Gaps exist concerning the associations of PM2.5-10, gaseous pollutants, and composite pollutants with the acute exacerbation of chronic obstructive pulmonary disease (AECOPD). The interaction effects of lifestyle factors, indoor air pollution, and meteorological conditions with air pollutants have been underexplored. This time-stratified case-crossover study was nested within the China Kadoorie Biobank cohort study of middle-aged and elderly participants from five urban and five rural areas in China spanning from 2004 to 2018. 10,712 participants were included, each with a mean of 2.3 episodes of AECOPD hospitalizations during the observation period. A composite air pollution score was derived through principal component analysis. Short-term exposure to particulate matter and NO2 was positively associated with hospital admissions for AECOPD, with the largest temperature- and humidity-adjusted odds ratio (95% confidence interval) of 1.101 (1.073, 1.129) at a lag of 1 day for per 1 standard deviation increase in air pollution score. The effect of O3 appeared to be conflicting. The associations were further corroborated by the self-controlled case-series design. Unfavorable body shapes, cold season, and low humidity could exacerbate the influence of air pollution. These findings reinforce the evidence of links between air pollution and AECOPD and implicate the management of body weight and cold and dry circumstances.

Plasma proteomics can provide a dynamic molecular readout of human health, but models that learn generalizable protein-expression patterns in population cohorts remain limited. Here we show that ProLM, a BERT-based plasma proteomics model pretrained on 15,499 relatively healthy UK Biobank participants, captures baseline protein-expression relationships and supports prediction of 16 common chronic diseases. After disease-specific fine-tuning, the ProLM-derived proteomic risk score outperformed the Age+Sex model for all 16 diseases, the cardiovascular disease (ASCVD) risk equation for 14 diseases and a 35-variable clinical PANEL score for 11 diseases. Model interpretation highlighted proteins including GDF15 whose expression changed more than 15 years before clinical diagnosis, and key findings were externally evaluated in the China Kadoorie Biobank. These results support plasma proteomics pretrained models as tools for early chronic-disease risk stratification, while prospective validation is needed before clinical implementation.

INTRODUCTION:Cardiovascular-kidney-metabolic (CKM) syndrome and depressive disorder represent major public health burdens. While associations between depression and individual components of CKM syndrome have been established, the relationship between depression and CKM syndrome as an integrated clinical construct remains poorly understood. METHODS:Data from the China Health and Retirement Longitudinal Study (CHARLS) were used, including 8,088 participants in cross-sectional analyses and 1,803 in longitudinal analyses. CKM syndrome was classified according to the American Heart Association (AHA) staging criteria, and depressive symptoms were assessed using the 10-item Center for Epidemiologic Studies Depression Scale (CES-D-10). The association between CKM stage and depressive symptoms was evaluated using ordinary least squares regression models with five levels of covariate adjustment. Subgroup analyses and interaction tests were conducted to investigate interaction effects across different populations. RESULTS:Higher CKM stages were significantly associated with increased depressive symptom severity. In the cross-sectional analysis (2011), mean CES-D-10 scores were 8.6 ± 6.4, 8.6 ± 6.3, 8.1 ± 6.2, and 10.7 ± 6.9 for the total population and CKM stages 0-1, 2-3, and 4, respectively. Scores in stage 4 exceeded the threshold for severe depressive symptoms and were significantly higher than those in other stages (p < 0.001). Subgroup analyses further confirmed the robustness of these findings. In longitudinal analyses, progression in CKM stage over a 4-year period was independently associated with an increase in CES-D-10 scores in the fully adjusted model (β = 0.31, 95% CI: 0.07-0.54). CONCLUSIONS:CKM syndrome is significantly associated with depressive symptoms, especially in stage 4. There is a positive relationship between CKM progression and depressive symptom severity, highlighting the need for integrated physical and mental health care for CKM patients.

