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Öğe Adherence to the United States department of agriculture dietary recommendations pre- and during the coronavirus disease-19 pandemic among pregnant women in Arab countries(2022) Hoteit, Maha; Hoteit, Reem; Al-Jawaldeh, Ayoub; Nasr, Mariane Abou; Obeid, Sara; Fakih, Chadi; El Hajj, Mohamad; Qasrawi, Radwan; Seir, Rania Abu; Allehdan, Sabika; Ismail, Mahmoud Samy; Bookari, Khlood; Arrish, Jamila; Al-Bayyari, Nahla; Tayyem, ReemaDuring pregnancy, woman's diet is one of the most preeminent factors affecting mother and child's health. Prior to the coronavirus disease-19 (COVID-19) pandemic, inadequate maternal diet and low adherence to dietary guidelines was reported among pregnant women in the Arab countries. Nowadays, COVID-19 infection during pregnancy is widely discussed among literature. However, there is limited data on the health impacts of the COVID-19 pandemic on non-infected pregnant women. This substantially larger group also suffered significant lifestyle changes during the lockdown period. The aim of the study is to characterize dietary patterns, intake and adherence to the United States Department of Agriculture (USDA) pregnancy guidelines before and during the COVID-19 pandemic in Arab pregnant women. Using a specially designed questionnaire and using the snowball sampling method, the survey was carried out among a convenient sample of 1,939 pregnant women from five Arab countries. Our study found an increment in the consumption of cereals, fruits, vegetables, dairy products, meats, and nuts that occurred during the pandemic compared to the preceding period. Despite this noticeable increase during the pandemic, the Arab pregnant women in this study had significantly lower adherence to the USDA pregnancy guidelines. The daily consumption of almost all food groups was lower than the USDA's daily recommendations, except for fruits intake, which was higher than the daily standard. Demonstrated poor adherence to prenatal USDA dietary guidelines by Arab pregnant women can lead to numerous deficiencies and health risks among their offspring. In conclusion, our study showed that before and during the COVID-19 pandemic, poor adherence to dietary recommendations occurred in a considerable number of Arab pregnant women. The findings emphasize the need for nutritional education and intervention during prenatal visits.Öğe Antibiotic resistance knowledge, attitudes, and practices among pharmacists : a cross-sectional study in West Bank, Palestine(Hindawi, 2023) Al-Halawa, Diala Abu; Seir, Rania Abu; Qasrawi, RadwanAntibiotic resistance is an increasing problem worldwide. Dispensing antibiotics without prescription is a major contributing factor to antibiotic resistance. Pharmacists as healthcare providers are, in many studies, considered responsible for this practice. -is study aims to explore Palestinian pharmacists’ knowledge, attitudes, and practices concerning antibiotic resistance. A descriptive cross-sectional survey was conducted in 2021–2022. A random sample of 152 pharmacists was selected from the West Bank. Data were collected using a self-administered questionnaire that includes :ve sections: demographic characteristics, knowledge, attitudes, practices, and potential interventions. Results indicated that 60% of pharmacists dispense antibiotics without a prescription. A signifcant association between pharmacies’ locality and antibiotic knowledge, attitudes, and practices was found. Pharmacists’ knowledge-related responses indicated that 92.1% of the pharmacists agreed that inappropriate use of antibiotics can lead to in effective treatment and 86.2% disagreed that patients can stop taking antibiotics upon symptoms’ improvement. Only 17.1% disagreed that antibiotics should always be used to treat upper respiratory tract infections. Over two thirds considered that they are aware of the regulations about antibiotic dispensing and acknowledged that antibiotics are classified as prescription drugs. Furthermore, 71.7% and 53.3% agreed that they have good knowledge of the pharmacological aspects of antibiotics and antibiotic resistance. Concerning attitudes, 75.6% agreed that antibiotic resistance is an important and serious public health issue facing the world, and 52% thought that antibiotic dispensing without a prescription is a common practice in the West Bank. Our findings indicate that pharmacists’ locality and practices related to antibiotic dispensing without prescription are associated with the increase in antibiotics misuse and bacterial resistance. -ere is a need to design education and training programs and implement legislation in Palestine to decrease antibiotic resistance.