity, those without diabetes mellitus and individuals in Beijing and Tianjin. Conclusions: Elevated Lp(a) concentrations were linearly associated with a higher risk of CHD in the general Chinese community population, especially in normolipidemic subjects. Both dyslipidemia and elevated Lp(a) independently or synergistically contributed to the risk of CHD. Our results suggest that more attention should be paid to the levels of Lp(a) in normolipidemic subjects, which may be an early predictor of CHD.

Introduction: Personal lifestyle and air pollution are potential risk factors for major non-communicable diseases (NCDs). However, these risk factors have experienced dramatic changes in the Beijing–Tianjin–Hebei (BTH) region in recent years, and few cohorts have focused on identifying risk factors for major NCDs in this specific region. The current study is a large, prospective, long-term, population-based cohort study that investigated environmental and genetic determinants of NCDs in BTH areas. The results of this study may provide scientific support for efforts to develop health recommendations for personalized prevention. Methods: About 36,000 participants 18 years or older would be obtained by multistage, stratified cluster sampling from five cities for the baseline assessment. Participants underwent seven examinations primarily targeting respiratory and circulatory system function and filled out questionnaires regarding lifestyle behavior, pollutant exposure, medical and family history, medication history, and psychological factors. Biochemistry indicators and inflammation markers were tested, and a biobank was established. Participants will be followed up every 2 years. Genetic determinants of NCDs will be demonstrated by using multiomics, and risk prediction models will be constructed using machine learning methods based on a multitude of environmental exposure, examination data, biomarkers, and psychosocial and behavioral assessments. Significant spatial and temporal differentiation is well-suited to demonstrating the health determinants of NCDs in the BTH region, which may facilitate public health strategies with respect to disease prevention and survivorship-related aspects.

The majority of single-nucleotide polymorphism (SNP) association studies of salt sensitivity (SS) have focused on SNPs in protein-coding genes rather than on SNPs in noncoding RNAs. This study attempted to identify the association between whole blood microRNA (miRNA)-related SNPs and the risk of SS in a Han Chinese population. A case-control study of 762 individuals was performed. A modified Sullivan’s acute oral saline load and diuresis shrinkage test was used to assess SS. All SNPs were analysed by RT-PCR on a Sequenom Mass ARRAY Platform (Sequenom, San Diego, CA, USA). A genetic risk score (GRS) was used to evaluate the joint genetic effect. In total, 24 miRNA-related SNPs were genotyped, four of which (miR-1307-5p/rs11191676, miR-1307-5p/rs2292807, miR-145/rs41291957 and miR-4638-3p/rs6601178) were associated with both SS and salt sensitivity of blood pressure (SSBP) (p ≤ 0.05). MiR-382-5p/rs4906032 and miR-15b-5/rs10936201 were associated with SSBP. Weighted GRS showed that participants in the second, third and fourth quartiles had 1.760-fold (95% CI: 1.068-2.903), 2.450-fold (95% CI: 1.470-4.083) and 2.774-fold (95% CI: 1.680-4.582) increased risk of SS, respectively. Bioinformatics analysis indicated that these four SNP risk alleles may affect transcription factor binding and influence promoter activity. A total of six miRNA-related SNPs were found to be associated with SS or SSBP, and the presence of multiple risk alleles resulted in increased risk level.