To explore the risk factors of re-admission of schizophrenic patients within one year after discharge and to establish a risk prediction model of re-admission.

By using cluster sampling, 353 inpatients with schizophrenia in a large mental hospital from July to December 2020 were collected from the in-patient electronic medical record and discharge follow-up system. Based on their demographic and clinical data, Logistic regression analysis was used to analyze the risk factors of re-admission within one year after discharge.

Four predictive factors were included: course of disease ≥ 20 years (OR=2.373, 95%CI: 1.242-4.533), combination of antipsychotics (OR=2.07, 95%CI: 1.211-3.538), underlying disease (OR=1.893, 95%CI: 1.111-3.226), and harmful behavior (OR=11.219, 95%CI: 5.544-22.701). The prediction model fitted well (χ² =3.444, P=0.903): the area under the receiver operating characteristic curve of the subjects was 0.805, the sensitivity was 82.6%,and the specificity was 65.6%. The results of Bootstrap re-sampling (n=1 000 times) showed that the model was stable.

The predictive model based on demographic and clinical data can be used as a tool to identify the schizophrenic patients at high risk of re-admission in the early stage.

To understand the current situation, influencing factors, and urban-rural heterogeneity of overweight/obesity among the elderly in China, so as to provide basis for formulating corresponding intervention measures.

The data of people age ≥ 60 years old in China Family Panel Studies (CFPS) database in 2020 were used. Unconditional binary logistic regression was used to analyze the influencing factors of overweight/obesity in the elderly.

A total of 4 870 eligible samples were included in this study, of which 1 903 were overweight/obese, and the overweight/obesity rate was 39.08%(33.10% in rural areas and 36.56% in urban areas). People aged 60-69 (OR = 2.145, 95%CI: 1.559-2.951), 70-79 years old (OR = 1.752, 95%CI: 1.270-2.416), suffering from chronic diseases (OR = 1.215, 95%CI: 1.061-1.392), smoking (OR = 0.651,95%CI: 0.556-0.763), living in the central China (OR = 1.255, 95%CI: 1.052-1.498), eastern China (OR = 1.378, 95%CI:1.169-1.623), living in town (OR = 1.366, 95%CI: 1.193-1.565), with primary school education (OR = 1.214, 95%CI: 1.034-1.427), retirement pension (OR = 1.342, 95%CI: 1.126-1.599), and endowment insurance (OR = 0.841, 95%CI: 0.739-0.956) were the influencing factors of overweight/obesity in the elderly. People aged 60- 69 (OR = 2.333, 95%CI: 1.561-3.487), 70-79 years old (OR = 2.057, 95%CI: 1.372-3.084), suffering from chronic diseases (OR = 1.364, 95%CI: 1.132-1.645), smoking (OR = 0.705, 95%CI: 0.563-0.881), living in the eastern region (OR = 1.278, 95%CI: 1.006-1.623). with primary school education (OR = 1.397, 95%CI: 1.104-1.768), and retirement pension (OR = 1.284, 95%CI: 1.046-1.577) were the influencing factors of overweight/obesity of the urban elderly. People aged 60-69 years old (OR = 1.779, 95%CI: 1.048-3.021), smoking (OR =0.594, 95%CI: 0.473-0.747), living in central China (OR = 1.28, 95%CI: 1.010-1.647), eastern China (OR = 1.481, 95%CI:1.176-1.867), retirement pension (OR = 1.424, 95%CI: 1.003-2.022), and new rural cooperative medical system (NCMS) (OR =0.475, 95%CI: 0.261-0.862) and health insurance for urban/rural residents (OR = 0.615, 95%CI: 0.380-0.995) were the influencing factors of overweight/obesity of the rural elderly.

The influencing factors of overweight/obesity in the elderly are multi-level and multi-dimensional and vary between urban and rural areas. Timely and targeted preventive strategies and preventive measures should be taken from individual to macro dimensions, based on the current situation of urban-rural differences in China.

To investigate the effect of night shift work on metabolic syndrome (MS) in railway workers.

