To understand the characteristics of atmospheric PM_2.5 pollution elements and their health risk assessment in Zhuhai in recent years, in order to provide relevant basis for pollution control in Zhuhai.

From April 2020 to March 2023, PM_2.5 samples were collected on a monthly basis in three administrative regions of Zhuhai City, with a total of 756 samples obtained. The elemental contents in PM_2.5 were analysed by ICP-MS.The health risks were calculated using the US EPA inhalation exposure model.

Monthly analysis of PM_2.5 samples in Zhuhai within the range of 34 elements.The mass concentrations of most elements were low in summer and high in winter.The annual average concentration of heavy metal elements in the three years of monitoring, from highest to lowest, was Zn(64.1 ng/m³) >Mn(14.22 ng/m³) >Pb(10.9 ng/m³) >Cu(6.57 ng/m³) >As(2.41 ng/m³) >Ni(1.91 ng/m³) >V(1.83 ng/m³) >Cr(1.62 ng/m³) >Sb(1.21 ng/m³) >Cd(0.54 ng/m³) >Tl(0.13 ng/m³)>Co(0.12 ng/m³)>Hg(4.88×10^-3ng/m³).Compared with previous studies in Zhuhai, the mass concentration of each element has decreased, but Sb, Al, As, Cr, Ni and Se had a trend of rising again.A health assessment was conducted on 6 carcinogenic elements Cr, Co, Ni, As, Mo and Cd, as well as 10 non carcinogenic elements Al, V, Mn, Cu, Zn, Se, Sb, Ba, Hg, and Pb. The results showed that the risk of non carcinogenic elements was at an acceptable level for the population(HQ≤1). Cr and As had a carcinogenic risk(R>10^-6).

The health risks of non carcinogenic elements PM_2.5 in the atmosphere of Zhuhai City are all at an acceptable level for the population. Cr and As pose a cancer risk and require special attention. From the perspective of element mass concentration, fuel and transportation pollution are still the key points of governance.

To analyze the hemoglobin (Hb) levels and anemia status of students in the Fujian Province Nutrition Improvement Plan area from 2021 to 2022, and to analyze their influencing factors.

A total of 8 895 students were selected for the study using multi-stage stratified random cluster sampling method. According to the WHO anemia diagnostic criteria, the Hb levels and anemia rates of students of different ages and genders were analyzed, and the logistic regression models was used to analyze possible influencing factors of anemia.

From 2021 to 2022, the average Hb of students in rural nutrition improvement plan areas in Fujian Province was 134.44g/L, and the anemia rate was 7.21%. Multivariate logistic regression analysis showed that female students (OR=1.51, 95% CI: 1.28-1.78), schools located in townships or villages (OR=1.50, 95% CI: 1.71-1.91), schools with unified recipes provided by the education bureau (OR=3.80, 95%CI: 1.62-8.92), schools that have not conducted health education (OR=1.54, 95% CI: 0.09-0.62) and students who do not know how to prevent iron deficiency anemia (OR=1.29, 95% CI: 1.03-1.63) were risk factors for anemia among students; School canteens that provide meat at least 3 times a week for lunch (OR=0.74, 95% CI: 0.56-0.99), students who consume more than 14 table tennis balls per week (OR=0.78, 95% CI: 0.62-0.98), and students who consume ≥ 3 types of vegetables per day (OR=0.53, 95% CI: 0.32-0.89) were protective factors for anemia in students.

The anemia rate of students in rural compulsory education student nutrition improvement plan areas in Fujian Province is lower than the average level of implementing the national student nutrition improvement plan, but significantly higher than the anemia rate of children aged 6-17 nationwide. There is still great room for improvement in the anemia status of students, and targeted interventions are needed in future work to improve their anemia status.

To evaluate the reliability and validity of the Chinese version of the Social Connectedness Scale-Revised(SCS-R) in order to provide correct way of its application among psychiatric patients.

