Objective: This study aims to examine regional disparities and spatiotemporal dynamics in the allocation of Practicing (Assistant) Physicians between northern and southern China, using a north–south division that captures pronounced geographic and population heterogeneity. Methods: Based on data on Practicing (Assistant) Physicians from 31 provincial-level administrative regions in China from 2012 to 2022, this study analyzes regional differences and their dynamic evolution from three dimensions: total supply, per capita availability, and spatial accessibility. The number of Practicing (Assistant) Physicians per 1,000 population and the Health Resource Density Index (HRDI) were employed as key indicators. Results: From 2012 to 2022, the number of Practicing (Assistant) Physicians in southern China increased from 1.424 million (54.4%, 1.80 physicians per 1,000 population) to 2.511 million (56.6%, 2.99 physicians per 1,000 population), while the corresponding figures in northern China rose from 1.191 million (45.6%, 2.11 physicians per 1,000 population) to 1.924 million (43.4%, 3.39 physicians per 1,000 population). The growth rate of Practicing (Assistant) Physicians was notably higher in the southern region than in the northern region. In terms of allocation equity, the Gini coefficient between the northern and southern regions increased from 0.350 in 2012 to 0.373 in 2021. Within-region inequality exhibited divergent trends: the Gini coefficient in the northern region rose from 0.358 to 0.391, whereas that in the southern region declined from 0.327 to 0.311. Moreover, the Theil T index was significantly higher in the southern region, while the Theil L index was slightly higher in the northern region. Spatial autocorrelation analysis further revealed distinct spatial patterns across indicators. The distribution of Practicing (Assistant) Physicians per 1,000 population showed pronounced north–south clustering, with hotspot areas mainly located in northern China and cold spots concentrated in southern China. In contrast, the HRDI exhibited a clear east–west pattern, with hotspots clustered in eastern China and cold spots in western China. Conclusion: Southern China outperformed northern China in terms of the total number, growth rate, and HRDI of Practicing (Assistant) Physicians, with the interregional gap showing a widening trend over time; however, the southern region remained disadvantaged in terms of physicians per 1,000 population. Allocation disparities in southern China were more pronounced across provinces with different levels of economic development, whereas in northern China, inequities were primarily associated with variations in population density. The spatial distribution of Practicing (Assistant) Physicians in China showed distinct agglomeration patterns across different indicators. Both population equity and spatial accessibility must be considered, as a single indicator cannot fully reflect resource allocation situation. Targeted resource regulation strategies should be developed to address these varying dimensions.

OBJECTIVE:Using the China Family Panel Studies (CFPS, 2012-2022), this study aimed to characterize changes in the distribution of usual sources of care and in subjective perceptions among Chinese adults, and to examine the associations of subjective perceptions and income change with next-wave transitions in usual source of care. METHODS:This was a retrospective longitudinal observational study based on adult CFPS data from 2012, 2014, 2016, 2018, 2020, and 2022. We first described temporal trends in three types of usual source of care (primary care, hospitals, and clinics), as well as trends in residents' subjective perceptions of healthcare providers, and in relative income change. We then constructed person-period samples from adjacent survey waves and analyzed two transition processes separately: outflow from primary care among baseline primary care users and inflow to primary care among baseline non-primary care users. Key predictors were prior-wave satisfaction, perceived medical competence, and relative income change; the income-change variable was defined based on changes in relative income group within the same wave and same province sample. Descriptive analyses applied cross-sectional weights; the main regressions were unweighted binary Logistic models with individual-level cluster-robust standard errors, reporting odds ratios (OR), 95% confidence intervals (95% CI), and P va-lues. RESULTS:The pooled sample comprised 135 986 observations from 34 010 individuals. From 2012 to 2022, the proportion using primary care as the usual source of care declined from 43.49% to 30.34%, whereas the hospital share rose from 34.06% to 46.81%. The decline in primary care was steeper during 2012-2018 (43.49% to 33.72%) and persisted at a slower pace thereafter (33.72% to 30.34%). Across adjacent survey waves, primary care outflow increased from 35.47% to 45.22%, while primary care inflow decreased from 30.09% to 19.60%, indicating simultaneous increases in exits and decreases in entries. Subjective perceptions improved for all three provider types over time; however, the relative gap between primary care and hospitals widened on perceived medical competence, and primary care shifted from a slight advantage over clinics to a clear disadvantage in composite subjective perceptions. The proportion of residents with unchanged relative income group rose from 50.64% to 60.33%. In multivariable models, each one-unit increase in satisfaction with primary care was associated with 7.5% lower odds of leaving primary care (OR=0.925, P < 0.001). In contrast, each one-unit increase in perceived medical competence of non-primary care providers was associated with 5.3% lower odds of moving into primary care (OR=0.947, P < 0.001). Compared with stable relative income group, upward relative income-group mobility, particularly low-to-high movement, was associated with higher odds of outflow from primary care and lower odds of inflow to primary care (outflow OR=1.166; inflow OR=0.840), whereas downward relative income-group mobility, especially high-to-low movement, showed the opposite pattern (outflow OR=0.785; inflow OR=1.371). CONCLUSION:Primary care utilization in China continued to decline, with increased outflow from primary care and reduced inflow to primary care occurring simultaneously. Residents ' subjective perceptions were associated with different considerations in retention in versus movement into primary care: the former was more closely related to satisfaction, whereas the latter was more closely related to perceived medical competence. People with upward relative income-group mobility showed a lower inclination to use primary care. Hierarchical care policy should address both entry into and retention in primary care by strengthening continuity of care, reinforcing service capability and institutional design, and aligning payment incentives.