BACKGROUND:Understanding the short-term effects of temperature on physical activity and sedentary behavior, as well as adaptation patterns under extreme temperatures, will help China and other countries with similar climatic conditions implement targeted interventions to promote physical activity and enhance public health. METHODS:During 2020 and 2021, 22,511 China Kadoorie Biobank participants in the 3rd resurvey consented to wear an Axivity AX3 wrist-worn triaxial accelerometer for 7 consecutive days to assess their movement behaviors. To investigate the short-term effects of daytime temperature on physical activity and sedentary behavior, we used distributed lag nonlinear models combined with generalized estimating equations. The final analysis included 110,553 days of acceleration data from 19,977 participants from 10 Chinese cities. RESULTS:Temperature exhibited an inverted U-shaped association with overall activity and moderate-to-vigorous intensity physical activity (MVPA), with a peak at 26°C. In contrast, light-intensity physical activity (LIPA) showed an inverted N-shaped relationship with temperature, while sedentary behavior gradually increased. The maximum change in overall activity was a decrease of 13.33% (95% CI: 11.54% to 14.93%, cumulative lag 0 days) and 4.50% (95% CI: 2.65% to 6.32%, cumulative lag 4 days) under extremely low and high temperatures, respectively. Males and manual workers exhibited greater variability in both overall activity and MVPA across the temperature range. CONCLUSIONS:Our findings highlight the need for targeted interventions to mitigate the adverse effects of temperature on physical activity, with strategies tailored to specific groups, particularly sex and occupation.

Gaps concerning general adiposity and chronic obstructive pulmonary disease (COPD) are delaying policies for weight interventions in COPD prevention, especially adiposity in early adulthood and weight changes during adulthood. Based on the China Kadoorie Biobank, a prospective cohort between 2004–2008 covering 5 urban and 5 rural areas, we included 138,764 males and 194,159 females aged 35 70 years. Weight change was defined as the difference between directly measured weight at baseline and self-reported weight at age 25. Incident COPD events were followed-up until the end of 2018. Cox proportional hazard models were conducted to estimate the hazard ratios (HRs) and 95

Metabolic dysfunction associated steatotic liver disease (MASLD) is a pressing global health issue with limited treatment options. Chinese sweet leaf tea (CSLT), rich in polyphenols, shows promise in addressing MASLD due to its anti-inflammatory, obesity-reducing, and metabolic-regulating properties. This study aimed to explore the therapeutic potential of CSLT polyphenols for MASLD treatment. A comprehensive approach combining bioinformatics, network pharmacology, molecular docking, high-throughput sequencing, and experimental validation was employed. CSLT extracts were screened for active compounds, and potential targets associated with MASLD were predicted. A protein-protein interaction network was constructed to identify key regulators of lipid metabolism. Molecular docking studies validated interactions between core polyphenols and MASLD-related targets. In vitro studies using HepG2 cells and in vivo studies in a high-fat diet-induced rat model were conducted to assess the efficacy of polyphenol-rich CSLT extract (PE-CSLT) in ameliorating MASLD symptoms. A total of Eighty-two chemical constituents were initially identified in CSLT. Twenty-six active compounds were screened in CSLT extracts, targeting one hundred and six proteins related to twenty MASLD-associated genes. PE-CSLT demonstrated significant efficacy in reducing body weight gain, serum lipid levels, and liver fat accumulation in MASLD rats. Gene expression analysis revealed modulation of key metabolic regulators, including SREBP1, ACACA, AMPK, and PPARα. Molecular docking confirmed strong binding of eleven PE-CSLT components to these targets. Our findings highlight the therapeutic potential of PE-CSLT for MASLD, providing a scientific basis for its development as a novel drug. This study underscores the promise of natural products in modern medicinal practices and emphasizes the need for further clinical evaluation of PE-CSLT in MASLD management.