In total 7 635 railway workers who took part in the physical examination in the First Affiliated Hospital of Guangdong Pharmaceutical University from September to December 2021 were selected as the research subjects. Logistic regression was used for correlation analysis and restricted cubic spline (RCS) was used to analyze the dose-response relationship.

The prevalence rate of metabolic syndrome in railway workers was 15.1%. After adjusting the confounding factors, former night shift (OR=1.198, 95%CI: 1.002-1.431) and current night shift (OR=1.219, 95%CI: 1.048-1.417), night shift duration of 6.0 ~ < 11.0 years (OR=1.323, 95%CI: 1.092-1.603) and ≥ 11.0 years (OR=1.256, 95%CI: 1.029-1.534), night shift twice a week (OR=1.269, 95%CI: 1.074-1.498), 3 times (OR=1.217, 95%CI: 1.001-1.479), and ≥ 4 times (OR=1.295, 95%CI:1.032-1.623) were significantly associated with the prevalence of MS in railway workers. The results of RCS showed that there was a linear positive correlation between the working years of night shift and the risk of MS (P _total < 0.001, P _non-linear=0.0760). The risk of MS began to increase after 1 year of night shift and reached the highest after 14.1 years.

Night shift work will lead to an increase in the risk of MS among railway workers, and the higher the number of years of night shift work, the higher the risk.

To analyze the current situation and potential influence paths of social support, imbalance of effort and reward, and sleep quality on self-rated health of male oil drilling crew workers in southwest China.

By using the method of cluster sampling, 1 951 male oil drilling crew workers were investigated, and a structural equation model was established to analyze the effects and pathways of social support, imbalance of effort and reward, and sleep quality on self-rated health.

The average score of social support of the sample population was 38.13 ± 9.02, 53.0% was with low reward, the average score of sleep quality was 6.39 ± 3.72, and 47.8% of the workers rated their health as average/relatively poor/poor. The results of structural equation model showed that social support (β = 0.123, 95%CI: 0.080-0.166) and sleep disorder (β =-0.407,95%CI: -0.447 to -0.364) respectively had a direct effect on self-rated health. The mediating effect of sleep disorder and its chain intermediary effect on effort and reward imbalance were 0.008 (95%CI: 0.006-0.010) and 0.005 (95%CI: 0.004-0.006),respectively.

The social support, effort and reward, sleep quality, and self-rated health status of male oil drilling crew workers in southwest China are poor. Social support and sleep disorder have a direct effect on self-rated health, and the imbalance of effort and reward and sleep disorder play an intermediary role in the effect of social support on self-rated health.

To explore the relationship between volatile organic compounds (VOCs) exposure and sleep problems in adults.

This study included 5 337 participants from the 2007-2014 National Health and Nutrition Examination Survey (NHANES) database. Weighted logical regression model and weighted quartile sum (WQS) regression model were used to evaluate the association of blood VOCs with short sleep duration (SSD), difficulty in falling asleep, and sleep disorders in adults.

After adjusting the confounding factors, blood benzene (OR = 1.120, 95%CI: 1.019-1.230, P = 0.02), 2,5-dimethylfuran (OR = 1.144, 95%CI: 1.043-1.254, P = 0.005), ethylbenzene (OR = 1.115, 95%CI: 1.025-1.211, P = 0.012), furan (OR =1.271, 95%CI: 1.086-1.489, P = 0.004), and o-xylene (OR = 1.097, 95%CI: 1.006-1.198, P = 0.037) had a significant positive correlation with SDD. Secondly, 2,5-dimethylfuran (OR = 1.082, 95%CI: 1.008-1.161, P = 0.03) and furan (OR = 1.148,95%CI: 1.002-1.315, P = 0.046) were positively correlated with difficulty in falling asleep. Subgroup analysis showed that the positive association between VOCs and SSD was consistent among different groups. WQS results showed that for every unit of increase, SSD risk increased by 25.4% (OR = 1.254, 95%CI: 1.009-1.559, P = 0.041).

There is a positive correlation between VOCs exposure and SSD in American adults.

To investigate the prevalence and influencing factors of abnormal bone mass in postmenopausal women of Dong and Miao ethnic groups in Guizhou Province, and to establish a nomogram prediction model and verify it, so as to provide theoretical basis for the prevention of abnormal bone mass in ethnic minority postmenopausal women in Guizhou Province.