Öğe Assessment of dietary and lifestyle responses after COVID-19 vaccine availability in selected arab countries(Frontiers in Nutrition, 2022) Cheikh İsmail, Leila; Osaili, Tareq M.; Mohamad, Maysm N.; Al Marzouqi, Amina; Habib-Mourad, Carla; Abu Jamous, Dima O.; I. Ali, Habiba; Al Sabbah, Haleama; Hasan, Hayder; Hassan, Hussein; Stojanovska, Lily; Hashim, Mona; AlHaway, Muna; Qasrawi, Radwan; Shaker Obaid, Reyad R.; Al Daour, Rameez; Saleh, Sheima T.; Al Dhaheri, Ayesha S.Background: The COVID-19 pandemic has been consistently associated with unhealthy lifestyle behaviors and dietary practices. This study aimed to assess the dietary and lifestyle behaviors of adults after COVID-19 vaccine availability and their attitude toward the vaccine in selected Arab countries. Methods: A cross-sectional survey-based study was conducted between October 2021 and December 2021 using Google Forms (n = 2259). A multi-component questionnaire was used to collect socio-demographic characteristics, attitudes toward the COVID-19 vaccine, and behavioral, dietary, and lifestyle responses after easing the restriction. Participants were given a score based on the sum of positive dietary and lifestyle changes. The generalized linear models were used to identify the association between positive dietary and lifestyle changes score and sociodemographic characteristics.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 Classification of stroke using machine learning techniques : review study(IEEE, 2023) Sawan, Aktham; Awad, Mohammed; Qasrawi, RadwanAbstract—Presently, stroke is the leading cause of adult injury worldwide. The World Health Organization estimates that each year 15 million people around the world suffer a stroke. Five million of them die, and another five million are disabled for life. There is a chance to dramatically enhance the classification of strokes in the early stages. In this article, we reviewed all portable devices that produced electroencephalogram(EEG) data and all machine learning (ML) methods and deep-learning methods used to identify stroke using EEG data, and we noted that the amount of work on ML and deep learning in analyzing EEG data have increased rapidly in recent years. Such analysis has achieved greater precision compared to that conventional methods. We also discussed in this study the opportunities and key challenges for improving the accuracy of future work.Öğe Cluster analysis and classification model of nutritional anemia associated risk factors among schoolchildren(Frontiers in Nutrition, 2022) Abu Al-Halawa, Diala; Qasrawi, RadwanNutritional inadequacy has been a major health problem worldwide. One of the many health problems that result from it is anemia. Anemia is considered a health concern among all ages, particularly children, as it has been associated with cognitive and developmental delays. Researchers have investigated the association between nutritional deficiencies and anemia through various methods. As novel analytical methods are needed to ascertain the association and reveal indirect ones, we aimed to classify nutritional anemia using the cluster analysis approach. In this study, we included 4,762 students aged between 10 and 17 years attending public and UNRWA schools in the West Bank. Students’ 24-h food recall and blood sample data were collected for nutrient intake and hemoglobin analysis. The K-means cluster analysis was used to cluster the hemoglobin levels into two groups. Vitamin B12, folate, and iron intakes were used as the indicators of nutrient intake associated with anemia and were classified as per the Recommended Dietary Allowance (RDA) values. We applied the Classification and Regression Tree (CRT) model for studying the association between hemoglobin clusters and vitamin B12, folate, and iron intakes, sociodemographic variables, and health-related risk factors, accounting for grade and age. Results indicated that 46.4% of the students were classified into the low hemoglobin cluster, and 60.7, 72.5, and 30.3% of vitamin B12, folate, and iron intakes, respectively, were below RDA. The CRT analysis indicated that vitamin B12, iron, and folate intakes are important factors related to anemia in girls associated with age, locality, food consumption patterns, and physical activity levels, while iron and folate intakes were significant factors related to anemia in boys associated with the place of residence and the educational level of their mothers. The deployment of clustering and classification techniques for identifying the association between anemia and nutritional factors might facilitate the development of nutritional anemia prevention and intervention programs that will improve the health and wellbeing of schoolchildren.