Frontiers in Public Health最新文献

Objective: This study examined the association between Parental Involvement in Developmental Advance (PIDA) and mental health in Chinese kindergarten children aged 3-6 years, specifically assessing how parental teaching activities relate to emotional and behavioral adjustments.

Methods: A cross-sectional study in a western Chinese city involved 21,366 children from 189 kindergartens, selected via stratified cluster sampling. PIDA was assessed via the StimQ Scale, measuring parental involvement in teaching activities related to emergent literacy and math/spatial orientation. Children's mental health was evaluated using the Strengths and Difficulties Questionnaire (SDQ), with outcomes operationalized as total difficulties scores and prosocial behavior scores.

Results: Each unit increase in PIDA score was corresponded to a 2% lower risk of total difficulties (OR = 0.98; 95% CI: 0.97-0.99) and a 4% higher likelihood of prosocial behavior (OR = 1.04; 95% CI: 1.03-1.05). Non-linear relationships showed optimal benefits at PIDA scores of 12 for total difficulties and 11 for prosocial behavior, beyond which excessive involvement elevated the risk of total difficulties by 18% (OR = 1.18; 95% CI: 1.14-1.22) and reduced prosocial behavior by 2% (OR = 0.98; 95% CI: 0.96-0.99). Subgroup analyses further indicated stronger effects in specific demographics, such as families with lower socioeconomic status. Significant interactions were found between PIDA and parental education level and employment status.

Conclusion: Balanced parental involvement enhances children's mental health by reducing total difficulties and boosting prosocial behavior. Excessive involvement may have negative effects, highlighting the need for tailored interventions to optimize early childhood mental health.

Objective: Individuals during emerging adulthood, particularly college students, show a higher prevalence for sedentary behavior and its associated depression. The aim of this study is to explores depression among college students in emerging adulthood in China, investigate the association between different levels of physical activity (PA) and depression among emerging adults and examine the potential mediating role of subjective exercise experience.

Methods: A total of 2,516 college students in China were selected as research subjects. The short form of an international physical activity questionnaire, a self-rating depression scale, and a subjective exercise experience scale were used to assess physical activity, depression, and exercise experience, respectively.

Results: (1) In terms of depression, 921 emerging adults reported depressive symptoms (40.5%), among whom 707 had mild depression (31%) and 214 had severe depression (9%). Emerging adults with high levels of PA have significantly lower levels of depression than those with medium and low levels of PA do, and those with low levels of PA have higher levels of depression than those with medium levels of PA do. (2) In terms of subjective exercise experience, compared with those who engage in medium or low levels of PA, emerging adults with high levels of PA experience more positive (positive wellbeing, PWB) and fewer negative (psychological distress, PD; fatigue) emotions during exercise. Additionally, compared with emerging adults with lower levels of PA, those with medium levels of PA experience fewer negative emotions (fatigue). (3) Depression was negatively correlated with PA and PWB and positively correlated with PD and fatigue. PA, PWB, PD, and fatigue all served as significant predictors of depression, and their total predictive power was 45.6%. PA had a significant direct effect on depression and a significant total indirect effect through its mediators. Four significant pathways were involved, and PWB emerged as the primary mediator. The most substantial pathways included direct mediation through PWB and serial mediation through PWB and PD.

Conclusion: The rate of depression among emerging adults in China is concerning. Higher levels of PA were associated with lower levels of depression; the more PA that one engaged in, the better their depression status. Both the amount of PA and the number of subjective exercise experience (PWB, PD, fatigue) were significantly associated with depression. The relationship between PA and depression involved multiple psychological pathways, which were primarily characterized by the mediating role of enhanced PWB experienced during physical activity. This highlights that future exercise interventions should target the enhancement of subjective wellbeing during activity, rather than focusing solely on increasing its volume or intensity.

Background: To evaluate the real-world effectiveness of an artificial intelligence (AI) and big data-driven personalized chronic disease management model for type 2 diabetes mellitus (T2DM) patients, compared to conventional nurse-led management, and to identify factors associated with successful glycemic control within the personalized model.

Methods: A retrospective cohort study was conducted involving 280 T2DM patients discharged from a single hospital between January 2019 and December 2024. Patients were divided into a conventional management group (n = 100) and a personalized management group (n = 180). The personalized group utilized a model integrating gradient boosting (XGBoost) for risk prediction and rule-based reasoning with reinforcement learning to dynamically generate individualized dietary, exercise, and blood glucose monitoring plans via a mobile application (APP). Both groups received 6 months of follow-up. Glycemic control [fasting blood glucose (FBG), 2-h postprandial glucose (2hPG), glycated hemoglobin (HbA1c)], self-care activities [Summary of Diabetes Self-Care Activities (SDSCA) scale], and quality of life [Diabetes-Specific Quality of Life (DSQL) scale] were assessed at baseline and 6 months. Within the personalized group, patients were further categorized into well-controlled (HbA1c ≤ 6.5%, n = 98) and poorly-controlled (HbA1c > 6.5%, n = 82) subgroups for case-control analysis.