This study was a cross-sectional study. In total 3 208 postmenopausal women of Dong and Miao ethnic groups were selected from the cohort study database of natural population of ethnic minorities in southwest China, and ultrasonic bone densitometer was used to measure calcaneal bone mineral density (BMD). The concentrations of cadmium, cobalt, copper, chromium, iron, mercury, manganese, molybdenum, nickel, lead, strontium, vanadium, and zinc in urine were determined by inductively coupled plasma mass spectrometer, and the relationship between urine metal, demographic characteristics, reproductive characteristics, ethnic diet, and BMD was analyzed by binary logistic regression, and the risk prediction model of bone mass abnormality was established.

A total of 3 208 people were included in the study, and a total of 1 520 people with abnormal bone mass were detected. The detection rate of abnormal bone mass was 47.38%. Based on age (OR=1.098, 95%CI: 1.083-1.113),history of bone fracture (OR=0.560, 95%CI: 0.395-0.794), age of menopause (OR=0.965, 95%CI: 0.949-0.982), number of live births (OR=0.900, 95%CI: 0.818-0.990), use of contraceptive (OR=0.708, 95%CI: 0.555-0.901), total physical activity (OR=0.989, 95%CI: 0.984-0.994), urinary cadmium (OR:1.060, 95%CI:1.009-1.113), and urinary chromium (OR=1.004, 95%CI:1.001-1.008) were independent influencing factors of abnormal bone mass. To establish a predictive model Logit (P) for predicting the risk of abnormal bone mass in postmenopausal women: Logit (P) =-2.170+0.093 * (age)-0.580 * (history of bone fracture)-0.035 * (menopausal age)-0.105 * (number of live births)-0.346* (whether or not you have taken contraceptive)-0.011 *(total physical activity) + 0.058 * (urinary cadmium) + 0.004 * (urinary chromium). The area under the receiver operating characteristic curve of the model was 0.722. The nomogram was drawn and verified internally. The results showed that the calibration curve predicted by the model for abnormal bone mass was basically consistent with the actual curve, and the fitting effect was good.

Cadmium and chromium are independent risk factors of abnormal bone mass, indicating that metal exposure can affect the occurrence and development of abnormal bone mass. The prediction model and score diagram of bone mass abnormality have good predictive ability, which provides a reference for screening abnormal bone mass of minority postmenopausal women in Guizhou Province.

To explore the relationship between hormone replacement therapy (HRT) and the time period when postmenopausal women received HRT and accelerated biological aging.

Based on the biochemical and anthropometric data collected from the UK Biobank baseline survey, the biological age (BA) and BA acceleration index were constructed by Klemera Doubal method (KDM). The subjects were divided into 5 groups according to the status of receiving HRT: no, 10 years before menopause, 0-10 years before menopause, 0-10 years after menopause, and 10 years after menopause. Multivariate linear regression model was used to explore the relationship between HRT and BA acceleration. The characteristic factors of the population were taken as stratified factors for stratified analysis.

A total of 96 889 subjects were included. Compared with people who did not receive HRT, there was a correlation for starting HRT 0-10 years before menopause (β=-0.28, 95%CI:-0.36 to -0.19) and starting HRT postmenopausal 0-10 years (β=-0.39, 95%CI: -0.46 to -0.31) with the delayed accelerated aging. The effect of HRT on delaying and accelerating aging was more obvious in postmenopausal women less than 60 years old.

Receiving HRT slows biological aging and is more effective when used within 10 years of menopause in postmenopausal women under 60 years of age.

To explore the mediating role of self-esteem in the relationship between childhood adverse experiences (ACEs) and depressive symptoms of junior high school students, and the regulatory effect of social support.

A total of 1 308 students from 3 junior middle schools in Xiangxi were selected by stratified random cluster sampling from February to April 2023. A questionnaire survey was conducted with the use of Childhood adverse experience questionnaire, Adolescent social support scale, PHQ-9 Depression symptom screening scale, and Rosenberg self-esteem scale. The data were analyzed by correlation analysis, intermediary analysis, and moderated intermediary model test.

