Outdoor Light at Night, Air Pollution, and Risk of Cerebrovascular Disease: A Cohort Study in China.

BACKGROUND: We sought to explore the associations of outdoor light at night (LAN) and air pollution with the risk of cerebrovascular disease (CeVD). METHODS: We included a total of 28 302 participants enrolled in Ningbo, China from 2015 to 2018. Outdoor LAN and air pollution were assessed by Satellite-derived images and land-use regression models. CeVD cases were confirmed by medical records and death certificates and further subdivided into ischemic and hemorrhagic stroke. Cox proportional hazard models were used to estimate hazard ratios and 95% CIs. RESULTS: A total of 1278 CeVD cases (including 777 ischemic and 133 hemorrhagic stroke cases) were identified during 127 877 person-years of follow-up. In the single-exposure models, the hazard ratios for CeVD were 1.17 (95% CI, 1.06-1.29) for outdoor LAN, 1.25 (1.12-1.39) for particulate matter with an aerodynamic diameter ≤2.5 µm, 1.14 (1.06-1.22) for particulate matter with aerodynamic diameter ≤10 µm, and 1.21 (1.06-1.38) for NO2 in every interquartile range increase. The results were similar for ischemic stroke, whereas no association was observed for hemorrhagic stroke. In the multiple-exposure models, the associations of outdoor LAN and PM with CeVD persisted but not for ischemic stroke. Furthermore, no interaction was observed between outdoor LAN and air pollution. CONCLUSIONS: Levels of exposure to outdoor LAN and air pollution were positively associated with the risk of CeVD. Furthermore, the detrimental effects of outdoor LAN and air pollution might be mutually independent.

Investigating Nonspecific Effects of the Live-Attenuated Japanese Encephalitis Vaccine on Lower Respiratory Tract Infections in Children Aged 25-35 Months: Retrospective Cohort Study.

BACKGROUND: Live attenuated vaccines may be used to prevent nontargeted diseases such as lower respiratory tract infections (LRTIs) due to their nonspecific effects (NSEs). OBJECTIVE: We aimed to analyze the NSEs of the Japanese encephalitis vaccine on pediatric LRTIs in children aged 25 months to 35 months. METHODS: A retrospective cohort study was conducted by using a population-based electronic health record database in Zhejiang, China. Enrolled participants were children born from January 1, 2017, to December 31, 2017, and who were inoculated with the live-attenuated Japanese encephalitis vaccine (JE-L) or inactivated Japanese encephalitis vaccine (JE-I) as the most recent vaccine at 24 months of age. The study was carried out between January 1, 2019, and December 31, 2019. All inpatient and outpatient hospital visits for LRTIs among children aged 25 months to 35 months were recorded. The Andersen-Gill model was used to assess the NSEs of JE-L against LRTIs in children and compared with those of JE-I as the most recent vaccine. RESULTS: A total of 810 children born in 2017 were enrolled, of whom 585 received JE-L (JE-L cohort) and 225 received JE-I (JE-I cohort) as their last vaccine. The JE-L cohort showed a reduced risk of LRTIs (adjusted hazard ratio [aHR] 0.537, 95% CI 0.416-0.693), including pneumonia (aHR 0.501, 95% CI 0.393-0.638) and acute bronchitis (aHR 0.525, 95% CI 0.396-0.698) at 25 months to 35 months of age. The NSEs provided by JE-L were especially pronounced in female children (aHR 0.305, 95% CI 0.198-0.469) and children without chronic diseases (aHR 0.553, 95% CI 0.420-0.729), without siblings (aHR 0.361, 95% CI 0.255-0.511), with more than 30 inpatient and outpatient hospital visits prior to 24 months of age (aHR 0.163, 95% CI 0.091-0.290), or with 5 to 10 inpatient and outpatient hospital visits due to infectious diseases prior to 24 months old (aHR 0.058, 95% CI 0.017-0.202). CONCLUSIONS: Compared with JE-I, receiving JE-L as the most recent vaccine was associated with lower risk of inpatient and outpatient hospital visits for LRTIs among children aged 25 months to 35 months. The nature of NSEs induced by JE-L should be considered for policymakers and physicians when recommending JE vaccines to those at high risk of infection from the Japanese encephalitis virus.