Results: At 6 months, the personalized management group demonstrated significantly better glycemic control (FBG: 6.79 ± 0.72 vs. 7.03 ± 0.89 mmol/L, p = 0.022; 2hPG: 6.27 ± 1.18 vs. 6.62 ± 1.16 mmol/L, p = 0.018; HbA1c: 6.48 ± 0.53% vs. 6.63 ± 0.46%, p = 0.018), superior self-care scores across all SDSCA domains (all p < 0.05, largest improvement in special diet: p = 0.001), and significantly higher quality of life (all DSQL dimensions p < 0.05) compared to the conventional group. Within the personalized group, multivariate analysis identified alcohol consumption [odds ratio (OR) = 3.576, p < 0.001], low baseline high-density lipoprotein cholesterol (HDL-C) (OR = 0.102, p = 0.007), and reduced blood glucose monitoring adherence (OR = 0.958, p < 0.001) as independent risk factors for poor control, while higher exercise plan completion was protective (OR = 0.976, p = 0.037).

Conclusion: The AI and big data-driven personalized management model significantly improved glycemic control, self-care behaviors, and quality of life in T2DM patients over conventional care within 6 months. Success within the model is influenced by behavioral and biological factors, alongside alcohol consumption. This approach demonstrates promise for enhancing diabetes care.

Background: Children's unintentional injuries represent a global public health problem. Guizhou, as an economically underdeveloped province in southwest China, faces challenges in children's unintentional injuries prevention and control, such as scarce resources and inadequate family supervision. Local social organizations play a crucial role in bridging the gap in government services. However, existing studies have predominantly focused on intervention models led by medical institutions or schools, lacking a systematic exploration of the practices and challenges of grassroots social organizations in this field.

Objective: This study aims to explore the practices of grassroots social organizations in Guizhou Province regarding the prevention and control of children's unintentional injuries, identify the internal and external challenges they face, and subsequently propose pathways for enhancement. The goal is to provide an evidence base for optimizing the governance of children's safety at the grassroots level.

Methods: This is a qualitative study. Using purposive sampling, semi-structured in-depth interviews were conducted in July 2024 with 15 social workers and 7 school administrators from two cities and one county in Guizhou Province. Thematic analysis of interview data was conducted using NVivo 15.

Results: Currently, as frontline implementers, social organizations have developed various localized intervention strategies, such as experiential education and peer-led advocacy. Through collaboration with schools and communities-for instance, by constructing "grid-based management" and "full-time guardianship" models for left-behind children-they have achieved notable effects in enhancing children's safety awareness and reducing injury incidents. However, the sustainability of these practices faces severe challenges. Internal challenges include insufficient human resources and funding and an imperfect training system. External challenges include poor cross-sectoral collaboration, a mismatch between interventions and children's developmental stages, and weak family supervision. Based on this, participants suggested enhancing prevention and control practice by increasing resource investment, strengthening government-led collaborative mechanisms, and applying innovative technologies.

Conclusion: Grassroots social organizations in Guizhou Province demonstrate localized innovative potential in the prevention and control of unintentional injury among children, but their effectiveness is constrained by systemic shortcomings. In the future, it is necessary to establish a multi-source resource support network, improve cross-sectoral collaboration mechanisms, and develop intervention strategies adapted to children's cognitive characteristics.

[This corrects the article DOI: 10.3389/fpubh.2025.1756127.].

Introduction: Reliable sarcopenia risk prediction models are essential for identifying older adults who are currently non-sarcopenic but at risk of developing sarcopenia in the future, thereby enabling early and personalized prevention strategies. However, the prediction models for sarcopenia have not yet been systematically evaluated. This systematic review aimed to conduct a comprehensive overview and critical appraisal of current sarcopenia risk prediction models.

Methods: We conducted a systematic search across MEDLINE, Embase, Cochrane Library, and SCI-EXPANDED. Eligible primary studies on sarcopenia prediction models were identified based on the CHARMS checklist (CHecklist for critical Appraisal and data extraction for systematic Reviews of prediction Modelling Studies). The Prediction model Risk Of Bias Assessment Tool (PROBAST) was applied to evaluate risk of bias and clinical applicability.