(1) ACEs positively predicted depressive symptoms of junior high school students (β=0.801, t=7.246, P<0.05), while self-esteem and social support negatively predicted depressive symptoms of junior high school students (β=-0.406, t=-14.276, P < 0.05; β =-0.027, t=-2.781, P < 0.05). (2) Self-esteem played a mediating role between ACEs and depressive symptoms (effect=0.468, P < 0.05), and the mediating effect accounted for 31.33% of the total effect. (3) Social support directly regulated the relationship between ACEs and depressive symptoms (β=-0.017, t=-3.043, P<0.01), and social support played a regulatory role in the latter half of the mediating pathway of “ACEs self-esteem and depressive symptoms” (β=-0.004, t=-2.887, P<0.01).

There is a mediating effect between ACEs and depressive symptoms of junior high school students, and self-esteem is the mediating variable of the relationship between them. Social support buffers the influence of ACEs on the risk of depressive symptoms of junior high school students and strengthens the relationship between self-esteem and depressive symptoms. Therefore, giving more care and social support to junior high school students with ACEs and improving their self-esteem will help prevent and reduce the occurrence of depressive symptoms.

To understand the current situation of non-suicidal self-injury (NSSI) behavior among middle school students in Taiyuan, and to explore the relationship between socio-ecological risk factors and NSSI behavior of middle school students, so as to provide evidence for targeted intervention strategies.

A total of 2 635 middle and high school students in Taiyuan were selected by stratified random cluster sampling. The general demographic characteristics, the risk level of social ecology, and the occurrence of NSSI behavior in the past year were investigated. Binary Logistic regression was used to analyze the relationship between NSSI behavior and socio-ecological risk factors.

The reporting rate of NSSI behavior of middle school students was 13.5%. There were significant differences in NSSI behavior report rate among middle school students with different genders (χ²=11.12), the number of close friends (χ²=30.52), and different learning burden (χ²=37.51). After adjusting gender, the number of close friends, and learning burden factors (all P<0.01), the Logistic regression model took the low risk level of social and ecological risk factors as the control group, high risk personal factor (OR=2.93, 95%CI: 1.87-4.59), high risk family factor (OR=3.10, 95%CI: 2.04-4.71), moderate risk family factor (OR=2.08, 95%CI: 1.40-3.08), high risk school factors (OR=2.36, 95%CI:1.48-3.76), and high risk cultural factors (OR=1.44, 95%CI: 1.01-2.06) were positively correlated with NSSI behavior of middle school students.

When middle school students are exposed to high risk levels of individuals, families, schools and cultures in the social ecosystem, the risk of NSSI behavior will increase. While carrying on the intervention of personal, family and school factors, we should also pay attention to the influence of cultural factors on the NSSI of middle school students.

To analyze the relationship between nicotine dependence and depression among the elderly of Dai ethnic group in Jinggu county, Yunnan Province.

By using the method of multi-stage stratified random sampling,1 409 rural Dai people aged 60 and over in Jinggu county, Yunnan Province were investigated by face-to-face questionnaire.

The current smoking rate of rural Dai elderly in Jinggu county, Yunnan Province was 18.6% (37.1% for males and 0.8% for females). The smoking rate of males was significantly higher than that of females (P < 0.01). At present, the nicotine dependence rate of smokers was 32.8% (32.4% for males and 50.0% for females). There was no significant difference in nicotine dependence among Dai elderly people of different genders (P > 0.05), age groups (P > 0.05), education (P > 0.05), and annual family per capita income (P > 0.05). The prevalence rate of depression in the surveyed population was 52.0% (49.4% for males and 54.5% for females). Multivariate Logistic regression model analysis showed that patients with nicotine dependence were more likely to suffer from depression than those without nicotine dependence (OR=1.517, 95%CI: 1.066-2.158).

Nicotine dependence is positively correlated with depression in the elderly of Dai ethnic group in Yunnan Province. Taking effective measures to reduce the nicotine dependence rate of smokers is helpful to improve the mental health level of the elderly.