Search Results (1,456)

Background: Health equity can only be achieved when every individual has access to quality healthcare without fear of being discriminated against. This study analyzed the sociodemographic characteristics associated with self-reported racial discrimination when receiving medical care in the United States. Methods: This quantitative cross-sectional study utilized the 2022 National Trends Survey 6. We performed a logistic regression analysis using 6102 survey responses from study participants who answered the question about perceived discrimination. Results: Older adults aged 75 years and above had significantly lower odds of reporting perceived discrimination when receiving medical care compared to those aged 18–34 years (AOR = 0.24; 95% CI: 0.10–0.58). The odds of reporting perceived discrimination were significantly higher among non-Hispanic Blacks (AOR = 7.30; 95% CI: 4.48–11.88), Hispanics (AOR = 3.56; 95% CI: 2.45–5.17), non-Hispanic Asians (AOR = 5.95; 95% CI: 2.25–15.73), and individuals identifying as non-Hispanic Other (AOR = 10.91; 95% CI: 5.42–21.98), compared to non-Hispanic Whites. Compared to individuals from households earning less than USD 20,000, the odds of reporting perceived discrimination when receiving medical care were significantly lower among individuals from households earning between USD 50,000 and <USD 75,000 (AOR = 0.42; 95% CI: 0.23–0.78) and those earning USD 75,000 or more (AOR = 0.43; 95% CI: 0.22–0.83). Conclusions: Despite having a multicultural and ethnically diverse population, racial discrimination persists in the United States and has become a barrier to achieving health equity. Health organizations should implement policies that ensure health workers attend mandatory anti-racism training. Full article

Background: Artificial intelligence (AI) and robotics are increasingly pivotal for reducing carbon emissions in supply chain management (SCM); however, research exploring their combined potential from a sustainability perspective remains fragmented. This study aims to systematically map the research landscape and synthesize evidence on the applications, benefits, and challenges. Methods: A systematic scoping review was conducted on 23 peer-reviewed studies from the Scopus database, published between 2013 and 2024. Data were systematically extracted and analyzed for publication trends, application domains (e.g., transportation, warehousing), specific AI and robotic technologies, emissions reduction strategies, and implementation challenges. Results: The analysis reveals that AI-driven logistics optimization is the most frequently reported strategy for reducing transportation emissions. At the same time, robotic automation is commonly associated with improved energy efficiency in warehousing. Despite these benefits, the reviewed literature consistently identifies significant barriers, including the high energy demands of AI computation and complexities in data integration. Conclusions: This review confirms the transformative potential of AI and robotics for developing low-carbon supply chains. An evidence-based framework is proposed to guide practical implementation and identify critical gaps, such as the need for standardized validation benchmarks, to direct future research and accelerate the transition to sustainable SCM. Full article