Öğe Determinants of exclusive breastfeeding and mixed feeding among mothers of infants in Dubai and Sharjah, United Arab Emirates(Frontiers, 2022) Al Sabbah, Haleama; Assaf, Enas A.; Taha, Zainab; Qasrawi, Radwan; Radwan, HadiaBackground: Breastfeeding (BF) is considered the ultimate method of infant feeding for at least the first 6 months of life. Exclusive breastfeeding (EBF) is one of the most effective interventions to improve child survival. The main objective of this study was to assess the prevalence and duration of exclusive breastfeeding and the associated factors among women in Dubai and Sharjah, UAE. Methods: A cross-sectional study was conducted in four hospitals and four healthcare centers in Dubai and Sharjah between September 2017 and December 2017. Hospitals and centers are governmental and provide maternal and child health services. A convenience sample of 858 Arab and Emirati mothers with children under the age of 2 years participated in the study. Face-to-face interviews were conducted by using structured questionnaires. The study was approved by the University Ethical Committee and the UAE Ministry of Health before data collection. Descriptive statistics were computed to describe all the questionnaire items. The chi-square test was used to compare the study’s categorical variables. A binary logistic regression analysis was used to predict the relationship between BF and its associated factors. Statistical tests with P-values < 0.05 were considered statistically significant. Results: The mean age of the participating mothers was 30.6 (SD 5.5) years. Results showed that the prevalence of exclusive breastfeeding among the study participants was 24.4% (31.1% in Sharjah and 22% in Dubai; P = 0.003). The binary logistic regression reported that mother’s and father’s education, skin-to-skin period, number of children, mothers’ health, and place of living were significantly associated with exclusive breastfeeding (P < 0.05). The results reported a significant association between EB and duration of breastfeeding (OR = 6.9, P = 0.002), husband education (OR = 2.1, P = 0.015), mother education (OR = 1.3, P = 0.027), number of children (OR = 7.9, P = 0.045), having any health problem (OR = 1.2, P = 0.045), and living place (OR = 1.4, P = 0.033), and a non-significant positive effect of family size and family income. Furthermore, the result reported a significant association betweenmixed breastfeeding and duration of breastfeeding (OR = 0.1, P = 0.000), skin-to-skin period (OR = 0.3, P = 0.002), underweight (OR = 4.7, P = 0.034), last infant’s sex (OR = 1.6, P = 0.010), having maid at home (OR = 2.1, P = 0.000), number of children (OR = 0.2, P = 0.013), and living place (OR =1.1, P = 0.014), and a non-significant association with family size and family income. Conclusions: Therefore, a health promotion program for exclusive breastfeeding during antenatal health visits, together with initiating health policies in maternal hospitals to encourage the initiation of breastfeeding during the first hour of birth and the introduction of skin-to-skin contact during the first 5 min of birth are highly recommended.Öğe Determinants of exclusive breastfeeding and mixed feeding among mothers of infants in Dubai and Sharjah, United Arab Emirates(Frontiers in Nutrition, 2022) Al Sabbah, Haleama; Assaf, Enas A.; Taha, Zainab; Qasrawi, Radwan; Radwan, HadiaBackground: Breastfeeding (BF) is considered the ultimate method of infant feeding for at least the first six months of life. The main objective of this study was to assess the prevalence and duration of exclusive breastfeeding and the associated factors among women in Dubai and Sharjah, UAE. Methods: A cross-sectional study was conducted in four hospitals and four healthcare centers in Dubai and Sharjah between September 2017 and December 2017. Hospitals and centers are governmental, and provide maternal and child health services. A convenience sample of 858 Arab and Emirati mothers for children under the age of 2 years participated in the study. Face-to-face interviews were conducted by using structured questionnaires. The study was approved by the University Ethical Committee and UAE Ministry of Health prior to data collection. Descriptive statistics were computed to describe all the questionnaire items. Chi-square test was used to compare between the study categorical variables. A binary logistic regression analysis was used to predict the relationship between BF and its associated factors. Statistical tests with p- values < 0.05 were considered statistically significant. Results: The mean age of the participating mothers was 30.6 (SD 5.5) years. Results showed that the prevalence of exclusive breastfeeding among the study participants was 24.4% (31.1 in Sharjah and 22% in Dubai) (p =.003). The binary logistic regression reported that