This study aims to investigate the predictive factors for postoperative atrial fibrillation (POAF) following aortic valve replacement (AVR) and evaluate the preventive effect of combined atorvastatin and metoprolol therapy on POAF. This study employed a mixed design of retrospective cohort analysis and prospective randomized controlled trial, including 268 patients who underwent isolated AVR from January 1, 2022, to March 31, 2024. The 168 patients from January 1, 2022, to May 31, 2023, were analyzed for POAF predictive factors, while 100 patients from June 1, 2023, were included in the prospective trial. The intervention group (n = 50) received combined atorvastatin and metoprolol treatment starting 7 days before surgery. Multivariate logistic regression analysis identified age (OR = 1.12, 95

BACKGROUND:Unhealthy lifestyle behaviors, leading to systemic metabolic disturbances, are significantly linked to the risk of late-onset asthma. However, the underlying metabolism-related mechanisms remain unclear. OBJECTIVE:We sought to identify lifestyle-related metabolites and assess their predictive value for incident asthma. METHODS:Using nuclear magnetic resonance metabolomics data from the UK Biobank population (ages 40-69), plasma metabolites associated with healthy lifestyle scores were identified through multiple linear regression. Cox proportional hazards regression was used to further screen metabolites linked to late-onset asthma risk. Elastic net regularization selected critical metabolites for developing an asthma risk prediction model, incorporating conventional clinical characteristics and lifestyle factors. A metabolic score based on nonzero regularization coefficients was derived, and its association with asthma risk was evaluated through survival analysis. Models and metabolic score performance were validated in unused internal UK Biobank participants and an external China Kadoorie Biobank cohort. RESULTS:Among 198,607 participants (mean age 56.4 years), 159 plasma metabolites were significantly related to healthy lifestyle scores, 103 of which were associated with incident asthma risk. Nine metabolites were selected and incorporated into the asthma risk prediction model, significantly improving its predictive performance (area under the curve 0.812 vs 0.758). Individuals with an unfavorable metabolic signature exhibited a 77.0% increased risk (hazard ratio 1.770, 95% CI 1.634-1.918) of developing asthma compared with individuals with a favorable metabolic signature, with a stronger effect observed in women (hazard ratio 1.914, 95% CI 1.729-2.118). The results for the predictive model and metabolic score were confirmed in both internal and external validations. CONCLUSIONS:Multiple lifestyle-related metabolites are associated with late-onset asthma risk and can help stratify asthma risk, particularly among women.

Background:Observational studies have shown that the correlation between neurodegenerative diseases and colorectal cancer (CRC) remains controversial. Therefore, this study aimed to verify the causal association between these two diseases. Methods:Mendelian randomization (MR) analysis was used to assess the causal relationships between five major neurodegenerative diseases and CRC. Multivariable MR (MVMR) analysis was conducted to assess the direct causal effect of neurodegenerative diseases on CRC. Colocalization and pathway enrichment analyses were conducted to further elucidate our results. Sensitivity analysis was conducted to assess the robustness of the results. Results:Genetically predicted Alzheimer's disease (AD) nominally increased CRC risk (OR = 1.0620, 95%CI = 1.0127-1.1136, P = 0.013). There was no causal effect of genetically predicted CRC on neurodegenerative diseases. Furthermore, we demonstrated that genetically predicted AD marginally increased colon cancer risk (OR = 1.1621, 95%CI = 1.0267-1.3153, P = 0.017). Genetically predicted Lewy body dementia (LBD) had a significant causal effect on the increasing risk of colon cancer (IVW OR = 1.1779, 95%CI = 1.0694-1.2975, P = 0.001). MVMR indicated that effect of AD on colon cancer was driven by LBD, type 2 diabetes, body mass index, low-density lipoprotein cholesterol, high-density lipoprotein cholesterol, triglyceride, total cholesterol (TC), processed meat consumption, smoking, alcohol consumption, and educational attainment, whereas the effect of LBD on colon cancer was only influenced by TC. Colocalization and pathway enrichment analysis suggested that LBD and colon cancer possibly shared causal variants (nearby gene APOE), and ERBB4 signaling and lipid metabolism may mediate the causal association between LBD and colon cancer. Sensitivity analysis confirmed the reliability of our findings. Conclusions:Our study demonstrated that genetic vulnerabilities to AD nominally increased the overall risk of CRC and colon cancer. Genetically predicted LBD indicated an elevated risk of colon cancer, potentially linked to ERBB4 signaling and lipid metabolism.

