Frontiers in Public Health最新文献

With the widespread use of antiretroviral therapy, human immunodeficiency virus (HIV) infection is considered to be a manageable chronic disease, but it is accompanied by an increased burden of comorbidities. Baise is an area characterized by a high incidence of HIV infection in Guangxi, China. However, research on its comorbidity patterns is limited. This study aims to clarify the burden, patterns, network features, and temporal evolution of comorbidities among HIV inpatients in Baise. We collected electronic medical records from 3,294 HIV patients hospitalized at Baise People's Hospital between January 2019 and August 2024. The Apriori algorithm was employed to extract association rules between diseases, while Gephi was utilized to construct comorbidity social network diagrams of the data. The findings revealed that 99.48% of patients presented with two or more comorbidities, with a median of 9 comorbidities per patient. Notably, the median number of comorbidities peaked at 11-12 during 2021-2022, subsequently decreasing to 7 in 2023-2024. The comorbidity patterns transitioned from (B20 + B37 → B99) in 2019 to (E46 + B20 → E87 + D64) in 2021 and ultimately evolved into (J18 + E87 → E46) by 2023. Social network analysis indicated that electrolyte imbalances (E87), HIV-related infections (B20) and candidiasis (B37) served as the core disease nodes within the network, displaying close connections with numerous other disease nodes. The identified specific comorbidity patterns can serve as early warnings and screening tools in clinical practice and they underscore the necessity for multidisciplinary care for HIV patients.

Background: High-speed running (HSR) and sprint exposure are monitored in soccer, but associations with injury are uncertain.

Objective: To synthesis evidence on associations between HSR exposure and injury risk/occurrence, and to explore heterogeneity.

Methods: PubMed, Scopus and Web of Science were searched. No date or language restrictions were applied. Eligibility criteria included observational studies in soccer quantifying training and/or match HSR/sprinting using microtechnology and reporting extractable associations with injury outcomes. Risk of bias was assessed with QUIPS. Narrative synthesis was undertaken without meta-analysis.

Results: From 3,824 records, 22 studies were included. Most were professional/elite and used GPS with absolute speed thresholds. Outcomes mainly involved time-loss or non-contact soft-tissue injuries. Across studies using relative change measures (e.g., acute:chronic contrasts or injury-week vs. control comparisons), short-horizon increases or disproportionate HSR/sprint exposure relative to recent history more often aligned with higher injury risk. In contrast, studies analyzing absolute weekly HSR volume more frequently reported negligible or inconsistent associations within typical exposure ranges, with no reproducible dose threshold emerging. Overall risk of bias was high in 20/22 studies.

Conclusions: Sudden increases in HSR/sprint-related load may be associated with injury, but heterogeneity and bias limit certainty and preclude definitive thresholds.

Registration: OSF (osf.io/wquh2).

The COVID-19 pandemic exacerbated many known risk factors for post-traumatic stress disorder (PTSD) among healthcare workers. This systematic review and meta-analysis examines pooled prevalence estimates of probable PTSD among this cohort prior to COVID-19 compared to during COVID-19 and investigates time trends in prevalence. Systematic multi-database literature searches were conducted to identify studies published between January 2017 and July 2023. Included studies reported the prevalence of probable PTSD, measured by validated screening tools, in clinical healthcare workers. Two reviewers independently conducted study screening, data extraction, and quality assessment. Random-effects meta-analyses were performed to estimate pooled prevalence of probable PTSD among healthcare workers in each time period. Subgroup analyses were carried out for year, profession, quality of study, COVID-19 mortality rates, and income level within the country of study. Screening identified 21 papers comprising 11,838 healthcare workers published in the 3 years preceding the pandemic, and 129 papers reporting on 130,363 healthcare workers during the pandemic. The pooled prevalence estimate of probable PTSD prior to the pandemic was 15.5% (95% CI: 12.3-19.3%) and this significantly increased during the pandemic to 24.8% (95% CI: 22.0-27.8%), peaking early in the pandemic in 2020 before returning to pre-pandemic levels in 2022. During the pandemic, prevalence estimates were significantly higher among nurses and those in countries with high COVID-19 mortality rates, whilst no significant difference was observed between studies conducted in high-income versus low- and middle-income countries. Substantial heterogeneity was observed. The findings of this review suggest that prevalence of PTSD among healthcare workers significantly increased following the COVID-19 outbreak. By the third year of the pandemic, probable PTSD prevalence rates appear to return to pre-pandemic levels, although these levels remain concerningly high. These findings support the call for targeted interventions to protect healthcare worker wellbeing, particularly during healthcare emergencies.

Systematic review registration: https://www.crd.york.ac.uk/PROSPERO/view/CRD42022364955, unique identifier is CRD42022364955.