Background/Objectives: Conventional ketogenic diets, although effective for weight loss, often contain high total and saturated fat intake, which leads to increased low-density lipoprotein cholesterol (LDL-C). Thus, the Healthy Ketogenic Diet (HKD) was developed to address these concerns. It emphasizes calorie restriction, limiting net carbohydrate intake to 50 g per day, prioritizing unsaturated fats, and reducing saturated fat intake. However, adherence to the HKD remains a challenge in urban, time-constrained environments. Therefore, this pilot randomized controlled trial aimed to investigate the effects of Healthy Ketogenic Diet Ready-To-Eat (HKD-RTE) meals (provided for the first month only) versus HKD alone on weight loss and metabolic parameters among overweight adults. Methods: Multi-ethnic Asian adults (n = 50) with a body mass index (BMI) ≥ 27.5 kg/m² were randomized into the HKD-RTE group (n = 24) and the HKD group (n = 26). Both groups followed the HKD for six months, with the HKD-RTE group receiving HKD-RTE meals during the first month. Five in-person workshops and mobile health coaching through the Nutritionist Buddy Keto app helped to facilitate dietary adherence. The primary outcome was the change in body weight at 6 months. Linear regression was performed on the change from baseline for each continuous outcome, adjusting for demographics and relevant covariates. Logistic regression was performed on binary weight loss ≥ 5%, adjusting for demographics and relevant covariates. Results: In the HKD group, participants’ adherence to the 50 g net carbohydrate target was 15 days, while that in the HKD-RTE group was 19 days over a period of 30 days. Participants’ adherence to calorie targets was 21 days in the HKD group and 23 days in the HKD-RTE. The average compliance with the HKD-RTE meals provided in the HKD-RTE group was 55%. The HKD-RTE group experienced a greater percentage weight loss at 1 month (−4.8 ± 3.0% vs. −1.8 ± 6.2%), although this was not statistically significant. This trend continued up to 6 months, with the HKD-RTE group showing a greater percentage weight reduction (−8.6 ± 6.8% vs. −3.9 ± 8.6%; p = 0.092). At 6 months, the HKD-RTE group had a greater reduction in total cholesterol (−0.54 ± 0.76 mmol/L vs. −0.05 ± 0.56 mmol/L; p = 0.283) and LDL-C (−0.43 ± 0.67 mmol/L vs. −0.03 ± 0.52 mmol/L; p = 0.374) compared to the HKD group. Additionally, the HKD-RTE group exhibited greater reductions in systolic blood pressure (−8.3 ± 9.7 mmHg vs. −5.3 ± 11.0 mmHg), diastolic blood pressure (−7.7 ± 8.8 mmHg vs. −2.0 ± 7.0 mmHg), and HbA1c (−0.3 ± 0.5% vs. −0.1 ± 0.4%) than the HKD group (not statistically significant for any). Conclusions: Both HKD-RTE and HKD led to weight loss and improved metabolic profiles. The HKD-RTE group tended to show more favorable outcomes. Short-term HKD-RTE meal provision may enhance initial weight loss, with sustained long-term effects. Full article

Civil aviation safety remains a critical concern globally, with continuous efforts aimed at reducing accidents and fatalities. This paper focuses on the comprehensive evaluation of civil aviation safety in the Slovak Republic over the past several years, with the main objective of identifying prevailing trends and key risk factors. A comprehensive analysis of 155 accidents and incidents was conducted based on selected operational parameters. Logistic regression was applied to identify potential causal factors influencing various levels of injury severity in aviation accidents. Moreover, the prediction model can also be used to predict the probability of specific injury severity for accidents with given parameter values. The results indicate a clear declining trend in the annual number of aviation safety events; however, the fatality rate has stagnated or slightly increased in recent years. Human error, particularly mistakes and intentional violations of procedures, was identified as the dominant causal factor across all sectors of civil aviation, including flight operations, airport management, maintenance, and air navigation services. Despite technological advancements and regulatory improvements, human-related failures persist as a major safety challenge. The findings highlight the critical need for targeted strategies to mitigate human error and enhance overall aviation safety in the Slovak Republic. Full article

Background/Objectives: Understanding the impact of dietary habits in terms of obesity, health outcomes, and functional decline is critical in Europe’s growing elderly population. This study analyzed trends in Mediterranean diet (MD) adherence, obesity prevalence, and grip strength among middle-aged and elderly Europeans using data from the Survey of Health, Ageing and Retirement in Europe (SHARE). Methods: Data from four SHARE waves (2015–2022) across 28 countries were analyzed. Dietary patterns were assessed through food frequency questionnaires classifying participants as MD-adherent or non-adherent where adherent implies daily consumption of fruits and vegetables and occasional (3–6 times/week) intake of eggs, beans, legumes, meat, fish, or poultry (an unvalidated definition of the MD pattern). Handgrip strength, a biomarker of functional capacity, was categorized into low, medium, and high groups. Body mass index (BMI), self-perceived health (SPHUS), chronic disease prevalence, and CASP-12 scores (control, autonomy, self-realization, and pleasure evaluated on the 12-item version) were also evaluated. Statistical analyses included descriptive methods, logistic regressions, and multiple imputations to address missing data. Results: A significant majority (74–77%) consumed fruits and vegetables daily, which is consistent with MD principles; however, the high daily intake of dairy products (>50%) indicates limited adherence to the MD, which advocates for moderate consumption of dairy products. Logistic regression indicated that individuals with two or more chronic diseases were more likely to follow the MD (odds ratio [OR] = 1.21, confidence interval [CI] = 1.11–1.32), as were those individuals who rated their SPHUS as very good/excellent ([OR] = 1.42, [CI] = 1.20–1.69). Medium and high maximal handgrip were also strongly and consistently associated with higher odds of MD adherence (Medium: [OR] = 1.44, [CI] = 1.18–1.74; High: [OR] = 1.27, [CI] = 1.10–1.48). Conclusions: The findings suggest that middle-aged and older adults are more likely to adhere to the MD dietary pattern if they have more than two chronic diseases, are physically active, and have a medium or high handgrip. Although an unvalidated definition of the MD dietary pattern was used, the results highlight the importance of implementing targeted dietary strategies for middle-aged and elderly adults. Full article