Using big data to analyze the vaccination status of children with congenital heart disease in Yinzhou District, China.

Congenital heart disease (CHD) represents a significant population warranting particular attention concerning vaccination coverage. To comprehend the vaccination status of CHD within Yinzhou District, Ningbo City, China, and to facilitate the formulation of preventive, control, and immunization strategies against vaccine-preventable diseases in children with congenital heart conditions. Using the China Yinzhou Electronic Health Record Study (CHERRY) database, we analyzed the vaccination coverage of children with CHD born between January 1, 2016 and September 20, 2021, and analyzed the influencing factors associated with the level of vaccination coverage. This study involved 762 children diagnosed with CHD at the age of 12 months, revealing that 86.74% of these children had received at least one dose of the National Immunization Program (NIP) vaccines. The coverage for non-NIP vaccines, such as the rotavirus vaccine, influenza vaccine, Influenza Haemophilus influenzae Type b (Hib) Conjugate Vaccine, 13-valent pneumococcal conjugate vaccine (PCV13), and inactivated enterovirus type 71 vaccine (EV71), stood at 27.30%, 7.74%, 63.25%, 33.76%, and 34.51%, respectively. The completion coverage for the entire vaccination schedule were 27.30%, 5.51%, 55.77%, 34.25%, and 25.59%, respectively. There was a statistically significant correlation between vaccination coverage in classification of diagnostic medical institutions and the types of diagnosed diseases. Compared to their typically developing counterparts, 12-month-old children afflicted with CHD exhibit a slightly diminished vaccination coverage, alongside a discernible inclination toward delayed vaccination. Notably, the determination to undergo vaccinations seems predominantly influenced by the classification of diagnostic medical institutions. In practical terms, proactive measures involving early diagnosis, comprehensive health assessments, and timely interventions ought to be implemented to enhance vaccination rates while prioritizing safety.

Association between drinking water quality and mental health and the modifying role of diet: a prospective cohort study.

BACKGROUND: Environmental factors play an important role in developing mental disorders. This study aimed to investigate the associations of metal and nonmetal elements in drinking water with the risk of depression and anxiety and to assess whether diets modulate these associations. METHODS: We conducted a prospective cohort study including 24,285 participants free from depression and anxiety from the Yinzhou Cohort study in the 2016-2021 period. The exposures were measured by multiplying metal and nonmetal element concentrations in local pipeline terminal tap water samples and total daily drinking water intakes. Cox regression models adjusted for multi-level covariates were used to estimate adjusted hazard ratios (aHRs) and 95% confidence intervals (95%CIs). RESULTS: During an average follow-up period of 4.72 and 4.68 years, 773 and 1334 cases of depression and anxiety were identified, respectively. A 1 standard deviation (SD) increase in manganese exposure reduced the incidence of depression by 8% (HR 0.92, 95%CI 0.88 to 0.97). In contrast, with a 1 SD increase in copper and cadmium exposure, the incidence of depression increased by 6% (HR 1.06, 95%CI 1.01 to 1.11) and 8% (HR 1.08, 95%CI 1.00 to 1.17), respectively. The incidence of anxiety increased by 39% (HR 1.39, 95%CI 1.20 to 1.62), 33% (HR 1.33, 95%CI 1.03 to 1.71), and 14% (HR 1.14, 95%CI 1.03 to 1.25) respectively for a 1 SD increase in manganese, iron, and selenium exposure. Diets have a moderating effect on the associations of metal and nonmetal elements with the risk of anxiety. Stronger associations were observed in older, low-income groups and low-education groups. CONCLUSIONS: We found significant associations between exposure to metal and nonmetal elements and depression and anxiety. Diets regulated the associations to some extent.

