To develop the influenza vaccine hesitation scale for the elderly aged 60 and above and evaluate its applicability.

Based on the Chinese version of the parents’ hesitation scale for children’s influenza vaccination, combined with the characteristics of the elderly population, the influenza vaccine hesitation scale for the elderly aged 60 and above was developed, and the reliability and validity of the scale were evaluated.

The scale finally included 3 dimensions and 14 items, the score of the total scale was 32.82 ±7.99, and the correlation coefficient between each item and the score of the total scale was between 0.20 and 0.87 (all P < 0.05). Exploratory factor analysis showed that the Kaiser-Meyer-Olkin （KMO） value of the scale was 0.916 (χ²_{approximation} = 14 315.26, P<0.05). Confirmatory factor analysis showed that the cumulative variance contribution rate of 14 common factors was 80.6%, GFI=0.909, IFI=0.961, TLI=0.952, and CFI=0.961,indicating that the overall fitness and structural validity of the model were good. Taking whether the elderly were vaccinated with influenza vaccine or not in the influenza season in 2022, the total vaccine hesitation score and the scores of “confidences”,“risk” and “support” were significantly correlated with the school standard (all P < 0.05). The Cronbach’s α coefficient of the scale was 0.859, indicating that the internal consistency reliability of the scale was high.

The influenza vaccine hesitation scale for the elderly developed in this study is good in reliability, validity and applicable stability, which can be used to evaluate the hesitation level of influenza vaccine in people aged 60 and above.

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 analyze the current situation of cognitive function of the elderly in China and the influence of internet use on the cognitive function of the elderly.

In total 10 546 people aged 60 and above were included in the study. The t-test and variance analysis were used to analyze the differences of cognitive function among elderly groups with different characteristics. Multiple linear regression model was used to explore the effect of internet use on the cognitive function of the elderly.

A total of 2 987 elderly people used the internet, accounting for 28.32% of the total, and the average score of cognitive function of the elderly who used the internet was 14.75±1.86. The average score of cognitive function of the elderly who had not used the internet was 13.34±2.91. There was a significant difference between the two groups (t=-29.48, P < 0.001). The use of the internet was related to the cognitive function of the elderly (β = 0.12, 95%CI: 0.608-0.845, P < 0.001), and the cognitive function of the elderly who used the Internet was better.

Internet use has an impact on the cognitive function of the elderly, and it is suggested that targeted measures be taken to improve the cognitive function of the elderly.

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 summarize the key elements and shortcomings of relevant policies in the field of mental health in China, so as to provide reference for the formulation and improvement of follow-up policies in the field of mental health in China.

Using NVivo11Plus software and content analysis method, a two-dimensional analysis framework of “policy tool-policy object” was constructed to quantitatively analyze 141 relevant policy texts in the field of mental health at the national level from 1999 to 2023 in China.

China has paid growing attention to mental health, and the National Health Commission, the Ministry of Education, and the Ministry of Civil Affairs were the core departments of policy formulation. The internal structure of supply-oriented policy tools was out of balance, and the application of environmental policy tools was insufficient. Demand-based policy tools were the least used, accounting for 49.96%, 28.36%, and 21.68%, respectively. The policy object was concentrated in the whole system, health system, and education system, accounting for 32.81%, 24.59%, and 21.94%, respectively.

It is suggested that the policy design balance the structure of policy tools, increase the supply of resources, apply strategies and measures, strengthen mental health education and promotion, strengthen community grass-roots mental health services, and standardize the development of social mental health service institutions so as to improve mental health and mental hygiene policy system.

To investigate the relationship between frailty and social activity of the elderly in China, and to study the influencing factors of frailty in the elderly, so as to provide scientific basis for the healthy life of the elderly.

Based on 43 health related variables in China Health and Retirement Longitudinal Study (CHARLS) 2018 database, the frailty index (FI) was constructed to evaluate the frailty of the elderly. Binary logistic regression was used to explore the effect of social activity on the frailty of the elderly.

A total of 1 519 elderly people aged 60 and above were included in the CHARLS 2018 database, including 401 frail elderly, with a frailty rate of 26.4%. The participation rate of the elderly in social activities was 48.5%,and there were 439 elderly people with high level of social activity, accounting for 28.9% of the total. After adjusting for confounding factors, the risk of debilitation in the elderly with high level of social activity was 41.9%, lower than that in those with medium and low level of social activity (OR=0.581, 95%CI: 0.439-0.77).

The degree of social activity affects the frailty of the elderly, and the social activity of the elderly in China is generally low. The elderly should be encouraged to participate in social activities, and attention should be paid to the older and female elderly.

To explore the causal relationship between the characteristics of glycemic traits (fasting blood glucose, fasting insulin, glycosylated hemoglobin, and insulin resistance) and benign colorectal neoplasm (colorectal adenomas, benign rectal neoplasm, and benign colon neoplasm).

The instrumental variables of blood glucose characteristics were extracted from MAGIC and GLGCL alliance, and the genome-wide data of colorectal benign tumors came from Finn-Gen alliance. In this study, random effect inverse-variance weighted method (IVW), MR-Egger regression, and weighted median method (WMM) were used to analyze the causal relationship between four glycemic traits and benign colorectal neoplasm.