Although evidence suggests adiposity as a modifiable risk factor for postmenopausal breast cancer (BC), its association with premenopausal BC remains uncertain. This potential differential relationship for menopausal status has been insufficiently investigated in the Moroccan population due to limited data. This study aims to assess the relationship between various indicators of adiposity and the risk of BC among Moroccan women by menopausal status. A multicenter case-control study was conducted in Morocco between December 2019 and August 2023, including 1400 incident BC cases and 1400 matched controls. Detailed measures of adiposity and self-reported measures from different life stages were collected. Unconditional logistic regression analyses were conducted to estimate odds ratios (ORs) and 95% confidence intervals (95% CIs) for the association between body size indicators and the risk of BC, adjusting for a range of known risk factors for BC. Higher waist circumference (WC) and hip circumference (HC) were associated with an increased risk of BC in both pre- (p-trend < 0.001 for both WC and HC) and post-menopausal women (p-trend < 0.001 for WC, 0.002 for HC). Current body mass index (BMI) ≥30 kg/m² increased the risk of postmenopausal BC (p-trend = 0.012). Among postmenopausal women, higher weight at age 20 was positively associated with BC risk (p-trend < 0.001), while, weight at age 30 was significantly associated with increased BC risk in both pre- (p-trend = 0.008) and post-menopausal women (p-trend = 0.028). Interestingly, weight gain since age 20 was inversely associated with BC risk in postmenopausal women in the adjusted model (p-trend = 0.006). Young-adult BMI observed a significant increased trend with BC risk in both pre- (p-trend = 0.008) and post-menopausal women (p-trend < 0.001). In premenopausal women, larger body shape during childhood and early adulthood was positively associated with BC risk (p-trend = 0.01 and = 0.011, respectively). In postmenopausal women, larger childhood and adolescent body silhouettes were also associated with increased BC risk (p-trend = 0.045 and 0.047, respectively). These results suggest that anthropometric factors may have different associations with pre- and post-menopausal BC among Moroccan women. This underscores the importance of conducting large prospective studies to better understand these findings and explore their links to different molecular subtypes of BC. Full article

Background and Objectives: Thrombocytopenia and hemolytic anemia are common but non-criteria manifestations of antiphospholipid syndrome (APS). However, their relationship with specific immunological profiles remains poorly characterized. This study aimed to evaluate these hematologic manifestations and identify their serological associations in patients with APS. Materials and Methods: We retrospectively reviewed 346 patients diagnosed with APS. Demographic, clinical, and laboratory characteristics were analyzed. Logistic regression was used to identify risk factors associated with hemolytic anemia. Results: The mean age was 47.1 ± 13.1 years, and 71.7% were female. Thrombocytopenia was present in 34.5%, and hemolytic anemia in 16.5% of patients. Lupus anticoagulant (LAC) was the most common antibody (66.8%). In univariate analysis, hemolytic anemia was significantly associated with LAC positivity (OR 4.216, 95% CI: 2.326–7.640, p < 0.001), anticardiolipin IgG (OR 7.170, p = 0.007), triple positivity (OR 3.638, p = 0.002), and diabetes mellitus (OR 2.084, p = 0.007). DIAPS showed a protective trend (OR 0.547, p = 0.002). In multivariate analysis, only LAC remained an independent risk factor for hemolytic anemia (adjusted OR 3.557, 95% CI: 1.355–9.335, p = 0.003). Conclusions: LAC positivity is an independent predictor of hemolytic anemia in APS. These findings suggest a distinct immunologic profile among patients with hematologic involvement and highlight the need for further investigation into non-criteria manifestations. Full article