Improving cardiovascular risk prediction through machine learning modelling of irregularly repeated electronic health records.

Aims: Existing electronic health records (EHRs) often consist of abundant but irregular longitudinal measurements of risk factors. In this study, we aim to leverage such data to improve the risk prediction of atherosclerotic cardiovascular disease (ASCVD) by applying machine learning (ML) algorithms, which can allow automatic screening of the population. Methods and results: A total of 215 744 Chinese adults aged between 40 and 79 without a history of cardiovascular disease were included (6081 cases) from an EHR-based longitudinal cohort study. To allow interpretability of the model, the predictors of demographic characteristics, medication treatment, and repeatedly measured records of lipids, glycaemia, obesity, blood pressure, and renal function were used. The primary outcome was ASCVD, defined as non-fatal acute myocardial infarction, coronary heart disease death, or fatal and non-fatal stroke. The eXtreme Gradient boosting (XGBoost) algorithm and Least Absolute Shrinkage and Selection Operator (LASSO) regression models were derived to predict the 5-year ASCVD risk. In the validation set, compared with the refitted Chinese guideline-recommended Cox model (i.e. the China-PAR), the XGBoost model had a significantly higher C-statistic of 0.792, (the differences in the C-statistics: 0.011, 0.006-0.017, P < 0.001), with similar results reported for LASSO regression (the differences in the C-statistics: 0.008, 0.005-0.011, P < 0.001). The XGBoost model demonstrated the best calibration performance (men: Dx = 0.598, P = 0.75; women: Dx = 1.867, P = 0.08). Moreover, the risk distribution of the ML algorithms differed from that of the conventional model. The net reclassification improvement rates of XGBoost and LASSO over the Cox model were 3.9% (1.4-6.4%) and 2.8% (0.7-4.9%), respectively. Conclusion: Machine learning algorithms with irregular, repeated real-world data could improve cardiovascular risk prediction. They demonstrated significantly better performance for reclassification to identify the high-risk population correctly.

Associations Between Thiazolidinediones Use and Incidence of Rheumatoid Arthritis: A Retrospective Population-Based Cohort Study.

OBJECTIVE: Preclinical studies suggest that thiazolidinediones (TZDs) may have a protective effect on rheumatoid arthritis (RA), but evidence from population-based studies is scarce. This study aimed to assess the association between use of TZDs and incidence of RA in a retrospective cohort of patients with type 2 diabetes mellitus (T2DM). METHODS: A retrospective cohort of patients with T2DM who were new users of TZDs or alpha glucosidase inhibitors (AGIs) was assembled. We applied the inverse probability of treatment weighted Cox model to estimate the hazard ratio (HR) of RA incidence associated with the use of TZDs compared with AGIs. RESULTS: The final analysis included 56,796 new users of AGIs and 14,892 new users of TZDs. The incidence of RA was 187.4 and 135.2 per 100,000 person-years in AGI users and TZD users, respectively. Compared with use of AGIs, TZD use was associated with a reduction in RA incidence, with an HR of 0.72 (95% confidence interval [95% CI] 0.59-0.89). HRs for cumulative use of TZDs for 0.51 to 4.0 years and more than 4 years with incidence of RA were 0.55 (95% CI 0.35-0.88) and 0.74 (95% CI 0.57-0.98), respectively. Various subgroup analyses and sensitivity analyses were consistent with the primary analysis. CONCLUSION: Use of TZDs is associated with a decreased risk of incident RA in patients with T2DM.

Association between visit-to-visit lipid variability and risk of ischemic heart disease: a cohort study in China.

