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A Study on the Effect of Breakfast Habits on Blood Pressure and Academic Performance among University Students in Saudi Arabia
No full textIntroduction: Skipping breakfast is becoming common and can significantly affect a person's physiological and psychological health.
Objectives: To determine the prevalence and factors associated with skipping breakfast among undergraduate students of Saudi Arabia.
Methods: A cross-sectional survey was conducted in two regions of Saudi Arabia using a self-designed and validated questionnaire that included demographic and anthropometric measurements with both open-ended and closed-ended questions. The sample size was 236 students, both adult males and females of age ≥ 18 years of age. Breakfast consumption was assessed using the single-question item: "How often do you eat breakfast?" (Almost every day, sometimes, rarely, or never). Skipping breakfast was defined as respondents indicating that they "sometimes," "rarely," or "never" have breakfast.
Results: Out of a total sample of 236, only 108 participants (45.8%) were consuming breakfast, and 128 participants (54.2%) skipped breakfast in the morning. Cereals were consumed daily by only approximately 20% of the participants. Toast or bread, eggs, and tea/coffee were the most consumed breakfast by more than 50% of the subjects. The highest recognized reason for skipping breakfast is no time to eat in the morning. Age, Systolic Blood pressure, and BMI were found to be significantly associated with breakfast skipping.
Conclusions: Evidence from observational studies suggests that skipping breakfast in real-world settings may contribute to weight gain and the development of overweight and obesity. Future research should explore other anthropometric measures beyond BMI and account for potential confounding factors
A Look at the New Developments in the European Union's Regulation on Crypto-Assets and Anti-Money Laundering
Full text linkThe article examines the recent developments in the European Union's regulation concerning crypto-assets. This regulation is evolving in a fragmented manner and by sectors, particularly focusing on markets and the financial sector in general, and does not have a defined perspective for a comprehensive regulation of the sector. It is a regulation that aims to introduce elements of public control over the actors in the system to regulate the markets and also in anticipation of future new instruments consisting of crypto-assets, introducing elements of public control entrusted to national authorities (notably Regulation 2023/1114 and 2022/858). Meanwhile, in order to enhance the fight against money laundering, elements of control and verification on intermediaries have been introduced as part of the AML Package (particularly with Regulation 2023/1113), imposing obligations on them and implementing control tools over end users, their identities, and their operations. National legal systems are gradually receiving these regulations and harmonizing with European Union law
Contextual Determinants of Stunting in Indonesia: A Systematic Review of Nutritional Interventions and Antenatal Care
Full text linkBackground: Stunting is a significant global health issue, especially in Indonesia, where long-term malnutrition adversely affects children's growth and development, with prevalence rates still exceeding the WHO's recommended threshold. This study examines the contextual factors that influence the effectiveness of nutritional interventions and antenatal care (ANC) in combating stunting in Indonesia.
Methods: A systematic review was conducted by the PRISMA guidelines. A comprehensive search across five major academic databases (Google Scholar, PubMed, ScienceDirect, Embase, and ProQuest) identified 3,690 articles. After a rigorous screening process, 13 studies published between 2019 and 2023 were included in the analysis, focusing on key contextual factors that impact stunting interventions in Indonesia. The quality appraisal utilized Joanna Briggs Institute checklists for analytical cross-sectional studies, cohort studies, quasi-experimental studies, qualitative research, systematic reviews, case reports, and text and opinion papers, each matched to the respective study design.
Findings: The review identified four critical contextual factors shaping stunting interventions: (1) socioeconomic status, particularly household income and education, which significantly influence access to healthcare and nutrition; (2) cultural beliefs, including food taboos and misconceptions, which hinder optimal nutritional practices; (3) geographical disparities, with rural populations experiencing higher stunting rates due to limited access to healthcare and resources; and (4) government policies, highlighting the importance of strong political commitment, multisectoral collaboration, and localized programs.
Conclusion: Nutritional interventions and ANC are more effective in reducing stunting among Indonesian children when tailored to local socioeconomic, cultural, and geographical contexts. These findings highlight the need for targeted, context-specific strategies to improve child growth outcomes in vulnerable populations
Role of Recombinant Human Erythropoietin in Neonates with Moderate to Severe Hypoxic Ischemic Encephalopathy - A Prospective Cohort Study
No full textBackground: Hypoxic-ischemic encephalopathy (HIE) is a significant brain injury that occurs when there is inadequate oxygen supply to the brain during the neonatal period. Newer researches have established that rhEPO, human recombinant erythropoietin possesses neurological, neuro-restorative, and anti-inflammatory properties in asphyxia newborns. These effects are invaluable in enhancing outcomes for neonates diagnosed with hypoxic-ischemic encephalopathy-HIE
Aims: To evaluate the role and effects of human recombinant erythropoietin in moderate to severe hypoxic-ischemic encephalopathy in neonates.