A convenience sampling method was employed to select 345 patients with different types of mental disorders from K Hospital in Shenzhen. The patients’ general demographic information and disease conditions were collected, and Chinese version SCS-R was used to assess their social connectedness status. Cronbach α and split-half reliability were calculated to evaluate the reliability of SCS-R. Structural, convergent, discriminant, and discriminative validity were performed to measure the validity. The sample was randomly divided into half, exploratory factor analysis was used to explore the internal dimension of SCS-R, and confirmatory factor analysis was used to compare the scale structure explored and compared with the other three existing scale structures.

The Cronbach α coefficients for the total scale, social connectedness, non-social connectedness, and integration sense sub scales were 0.922, 0.904, 0.887 and 0.740, respectively. The split-half coefficients were 0.908, 0.918, 0.875 and 0.760, respectively. Exploratory factor analysis identified a three-factor structure, and confirmatory factor analysis showed that the scale structure developed in this study had a better fit than the other three and could explain 62.253% of the total variance. Both convergent validity and discriminant validity had success rates of calibration experiment as 100%. The correlation coefficients indicated good discriminative validity for the three dimensions of the scale.

The Chinese version of the SCS-R scale has shown good reliability and validity among psychiatric patients, making it suitable for evaluating the social connectedness of this population.

To construct the Bayesian network model of H-type hypertension in middle-aged and elderly people, and to explore the influencing factors of H-type hypertension and the network relationship between factors, and the strength of each influencing factor on H-type hypertension.

A total of 1 119 middle-aged and elderly people who underwent physical examination in the hospital health management center from May 2022 to April 2023 were selected as the research objects and relevant data were collected. Univariate logistic regression analysis and multivariate logistic regression analysis models were used for preliminary screening of variables, “bnlearn” Bayesian network software package was used for model construction, and Netica software was used for model inference.

Logistic regression analysis model was used to screen the variables, such as age, gender, education level, smoking, drinking, body mass index(BMI), fasting blood glucose, etc. FBG, total cholesterol(TC), triglyceride(TG), high density lipoprotein cholesterol((HDL-C), low density lipoprotein cholesterol(LDL-C) and uric acid(UA) were included in the Bayesian network model. A Bayesian network model of H-type hypertension related factors in middle-aged and elderly people with 13 nodes and 16 directed edges was constructed by using 12 selected variables as network nodes. Age, FBG, TG, HDL-C and BMI were directly related to H-type hypertension, while gender, smoking, drinking, educational level, TC, LDL-C and UA were indirectly related to H-type hypertension. When the age was≥60years old, FBG≥6.85 mmol/L, BMI≥24.83 kg/m², HDL-C≥1.02 mmol/L, TG<1.6 mmol/L, the risk of H-type hypertension reached 0.565.

The Bayesian network model reveals the direct and indirect factors and correlation strength of H-type hypertension in middle-aged and elderly people, clarifies the complex network relationship between factors, and provides a scientific basis for early prevention of H-type hypertension in middle-aged and elderly people.

To explore the impact mechanism of peer relationship networks in children and adolescents on overweight and obesity, and to provide some empirical basis for the health management and intervention of overweight and obesity in children and adolescents.

Based on a sampling survey data on overweight and obesity among children and adolescents aged 7-17 in Nanchong City of Sichuan Province, social network analysis, regression analysis, and Bayesian network models were used to analyze the specific impact mechanism of peer relationship networks on overweight and obesity.