AIMS: To explore the associations between visit-to-visit lipid variability and risk of ischemic heart disease (IHD) in a population-based cohort in China. METHODS: We evaluated lipid variability in 30,217 individuals from the Yinzhou Health Information System who had ≥3 recorded lipid measurements during 2010-2014. We used various indicators including standard deviation (SD), coefficient of variation (CV), variability independent of the mean (VIM), and average real variability (ARV) to quantify the variability in triglycerides, total cholesterol (TC), high-density lipoprotein cholesterol (HDL-C), and low-density lipoprotein cholesterol (LDL-C). We used Cox proportional hazards models to estimate hazard ratios (HRs) and 95% confidence intervals (CIs). RESULTS: Overall, a total of 1305 participants with IHD were identified during the follow-up of 194,421 person-years. Subjects in Q4 had a 21% elevated risk of IHD (HR = 1.21, 95% CI: 1.03-1.41) for LDL-C variability (CV) compared with the reference (Q1). The HRs for Q4 vs Q1 were 1.21 (95% CI: 1.04-1.42) for HDL-C variability, and 1.28 (95% CI: 1.10-1.50) for TC variability. However, no association was observed between triglycerides variability and risk of IHD. CONCLUSIONS: Higher variability in LDL-C, HDL-C, and TC levels was associated with an elevated risk of IHD, suggesting that lipid variability could be considered as an independent risk factor of IHD.

Long-Term Exposure to PM2.5 and Mortality: A Cohort Study in China.

We investigated the association of long-term exposure to atmospheric PM2.5 with non-accidental and cause-specific mortality in Yinzhou, China. From July 2015 to January 2018, a total of 29,564 individuals aged ≥ 40 years in Yinzhou were recruited for a prospective cohort study. We used the Cox proportional-hazards model to analyze the relationship of the 2-year average concentration of PM2.5 prior to the baseline with non-accidental and cause-specific mortality. The median PM2.5 concentration was 36.51 µg/m3 (range: 25.57-45.40 µg/m3). In model 4, the hazard ratios per 10 µg/m3 increment in PM2.5 were 1.25 (95%CI: 1.04-1.50) for non-accidental mortality and 1.38 (95%CI:1.02-1.86) for cardiovascular disease mortality. We observed no associations between PM2.5 and deaths from respiratory disease or cancer. In the subgroup analysis, interactions were observed between PM2.5 and age, as well as preventive measures on hazy days. The observed association between long-term exposure to atmospheric PM2.5 at a relatively moderate concentration and the risk of non-accidental and cardiovascular disease mortality among middle-aged and elderly Chinese adults could provide evidence for government decision-makers to revise environmental policies towards a more stringent standard.

Exposure to Neighborhood Walkability and Residential Greenness and Incident Fracture.

Importance: Emerging studies have suggested that environmental factors are associated with fracture. However, little is known about the association of neighborhood walkability and residential greenness with fracture. Objective: To investigate the association of long-term exposure to walkability and greenness with incident fracture and explore the potential interaction effect. Design, Setting, and Participants: This cohort study recruited participants aged 40 years or older in Ningbo, China from June 2015 to January 2018. Participants were observed for outcomes through February 2023, with data analysis conducted in March 2023. Exposures: Neighborhood walkability was measured by a modified walkability calculation method according to a walk score tool. Residential greenness was assessed by satellite-derived normalized difference vegetation index (NDVI) within a 1000-m buffer. Main Outcomes and Measures: Incident fracture was ascertained according to International Statistical Classification of Diseases and Related Health Problems, Tenth Revision codes via the Yinzhou Health Information System. Cox proportional hazards models were fit, with age as time scale to estimate the associations of walkability and greenness with fracture. Potential effect modification was explored by covariates, as well as the interactive effect of walkability and greenness. Results: A total of 23 940 participants were included in this study with 13 735 being female (57.4%). The mean (SD) age at baseline was 63.4 (9.4) years. During a follow-up period of 134 638 person-years, 3322 incident fractures were documented. In the full adjusted model, every IQR increment in neighborhood walkability and residential greenness was associated with a hazard ratio (HR) of 0.88 (95% CI, 0.83-0.92) and 0.84 (95% CI, 0.80-0.89), respectively, for fracture. Furthermore, the association of greenness and fracture was greater with an increase in walkability. The HR (Q4 vs Q1) for greenness was 0.62 (95% CI, 0.46-0.82) in neighborhoods with the highest quartile of walkability. Conclusions and Relevance: This population cohort study suggested that long-term exposure to neighborhood walkability and residential greenness were both associated with lower risk of incident fracture. The benefits of greenness increased in more walkable areas.

