With the population aging, mental health of the middle-aged and elderly adults is of great concern, especially in middle-aged and elderly women. Compared with urban women, rural women are more likely to suffer from mental diseases due to their poorer health status, lower education level and backward living conditions, however, the accessibility of mental health services among them is low.
To understand the prevalence of depression among middle-aged and elderly women in rural China and analyze its influencing factors, in order to provide empirical evidence for improving the mental health of middle-aged and elderly women.
From May to July 2021, the follow-up data of the 2018 China Health and Retirement Longitudinal Study (CHARLS) was extracted, and rural women aged 45 years and above were selected as the study subjects (n=6 736) . The scores of the simplified version of the Center for Epidemiologic Studies Depression Scale (CES-D) were used to determine the depression status of rural middle-aged and elderly women. Chi-square tests and multivariate Logistic regression model were used to analyze the influencing factors of the occurence of depressive symptoms among rural middle-aged and elderly women (including individual characteristics, health behaviors, social participation and utilization of medical services utilization) .
The CES-D score of 6 736 rural middle-aged and elderly women was (20.0±6.9) , 42.46% (2 860/6 736) of whom had depressive symptoms. The results of multivariate Logistic regression analysis showed that satisfication with health status〔OR (95%CI) =0.40 (0.36, 0.45) 〕, sleep duration ≥6 h〔OR (95%CI) =0.48 (0.43, 0.54) 〕, Internet use〔OR (95%CI) =0.63 (0.50, 0.80) 〕 and satisfication with life 〔OR (95%CI) =0.25 (0.21, 0.30) 〕 were correlated with lower risk of depression; hysical disability〔OR (95%CI) =1.41 (1.16, 1.71) 〕, suffering from chronic diseases〔OR (95%CI) =1.35 (1.21, 1.50) 〕, receiving outpatient services within 1 month〔OR (95%CI) =1.25 (1.09, 1.43) 〕 and hospitalization services within 1 year〔OR (95%CI) =1.31 (1.13, 1.52) 〕 were correlated with higher risk of depression.
Based on the results of this study, the depression status of middle-aged and elderly women in rural China is relatively severe and affected by individual characteristics, health behaviors, social participation, and the medical services utilization. It is recommended that governments and civil affairs departments at all levels pay close attention to the mental health of rural middle-aged and elderly women, especially through the intervention and prevention from multiple dimensions such as health promotion and education, medical service quality, and accessibility of information, in order to promote the construction of healthy villages and process of health aging in China.
China is facing an increasing number of chronic disease patients. Health-related quality of life (HRQoL) is an important indicator assessing the effect of prevention and treatment measures for chronic diseases, so it is important to select an appropriate HRQoL measurement tool for these patients.
To compare the validity, consistency and correlation of the Chinese Medicinal Quality of Life scale (CQ-11D) , Short-form 6-dimension version 1 (SF-6Dv1) , and the 3-level version of EQ-5D (EQ-5D-3L) in terms of utility values measuring HRQoL in chronic disease patients, and to identify a scale that is most applicable to Chinese chronic disease patients.
From February 2021 to April 2021, this study recruited the initial sample of Chinese people using quota sampling with quotas based on sex and age from a total of 28 representative provinces, autonomous regions or municipalities selected from seven geographical regions (north China, northeast China, east China, central China, southwest China, northwest China, and south China, with 2 to 6 selected from each of the regions) . A face-to-face survey was used to collect the sample people's basic demographic information and the situation of chronic diseases, and self-reported HRQoL measured using the CQ-11D, SF-6Dv1 and EQ-5D-3L, respectively, then according to the survey results, those with chronic diseases were selected, and the utility values of the three scales in them were analyzed. Bland-Altman chart and intraclass correlation coefficient (ICC) were used to analyze the consistency and correlation of the three scales. Kruskal-Wallis H test was used for univariate analysis to determine whether or not there is a statistically significant difference between the utility values of the scales across age or sex groups.
A total of 692 chronic disease patients were finally included. The mean (standard deviation) of utility scores of CQ-11D, SF-6Dv1 and EQ-5D-3L scales were (0.855±0.168) , (0.793±0.132) and (0.876±0.136) , respectively. The top three prevalent chronic diseases were hypertension (n=275) , arthritis (n=128) and hyperlipidemia (n=124) . Histogram showed that EQ-5D-3L had obvious ceiling effect, and CQ-11D was more widely distributed. The Bland-Altman chart showed that the consistency between the three scales was relatively good, and the points within the 95% limits of agreement (LOA) were all about 95%. The strength of correlation between CQ-11D and visual analogue score (VAS) was the highest (P<0.001) . The ICC among the three scales ranged from 0.528 to 0.625, showing a moderate level of correlation (P<0.001) . Both Bland-Altman chart and ICC analysis showed that SF-6Dv1 and EQ-5D-3L had the best consistency. The results of analysis for the three chronic diseases in subgroups were similar to those in the total sample. Univariate analysis showed that male patients with hypertension or hyperlipidemia had higher utility scores of three scales than their female counterparts (P<0.05) . And the utility scores of three scales were the lowest in 60-year-olds and above among patients with hyperlipidemia.
The ceiling effect of EQ-5D-3L scale is obvious in patients with chronic diseases. CQ-11D demonstrated a wide range of distribution of utility values in measuring the three chronic diseases, which may be more suitable for measuring HRQoL in Chinese chronic disease population, as no ceiling effect was observed and its correlation with VAS was the strongest.