Several observational studies have revealed an association between autoimmune diseases (AIDs) and colorectal cancer (CRC), although their causal association remained controversial. Therefore, our study used a two-sample Mendelian randomization (MR) analysis to verify the causal association between AIDs and CRC. We employed three common MR approaches, including inverse variance weighted (IVW), weighted median, and MR-Egger methods, to assess the causal association between type 1 diabetes (T1D), systemic lupus erythematosus, rheumatoid arthritis, psoriasis, multiple sclerosis, juvenile idiopathic arthritis, celiac disease, and primary sclerosing cholangitis (PSC) and CRC. The reverse MR analysis was performed to assess the possibility of reverse causation. To evaluate the validity of the analysis, we also performed sensitivity analysis, such as the heterogeneity test, the horizontal pleiotropy test, and the leave-one-out sensitivity analysis, and validated the results in the validation cohort. Our results showed that genetically predicted T1D was nominally associated with a lower risk of CRC (IVW OR = 0.965, 95% CI = 0.939–0.992, P = 0.012). However, genetic susceptibility to psoriasis nominally increased the risk of CRC (IVW OR = 1.026, 95% CI = 1.002–1.050, P = 0.037). Genetically predicted PSC had a significant causal effect on the increasing risk of CRC (IVW OR = 1.038, 95% CI = 1.016–1.060, P = 5.85 × 10−4). Furthermore, the MR analysis between PSC and the CRC validation cohort indicated consistent results. We found no causal association between genetically predicted other five AIDs and CRC (P > 0.05). The results of reverse MR analysis showed that genetically predicted CRC had no causal effect on T1D, psoriasis, and PSC (P > 0.05). The sensitivity analysis demonstrated that the results of the MR analysis were reliable. Our findings help to understand the causal association between AIDs and CRC, which deserves further investigation.

There is no consensus on the cause and effect of systemic chronic inflammation (SCI) regarding chronic obstructive pulmonary disease (COPD). The impact of second-hand smoke (SHS) on COPD has reached inconsistent conclusions. The China Kadoorie Biobank cohort was followed up from the 2004–08 baseline survey to 31 December 2018. Among the selected 445,523 participants in the final analysis, Cox and linear regressions were performed to estimate hazard ratios (HRs) and 95

Introduction Cohort evidence of the association of diabetes mellitus (DM) with chronic kidney disease (CKD) is limited. Previous studies often describe patients with kidney disease and diabetes as diabetic kidney disease (DKD) or CKD, ignoring other subtypes. The present study aimed to assess the prospective association of diabetes status (no diabetes, pre-diabetes, screened diabetes, previously diagnosed controlled/uncontrolled diabetes with/without antidiabetic treatment) and random plasma glucose (RPG) with CKD risk (including CKD subtypes) among Chinese adults.Research design and methods The present study included 472 545 participants from the China Kadoorie Biobank, using baseline information on diabetes and RPG. The incident CKD and its subtypes were collected through linkage with the national health insurance system during follow-up. Cox regression models were used to calculate the HR and 95% CI.Results During 11.8 years of mean follow-up, 5417 adults developed CKD. Screened plus previously diagnosed diabetes was positively associated with CKD (HR=4.52, 95% CI 4.23 to 4.83), DKD (HR=33.85, 95% CI 29.56 to 38.76), and glomerulonephritis (HR=1.66, 95% CI 1.40 to 1.97). In those with previously diagnosed diabetes, participants with uncontrolled diabetes represented higher risks of CKD, DKD, and glomerulonephritis compared with those with controlled RPG. The risk of DKD was found to rise in participants with pre-diabetes and increased with the elevated RPG level, even in those without diabetes.Conclusions Among Chinese adults, diabetes was positively associated with CKD, DKD, and glomerulonephritis. Screen-detected and uncontrolled DM had a high risk of CKD, and pre-diabetes was associated with a greater risk of DKD, highlighting the significance of lifelong glycemic management.