mother’s and father’s education, skin-to-skin period, number of children, mothers’ health, and place of living were significantly associated with exclusive breastfeeding (p < 0.05). Furthermore, the results reported a significant and positive effect with the duration of breast feeding, skin to skin period, underweight, last infant sex, number of children , and having a maid at home, and a non-significant positive effect of family size, and family income on the increased odds ratio of mixed breastfeeding (OR=2.1, p=.000; OR=7.1, p=0.926; and OR=2.5, p=0.755). Conclusions: Therefore, a health promotion program for exclusive breastfeeding during antenatal health visits, together with initiating health policies in maternal hospitals to encourage the initiation of breastfeeding during the first hour of birth and the introduction of skin-to-skin contact during the first five minutes of birth.Öğe Dietary diversity in the eastern mediterranean region before and during the covıd-19 pandemic: disparities, challenges, and mitigation measures(2022) Hoteit, Maha; Mortada, Hussein; Al-Jawaldeh, Ayoub; Mansour, Rania; Yazbeck, Batoul; Qasrawi, RadwanThe COVID-19 pandemic has revealed the Eastern Mediterranean Region's food system's fragility posing severe challenges to maintaining healthy sustainable lifestyle. The aim of this cross-sectional study (N = 13,527 household's family members, mean age: 30.3 ±11.6, 80% women) is to examine the impact of the COVID-19 pandemic on food consumption patterns and household's dietary diversity in 10 Eastern Mediterranean countries. A food frequency questionnaire was used to investigate the consumption patterns along with the calculation of the Food Consumption Score (FCS), a proxy indicator of dietary diversity. Data collected on cooking attitudes, shopping and food stock explore the community mitigation measures. In the overall population, before and during the pandemic, most food groups were consumed less or equal to 4 times per week. As evident from our findings and considering that the pandemic may be better, but it's not over, small to moderate changes in food consumption patterns in relatively short time periods can become permanent and lead to substantial poor dietary diversity over time. While it is a priority to mitigate the immediate impact, one area of great concern is the long-term effects of this pandemic on dietary patterns and dietary diversity in Eastern Mediterranean households. To conclude, the COVID-19 crisis revealed the region's unpreparedness to deal with a pandemic. While the aggressive containment strategy was essential for most countries to help prevent the spread, it came at a high nutritional cost, driving poor dietary diversity.Öğe Dietary intake and lifestyle practices of eastern mediterranean postpartum women before and during COVID-19 pandemic: An internet-based cross sectional survey.(Frontiers, 2022) Qasrawi, Radwan; Tayyem, Reema F.; Al-Bayyari, Nahla; Al-Awwad, Narmeen; Abuhijleh, Haya; Hoteit, Reem; Badran, Eman; Allehdan, Sabika S.; Allehdan, Sabika; Bookari, Khlood; Arrish, Jamila; Abu-Seir, Rania; Hoteit, MahaBackground: During the lockdown period, a substantial group of these women reported lifestyle changes. Aim: The aim of the study is to characterize the dietary patterns, intake and the adherence to the United States Department of Agriculture (USDA) pregnancy guidelines before and during the COVID 19 pandemic in Eastern Mediterranean postartum women. Methods: An internet-based cross-sectional survey was used to collect the data. The survey was carried out among 1,939 postpartum women from five countries from the Eastern Mediterranean region. Change in dietary intake from the five food groups and the adherence to USDA's daily recommendations were assessed. Findings: There was a significant increase in the mean (SD) consumption of all the food groups, including bread, rice, and other cereals, fruits, vegetables, milk and milk products, white and red meat, and nuts during the pandemic. Around 84% of participants reported no/low adherence (0-2) to USDA guidelines, whereas only 15% reported moderate or high adherence (3-5) to the guidelines before the pandemic. However, there was an increase in the proportion of subjects reporting moderate/high adherence (22%) during the pandemic. Discussion and Conclusions: A substantial proportion of our study participants reported a lower dietary intake than the recommended amounts, and low adherence to the five food groups. Reasonable and applicable actions should be taken to protect postpartum women and their children from the effects of low dietary intake, particularly during pandemics and lockdowns. More researches are needed to identify the modifiable factors which could improve the nutritional status of the postpartum women during the pandemic.