Evaluating the effectiveness and cost-effectiveness of free influenza vaccination policy for older adults in Yinzhou, China: Study protocol of a real-world analyses.

BACKGROUND: Influenza causes excessive morbidity and mortality among older adults. While influenza vaccine provides protection against its infection, the vaccination coverage in China among older adults has been very low. Previous evidence on the cost-effectiveness of government-sponsored free influenza vaccination programs in China was primarily based on literature data, which might not always reflect real-world patient populations. The Yinzhou Health Information System (YHIS) is a regional database that captures electronic health records, insurance claims data, etc. for all residents in Yinzhou district, Zhejiang province, China. We will use YHIS to study the effectiveness, influenza-related direct medical cost and cost-effectiveness analysis (CEA) of the free influenza vaccination program for older adults. In this paper, we describe the study design and innovations in detail. METHODS: We will establish a retrospective cohort of permanent older residents aged 65 and over, using YHIS between 2016 and 2021. We will estimate the vaccine coverage rate, influenza incidence rate and influenza-related direct medical cost from 2016 to 2021. Regression discontinuity will be used to estimate vaccine effectiveness for the 2020/2021 season. We will build a decision tree model to compare the cost-effectiveness of three influenza vaccination options (free trivalent influenza vaccine, free quadrivalent influenza vaccine, and no policy) from both societal and health system perspectives. Parameter inputs will be gathered from both YHIS and published literature. We will calculate the incremental cost-effectiveness ratio with cost and quality-adjusted life years (QALYs) discounted at 5 % annually. DISCUSSION: Our CEA solidifies multiple sources including regional real-world data and literature for a rigorous evaluation of the government-sponsored free influenza vaccination program. The results will provide real-world evidence from real-world data on the cost-effectiveness of a real-world policy. Our findings are expected to support evidence-based policy making and to promote health for older adults.

Validation and comparison of cardiovascular risk prediction equations in Chinese patients with Type 2 diabetes.

AIMS: For patients with diabetes, the European guidelines updated the cardiovascular disease (CVD) risk prediction recommendations using diabetes-specific models with age-specific cut-offs, whereas American guidelines still advise models derived from the general population. We aimed to compare the performance of four cardiovascular risk models in diabetes populations. METHODS AND RESULTS: Patients with diabetes from the CHERRY study, an electronic health records-based cohort study in China, were identified. Five-year CVD risk was calculated using original and recalibrated diabetes-specific models [Action in Diabetes and Vascular disease: PreterAx and diamicroN-MR Controlled Evaluation (ADVANCE) and the Hong Kong cardiovascular risk model (HK)] and general population-based models [Pooled Cohort Equations (PCE) and Prediction for Atherosclerotic cardiovascular disease Risk in China (China-PAR)]. During a median 5.8-year follow-up, 46 558 patients had 2605 CVD events. C-statistics were 0.711 [95% confidence interval: 0.693-0.729] for ADVANCE and 0.701 (0.683-0.719) for HK in men, and 0.742 (0.725-0.759) and 0.732 (0.718-0.747) in women. C-statistics were worse in two general population-based models. Recalibrated ADVANCE underestimated risk by 1.2% and 16.8% in men and women, whereas PCE underestimated risk by 41.9% and 24.2% in men and women. With the age-specific cut-offs, the overlap of the high-risk patients selected by every model pair ranged from only 22.6% to 51.2%. When utilizing the fixed cut-off at 5%, the recalibrated ADVANCE selected similar high-risk patients in men (7400) as compared to the age-specific cut-offs (7102), whereas age-specific cut-offs exhibited a reduction in the selection of high-risk patients in women (2646 under age-specific cut-offs vs. 3647 under fixed cut-off). CONCLUSION: Diabetes-specific CVD risk prediction models showed better discrimination for patients with diabetes. High-risk patients selected by different models varied significantly. Age-specific cut-offs selected fewer patients at high CVD risk especially in women.

