Trends and burden in mental disorder death in China from 2009 to 2019: a nationwide longitudinal study

ObjectivesWe aimed to elucidate trends in the crude mortality rate (CMR), age-standardized mortality rate (ASMR), and burden of mental disorders (MD) in China.MethodsA longitudinal observational study was performed using the data of MD deaths in the National Disease Surveillance System (DSPs) during 2009–2019. The mortality rates were normalized using the Segis global population. Trends in the mortality of MDs stratified by age, gender, region, and residency, respectively. The burden of MD was evaluated using age-standardized person years of life loss per 100,000 people (SPYLLs) and average years of life lost (AYLL).ResultA total of 18,178 MD deaths occurred during 2009–2019, accounting for 0.13% of total deaths, and 68.3% of MD deaths occurred in rural areas. The CMR of MD in China was 0.75/100,00 persons (ASMR: 0.62/100,000 persons). The ASMR of all MDs decreased mainly due to the decrease in ASMR in rural residents. Schizophrenia and alcohol use disorder (AUD) were the leading causes of death in MD patients. The ASMR of schizophrenia and AUD was higher in rural residents than in urban residents. The ASMR of MD was highest in the 40–64 age group. As the leading causes of MD burden, the SPYLL and AYLL of schizophrenia were 7.76 person-years and 22.30 years, respectively.ConclusionAlthough the ASMR of all MDs decreased during 2009–2019, schizophrenia and AUD were still the most important causes of death for MDs. Targeted efforts focusing on men, rural residents, and the 40–64 years old population should be strengthened to decrease MD-related premature deaths

Time of harvest affects United States-grown Aronia mitschurinii berry polyphenols, ◦Brix, and acidity

The goal of this study was to determine how the date of harvest impacts the quality characteristics of Aronia mitschurinii (A. K. Skvortsov and Maitul.) ‘Viking’ and ‘Galicjanka’ berries. Aronia berries were collected from farms in the Midwestern and Northeastern United States over seven weeks of harvest during 2018, 2019 and 2020. The berries were analyzed for total phenol, anthocyanins, proanthocyanins, sugar, and acid. Aronia berry composition modestly deviated between each year of the study. Berries harvested in 2018 had the highest total phenols and proanthocyanidins, both increasing in content from weeks 1–5 from 15.90 ± 3.15–19.65 mg gallic acid equivalents/g fw, a 24% increase, and 2.22 ± 0.40–2.94 mg (+)-catechin equivalents/g fw, a 32% increase, respectively. Berries harvested in 2019 had the lowest total phenol and proanthocyanidin levels and had increasing anthocyanins until week 4. In 2020, aronia berry proanthocyanidins differed from those in 2018 by having 38% lower levels after the 4th week. Across years, berries had increasing ◦Brix, ◦Brix: acid, and pH throughout the seven weeks of harvest. Additionally, all years had slight, but statistically insignificant decreases in acidity over the harvest period. Moreover, analysis from berries collected in 2019 suggests no significant difference in quality factors between Viking and Galicjanka aronia cultivars. In conclusion, aronia berry total phenols, proanthocyanidins, pH, and berry size can be significantly affected by the growing year and time of harvest. Acidity was impacted more by growing year than harvest week. In contrast, anthocyanins and ◦Brix were consistent between years, but influenced considerably by the week of harvest

Association of demographics, cardiovascular indicators and disability characteristics with 7-year coronary heart disease incident in persons with disabilities

Abstract Objective Previous studies had demonstrated that disability increases mortality in patients with coronary heart disease (CHD). However, for people who had been disabled but do not have baseline cardiovascular disease, there is still limited data on how they might develop CHD. This study aimed to investigate the incidence and predictors of CHD in people with disabilities. Methods We conducted a 7-year retrospective study utilizing data from the Shanghai Comprehensive Information Platform for Persons with Disabilities Rehabilitation. Subjects aged over 18 years with at least four annual complete electronic health records were included. The primary outcome was CHD, defined as ischemic heart disease or myocardial infarction. Kaplan–Meier analysis and log-rank tests were used to compare cumulative CHD for sub-populations, stratified by age, gender, and the classification of disabilities. Cox regression was used to identify the potentially important factors. Results Out of 6419 persons with disabilities, 688 CHD cases (mean age 52.95 ± 7.17 years, male 52.2%) were identified, with a cumulative incidence of 10.72% and an incidence density of 15.15/1000 person-years. The incidence density of CHD is higher in the male gender, people over 45 years, and those with physical disabilities. Male (HR = 1.294, 95% CI, 1.111–1.506), hypertension (HR = 1.683, 95% CI, 1.405–2.009), diabetes mellitus (HR = 1.488, 95% CI, 1.140–1.934), total cholesterol (HR = 1.110, 95% CI, 1.023–1.204), and physical disabilities (HR = 1.122, 95% CI, 1.019–1.414) were independently associated with CHD. Conclusion The findings indicate that the incidence of CHD differs across disability categories rather than the severity of disability. People with physical disabilities had significantly higher risks for the development of CHD. The underlying physiological and pathological factors need to be further studied

