Objective To analyze the differences in chronic disease multimorbidity trajectories and influencing factors between middle-aged and elderly agricultural and non-agricultural production operators. Methods Data from five waves of the China Health and Retirement Longitudinal Study (CHARLS) from 2011 to 2020 were used. Group-based trajectory modeling (GBTM) was applied to fit multimorbidity trajectories for both groups, and multivariable logistic regression analysis was conducted to identify factors influencing the trajectory groups. Results A total of 9 937 participants were included, with 5 010 in the agricultural group and 4 927 in the non-agricultural group. In the agricultural group, the multimorbidity trajectories were classified into three patterns: no-multimorbidity (19.22%, 963 cases), new-onset multimorbidity (56.45%,2 828 cases), and progressive multimorbidity (24.33%, 1 219 cases). In the non-agricultural group, four patterns were identified: no-multimorbidity (18.06%, 890 cases), new-onset multimorbidity (41.10%, 2 025 cases), progressive multimorbidity (33.65%, 1 658 cases), and high-growth multimorbidity (7.18%, 354 cases). Increasing age, obesity, sleep duration ≤6 hours, and poor psychological status significantly increased the risk of multimorbidity in both groups (P<0.05). Among agricultural group, overweight (OR=1.37, 95% CI: 1.14-1.65; OR=2.49, 95% CI: 2.01-3.08) and obesity(OR=2.21, 95%CI: 1.59-3.06; OR=5.58, 95% CI: 3.93-7.92) significantly increased the risks of multimorbidity. In the non-agricultural group, higher education levels reduced the risk of new-onset multimorbidity(OR=0.75, 95% CI: 0.60-0.95), and moderate physical activity decreased the risk of high-growth multimorbidity(OR=0.68, 95% CI: 0.52-0.90). Smoking cessation was significantly associated with increased risks of multimorbidity (OR=1.55, 95% CI: 1.04-2.32; OR=2.37, 95% CI: 1.57-3.57; OR=4.02, 95%CI: 2.31-7.00). Conclusion In agricultural populations, the new-onset multimorbidity type is dominant, driven by obesity and insufficient sleep. In non-agricultural populations, the high-growth multimorbidity type is associated with poor psychological status and health deterioration after smoking cessation. It is necessary to strengthen weight and sleep management for agricultural populations and focus on mental health as well as post-cessation monitoring for non-agricultural populations to reduce the risk of multimorbidity.

Objective To establish a paper spray mass spectrometry method for the determination of 1-methoxy-2-propanol and 2-methoxypropionic acid as biomarkers of propylene glycol monomethyl ether in urine. Methods The urine sample was dropped onto the chromatographic paper, and a high voltage of 4 kV was applied to the back of the paper. After dissolution in the spray solvent, the sample formed an electrospray at the paper tip under the effect of voltage, which then entered the mass spectrometer for detection. Results The linear ranges of 1-methoxy-2-propanol and 2-methoxypropionic acid were 0.036-46.15 μg/mL and 0.029-54.25 μg/mL, respectively, with correlation coefficients ranging from 0.999 6 to 0.999 9. The detection limit (LOD) was between 0.008 8 and 0.011 μg/mL, and the quantification limit(LOQ) was between 0.029 and 0.036 μg/mL. The sample recovery rate ranged from 90.8% to 105.0%, and RSDs ranged from 3.3% to 9.7%. Conclusion This method requires no sample processing, features simplicity, rapidity and high sensitivity, making it suitable for the rapid screening of propylene glycol monomethyl ether in urine.

Objective Based on the Python platform, the entire process of vector-borne infectious disease mathematical models is expanded to better fit models and evaluate intervention effects, to provide new ideas for grassroots prevention and control, and to open up new perspectives. Methods The SmEmIm-SpEpIpApRp model was fitted using the lmfit library, solved with the solve_ivp function, and sensitivity analysis of key model parameters was performed. The Rt calculation was based on the next generation matrix method, and all results were visually displayed with the help of Matplotlib. Results The results showed that R²=0.98 and RMSE=2.07. Rt was 5.607 in the early stage of the epidemic, and Rt_peak was 8.439 on day 41. The period with Rt>1 lasted 81 days, and q had the highest sensitivity (S=35.435). Under a single intervention, when β_mp and β_pm<0.01, Rt<1 and the epidemic disappeared. Controlling only γ and q would not eliminate the epidemic. Under comprehensive intervention, Scenario 1 could reduce the cumulative cases by 98.64%, and Rt_peak=0.868. Scenario 2 could reduce the cumulative cases by 87.95%,and Rt_peak=1.988. For Scenario 3, Rt_peak=4.78. Although the increase in Rt was smaller and the change rate was low, the longer duration could increase cumulative cases by 161.47%. Scenario 4 could reduce the cumulative cases by 99.38%, and Rt_peak=0.28. Conclusions The high goodness of fit of the model based on the Python platform verifies the necessity of seasonal dynamic modeling, provides an integrated solution for the prevention and control of vector-borne infectious diseases, expands the practical boundaries of theoretical models, and opens a new perspective for precise prevention and control at the grassroots level.

