The COVID-19 pandemic and accompanying social distancing measures might have caused adverse health consequences. We aimed to describe changes in participants' self-rated health and mental health (depression, anxiety, and stress), and investigate factors associated with them. We collected data from the German National Cohort (NAKO). We first described changes in participants' self-rated health and mental health from the baseline examination (1 to 6 years earlier) to the early phase of the COVID-19 pandemic. We then applied the multinomial logistic regression model (self-rated health) and the quantile regression model (mental health) to investigate the potential factors associated with the health status and changes. After a median of 3.1 [2.1, 4.1] years from baseline to the early pandemic phase (N = 91,809), 39.3% of participants with good health and 69.7% with less good health status at baseline reported better health. However, the percentage of participants with high depression, anxiety, and stress scores (≥ 10) increased from 6.2%, 4.1%, and 4.3% to 8.6%, 5.6%, and 10.1%, respectively. In the multivariable models, we found that being younger, being male, highly educated, being employed, having higher life satisfaction at baseline, being more physically active, drinking heavily, and experiencing improved anxiety symptoms were associated with improved self-rated health. In contrast, smoking and having mental health disorders were all associated with worse self-rated health. Our results showed that being younger, being female, smoking, drinking heavily, and drinking more since baseline were associated with higher depression scores. Having had a coronavirus test was associated with worse self-rated health and more severe anxiety and stress. During the early COVID-19 pandemic, many participants experienced improvements in self-rated health but suffered deterioration in mental health and physical activity engagement. Female participants, those who were physically inactive, and those with pre-existing mental disorders were more likely to report poorer health.
Digital health tools, particularly patient portals, can support caregiving, but there is limited understanding of how sociodemographic and geographic factors influence digital health engagement among U.S. caregivers, especially dementia caregivers. Dementia caregiving involves complex coordination, medication management, and frequent healthcare interactions. Therefore, access to online medical records is particularly valuable. Moreover, most previous research focuses on general digital health adoption or patient portal use among patients, not caregivers, particularly among dementia caregivers, and rarely considers geographic differences or the interaction effects between age and caregivers' self-rated health. Comparing dementia caregivers to those without is essential because dementia caregiving entails more extensive care, longer duration, behavioral challenges, and emotional strain. These factors may increase reliance on digital health tools like online medical records. However, national studies often do not distinguish between dementia and non-dementia caregiving in digital health analyses. This study explored how sociodemographic and geographic factors are associated with caregivers' frequency of accessing care recipients' online medical records, especially for caregivers of individuals living with dementia compared to those caregivers of individuals without dementia. We also evaluated the interaction effect between age and health condition, motivated by the hypothesis that digital engagement is influenced not only by age but also by functional health status. This study examined caregivers' portal access frequency using data from the 2022 National Health Interview Survey, collected between March 7th and November 8th, 2022. Descriptive statistics captured differences in access frequency and sociodemographic characteristics between dementia caregivers and non-dementia caregivers. Three ordered logistic regression models examined predictors of accessing online medical records for dementia caregivers, non-dementia caregivers, and all caregivers, followed by an all-caregiver model with interaction terms to assess moderation effects between caregiver age and self-reported health. ArcGIS Pro was adopted to visually capture the geographic regional divide in portal access frequency across the U.S. Of the 6,252 total responses, 916 caregivers provided data on portal access frequency. More than half of dementia caregivers (60.25%) and non-dementia caregivers (51.11%) did not access online medical records in the past 12 months. Frequent access (≥ 10 times/year) was low across both groups (dementia caregivers (7.03%) vs. non-dementia caregivers (12.66%)). Survey-weighted ordered logistic regression models identified significant sociodemographic and geographic disparities in portal access frequency. Being female (OR = 1.931, SE: 0.074), having a bachelor's degree (OR = 1.769, SE: 0.168), and being married (OR = 1.749, SE: 0.068) were associated with higher portal access frequency in the all-caregivers model, and similar results were found in dementia caregivers and non-dementia caregivers. Regarding geographic disparities, dementia caregivers residing in micropolitan areas had substantially lower odds of frequent portal access than those in metropolitan areas (OR = 0.633, SE: 0.071); a similar trend was observed among dementia and non-dementia caregivers. Rural residence was also associated with lower portal access among dementia caregivers (OR = 0.529, SE: 0.152) and non-dementia caregivers (OR = 0.654, SE: 0.097). In the all-caregiver sample, caregivers in small-town areas (OR = 0.522, SE: 0.071) had lower odds of portal access compared to metropolitan caregivers. Health status showed differential patterns across caregiving groups. Among dementia caregivers, reporting very good health (vs. excellent) was associated with lower odds of portal access (OR = 0.268, SE: 0.023), whereas among non-dementia caregivers, very good health was associated with higher portal access (OR = 1.246, SE: 0.062). Good or fair health was associated with lower portal access across all caregiver groups. Interaction analysis revealed that as caregiver age increased, those in poor health had a significantly lower portal access frequency. Accessing online medical records among family caregivers remains limited and varies notably by gender, educational attainment, geographic location, and the interaction between age and health status. These findings highlight the importance of developing tailored digital support strategies that address the intersecting socioeconomic and health-related barriers faced by caregivers, particularly as artificial intelligence-enabled tools become more prevalent in dementia care. Older caregivers in poor health are especially unlikely to adopt digital resources, underscoring the urgent need for targeted outreach and educational initiatives. Additionally, the persistent geographic digital divide among dementia caregivers, especially those in small towns, calls for increased support to promote equitable access to caregiving technologies. This study conducted a secondary data analysis, so trial registration is NOT required because it does not run a prospective randomized trial. And Institutional Review Board approval is also not needed because the dataset is de-identified and public.