Association of blood pressure trajectories with coronary heart disease among the disabled population in Shanghai, China: a cohort study of 7 years following up

Abstract Background Much less is known about the importance of blood pressure (BP) trajectories concerning the incidence of coronary heart disease (CHD) in people with disabilities. Our aim was to evaluate this association. Methods This cohort study surveyed 5711 adults from the Shanghai Disability Health Survey from June 2012 to June 2019. The latent class growth mixture model was used to examine distinct BP trajectories. We evaluated the association of BP trajectories with the risk of CHD by Cox proportional hazard models. The model for CHD risk fitted to BP trajectories was compared with models fitted to other BP-related indicators by goodness-of-fit, discrimination, and calibration. Results During a median follow-up of 71.74 months, 686 cases (median age was 49.03 (54.49, 58.55) years, 51.90% female) with CHD were identified, with a cumulative incidence of 12.01%. Systolic BP (SBP) and diastolic BP (DBP) were categorized into three classes, respectively. A statistically significant association was only observed between SBP trajectories and CHD. Compared with the normotensive stable SBP group (n = 1956), the prehypertension-stable group (n = 3268) had a higher risk (adjust hazards ratio (aHR) = 1.266, 95% confidence interval (CI) 1.014–1.581), and the stage 1 hypertension-decreasing group (n = 487) had the highest risk (aHR = 1.609, 95%CI 1.157–2.238). Among the BP-related indicators, the SBP trajectory was the strongest predictor of new-onset CHD. Findings were similar when sensitivity analyses were conducted. Conclusions SBP trajectory was a more important risk factor for CHD than other BP-related indicators and stringent BP control strategies may be effective for primary CHD prevention in the disabled population

The power of a healthy lifestyle for cancer prevention: the example of colorectal cancer

Objective: We aimed to directly compare the estimated effects of adherence to a healthy lifestyle with those of risk predisposition according to known genetic variants affecting colorectal cancer (CRC) risk, to support effective risk communication for cancer prevention. Methods: A healthy lifestyle score (HLS) was derived from 5 lifestyle factors: smoking, alcohol consumption, diet, physical activity, and body adiposity. The association of lifestyle and polygenic risk score (PRS) (based on 140 CRC-associated risk loci) with CRC risk was assessed with multiple logistic regression and compared through the genetic risk equivalent (GRE), a novel approach providing an estimate of the effects of adherence to a healthy lifestyle in terms of percentile differences in PRS. Results: A higher HLS was associated with lower CRC risk (4,844 cases, 3,964 controls). Those adhering to all 5 healthy lifestyle factors had a 62% (95% CI 54%–68%) lower CRC risk than those adhering to ≤ 2 healthy lifestyle factors. The estimated effect of adherence to all 5 compared with ≤ 2 healthy lifestyle factors was as strong as the effect of having a 79 percentile (GRE 79, 95% CI 61–97) lower PRS. The association between a healthy lifestyle and CRC risk was independent of PRS level but was particularly pronounced among those with a family history of CRC in ≥ 1 first-degree relative (P-interaction = 0.0013). Conclusions: A healthy lifestyle was strongly inversely associated with CRC risk. The large GRE indicated that CRC risk determined by polygenic risk may be offset to a substantial extent by adherence to a healthy lifestyle

2.6 μm MBE grown InGaAs detectors with dark current of SRH and TAT

We fabricate 2.6 μm InGaAs photodetectors by MBE technology and study its dark current mechanisms. Deep-level transient spectroscopy (DLTS) demonstrates a deep-level trap located at Ec - 0.25 eV in the absorption layer. Using the trap parameters, a dark current model is constructed and the device simulation generates the dark current characteristic which agrees well with the experimental data. The model suggests that the dark current at low reverse voltage is dominated by the Shockley-Read-Hall (SRH) and trap-assisted tunneling (TAT). Furthermore, it predicts some basic rules for suppressing the dark current in 2.6 μm InGaAs detectors

Additional file 1 of Prevalence and associated risk factors for chronic kidney disease in the elderly physically disabled population in Shanghai, China: a cross-sectional study

Additional file 1: Table S1. Normal reference range of blood pressure and blood biochemistry indicators. Table S2. The mean value of blood pressure and blood biochemistry among study population with CKD group and Non-CKD group. Table S3. Baseline characteristics of I-II disability population with CKD group and Non-CKD group. Table S4. Baseline characteristics of III-IV disability population with CKD group and Non-CKD group. Table S5. Multiple logistic regression analysis of the risk factors of CKD among I-II disability population. Table S6. Multiple logistic regression analysis of the risk factors of CKD among III-IV disability population