Adolescents living with HIV (ALHIV) in Zambia experience poorer treatment outcomes than adults, with lower viral suppression and higher loss to follow-up rates. Electronic medical record (EMR) systems such as SmartCare aim to strengthen patient monitoring, but their utility is contingent on high data quality. Accurate monitoring of ALHIV treatment outcomes is critical for improving patient care and supporting progress toward UNAIDS 95-95-95 targets. We conducted a retrospective cross-sectional review of EMR data for ALHIV on antiretroviral therapy in selected Lusaka facilities (January-December 2023). Data were extracted from SmartCare and assessed using the WHO Routine Data Quality Assessment framework across three dimensions: completeness, correctness, and consistency. Records from 3,978 ALHIV were analysed. Socio-demographic variables (gender, date of birth, age at ART initiation) and treatment data (ARV regimen) performed strongly, with ≥98% completeness, correctness, and consistency. In contrast, clinical variables showed substantial gaps. Completeness for baseline (n = 1,707) and current (n = 2,149) CD4 counts was 43% and 54%, respectively, though correctness and consistency exceeded 99%. Pregnancy and breastfeeding data among female adolescents (n = 2,177) were particularly poor, with completeness of 4% and 12%. By comparison, history of tuberculosis (100%) and current viral load results (91%) were reliably captured. Whereas SmartCare demonstrated strong reliability for demographic and treatment indicators, notable weaknesses in the completeness of key clinical variables, such as CD4 count and pregnancy/breastfeeding status were observed. These gaps may reflect variability in data entry workflows and system-level factors, including EMR upgrades, highlighting areas for targeted improvement. We recommend targeted training, system redesign to enforce mandatory entry of critical fields, and routine data quality monitoring to ensure EMR systems provide accurate and actionable data. Addressing these gaps would facilitate optimising HIV care and support progress toward achieving the UNAIDS 95-95-95 goals for ALHIV in Zambia.

Background: The number of patients with chronic kidney disease (CKD) continues to rise in China, where maintenance hemodialysis (MHD) is a primary treatment. However, long-term hemodialysis is frequently associated with malnutrition, which severely compromises patients' quality of life and prognosis.

Objective: To systematically evaluate the incidence and influencing factors of malnutrition in MHD patients by using Meta-analysis methods, thereby providing a basis for early clinical identification and intervention.

Methods: We systematically searched PubMed, Web of Science, the Cochrane Library, CINAHL, China National Knowledge Infrastructure (CNKI), VIP, Wan Fang Data and SinoMed. The search covered the period from database inception to October 10, 2025, for studies investigating factors influencing malnutrition in MHD patients. Data were analyzed using Stata 15.0. A random-effects model was applied in cases of substantial heterogeneity (I ² ≥ 50%), otherwise a fixed-effects model was used. Publication bias was assessed using Egger's test, and the trim-and-fill method was employed if necessary.

Results: A total of 26 studies involving 5,055 patients were included, and the overall incidence of malnutrition in MHD patients was 46.9% (95% CI: 41.8-52%). Meta-analysis showed that age (OR = 1.509), body mass index (BMI) (OR = 1.544), dialysis vintage (OR = 2.265), urea clearance index (Kt/V) (OR = 2.019), serum C-reactive protein (CRP) (OR = 3.013), high-sensitivity C-reactive protein (hs-CRP) (OR = 2.104), protein intake (OR = 3.018), frequency of dialysis (OR = 2.100), depression (OR = 2.671), anxiety (OR = 2.531), monthly household income (OR = 1.563), serum albumin (ALB) (OR = 1.115), frequency of erythropoietin (EPO) use (OR = 1.506) and duration of dialysis per session (OR = 1.879) were the main influencing factors (p < 0.05).

Conclusion: Malnutrition is present in 46.9% of maintenance hemodialysis patients. Individualized assessment and intervention targeting these key factors are essential to improve nutritional status and patient prognosis.

Systematic review registration: https://www.crd.york.ac.uk/PROSPERO/, registration no. CRD42024596946.

Background: Hypertension disproportionately affects older adults in rural settings. Labour-type physical activity is commonly assumed to protect cardiovascular health, yet it may not replicate the physiological stimulus of structured exercise. Evidence remains limited regarding how labour intensity and blood pressure-free obesity-metabolic phenotypes relate to hypertension in cold-climate rural populations.

Methods: This community-based cross-sectional study analysed 2,191 adults aged ≥65 years from a government health examination programme in a cold-climate agricultural county in Northeast China. Blood pressure-free obesity-metabolic phenotypes were defined using BMI, triglycerides (TG), and HDL-C only. Physical activity was quantified using a cohort-specific PA Index (weekly frequency × duration) and categorised as inactive (0), low active (0-<180), and high active (≥180; median among active participants). We fitted multivariable logistic regression models for prevalent hypertension, excluding blood pressure (BP) variables to avoid circularity, and developed leakage-free prediction models using non-haemodynamic predictors.

Results: The prevalence of hypertension was 75.9%. Hypertension prevalence differed across BP-free phenotypes (χ²  = 28.07, p < 0.001), ranging from 75.1% (MHNO) to 89.7% (MUO). Compared with inactive participants, the odds of prevalent hypertension were higher in the low active group (OR = 1.85, 95% CI 1.32-2.58) and the high active group (OR = 2.00, 95% CI 1.61-2.49) (both p < 0.001). In leakage-free prediction, the primary LASSO model achieved a test-set ROC-AUC of 0.664 and PR-AUC of 0.841, with good calibration (slope 1.10).

