To explore the coupling coordination degree and relative development degree between traditional chinese medicine (TCM) healthcare resource allocation and socioeconomic development in Guizhou Province from 2021 to 2023.

The entropy method, coupling coordination degree model, relative development degree, and Moran's I were used to evaluate the coupling coordination relationship between TCM healthcare resource allocation and socioeconomic development across 88 counties in Guizhou Province during 2021—2023.

From 2021 to 2023, the overall comprehensive score increased from 0.169 8 to 0.205 2, representing an increase of 20.85%. Both the coupling coordination degree and the relative development degree showed an overall upward trend, and the coordination status shifted from mild imbalance to near imbalance. Moran's I was greater than 0 in 2021—2023 (P<0.05), increasing from 0.041 in 2021 to 0.056 in 2023.

The overall comprehensive score between TCM healthcare resource allocation and socioeconomic development in Guizhou Province increased markedly, with an overall improving coordination trend and strengthened spatial clustering. Further efforts are needed to enhance the coordination between TCM healthcare resources and socioeconomic development and to promote balanced development across counties.

To develop a medication adherence scale for tuberculosis (TB) patients and to validate its reliability and validity.

The initial scale was constructed based on a multi-theory model (MTM) through literature review, expert consultation, and a pilot survey with TB patients. A survey was conducted among 310 TB patients from Yangzhou Third People's Hospital between October 2024 and March 2025 to assess the scale's reliability and validity.

The final scale contained 6 dimensions (perceived benefits, perceived barriers, emotional transformation, self-efficacy, social support, and behavioral transformation) with a total of 48 items. The item-total correlations ranged from 0.592 to 0.884 (all P<0.001). Exploratory factor analysis identified 6 common factors, which collectively explained 85.234% of the total variance. Confirmatory factor analysis demonstrated good model fit. The overall Cronbach's α coefficient was 0.978, with subscale coefficients ranging from 0.959 to 0.982, and the split-half reliability was 0.831.

The MTM-based medication adherence scale for tuberculosis patients shows good reliability and validity, and can be used as a specific assessment tool for medication adherence in patients with tuberculosis.

To assess the current level of medical-service resistance across prefectures in Sichuan and to provide evidence for building a highly resilient healthcare system.

Using panel data for 21 prefectures from 2013 to 2022, an evaluation index system for medical service resistance in Sichuan Province was constructed. CRITIC-Entropy Weight Method and TOPSIS were applied to calculate resistance scores, while kernel density, Moran's I and Markov-chain models were employed to analyze spatiotemporal evolution and state-transition probabilities.

Resistance rose from 0.431 to 0.477, with 90.48% of prefectures recording positive growth. The resistance level shifted from medium to high, and the high level was the dominant category. LISA maps revealed “high-low”, “low-high” and “low-low” clusters. Transition probabilities showed a gradient effect and a pronounced lock-in, making leapfrog upgrades difficult.

Overall resistance in Sichuan is improving, but significant regional disparities persist, local spatial clustering is evident, and a strong lock-in effect governs state transitions.

To explore dynamic bidirectional associations among cognitive frailty symptoms in Chinese older adults and identify core symptoms within the cognitive frailty network.

Older adults from the baseline and two follow-up waves (2011—2018) of the Chinese Longitudinal Healthy Longevity Survey were included. The longitudinal network structure of cognitive function and physical frailty was analyzed using cross-lagged panel network analysis.

A total of 2 377 older adults were included. The T1→T2 network contained 63 non-zero predictive effects (57.27%), with the strongest prediction being the negative impact of instrumental activities of daily living on general ability (β=-0.47) and attention-based calculation ability (β=-0.39). The T2→T3 phase showed an increase to 71 non-zero effects (64.55%), revealing a feedback loop: instrumental activities of daily living→health status evaluation→verbal comprehension and self-coordination→instrumental activities of daily living. The centrality analysis showed that the language comprehension and self-coordination ability in the T1-T2 stage had the strongest outward influence (out-EI=0.98), and the basic activities of daily living in the T2-T3 stage became the strongest output node (out-EI=1.35). Physical function manifested as the introverted core (in-EI=1.43, 0.86) that was most susceptible to other nodes in both stages.

Priority should be given to improving basic activities of daily living and language comprehension abilities, implementing early comprehensive intervention, and strengthening the dynamic monitoring and management of physical functions and chronic diseases to delay the process of functional decline and promote healthy aging.