This large electronic health records-based real-world study indicated that the diabetes-specific cardiovascular risk models had better discriminative abilities than the models derived from the general population in Chinese patients with Type 2 diabetes.Current guidelines-recommended models, i.e. ADVANCE, PCE, and China-PAR, selected significantly different high-risk groups with various observed cardiovascular risks, indicating the potential considerable misclassification of risk stratification in clinical decision-making for preventive interventions.Compared with the fixed cut-off, the influence of the age-specific cut-offs for high risk of cardiovascular disease was different in men and women: age-specific cut-offs selected ∼27% fewer high-risk patients in women but similar in men.

Age at diagnosis modifies associations of type 2 diabetes with cancer incidence and mortality: a retrospective matched-cohort study.

AIMS/HYPOTHESIS: The age-specific associations between type 2 diabetes and cancer risk are not fully understood. The aim of this study was to assess how age at diagnosis modifies the associations between type 2 diabetes and cancer risk. METHODS: We used data from the Yinzhou Health Information System, and included 42,279 individuals who were newly diagnosed with type 2 diabetes between 2010 and 2014, as well as 166,010 age- and sex-matched control individuals without diabetes who were selected randomly from the electronic health records of the entire population. Patients were divided into four age groups according to age at diagnosis: <50, 50-59, 60-69 and ≥70 years. Stratified Cox proportional hazards regression models, with age as the time scale, were used to estimate the HRs and 95% CIs for the associations of type 2 diabetes with the risks of overall and site-specific cancers. Population-attributable fractions were also calculated for outcomes associated with type 2 diabetes. RESULTS: During median follow-up periods of 9.20 and 9.32 years, we identified 15,729 incident cancer cases and 5383 cancer deaths, respectively. Patients diagnosed with type 2 diabetes before 50 years of age had the highest relative risks of cancer incidence and mortality, with HRs (95% CI) of 1.35 (1.20, 1.52) for overall cancer incidence, 1.39 (1.11, 1.73) for gastrointestinal cancer incidence, 2.02 (1.50, 2.71) for overall cancer mortality, and 2.82 (1.91, 4.18) for gastrointestinal cancer mortality. Risk estimates decreased gradually with each decade increase in diagnostic age. The population-attributable fractions for overall cancer and gastrointestinal cancer mortality also decreased with increasing age. CONCLUSIONS/INTERPRETATION: The associations of type 2 diabetes with cancer incidence and mortality varied by age at diagnosis, with a higher relative risk among patients who were diagnosed at a younger age.

Residential greenness, air pollution and incident neurodegenerative disease: A cohort study in China.