As the demand for more accurate crime prediction and risk assessment grows, researchers have been developing smarter models that blend statistical methods with machine learning. This study compares a hybrid ARIMA-ANN model with traditional classification techniques to see which best forecast monthly crime risk levels in Galați County, Romania. The analysis is based on a newly compiled dataset of 132 monthly observations from January 2014 to December 2024, which combines a broad array of social, economic, and environmental data points. The main variable, ‘Crime risk’, is based on normalized counts of offenses per capita and divided into five balanced levels: very low, low, moderate, high, and very high. The hybrid ARIMA-ANN model merges the strengths of statistical time series analysis with the flexible learning ability of artificial neural networks. Performance is evaluated against multinomial logistic regression, decision trees, random forests, and support vector machines. Overall, the results show that an ARIMA-ANN model consistently outperforms traditional methods, especially in recognizing patterns over time, seasonal trends, and complex nonlinear relationships in crime data. This study not only sets a new benchmark for crime analytics in Romania but also offers a flexible, scalable framework for classifying crime risk levels across different regions. Full article

Background/Objectives: Pathological vertebral fragility (path-VF) increases the risk of osteoporotic fractures and pedicle screw loosening (PSL) after posterior instrumented spinal fusion (PISF). While WHO body mass index (BMI) categories broadly identify risks related to underweight and obesity, fixed thresholds may inadequately reflect vertebral fragility risks among elderly patients, especially within the normal-weight range. This study investigates whether current BMI classifications sufficiently capture the risk of path-VF in older adults. Methods: This retrospective study included 225 patients who underwent kyphoplasty or PISF (2022–2023). Path-VF was defined by non-tumorous fractures, screw reinforcement, or PSL within six months without prior reinforcement. Patients were grouped into the path-VF (n = 94) and control (n = 131) groups. HU and BMI values, BMI-related ORs, and age trends were analysed, and a logistic regression was performed. Results: Mean HU values were significantly lower in the path-VF group (71.37 ± 30.50) than in controls (130.35 ± 52.53, p < 0.001). Path-VF females (26.26 ± 5.38) had a lower BMI than the control females (29.33 ± 5.98, p = 0.002); no difference was found in males. Normal-weight females showed a borderline risk for path-VF (OR 2.03, p = 0.0495). Obesity (OR_male 0.31/OR_female 0.37) and being male and overweight (OR 0.21) were protective (all p < 0.05). BMI declined with age in path-VF males (p = 0.001) but increased in the controls (p = 0.023). A logistic regression identified a BMI < 22.5 kg/m² and age > 67.5 years as significant risk thresholds. Notably, 20.2% of path-VF patients over 67.5 had a normal weight, suggesting a potentially overlooked subgroup. Conclusions: The current WHO lower limit for normal BMI (18.5 kg/m²) may underestimate the risk of path-VF in patients older than 67.5 years, potentially overlooking 24.7% of cases. The results offer a new approach for clinicians to interpret BMI values at the lower end of the normal range (<22.5 kg/m²) with caution in elderly patients undergoing spinal surgery. Full article

The production of bio-based products for different purposes has become an increasingly common strategy over the last few decades, both in Europe and worldwide. This trend seeks to contribute to mitigating the impacts associated with climate change and to cope with the ambitious objectives established at European level. Over recent decades, agro-industries have shown significant potential as biomass suppliers, triggering the development of robust logistical supply chains and the valorization of by-products to obtain bio-based products that can be marketed at competitive prices. However, this transformation may, in some cases, involve restructuring traditional business model to incorporate the biorefinery concept. In this sense, the first step in developing a bio-based value chain involves assessing the resource’s availability and characterizing the feedstock to select the valorization pathway and the bio-application with the greatest potential. The paper incorporates inputs from a case study on PATURPAT, a company commercializing a wide range of ready-prepared potato products, which has commissioned a starch extraction facility to process the rejected pieces of potatoes and water from the process to obtain starch that can be further valorized for different bio-applications. This study aims to comprehensively review current trends and frameworks for potatoes processing agro-industries and define the most suitable bio-applications to target, as well as identify opportunities and challenges. Full article