Somalia has one of the lowest childhood immunization coverage rates globally, with only 34.8% of children aged 0-59 months having received at least one vaccine and a high burden of zero-dose children. Immunization uptake is influenced by socioeconomic, maternal, healthcare access, and geographic factors. This study examined determinants of childhood immunization coverage in Somalia to inform equity-focused strategies. A cross-sectional analysis was conducted using nationally representative data from the 2020 Somalia Demographic and Health Survey (SDHS), including 7,373 mother-child pairs. bivariate and multivariable logistic regression models assessed associations between sociodemographic, economic, maternal, healthcare access, and geographic characteristics and child vaccination status, accounting for survey design and confounders. Overall vaccination coverage was 34.8%. Health facility delivery was the strongest independent predictor (AOR = 1.93; 95% CI:1.68-2.22; p < 0.001). Children from the highest household wealth quintile had higher odds than the poorest (AOR = 2.45; 95% CI:2.00-3.00; p < 0.001). Maternal primary and secondary education were positively associated with vaccination (AOR = 1.58; 95% CI:1.34-1.87 and AOR = 1.94; 95% CI:1.40-2.67; respectively; p < 0.001). Nomadic residence was associated with higher odds compared with rural residence (AOR = 1.69; 95% CI:1.46-1.96; p < 0.001). Compared with infants aged 0-11 months, children aged 12-23 months (AOR = 1.36; 95% CI:1.10-1.69; p = 0.005) and 24-59 months (AOR = 1.33; 95% CI:1.12-1.59; p = 0.001) were more likely to be vaccinated. Lack of radio exposure was associated with lower vaccination odds (AOR = 0.64; 95% CI:0.50-0.82; p < 0.001). Children living in Gedo region had markedly lower odds of vaccination than those in Awdal region (AOR = 0.26; 95% CI:0.17-0.39; p < 0.001). Childhood immunization coverage in Somalia remains critically low, reflecting socioeconomic, maternal, healthcare access, and geographic inequalities that require strategies targeting disadvantaged populations and regions.
Lipid-poor adrenal adenomas (LPAs) and pheochromocytomas (PCCs) are similar tumours, but misdiagnosed LPAs may lead to health risks such as hypertensive crisis due to improper treatment. The aim of this study was to develop an efficient method for classifying LPAs and PCCs on the basis of different CT scans that minimises the number of radiation doses. The patients included in this study were randomly divided into training and validation groups (the ratio was 7:3). The datasets, including 2-(plain and venous enhanced CT scans) or 3-phase CT data, were separately used to construct XGBoost, Gradient Boosted Decision Tree (GBDT), AdaBoost, random forest and decision-tree models. Receiver operator characteristic (ROC) curves were used to evaluate the models, and the DeLong test was used to determine significant differences. The models constructed were XGBoost, GBDT, AdaBoost, random forest and decision tree and their efficacies Area Under the Curves (AUCs) in the 2-phase CT group were 0.91, 0.89, 0.85, 0.78, and 0.71, respectively, while those in the 3-phase CT group were 0.92, 0.91, 0.89, 0.81, and 0.78, respectively. The optimal model in both the 2-and 3-phase groups was XGBoost; this model exhibited similar performance in both groups. The DeLong test also confirmed some difference in XGBoost between the two groups. Our XGBoost-based model constructed using 2-phase CT data is similar to that constructed using 3-phase CT data; both of them exhibited good performance in the classification of LPAs and PCCs.
