Background:Severe delayed encephalopathy after acute carbon monoxide poisoning (s-DEACMP) is a disabling complication associated with substantial long-term neurological impairment, yet reliable predictors for risk stratification during acute hospitalization remain limited. This study aimed to identify predictors associated with s-DEACMP and to develop a preliminary predictive model. Methods:In this retrospective single-center cohort study, 200 patients with acute carbon monoxide poisoning (ACMP) admitted between 2017 and 2024 were analyzed. Patients were categorized into DEACMP (n = 140) and non-DEACMP (n = 60) groups; the DEACMP group was further stratified into severe (s-DEACMP, n = 97) and mild-to-moderate (m-DEACMP, n = 43) subgroups based on Activities of Daily Living scores assessed at peak disease severity during hospitalization. Clinical characteristics were compared between the s-DEACMP group and a combined control group (n-DEACMP + m-DEACMP). Independent predictors were identified using multivariate logistic regression. A nomogram was constructed and internally validated using receiver operating characteristic (ROC) curves, calibration analysis, and decision curve analysis (DCA). Results:Patients with s-DEACMP were significantly older and had longer duration of disturbance of consciousness, higher prevalence of hypertension and hyperhomocysteinemia, elevated D-dimer levels, and lower serum albumin concentrations compared with controls (all P < 0.05). Multivariate analysis identified age >40 years (OR = 31.90, 95% CI = 3.93-259.14), disturbance of consciousness >24 h (OR = 3.06, 95% CI = 1.58-5.94), hypertension (OR = 1.99, 95% CI = 1.02-3.90), and hyperhomocysteinemia (OR = 2.57, 95% CI = 1.24-5.31) as factors independently associated with s-DEACMP. The nomogram demonstrated acceptable discrimination and calibration. Conclusion:The proposed nomogram may assist in identifying patients at increased risk for s-DEACMP during acute hospitalization. External multicenter validation is required before broader clinical application.

ABSTRACT Hypertension is a leading chronic disease globally, with rising prevalence in China. A considerable number of hypertension patients struggle to achieve target blood pressure levels with monotherapy alone. The bisoprolol/amlodipine FDC shows promise for blood pressure control and adherence, whereas clinical evidence for Chinese patients is limited. This prospective study evaluated efficacy and safety in patients inadequately controlled by free combination of bisoprolol/metoprolol and amlodipine. In a prospective trial spanning 12 weeks across multiple centers, 78 patients were enrolled who failed 4‐week free combinations (e.g., bisoprolol 2.5 mg/day or metoprolol formulations + amlodipine/levamlodipine). Inclusion required office systolic blood pressure (SBP) ≥140 mmHg and/or office diastolic blood pressure (DBP) ≥90 mmHg, with resting heart rate (RHR) ≥70 beats per minute (bpm). Assessments included office BP (OBP) at 4th, 8th, 12th weeks; home BP (HBP) at 0, 1st, 5th, 9th weeks; ambulatory BP at 0, 11 weeks; and time in target range (TTR) at 12 weeks. Patients averaged 49±12.4 years, 73.1% male. After 1 week, home SBP decreased by 6.6 mmHg, DBP by 4.2 mmHg, RHR by 5.5 bpm (all p < 0.0001). OBP significantly reduced at 4 and 8 weeks. By 12 weeks, office SBP dropped by 13.9 mmHg, DBP by 11.2 mmHg, and RHR by 11.3 bpm (all p < 0.0001). The mean Clinic TTR significantly increased by 47.9 percentage points (from 31.3% to 79.2%, p < 0.0001), with the proportion of patients achieving Clinic TTR >70% rising from 19.2% to 66.7% ( p < 0.0001). At 11 weeks, ambulatory SBP and HR fell substantially ( p < 0.001), and Ambulatory TTR also significantly improved across 24‐hour, daytime, and nighttime periods. Bisoprolol/amlodipine FDC is safe and effective for Chinese patients with hypertension not adequately controlled by free combinations of bisoprolol/metoprolol and amlodipine.