BACKGROUND: Neurodegenerative disease has a great adverse impact on population's death and disability worldwide. However, the association of air pollution and residential greenness with neurodegenerative disease and their potential mechanisms still remain uncertain. METHODS: We used data from a population-based prospective cohort in Ningbo, China. Exposure to PM2.5, PM10 and NO2 were assessed by land-use regression (LUR) models and residential greenness was estimated by Normalized Difference Vegetation Index (NDVI). Our primary outcomes were all neurodegenerative diseases, Parkinson's disease (PD) and Alzheimer's disease (AD). Cox proportional hazards regression models were used to examine the association of air pollution and residential greenness with risk of incident neurodegenerative disease. Furthermore, we also explored the potential mediation relationship and effect modification between greenness and air pollutants. RESULTS: During the follow-up period, we identified a total of 617 incident neurodegenerative diseases, 301 PD and 182 AD. In single-exposure models, PM2.5 was positively associated with all outcomes (e.g. AD hazard ratio (HR): 1.41, 95 % confidence interval (CI): 1.09-1.84, per interquartile range (IQR) increment), whereas residential greenness showed protective effects (e.g. neurodegenerative disease, HR: 0.82, 95%CI: 0.75-0.90, per IQR increment for NDVI in 1000 m buffer). NO2 was positively associated with risk of neurodegenerative disease and PM10 was associated with neurodegenerative disease and AD. In two-exposure models, after adjustment for PM2.5, the association for greenness generally attenuated towards null. Moreover, we identified the significant modification effect of greenness on PM2.5 on additive and multiplicative scales. CONCLUSION: In this prospective study, we found that exposure to higher residential greenness and lower concentrations of particulate matter were associated with lower risk of neurodegenerative disease, PD and AD. Residential greenness could modify the association of PM2.5 with neurodegenerative disease.

Effectiveness of hierarchical medical system policy: an interrupted time series analysis of a pilot scheme in China.

The Chinese healthcare system faces a dilemma between its hospital-centric approach to healthcare delivery and a rapidly ageing population that requires strong primary care. To improve system efficiency and continuity of care, the Hierarchical Medical System (HMS) policy package was issued in November 2014 and fully implemented in 2015 in Ningbo, Zhejiang province, China. This study aimed to investigate the impact of the HMS on the local healthcare system. We conducted a repeated cross-sectional study with quarterly data collected between 2010 and 2018 from Yinzhou district, Ningbo. The data were analysed with an interrupted time series design to assess the impact of HMS on the changes in levels and trends of three outcome variables: primary care physicians' (PCPs') patient encounter ratio (i.e. the mean quarterly number of patient encounters of PCPs divided by that of all other physicians), PCP degree ratio (i.e. the mean degree of PCPs divided by the mean degree of all other physicians, with the mean degree revealing the mean activity and popularity of physicians, which reflected the extent to which he/she coordinated with others in delivering health services), and PCP betweenness centrality ratio (i.e. the mean betweenness centrality of PCPs divided by the mean betweenness centrality of all other physicians; the mean betweenness centrality was interpreted as the mean relative importance of physicians within the network, indicating the centrality of the network). Observed results were compared with counterfactual scenarios computed based on pre-HMS trends. Between January 2010 and December 2018, 272 267 patients visited doctors for hypertension, a representative non-communicable disease with a high prevalence of 44.7% among adults aged 35-75 years, amounting to a total of 9 270 974 patient encounters. We analysed quarterly data of 45 464 observations over 36 time points. Compared to the counterfactual, by the fourth quarter of 2018, the PCP patient encounter ratio rose by 42.7% [95% confidence interval (CI): 27.1-58.2, P < 0.001], the PCP degree ratio increased by 23.6% (95%CI: 8.6-38.5, P < 0.01) and the PCP betweenness centrality ratio grew by 129.4% (95%CI: 87.1-171.7, P < 0.001). The HMS policy can incentivize patients to visit primary care facilities and enhance the centrality of PCPs within their professional network.

Baseline and longitudinal trajectories of body-mass index and all-cause mortality among patients with type 2 diabetes.