Öğe Dietary intake and lifestyle practices of eastern mediterranean postpartum women before and during COVID-19 pandemic: An internet-based cross-sectional survey(FRONTIERS MEDIA SA, 2022) Tayyem, Reema; Al-Bayyari, Nahla; Al-Awwad, Narmeen; Abuhijleh, Haya; Hoteit, Reem; Qasrawi, Radwan; Badran, Eman; Basha, Asma; Allehdan, Sabika; Boukari, Khlood; Arrish, Jamila; Seir, Rania Abu; Hoteit, MahaBackgroundDuring the lockdown period, a substantial group of these women reported lifestyle changes. AimThe aim of the study is to characterize the dietary patterns, intake and the adherence to the United States Department of Agriculture (USDA) pregnancy guidelines before and during the COVID-19 pandemic in Eastern Mediterranean postartum women. MethodsAn internet-based cross-sectional survey was used to collect the data. The survey was carried out among 1,939 postpartum women from five countries from the Eastern Mediterranean region. Change in dietary intake from the five food groups and the adherence to USDA's daily recommendations were assessed. FindingsThere was a significant increase in the mean (SD) consumption of all the food groups, including bread, rice, and other cereals, fruits, vegetables, milk and milk products, white and red meat, and nuts during the pandemic. Around 84% of participants reported no/low adherence (0-2) to USDA guidelines, whereas only 15% reported moderate or high adherence (3-5) to the guidelines before the pandemic. However, there was an increase in the proportion of subjects reporting moderate/high adherence (22%) during the pandemic. Discussion and conclusionsA substantial proportion of our study participants reported a lower dietary intake than the recommended amounts, and low adherence to the five food groups. Reasonable and applicable actions should be taken to protect postpartum women and their children from the effects of low dietary intake, particularly during pandemics and lockdowns. More researches are needed to identify the modifiable factors which could improve the nutritional status of the postpartum women during the pandemic.Öğe Editorial: Food literacy and healthy diets in childhood and adolescence(Frontiers Media Sa, 2024) Hoteit, Maha; Qasrawi, Radwan; Tayyem, Reema[Abstract Not Available]Öğe Editorial: Innovation and trends in the global food systems, dietary patterns and healthy sustainable lifestyle in the digital age(Frontiers Media, 2023) Hoteit, Maha; Qasrawi, Radwan; Al Sabbah, Haleama; Tayyem, ReemaThe global food systems are undergoing significant changes due to evolving dietary habits and the digital era's influence, impacting health and overall global stability. As processed foods and sedentary lifestyles become more prevalent, there's a marked increase in non-communicable diseases like obesity and diabetes. Despite advancements in food security in developed regions, low-to-middle-income countries still grapple with substantial challenges, exacerbated by the COVID-19 pandemic's disruptions. Technology offers promising solutions. Developments in artificial intelligence, data science, and ICT are reshaping our understanding and approaches to global food systems, dietary choices, and sustainable health behaviors. This Research Topic compiles studies examining the intersection of food security, nutrition, and technological innovation. Comprising 15 papers, the collection emphasizes global dietary trends, especially in the Eastern Mediterranean Region, both pre and post-COVID-19. Highlights include the growing prevalence of nutrition-related diseases in the region, the efficacy of long-term dietary interventions for obesity, the links between dietary patterns and childhood anemia, and the ripple effect of parental dietary habits on families. The importance of maintaining practices like the Mediterranean Diet is also underscored, given its health benefits.Öğe Hybrid deep learning and metaheuristic model based stroke diagnosis system using electroencephalogram (EEG)(Elsevier, 2023) Sawan, Aktham; Awad, Mohammed; Qasrawi, Radwan; Sowan, MohammadOver the last few decades, there has been a significant increase in the average lifespan. Consequently, the number of elderly people suffering from strokes has also risen. As a result, strokes and their treatments have become crucial subjects of research, particularly for the application of machine learning. One of the primary factors in stroke treatment is the speed of response. Currently, both computed tomography (CT) and magnetic resonance imaging (MRI) are used to diagnose strokes. However, CT takes eight hours before an accurate diagnosis can be made, and MRI is expensive and not available in all hospitals. Therefore, there is a growing need for novel approaches to