Primary health care quality is central to recent reforms in China, yet real-world evidence remains limited. This study aimed to assess the quality of primary care delivered by village clinics in rural China after primary health care reforms and to identify system-level drivers of performance gaps. We conducted an explanatory sequential mixed-methods study combining unannounced standardised patient (SP) visits with qualitative interviews and non-participant observation (direct observation of routine clinic practice without researcher involvement, included to contextualise clinician behaviour). Sixty-one unannounced SP visits were completed (influenza n = 30; tuberculosis n = 31). Fifteen participants were interviewed and 42 h of non-participant observation were conducted in six clinics. Outcomes included SP-assessed process quality, diagnostic accuracy and correct case management benchmarked to clinical guidelines. Qualitative analysis of determinants drew on Structure–Process–Outcome and the Consolidated Framework for Implementation Research. Process quality was low: clinicians completed 14.6

Background:Loneliness is a growing public health challenge among older adults and is associated with a wide range of adverse health outcomes. The role of eHealth literacy in shaping the relationship between loneliness and quality of life remains unclear. Objective:This study aimed to examine the contributing role of eHealth literacy in moderating the associations between loneliness and quality of life among older adults. Methods:A community-based survey was conducted in 2025 among older adults aged 60 years or older living in northwestern China. A total of 2110 participants were included. Multiple linear regression and interaction models were used to assess associations and moderating effects. Sensitivity analyses were conducted by replacing the outcome variable with depressive symptoms and by performing stratified analyses to assess the robustness of the primary interaction findings. Results:Loneliness showed a consistent negative association with quality of life (β=-0.83, 95% CI -1.18 to -0.49; P<.001). Higher overall eHealth literacy was associated with better quality of life (β=0.41, 95% CI 0.35-0.47; P<.001). Interaction models indicated that higher eHealth literacy was associated with a steeper negative association between loneliness and quality of life (β=-0.04, 95% CI -0.08 to -0.002; P=.04). Sensitivity analyses produced similar results across alternative outcomes and subgroups. Conclusions:Higher loneliness was related to a poorer quality of life. Higher eHealth literacy was associated with a steeper negative association between loneliness and quality of life. These findings suggest that eHealth literacy may function as a double-edged sword in later life. Future research is needed to clarify the underlying mechanisms and to examine how digital health competencies interact with psychosocial vulnerability in shaping older adults' well-being.

Importance:Cervical cancer remains a major public health challenge in China, and human papillomavirus (HPV) vaccine uptake remains far below the global average. Understanding public responses to national policy interventions is critical for promoting equitable vaccine access and uptake. Objective:To assess the association between 2 national HPV vaccination policies (August 2022 age expansion approval for HPV vaccination [policy 1] and January 2023 National Action Plan for Accelerating the Elimination of Cervical Cancer [policy 2]) in China and public discourse and engagement on social media. Design, Setting, and Participants:Cross-sectional study using interrupted time-series analysis of publicly available posts by individual users containing HPV-related and vaccine-related keywords from China's largest text-based social media platform collected between December 2021 and December 2024. Latent Dirichlet allocation topic modeling was used to identify 16 topics grouped into 5 thematic domains. Main Outcomes and Measures:Changes in the daily trends of public discussions across 5 thematic domains and 16 topics before and after policy implementation using interrupted time-series analysis. Results:This study analyzed 353 530 HPV-related posts on the social media platform from December 2021 to December 2024. Vaccine accessibility discussions initially increased following the age expansion policy (regression coefficient, 0.08; 95% CI, 0.05-0.12; P < .001). After the launch of the National Action Plan, discussions on the theme of vaccine accessibility decreased by 0.11 percentage points per day (95% CI, -0.14 to -0.08; P < .001). Conversely, discussions on awareness and knowledge increased by 0.04 percentage points per day (95% CI, 0.03-0.06; P < .001), as well as gender and sociocultural factors, which increased by 0.04 percentage points per day (95% CI, 0.02-0.06; P < .001). Conclusions and Relevance:These findings suggest that national HPV vaccination policies in China were associated with shifts in public discourse, including alleviated access concerns and increased health awareness and gender equity discussions. Social media data can provide timely insights into public responses to health interventions and inform strategies to promote equitable HPV vaccine uptake and cervical cancer elimination.

