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.

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.

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.

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.

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.

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.

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.

Developing a Capsule Clinic-A 24-Hour Institution for Improving Primary Health Care Accessibility: Evidence From China.

Telehealth is an effective combination of medical service and intelligent technology. It can improve the problem of remote access to medical care. However, an imbalance in the allocation of health resources still occurs. People spend more time and money to access higher-quality services, which results in inequitable access to primary health care (PHC). At the same time, patients' usage of telehealth services is limited by the equipment and their own knowledge, and the PHC service suffers from low usage efficiency and lack of service supply. Therefore, improving PHC accessibility is crucial to narrowing the global health care coverage gap and maintaining health equity. In recent years, China has explored several new approaches to improve PHC accessibility. One such approach is the capsule clinic, an emerging institution that represents an upgraded version of the internet hospital. In coordination with the United Nations, the Yinzhou district of Ningbo city in Zhejiang, China, has been testing this new model since 2020. As of October 2022, the number of applications in Ningbo was 15, and the number of users reached 12,219. Unlike internet hospitals, the entire process-from diagnosis to prescription services-can be completed at the capsule clinic. The 24-hour telehealth service could also solve transportation problems and save time for users. Big data analysis can accurately identify regional populations' PHC service needs and improve efficiency in health resource allocation. The user-friendly, low-cost, and easily accessible telehealth model is of great significance. Installation of capsule clinics would improve PHC accessibility and resolve the uneven distribution of health resources to promote health equity.

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.

Association of walkability and fine particulate matter with chronic obstructive pulmonary disease: A cohort study in China.

BACKGROUND: Walkability has been considered to be associated with metabolic and cardiovascular diseases, but the relationship between walkability and chronic obstructive pulmonary disease (COPD) remains unclear. Moreover, fine particulate matter (PM2.5), possibly positively correlated to walkability, may lead to an increased risk of COPD. The separate and joint effects of PM2.5 and walkability on risk of COPD were explored in our study. METHODS: We used prospective data of 29,572 participants from the Yinzhou cohort in Ningbo, China. COPD cases were diagnosed based on the Yinzhou Health Information System (YHIS). Walkability was measured using walk score in relation to the built environment based on geographic information systems (GIS). Air pollution levels were assessed by fitting land use regression (LUR) models. Cox proportional hazards models were used to evaluate the relationships of PM2.5 and walkability with COPD. Furthermore, we also examined additive and multiplicative interactions between walkability and PM2.5. RESULTS: Overall, a total of 29,572 participants were included in the final analysis and 722 COPD incident cases were identified during 134,846 person-years of follow-up. Compared with subjects with lower walkability, individuals with higher walkability had a decreased risk of COPD (HR = 0.88, 95 % CI: 0.82-0.95) for every IQR increase. By contrast, exposure to PM2.5 (every IQR increase) was associated with an elevated risk of COPD (HR = 1.21, 95 % CI: 1.06-1.37). No interaction between PM2.5 and walkability was observed. CONCLUSIONS: Living in a highly walkable neighborhood could decrease risk of COPD, whereas high levels of PM2.5 were positively associated with COPD. In addition, the beneficial effects of walkability were not attenuated by exposure to PM2.5.

Associations of Diet Quality and Heavy Metals with Obesity in Adults: A Cross-Sectional Study from National Health and Nutrition Examination Survey (NHANES).