Objective: To assess the safety and feasibility of rhEPO in asphyxiated neonates with moderate to severe encephalopathy. To know and to correlate the effect of EPO on EEG, RI (resistive index) in Neurosonogram (NSG), MRI brain in asphyxiated neonates with moderate to severe encephalopathy.
Materials and methods: This is a Prospective Cohort Study conducted over 12-18 months with a sample size of 92, comprising 46 participants in each group. All neonates received intravenous recombinant human erythropoietin (rhEPO) after 6 hours of life. A total of 5 doses were administered.
Results: In the EPO group, 47.8% (n = 22) had moderate encephalopathy, while 52.2% (n = 24) had severe encephalopathy. In our study we found that Amplitude–integrated electroencephalogram [aEEG] showed burst suppression [21.7% vs. 6.5%], low voltage [10.9% vs. 4.3%], flat trace [13.0% vs. 8.7%], and status epilepticus [6.5% vs. 2.2%] in the control group in comparison with EPO Group. A neurosonogram [NSG] was done and showed Abnormal RI [56.5% vs. 15.2%] and Normal RI [43.5% vs. 84.8%] in the control group in comparison with the EPO Group. Brain magnetic-resonance imaging [MRI] done at discharge showed severe brain injury [32.6% vs. 8.6%] and regional-specific HIE [19.5% vs. 39.1%] in the control group in comparison with the EPO Group. Mortality outcome was 10.8% in control group in comparison with EPO Group(2.17%).
Conclusion: The study concludes that administering recombinant human erythropoietin (rhEPO) to newborns with moderate to severe hypoxic-ischemic encephalopathy (HIE) is safe and practical. In comparison to the control group, rhEPO treatment significantly reduces the occurrence of an abnormal resistive index (RI). Furthermore, EPO-treated neonates showed improvements in electroencephalographic (EEG) patterns, neurosonogram (NSG) resistive index, and MRI brain findings, suggesting possible neuroprotective advantages
Analysis of the Determinants of Foreign Direct Investment Attractiveness in the Industrial Sector in Tunisia
Full text linkThis study aims to assess, using an econometric model based on panel data, the impact of macroeconomic variables on Foreign Direct Investment (FDI) flows in Tunisia's manufacturing sector.
The econometric analysis reveals that factors such as geographic distance, disparities in market size and factor endowments between Tunisia and investor countries, as well as labor availability and competitiveness, are the key determinants of Tunisia's attractiveness for FDI. These results underscore the importance of structural conditions and comparative advantages in attracting foreign investment to this strategic sector
Exploring Parents' Motivations for Sharenting and Consequences for Children's Well-Being
No full textIntroduction: This literature review uses thematic analysis to identify common themes and topics in recent literature on the perceptions, attitudes, and motivations towards parents’ sharenting behavior.
Objective: This study investigates perspectives on sharenting—the practice of parents posting content about their children on social media—and the rationale behind this behavior. As digital platforms become more integrated into family life, understanding the motives for sharing is critical for assessing their social, ethical, and developmental consequences.
Methods: Articles were selected through a literature search. We eliminated articles that included sharenting, sharenting practices in Malaysia, impression management and sharenting, and reinforcement theory and sharenting. 41 articles were chosen and reviewed to identify the main topics of discussion.
Findings: This study identifies major motives for sharing, as revealed through qualitative interviews and surveys with parents and social media users, including a need for social connection, community support, and documenting parenting milestones. The findings reflect a variety of viewpoints on the practice, with some seeing sharing as a way to celebrate parenting and develop relationships. In contrast, others are concerned about privacy and the digital legacy left for children.
Conclusion: By analyzing these perspectives, the study contributes to the broader discussion of digital parenting practices and sheds light on the balance between sharing and privacy in the digital era. This study emphasizes the importance of raising parental awareness and providing help as they navigate the difficulties of social media sharing.
Recommendation: These results serve as a reference for future child psychology and mental health research. Thus, it is recommended that parental sharenting behavior be further explored, and a suitable legal framework should be established in Malaysia to govern and manage this issue before violations related to sharenting, such as digital kidnapping and cyberbullying, become difficult to address in the Malaysian context
Multifactorial Determinants of Stunting among Under-Five Children in Tambun Tulang Village, South Coastal District, Indonesia
No full textBackground: Stunting is a chronic condition of impaired growth in children under five, primarily due to long-term malnutrition. It is identified using the height-for-age (TB/U) indicator, where a Z-score below -2 standard deviations (SD) from the WHO child growth standards signifies stunting. In Kenagarian IV Koto Hilie, 53 children (8.32%) were recorded as stunted. Although malnutrition can begin during pregnancy or shortly after birth, it often becomes evident when the child reaches two years of age.
