Public health challenges最新文献

Background: Diabetes mellitus (DM) is a chronic metabolic disease resulting from insulin deficiency, leading to hyperglycemia. Effective management, particularly for insulin-dependent patients, relies heavily on correct insulin administration. Assessing patient knowledge regarding this is crucial for identifying educational needs.

Objectives: This study aimed to assess the level of knowledge on insulin administration among DM patients attending Kathmandu Diagnostic Center, Lalitpur.

Methods: A descriptive, cross-sectional study was conducted from February 2, 2024, to April 2, 2024. A total of 187 DM patients were included. Data were collected using a semi-structured questionnaire covering various aspects of insulin administration and analyzed using Statistical Package for Social Science (SPSS) version 23.

Results: The study found that 84% of participants had adequate knowledge of insulin administration, though gaps existed in understanding insulin types and postinjection care. Most patients demonstrated good adherence to injection techniques such as priming and aseptic practices, but fewer consistently checked insulin expiry or practiced proper needle disposal. Knowledge and practice were significantly associated with diabetes duration, insulin therapy length, and age, whereas the type of delivery device showed no significant impact.

Conclusions and recommendations: This study demonstrates that although the majority of patients with DM in Nepal possess adequate knowledge of insulin administration, critical gaps remain, particularly in understanding insulin complications, types, and comprehensive postinjection care. Knowledge positively correlates with correct insulin administration practices, underscoring the importance of patient education. Moreover, longer disease duration, extended insulin therapy, and older age are significantly associated with better knowledge and adherence, whereas the type of insulin delivery device does not influence these factors. These findings highlight the urgent need for targeted, age- and experience-tailored educational interventions to improve insulin management skills and self-care practices. Improving patient literacy and technique can contribute substantially to optimizing glycemic control and reducing diabetes-related complications in this population.

An outcomes/impact evaluation was undertaken (July 2023-April 2024) to evaluate the work of the World Health Organization (WHO) infection prevention and control (IPC) coronavirus disease (COVID-19) response team during the COVID-19 pandemic and to identify how to better prepare for the next pandemic. The evaluation used mixed methods, focusing on three pillars of the team's work: (1) interim guidance and guidelines; (2) OpenWHO IPC courses; and (3) risk communication and community engagement (RCCE) interventions. A literature review, interviews with WHO headquarters and regional staff, case studies, and multicountry surveys were undertaken. Of the national representatives surveyed, 97% reported that the guidelines impacted their work; overall 76% of Member States used RCCE interventions and products; and 99% of course participants used what they learned professionally or personally. Member States identified gaps relating to national contextualization, availability of feedback and monitoring mechanisms, and knowledge sharing. There is strong evidence of the impact, effectiveness, and use of this team's work in developing IPC COVID-19 guidelines and through courses developed and shared via OpenWHO; however, there is weaker evidence on the impact of RCCE products/interventions as a standalone activity. To be better prepared for the next pandemic, Member States and the WHO need to collectively identify how best to sustain the IPC gains and address the gaps.

The workforce in many industries is ageing. With longer life expectancy and extended retirement ages, the proportion of older workers is growing, leading to challenges such as reduced physical and cognitive abilities. However, older workers bring valuable experience, knowledge, and skills that can benefit organizations. Technologies have a crucial role in this challenge, that is, in reducing physical and cognitive loads and improving workplace safety. Within the Industry 5.0 paradigm, the focus is moving away from solely automation and productivity toward improving human abilities and promoting worker well-being. Industry 5.0 aims to create more personalized, efficient, and flexible work environments that can adapt to diverse worker needs, including those of older workers. This study aims to investigate the challenges and opportunities associated with an ageing workforce and how a human-machine collaboration can enhance their productivity and well-being, promoting a human-centric approach that leverages their strengths while addressing their evolving needs.

Background: Dissociation, involving disruptions in cognition, perception, and identity, is closely linked to trauma and various psychiatric disorders but remains underrecognized, especially in non-Western contexts. Although tools like the Dissociative Symptoms Scale-Brief (DSS-B) have improved assessment, validated Arabic-language versions are lacking. Given rising mental health concerns and limited resources in the Arab world, this study aims to evaluate the psychometric properties of the Arabic-translated DSS-B to support culturally appropriate diagnosis and research on dissociation.

Methods: In this cross-sectional study, participants from KSA, Egypt, Lebanon, Palestine, and Jordan were recruited via snowball sampling and completed an online survey. The DSS-B was translated into Arabic using a forward-backward method and reviewed by experts for cultural and semantic accuracy. Participants also completed validated Arabic versions of the Jong-Gierveld Loneliness Scale, Patient Health Questionnaire-4, and the Brief Irritability Test.