To explore the latent classes and influencing factors of community nursing needs in elderly patients with type 2 diabetes mellitus (T2DM) in Chengdu, providing a reference for optimizing community diabetes care.

In 406 community-dwelling elderly patients with T2DM sampled by stratified convenience sampling, we administered general information questionnaire, community nursing needs scale, health literacy questionnaire and self-care ability scale. Latent class analysis identified need subtypes, and multinomial logistic regression identified their influencing factors.

Community nursing needs were moderate overall, categorized into three latent classes: low-level needs (52.2%), high multidimensional needs (37.7%), and high health promotion-low disease management and psychosocial support needs (10.1%). Age, monthly household income, complications, comorbidities, exercise, health literacy, and self-care ability were influencing factors for different subtypes (all P<0.05).

Three latent classes exist for community nursing needs in elderly T2DM patients, influenced by multiple factors. Community nursing services should implement targeted interventions based on need classification, rationally allocate elderly nursing resources, and improve the quality of diabetes management and patient satisfaction.

To assess elderly care vulnerability within the Intergovernmental Panel on Climate Change (IPCC) framework and examine its effects and heterogeneity in the choice of care modes, and provide evidence for the optimization of elderly care policies.

Using data from China longitudinal aging social survey (CLASS) 2020 and including 8 221 elderly individuals, this study constructed an evaluation index system for elderly care vulnerability based on the entropy method and conducted K-means cluster analysis. Univariate tests and multinomial logistic regression were then employed to examine the impact of elderly care vulnerability and its heterogeneity on the choice of care modes.

An elderly care vulnerability assessment system was constructed comprising three primary indicators and seventeen secondary indicators, with vulnerability scores ranging from -0.083 to 0.529. Clustering classified respondents into high (7.05%), medium (75.28%), and low (17.67%) vulnerability groups. Univariate analysis showed that vulnerability was associated with care-mode choice (χ²=109.821, P<0.001). Multinomial logistic regression showed that, relative to self-care, high vulnerability increased the likelihood of community care (OR=2.729, 95% CI: 1.645-4.527) and institutional care (OR=5.150, 95% CI: 3.115-8.515), and decreased the likelihood of care by children (OR=0.631, 95% CI: 0.481-0.828). Heterogeneity analysis indicated that effects were stronger among the oldest-old and urban respondents. Highly vulnerable women were more likely to choose self-care, whereas highly vulnerable men were more likely to choose institutional care.

Elderly care vulnerability in China is moderate overall. As vulnerability increases, preferences for elderly care modes show a trend of “care by children < self-care < community care < institutional care”. Strengthening the socialized care system, delivering targeted services, and building resilient support networks are recommended.

To construct a medical literacy evaluation index system for patients with chronic kidney disease (CKD), aiming to assess and enhance their ability to acquire, understand, and apply relevant medical information.

An indicator pool was initially established through literature analysis and semi-structured interviews. The Delphi method and analytic hierarchy process were employed to finalize the evaluation index system and determine the weights.

The questionnaire recovery rates for the two rounds of expert consultation were 94.44% and 88.24%. The expert authority coefficients for the two rounds were 0.915 and 0.927. The Kendall's coefficient for the second round of expert consultation ranged from 0.130 to 0.215, and the intraclass correlation coefficient ranged from 0.326 to 0.906. Ultimately, a medical literacy evaluation index system for patients with CKD was established, comprising 4 first-level indicators, 10 second-level indicators, and 42 third-level indicators.

The medical literacy evaluation index system for patients with CKD constructed in this study is necessary and practical. It can objectively assess and improve patients' level of medical literacy, thereby providing support for clinical diagnosis, treatment, and medical communication practices.

To investigate the treatment outcome and influencing factors of subclinical tuberculosis (STB) in Guizhou Province, and to provide a reference for further prevention and treatment of STB.

The STB patient information in Guizhou Province from 2021 to 2023 was derived from the National Tuberculosis Management Information System. Baseline characteristics of patients were described, and factors influencing patient treatment outcome were analyzed using χ² test and multivariable logistic regression, and subgroup analysis was performed.