AIM: To investigate the associations of baseline body mass index (BMI) and longitudinal BMI trajectories with all-cause mortality among patients with type 2 diabetes mellitus (T2DM). METHODS,: We used data from the diabetes surveillance system of Yinzhou Health Information System with T2DM patients registered from 2010 to 2015. Participants aged ≥ 40 years were included and were followed up until September 30, 2021. The latent class growth mixture model was used to identify different changing patterns in BMI for 5 years from registration. Cox proportional hazards models were used to examine the associations of baseline BMI and 5-year BMI trajectories with all-cause mortality. RESULTS: We observed a nonlinear association between baseline BMI and all-cause mortality (P for nonlinearity < 0.001), with an increased risk of death for low but not high BMI. However, compared with participants with medium-stable BMI for 5 years from baseline, individuals with increasing BMI had higher mortality, with adjusted hazard ratios (95% confidence intervals) 1.21 (1.02;1.43) for early-increasing and 1.47 (1.19;1.80) for late-sharp increasing groups. CONCLUSION: These findings suggest that while obesity itself may not be associated with an increased risk for mortality, weight gain, and in particular rapid weight gain, is a risk factor for mortality among patients with T2DM.

Thiazolidinedione use is associated with reduced risk of dementia in patients with type 2 diabetes mellitus: A retrospective cohort study.

BACKGROUND: Type 2 diabetes mellitus (T2DM) and dementia cause heavy health burden in mainland China, where few studies have investigated the association between glucose-lowering agents and dementia risk. We aimed to assess the association between use of thiazolidinediones (TZDs) and dementia incidence in a mainland Chinese population with T2DM. METHODS: A retrospective cohort of T2DM patients who were new users of TZDs or alpha glucosidase inhibitors (AGIs) was assembled using the Yinzhou Regional Health Care Database. A Cox model with inverse probability of treatment weighting (IPTW) for controlling potential founding was applied to estimate the hazard ratio (HR) of the association between use of TZDs and dementia risk. RESULTS: A total of 49 823 new users of AGIs and 12 752 new users of TZDs were included in the final cohort. In the primary analysis, the incidence of dementia was 195.7 and 78.2 per 100 000 person-years in users of AGIs and TZDs respectively. TZD use was associated with a reduced risk of incident dementia after adjusting for potential confounding using IPTW, with a HR of 0.51 (95% CI, 0.38-0.67). The results in various subgroup analyses and sensitivity analyses were consistent with the findings of the primary analysis. CONCLUSIONS: Use of TZDs is associated with a decreased risk of dementia incidence in a mainland Chinese population with T2DM.

Association of walkability and NO2 with metabolic syndrome: A cohort study in China.

BACKGROUND: Epidemiological studies have reported an association between traffic-related pollution with risk of metabolic syndrome (MetS). However, evidence from prospective studies on the association of walkability and nitrogen dioxide (NO2) with MetS is still scarce. We, therefore, aimed to evaluate the association of long-term exposure to NO2 and walkability with hazards of incident MetS. METHODS: A total of 17,965 participants without MetS diagnosed within one year at baseline were included in our study from a population-based prospective cohort in Yinzhou District, Ningbo, Zhejiang Province, China. Participants were followed up by the regional Health Information System (HIS) until December 15, 2021. MetS was defined based on the criteria of Chinese Diabetes Society (CDS2004). We used walkscore tools, calculating with amenity categories and decay functions, and spatial-temporal land-use regression (LUR) models to estimate walkability and NO2 concentrations. We used Cox proportional hazards regression models to examine the association of walkability and NO2 with hazards of MetS incidence reporting with hazard ratios (HRs) and 95% confidence intervals (CIs). RESULTS: Overall, we followed up 77,303 person-years and identified 4040 incident cases of MetS in the entire cohort. Higher walkability was inversely associated with incident MetS (HR = 0.94, 95 % CI: 0.91-0.99), whereas NO2 was positively associated with MetS incidence (HR = 1.07, 95 %CI: 1.00-1.15) per interquartile range increment in two-exposure models. Furthermore, we found a significant multiplicative interaction between walkability and NO2. Stronger associations were observed for NO2 and incident MetS among men, smokers, drinkers and participants who aged < 60 years and had higher levels of income. CONCLUSION: In summary, we found living in areas with lower walkability and higher concentrations of NO2 were associated with increased incidence of MetS. The beneficial effect of higher walkability may be attenuated by exposure to NO2.