A poor diet cannot fully explain the prevalence of obesity. Other environmental factors (e.g., heavy metals) have been reported to be associated with obesity. However, limited evidence is available for the combined effect of these factors on obesity. Therefore, we conducted a cross-sectional study and used the data from the National Health and Examination Survey (2007−2018) to explore the associations between diet quality and heavy metals and obesity. Diet quality was evaluated by the Healthy Eating Index-2015 (HEI-2015) score. Heavy metals included serum cadmium (Cd), lead (Pb), and mercury (Hg). We included 15,959 adults, with 5799 of obesity (body mass index ≥ 30 kg/m2). After adjustment for covariates, every interquartile range increase in HEI-2015 scores, Pb, Cd and Hg was associated with a 35% (odds ratios [OR] = 0.65, 95% confidence interval [CI]: 0.60, 0.70), 11% (OR = 0.89, 95% CI: 0.82, 0.98), 9% (OR = 0.91, 95% CI: 0.87, 0.96), 5% (OR = 0.85, 95% CI: 0.82, 0.89) reduction in risk of peripheral obesity, respectively. In addition, the association between the HEI-2015 scores and peripheral obesity was attenuated by higher levels of heavy metals (All p interaction < 0.05). Results remained similar for abdominal obesity. Our study reveals the distinct effects of a high-quality diet and heavy metals on obesity prevalence, and the beneficial effect of a high-quality diet could be weakened by higher levels of heavy metals.

Long-term exposure to residential surrounding greenness and incidence of diabetes: A prospective cohort study.

Exposure to residential greenness might affect population health through increasing physical activity and social engagement, improving mental health, and reducing harmful environmental exposure. However, evidence on the association of greenness with risk of diabetes is still controversial. In this study, we recruited a total of 22,535 participants aged ≥18 years from Yinzhou District, Ningbo, Zhejiang Province, China to investigate the associations between residential greenness and risk of diabetes incidence. Residential greenness was estimated using Normalized Difference Vegetation Index (NDVI), Enhanced Vegetation Index (EVI), and Vegetation Continuous Field (VCF). We also calculated cumulative average NDVI, EVI and VCF values, and changes in NDVI, EVI and VCF during the follow-up period. We used Cox proportional hazards models controlling for demographic characteristics, lifestyles, individual socioeconomic status, history of diseases and particulate matter with an aerodynamic diameter ≤2.5 µm (PM2.5) to examine hazard ratios (HRs) and 95% confidence intervals (95% CIs) and assessed physical activity, body mass index (BMI) or PM2.5 as potential mediators. During 84,992.64 person-years of follow-up, a total of 1,154 incident cases of diabetes occurred. In multivariable models, living in the highest quartile of cumulative average NDVI, EVI and VCF within 250-m buffer was associated with 57% (HR = 0.43, 95% CI: 0.36, 0.52), 62% (HR = 0.38, 95% CI: 0.32, 0.45), and 55% (HR = 0.45, 95% CI: 0.38, 0.54) reduction in diabetes risk compared with the lowest quartile, respectively. Results remained similar for NDVI, EVI, and VCF within 500-m and 1000-m buffers. Stratified analyses showed stronger association for residential greenness and diabetes among older people. The association between greenness and diabetes did not appear to be mediated by physical activity, PM2.5 or BMI. Our findings suggested that higher residential greenness was significantly associated with lower risk of diabetes.

Residential greenness, air pollution, and incident ischemic heart disease: A prospective cohort study in China.

Greener residential surroundings are associated with beneficial health outcomes, whereas higher air pollution exposure is linked with elevated risks of chronic diseases. To date, limited studies have explored the interaction between residential greenness and air pollution on the risk of ischemic heart disease (IHD). We performed a prospective cohort study that included 29,141 adult participants recruited from Yinzhou District, Ningbo, China. Normalized Difference Vegetation Index (NDVI) around each participant's residence was calculated to measure residential greenness exposure. Land-use regression models were conducted to estimate long-term individual exposure to air pollutants, including nitrogen dioxide (NO2) and particulate matter with aerodynamic diameters ≤ 2.5 µm (PM2.5) and ≤10 µm (PM10). Cox proportional hazard models were used to calculate the hazard ratios (HRs) and 95% confidence intervals (95% CIs) for the associations of residential greenness and air pollutants with the risk of incident IHD. During 101,172.5 person-years of follow-up, 1392 incident IHD cases were reported in the study population. Residential greenness, expressed as an interquartile range (IQR) increase in NDVI within 250 m, was inversely associated with incident IHD (HR = 0.89, 95%CI: 0.81,0.98). However, long-term exposures to air pollution were associated with higher IHD incidence (HR = 1.21, 95%CI:1.10,1.33 per IQR increase for PM2.5; HR = 1.12, 95%CI:1.03,1.22 per IQR increase for PM10; HR = 1.09, 95%CI:1.02,1.16 per IQR increase for NO2). Mediation analyses suggested that the beneficial effect of residential greenness on incident IHD could be partly mediated by reducing the exposure to PM2.5. These findings suggested that higher greenness was associated with decreased risk of IHD, while air pollutants were positively associated with incident IHD. Meanwhile, residential greenness may decrease the risk of IHD by reducing exposure to PM2.5.