A total of 4 406 STB patients were registered in Guizhou Province from 2021 to 2023, 190 (4.3%) cases had adverse outcomes, and 4 216 (95.7%) cases were successfully treated. Among them, 2 600 (59.0%) were male, 3 069 (69.7%) were Han, and 2 146 (48.7%) were farmers. 3 532 (80.2%) cases were found after referral and follow-up. Multivariable logistic regression analysis showed that age≥60 years old (OR=2.892, 95% CI: 1.143-7.317), comorbidities (OR=1.632, 95% CI: 1.114-2.392), hematogenous pulmonary tuberculosis (OR=9.618, 95% CI: 1.047-88.317), positive etiology (OR=2.164, 95% CI: 1.539-3.043), and retreatment (OR=5.338, 95% CI: 2.011-14.167) were risk factors for adverse outcomes in STB patients. Primary management (OR=0.124, 95% CI: 0.039-0.392) and use of standard protocols (OR=0.372, 95% CI: 0.262-0.527) were protective factors. The impact of treatment regimen on the treatment outcome of STB patients had interactions in different comorbidities and diagnostic subgroups (interaction P<0.05). Among them, patients with STB without comorbidities (OR=0.22, 95% CI: 0.15-0.31) and patients with secondary STB (OR=0.23, 95% CI: 0.17-0.31) had better treatment effects with the standard regimen.

The majority of subclinical tuberculosis patients in Guizhou Province are male, young and middle-aged, Han nationality, farmers, and secondary pulmonary tuberculosis, and the main source is passive detection. Patients with STB aged≥60 years old, comorbidities, hematogenous pulmonary tuberculosis, positive etiology, retreatment, no primary management, and no use of standard treatment options will increase the risk of adverse outcomes. For the above types of patients, we should focus on the occurrence and development of their clinical treatment outcomes, and take corresponding treatment and management measures to reduce the occurrence of adverse outcomes.

To investigate the association between 24-hour physical activity and the risk of metabolic syndrome using functional data analysis.

Data were obtained from the National Health and Nutrition Examination Survey (NHANES) 2011—2014. A total of 1 110 eligible participants were included in the analysis. Parametric and nonparametric generalized propensity score methods with functional exposures were used to adjust for potential confounders, including age and sex. Inverse probability weighting in conjunction with a functional linear model was employed to estimate the association between 24-hour physical activity and the risk of metabolic syndrome and to examine sex-specific differences.

Physical activity during the periods of 10:15-11:15 and 16:35-19:45 (parametric method: F=4.969, P<0.001; nonparametric method: F=6.313, P<0.001) was associated with a reduced risk of metabolic syndrome. Sex-stratified analyses indicated that, among males, physical activity between 16:45 and 19:40 (parametric method: F=3.573, P<0.001; nonparametric method: F=4.816, P<0.001) was negatively associated with metabolic syndrome risk, whereas among females, a significant negative association was observed during 09:05-10:15 (parametric method: F=3.076, P=0.003; nonparametric method: F=3.008, P=0.004).

The association between 24-hour physical activity and the risk of metabolic syndrome exhibits both time-specific patterns and sex differences, suggesting that prevention strategies should incorporate activity timing and recommend exercise periods aligned with individuals' circadian rhythms to optimize health benefits.

To understand the current status and influencing factors of frailty occurrence among middle-aged and elderly patients with H-type hypertension, and to construct a predictive model for frailty risk in this population.

Based on univariate and binary logistic regression analyses, screen for independent influencing factors, construct a risk prediction model for the occurrence of frailty in H-type hypertension, and create a visual nomogram. Finally, evaluate the predictive value of the risk prediction model using the H-L goodness-of-fit test, ROC curve, and calibration curve.

This study included a total of 783 middle-aged and elderly patients with H-type hypertension, among whom 207 developed frailty (26.4%). Binary logistic regression analysis showed that age (OR=1.055, 95% CI: 1.032-1.079), education level (OR=0.656, 95% CI: 0.495-0.870), blood urea nitrogen (OR=1.215, 95% CI: 1.092-1.352), and high-density lipoprotein (OR=0.475, 95% CI: 0.273-0.826) were independent factors influencing the development of frailty in middle-aged and elderly patients with H-type hypertension. A logistic regression prediction model was constructed based on these influencing factors, with the Hosmer-Lemeshow goodness-of-fit test yielding a P-value of 0.836. The area under the ROC curve (AUC) was 0.733, 95% CI=0.694-0.771, indicating that the model has good discriminative ability. The calibration curve showed a high consistency between the predicted values and the observed values.

The incidence of frailty among middle-aged and elderly patients with H-type hypertension remains at a relatively high level. A risk prediction model based on these factors has certain predictive value for the occurrence of frailty in patients with H-type hypertension.