Logistic regression showed that high personal popularity(OR=0.001, 95% CI=0-0.026) and high personal activity(OR=0.084, 95% CI=0.009-0.790) were associated with reduced detection of overweight and obesity in children and adolescents, with a relatively stronger correlation between personal activity and obesity. In addition, high household income(OR=19.237, 95% CI=3.799-97.403), high-energy dietary patterns(OR=21.660, 95% CI=1.600-292.904), sitting still for more than 8 hours(OR=10.395, 95% CI=2.013-53.687) increased the risk of overweight and obesity. Long exercise time(OR=0.085, 95% CI=0.019-0.378), both parents have attended college(OR=0.023, 95% CI=0.003-0.169), and mental health(OR=0.030, 95% CI=0.006-0.147) Children and adolescents with high sleep quality(OR=0.006, 95% CI=0.001-0.045) had a lower risk of developing overweight and obesity. The BIC score of the Bayesian network model was -3 954.8. When both individual activity and popularity were set at the 0:1:0 level, the detection probability of overweight and obesity in children and adolescents was 0.126, which was at the lowest level. Adjusting for other intervention variables under the recommended appropriate social network level(i.e. moderate popularity and moderate activity), with the best effect on controlling exercise duration, the likelihood of overweight and obesity in children and adolescents will decrease to 0.044. If social network indicators, dietary habits, exercise duration, psychological and sleep conditions were controlled simultaneously, the detection probability of overweight and obesity was 0, which will achieve the best expected prevention of overweight and obesity detection.

Strengthening social networks, changing lifestyle habits, and improving dietary quality may be important links in the prevention and treatment of obesity in children and adolescents. Therefore, it is necessary to strengthen the responsibility of government departments to accelerate the construction of a comprehensive overweight and obesity prevention and control system.

Observational studies have proposed a link between frailty and chronic obstructive pulmonary disease. However, the causal relationship between the two diseases needs further investigation.

The study data were drawn from the GWAS dataset, in which the frailty data contained 175 226 samples, by selecting SNPs closely related to frailty as instrumental variables. Two-sample MR was applied to assess causality between diseases. Inverse variance weighting (IVW) methods were used as the main analyses. MR-Egger intercepts, MR-PRESSO and funnel plots were also used to detect horizontal multi-effects, and sensitivity analyses were performed using the “leave-one-out” and Cochran’s Q tests simultaneously.

IVW analysis showed that frailty genetic susceptibility increased the risk of COPD, with odds ratios (OR) of 1.935 (95% CI:1.178-13.179; P=0.009). No horizontal pleiotropism was observed in MR-Egger intercept (P=0.757), MR-PRESSO and funnel plots detection. In the test of heterogeneity (P=0.952), no heterogeneity was observed in the funnel plot. The “leave-one-out” did not reveal a single SNP with a biased effect on the instrumental variable.

The study findings suggest a possible positive causal relationship between frailty and increased risk of developing COPD.

To use disability-adjusted life years(DALYs) to assess unequal differences in the burden of disease due to diabetes across global socioeconomic groups.

Number of DALYs due to diabetes, age-standardized DALYs rates from the GBD database, 1990-2019, and national Human Development Index(HDI) data from the Human Development Report 2021-2022 were collected. The relationship between age-standardized DALY rates and HDI was analyzed to understand socioeconomic differences in diabetes disease burden. Calculation of Annual Percentage Change(APC) and Average Annual Percentage Change(AAPC) to assess temporal trends in the burden of diabetes disease during recent decades.

From 1990-2019, the number of DALYs due to diabetes globally increased from 28.3 million to 69.9 million, an increase of 146.85%, with the fastest growth(206.49%) in Lower middle-income countries. The age-standardized DALYs rates were negatively correlated with HDI(r=-0.480, P<0.001). Countries with medium HDI exhibit higher DALYs rates due to diabetes mellitus. From 1990-2019, the average annual increase in the rate of age-standardized DALYs was 0.78%(AAPC=0.78%, 95% CI=0.74% to 0.81%), and the average annual increase in the age-standardized mortality rate was 0.46%(AAPC=0.46%, 95% CI=0.41%～0.51%).

The global burden of diabetes disease has increased substantially over the last few decades, with the fastest growth in Lower middle-income countries. The age-standardized burden was higher in developing countries. Although a slower increase in the burden of diabetes was observed, the persistence of the increase in the burden of disease suggests that more diabetes prevention programs and health-care services should be made available to developing countries.

To investigating the impact of Financial Burden on Health-Related Quality of Life in elderly patients with Chronic Comorbid Conditions and its mechanisms.