Objectives In the face of pandemics resulting from infectious disease, improving community resilience has become increasingly vital. China’s sudden exit from Zero-COVID policy in December 2022 triggered a surge in COVID-19 cases, compounded by medication shortages due to earlier restrictions, creating a public health crisis. This study assesses community resilience during the first post-Zero-COVID infection wave (8 December 2022 to 7 January 2023), focusing on adaptation mechanisms, resource mobilisation, protective behaviours and medicine access, using real-time social media data to capture these dynamics.Methods This cross-sectional study analysed all geotagged COVID-19-related posts on Sina Weibo—China’s largest public microblogging platform—collected from a megacity in eastern China with over 10 million residents, covering 8 December 2022 to 7 January 2023. Posts were obtained through a data purchase agreement with Sina Weibo and comprised publicly available content. Machine learning and natural language processing were applied to classify posts across four dimensions: content, responder, response type and time. Community resilience was assessed using the community-level response ratio, response speed and sentiment expressed in interactions related to medicine-seeking posts.Results 26 973 posts were analysed, of which 12 152 (45.05%) were help-seeking. Among these help-seeking posts, 11 236 (92.46%) specifically sought COVID-19 medicine, of which 8495 (75.61%) of these medicine-seeking posts received community support. Over 4 weeks, community responses comprised >70% of all replies (the rest were from market-based responders, government and NGOs). More than half of the community responses occurred within an hour, and the emotional state at the community level was the most stable and consistently positive, indicating a high level of prompt community engagement.Conclusion Communities in the sample area consistently exhibited prompt and proactive responses during the health crisis, with community responses accounting for the majority of interactions on medicine-seeking posts. The power of community mutual aid can significantly enhance responsiveness to public health emergencies. Such insights suggest that strengthening community resilience is crucial in designing more effective disaster response strategies.

Objective: To examine the relationship between Knowledge, Attitude, and Practice (KAP) regarding medical-preventive integration and depressive symptoms among Chinese healthcare workers, placing special emphasis on the moderating association of monthly income, while adjusting for work stress as an important covariate. Methods: This study analyzed data from a 2024 cross-sectional survey conducted in two provinces of China, encompassing a total of 5908 healthcare workers. Descriptive statistics were employed to examine the demographic and professional characteristics of the participants. Multiple linear regression was used to investigate the direct associations between medical-preventive integration knowledge, attitude, practice, and depressive symptoms. Furthermore, while moderation analysis was used to assess the interactive association of monthly income in this relationship. Results: The findings demonstrate a significant link between medical-preventive integration knowledge, attitude, and practice (KAP) and depressive symptoms, with knowledge (B = -0.074, 95% CI = -0.134, -0.015) and attitude (B = -0.467, 95% CI = -0.531, -0.403) showing a negative association with depressive symptoms, while practice (B = 0.648, 95% CI = 0.527, 0.770) was positively associated with depressive symptoms. Work stress was positively associated with both practice engagement and depressive symptoms. Additionally, higher income amplified the inverse associations of knowledge (B = -0.040, 95% CI = -0.061, -0.019) and attitude (B = -0.028, 95% CI = -0.046, -0.012) with depressive symptoms and strengthened the positive association between practice (B = 0.066, 95% CI = 0.022, 0.109) and depressive symptoms, as indicated by significant interaction association. Conclusions: Our findings highlight a complex link between KAP patterns and depressive symptoms, with work stress as a significant correlate and income as a moderator. Healthcare workers with higher income and those with supportive knowledge and attitude show a lower probability of experiencing depressive symptoms, whereas greater behavioral engagement is associated with increased depressive symptoms, particularly among those with higher income. There is an urgent requirement to establish targeted interventions, optimizing support and resources, to decrease susceptibility to depressive symptoms among healthcare workers, particularly those with higher income and higher levels of behavioral engagement.