Objective: This study aimed to identify the factors influencing the incidence of stunting among toddlers in Kampung Bukit Tambun Tulang.
Methods: A quantitative, cross-sectional study design was employed. The population consisted of 173 toddlers, with a sample of 63 selected through simple random sampling. Primary data were collected via structured interviews using questionnaires, and secondary data were sourced from Kenagarian IV Koto Hilie health reports. Data analysis included univariate and bivariate methods, with the chi-square test employed to identify associations.
Results: The study found that 57.1% of the sampled toddlers were stunted. Bivariate analysis revealed significant relationships between stunting and maternal knowledge (p = 0.003), family income (p = 0.022), and nutritious food intake (p = 0.016).
Conclusion: Stunting is closely linked to maternal education, socioeconomic conditions, and child nutrition. Health workers should provide targeted education to promote behavioral change and improve parenting practices. Structured family coaching is recommended to support nutritional fulfillment and prevent stunting during early childhood development
Optimizing Physical Performance and Nutritional Strategies for Young Basketball Players: Training Load Distribution and Recovery Approaches
No full textBackground: This study examines the optimization of physical load distribution in young basketball players while integrating nutritional strategies to enhance performance, recovery, and overall health. Proper nutrition supports endurance, muscle function, injury prevention, and physiological development in young athletes, making it essential in conjunction with structured training.
Method: This study employs a scoping review methodology to analyze recent literature on the physical performance and nutrition of young basketball players. It synthesizes findings from studies published between 2014 and 2024, focusing on training strategies, nutritional practices, and their impact on the physical development of athletes. The review examines factors such as exercise routines, hydration, macronutrient and micronutrient intake, and post-exercise recovery strategies to optimize performance and ensure long-term health for youth athletes.
Results: The review identifies key factors that influence youth basketball performance, including structured training, proper nutrition, and hydration. It emphasizes the importance of balanced macronutrient intake and targeted interventions to enhance strength, endurance, and recovery, thereby optimizing physical development.
Conclusions: A holistic approach that combines structured training with tailored nutrition plans is essential for enhancing youth basketball performance and promoting long-term health
Determination of Alzheimer's Disease Stages by Artificial Learning Algorithms
Full text linkIntroduction: This study aims to determine the stages of Alzheimer's disease (AD) using different machine learning algorithms, and compares the performance of these models.
Methods: Demographic, genetic, and neurocognitive inventory data from the National Alzheimer's Coordinating Center (NACC) database as well as brain volume/thickness data from magnetic resonance imaging (MRI) scans were used. Deep Neural Networks, Ordinal Logistic Regression, Random Forest, Gaussian Naive Bayes, XGBoost, and LightGBM models were used to identify four different ordinal stages of AD.
Results: Although the performance measures of the developed models were similar, the highest classification rate of AD stages was achieved by the Random Forest model (accuracy: 0.86; F1 score: 0.86; AUC: 0.95). The outputs of the model with the best performance were explained by the SHapley Addictive exPlanations (SHAP) method.
Conclusions: This indicates that non-invasive markers and machine learning models can be used effectively in early diagnosis and decision support systems to predict stages of AD
Evaluation of A Novel Risk Factor Screening Tool for Gestational Diabetes Mellitus: A Machine Learning Based Predictive Method
Full text linkIntroduction: Gestational diabetes mellitus (GDM) is a significant pregnancy complication linked to adverse outcomes for both mother and child. Early identification of high-risk individuals is crucial for effective management and prevention for the onset/progression of the GDM. Our study aims to a) evaluate the effectiveness of a newly developed machine learning based risk factor screening tool for predicting GDM and b) to compare its predictive performance against established models and current literature.
Methods: This study explored SNP data from the leptin (LEP) and leptin receptor (LEPR) genes to develop machine learning models for predicting gestational diabetes mellitus (GDM). It included data preprocessing, such as cleaning and feature selection, focusing on genetic markers, metabolic parameters, and demographic information. Various algorithms, including Logistic Regression, Decision Trees, and Random Forests, were used, and their performance was evaluated using metrics like accuracy and ROC-AUC to determine the best model for GDM prediction.
Results: The newly developed screening tool demonstrated a sensitivity of 85%, specificity of 78%, positive predictive value (PPV) of 68%, and negative predictive value (NPV) of 90% in predicting GDM. Comparatively, machine learning models showed higher sensitivity (90-95%) but lower specificity (65-75%).
Conclusion: The developed risk factor screening tool is a viable method for predicting GDM, with accuracy metrics comparable to advanced machine learning models and established literature. Future research should focus on refining these tools and exploring their integration into routine prenatal care to enhance early detection and intervention strategies for GDM