Objective The study aims to analyze the types and causes of multiple misalignment between supply and demand of health and wellness services in China, with a view to providing novel and operable theoretical perspectives and practical paths for solving the problem of misalignment between supply and demand and breaking through the bottlenecks of current health and wellness services. Methods A meta-ethnographic approach was adopted to analyse 16 original studies, to scientifically classify the types of multiple misalignment between supply and demand of health and wellness services in China, and to systematically deconstruct their causes with the help of the ROCCIPI technology framework. Results This study summarized the significant misalignment between supply and demand of health and wellness services in China in terms of quantity matching, quality satisfaction, structural rationality and information symmetry. Then, the root causes of the misalignment were analyzed from the seven core dimensions of rule-making and enforcement, opportunity grasping, capacity provision, information exchange, benefit distribution, process optimization, and awareness enhancement. Conclusion It is suggested to focus on five core dimensions, including collaborative participation of multiple stakeholders, dynamic requirements identification, efficient resource integration, integration of digital and intelligent technologies, and cultivation of professional talents, so as to promote the precise matching and sound development of supply and demand in health and wellness services.

Objective This study investigates the mediating effects of general self-efficacy and social participation on the relationship between physical function and physical resilience (PR) among older adults. Methods The elderly in five communities selected by cluster sampling in Xinxiang City were surveyed using the Simplified Physical Fitness Test Scale,Physical Resilience Scale, General Self-Efficacy Scale, and the Social Participation Scale from March to November 2024.Descriptive statistics, variance analysis, and correlation analysis were conducted, and a chain mediation effect model was constructed using Mplus 8.3. Results A total of 1 071 elderly people in the community were surveyed, the PR score of the elderly in the community was (48.81±5.66), and the PR of the elderly was positively correlated with physical function, general self-efficacy, and social participation (all P<0.05). After including control variables such as age, sleep duration, and living arrangement, general self-efficacy and social participation played a chain mediating effect between physical function and PR,with a mediating effect value of 0.311, accounting for 55.24% of the total effect. Conclusion Physical function in the elderly can directly affect PR, and can also indirectly affect PR through general self-efficacy and social participation. The PR of older adults can be improved by improving their physical functioning, self-efficacy, and social participation.

Objective To analyze the changes in the disease burden of stroke attributable to low physical activity in China from 1990 to 2021, and to provide a scientific basis for the development of prevention and control strategies for stroke. Methods Data on mortality, years of life lost (YLLs), years lived with disability (YLDs), and disability-adjusted life years (DALYs) for stroke attributable to low physical activity in China from 1990 to 2021 were extracted from the Global Burden of Disease Study 2021. The disease burden of stroke attributable to low physical activity in China was analyzed by gender and age group from 1990 to 2021. The Joinpoint regression model was utilized to analyze the trends in disease burden. Results From 1990 to 2021, the number of deaths, mortality rates, YLLs, YLLs rates,YLDs, YLDs rates, DALYs, and DALYs rates attributable to low physical activity in China showed an upward trend, with increases of 129.80%, 90.48%, 97.39%, 63.26%, 216.74%, 162.17%, 112.94%, and 76.05%, respectively. The age-standardized mortality rate, age-standardized YLLs rate, and age-standardized DALYs rate showed a downward trend, with decreases of 20.14%, 25.68%, and 18.75%,respectively, while the age-standardized YLDs rate has increased by 18.26% compared to 1990. Joinpoint regression analysis results indicated that the average annual percent change (AAPC) for the age-standardized mortality rate, age-standardized YLLs rate, age-standardized DALYs rate, and age-standardized YLDs rate attributable to low physical activity from 1990 to 2021 were-0.72%, -0.96%, -0.68%, and 0.92%, respectively. Gender-stratified analysis revealed that in 2021, the age-standardized mortality rate, age-standardized YLLs rate, and age-standardized DALYs rate attributable to low physical activity were higher in males than in females. Meanwhile, the decline in the age-standardized mortality rate, age-standardized YLLs rate, and age-standardized DALYs rate attributable to low physical activity was more rapid in females compared to males. Age-stratified results indicated that the disease burden of stroke attributable to low physical activity increased with age but showed a trend toward affecting younger individuals. Conclusion The disease burden of stroke attributable to low physical activity in China remains substantial, indicating a need for targeted and comprehensive prevention and control measures, particularly for key populations such as the elderly, males, and middle-aged and young adults.