As China deepens health system reform to strengthen primary care by integrating hospital-based specialist services into community settings, empirical evidence is still limited. This quasi-experimental difference-in-differences analysis examined the effect of the digitally enabled GP-specialist collaborative care model implemented in Shenzhen since January 2022, using 2021-2023 electronic health records of hypertensive adult patients receiving care at community health centers. The implementation of this collaborative care model was significantly associated with reduced quarterly mean diastolic and systolic blood pressure levels (difference, -0.84 mmHg and -0.73 mmHg), a 4.6-percentage-point increase in blood pressure control, and a 6.7-percentage-point decrease in hospital referral, with larger effects observed among women, the elderly, unemployed and those with diabetes. Digitally enabled GP-specialist collaborative care could improve care efficiency and hypertension outcomes in primary care settings, but more efforts, such as payment reform and incentive alignment, are still needed to sustain long-term implementation at scale.

Objective:To investigate the changes in knowledge, attitude, and practice (KAP) regarding the integration of medical care and prevention among medical professionals in medical institutions of pilot cities of the collaboration and integration of medical care and prevention, a national pilot program for infectious disease prevention and control, to examine the effect pathways, and to provide empirical evidence for promoting the implementation of the integration of medical care and prevention and improving relevant policies. Methods:The participants in this study were medical professionals involved in medical care and prevention integration work. The participants were all from medical institutions of pilot cities for the collaboration and integration of medical care and prevention. The study sample was selected through multi-stage sampling. A questionnaire based on the theoretical framework of the KAP model was designed. Two cross-sectional surveys were conducted-once before the initiation of the pilot program (baseline) and again 12 months after implementation (after implementation). After propensity score matching (PSM), descriptive statistics and hypothesis testing were used to statistically analyze the questionnaire data. In addition, a structural equation model (SEM) was applied to assess the current status and effect pathways of the participants' KAP regarding the integration of medical care and prevention. Results:A total of 11472 responses were collected, and 10627 were included in analysis after PSM, including 5007 before the implementation of the policy and 5620 after the implementation of the policy. No significant differences were observed in demographic variables between the two samples. Baseline scores for knowledge, attitude, and practice regarding the integration of medical care and prevention were 13.32 ± 0.05, 15.62 ± 0.04, and 6.37 ± 0.02 respectively, while the scores at the end of the study were 13.69, 15.74, and 6.51, respectively, all show an increase to a certain degree (P < 0.05). Stratified analysis by institution level revealed relatively significant improvements in knowledge and practice (P < 0.05), but no significant improvement in attitudes (P > 0.05) among medical professionals. Medical professionals in primary medical institutions generally demonstrated superior knowledge, attitudes, and practice frequency compared with those in secondary and tertiary hospitals (P < 0.001). No significant changes in KAP were observed among medical professionals in secondary hospitals (P > 0.05). Regarding the integration of medical care and prevention, the effect of knowledge on practice (standardized path coefficient = 0.496, 95% CI: 0.482, 0.508) was stronger than that of attitude on practice (standardized path coefficient = 0.267, 95% CI: 0.244, 0.290). The direct effect of knowledge on practice (78.0%) was greater than the indirect effect mediated by attitude (22.0%). Conclusion:The national pilot program for the collaboration between and integration of medical care and prevention in infectious disease prevention and control has a positive effect on improving the KAP regarding the integration of medical care and prevention among medical professionals. Knowledge of the integration of medical care and prevention is the primary factor influencing practice.

To fulfill the World Health Organization's (WHO) goal of active aging, it is essential to concentrate on the health of individuals with disabilities. However, there is a significant gap in research regarding the impact of disability on lifespan in low- and middle-income countries (LMICs). Additionally, the specific social determinants of health for middle-aged and older adults with disabilities are not well understood in LMICs. Our study aims to address these gaps by focusing on China's aging population. We utilized a Weibull regression model to predict individual lifespans and employed linear regression models to identify health determinants for people with disabilities. Our findings revealed that, compared to those without disability, the life expectancy of individuals with mild, moderate, and severe disabilities was reduced by 18%, 37%, and 53%, respectively, with even larger disparities in Quality-Adjusted Life Years (QALYs) at 19%, 39%, and 55%. Key determinants of health for middle-aged and older adults with disabilities included social contact, living areas, and labor market status. Consequently, we recommend three policy interventions: 1) improving access to social contact opportunities within communities; 2) reinforcing the pension system for both urban and rural residents; 3) expanding the elder care industry and enhancing fiscal transfers in rural regions.