Background/Objectives: With the rising trend of out-of-home dining in China, the use of iodized salt (IS) in eating-out venues plays a key role in preventing iodine deficiency disorders (IDDs). However, the coverage rate of iodized salt (CRIS) and the utilization rate of adequately iodized salt (URAIS) in these venues in China remain underexplored, potentially undermining IDD prevention strategies. This study aims to assess the CRIS and URAIS in such venues across China and identify the factors influencing their prevalence. Methods: From 2021 to 2024, a nationwide cross-sectional study was conducted in China, involving 19,346 venues. A 50 g sample of cooking salt was collected from each venue, and the iodine content was measured. The CRIS and URAIS were calculated, and associations with various factors were assessed using Chi-square tests, the Cochran–Armitage trend test, and multivariate logistic regression. Results: Of the 19,346 samples, 18,519 tested positive for IS, and 17,588 contained adequately iodized salt (AIS), resulting in a CRIS of 95.7% and a URAIS of 90.9%. Significant regional differences were found, with coastal areas showing a lower CRIS and URAIS than inland areas (87.0% vs. 97.8%; 81.0% vs. 93.2%) and urbanized areas having lower rates compared to less urbanized areas (94.1% vs. 97.3%; 88.9% vs. 92.9%). Higher per capita income was associated with a lower CRIS and URAIS (Z = −19.72, p < 0.0001; Z = −13.85, p < 0.0001). Lower per capita income (OR = 3.24, OR = 1.36, p < 0.0001), inland areas (OR = 4.14, OR = 2.68, p < 0.0001), and mountainous areas (OR = 2.48, OR = 1.27, p < 0.0001) were associated with a higher likelihood of IS and AIS use. Conclusions: While the CRIS and URAIS in dining venues meet national standards, regional disparities persist, particularly in coastal, plain, and economically advanced areas. Strengthening regulatory oversight and public education on iodized salt’s health benefits is essential. Full article

Vegetation succession is a critical indicator of ecosystem structure and function and is often disrupted by the expansion of invasive species. However, ecosystem-scale studies elucidating invasion-driven succession mechanisms remain limited. This research focused on the Yancheng coastal salt marsh and analyzed the distribution variation of invasive species (Spartina alterniflora) and native species (Suaeda salsa and Phragmites australis) from 1987 to 2022 via the Google Earth Engine and random forest method. Logistic/Gaussian models were used to quantify land–sea distribution changes and vegetation succession trajectories. By integrating data on soil salinity, invasion duration, and fractional vegetation cover, generalized additive models (GAMs) were applied to identify the main factors influencing vegetation succession and to explore how Spartina alterniflora invasion affects the succession of salt marsh vegetation. The results indicated that the areas of Spartina alterniflora and Phragmites australis significantly increased by 3787.49 ha and 3452.60 ha in 35 years, respectively, contrasting with Suaeda salsa’s 82.46% decline. The FVC in the area has significantly increased by 42.10%, especially in the coexisted areas of different vegetation communities, indicating intensified interspecific competition. The overall trend of soil salinity was decreasing, with a decrease in soil salinity in native species areas from 0.72% to 0.37%. From the results of GAMs, soil salinity, tidal action, and invasion duration were significant factors influencing the distribution of native species, but salinity was not a significant factor affecting the Spartina alterniflora distribution. The findings revealed that the expansion of Spartina alterniflora changed the soil salinity and interspecific interactions, thereby altering the original plant community structure and establishing a new vegetation succession. This study enhances the understanding of the impacts of invasive species on ecosystems and offers theoretical support for salt marsh restoration. Full article