Parkinson's disease (PD) remains underdiagnosed in Thailand, and its rising prevalence presents a growing challenge for the healthcare system. The previously validated CheckPD digital population screening platform has been implemented nationally in collaboration with the Thai Red Cross Society (TRCS) and the National Health Security Office (NHSO), enabling integration of digital PD risk screening into preventive health frameworks. To evaluate the early phase of a national rollout of the CheckPD platform, focusing on population reach, adoption, predictive performance, exploratory usability, and implementation factors influencing scalability across diverse real-world settings. This RE-AIM-guided implementation study in 10 Thai provinces assessed reach, adoption, completion, system performance and positive predictive value among neurologist-evaluated screen-positive participants. Preliminary usability was assessed in 30 post-screening completers using the SUS and UEQ-S. Supplementary implementation feedback was collected from Village Health Volunteers and public health officers. Between January 2024 and October 2025, 13,381 out of 18,520 users completed screening across 10 provinces (completion rate: 72.3%). The mean SUS score was 83, with a 92% first-time task completion rate. Programme reach was achieved through multiple channels, including Village Health Volunteers (6,742 participants), community field campaigns (5,207), facilitated online training initiatives (3,448), and self-initiated app downloads (3,123). When compared with neurologists' diagnoses among 730 screen-positive participants who underwent evaluation, the screening demonstrated a positive predictive value of 81.23% (593/730; 95% CI 78.39%-84.07%). Key facilitators of implementation included TRCS endorsement and network support, community volunteer engagement, and user-centred app design. Exploratory multivariable logistic regression analysis identified educational attainment and geographic context as significant predictors of screening completion, with higher educational attainment and residence outside Bangkok associated with a higher likelihood of completing the screening workflow. The CheckPD programme demonstrates that national-scale digital screening for neurological disorders is feasible in a low-to-middle-income country when embedded within trusted institutions, supported by community networks, and aligned with data protection standards. Thailand's experience provides an early, promising, and potentially scalable model for implementing population-level improvements in brain health by enabling earlier detection and assessment of individuals at risk, in alignment with the World Health Organization's Brain Health framework.
Understanding the supply-demand relationship of medical services is essential for regional planning. Existing city-scale studies typically exclude cross-city flows, whereas national-scale studies often overlook intra-city heterogeneity. In urban agglomerations, healthcare resources and transport infrastructure are usually planned by cities, although patients may cross city boundaries to seek care. The implications of cross-city trips for regional medical services remain insufficiently understood. Taking the Pearl River Delta as a case, this study investigates cross-city hospital visiting trips and their implications for medical service evaluation. Using 91.2 million automobile navigation records collected in 2019, 1.37 million hospital visiting trips to Grade 3 hospitals were identified through a modified spatial join method. A population-hospital bipartite network and a multi-scale analytical framework were constructed. Cross-city demand and supply indices were developed at the city, subdistrict, and hospital scales to characterize cross-city medical service patterns and influencing factors. Accessibility and Gini coefficients were computed under intra-city and regional evaluation scenarios to assess how incorporating cross-city hospital visiting trips affects medical service evaluation. Based on automobile navigation data, 9.1% of identified hospital visiting trips crossed city boundaries. Guangzhou and Shenzhen served as dominant regional suppliers, with cross-city supply indices of 55.9% and 21.8%, respectively. Cross-city demand was negatively associated with distance to boundary, GDP per capita, and hospital beds. Cross-city service share was negatively associated with distance to boundary, whereas contributions to regional cross-city service provision were positively associated with hospital size and hospital grade. Incorporating cross-city flows increased accessibility in most peripheral areas and reduced the regional population-weighted Gini coefficient from 0.596 to 0.522. Based on automobile navigation data, cross-city hospital visiting trips constitute an important component of medical service utilization in urban agglomerations. At the subdistrict scale, cross-city demand was jointly associated with boundary proximity and local economic and medical conditions. At the hospital scale, the cross-city service share was higher among hospitals closer to city boundaries, whereas contributions to regional cross-city medical service provision were greater among larger and higher-grade hospitals. Evaluation frameworks relying solely on intra-city data tend to underestimate accessibility in boundary areas and, in most cases, overestimate the Gini coefficient.
Breastfeeding has been shown to provide numerous benefits for mothers and babies in the short and long term. During the COVID-19 pandemic, breastfeeding support, which was traditionally provided offline, shifted to online platforms. Although these remote services were available before the pandemic began, online interventions emerged as an alternative and proved effective in helping mothers breastfeed during that period. We aimed to explore the existing literature on the experiences of mothers and health care professionals with remote one-to-one synchronous breastfeeding support and to identify the unmet support needs of mothers regarding this type of support. We systematically searched seven literature databases: MEDLINE, CINAHL Plus, MIDIRS, Web of Science, ASSIA, WHO Global Index, and Google Search. Articles published before 2010 and in languages other than English and Bahasa were excluded. A thematic approach was used to synthesise the data. Twenty-one studies were included in this review. Three themes generated from the synthesis: (1) mothers' acceptance of one-to-one synchronous telelactation, (2) benefit of one-to-one synchronous telelactation, and (3) challenges faced in one-to-one synchronous telelactation. In conclusion, mothers generally accepted one-to-one synchronous breastfeeding support as an alternative to in-person sessions, although some challenges remain. Further improvements are needed to address accessibility and scheduling issues.