Mild cognitive impairment (MCI) is an important stage to intervene and delay the progression of dementia, and it has been shown closely associated with genetic factors, among which apolipoprotein E (APOE) ε4 is recognized as an important risk allele of MCI in the medical field. Due to the lack of Genome-Wide Association Study (GWAS) summary data of MCI, it is common to use the GWAS summary data of Alzheimer's disease (AD) as the base dataset to calculate the polygenic risk score (PRS) of MCI, resulting in suboptimal PRS genetic risk prediction for MCI.
To explore the and optimize the statistical modeling strategy of genetic risk in MCI from the perspective of generalized linear model and machine learning, using meta-polygenic risk score (metaPRS) and APOEε4 as important predictors.
PRS for the 12 MCI-related traits were calculated and integrated into metaPRS for MCI by elastic-net Logistic regression model. SCOREAPOE was calculated by weighting the APOEε4 effect size with age correction. XGBoost, GBM, Logistic regression and Lasso regression were used as statistical modeling methods to verify the inclusion strategies of different predictors based on metaPRS, SCOREAPOE and basic demographic information (age, gender, education level) . AUC and F-measure were used to evaluate the predictive effect of statistical modeling of genetic risk of MCI.
metaPRS and SCOREAPOE have high predictive value for the genetic risk of MCI. After including metaPRS, SCOREAPOE and basic demographic information (age, gender, education level) , the predictive effect of each statistical modeling method is XGBoost (AUC=0.69, F-measure=0.88) , GBM (AUC=0.76, F-measure=0.87) , Logistic regression (AUC=0.77, F-measure=0.89) , and Lasso regression (AUC=0.76, F-measure=0.92) .
When the sample size is 325 (less than 500) , the Lasso regression model constructed by including metaPRS, SCOREAPOE and basic demographic information (age, gender, education level) as predictors has the best effect on MCI genetic risk prediction, providing a new idea and perspective for statistical modeling of genetic risk of complex diseases such as MCI.
The development of traditional Chinese medicine (TCM) has been listed as a national development strategy with vigorous improvement of TCM service capacity in primary care institutions as the important elements, however, there are few studies on the disease spectrum of TCM in community health service institutions.
To analysis the TCM disease spectrum in outpatient clinics of contracted residents by family doctors in Shenzhen community health service centers (abbreviated as CHSC) and understand the capability of TCM in Shenzhen health centers, thus providing a theoretical basis for promoting the development of TCM in primary care in China.
From May to June 2022, the records of outpatient consultations with treatment cost of 10 Shenzhen CHSCs from 2021-01-01 to 2021-06-30 were extracted by the unified information platform of the Health Commission of Shenzhen Municipality (Hangchuang Community Health Service Center Business System) . The 385 138 records with purpose of TCM treatment, matching diagnosis and treatment costs, first diagnosis can be coded in Classification and Codes of Diseases and ZHENG of Traditional Chinese Medicine (TCD) were collected. The disease spectrum was analyzed based on the classification of disease in TCD, mainly involving department categories, specialty system classifications, and TCM disease terms.
A total of 385 138 records of TCM diagnosis and treatment were selected in this study, including 170 077 (44.16%) male cases and 215 061 (55.84%) female cases, with an average age of (36.7±9.4) years. All of the 7 TCD categories of disease spectrum were involved, including internal medicine accounting for 56.98% (219 445 cases) , pediatrics accounting for 20.56% (79 201 cases) , otolaryngology accounting for 12.45% (47 965 cases) , gynecology accounting for 7.95% (30 620 cases) , surgery accounting for 1.51% (5 797 cases) , orthopedics accounting for 0.37% (1 407 cases) and ophthalmology accounting for 0.18% (703 cases) . Apart from the specialty system classifications of tumor diseases, cancer diseases in each category, classifications of middle canthal disease, black eye disease, pupillary disease, traumatic eye disease in Ophthalmology, the disease spectrum involves all specialty system classifications in 7 categories. The cumulative diagnosis and treatment volume of several disease spectrums accounted for 90.00% of the total diagnosis and treatment in each category. The top 5 system diseases in the spectrum included respiratory system diseases accounting for 54.19% (208 701 cases) , musculoskeletal system diseases accounting for 19.05% (73 369 cases) , gynecological system diseases accounting for 7.95% (30 620 cases) , cardiovascular and cerebrovascular system diseases accounting for 7.15% (27 539 cases) , and the digestive system diseases accounting for 4.98% (19 162 cases) . Patients aged <15 years and 15-24 years mainly suffered from diseases related to the respiratory and digestive systems, and the incidence of diseases such as paralysis, dizziness, headache, insomnia, fatigue were increased with the increase of age; cold ranked the first for patients aged below 45 years, the paralysis of muscle and joint pain ranked the first for patients aged above 45 years.
The TCM diseases spectrum in Shenzhen CHSCs is wide, but the categories are relatively concentrated and single, mainly involving internal medicine, concentrating on respiratory system diseases, musculoskeletal system diseases, gynecological system diseases, cardiovascular and cerebrovascular system diseases, and digestive system diseases. It is necessary to strengthen and expand the TCM diagnosis and treatment capabilities in CHSCs to better meet diverse health needs of the residents.