The success of mRNA vaccines has established lipid nanoparticles (LNPs) as a clinically validated delivery platform, yet their application to pulmonary therapeutics presents formidable challenges. This review systematically summarizes the mechanisms, delivery methods, key challenges, safety considerations, and translational gaps associated with mRNA-LNP therapeutics for pulmonary disorders. It surveys LNP-mediated delivery to pulmonary cell populations, distinguishing readily accessible targets (such as alveolar type II cells, bronchial epithelia, and macrophages) from refractory cell types (including T cells and rare fibroblast subsets). The evolution of LNPs is traced through three generations: from initial hepatic-optimized carriers, to lung-tropic selective organ targeting (SORT) formulations, and onward to contemporary precision-engineered aerosol systems. These advances have enabled diverse mRNA-based therapeutic modalities, encompassing protein replacement, gene editing, cell reprogramming, and cancer immunotherapy, each of which is examined with emphasis on their distinct mechanisms of action and safety profiles. Lung cancer represents a particularly intractable therapeutic challenge. Stromal barriers and tumor-associated macrophages render most lung-selective LNPs ineffective in orthotopic models, necessitating development strategies decoupled from those for non-malignant indications. Significant translational gaps persist, including a limited understanding of inhaled delivery barriers, insufficient long-term safety data for repeated dosing regimens, and the poor predictive value of healthy rodent models. While AI-guided lipid discovery, biodegradable formulations, and active targeting strategies offer considerable promise, clinical success will demand rigorous validation in disease-relevant preclinical models.

Functional outcomes after acute ischemic stroke vary substantially among patients with similar neurological deficit severity, suggesting that factors beyond acute injury burden contribute to recovery. Metabolic–inflammatory dysregulation represents a chronic host condition that may influence the poststroke recovery processes. Whether such background vulnerability modifies stroke prognosis across different levels of baseline neurological severity remains unclear. We conducted a single-center retrospective cohort study including 1,017 consecutive patients with acute ischemic stroke admitted within 24 h of symptom onset. The C-reactive protein–triglyceride glucose index (CTI), calculated using a previously published logarithmic formula incorporating hs-CRP, triglycerides, and fasting blood glucose, was categorized into quartiles. The primary outcome was poor functional outcome at 90 days (modified Rankin Scale score 3–6). Multivariable logistic regression models with sequential adjustment were applied. Potential interaction between CTI and baseline stroke severity was evaluated using multiplicative interaction terms between CTI and admission National Institutes of Health Stroke Scale (NIHSS). Overall, 423 patients (41.6

ABSTRACT Background Predicting the prognosis of patients with acute cerebral infarction (ACI) is crucial for clinical decision‐making and personalized treatment. However, existing models often lack the comprehensive integration of clinical and biological indicators necessary for accurate and interpretable predictions. This study aims to develop and validate a predictive model using a combination of clinical assessments and inflammatory biomarkers to improve the prognostication of ACI patients. Methods This real‐world, retrospective cohort study was conducted at Luhe Hospital, Beijing, and included 1,017 ACI patients admitted within 24 h of symptom onset. The dataset was randomly split into a training set (80%) and a validation set (20%). Twelve machine learning models were developed and evaluated, with the optimal model and feature set selected based on comprehensive performance metrics. To enhance interpretability, the Shapley Additive exPlanations (SHAP) method was employed to quantify and visualize the contribution of each feature to the model's predictions. Results The final model, utilizing the Logistic Regression (LR) algorithm, incorporated six key features: NIHSS at 24 h (NIHSS_24 h), NIHSS_change, D‐dimer, neutrophil count (N), lymphocyte percentage at 24 h (L_pct_24 h), and length of stay (LOS). NIHSS_24 h emerged as a critical early prognostic indicator, effectively predicting three‐month outcomes post‐discharge. Inflammatory markers, including D‐dimer, N, and L_pct_24 h, significantly enhanced the model's predictive performance. The SHAP method provided both global and local interpretability, elucidating the relative importance of each feature in the model's predictions. To facilitate clinical decision‐making, a web‐based application was developed for real‐time prognostic assessment. Conclusion This study developed a robust and interpretable predictive model for ACI prognosis by integrating clinical and inflammatory biomarkers. The model underscores the prognostic significance of NIHSS_24 h and inflammatory markers, highlighting the critical role of early assessment and personalized treatment strategies. Future research should focus on multi‐center validation and the incorporation of additional predictive variables to further enhance the model's accuracy and generalizability.