Background This study aimed to: 1) assess the associations of biological age acceleration based on Klemera and Doubal's method (KDM-AA) with long-term risk of all-cause mortality; and 2) compare the association of KDM-AA with all-cause mortality among participants potentially at different stages of the cardiovascular disease (CVD) continuum. Methods The present study was based on a subpopulation of the China Kadoorie Biobank, with baseline survey during 2004-08. A total of 12,377 participants free of ischemic heart disease, stroke, or cancer at baseline were included, in which 8180 participants were identified to develop major coronary event (MCE), ischemic stroke (IS), intracerebral hemorrhage (ICH) or subarachnoid hemorrhage (SAH), and 4197 remained free of these cardiovascular diseases before 1 January 2014. These participants were followed up until 1 Jan 2018. KDM-AA was calculated by regressing biological age measurement, which was constructed based on baseline 16 physical and 9 biochemical markers using Klemera and Doubal's method, on chronological age. We estimated the associations of KDM-AA with the mortality risk using the hazard ratio (HR) and 95% confidence interval (CI) from Cox proportional hazard models. We assessed discrimination performance by Harrell's C-index and net reclassification index (NRI). Findings The participants who developed MCE (mean KDM-AA = 0.1 year, standard deviation [SD] = 1.6 years) or ICH/SAH (0.3 +/- 1.5 years) during subsequent follow-up showed accelerated aging at baseline compared to those of IS (0.0 +/- 1.2 years) and control (-0.3 +/- 1.3 years) groups. The KDM-AA was positively associated with long-term risk of all-cause mortality (HR = 1.20; 95% CI: 1.17, 1.23), and the association was robust for participants potentially at different stages of the CVD continuum. Adding KDM-AA improved mortality prediction compared to the model only with sociodemographic and lifestyle factors in whole participants, with the Harrell's C-index increasing from 0.813 (0.807, 0.819) to 0.821 (0.815, 0.826) (NRI = 0.011; 95% CI: 0.003, 0.019). Interpretation In this middle-aged and elderly Chinese population, the KDM-AA is a promising measurement for biological age, and can capture the difference in cardiovascular health and predict the risk of all-cause mortality over a decade. Copyright (c) 2023 The Author(s). Published by Elsevier B.V.

Background DNA methylation clocks emerged as a tool to determine biological aging and have been related to mortality and age-related diseases. Little is known about the association of DNA methylation age (DNAm age) with coronary heart disease (CHD), especially in the Asian population. Results Methylation level of baseline blood leukocyte DNA was measured by Infinium Methylation EPIC BeadChip for 491 incident CHD cases and 489 controls in the prospective China Kadoorie Biobank. We calculated the methylation age using a prediction model developed among Chinese. The correlation between chronological age and DNAm age was 0.90. DNA methylation age acceleration (Δage) was defined as the residual of regressing DNA methylation age on the chronological age. After adjustment for multiple risk factors of CHD and cell type proportion, compared with participants in the bottom quartile of Δage, the OR (95% CI) for CHD was 1.84 (1.17, 2.89) for participants in the top quartile. One SD increment in Δage was associated with 30% increased risk of CHD (OR = 1.30; 95% CI 1.09, 1.56; Ptrend = 0.003). The average number of cigarette equivalents consumed per day and waist-to-hip ratio were positively associated with Δage; red meat consumption was negatively associated with Δage, characterized by accelerated aging in those who never or rarely consumed red meat (all P < 0.05). Further mediation analysis revealed that 10%, 5% and 18% of the CHD risk related to smoking, waist-to-hip ratio and never or rarely red meat consumption was mediated through methylation aging, respectively (all P for mediation effect < 0.05). Conclusions We first identified the association between DNAm age acceleration and incident CHD in the Asian population, and provided evidence that unfavorable lifestyle-induced epigenetic aging may play an important part in the underlying pathway to CHD.

