To explore how the subjective life expectancy of patients with chronic diseases affects their medical expenditure and provide a policy intervention perspective for improving the quality of life of patients with chronic diseases.

The data from the China Health and Retirement Longitudinal Study (CHARLS) were used. A total of 9 949 samples with any chronic disease at three time points in 2015 (T1), 2018 (T2), and 2020 (T3) were selected. Information such as subjective life expectancy, annual medical expenditure, frequency of outpatient and inpatient visits from modules including health status, medical service utilization records, family economy, and individual basic information was used. A cross-lagged model was applied to test the interaction between subjective life expectancy and medical expenditure and explore the mediating effect of medical resource utilization.

The results of the standardized cross-lagged analysis showed that the subjective life expectancy T1 of patients with chronic diseases significantly negatively predicted the medical expenditure T2 (β=-0.043, P < 0.01), and the medical expenditure T2 significantly negatively predicted the subjective life expectancy T3 (β=-0.043, P < 0.01); the medical expenditure T1 of patients with chronic diseases significantly negatively predicted the subjective life expectancy T2 (β=-0.034, P < 0.05), and the subjective life expectancy T2 significantly negatively predicted the medical expenditure T3 (β=-0.043, P < 0.01). Medical resource utilization had a mediating effect in this process (β=-0.02, P < 0.05).

There is a complex interaction mechanism between the subjective life expectancy and medical expenditure of patients with chronic diseases. There may be a vicious cycle in which health anxiety leads to the deterioration of the condition and an increase in medical expenditure, which further aggravates anxiety, as well as the phenomenon of excessive medical treatment due to pessimistic health expectations. This indicates the value of formulating differentiated psychological intervention policies for different groups to improve the quality of life of patients with chronic diseases.

To understand the focus and central aspects of government attention allocation in provincial-level infant and toddler care service policies in China to reveal the characteristics of provincial governments’ attention to various issues related to infant and toddler care services, providing a basis for rational allocation of government attention in the next phase and optimizing policy resources for these services.

A total of 87 provincial-level government policies on infant and toddler care services issued from April 2018 to July 2023 were selected as the research subjects. The study primarily employed word frequency analysis and semantic network analysis to measure the direction and center of government attention allocation in the policy texts.

The direction of government attention allocation in infant and toddler care policies across different regions was relatively consistent, with the top ten high-frequency words including “service”, “care”, “institution”, “infant and toddler”, “care”,“elderly”, and “health”. The central focus of attention allocation in the eastern, central, and western regions was “institution”,while the northeastern region showed a different central focus. The node with the highest intermediary centrality was “service”,followed by “infant and toddler” and “elderly” as secondary central nodes.

Provincial governments have placed excessive emphasis on services provided by care institutions, necessitating greater attention to the diversity of infant and toddler care service types. There is also a need to enhance focus on inclusive infant and toddler care services, with the northeastern region particularly requiring innovative models for the coordinated development of elderly and infant and toddler care services.

To conduct a quantitative analysis of national-level hypertension prevention and control policies and provide suggestions for the improvement and optimization of these policies.

Hypertension prevention and control policies from 2009 to 2023 were retrieved. A three-dimensional analytical framework of policy tools, policy intensity, and four-level prevention was constructed. Content analysis was used to conduct single-dimension and cross-analysis of policies related to hypertension prevention and control.

A total of 68 policy texts were included in this study, forming 110 coding units.The proportions of environmental, supply-based, and demand-based policy tools were 56.4%, 25.5%, and 18.2%, respectively.The average score of policy intensity was 3.1 (score range: 1-6). The proportions of policy texts for zero-level prevention, primary prevention, secondary prevention, and tertiary prevention were 27.3%, 20.9%, 45.5%, and 6.4%, respectively. Crossanalysis showed that there were significant differences in policy intensity among different types of policy tools. The policy intensity of prevention strategies at all levels was relatively balanced. The environmental policy tools had the highest proportion among prevention strategies at all levels. There were significant differences in supply-based and demand-based policy tools among different prevention strategies.

There is a lack of internal balance in hypertension prevention and control policy tools, and the use of supply-based and demand-based tools needs to be strengthened. The overall policy intensity is relatively weak. Attention should be paid to the overall relevance of policy content. It is urgent to move forward the prevention threshold of hypertension and strengthen the synergistic effect of four-level prevention.