Gut dysbiosis impacts the recovery of neurological function after spinal cord injury (SCI). Hyperbaric oxygen (HBO) can alleviate SCI, but its effects on the gut microbiota post-SCI remain unclear. This study aimed to clarify the impact of HBO on SCI-induced gut dysbiosis and to explore the mechanisms of locomotor recovery in HBO-treated SCI mice. After establishing different groups of mouse models, bacterial cultures and Basso Mouse Scale (BMS) scores were performed at various time points post-SCI. Intestinal tissues were collected for intestinal permeability assay, histological analysis, immunofluorescence, and qPCR analysis. Flow cytometry and ELISA were used to detect immune-inflammatory cells and cytokines in intestinal tissue. The composition of gut microbiota in fecal samples from each group was also analyzed. Spinal cord tissues were collected for immunofluorescence and untargeted metabolomics analysis. Spearman correlation analysis was used to correlate differential microbiota with differential metabolites. Our results showed that the expression of tight junction proteins was increased after HBO treatment in SCI mice. Metagenomic analysis of the fecal DNA revealed that HBO altered intestinal bacterial composition. Differential metabolites were mainly enriched in pathways, such as glycerophospholipid metabolism, steroid biosynthesis, and glycolysis/gluconeogenesis. Moreover, differential microbiota showed a strong correlation with differential metabolites related to glycerophospholipids. HBO treatment significantly inhibited immune cells and inflammatory cytokines in the gut after SCI. In addition, HBO treatment significantly increased BMS scores and body weight, and repaired damaged cholinergic neurons. Antibiotic-induced gut dysbiosis impaired the recovery of locomotor function and exacerbated intraspinal pathology. However, these effects could be mitigated by HBO treatment. Overall, HBO treatment may improve neurological recovery through multiple regulatory mechanisms including alleviating gut dysbiosis, reducing intestinal inflammation, and rectifying glycerophospholipid metabolic disorders after SCI. These findings highlight HBO as a promising therapeutic strategy for SCI treatment and support its clinical application. KEY MESSAGES: The intestinal microbiota composition of mice changed after SCI. HBO treatment could preserve intestinal barrier integrity, modulate the composition of intestinal microbiota, rectify glycerophospholipid metabolic disorders, and reduce intestinal immune inflammatory responses. Intestinal microbiota identified as the target for HBO therapeutic in SCI recovery. Alleviating SCI-induced gut dysbiosis may be one of the mechanisms underlying the beneficial effect of HBO on neurological functions.

Background and purposePosterior circulation stroke patients have worse outcomes after mechanical thrombectomy (MT) and higher mortality than anterior circulation acute ischemic stroke (AIS) patients due to large vessel occlusions (LVOs). To determine the ideal recanalization device for posterior circulation LVO strokes, this study compared the operational parameters and prognosis among three commonly used thrombectomy devices.MethodsA total of 99 patients with posterior circulation AIS who underwent mechanical thrombectomy were enrolled. The patients were divided into three groups based on the different thrombectomy devices used during the procedure. Patient demographics, procedural metrics, functional outcomes, and symptomatic intracranial hemorrhage (sICH) were assessed. Any association between the devices and favorable clinical outcomes was assessed by logistic regression analysis.ResultsA total of 80 patients were analyzed. The Penumbra aspiration catheter revealed a significant advantage for the time of recanalization vs. the other devices (32 min vs. 44 and 41 min). No significant difference was observed in other procedural parameters or functional outcome. There was no significant difference in symptomatic cerebral hemorrhage (sICH), mortality, or functional independence after MT among the three groups. Diabetes mellitus, NIHSS score at admission, time from onset to recanalization, and occlusion site were associated with functional independence at 90 days, though the use of different recanalization devices did not make a significant difference.ConclusionAspiration achieved vessel recanalization faster than the retriever stent during mechanical thrombectomy in posterior circulation AIS. No clear improved functional outcome favored one device over another in this study. The key factors affecting functional outcomes in posterior circulation LVOs were the presence or absence of diabetes, baseline NIHSS, occlusion site of basilar artery, and TOR time.