Osteoporosis and asthma are prevalent chronic conditions that significantly impact public health. Inflammatory cell merging, leading to reduced bone density, increases the risk of fractures, while asthma is a chronic respiratory disease characterized by airway inflammation and bronchoconstriction. More and more emerging research suggests a potential connection through shared pathways and biological mechanisms. In this study, we aim to investigate the causal effect of anti-osteoporosis drug treatment on chronic disease asthma through the Mendelian randomization (MR) analysis method. In our study, we employed a two-stage study design, utilizing observational data from the National Health and Nutrition Examination Survey (NHANES) and summary statistics data from genome-wide association studies (GWAS) with a large sample of European adults. Section-cross research was performed using NHANES datasets and analysis of the risk of asthma with bone mineral density (BMD) through a risk proportion regression model. After that, a two-sample MR analysis was performed to investigate the causal effect of anti-osteoporosis drug therapy on asthma. Finally, sensitivity analysis was conducted to evaluate the stability of the results. Our study revealed a non-linear association between femur BMD and asthma risk, with a critical inflection point at a BMD value of 1.114 g/cm2. MR analysis indicated that denosumab did not exert a causal effect on asthma risk (OR = 1.008, 95% CI: 0.994-1.022, P = 0.285) but was associated with improved lung function (β = 0.085, 95% CI: 0.006-0.164, P = 0.035). Conversely, calcitriol exhibited a protective effect against both asthma (OR = 0.931, 95% CI: 0.894-0.969, P < 0.001) and lung function decline (β = 0.294, 95% CI: 0.062-0.525, P = 0.013). These findings suggest a pleiotropic role for these anti-osteoporosis drugs in respiratory health. This study provides novel insights into the complex relationships between osteoporosis treatments, bone health, and asthma risk. The use of MR analysis enhances the reliability of our findings and highlights the potential benefits of osteoporosis treatments in reducing asthma risk and improving lung function. These results call for further research and may have implications for developing integrated treatment approaches for individuals managing osteoporosis and asthma.
To propose a new method using a physics-guided neural network for quantitative parameter mapping in balanced steady-state free precession (bSSFP) imaging. We trained physics-guided neural networks with a multilayer perceptron using simulated bSSFP signals generated from tissue parameters ( T 1 $$ {T}_1 $$ , T 2 $$ {T}_2 $$ , M eff c $$ {M}_{{\mathrm{eff}}_{\mathrm{c}}} $$ , ∆f and φ RF $$ {\varphi}_{RF} $$ ) uniformly sampled from predefined ranges corresponding to gray matter, white matter, and cerebrospinal fluid. Over 80 million samples were simulated using six phase-cycling angles with L2 loss combining parameter and reconstructed signal terms. The model output was obtained both without and with test-data-specific adaptation. PLANET and CELF were used as comparison methods. Evaluation was conducted using 10 brain digital phantoms from the BrainWeb database and in vivo bSSFP datasets acquired from 10 human subjects on a 3 T scanner using the same scan parameters. The proposed approaches improved mapping accuracy and consistency visually and quantitatively in both digital phantom and in vivo data compared with PLANET and CELF. Performance with test-data adaptation was better than that without adaptation. The estimated parameters enabled more accurate reconstruction of images at unseen phase-cycling angles and flip angles, suggesting the models' generalization capability. Trained entirely on simulated data, the proposed physics-guided neural networks enable accurate and efficient multiparameter mapping with high spatial resolution (1.3 × 1.3 × 2.6  mm 3 $$ {\mathrm{mm}}^3 $$ ) from phase-cycled bSSFP within a clinically reasonable scan time of 7 min, offering a promising alternative for MR parameter mapping and data augmentation in training and validating quantitative MRI.
The early phase of psychosis is critical for interventions to modify long-term outcomes. It is unclear what proportion of individuals' exhibit early persistent psychosis and the long-term implications. An epidemiologic sample of individuals with acute psychosis was recruited at first admission and followed for 25 years. Early persistent psychosis was defined as presence of active psychosis for ≥90% of the days of the 4 years after first hospitalization for psychosis. Multivariable regression analyses were conducted, testing the association between baseline predictors and persistent psychosis, and between persistent psychosis and 25-year outcomes. Out of 526 individuals (age = 27.4 ± 9.4 years, males = 56.8%, baseline schizophrenia/schizoaffective disorder = 30.0%), 101 (19.2%) had early persistent psychosis. At baseline, low premorbid cognitive performance (odds ratio (OR) = 2.08, 95% CI, 1.05-4.12), lower Global Assessment of Functioning (OR = 1.59, 95% CI, 1.16-2.13), low role function (OR = 1.49, 95% CI, 1.03-2.16) and worse social function (OR = 1.52, 95% CI, 1.03-2.22) were predictive of persistent psychosis. At 25-year follow-up (n = 307, 58.9%), early persistent psychosis was associated with worse avolition ($\beta$=0.25, 95% CI, 0.14-0.35), more severe reality distortion ($\beta$=0.19, 95% CI, 0.07-0.31), disorganization ($\beta$=0.21, 95% CI, 0.09-0.32), worse social ($\beta$=-0.18, 95% CI, -0.06 to -0.30), role ($\beta$=-0.22, 95% CI, -0.09 to -0.34), and global function ($\beta$=-0.28, 95% CI, -0.17 to -0.38), greater odds of being on public assistance (OR = 2.13, 95% CI, 1.15-3.95), lower odds of living independently (OR = 0.43, 95% CI, 0.23-0.80) or recovery (OR = 0.09, 95% CI, 0.02-0.38). One in 5 individuals with first-episode psychosis had early persistent psychosis without clearly modifiable premorbid factors, and with strong associations with adverse long-term outcomes. Individuals experiencing early persistent psychosis require focused long-term interventions.