Background Ambulatory care sensitive conditions (ACSCs) serve as a critical indicator for assessing healthcare system performance globally. However, China lacks a standardized ACSCs list adapted to its unique healthcare context and evolving medical needs. Methods This study employed a modified Delphi method combined with evidence-based medicine. First, we systematically reviewed international ACSCs lists and their development methodologies to identify potential diseases. Next, we evaluated the evidence of these potential conditions within China's healthcare system. Finally, a two-round Delphi survey was performed to finalize a consensus-based ACSCs list for China. Findings The finalized ACSCs list comprises 14 conditions, categorized into: five core conditions (chronic obstructive pulmonary disease [COPD], bronchial asthma, hypertension, chronic kidney disease [CKD], and diabetes mellitus) and nine general conditions (bronchiectasis, chronic heart failure, atrial fibrillation, chronic hepatitis B, tuberculosis, iron-deficiency anemia, primary osteoporosis, gastroenteritis, and influenza). Based on the prevailing classification framework in academia, the list includes 12 chronic ACSCs, one acute ACSC, and one infectious ACSC. Compared to most international lists (typically covering about 20 ACSCs), China's ACSCs list prioritizes diagnostic specificity over breadth, ensuring practical applicability in China's current healthcare setting. Interpretation This study developed the first evidence-based ACSCs list tailored to China, providing a tool for healthcare performance evaluation and policy development. Future studies should validate its real-world applicability and implement mechanisms for dynamic updates. Funding This work is supported by National Science and Technology Major Project of China (Grant No. 2024ZD0523902), National Natural Science Foundation of China (Grant No. 72374149), and Institutional Research Fund from Sichuan University (Grant No. 2023SCUH0025).

Background:In the face of pandemics from infectious diseases, enhancing community resilience is increasingly important. It is, therefore, essential to evaluate community resilience and identify factors that can strengthen it. This study aimed to evaluate community resilience by leveraging a data set comprising user information from Weibo and applying interpretable machine learning (ML) techniques to identify the contributions of various indicators underpinning community resilience. Methods:This cross-sectional study analysed social media data from December 2022 to January 2023. COVID-19-related user interactions were examined as indicators of community resilience within the context of community response. This study introduced an evaluation framework comprising thirteen indicators. It also described the application of natural language processing (NLP) techniques, the K-means (KM) clustering, a random forest (RF) classifier and SHapley Additive exPlanations (SHAP) to achieve its objectives. Results:A total of 177 000 Weibo posts were collected for this study. The NLP model demonstrated strong performance in accurately labelling posts, with the area under the curve (AUC) of 0.8862 (95% confidence interval (CI) = 0.8600-0.9102) and accuracy (ACC) of 0.8939 (95% CI = 0.8563-0.9277). This study identified four distinct community resilience levels: low (77.64%), medium-low (9.86%), medium-high (10.55%), and high (1.95%). Further analyses revealed clear regional disparities in community resilience, with higher levels observed in Eastern China. The top five indicators associated with community resilience, as determined by mean SHAP values, were 'Efficacy of performance altruistic response' (0.0101), 'Tangible aid engagement' (0.0051), 'Rapid performance of altruism' (0.0044), 'Sentiment response associated with recording positive posts' (0.0036), and 'Help-seeking response efficacy' (0.0035). Conclusions:This study is the first to harness social media data to quantify community resilience in mainland China. Five indicators associated with enhanced community resilience are identified as potential predictors that can inform governmental strategies and strengthen decision-making support for improving health emergency responses.

OBJECTIVES:Comprehensive evidence on nationwide impact of China's National Reimbursement Drug List (NRDL) negotiation policy is lacking. This study is to assess the availability, affordability, and regional equity of negotiated drugs included in NRDL using nationally representative data. METHODS:This cross-sectional study utilized 3 drug databases: 2 nationwide databases in China (2018-2021 and 2019-2021) and 1 multinational database (2017-2022). We examined changes in 6 indicators for negotiated drugs added to the NRDL: proportion of procurement hospital and defined daily doses (DDDs) for availability; defined daily dose cost (DDDc), reimbursement proportion (RP), and drug price index (DPI) for affordability; and Gini coefficient for equity. Drugs were grouped depending on approval time, negotiation year, and status (new vs renewed listing) across the Anatomical Therapeutic Chemical (ATC) classification. We performed inter- and intragroup descriptive analyses to show trends over time and across categories. The DPI was compared with 10 countries. RESULTS:For availability, the proportion of procurement hospital increased by 0.89% to 53.44%, and DDDs grew substantially across all groups (compound annual growth rate [CAGR]:25.21%-26,700%). For affordability, DPI decreased from a mid-level among reference countries (10 other countries) in 2017 to the lowest in 2022. DDDc declined after negotiation (CAGR: -6.28% to -70.20%). Reimbursement proportion remained stable (62.40%-80.12%) from 2019 to 2021. Regional equity improved with most ATC classifications (60.66%) having a Gini coefficient below 0.4. CONCLUSIONS:China's NRDL negotiation policy has improved drug availability and affordability while ensuring geographic equity, although risks remain. This study offers insights for policy makers, particularly in low-accessibility countries, to refine drug pricing policies.