Objective The aim is to explore the influence of age-friendly community environments on social adaptation of urban older adults, and to test the mediating role of social participation between the two, so as to provide a theoretical basis for optimizing age-friendly community environments and promoting healthy aging. Methods Based on CLASS 2020, 5 726 urban older adults aged 60 and above were selected as the study population, with age-friendly community environments as the explanatory variable, social adaptation as the outcome variable, and social participation as the mediating variable. The relationship between the variables was explored through Pearson correlation analysis, and the mediating effect was tested using Hayes’ Process plug-in. Results The mediating effect analysis showed that the age-friendly community environments had a direct effect (β=0.036, 95% CI: 0.005-0.068) on the social adaptation of urban older adults, accounting for 90.00% of the total effect. Social participation (β=0.004, 95% CI: 0.001-0.007), which accounted for 10.00% of the total effect, played a mediating role between the two. Conclusion Age-friendly community environments can improve the social adaptation of older adults through the path of social participation, suggesting that policymaking needs to focus on optimizing community environments and stimulating social participation of older adults in order to achieve the goals of healthy ageing and active ageing.

Objective To explore the relationship between low grip strength and the occurrence of falling in the elderly. Methods A cohort study was conducted using the China Healh and Retirement Longiudinal Sudy (CHARLS) database, including individuals without a history of falling at the 2011 baseline. Demographic characteristics, chronic disease history, and grip strength information of the subjects were collected. Subjects were grouped based on whether they experienced falling during the follow-up from 2013 to 2020. Multivariable logistic regression analysis was used to examine the relationship between low grip strength and falling occurrence. The causal relationship between low grip strength and falling was assessed using two-sample MR based on the corresponding datasets. Datasets were sourced from the IEUGWAS database. MR analysis was conducted using inverse variance weighting (IVW), MR-Egger regression, weighted median estimation (WME), simple mode,and weighted mode methods. Cochran’s Q test, MR-pleiotropy, and leave-one-out methods were employed to evaluate pleiotropy, sensitivity, and heterogeneity. Results After adjusting for age, gender, marital status, disease status and other related confounding factors, low grip strength was still associated with the occurrence of falling. Compared with the normal grip group, the low grip group had an increased risk of falling (OR=1.29, 95% CI: 1.06-1.56, P=0.01). The results of MR also showed that low grip strength increased the occurrence of falling. Conclusion Low grip strength is associated with falling in the elderly. The elderly with low grip strength have a higher risk of falling.

Objective To understand the incidence and mortality trends of uterine cancer in tumor registration areas of Shandong Province from 2013 to 2021, and to provide a basis for the prevention and control of uterine cancer. Methods Data were obtained from the Shandong Cancer Surveillance Database. Crude incidence (mortality) rates and age-standardized rates were calculated using Excel 2010 and R 4.4.2. Joinpoint regression was used to calculate the average annual percentage change (AAPC). Results From 2013 to 2021, the crude incidence rate and the Chinese age-standardized incidence rate of uterine cancer among women in tumor registration areas of Shandong Province increased by 4.08% and 2.85% per year, respectively (crude incidence rate AAPC=4.08%, 95% CI: 2.25%-5.95%, P<0.001; Chinese age-standardized incidence rate AAPC=2.85%, 95% CI: 1.02%-4.72%; All P=0.002). Although there was a decrease in crude mortality rate and Chinese age-standardized mortality rate, the difference was not statistically significant (crude mortality rate AAPC=-1.33%, 95% CI: -4.28%-1.71%, P=0.389; Chinese age-standardized mortality rate AAPC=-2.53%, 95% CI: -5.86%-0.91%, P=0.165). The urban incidence rate and mortality were higher than those in rural areas(χ²=513.53, χ²=64.27, both P<0.01). Both the Chinese age-standardized incidence rate in urban areas and the crude incidence rate in rural areas showed upward trends, with annual increases of 3.05% and 3.90%, respectively. Conclusion From 2013 to 2021, uterine cancer among female residents in Shandong Province has shown an upward trend and is a malignant tumor that women should focus on preventing. Early diagnosis and treatment of high-risk groups for uterine cancer should be emphasized, and etiological exploration and research should be strengthened to provide reference for the prevention and treatment of uterine cancer.

Objective To examine the relationship between body roundness index (BRI) and depression risk in individuals with hyperlipidemia. Methods Data were obtained from the National Health and Nutrition Examination Survey (NHANES) 2005—2018, including 20 492 adults with hyperlipidemia. Multivariable logistic regression and restricted cubic spline analyses were used to analyze the association between BRI and depressive status. Results Multivariable analysis revealed a significant U-shaped relationship between BRI and depression risk (P=0.002), with an inflection point at 3.15. For BRI<3.15, each unit increase in BRI was associated with a 33% decrease in depression risk (OR=0.67, 95% CI: 0.50-0.88, P=0.004 3). For BRI≥3.15, each unit increase in BRI was associated with a 7% increase in depression risk (OR=1.07, 95% CI: 1.04-1.09, P<0.000 1). In tertile analysis, the highest BRI tertile showed a 30% increased risk of depression compared to the lowest tertile(OR=1.30, 95% CI: 1.13-1.49, P=0.000 2). Conclusion There is a U-shaped relationship between BRI and depression risk in individuals with hyperlipidemia, suggesting that both excessively low and high BRI values may increase the risk of depression.Large prospective cohort studies are needed to validate these findings.