Timely palliative care can reduce the disease burden and improve quality of life in patients with cancer. Although several studies have developed assessment models for palliative care needs in cancer patients, the quality and clinical applicability of these models remain unclear. To systematically review existing assessment models for palliative care needs in patients with cancer, with a focus on their characteristics, predictors, risk of bias, and applicability. A systematic search was conducted in PubMed, Cochrane Library, Embase, Web of Science, CINAHL, Scopus, China National Knowledge Infrastructure (CNKI) through September 12, 2025. Data extraction and evaluation were rigorously performed by two researchers based on the Prediction Model Risk of Bias Assessment Tool (PROBAST). A total of 5714 articles were identified, and eight studies were included, which covered 24 models for assessing palliative care needs. The sample size of the included studies ranged from 179 to 54,628, with areas under the curve ranging from 0.724 to 0.998. The models in all the included studies encompassed four categories of predictive factors: general demographic data, symptom/functional assessments, laboratory indicators, and treatment status. Five studies were rated as having a high risk of bias, primarily due to high risks associated with participants and conclusions, with generally low applicability. Existing models demonstrate potential for identifying patients with cancer who have increased palliative care needs using routinely collected clinical data. Commonly included predictors were symptom burden, functional status, laboratory parameters, treatment-related factors, and demographic characteristics. However, the overall body of evidence is constrained by a substantial risk of bias, particularly arising from inappropriate data sources, limited sample sizes, suboptimal handling of continuous variables, insufficient reporting of missing data, and the lack of robust internal or external validation. In addition, many models adopted mortality-based surrogate outcomes rather than clinically meaningful indicators of palliative care needs. Therefore, the currently available models should be interpreted with caution, and further high-quality model development and external validation are required before they can support broader routine clinical implementation. Future research should prioritize clinically actionable outcomes and incorporate patient-, caregiver-, and family-level factors to improve the relevance of these models for referral decisions and care planning.
Ethiopian people possess deep knowledge of how to use plant resources and are dependent on plant values mainly for traditional medicine. However, most ethnobotanical studies are restricted to rural areas, leaving urban centers poorly documented, which implies the need for further study. Thus, this study was conducted in Gondar City Administration, aimed at investigating medicinal plants to fill the traditional knowledge documentation gap. The study was conducted from February 2024 to January 2025 in 12 kebeles selected purposively based on vegetation cover, availability of knowledgeable practitioners and representation of both urban and rural settings. Data were collected using interviews, focus group discussions, guided field walks, and market surveys with 120 randomly selected general informants and 60 purposively selected key informants. Descriptive statistics were used to analyze the basic ethnobotanical data. An independent sample t-test and two-way ANOVA were used to analyze socio-demographic effects of informants on their indigenous knowledge. Different ethnobotanical ranking and clustering methods, Rahman's similarity index (RSI) and Jaccard's coefficient of similarity were also used. A total of 109 medicinal plants distributed across 95 genera and 54 families were recorded to treat 76 ailment types. Asteraceae was the foremost family with 9 (8.26%) species. Shrub was the dominant habit (39.45%) and leaves were the most valuable plant parts used for 33.80% of remedy preparations. Remedies were prepared mainly from fresh forms (76.39%) by crushing (20.37%) and administered through the dermal route (41.20%). Significant knowledge variation on medicinal plants was observed between key and general informants (P = 0.000), rural and urban kebeles (P = 0.001), and between age groups (P = 0.013). Informant type (general vs. key informant) and age had a highly significant interaction effect on the medicinal plant knowledge (P = 0.000). About 14.68% of all recorded species were reported to treat hepatitis. From those, Clutia lanceolata was the most preferred. The highest informant consensus factor value (98%) was associated with respiratory conditions. The RSI ranged from 0.5 to 13.79%, and the JSI ranged from 3.5 to 36%. After a systematic search was performed across various reputable databases (Scopus, PubMed, EMBASE, Web of Science, and Google Scholar), unique ethnobotanical information on the therapeutic roles of 12 medicinal plant species that have not been reported previously was documented. This finding indicates that the rich diversity of medicinal plants in Gondar City, along with unique ethnomedicinal findings, is an indicator of alternative use of traditional medicine by urban inhabitants for their healthcare system. However, urban ethnobotany is a distinct field in which is expected to evolve knowledge systems influenced by migration. So, these knowledge systems could experience an accelerated loss due to urbanization-related factors unless prior documentation is made.