BACKGROUND:Depressive symptoms and multiple chronic diseases (MCDs) significantly contribute to the global disease burden among middle-aged and older adults, while few studies have considered the long-term dynamics of depressive symptoms or employed machine learning (ML) models to predict the risk of MCDs. We aimed to identify the similarities and differences risk factors of MCDs based on depressive symptom trajectories among Chinese adults aged 45 and older. METHODS:This cohort study utilized 10-year of national data from the China Health and Retirement Longitudinal Study (CHARLS), with baseline in 2011 and follow-ups in 2013, 2015, 2018, and 2020. Latent class growth modeling (LCGM) and growth mixture modeling (GMM) were employed to identify the long-term trajectories of depressive symptoms. ML algorithms were employed to develop predictive models for MCDs based on these trajectories. Model performance was evaluated using metrics such as the area under the receiver operating characteristic curve (AUC-ROC). We also employed SHapley Additive exPlanations (SHAP) to rank the importance of risk factors and provide both global and local explanation. Finally, we developed a web application to input feature values and obtain predicted probabilities of MCDs. RESULTS:A total of 2552 individuals were analyzed. Four distinct trajectories of depressive symptoms were identified: Stable low symptoms (75.12 %), Persistent high symptoms (6.62 %), New-onset increasing symptoms (12.15 %), and Remitting symptoms (6.11 %). The Random Forest (RF) model performed best for the "Persistent high symptoms" trajectory (AUC-ROC: 0.834 [95 % CI 0.801 to 0.862]), the Extreme Gradient Boosting (XGBoost) model for the "New-onset increasing symptoms" trajectory (AUC-ROC: 0.838 [95 % CI 0.809 to 0.864]), and the Gradient Boosting Decision Tree (GBDT) model for the "Remitting symptoms" trajectory (AUC-ROC: 0.805 [95 % CI 0.771 to 0.838]). Frequently observed risk factors were waist circumference, self-reported health, sleep duration, depressive symptom score, and age. Trajectory-specific risk factors included BMI, grip strength, and nap duration. Sensitivity analyses confirmed the robustness of these findings. The web application is available at: https://chronic-disease-prediction.streamlit.app/. LIMITATIONS:Depressive symptoms and chronic diseases were based on self-reported data without clinical diagnosis, and findings may not be generalizable beyond the Chinese context. CONCLUSIONS:This study provides a scientific foundation for personalized interventions and MCDs prevention among middle-aged and older adults. By identifying both frequently observed and trajectory-specific risk factors, our findings suggest that clinicians could more effectively stratify patients according to their depressive symptom trajectories. For example, individuals with persistent high symptoms may particularly benefit from intensified monitoring of waist circumference, age, and self-reported health, while those with remitting symptoms may require targeted attention to nap duration.

OBJECTIVE:To assess the association between socioeconomic status and vision impairment (Ⅵ) among Chinese elderly aged 65 years and above, and explore its comparison and contrast from 2008 to 2018. METHODS:Using the 2008 and 2018 waves of cross-sectional data from the Chinese Longitudinal Healthy Longevity Survey (CLHLS), which included 12970 and 9702 participants, respectively. Logistic regression models with a stepwise forward approach were employed to assess the association between the household income, educated level, job before retirement and Ⅵ. RESULTS:In 2008, the prevalence of Ⅵ among the elderly aged 65 years and above in China was 16.92% (95%CI: 15.91%-17.98%), which increased to 18.45% (95%CI: 17.41%-19.53%) in 2018. In terms of household income, the highest and upper middle income groups had lower odds of Ⅵ compared with the lowest one in 2008. By 2018, only the upper middle had lower odds (OR=0.761, 95%CI: 0.603-0.961), with its disparity narrowing compared with 2008. For educated level, in 2008, individuals with primary school education, and those with junior high school education or above had lower odds of Ⅵ compared with illiterate individuals. By 2018, the disparity in Ⅵ between the illiterate individuals and those with primary school education widened, while the gap between the illiterate ones and those with junior high school education or above decreased. In addition, after controlling for other factors, the odds of Ⅵ for the individuals educated by junior high school and above was higher than for those educated by primary school (OR=0.691, 95%CI: 0.533-0.896; OR=0.592, 95%CI: 0.494-0.708). Regarding job before retirement, in 2008, compared with the professional, technical or managerial personnel, those engaged in agriculture or domestic work had higher odds of Ⅵ. In 2018, this disparity persisted (OR=1.707, 95%CI: 1.319-2.210; OR=1.925, 95%CI: 1.310-2.829), with the gaps widening compared with the reference group. CONCLUSION:The prevalence of Ⅵ among Chinese elderly increased from 2008 to 2018, with socioeconomic status, specifically household income, educated level, and job before retirement, demonstrating associations with Ⅵ. To be specific, the gap in the odds of Ⅵ across household income strata decreased from 2008 to 2018; disparities among different educated levels generally diminished, while the gap between illiterate individuals and ones educated by primary school widened; and job-before-retirement groups exhibited expanding disparities over time.