Results: Among 1494 participants (mean age = 24.97; 74.5% female), Palestinians showed the highest dissociative symptoms. Confirmatory factor analysis confirmed good model fit, excellent reliability (ω = 0.93; α = 0.92), and strong convergent validity average variance extracted (AVE = 0.70). Measurement invariance across genders and countries was supported, with no significant gender differences in scores. Dissociation was positively correlated with depression-anxiety (r = 0.57), irritability (r = 0.51), and loneliness (r = 0.45), confirming concurrent validity, while discriminant validity was also established.

Conclusion: This study validates the Arabic DSS-B as a reliable, valid, and culturally adaptable tool for assessing dissociation in Arab populations, reinforcing its clinical and research utility. Future research should explore its generalizability in underrepresented groups, use longitudinal and clinician-based assessments, and investigate neurobiological underpinnings to deepen understanding and application of dissociation measurement globally.

Artificial intelligence (AI) is rapidly transforming maternal healthcare through tools like risk prediction algorithms, telemedicine platforms, and postpartum support chatbots. Although these innovations offer promise, particularly in low- and middle-income countries (LMICs), their impact on health equity remains contested. This commentary explores how AI can either bridge or widen maternal health inequities, depending on how it is designed, governed, and implemented. We introduce a conceptual framework comprising four interdependent domains that shape equity outcomes in maternal health: inclusive data practices, equitable governance, participatory design, and local capacity-building. Drawing from interdisciplinary literature, we situate AI within broader health and social systems and argue for equity-oriented approaches that foreground representation, accountability, and community engagement. By examining both opportunities and risks, this commentary offers practical, context-sensitive recommendations for LMICs to ensure AI serves as a tool for justice in maternal healthcare.

Introduction: Globally, 17.7% of under-5 mortality and 36.1% of neonatal mortality occur due to preterm birth complications. Ethiopia is one of the top 10 countries with the highest neonatal mortality. Data on survival status and predictors of mortality among preterm neonates in Ethiopia remain limited. This study aimed to assess the survival status and predictors of mortality among preterm neonates admitted to the neonatal intensive care units of public hospitals in Central Ethiopia.

Methods: A facility-based prospective cohort study was conducted among 347 preterm neonates admitted to the neonatal intensive care units in selected public hospitals from October 1, 2022, to June 28, 2023. All admitted preterm neonates were enrolled. Data were collected using a structured questionnaire. The Kaplan-Meier curve was used to estimate the mean survival time and cumulative survival probability. To declare the associations, the Cox proportional hazards model was used to identify mortality predictors with adjusted hazard ratios with 95% confidence interval (CI) and p value.

Results: Of 347 preterm newborns, 104 (29.97%) died, resulting in an incidence rate of 39.88 (95% CI: 32.90-48.33) fatalities per 1000 person-day observations. Born from mothers with chorioamnionitis (AHR 3.89; 95% CI: 2.44, 6.18), born from mothers with gestational diabetes mellitus (GDM) (AHR 2.01; 95% CI: 1.27, 3.17), Apgar score at fifth minute less than 7 (AHR 1.87; 95% CI: 1.04, 3.36), having respiratory distress syndrome (RDS) (AHR 2.03; 95% CI: 1.14, 3.61), receiving kangaroo mother care (KMC) (AHR 1.86; 95% CI: 1.18, 2.94), and born less than 32 weeks of gestation (AHR 2.52; 95% CI: 1.27, 3.17) were significant predictors of mortality.

Conclusions: Around one-third of preterm neonates died. Improving the survival status should emphasize high-risk neonates, with low fifth-minute Apgar scores, having RDS, not receiving KMC, and neonates born to mothers with chorioamnionitis or GDM.

Background: Tricuspid regurgitation (TR) is a common occurrence in patients with heart failure (HF), and its role in disease progression has gained attention in recent years. Although TR can worsen clinical outcomes in HF patients, the impact of gender, racial, and socioeconomic factors remains largely unexplored. With growing evidence supporting the role of percutaneous interventions for the treatment of significant TR, understanding these disparities is more crucial than ever.

Methods: Data were extracted from the National Inpatient and National Readmission 2016-2020 Databases. We used ICD-10 code I50 to identify the patients primarily admitted for HF and subdivided the cohort into two groups based on the presence or absence of TR. We performed multivariable logistic regression analysis to determine odds of the in-hospital mortality and multivariable Cox regression analysis to assess the 30- and 90-day hospital readmission in HF patients with and without TR. All the analyses were adjusted for age, gender, insurance status, Charlson comorbidity index, and hospital characteristics. STATA 16 software was used for analysis.