The number of older people in Germany has risen steadily in recent decades. One in four people is now aged 65 or over. As people age, their health problems tend to increase, as do their fundamental care needs. Nurses play a key role in addressing these needs through a holistic approach. To fulfil this responsibility effectively, it is necessary to examine existing nursing research on the fundamentals of care for older people and to identify gaps in the current evidence base. Therefore, we plan to conduct a mapping review with the aim of mapping the extent, range and nature of nursing research activities on the fundamentals of care, as defined in the physical, psychosocial and relational components of the Integration of Care dimension of the Fundamentals of Care Framework for older people in Germany. We will search the electronic databases PubMed/MEDLINE, CINAHL, CareLit and GeroLit, the catalogue of the German Federal Ministry of Research, Technology and Space and the German National Library for publications on nursing research based on the Integration of Care dimension of the Fundamentals of Care Framework among older people (≥ 65 years). There will be no time limit. We will include studies published in English and German. Initial screening of the first ten per cent of titles and abstracts and other stages will be carried out by two independent researchers. This process will be repeated until full agreement between the researchers. Any discrepancies will be resolved with consultation of a third reviewer. Results will be reported in a narrative synthesis and complemented by tabular and numerical presentations. To the best of our knowledge, this mapping review will be the first to provide an overview of current nursing research on the fundamentals of care for older people in Germany. The inclusion of German-language texts and the absence of time limits in this review are intended to complement previous reviews. The planned mapping review will also identify the evidence gap in research in this area and contribute to the determination of future scientific research in Germany. Consequently, the findings of the mapping review could be of great interest to nurses and other health professionals for evidence-based practice, research and educational programmes. In addition, the data can be used to develop a programme for the provision of age-friendly and caring living conditions for older people in the future. The protocol was registered with Open Science Framework (osf.io/9e3uv).
Breast cancer is the most prevalent and costly cancer. Oral endocrine therapy (OET) improves survival rates and quality of life while reducing recurrence, mortality, morbidity, and medical costs. However, adherence to OET is challenging because OET is prescribed for 5-10 years. Determinants of OET nonadherence (NA) among women aged 65 and older remain poorly characterized. Existing studies are limited, often focusing on small, single-site samples and focusing on patient-level rather than multi-level determinants. Despite the unique needs of older women, research on OET-NA remains scarce. This study identified multi-level determinants of OET-NA in older women using ecological systems theory and the World Health Organization's five-dimension model. A descriptive, correlational secondary data analysis was conducted using the 2019 Surveillance-Epidemiology-End-Results (SEER) Medicare database, which includes more than 9 million cancer cases in the United States. OET-NA was significantly affected by (a) patient-related factors of ethnicity (i.e., Black [AOR 1.55; 95% CI 1.34-1.78; p < 0.001]) and psychological issues (i.e., depression [OR 1.40; 95% CI 1.27-1.54; p < 0.001]), (b) socioeconomic-related factors of marital status (i.e., divorced [OR 1.17; 95% CI 1.04-1.32; p ≤ 0.01]), and lifestyle (i.e., tobacco use [OR 1.41; 95% CI 1.22-1.63; p < 0.001]), (c) therapy-related factors of switching OET medications (OR 2.72; 95% CI 2.41-3.07; p < 0.001), (d) condition-related factors of comorbidities (i.e., obesity [OR 1.13; 95% CI 1.03-1.23; p < 0.01]), and (e) characteristics of the healthcare team and health system-related factors (i.e., group practice type [OR 1.26; 95% CI 1.01-1.56; p < 0.05]). OET-NA was associated with multi-level determinants, including being Black, having depression, being divorced, using tobacco, switching OET medications, having obesity, and receiving care in group practices. Identifying these determinants is a critical first step toward developing and testing interventions to improve OET-NA and enhance survival and quality of life.