Background: The purpose of this study was to evaluate the impact of glucose levels on admission, on the risk of 30-day major adverse cardiovascular events (MACEs) in patients with acute myocardial infarction (AMI), and to assess the difference in outcome between ST-segment elevation myocardial infarction (STEMI) and non-ST-segment elevation myocardial infarction (NSTEMI) patients. Methods: This study was a post hoc analysis of the Acute Coronary Syndrome Quality Improvement in Kerala Study, and 13,398 participants were included in the final analysis. Logistic regression models were used to assess the association between glucose levels on admission and the risk of 30-day MACEs, adjusting for potential confounders. Results: Participants were divided according to the glucose quintiles. There was a positive linear association between glucose levels at admission and the risk of 30-day MACEs in AMI patients [adjusted OR (95% CI): 1.05 (1.03, 1.07), p < 0.001]. Compared to participants with an admission glucose between 5.4 and 6.3 mmol/L, participants with the highest quintile of glucose level (≥10.7 mmol/L) were associated with increased risk of 30-day MACEs in the fully adjusted logistic regression model [adjusted OR (95% CI): 1.82 (1.33, 2.50), p < 0.001]. This trend was more significant in patients with STEMI (p for interaction = 0.036). Conclusions: In patients with AMI, elevated glucose on admission was associated with an increased risk of 30-day MACEs, but only in patients with STEMI.

Background and aims: In prospective studies, there is limited evidence of the association between inflammation and hypertension. We aimed to explore the relationship between systemic immune inflammatory index (SII)/systemic inflammatory response index (SIRI) and hypertension in a prospective cohort study to identify the best inflammatory cell markers that predict hypertension. Methods and results: This study was conducted in a functional community cohort in Beijing. In 2015, a total of 6003 individuals without hypertension were recruited and followed up until 2021. Using a restriction cubic spline with baseline SII/SIRI as a continuous variable, the doseresponse relationship between hypertension and SII/SIRI was explored. Logistic regression was used to analyze the correlation between hypertension and SII/SIRI trajectory groups. At a mean follow-up of 6 years, 970 participants developed hypertension. SII showed a significant nonlinear dose-response relationship with hypertension (P < 0.05). Higher SII/SIRI was associated with an increased risk of hypertension (SII: RR = 1.003, 95%CI: 1.001-1.004; SIRI: RR = 1.228, 95%CI: 1.015-1.48 6). Both SII and SIRI were more predictive in males than females (SII: 0.698 vs. 0.695; SIRI: 0.686 vs. 0.678). Conclusion: Both systemic immune inflammatory index (SII) and systemic inflammatory response Index (SIRI) independently increased the risk of hypertension, and both were effective inflammatory cell indicators that predict the risk of hypertension. (c) 2023 The Italian Diabetes Society, the Italian Society for the Study of Atherosclerosis, the Italian Society of Human Nutrition and the Department of Clinical Medicine and Surgery, Federico II University. Published by Elsevier B.V. All rights reserved.