Background The associations between blood lipids and DNA methylation have been investigated in epigenome-wide association studies mainly among European ancestry populations. Several studies have explored the direction of the association using cross-sectional data, while evidence of longitudinal data is still lacking. Results We tested the associations between peripheral blood leukocytes DNA methylation and four lipid measures from Illumina 450 K or EPIC arrays in 1084 participants from the Chinese National Twin Registry and replicated the result in 988 participants from the China Kadoorie Biobank. A total of 23 associations of 19 CpG sites were identified, with 4 CpG sites located in or adjacent to 3 genes (TMEM49, SNX5/SNORD17 and CCDC7) being novel. Among the validated associations, we conducted a cross-lagged analysis to explore the temporal sequence and found temporal associations of methylation levels of 2 CpG sites with triglyceride and 2 CpG sites with high-density lipoprotein-cholesterol (HDL-C) in all twins. In addition, methylation levels of cg11024682 located in SREBF1 at baseline were temporally associated with triglyceride at follow-up in only monozygotic twins. We then performed a mediation analysis with the longitudinal data and the result showed that the association between body mass index and HDL-C was partially mediated by the methylation level of cg06500161 (ABCG1), with a mediation proportion of 10.1%. Conclusions Our study indicated that the DNA methylation levels of ABCG1, AKAP1 and SREBF1 may be involved in lipid metabolism and provided evidence for elucidating the regulatory mechanism of lipid homeostasis.

ObjectiveThe metabolic mechanism of harmful effects of red meat on the cardiovascular system is still unclear. The objective of the present study is to investigate the associations of self-reported red meat consumption with plasma metabolic markers, and of these markers with the risk of cardiovascular diseases (CVD).MethodsPlasma samples of 4,778 participants (3,401 CVD cases and 1,377 controls) aged 30–79 selected from a nested case-control study based on the China Kadoorie Biobank were analyzed by using targeted nuclear magnetic resonance to quantify 225 metabolites or derived traits. Linear regression was conducted to evaluate the effects of self-reported red meat consumption on metabolic markers, which were further compared with the effects of these markers on CVD risk assessed by logistic regression.ResultsOut of 225 metabolites, 46 were associated with red meat consumption. Positive associations were observed for intermediate-density lipoprotein (IDL), small high-density lipoprotein (HDL), and all sizes of low-density lipoprotein (LDL). Cholesterols, phospholipids, and apolipoproteins within various lipoproteins, as well as fatty acids, total choline, and total phosphoglycerides, were also positively associated with red meat consumption. Meanwhile, 29 out of 46 markers were associated with CVD risk. In general, the associations of metabolic markers with red meat consumption and of metabolic markers with CVD risk showed consistent direction.ConclusionsIn the Chinese population, red meat consumption is associated with several metabolic markers, which may partially explain the harmful effect of red meat consumption on CVD.

Background: Few studies have assessed the role of individual plasma cholesterol levels in the association between egg consumption and the risk of cardiovascular diseases. This research aims to simultaneously explore the associations of self-reported egg consumption with plasma metabolic markers and these markers with the risk of cardiovascular disease (CVD). Methods: Totally 4778 participants (3401 CVD cases subdivided into subtypes and 1377 controls) aged 30–79 were selected based on the China Kadoorie Biobank. Targeted nuclear magnetic resonance was used to quantify 225 metabolites in baseline plasma samples. Linear regression was conducted to assess associations between self-reported egg consumption and metabolic markers, which were further compared with associations between metabolic markers and CVD risk. Results: Egg consumption was associated with 24 out of 225 markers, including positive associations for apolipoprotein A1, acetate, mean HDL diameter, and lipid profiles of very large and large HDL, and inverse associations for total cholesterol and cholesterol esters in small VLDL. Among these 24 markers, 14 were associated with CVD risk. In general, the associations of egg consumption with metabolic markers and of these markers with CVD risk showed opposite patterns. Conclusions: In the Chinese population, egg consumption is associated with several metabolic markers, which may partially explain the protective effect of moderate egg consumption on CVD. Funding: This work was supported by the National Natural Science Foundation of China (81973125, 81941018, 91846303, 91843302). The CKB baseline survey and the first re-survey were supported by a grant from the Kadoorie Charitable Foundation in Hong Kong. The long-term follow-up is supported by grants (2016YFC0900500, 2016YFC0900501, 2016YFC0900504, 2016YFC1303904) from the National Key R&D Program of China, National Natural Science Foundation of China (81390540, 81390541, 81390544), and Chinese Ministry of Science and Technology (2011BAI09B01). The funders had no role in the study design, data collection, data analysis and interpretation, writing of the report, or the decision to submit the article for publication.