Conclusion: In this cold-climate rural cohort, BP-free metabolic-obesity phenotypes and higher labour-type activity volume were independently associated with higher odds of prevalent hypertension, which is not consistent with the assumption that "work equals exercise." Leakage-free prediction using routinely collected screening variables may help inform outreach prioritisation and follow-up planning in resource-limited agricultural communities, pending external validation and implementation evaluation.

Social prescribing involves trusted individuals in clinical and community settings identifying non-medical, health-related social needs and connecting people to community-based supports through a collaboratively developed social prescription. Social prescribing operates within a dynamic, complex adaptive system, making evaluation challenging. This study presents two Australian case studies of co-designed social prescribing programs-Connect Local in Melbourne and Spark in Adelaide-to examine how evaluation can be conceptualized and implemented. Rather than focusing on program delivery, these case studies are used to interrogate the processes, methodological challenges, and system conditions that shape how impact is understood. The evaluation challenges for both initiatives included shared complexities: the need to balance meaningful data collection with individual and community preferences; measuring impact to meet the needs of interest holders; and the evolution of the contexts in which the programs are delivered and their influence on what constitutes 'success.' Analyzing the two case studies against assumptions of linear, simple systems highlighted that a shift in how evaluation is conceptualized and undertaken is required. Impacts were not static, discrete, measurable outputs, but dynamic processes shaped by relationships, shared meaning-making, and adaptive capacity. Conventional evaluation frameworks centered on linear logic models and fixed indicators do not effectively capture impacts driven by relationships, community capacity, and adaptive change. Therefore, program success must be reframed as an emergent presence in which outcomes unfold through interactions between individuals, organizations, and wider systems. This study argues for a shift from milestone-based models to ongoing stewardship-oriented approaches that prioritize monitoring patterns, relationships, and adaptive responses. Indicators may need to shift from static quantitative measures to relational indicators that reflect relationship alignment, coherence of working practices, and growth within the networks and relationships. The question this research poses is: How can evaluators identify and track indicators that remain meaningful when both the context and intervention are evolving, and thereby the outcomes are also changing? By examining the evaluation journeys of Connect Local and Spark, this study demonstrates the need for methodological approaches that align with complexity, center on community voice, and explain the emergent, co-constructed nature of social connection impacts.

Introduction: Social housing plays a critical role in addressing housing inequality and promoting well-being. This paper examines the creation of a registry of social housing sites across all six Ontario Health (OH) regions.

Methods: For all 47 housing service providers in Ontario, social housing address, provider type, and building type were extracted from their website or from documents provided by the housing organization. The Registry included rent-geared-to-income housing with unique or minimally shared postal codes. Descriptive statistics were analyzed for the housing site characteristics aggregated by OH region.

Results: 2,109 social housing sites were included in the final Registry, including 472 designated as seniors only (low-income naturally occurring retirement communities, LI-NORCs). There were regional differences in the proportions of each tenant designation, postal code uniqueness, housing provider types, and building classifications. For instance, the Toronto and North West regions had higher government-owned social housing sites (61% and 57%), whereas the East region had more non-profit owned sites (55%). Apartments were the most common building type across regions (57%), with varying proportions of townhouses and single/semi-detached houses.

Discussion: A social housing registry, the SHO, has been established, serving as a valuable resource for health research, especially for marginalized populations. It can be linked to other datasets for future studies. The SHO Registry provides a robust method for the determination of LI-NORCs (low-income naturally occurring retirement communities).

Background: Menstrual health is a critical public health issue tied to gender equity and adolescent well-being. Brazil's School Health Program (SHP) mandates sexual and reproductive health education, yet structured models for integrating medical students into this policy-driven, community-based work are scarce. This study describes and analyzes an experiential learning project where first-year medical students facilitated menstrual health education within the SHP.

Methods: A qualitative case study was conducted. Six female medical students developed and delivered a developmentally tailored educational session on puberty, menstrual physiology, and dignity to 5th-grade (elementary school) girls at a public school, as part of the 2025 activities of the SHP. Data from structured reflective debriefings with students, supervisor observations, and SHP records were analyzed through thematic content review and consensual validation.

Results: Analysis revealed three primary learning outcomes for medical students: (1) Development of core communication and empathetic skills for discussing sensitive topics; (2) A deepened, experiential understanding of menstrual stigma and social determinants of health; and (3) Practical insights into intersectoral collaboration and public policy implementation through the SHP framework. School staff observed a marked reduction in embarrassment and increased openness to discussion among the adolescent participants.

Conclusion: Integrating menstrual health promotion into early medical training via established public policy platforms like the SHP is feasible, low-cost, and highly effective. This model serves as a dual-purpose intervention, fostering socially accountable, humanistic competencies in future physicians while simultaneously advancing adolescent health literacy and dignity. It provides a replicable framework for community-engaged medical education in Brazil and similar low-resource settings.

[This corrects the article DOI: 10.3389/fpubh.2025.1726568.].