Interaction between walkability and fine particulate matter on risk of ischemic stroke: A prospective cohort study in China.

Living in walkable neighborhoods has been reported to be associated with a lower risk of cardiovascular disease. Features of walkable neighborhoods, however, may be related to particulate matter with an aerodynamic diameter ≤2.5 µm (PM2.5), which could increase risk of cardiovascular disease. The interaction effect between walkability and PM2.5 on risk of ischemic stroke remains to be elucidated. In this study, we recruited a total of 27,375 participants aged ≥40 years from Yinzhou District, Ningbo, Zhejiang Province, China to investigate the associations of walkability and PM2.5 with risk of ischemic stroke. We used amenity categories and decay functions to evaluate walkability and high-spatiotemporal-resolution land-use regression models to assess PM2.5 concentrations. We used Cox proportional hazards regression models to calculate hazard ratios (HRs) and 95% confidence intervals (CIs). During a median follow-up of 4.08 years, we identified a total of 637 incident cases of ischemic stroke in the entire cohort. Higher walkability was associated with a lower risk of ischemic stroke (quartile, Q4 vs. Q1 walkability: HR = 0.59, 95% CI: 0.47-0.75), whereas PM2.5 was positively associated with risk of ischemic stroke (Q4 vs. Q1 PM2.5: HR = 1.70, 95% CI: 1.29-2.25). Furthermore, we observed a significant interaction between walkability and PM2.5 on risk of ischemic stroke. Walkability was inversely associated with risk of ischemic stroke at lower PM2.5 concentrations, but this association was attenuated with increasing PM2.5 concentrations. Although walkable neighborhoods appear to decrease the risk of ischemic stroke, benefits may be offset by adverse effects of PM2.5 exposure in the most polluted areas. These findings are meaningful for future neighborhood design, air pollution control, and stroke prevention.

Long-term exposure to ambient air pollution and incidence of depression: A population-based cohort study in China.

BACKGROUND: Long-term exposure to ambient air pollution was linked to depression incidence, although the results were limited and inconsistent. OBJECTIVES: To investigate the effects of long-term air pollution exposure on depression risk prospectively in China. METHODS: The present study used data from Yinzhou Cohort on adults without depression at baseline, and followed up until April 2020. Two-year moving average concentrations of particulate matter with a diameter ≤ 2.5 µm (PM2.5), ≤10 µm (PM10) and nitrogen dioxide (NO2) were measured using land-use regression (LUR) models for each participant. Depression cases were ascertained using the Health Information System (HIS) of the local health administration by linking the unique identifiers. We conducted Cox regression models with time-varying exposures to estimate the hazard ratios (HRs) and 95% confidence intervals (95% CIs) of depression with each pollutant, after adjusting for a sequence of individual covariates as demographic characteristics, lifestyles, and comorbidity. Besides, physical activity, baseline potential depressive symptoms, cancer status, COVID-19 pandemic, different outcome definitions and air pollution exposure windows were considered in sensitivity analyses. RESULTS: Among the 30,712 adults with a mean age of 62.22 ± 11.25, 1024 incident depression cases were identified over totaling 98,619 person-years of observation. Interquartile range increments of the air pollutants were associated with increased risks of depression, and the corresponding HRs were 1.59 (95%CI: 1.46, 1.72) for PM2.5, 1.49 (95%CI: 1.35, 1.64) for PM10 and 1.58 (95%CI: 1.42, 1.77) for NO2. Subgroup analyses suggested that participants without taking any protective measures towards air pollution were more susceptible. The results remained robust in all sensitivity analyses. CONCLUSIONS: Long-term exposure to ambient air pollution was identified as a risk factor for depression onset. Strategies to reduce air pollution are necessary to decrease the disease burden of depression.