BACKGROUND There are concerns that Asian patients respond differently to some medications. This study evaluated the efficacy and safety of evolocumab among Asian vs. other subjects in the FOURIER trial, which randomized stable atherosclerosis patients to receive either evolocumab or placebo.Methods and Results:Effects of adding evolocumab vs. placebo to background statin therapy on low-density lipoprotein cholesterol (LDL-C) reductions, cardiovascular outcomes, and adverse events were compared among 27,564 participants with atherosclerotic disease, according to self-reported Asian (n=2,723) vs. other (n=24,841) races followed for a median of 2.2 years in the FOURIER trial. The primary endpoint was a composite of cardiovascular death, myocardial infarction, stroke, hospitalization for unstable angina, or coronary revascularization. At randomization, Asians had slightly lower LDL-C (median 89 [IQR 78-104] mg/dL vs. 92 [80-109] mg/dL; P<0.001) and were much less likely to be on a high-intensity statin (33.3% vs. 73.3%; P<0.001). Evolocumab lowered LDL-C more in Asians than in others (66% vs. 58%; P<0.001). The effect of evolocumab on the primary endpoint was similar in Asians (HR, 0.79; 95% CI, 0.61-1.03) and others (HR, 0.86; 95% CI, 0.79-0.93; P interaction=0.55). There was no excess of serious adverse events with evolocumab among Asians over others. CONCLUSIONS Use of evolocumab robustly lowers LDL-C and is equally efficacious in lowering the risk of cardiovascular events and safe in Asians as it is in others.

Background The relationship between educational attainment and ischaemic heart disease (IHD) is limited in evidence in middle-income countries like China. Exploring lifestyle-related mediators, which might be not universal between socioeconomic status and health outcomes in diverse regions, can contribute to interventions targeted at the Chinese to narrow the educational gap in IHD. Methods Based on the China Kadoorie Biobank of 489 594 participants aged 30–79 years who did not have heart disease or stroke at baseline, this study examined the association of educational attainment with IHD. Total IHD cases were further divided into acute myocardial infarction (AMI) cases and non-AMI cases. The Cox proportional hazard model was performed to estimate the HRs and 95% CIs for mortality and incidence of IHD. Logistic regression was used to estimate the ORs and 95% CIs for case fatality. Results During the median follow-up period of 11.1 years, this study documented 45 946 (6668) incident IHD (AMI) cases and 5948 (3689) deaths altogether. Lower educational attainment was associated with increased risk of incident AMI as well as death and fatality of total IHD including its subtypes (p trend <0.001). Although the risk of incident non-AMI was greater for participants with higher levels of education in the whole population (p trend <0.001), an inverse association of education with its incidence was found in participants from <50 years age group and rural areas. Smoking and dietary habits were the two most potent mediating factors in the associations of education with mortality and AMI incidence; whereas, physical activity was the major mediating factor for non-AMI incidence in the whole population. Discussion Interventions targeting unhealthy lifestyles are ideal ways to narrow the educational gap in IHD while solving ‘upstream’ causes of health behaviours might be the most fundamental ones.

Objective To simultaneously explore the associations of self-reported egg consumption with plasma metabolic markers and these markers with CVD risk. Methods Totally 4,778 participants (3,401 CVD cases subdivided into subtypes and 1,377 controls) aged 30-79 were selected from a nested case-control study based on the China Kadoorie Biobank. Targeted nuclear magnetic resonance was used to quantify 225 metabolites and derived traits in baseline plasma samples. Linear regression was conducted to assess associations between self-reported egg consumption and metabolic markers, which were further compared with associations between metabolic markers and CVD risk. Results Egg consumption was associated with 24 out of 225 markers, including positive associations for apolipoprotein A1, acetate, mean HDL diameter, and lipid profiles of very large and large HDL, and inverse associations for total cholesterol and cholesterol esters in small VLDL. Among these 24 markers, 14 of them were associated with CVD risk. In general, the associations of metabolic markers with egg consumption and of metabolic markers with CVD risk showed opposite patterns. Conclusions In the Chinese population, egg consumption is associated with several metabolic markers, which may partially explain the protective effect of egg consumption on CVD.