Results: Twenty-six sarcopenia prediction models were identified, mostly targeting community-dwelling older adults or patients. Twenty-three studies developed diagnostic prediction models, while only three studies established sarcopenia prognostic models. Age, BMI, calf circumference and gender were most frequently utilized predictors. Despite reported discriminative performance ranging from moderate to excellent (AUC > 0.70), 96.1% of prediction models exhibited high risk of bias due to significant methodological shortcomings, suggesting that model performance might be overestimated. Moreover, most existing prediction models were diagnostic study design, limiting their ability to predict the future risk of sarcopenia development.

Conclusion: Most existing sarcopenia prediction models demonstrated moderate to high discriminatory performance. However, due to their predominantly diagnostic study design and high risk of bias, these models cannot yet be broadly recommended for routine clinical application in the early identification of high-risk older adults with sarcopenia. Future studies are needed to develop and externally validate practical, accurate prognostic sarcopenia models to fulfill sarcopenia early prevention.

Systematic review registration: The protocol has been registered on the Open Science Framework (10.17605/OSF. IO/BFDK6).

Background: Policy experimentation has become a central strategy for governments seeking to navigate complexity in healthcare reform. In China, extensive rounds of county-level healthcare reform pilots aim to strengthen primary care and improve service equity. However, while some pilots expand successfully, others stagnate or are suspended. The underlying mechanisms that generate these divergent outcomes remain insufficiently examined.

Objectives: This study investigates how healthcare reform pilots evolve in practice by identifying the key actors involved in pilot management, analyzing the driving forces that shape pilot performance, and explaining the different developmental trajectories of pilots within China's county medical service community (CMSC) reform.

Methods: Drawing on large-scale fieldwork across 23 CMSCs, we collected qualitative data through semi-structured interviews and focus group discussions with 127 internal and external stakeholders. Using grounded theory, the data were analyzed through open, axial, and selective coding, and subsequently integrated to construct a typological framework explaining variations in policy pilot outcomes.

Results: Drawing on the coding framework, the analysis identifies two overarching forces shaping CMSC pilot implementation: institutional compatibility and policy potential energy. Institutional compatibility reflects the alignment of CMSC policy design, healthcare insurance payment rules, interdepartmental coordination, incentive structures, and resource-benefit allocation. Policy potential energy derives from the redistribution of administrative power, political momentum from higher-level governments, the capacity of policy entrepreneurs, and the contextual foundations of social capital and trust. Mapping these dynamics reveals four pilot trajectories: upscaling, adjustment, suspension, and autonomy.

[This corrects the article DOI: 10.3389/fpubh.2025.1653576.].

As global aging accelerates, there is a dramatic shift in the structure of world health. Frailty marks the entry into aging and becomes an important factor affecting the health of older adults. In order to reduce the harm of infirmity to the physical health of the older adults, international interventions for infirmity have been continuously developed, and exercise management has been widely studied as an effective intervention strategy in geriatric infirmity, but the domestic research on infirmity started late and has been less studied. This paper reviews the definition and clinical manifestations of frailty in the older adults, types of exercise interventions and assessment of exercise effects, and research progress in health management theory, with a view to providing reference for the development of exercise programs for frail older adults.

Antimicrobial resistance (AMR) poses a critical threat to global health, driven by the extensive use of antibiotics in both human medicine and livestock production. In the context of the One Health framework, this review investigates the role of the gut microbiome and resistome, which represents the collection of antimicrobial resistance genes (ARGs), within livestock and among occupationally exposed workers. Intensive farming practices often involve routine, subtherapeutic antibiotic use, fostering antibiotic-resistant bacteria (ARB) in the gastrointestinal tract of animals. These ARB and ARGs are excreted into the environment, contributing to resistance spread through mobile genetic elements. From a Planetary Health perspective, this environmental dissemination reflects how human-driven livestock practices can perturb ecosystems, creating global health risks that link animal, human, and environmental well-being. Human exposure, particularly among farm workers and veterinarians, raises significant concerns about zoonotic transmission of pathogens and, potentially, ARB. Novel advances in metagenomic and metatranscriptomic technologies enhanced our understanding of gut microbial communities and their resistomes, revealing overlaps in ARG profiles between animals and livestock workers. These technologies also support the development of novel microbiome-targeted strategies, including prebiotics, probiotics, food supplementation and workplace-improvement strategies, aimed at reducing antimicrobial use and restoring healthy microbiome balance. The review also highlights the importance of integrated surveillance and cross-sectoral collaboration to monitor and control AMR transmission. Understanding the ecological dynamics of the gut resistome in livestock systems is essential for designing effective interventions that safeguard both animal and human health.