Association of residential greenness and incident depression: Investigating the mediation and interaction effects of particulate matter.

BACKGROUND: Growing evidence has linked residential greenness to depression, the results from prospective cohort study are still limited. And it remains unclear whether particulate matter (PM) modify, mediate, or interact the greenness-depression relationship. METHODS: We collected data from Yinzhou Cohort(N = 47,516) which was recruited between June 2015 and December 2017. Depression cases before April 2020 were ascertained from local Health Information System covered all residents' health care records. Residential greenness (the Normalized Difference Vegetation Index, NDVI, and the Enhanced Vegetation Index, EVI) and PM (particulate matters with diameters≤2.5 µm, PM2.5 and particulate matters with diameters≤10 µm, PM10) were estimated based on participants' residential coordinates. We conducted Cox models employing age as timescale to estimate the association between residential greenness within different buffers and incident depression. Furthermore, we explored the potential confounding, mediation and interaction relationship between greenness and PM. RESULTS: During the 99,556 person-years of follow-up, 1043 incident depression cases occurred. In single exposure models, residential greenness was inversely associated with depression incidence (e.g. Hazard Ratio (HR) = 0.86, 95% confidence interval (CI): 0.79, 0.94 for per interquartile range (IQR) increase NDVI 250 m). The protective association between greenness was attenuated after introducing PM2.5 and PM10 into the models. We identified multiplicative interactions between greenness and PM exposure for depression (e.g. HR interaction = 0.91, 95%CI: 0.85, 0.98 for per IQR decrease NDVI 250 m and per IQR increase PM2.5). Besides, we found the protective association of greenness was partly mediated by PM (e.g. mediation proportion = 52.9% between NDVI 250 m and PM2.5). CONCLUSIONS: In this longitudinal cohort study, residents living in greener neighborhoods had a lower risk of depression incidence and the benefits were interacted and partly mediated by PM. Improvement in residential greenness could be an actionable and planning intervention to prevent depression.

HDL-C, longitudinal change and risk of mortality in a Chinese cohort study.

BACKGROUND AND AIMS: High-density lipoprotein cholesterol (HDL-C) concentration and variability are both important factors of cardiovascular disease (CVD) and mortality. We aimed to explore the associations of HDL-C and longitudinal change in HDL-C with risk of mortality. METHODS AND RESULTS: We recruited a total of 69,163 participants aged ≥40 years and had medical examination records of HDL-C during 2010-2014 from the Yinzhou District, Ningbo, China. Hazard ratios (HRs) and 95% confidence intervals (CIs) were estimated using Cox proportional hazards regression models. We observed a non-linear association of HDL-C with risks of non-accidental and CVD mortality. Compared with the moderate concentration group (1.4-1.6 mmol/L), HDL-C <1 mmol/L was associated with a higher risk of non-accidental mortality (HR: 1.13 (95% CI: 1.01-1.27)) and both HDL-C <1 mmol/L and ≥2 mmol/L were associated with a higher risk of CVD mortality (HRs: 1.23 (95% CI: 1.01-1.50) and 1.37 (95% CI: 1.03-1.82), respectively). Compared with the stable group ([-0.1, +0.1 mmol/L]), a large decrease ([-0.5, -0.3 mmol/L]) and very large decrease (<-0.5 mmol/L) in HDL-C were associated with a higher risk of non-accidental mortality (HRs: 1.40 (95% CI: 1.21-1.63) and 1.78 (95% CI: 1.44-2.20), respectively). Similar results were observed for CVD mortality and cancer mortality. CONCLUSION: Extremely low or high HDL-C and a large decrease or very large decrease in HDL-C were associated with a higher risk of cause-specific mortality. Monitoring of HDL-C may have utility in identifying individuals at higher risk of mortality.