A convenience sample of 493 chronic comorbid patients was extracted from two community health service centers in Yanji City. General information was collected using a questionnaire, and the Patient Experiences with Primary Care (ASPC) scale, Comprehensive Score of Financial Burden (COST), Herth Hope Scale, and SF-36 Health Survey were utilized for the investigation.Univariate analysis, partial correlation analysis, and testing a moderated mediation model was conducted.

(1) Financial Burden significantly predicted HRQoL(β=0.32, 95% CI:0.24-0.40, P<0.001);(2) Hope level partially mediated the relationship between Financial Burden and HRQoL (β=0.12, 95% CI:0.08-0.16, P<0.001), accounting for 37% of the total effect; (3) The direct predictive effect of Financial Burden on health-related quality of life (β=0.07, 95% CI:0.01-0.14，P<0.05) and the mediating role of hope in their relationship(β=0.13，95% CI：0.05-0.21，P<0.01) were both moderated by the core features of comprehensive primary care.

This study reveals the mechanism by which Financial Burden impacts HRQoL in elderly patients with chronic comorbidities. The findings emphasize the importance of enhancing economic support and hope levels for this patient group and highlight the role of comprehensive primary care function in mitigating the adverse effects of Financial Burden on HRQoL. These insights contribute to providing more comprehensive and effective medical services to patients with chronic comorbidities, alleviating the impact of Financial Burden, and enhancing their overall quality of life.

To realize rapid qualitative and quantitative detection of 13 triterpenoids in Wolfiporia cocos from Yunnan by ultra performance liquid chromatography coupled with quadrupole-time of flight mass spectrometry.

Triterpenoids in Wolfiporia cocos were extracted by ultrasonic extraction (methanol). The separation was carried on an ACQUITY UPLC © HSS C18 column (2.1 mm×50mm, 1.7μm) with, 10 mmol/L ammonium formate-0.1% formic acid aqueous solution and acetonitrile as mobile phase. The gradient elution flow rate was 0.5ml/min, with the column temperature of 30℃. Negative ion multiple reaction monitoring mode was used for detection. Qualitative and quantitative analysis using secondary mass spectrometry and accurate molecular weight.

13 triterpenoids in Wolfiporia cocos were good with in the linear ranges (r≥0.99). The spiked recoveries were from 80.35% to 116.92%, with relative standard deviations of 1.88% to 9.7%. 13 triterpenoids were detected in Wolfiporia cocos samples, and the total contents were between 79 433-85 900 mg/kg.

The method is simple, accurate, efficient and sensitive, and it is suitable for the qualitative and quantitative detection of 13 triterpenoids in Wolfiporia cocos.

To explore the correlation between visceral fat index(CVAI) and the incidence of diabetes in Chinese elderly population.

The data were obtained from the China Health and Retirement Longitudinal Survey(CHARLS) 2011 and 2015 waves. A total of 2 295 elderly people aged ≥60 years were included. Binary logistic regression was used to analyze the correlation between CVAI and the incidence of diabetes. The restricted cubic spline(RCS) method was used to test the dose-response relationship. Subgroup analysis was performed according to BMI.

333(14.50%) of the 2295 elderly participants developed diabetes during the 4-year follow-up period. CVAI were divided by quartiles. There were statistically significant differences in baseline FBG, HBA1c, SBP, DBP, TG, TC, HDL-C, LDL-C, UA, gender, smoking status, drinking status, hypertension history and follow-up incident diabetes among groups(P<0.05). Compared with the group with lowest quartile of CVAI Q1, the OR(95% CI) in the group the highest quartile of CVAI Q4 was 1.96(1.37-2.83). The restricted cubic splines model results showed that the higher CVAI accompanied by higher risk of incident diabetes in the elderly. Subgroup analysis showed that CVAI was independently associated with incident diabetes in both non-overweight and overweight/obese groups.

There is a positive association between CVAI the risk of diabetes mellitus in the elderly population. The control of visceral fat in the elderly is helpful to prevent the occurrence of diabetes.