Observational studies have suggested that body mass index (BMI) is associated with accelerated epigenetic aging; however, the age at which this association begins and the duration of its effects have not been fully established. This study evaluated the effects of BMI and physical activity on epigenetic aging from early life to adulthood. We integrated multi-source data from populations of different racial backgrounds, including genome-wide association study (GWAS) data, the National Health and Nutrition Examination Survey (NHANES), clinical visceral adipose tissue, and blood samples from obese and physically active populations. Specifically, Mendelian randomization (MR) analysis was used to infer the causal relationship between early-life BMI and epigenetic age acceleration and to identify potential mediators. NHANES data were then analyzed to validate this association at the population level. Finally, biomarkers in blood and adipose tissue were examined to assess whether physical activity is associated with reduced aging-related signatures. The Mendelian randomization analyses indicated that high early-life BMI was causally associated with accelerated epigenetic aging across multiple epigenetic clocks, with β ranging from 0.231 to 0.506; similar associations were also observed for childhood obesity, with β ranging from 0.139 to 0.231. Physical activity was identified as an important mediator that attenuated epigenetic aging acceleration, with mediation effects accounting for 10.70% to 16.22%. Analysis of the NHANES dataset further confirmed that epigenetic age acceleration increases progressively with increasing BMI: [25 ≤ BMI < 30: β = 0.83, 95% CI (0.66, 1.00); 30 ≤ BMI < 35: β = 1.73, 95% CI (1.54, 1.93); 35 ≤ BMI < 40: β = 2.93, 95% CI (2.67, 3.20); BMI ≥ 40: β = 4.64, 95% CI (4.30, 4.99)]. Subgroup analysis showed that, at the same BMI level, female exhibited more severe PhenoAA acceleration than male. Validation using multi-tissue samples showed that obesity accelerates DNA damage and significantly upregulates genes involved in cell cycle regulation. Physical activity significantly inhibited the upregulation of aging-related genes and reduced oxidative stress. BMI is strongly associated with accelerated epigenetic aging. This association is evident in children with obesity, becomes stronger with higher BMI, and is also observed in adults, whereas physical activity may partially attenuate this process. Trial registration Name of the registry: China-Japan Friendship Hospital National Integrated Chinese and Western Medicine Medical Center. Unique identifying number or registration ID: NCT06452303. Hyperlink to your specific registration (must be publicly accessible and will be checked): https://www.centerwatch.com/clinical-trials/listings/NCT06452303/the-patient-cohort-for-bariatric-surgery.
This study aimed to standardize the global prevalence of metabolic syndrome (MetS) in patients with epilepsy. Several databases including PubMed, Scopus, Web of Science, Embase, Science Direct, and Google Scholar were thoroughly searched. Studies up to 2025 on MetS prevalence in people with epilepsy were included. The search covered cross-sectional, cohort, and case-control studies in English that reported MetS prevalence in this group. Statistical analysis was performed using Comprehensive Meta-Analysis software (Version 2). The I² statistic was used to assess heterogeneity across studies, and the random-effects model was applied for data analysis. Analysis of 24 findings from 18 studies estimated that the overall prevalence of (MetS) in people with epilepsy was 29.6% (95% CI: 25.7%-33.9%). Further analysis showed that the highest prevalence of MetS in epilepsy patients was in studies conducted in South America, with a prevalence of 42.4% (95% CI: 37.8%-47.0%). The only study that used the Harmonized Criteria diagnostic tool reported the prevalence equal to 49.4% (95% CI: 39.2%-59.7%). Furthermore, a meta-regression analysis found no significant association between the year of publication or the number of participants and the prevalence of MetS in epilepsy patients (P > 0.01). The results highlighted a high prevalence of MetS among patients with epilepsy. Therefore, healthcare professionals should not only focus on epilepsy but also regularly monitor risk factors associated with MetS and identify them early in patients with epilepsy.
Tuberculosis (TB) is one of the deadliest bacterial infectious diseases worldwide, with rising cases of multidrug-resistant (MDR) and extensively drug-resistant (XDR) strains. Bedaquiline (BDQ)-containing regimens have become important for the treatment of MDR/XDR-TB, and resistance to BDQ is increasing. Understanding genetic mutations is crucial for early detection of BDQ-resistant strains and thus maintaining the effectiveness of these drugs. This study aimed to review mutations associated with BDQ-resistant TB globally. This study systematically searched the keywords TB, XDR, MDR, BDQ, and genes in the PubMed, Scopus, Web of Science, and Embase databases for studies reporting BDQ-resistant TB and their associated genes globally from 2014 to 2025. This systematic review included 40 studies and 25,234 patient samples with MDR and XDR-TB from around the world. Results showed significant variation in BDQ resistance across the World Health Organization (WHO) regions, with the highest in the Eastern Mediterranean and the lowest in the Western Pacific. Furthermore, the data collected showed that, among the continents studied, resistance was highest in Africa and lowest in the Americas. The country distribution showed that resistance rates were higher in Iran (n = 24), Moldova (n = 26), and Armenia (n = 35), and lower in Italy (n = 1001) and the Philippines (n = 724) than in other countries in the analysis. Genetically, the most resistance-associated mutations were observed in the Rv0678, atpE, and pepQ genes, respectively. Given the increasing BDQ resistance and regional variability, it is essential to develop early detection systems, genomic surveillance, robust drug policy enforcement, and rapid diagnostics to maintain treatment effectiveness and curb the spread of resistance. Future research should focus on elucidating resistance mechanisms and developing novel therapeutic strategies.