Results: There was no difference in the in-hospital mortality among HF patients with and without TR (OR: 1.04, 95% CI 0.94-1.16, p = 0.442) except in certain subgroups of HF patients. HF patients with TR were 6% more likely to have HF-specific readmission in 30 days (HR: 1.06, 95% CI 1.00-1.13, p = 0.044) and 9% more likely to have HF-specific readmission in 90 days (HR: 1.09, 95% CI 1.03-1.15, p = 0.002). Subgroup analysis revealed significant gender, racial, and socioeconomic disparities in the in-hospital mortality and the readmission outcomes of HF patients with TR compared to those without TR.

Conclusion: In our population-based survey analysis, we observed significant gender, racial, and socioeconomic disparities in the clinical outcomes of HF patients with TR compared to those without TR.

Background: Nigeria's aging population is expanding rapidly. Older adults face intersecting challenges of poverty, chronic disease burden, and inadequate access to healthcare. With limited formal income support and minimal health insurance coverage, most elderly Nigerians rely on family or continue informal labor to survive. This compounds their vulnerability in later life.

Objectives: This article examines the economic and health-related barriers to healthcare utilization among older Nigerians. It incorporates recent demographic and epidemiological trends, wealth-based inequalities, rural-urban disparities, and evolving policy responses. The analysis integrates insights from the Nigeria Demographic and Health Survey (NDHS) 2018 and applies Andersen's healthcare access model.

Methods: A perspective approach was adopted to synthesize empirical literature, national data (including NDHS), and recent policy developments such as the National Health Insurance Authority Act and the National Senior Citizens Centre (NSCC) Act. Comparisons are drawn with other lower-middle-income countries, notably India, to highlight global relevance.

Findings: Older Nigerians, particularly women and rural dwellers, experience high poverty rates, with up to 85% of women aged 70 and above living in poverty. They face chronic multimorbidity and have some of the lowest health service utilization rates due to cost, distance, and systemic neglect. Although policy frameworks, such as the NSCC and Basic Health Care Provision Fund (BHCPF), exist, implementation remains weak.

Conclusions: Comprehensive reforms are essential to improve elderly health outcomes in Nigeria. Priorities include expanding subsidized health insurance, implementing universal social pensions, strengthening rural health services, and combating ageism. A coordinated and inclusive policy strategy can transform aging from a crisis into an opportunity for national development.

Background and aim: Mathematical modelling plays an important role in public health by enabling the prediction of disease outbreaks, assessment of transmission dynamics and evaluation of intervention strategies. Although widely applied in high-resource settings, its use in underserved contexts remains underexplored. This review aimed to examine and synthesize current evidence on the application of mathematical modelling for predicting and controlling infectious diseases in underserved settings.

Methods: A comprehensive and reproducible search was conducted using Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) and population, intervention, comparison and outcome (PICO) frameworks across databases, including PubMed, Scopus, Medline, ScienceDirect and EBSCOhost. Keywords and Medical Subject Headings (MeSH) terms related to mathematical modelling and infectious disease control were applied. Two reviewers independently screened titles, abstracts and full texts, with a third resolving discrepancies. Thematic analysis and meta-analysis were used for synthesis.

Results: Out of 838 studies screened, 27 (3.2%) met inclusion criteria. Deterministic models were most used, followed by stochastic and agent-based models. Diseases modelled included COVID-19, malaria, tuberculosis (TB), Ebola, Zika, chikungunya, dengue, diphtheria, respiratory infections, visceral leishmaniasis (VL) and Mpox. Modelling predicted the impact of interventions on transmission, with pooled effect size (Ro) of 1.32 (θ = 1.3, p < 0.0001). However, challenges, such as data underreporting, gaps and inconsistencies, were common, potentially affecting model accuracy and real-world applicability.

Conclusion: Mathematical modelling has demonstrated value in supporting infectious disease control in underserved settings. However, the predominance of deterministic models limits adaptability across diverse contexts. Poor data quality further constrains reliability. Future work should focus on expanding modelling approaches, strengthening data infrastructure and addressing a broader range of diseases. These findings can guide public health policy by supporting data-driven decision-making, improving resource allocation and integrating modelling into outbreak preparedness and response strategies in underserved settings.

Public health discussions now apply the label of 'unhealthy commodities' to items attractive to consumers but which bring harm to health and welfare. The list includes tobacco, alcohol, cannabis and other drugs, sugar-sweetened beverages, overprocessed foods and commercial gambling. The histories of markets and controls in such commodities vary, with commerce in alcohol, drugs and gambling prohibited in many places at times during the last two centuries, but few limits on sugar, or on tobacco until recent years. In the current world, regimes vary for retail sale between commodities and in different jurisdictions. Some examples are given of successful control measures which might be more widely applied: measures such as licensing of retail sales; closing off web-based sales; and imposing minimum unit pricing. The new thinking in public health offers the opportunity to look across what have been separate fields of action and experience and to learn from case study examples of effective mechanisms to reduce rates of harmful consequences from unhealthy commodities.