BACKGROUND:County-level hospitals are the main providers of health services in rural areas in China. On the eve of the Chinese government's plan to lift the Zero-COVID policy, a number of healthcare workers in county-level hospitals received emergency fourth-dose vaccination against COVID-19. This study aims to evaluate the extent to which these rapid emergency fourth-dose vaccination administered to county-level hospital nurses have provided protection against the Omicron infection wave affecting Mainland China. METHODS:A total of 3,302 clinical nurses from 40 county-level hospitals in mainland China participated in this study. The control group was set to comprise nurses who had not received a fourth dose within the past month or indeed any dose of the COVID-19 vaccine within the previous 6 months. The intervention group was set to comprise nurses who received emergency fourth-dose vaccine doses within the month preceding the lifting of the Zero-COVID policy and those who had not received such a fourth-dose within the prior month but who had received a dose of the COVID-19 vaccine within the previous 6 months. Regression methods were used to analyze the factors associated with the probability of symptoms, duration, recovery time and hospitalization rates. RESULTS:About 13.1% of the nurses surveyed reported having received the emergency fourth-dose vaccination. It emerged that those nurses had a lower risk of developing clinical symptoms such as fever and diarrhea. Where they did experience symptoms, the duration of these tended to be shorter, with an accompanying and significant reduction in hospitalization rates. It was also found that emergency vaccination was associated with significantly shorter recovery time. CONCLUSIONS:The emergency fourth-dose COVID-19 vaccination has had a significant protective effect. At a broader level, reducing hesitancy towards booster shots is an important part of protecting the health of healthcare workers and thereby reducing the impact of the pandemic on the healthcare system and maintaining its resilience.

OBJECTIVE:To examine the relationship between social trust and depressive symptoms among China's elderly, placing special emphasis on the disparities between urban and rural settings. DESIGN:We employed latent profile analysis to categorise individual patterns of social trust. Subsequently, multiple linear regression analysis was employed to determine if there was an association between these identified social trust patterns and depressive symptoms. Additionally, we examined the potential interactive effects between urban-rural differences and patterns of social trust on depressive symptoms. SETTING:The China Family Panel Studies (CFPS) database. PARTICIPANTS:The data was sourced from the CFPS for the years 2018 and 2020, encompassing a total of 5645 participants aged 60 and above. OUTCOME MEASURES:Depressive symptoms were evaluated employing an eight-item adaptation of the Centre for Epidemiologic Studies Depression Scale. The scores from these eight items were aggregated to create an index of depressive symptoms, which was used to quantify the severity of depressive symptoms. RESULTS:The findings demonstrate a significant link between patterns of social trust and depressive symptoms, with individuals manifesting high social trust (HST) showing a lower propensity for depressive symptoms (Beta=-2.26, 95% CI=-2.62, -1.92). Furthermore, a marked association is apparent between social trust patterns and the changes in depressive symptoms. Additionally, urban dwellers (Beta=-0.67, 95% CI=-1.23, -0.11) demonstrate a more pronounced correlation between patterns of social trust and depressive symptoms, particularly within the HST group. CONCLUSION:Our findings highlight a strong link between social trust patterns and depressive symptoms, particularly regarding their changes. Urbanites, notably within the HST group, show a lower risk of experiencing depressive symptoms. There is an urgent requirement to establish social trust-specific interventions to decrease susceptibility to depressive symptoms among the rural populace.