Self-harm in young people is a pressing public health issue, with family support playing a crucial role in the young person's prognosis. Concurrently, the impact extends to families themselves, who must navigate caregiving responsibilities while also requiring support. Understanding these experiences is key to providing more effective assistance in their caregiving roles. With this mixed-methods systematic review we investigated the experiences, barriers, and needs of families of young people who self-harm. Following PRISMA guidelines, a search was conducted within PsycINFO, PubMed, Web of Science, and Scopus databases in July 2024 and April 2025. Thirty-one studies were included in this review, and quality was assessed with the Mixed Methods Appraisal Tool (MMAT). A narrative synthesis was employed for the quantitative data, while qualitative data were analysed with thematic synthesis. The quantitative findings revealed two themes: (1) the repercussions of self-harm in the family and (2) family support needs. Qualitative analysis identified four themes: (1) parents' emotional and psychological impact; (2) impact on parenting and the bond with the young person; (3) disruption of family dynamics; and (4) barriers to and pathways for family support. We discuss the implications of these findings, offering recommendations for future research and improvements in family support services to alleviate caregiver burden and foster supportive environments for recovery. Siblings’ experiences can vary with age, and many of their needs remain unaddressedAccessible care, family involvement, trained staff, and follow-up are neededFindings call for a systemic, family-centered approach to self-harm recovery.
Cutaneous leishmaniasis (CL) is a neglected tropical skin disease. In Ethiopia, CL is a public health concern; about 29 million people are at risk, with an estimated incidence of up to 50,000 new cases annually. In endemic communities, access to diagnosis, treatment, and prevention is crucial but often limited. Understanding the prevalence and access to care, as well as exploring its relationship to agroecological factors, is crucial to inform control strategies. The aim of this work is to estimate the pooled prevalence, access to care service facilities, and spatial distribution and relationship to agroecological factors. A systematic review and meta-analysis were conducted following the Preferred Reporting Items for Systematic Review and Meta-Analysis (PRISMA) framework. The metafor and metadata packages from R Studio were used to obtain pooled prevalence and odds ratio using a random-effects model with a double arcsine transformation. The CL endemicity at the woreda level was overlaid with the locations of CL treatment centers and agroecological zones using ArcGIS. The pooled prevalence of CL was 6.75% (95% confidence interval (CI) 3.37-11.17). Sociodemographic factors (male gender, rural living) and environmental factors (muddy walls, outdoor sleeping, proximity to rocky habitats, and hyrax populations) were significantly associated with CL. CL cases were reported from 85 woredas with a broad spatial distribution; a higher proportion of them were from the Weyna Dega, Dega, and Upper Kola agroecological zones. Access to care is generally poor, with service centers for CL often centralized at the zone level. The estimated pooled prevalence likely underrepresents the true burden of CL. The identified risk factors are more related to rural livelihoods and living conditions, and most of the endemic woredas are in the most productive agrarian agroecological zones, which underlines the health and socioeconomic significance of CL in Ethiopia. Thus, decentralizing healthcare services and improving surveillance for CL are crucial steps in breaking the vicious cycle of poverty.
Information on the burden of disease caused by foodborne pathogens in Northwest China is limited. This study aims to estimate the burden of acute gastroenteritis (AGE) and foodborne salmonellosis, shigellosis and norovirus gastroenteritis in Gansu Province. Using data from population surveys conducted during 2011-2015, the burden of AGE was estimated in Gansu Province. By determining the number of pathogen-specific cases from sentinel hospital surveillance conducted during 2014-2019, with adjustments applied for healthcare-seeking behavior and stool specimen submission based on data from population surveys, the burden of foodborne gastroenteritis caused by non-typhoidal Salmonella enterica, Shigella and norovirus in Gansu Province was calculated. A multiplier calculation model was developed, using Monte Carlo simulation to perform uncertainty estimation. The adjusted monthly prevalence of AGE was 4.0%, equivalent to an average of 0.53 episodes of AGE per person-year in the region. The multiplier for salmonellosis was estimated at 1,739, for shigellosis at 1,646, and for norovirus gastroenteritis at 2,787. The estimated annual incidence of foodborne salmonellosis, shigellosis and norovirus gastroenteritis were 242, 36, and 567 cases per 100,000 population, respectively, which substantially exceeded the incidence of reported foodborne disease. We concluded that AGE and foodborne gastroenteritis caused by non-typhoidal S. enterica, Shigella and norovirus constitute a significant health burden in Gansu Province. By continuously implementing population survey and enhanced sentinel hospital surveillance, with constructing a multiplier calculation model to estimate the burden of disease, we may gain a better understanding of the food safety situation in Northwest China.