BackgroundNon-alcoholic fatty liver disease (NAFLD) is increasingly observed in non-obese individuals. The ZJU (Zhejiang University) index has been established as a new and efficient tool for detecting NAFLD, but the relationship between the ZJU index and NAFLD within non-obese individuals still remains unclear.MethodsA post-hoc evaluation was undertaken using data from a health assessment database by the Wenzhou Medical Center. The participants were divided into four groups based on the quartile of the ZJU Index. Cox proportional hazards regression, Kaplan-Meier analysis and tests for linear trends were used to evaluate the relationship between the ZJU index and NAFLD incidence. Subgroup analysis was conducted to test the consistency of the correlation between ZJU and NAFLD in subsgroups. Receiver operative characteristic (ROC) curve analysis was performed to evaluate the predictive performance of the ZJU index, compared with the Atherogenic index of plasma (AIP) and Remnant lipoprotein cholesterol (RLP-C) index.ResultsA total of 12,127 were included in this study, and 2,147 participants (17.7%) developed NAFLD in 5 years follow-up. Participants in higher ZJU quartiles tended to be female and have higher liver enzymes (including ALP, GGT, ALT, AST), GLU, TC, TG, LDL and higher NAFLD risk. Hazard Ratios (HR) and 95% confidence intervals (CI) for new-onset NAFLD in Q2, Q3, and Q4 were 3.67(2.43 to 5.55), 9.82(6.67 to 14.45), and 21.67(14.82 to 31.69) respectively in the fully adjusted model 3. With increased ZJU index, the cumulative new-onset NAFLD gradually increased. Significant linear associations were observed between the ZJU index and new-onset NAFLD (p for trend all<0.001). In the subgroup analysis, we noted a significant interaction in sex, with HRs of 3.27 (2.81, 3.80) in female and 2.41 (2.21, 2.63) in male (P for interaction<0.01). The ZJU index outperformed other indices with an area under the curve (AUC) of 0.823, followed by AIP (AUC=0.747) and RLP-C (AUC=0.668).ConclusionThe ZJU index emerges as a promising tool for predicting NAFLD risk in non-obese individuals, outperforming other existing parameters including AIP and RLP-C. This could potentially aid in early detection and intervention in this specific demographic.

BACKGROUND AND AIMS:This study focused on the recent advancements in understanding the association between N6-methyladenosine (m6A) modification and cardiovascular disease (CVD). METHODS:The potential mechanisms of m6A related to CVD were summarized by literature review. Associations between m6A levels and CVD were explored across 8 electronic databases: PubMed, Embase, Web of Science, Cochrane Library, Sinomed, Wan Fang, CNKI, and Vip. Standard mean difference (SMD) and 95 % confidence interval (95 % CI) were calculated to assess the total effect in integrated analysis. RESULTS:The systematic review summarized previous studies on the association between m6A modification and CVD, highlighting the potential role of m6A in CVD progression. A total of 11 studies were included for integrative analysis. The mean m6A levels were significantly higher in CVD than those in normal controls (SMD = 1.86, 95 % CI: 0.16-3.56, P < 0.01). CONCLUSIONS:This systematic review provided new targets for early detection and treatment for CVD. And the integrated analysis showed that increased level of m6A was associated with CVD.

This study focuses on recent advances in proteomics and provides an up-to-date use of this technology in identifying cardiovascular disease (CVD) biomarkers. A total of eight electronic databases (PubMed, EMBASE, Web of Science, Cochrane Library, Wanfang, Vip, Sinomed, and CNKI) were searched and five were used for integrative analysis of sensitivity, specificity, positive likelihood ratio (PLR), negative likelihood ratio (NLR), diagnostic ratio (DOR) and 1 secondary indicator area under the curve (AUC). This systematic review and integrative analysis summarized potential biomarkers previously identified by proteomics. The integrative analysis suggested that proteomics technology had high clinical value in CVD diagnosis. The findings provided new possible directions for the prevention or diagnosis of CVD.

This study focuses on recent advances in proteomics and provides an up-to-date use of this technology in identifying cardiovascular disease (CVD) biomarkers. A total of eight electronic databases (PubMed, EMBASE, Web of Science, Cochrane Library, Wanfang, Vip, Sinomed, and CNKI) were searched and five were used for integrative analysis of sensitivity, specificity, positive likelihood ratio (PLR), negative likelihood ratio (NLR), diagnostic ratio (DOR) and 1 secondary indicator area under the curve (AUC). This systematic review and integrative analysis summarized potential biomarkers previously identified by proteomics. The integrative analysis suggested that proteomics technology had high clinical value in CVD diagnosis. The findings provided new possible directions for the prevention or diagnosis of CVD.

