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Öğe Assessment of the vitamin D status and its determinants in young healthy students from Palestine(Cambridge Univ Press, 2023) Lenz, Janina Susann; Tintle, Nathan; Kerlikowsky, Felix; Badrasawi, Manal; Zahdeh, Rana; Qasrawi, Radwan; Hahn, AndreasThe global prevalence of vitamin D deficiency is high. Poor vitamin D status, especially in women, has been reported in several countries in the Middle East despite adequate year-round sunlight for vitamin D synthesis. However, data on vitamin D status in Palestine are scarce. The aim of this cross-sectional study was to evaluate vitamin D status based on serum concentrations of 25-hydroxycholecalciferol [25-(OH)D] among young healthy Palestinian students (18-27 years) and to assess associations between 25-(OH)D concentrations and several predictors. The mean 25-(OH)D concentration of women (n 151) was 27.2 +/- 14.5 nmol/l, with the majority having insufficient (31.1 %) or deficient (<60 %) 25-(OH)D status. Only 7 % of women achieved sufficient or optimal 25-(OH)D status. In contrast, men (n 52) had a mean 25-(OH)D concentration of 58.3 +/- 14.5 nmol/l, with none classified as deficient, and most obtaining sufficient (55.8 %) or even optimal 25-(OH)D status (11.5 %). Among women, 98 % wore a hijab and 74 % regularly used sunscreen. Daily dietary vitamin D intake (3-d 24-h recalls) was 45.1 +/- 36.1 IU in the total group (no sex differences). After adjustment, multiple linear regression models showed significant associations between 25-(OH)D concentrations and the use of supplements (B = 0.069; P = 0.020) and dietary vitamin D (B = 0.001; P = 0.028). In gender-stratified analysis, the association between supplement use and 25-(OH)D concentrations was significant in women (B = 0.076; P = 0.040). The vitamin D status of women in the present cohort is critical and appears to be mainly due to wearing a hijab, regular use of sunscreen and low dietary vitamin D intake. The vitamin D status of the women should be improved by taking vitamin D containing supplements or fortified foods.Öğe Identification and prediction of association patterns between nutrient intake and anemia using machine learning techniques: results from a cross-sectional study with university female students from Palestine(Springer Heidelberg, 2024) Qasrawi, Radwan; Badrasawi, Manal; Abu Al-Halawa, Diala; Polo, Stephanny Vicuna; Abu Khader, Rami; Al-Taweel, Haneen; Abu Alwafa, ReemPurposeThis study utilized data mining and machine learning (ML) techniques to identify new patterns and classifications of the associations between nutrient intake and anemia among university students.MethodsWe employed K-means clustering analysis algorithm and Decision Tree (DT) technique to identify the association between anemia and vitamin and mineral intakes. We normalized and balanced the data based on anemia weighted clusters for improving ML models' accuracy. In addition, t-tests and Analysis of Variance (ANOVA) were performed to identify significant differences between the clusters. We evaluated the models on a balanced dataset of 755 female participants from the Hebron district in Palestine.ResultsOur study found that 34.8% of the participants were anemic. The intake of various micronutrients (i.e., folate, Vit A, B5, B6, B12, C, E, Ca, Fe, and Mg) was below RDA/AI values, which indicated an overall unbalanced malnutrition in the present cohort. Anemia was significantly associated with intakes of energy, protein, fat, Vit B1, B5, B6, C, Mg, Cu and Zn. On the other hand, intakes of protein, Vit B2, B5, B6, C, E, choline, folate, phosphorus, Mn and Zn were significantly lower in anemic than in non-anemic subjects. DT classification models for vitamins and minerals (accuracy rate: 82.1%) identified an inverse association between intakes of Vit B2, B3, B5, B6, B12, E, folate, Zn, Mg, Fe and Mn and prevalence of anemia.ConclusionsBesides the nutrients commonly known to be linked to anemia-like folate, Vit B6, C, B12, or Fe-the cluster analyses in the present cohort of young female university students have also found choline, Vit E, B2, Zn, Mg, Mn, and phosphorus as additional nutrients that might relate to the development of anemia. Further research is needed to elucidate if the intake of these nutrients might influence the risk of anemia.Öğe Investigating the association between nutrient intake and food insecurity among children and adolescents in palestine using machine learning techniques(MDPI, 2024) Qasrawi, Radwan; Sgahir, Sabri; Nemer, Maysaa; Halaikah, Mousa; Badrasawi, Manal; Amro, Malak; Vicuna Polo, Stephanny; Abu Al-Halawa, Diala; Mujahed, Doa’a; Nasreddine, Lara; Elmadfa, Ibrahim; Atari, SihamFood insecurity is a public health concern that affects children worldwide, yet it represents a particular burden for low- and middle-income countries. This study aims to utilize machine learning to identify the associations between food insecurity and nutrient intake among children aged 5 to 18 years. The study's sample encompassed 1040 participants selected from a 2022 food insecurity household conducted in the West Bank, Palestine. The results indicated that food insecurity was significantly associated with dietary nutrient intake and sociodemographic factors, such as age, gender, income, and location. Indeed, 18.2% of the children were found to be food-insecure. A significant correlation was evidenced between inadequate consumption of various nutrients below the recommended dietary allowance and food insecurity. Specifically, insufficient protein, vitamin C, fiber, vitamin B12, vitamin B5, vitamin A, vitamin B1, manganese, and copper intake were found to have the highest rates of food insecurity. In addition, children residing in refugee camps experienced significantly higher rates of food insecurity. The findings emphasize the multilayered nature of food insecurity and its impact on children, emphasizing the need for personalized interventions addressing nutrient deficiencies and socioeconomic factors to improve children's health and well-being.Öğe Machine learning approach for predicting the impact of food insecurity on nutrient consumption and malnutrition in children aged 6 months to 5 years(MDPI, 2024) Qasrawi, Radwan; Sgahir, Sabri; Nemer, Maysaa; Halaikah, Mousa; Badrasawi, Manal; Amro, Malak; Polo, Stephanny Vicuna; Abu Al-Halawa, Diala; Mujahed, Doa'a; Nasreddine, Lara; Elmadfa, Ibrahim; Atari, Siham; Al-Jawaldeh, AyoubBackground: Food insecurity significantly impacts children's health, affecting their development across cognitive, physical, and socio-emotional dimensions. This study explores the impact of food insecurity among children aged 6 months to 5 years, focusing on nutrient intake and its relationship with various forms of malnutrition. Methods: Utilizing machine learning algorithms, this study analyzed data from 819 children in the West Bank to investigate sociodemographic and health factors associated with food insecurity and its effects on nutritional status. The average age of the children was 33 months, with 52% boys and 48% girls. Results: The analysis revealed that 18.1% of children faced food insecurity, with household education, family income, locality, district, and age emerging as significant determinants. Children from food-insecure environments exhibited lower average weight, height, and mid-upper arm circumference compared to their food-secure counterparts, indicating a direct correlation between food insecurity and reduced nutritional and growth metrics. Moreover, the machine learning models observed vitamin B1 as a key indicator of all forms of malnutrition, alongside vitamin K1, vitamin A, and zinc. Specific nutrients like choline in the "underweight" category and carbohydrates in the "wasting" category were identified as unique nutritional priorities. Conclusion: This study provides insights into the differential risks for growth issues among children, offering valuable information for targeted interventions and policymaking.