The results of IVW model showed that there was no causal relationship between fasting blood glucose (OR=0.999, 95%CI: 0.997-1.001), fasting insulin (OR=1.002, 95%CI: 0.998-1.006), glycosylated hemoglobin (OR=1.001, 95%CI: 0.999-1.004), insulin resistance (OR=0.999, 95%CI: 0.997-1.002), and colorectal adenoma. There was no causal relationship between fasting blood glucose (OR=0.909, 95%CI: 0.684-1.209), fasting insulin (OR=1.220, 95%CI: 0.706-2.107), glycosylated hemoglobin (OR=0.678, 95%CI:0.440-1.046), insulin resistance (OR=1.161, 95%CI: 0.810-1.663) and rectal benign tumor. There was no causal relationship between fasting blood glucose (OR=0.966, 95%CI: 0.836-1.116), fasting insulin (OR=1.318, 95%CI: 0.906-1.916), glycosylated hemoglobin (OR=1.124, 95%CI: 0.882-1.431), insulin resistance (OR=1.071, 95%CI: 0.875-1.311) and benign tumors of colon.

There is no evidence of causal relationships of fasting blood glucose, fasting insulin, glycosylated hemoglobin, and insulin resistance with colorectal adenomas, benign rectal neoplasm, and benign colon neoplasm.

To investigate the positive rate of HBsAg and HBsAb in the population born during 2004 and 2022 in Jiangxi Province.

By using stratified cluster sampling method, venous blood samples were collected from 8 126 people born after 2004 from 2016 to 2022 in 11 districts and cities of Jiangxi Province, and the sera were separated. HBsAg and HBsAb were detected by Elisa method, and the positive rate was calculated. The chi-square test was used to analyze the difference of positive rate among different groups.

The positive rates of HBsAg and HBsAb among people born during 2004 and 2022 in Jiangxi Province were 1.40% and 74.92%, respectively. The positive rates of HBsAg in males and females were 1.14% and 1.80%, respectively (χ²=6.18, P=0.013) and the positive rates of HBsAb were 75.55% and 74.00%, respectively (χ²=2.51, P=0.113). The positive rates of HBsAg were 1.17%, 1.31%, 2.14%, and 3.12% (χ²=13.49, P=0.004) at the age of 4, 9, 14, and 15 to 18 years, respectively, and the positive rates of HBsAb were 85.65%, 60.26%, 50.04%, and 46.42%, respectively (χ²=9.90, P <0.001). The positive rates of HBsAg and HBsAb in urban and rural areas were 1.62% and 1.14% (χ²=11.99, P=0.001), 74.18%and 75.81%, respectively (χ²=2.83, P=0.095). The positive rates of HBsAg and HBsAb in people born before and after 2012 were 2.18% and 1.14%, 52.18%, and 82.28%, respectively (χ²=7.64, P < 0.001). The positive rate of HBsAg in 11 districts and cities was between 0.45% and 2.79% (χ²=37.18, P < 0.001), and the positive rate of HBsAb was between 69.88% and 84.30% (χ²=65.61, P < 0.001).

The positive rate of HBsAg among the people born during 2004 and 2022 in Jiangxi Province is low, and the prevention and control of hepatitis B is effective. There are population and regional differences in the prevalence of HBsAg and HBsAb. Targeted measures should be taken to further improve the effect of prevention and control.

Based on the US National Health and Nutrition Survey from 2005 to 2021, an interpretable machine learning method was used to identify patients with depression in people over 65 years old.

The data of 2005 Mel 2018 and 2019-2020 were used as training set and test set, respectively, and three machine learning models of Lasso Logistic, random forest, and XG Boost were fitted. The best model of area under the curve (AUC) on the test set was selected and explained by interpretable machine learning model SHAP.

The AUC value of XG Boost model was the highest, which was 0.933 (0.912-0.954). Sleep problems, health problems, and eosinophil count were the top three important variables affecting senile depression. The absolute values of SHAP were 1.16, 0.83, and 0.55, respectively, which showed the main influencing factors of each individual.

Machine learning is superior to logistic regression model in predicting depression in the elderly. Interpretable machine learning can explain the model from the global and individual levels to make predictions, open the black box of machine learning models, and can be used as a supplement to machine learning models in practical application.

To explore the causal relationship between age-related hearing loss and Alzheimer’s disease through two-sample Mendelian randomized analysis.

Inverse variance weighted, MR-Egger regression, weighted median, simple model, and weighted model were used to evaluate the relationship between age-related hearing loss and the risk of Alzheimer’s disease. Sensitivity analysis (pleiotropy, heterogeneity, and leave-one-out test) was used to evaluate the robustness of the results.

Statistical results showed that there was no causal association between age-related hearing loss and Alzheimer’s disease (inverse variance weighting method: OR=1.0526, 95%CI: 0.7155-1.5485; MR-Egger: OR=1.1347, 95%CI:0.2123-6.0660; weighted median method: OR=0.8908, 95%CI: 0.5281-1.5025; simple model method: OR=0.7157, 95%CI:0.2505-2.0445; weighted model method: OR=0.7470, 95%CI: 0.3153-1.7698). These results were consistent with that of Alzheimer’s disease proxy cases (inverse variance weighting method: OR=0.9560, 95%CI: 0.9008-1.0146; MR-Egger: OR=0.9887, 95%CI: 0.7729-1.2647; weighted median method: OR=0.9487, 95%CI: 0.8752-1.0283; simple model method: OR=0.9597, 95%CI: 0.8147-1.1305; Weighted model method: OR=0.9632, 95%CI: 0.8298-1.1179). Sensitivity analysis showed that there was no significant heterogeneity or pleiotropy, indicating that the results were robust.

There is no evidence that age-related hearing loss is associated with an increased risk of Alzheimer’s disease.