Background: Sarcopenia and cardiometabolic risk factors are very common in the middle-aged and older population. This study aimed to explore the joint effect of sarcopenia and cardiometabolic risk factors on cognitive performance and cognitive decline. Methods: The definition of sarcopenia status was referenced in the AWGS 2019 algorithm. Linear regression models were used to explore the association of sarcopenia status with cognitive performance at baseline. Mixed effect models and multinomial logistic regression models were used to evaluate the long-term effect of sarcopenia status. The additive interaction between the effects of sarcopenia and cardiometabolic risk factors on cognitive performance was also evaluated. Results: In the cross-sectional analysis, sarcopenia and possible sarcopenia were associated with worse cognitive performance. In the longitudinal analysis, the participant with sarcopenia had a 0.34 [95 % CI (-0.43,-0.24)] lower global cognition score, and those with possible sarcopenia had a 0.20 [95 % CI (-0.27,-0.14)] lower global cognition score, compared with participants with no-sarcopenia. Sarcopenia and possible sarcopenia were identified as significant risk factors for cognitive decline. Sarcopenia combined with hypertension, type 2 diabetes, dyslipidemia, or abdominal obesity was associated with worse cognitive function. Limitations: The assessment of cognitive function was not diagnosed accurately. Conclusions: Sarcopenia and possible sarcopenia had adverse effects on cognitive performance and cognitive decline, sarcopenia combined with cardiometabolic risk factors can significantly enhance these effects. Therefore, the prevention of sarcopenia in the older population is crucial.

Background The triglyceride-glucose (TyG) index is a reliable surrogate marker of insulin resistance and previous studies have confirmed the association of TyG index with incident chronic kidney disease (CKD). However, the impact of longitudinal patterns of TyG index on CKD risk among non-diabetic population is still unknown. Therefore, this study aimed to investigate the association of longitudinal patterns of TyG index with incident CKD among non-diabetic population. Methods A total of 5484 non-diabetic participants who underwent one health examination per year from 2015 to 2017 were included in this prospective study. TyG index variability and cumulative TyG index were calculated to assess the longitudinal patterns of TyG index. Cox proportional hazard models were performed to estimate the association of TyG index variability or cumulative TyG index with incident CKD. Results During a median of 3.82 years follow-up, 879 participants developed CKD. Compared with participants in the lowest quartile, the hazard ratio (HR) and 95% confidence interval (CI) of incident CKD were 1.772 (95% CI: 1.453, 2.162) for the highest TyG index variability quartile and 2.091 (95% CI: 1.646, 2.655) for the highest cumulative TyG index quartile in the fully adjusted models. The best discrimination and reclassification improvement were observed after adding baseline TyG, TyG index variability and cumulative TyG index to the clinical risk model for CKD. Conclusions Both TyG index variability and cumulative TyG index can independently predict incident CKD among non-diabetic population. Monitoring longitudinal patterns of TyG index may assist with prediction and prevention of incident CKD.

Purpose: Frailty, type 2 diabetes (T2D) and dyslipidemia are highly prevalent in middle-aged and elderly populations. However, evidence on the longitudinal association of frailty with T2D and dyslipidemia is limited. The aim of our study was to explore the cross-sectional and longitudinal effects of frailty levels on T2D and dyslipidemia in combination with phenotypic frailty and frailty index (FI).Materials and methods: Multivariate logistic regression model was used to explore the association of frailty status with T2D and dyslipidemia. Area under curve (AUC) of the receiver operating characteristic curve (ROC) to estimate the predictive values of phenotypic frailty and frailty index for T2D and dyslipidemia. In addition, depressive symptom was used as a mediating variable to examine whether it mediates the association between frailty and T2D or dyslipidemia.Results: 10,203 and 9587 participants were chosen for the longitudinal association analysis of frailty with T2D and dyslipidemia. Frailty was associated with T2D (phenotypic frailty: OR=1.50, 95 %CI=1.03, 2.17; FI: OR=1.17, 95 %CI=1.08, 1.26) and dyslipidemia (phenotypic frailty: OR=1.56, 95 %CI=1.16, 2.10; FI: OR=1.17, 95 %CI=1.10, 1.25). Phenotypic frailty and frailty index significantly improved the risk discrimination of T2D and dyslipidemia (p<0.05). Depressive symptoms played a mediating role in the association between frailty and long-term T2D or dyslipidemia (p<0.05).Conclusion: Frailty had adverse effects on type 2 diabetes and dyslipidemia, with depressive symptoms acting as the mediator.