IntroductionThe Chinese government lifted most COVID-19 pandemic restrictions in December 2022, triggering a spike in confirmed cases and higher demand for medications. Consequently, a significant number of residents resorted to social media to seek assistance. This study aimed to evaluate community resilience by leveraging Weibo user datasets, coupled with interpretable machine learning (ML)-based techniques, to identify important resilience characteristics.MethodsDatasets geotagged from the Sina Weibo social media platform between 8 December 2022 and 7 January 2023 were crawled using search terms of “help-seeking” and the keywords of conventional drugs. This study utilized natural language processing (NLP) to label COVID-19-related posts to identify the type of posts, stakeholders’ behaviors, and other information. We built a comprehensive evaluation model, and five ML-based algorithms were compared for analyzing community resilience. Local interpretable model-agnostic explanations (LIME) was employed to verify five models and the XGBoost algorithm showed optimal effects. Shapley Additive Explanations (SHAP) elucidated the best model’s outputs and estimated contributions for key resilience characteristics.ResultsFor this study, 199,709 posts were collected. Out of these, 48,425 posts were identified as help-seeking posts, with more than two-thirds receiving responses from community level. The area under curve (AUC) of the XGBoost model was 0.82 (95% confidence interval [CI]: 0.82, 0.83), and the values of accuracy and F1 score were 0.72 and 0.80, respectively. This result demonstrated that the model can successfully evaluate community resilience and subsequently identify the features driving this outcome. Collective efficacy in providing aid, support from official rescue guidelines, and residents’ rapid response to rescue information were identified as the most important characteristics for evaluating community resilience.ConclusionsThis study is the first to harness social media data to quantify community resilience in China based on a framework we developed. Five updated ML-based algorithms were developed to evaluate community resilience, and XGBoost showed optimal effects. Three characteristics of community resilience were found as potential predictors that can enhance decision-making support to reshape health emergency rescue activities.

Globally, poverty and illness are linked, attracting widespread attention. In China, illness contributes to about 40% of rural poverty. This study sought to investigate how healthcare-seeking behavior differs between impoverished and non-impoverished populations within the same Chinese healthcare delivery system. It also sought to understand how differences should be considered when assessing spatial accessibility to provide more accurate recommendations for healthcare resource optimization and promote village revitalization and health equity in China. Methodologically, a survey conducted in May 2019 in Enshi Prefecture (a national impoverished region in Hubei Province, China) collected data on healthcare resource utilization regarding the inpatient and outpatient needs of both impoverished and non-impoverished populations. A Chi-square test compared their respective healthcare-seeking behaviors in three respects (e.g., preference for healthcare institution type, transportation mode, and travel time). Baidu Map data with healthcare institution locations and real-life travel times were then incorporated to assess spatial access to different types of healthcare institutions. Results showed that in Enshi, the most widespread village clinics (low-level) were generally the most utilized healthcare institutions for outpatient visits, with patients usually walking for about 30 min. The middle-level Township Health Centers (THCs) and high-level public hospitals were the most used for inpatient visits, with patients willing to drive up to 30 min to THCs and 60 min to hospitals. Comparatively, the impoverished have more frequent service demands but tend to choose lower-level healthcare institutions, with longer travel times and limited transportation modes. Although 75% of Enshi’s area was covered within 30 min by village clinics and 51% of the villages were within 60 min’ drive to hospitals, considerable areas remain under-served compared with the shortest travel time targets in China. In conclusion, spatial access to healthcare resources in Enshi must be further improved, especially by strengthening the service capacity of primary healthcare institutions to address the healthcare needs of Enshi’s impoverished population. The disparity in healthcare-seeking behavior between different population groups should be fully considered to effectively allocate limited healthcare resources to promote health equity for vulnerable populations as proposed in international and domestic policies.

As a highly destructive gaming behaviour in Diagnosis-Related Group (DRG), upcoding has garnered increasing scholarly attention. This study considers the prevalence, types and risk characteristics of upcoding during the pilot implementation of DRG payments in China, and it also explores the drivers of upcoding and provides corresponding policy recommendations for improving the system. Quantitative research data were sourced from the DRG payment audit database in City Z between the dates of June 1, 2019 and May 31, 2020, encompassing audit results comprising 200 medical records randomly selected from 28 hospitals. Qualitative research methods were used, including semi-structured interviews conducted with 10 stakeholders with interests in the DRG payment system, and thematic framework of the consequent data. 5,157 (92.01%) valid records were re-abstracted. 666 (12.91%) evaluated records were found to be upcoded, resulting in an additional payment at a rate of 45.27%. Several factors emerged as shedding light on the probability of upcoding, including cases with comorbidities, those undergoing non-operating room procedures and internal medical treatments, cases in for-profit hospitals and cases in tertiary hospitals. The main drivers of upcoding were found to be financial and administrative pressures, dysfunctional attitudes towards upcoding, technical facilitation and lack of supervision. This paper provides a comprehensive analysis of the behaviours and drivers of DRG upcoding in China, considering the unique hospital management system and incentive mechanisms in place. The results demonstrate that, following the initiation of the DRG payment system, providers have begun to engage in upcoding behaviour under various drivers, leading to additional health care expenditures and undermining the effectiveness of the scheme. In terms of mounting a response to this behaviour, understanding it and what drives it can aid in its prevention. This study suggests implementing intelligent audits to strengthen supervision and supporting hospitals in cost management.