Low LDL-C levels are associated with risk of mortality in a Chinese cohort study.

BACKGROUND AND AIMS: Although low-density lipoprotein cholesterol (LDL-C) has been considered as a risk factor of atherosclerotic cardiovascular disease, limited studies can be available to evaluate the association of LDL-C with risk of mortality in the general population. This study aimed to examine the association of LDL-C level with risk of mortality using a propensity-score weighting method in a Chinese population, based on the health examination data. METHODS: We performed a retrospective cohort study with 65,517 participants aged 40 years or older in Ningbo city, Zhejiang. LDL-C levels were categorized as five groups according to the Chinese dyslipidemia guidelines in adults. To minimize potential biases resulting from a complex array of covariates, we implemented a generalized boosted model to generate propensity-score weights on covariates. Then, we used Cox proportional hazard regression models with all-cause and cause-specific mortality as the dependent variables to estimate hazard ratios (HRs) and 95% confidence intervals (95% CIs). RESULTS: During the 439,186.5 person years of follow-up, 2403 deaths occurred. Compared with the median LDL-C group (100-130 mg/dL), subjects with extremely low LDL-C levels (group 1) had a higher risk of deaths from all-cause (HR = 2.53, 95% CI:1.80-3.53), CVD (HR = 1.84, 95% CI: 1.28-2.61), ischemic stroke (HR = 2.29, 95% CI:1.32-3.94), hemorrhagic stroke (HR = 3.49, 95% CI: 1.57-7.85), and cancer (HR = 2.12, 95% CI: 1.04-4.31) while the corresponding HRs in LDL-C group 2 were relatively lower than that in group 1. CONCLUSIONS: Low LDL-C levels were associated with an increased risk of all-cause, CVD, ischemic stroke, hemorrhagic stroke, and cancer mortality in the Chinese population.

Effect of COVID-19 on hospital visits in Ningbo, China: an interrupted time-series analysis.

OBJECTIVE: Unprecedented rigorous public health measures were implemented during the coronavirus disease 2019 (COVID-19) epidemic, but it is still unclear how the intervention influenced hospital visits for different types of diseases. We aimed to evaluate the impact of the intervention on hospital visits in Yinzhou District, Ningbo, Zhejiang province, China. METHODS: We conducted an interrupted time-series analysis from 1 January 2017 to 6 September 2020 based on the Yinzhou Health Information System in Ningbo, Zhejiang province. The beginning of the intervention was on 23 January 2020, and thus, there were 160 weeks before the intervention and 32 weeks after the implementation of the intervention. Level changes between expected and observed hospital visits in the post-intervention period were estimated using quasi-Poisson regression models. RESULTS: Compared with the expected level, there was an estimated decrease of -22.60% (95% confidence interval (CI): -27.53%, -17.36%) in the observed total hospital visits following the intervention. Observed hospital visits for diseases of the respiratory system were found to be decreased dramatically (-62.25%; 95% CI: -65.62%, -58.60%). However, observed hospital visits for certain diseases were estimated to be increased, including diseases of the nervous system (+11.17%; 95% CI: +3.21%, +19.74%); diseases of pregnancy, childbirth and the puerperium (+27.01%; 95% CI: +17.89%, +36.85%); certain conditions originating in the perinatal period (+45.05%; 95% CI: +30.24%, +61.56%); and congenital malformation deformations and chromosomal abnormalities (+35.50%; 95% CI: +21.24%, +51.45%). CONCLUSIONS: Our findings provided scientific evidence that cause-specific hospital visits evolve differently following the intervention during the COVID-19 epidemic.