To explore the relationship between oral health-related quality of life (OHRQoL) and dental care-seeking behavior among the elderly in Sichuan Province, while analyzing the impact of income on this relationship.

A total of 744 elderly individuals aged 65 to 74 years from Sichuan Province were included in this study through multi-stage stratified random sampling during the Fourth National Oral Health Epidemiological Survey conducted from 2015 to 2016. A questionnaire was used to assess the participants’ income levels, dental care-seeking behavior, and OHRQoL. Stratified logistic regression was employed to examine the relationship between dental care-seeking behavior and OHRQoL, as well as the moderating effect of income.

Among the 744 participants, 552 (74.2%) reported engaging in dental care-seeking behavior. Lower overall (β=-0.040, P < 0.001), functional (β=-0.028,P=0.002), pain-related (β=-0.037, P < 0.001), and psychological (β=-0.029, P=0.002) dimensions of OHRQoL were associated with an increased likelihood of dental care-seeking among the elderly. Additionally, income had a positive moderating effect only on the relationship between oral health-related psychological discomfort and dental care-seeking behavior; specifically, lower income was associated with a weaker correlation between psychological discomfort related to oral health and dental care-seeking behavior (β=-0.007,P=0.039).

The utilization of oral health services among the elderly in Sichuan Province is suboptimal, with poor OHRQoL being a primary driving factor for dental care-seeking behavior. High income only facilitates dental visits when oral health issues lead to psychological discomfort. Public health efforts targeting oral health among the elderly should focus on updating their perceptions of oral health and addressing the psychological impacts associated with oral health.

To understand the healthy life expectancy (HLE) of residents aged 18 and above in Nanjing under various standards and evaluate the health status of the population.

Using data from the 2023 Jiangsu Provincial Health Commission’s survey on per capita life expectancy and the health expectancy survey of Nanjing residents, we calculated disability measures based on four health standards: self-rated health, reported health, GALI (Global Activity Limitation Indicator), and EQ-5D. The Sullivan method was employed to estimate the healthy life expectancy for Nanjing under these different standards.

In 2023, the life expectancy (LE) for residents aged 18 in Nanjing was 63.05 years. The HLE under the four health standards for 18-year-old residents were 49.35 years, 42.39 years, 55.08 years, and 60.95 years, respectively.The HLE across all age groups followed the order of EQ-5D > GALI > self-rated health > reported health. Notably, HLE for males under 85 years was lower than that for females, although males exhibited a relatively higher quality of life compared to females at all age levels.

There are certain discrepancies in the results derived from the four standards; however, the observed age trends and gender patterns are consistent. The differences in results may be attributed to the dimensions of health evaluation and the methods used for calculating disability measures, necessitating further research.

To explore the longitudinal mediating role of cognitive function in the relationship between depression and activities of daily living (ADL) among individuals aged 60 and above in China, as well as the moderating effect of sleep quality.

Data from the China Health and Retirement Longitudinal Study (CHARLS) collected in 2018 (T1) and 2020(T2) were analyzed. The Center for Epidemiologic Studies Depression Scale (CES-D10), the Mini-Mental State Examination (MMSE), and the ADL scale were used for measurement. Descriptive statistics and correlation analyses were conducted using STATA 18.0 and SPSS 26.0, while mediation and moderated mediation models were constructed and analyzed using Model 4 and Model 59 in the Process 4.0 program.

T1 depression significantly negatively predicted T2 ADL (r=-0.247, P <0.01). Both T2 cognitive function and T2 sleep quality significantly positively predicted T2 ADL (r=0.227, P < 0.01; r=0.131,P < 0.01). T2 cognitive function served as a longitudinal mediator between T1 depression and T2 ADL, with a mediation effect value of 0.022 (95%CI: -0.027 to -0.018), accounting for 14.5% of the total effect. T2 sleep quality moderated all paths in the mediation model (β=-0.018, P < 0.05; β=0.040, P < 0.001; β=-0.034, P < 0.001).

Depression reduces the ability of elderly individuals to perform daily activities by affecting cognitive function. Improving sleep quality can enhance the impact of depression on cognitive function, and can mitigate the effects of depression and cognitive function on ADL.

To assess the association between the trajectories of depression symptoms and the risk of stroke in the elderly.