Background and Objectives: Hospital mortality rates have repeatedly been used as important indicators of the quality of care provided and as a good monitoring and evaluation tool. Studies on hospital mortality in Saudi Arabia are scant, with most of the available literature focusing on the COVID-19 era. In this study, the patterns and trends in inpatient mortality at King Fahad Central Hospital in southwest Saudi Arabia from 2018 to 2022 were analyzed. Mortality characteristics, including age-specific mortality rates and associated factors, were also investigated. Materials and Methods: This was a retrospective study analyzing hospital mortality data in King Fahad Central Hospital (KFCH) from 2018 to 2022 using the largest hospital discharge database in the Jazan region. The mortality rates were calculated, and 95% confidence intervals (CIs) were reported. The analysis also documented some associations using logistic regression models. Results: Of the 62,534 patients admitted, 36,971 (59.1%) were females, and 25,543 (40.9%) were males. The mean age (standard deviation) was 24.6 (22.8) years. The overall hospital mortality was 4.8% [95% CI: 4.6–5.0] and was significantly higher among males [7.0%, 95% CI: 6.7–7.3] than females [3.2% 95% CI: 3.1–3.4] (p < 0.05). Mortality was significantly higher in the population aged 60 years and above [17.25%, 95% CI: 16.3–18.2] (p < 0.001). During the five-year period analyzed, mortality was low in 2018 (3.3%), with remarkably high rates during the COVID-19 period of 2020 and 2021 (5.6% and 6.0%, respectively). The disease groups with the highest prevalence of mortality include certain conditions originating in the perinatal period. In the logistic regression model, the male sex [odds ratio OR = 2.3, 95% CI = 2.01–2.43) was associated with an increased mortality risk. Compared to intensive care beds, general bed departments are associated with a 98% lower risk of mortality [OR = 0.015, 95% CI = 0.014–0.017]. Conclusions: This analysis of hospital data statistics revealed a relatively low hospital mortality rate in Jazan. However, the high mortality rates among male patients require further analysis and investigation. Customized interventions targeting high-mortality diseases are recommended. Full article

This study investigates farmers’ knowledge, perceptions, and adaptation strategies to climate change in Rwanda’s Eastern Province, integrating social and physical science approaches. Analyzing meteorological data (1981–2021) and surveys from 204 farmers across five districts, we assessed climate trends and adaptation behaviors using statistical methods (descriptive statistics, Chi-square, logistic regression, Regional Kendall test, dynamic linear state-space model). Results show that 85% of farmers acknowledge climate change, with 54% observing temperature increases and 37% noting rainfall declines. Climate data confirm significant rises in annual minimum (+0.76 °C/decade) and mean temperatures (+0.48 °C/decade), with the largest seasonal increase (+0.86 °C/decade) in June–August. Rainfall trends indicate a non-significant decrease in March–May and a slight increase in September–December. Farmers report crop failures, yield reductions, and food shortages as major climate impacts. Common adaptations include agroforestry, crop diversification, and fertilizer use, though financial limitations, information gaps, and input scarcity impede adoption. Despite limited formal education (53.9% primary, 22.3% no formal education), indigenous knowledge aids seasonal prediction. Farm location, group membership, and farming goal are key adaptation enablers. These findings emphasize the need for targeted policies and climate communication to enhance rural resilience by strengthening smallholder farmer support systems for effective climate adaptation. Full article

In the modern world, there is a need to provide a better understanding of the importance or relevance of the available descriptive features for predicting target attributes to solve the feature ranking problem. Among the published works, the vast majority are devoted to the problems of feature selection and extraction, and not the problems of their ranking. In this paper, we propose a novel method based on the Bayesian approach that allows us to not only to build a methodically justified way of ranking features on small datasets, but also to methodically solve the problem of benchmarking the results obtained by various ranking algorithms. The proposed method is also model-free, since no restrictions are imposed on the model. We carry out an experimental comparison of our proposed method with the classical frequency method. For this, we use two synthetic datasets and two public medical datasets. As a result, we show that the proposed ranking method has a high level of self-consistency (stability) already at the level of 50 samples, which is greatly improved compared to classical logistic regression and SHAP ranking. All the experiments performed confirm our theoretical conclusions: with the growth of the sample, an increasing trend of mutual consistency is observed, and our method demonstrates at least comparable results, and often results superior to other methods in the values of self-consistency and monotonicity. The proposed method can be applied to a wide class of rankings of influence factors on small samples, including industrial tasks, forensics, psychology, etc. Full article