Evidence of associations between ambient fine particulate matter (PM2.5) and risks of decline of kidney function and hyperuricemia is limited. We aimed to investigate the associations between long-term exposure to PM2.5 with decline of kidney function and hyperuricemia in China. We conducted a two-stage study based on China Health and Retirement Longitudinal Study (CHARLS) from 2011 to 2015. Cox proportional hazard regression models and restricted cubic splines were used to evaluate the associations of PM2.5 with risks of decline of kidney function and hyperuricemia. Latent class trajectory models (LCTM) were used to identify trajectories of PM2.5 from 2011 to 2015 in the sensitivity analysis. A total of 9760 participants were included in baseline analysis, and 5902 participants were in follow-up analysis. PM2.5 was associated with the risks of decline of kidney function [hazard ratio (HR): 2.14; 95% confidence interval (CI): (1.03, 4.44)] and hyperuricemia [HR 1.40 (95% CI: 1.10, 1.79)] in the second quartile group versus the lowest quartile group of PM2.5. We also observed nonlinear relationships between PM2.5 and the risks of the decline of kidney function and hyperuricemia (Pnon-linear < 0.001). In sensitivity analysis, four trajectory groups were identified. "Maintaining a high PM2.5 " [odds ratio (OR): 2.20; 95%CI: (1.78, 2.73)] and "moderately high starting PM2.5 then steadily decreased " [OR (95%CI): 5.15 (1.55, 16.13)] were associated with hyperuricemia risk, using "low starting PM2.5 then steadily decreased " trajectory as reference. In conclusion, improved air quality is essential for prevention of decline of kidney function and hyperuricemia.

This study aimed to explore the separate and joint effects of long-term ambient air pollution and household air pollution exposure on 10-year high cardiovascular disease (CVD) risk among postmenopausal women. A total of 4679 postmenopausal women from the China Health and Retirement Longitudinal Study (CHARLS) were included in this study. Information of fuel type was collected by standard questionnaires and use of solid fuel was considered as a proxy for household air pollution. Data of ambient air pollutants (PM1, PM2.5, PM10, SO2, NO2, CO, O-3) were obtained from the ChinaHighAirPollutants (CHAP) datasets. Logistic regression models were performed to assess the separate and joint effects of long-term exposure to ambient air pollution and use of solid fuel on 10-year high CVD risk. We found use of solid fuel and its duration and ambient air pollutants (PM1, PM2.5, PM10, SO2, NO2) were all positively associated with 10-year high CVD risk among postmenopausal women (P < 0.05). Compared to those used clean fuel and exposed to low ambient air pollution levels, odds ratios (ORs) and 95% confidence intervals (CIs) for participants using solid fuels and exposed to high ambient air pollution levels (PM1, PM2.5, PM10, SO2, NO2, CO, O-3) were 1.66 (1.35, 2.05), 1.66 (1.35, 2.04), 1.49 (1.22, 1.83), 1.28 (1.05, 1.57), 1.67 (1.34, 2.07), 1.28 (1.04, 1.57), 1.46 (1.18, 1.80), respectively. Moreover, significant additive interactions of solid fuel use with PM1 and PM2.5 on 10-year high CVD risk were observed, with approximately 18% and 23% of 10-year high risk of CVD attributable to the interaction. Overall, indoor and outdoor air pollution had separate and joint effects on 10-year high CVD risk among postmenopausal women. Therefore, simultaneously improving indoor and outdoor air quality are of great importance and could have a joint impact on prevention of CVD and improved health among postmenopausal women.