Data from four waves of the China Health and Retirement Longitudinal Study (CHARLS) from 2011 to 2018 were utilized.Group-based trajectory modeling was employed to identify the trajectories of depression symptoms, and logistic regression models were used to evaluate the relationship between these trajectories and stroke.

Four trajectories of depression symptoms were identified:low stable (n=2 392, 60.7%), moderate decreasing (n=762, 20.2%), moderate increasing (n=416, 12.3%), and high stable (n=250, 6.8%).During the period from 2015 to 2018, a total of 305 respondents experienced a stroke. Compared to participants with the low stable depression symptom trajectory, those following the moderate decreasing (OR=1.48, 95%CI: 1.09-2.02), moderate increasing (OR=2.22,95%CI: 1.58-3.11), and high stable depression symptom trajectories (OR=1.78, 95%CI: 1.12-2.83) had a higher risk of stroke.

Over time, elderly individuals following moderate decreasing, moderate increasing, and high stable trajectories of depression symptoms exhibited an increased risk of stroke. Long-term depression symptoms may serve as a strong predictor for stroke.

To explore the association between sleep duration and fall incidents among middle-aged and elderly individuals in China.

A cross-sectional analysis was conducted using data from the 2020 China Health and Retirement Longitudinal Study (CHARLS), involving 18 515 participants aged 45 and older. Demographic characteristics, behaviors, lifestyle factors, and health status of the subjects were collected, and logistic regression and restricted cubic spline (RCS) models were employed to investigate the relationship between sleep duration and fall risk.

The incidence of falls among middle-aged and elderly individuals in China over two years was 17.20%, with an average sleep duration of (6.11 ± 1.86) hours. The fall incidence for those sleeping less than 5 hours per night was 26.39%, for 5 to less than 7 hours was 16.39%, for 7 to less than 9 hours was 13.04%, for 9 to less than 11 hours was 15.99%, and for those sleeping 11 hours or more was 30.00%. Multivariate logistic regression results indicated that the fall risks for individuals with sleep durations of less than 5 hours, 5 to less than 7 hours, and 11 hours or more were 1.46,1.15, and 2.01 times higher respectively compared to those sleeping 7 to less than 9 hours (P < 0.05). Analysis using the restricted cubic spline model revealed a U-shaped non-linear dose-response relationship between sleep duration and falls (overall trend P <0.05, non-linear test P < 0.05), with the lowest risk of falls occurring at approximately 7.5 hours of sleep.

Falls are significantly associated with both short and long sleep durations, with the optimal sleep duration being around 7.5 hours. Intervention measures should be implemented for middle-aged and elderly individuals with poor sleep quality to reduce their fall risk.

To explore the trends in cognitive function and depression symptoms over time among middle-aged and older adults in China, and to identify populations with differing trajectories of cognitive function and depression symptoms, thereby providing a scientific basis for formulating targeted prevention and control measures.

A total of 11 863 individuals aged 45 and above from the China Health and Retirement Longitudinal Study (CHARLS) were included. The Group-based Dual Trajectory Model (GBDTM) was employed to identify the developmental trajectories of cognitive function and depression symptoms, and multinomial logistic regression analysis was utilized to examine the influencing factors of different trajectories.

The GBDTM identified four trajectory groups: “Poor cognitive function but mild depression symptoms” (Group 1, 32.9%),“Poor cognitive function and severe depression symptoms” (Group 2, 10.8%), “Good cognitive function and mild depression symptoms” (Group 3, 40.5%), and “Moderate cognitive function and moderate depression symptoms” (Group 4, 15.7%). Factors associated with a higher likelihood of being classified in the“Poor cognitive function and severe depression symptoms” group included being female (OR=4.70, 95%CI: 3.82-5.78), unmarried (OR=2.09, 95%CI: 1.67-2.60), residing in rural areas (OR=4.26,95%CI: 3.59-5.07), smoking (OR=1.26, 95%CI: 1.02-1.56), having activities of daily living (ADL) disabilities (OR=1.92, 95%CI:1.39-2.65), and having instrumental activities of daily living (IADL) disabilities (OR=7.43, 95%CI: 5.90-9.35).

There is a partially “joint development” trajectory relationship between cognitive function and depression symptoms in middle-aged and older adults. Early intervention targeting the influencing factors of different trajectory groups is crucial.