identifying strokes based on electroencephalogram (EEG) signals. In this paper, a hybrid model of deep learning and metaheuristic was developed in the offline stage to classify strokes. Since EEG data is a time series with frequencies, a hybrid model was deemed appropriate. This hybrid model combined a Convolutional Neural Network (CNN) with bidirectional Gated Recurrent Unit (BiGRU). The performance of this model surpassed that of other comparable models. Given the paramount importance of speed and accuracy in this work, the harmony search (HS) algorithm, which is specialized in handling frequencies, was used for feature selection. HS outperformed all similar algorithms when applied to the CNN-BiGRU hybrid model. Additionally, for the optimization of continuous hyperparameters, the multiverse optimization (MVO) algorithm was employed, which proved to be the most effective when compared to another similar algorithm for validation purposes. The new model, CNN-BiGRU-HS-MVO, was applied to analyze the data collected from Al Bashir Hospital using the MUSE-2 portable device, resulting in an impressive prediction accuracy of 99.991%. Moreover, it demonstrated an 11.08% improvement over the results from the paper titled “Predicting stroke severity with a 3-min recording from the Muse portable EEG study”. Furthermore, a decision support system was built on the cloud computing environment based on the hybrid model. This system allows for the diagnosis of patients anytime and from anywhere within minutes, with the authorized person receiving the diagnosis results through SMS notification.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 The impact of COVID-19 on physical (in)activity behavior in 10 Arab countries(MDPI, 2022) Al Sabbah, Haleama; Taha, Zainab; Qasrawi, Radwan; Assaf, Enas A.; Ismail, Leila CheikhInsufficient physical activity is considered a strong risk factor associated with non-communicable diseases. This study aimed to assess the impact of COVID-19 on physical (in)activity behavior in 10 Arab countries before and during the lockdown. A cross-sectional study using a validated online survey was launched originally in 38 different countries. The Eastern Mediterranean regional data related to the 10 Arabic countries that participated in the survey were selected for analysis in this study. A total of 12,433 participants were included in this analysis. The mean age of the participants was 30.3 (SD, 11.7) years. Descriptive and regression analyses were conducted to examine the associations between physical activity levels and the participants' sociodemographic characteristics, watching TV, screen time, and computer usage. Physical activity levels decreased significantly during the lockdown. Participants' country of origin, gender, and education were associated with physical activity before and during the lockdown (p < 0.050). Older age, watching TV, and using computers had a negative effect on physical activity before and during the lockdown (p < 0.050). Strategies to improve physical activity and minimize sedentary behavior should be implemented, as well as to reduce unhealthy levels of inactive time, especially during times of crisis. Further research on the influence of a lack of physical activity on overall health status, as well as on the COVID-19 disease effect is recommended.Öğe Machine learning techniques for identifying mental health risk factor associated with schoolchildren cognitive ability living in politically violent environments(Frontiers Media Sa, 2023) Qasrawi, Radwan; Polo, Stephanny Vicuna; Abu Khader, Rami; Abu Al-Halawa, Diala; Hallaq, Sameh; Abu Halaweh, Nael; Abdeen, ZiadIntroductionMental health and cognitive development are critical aspects of a child's overall well-being; they can be particularly challenging for children living in politically violent environments. Children in conflict areas face a range of stressors, including exposure to violence, insecurity, and displacement, which can have a profound impact on their mental health and cognitive development. MethodsThis study examines the impact of living in politically violent environments on the mental health and cognitive development of children. The analysis was conducted using machine learning techniques on the 2014 health behavior school children dataset, consisting of 6373 schoolchildren aged 10-15 from public and United Nations Relief and Works Agency schools in Palestine. The dataset included 31 features related to socioeconomic characteristics, lifestyle, mental health, exposure to political violence, social support, and cognitive ability. The data was balanced and weighted by gender and age. ResultsThis study examines the impact of living in politically violent environments on the mental health and cognitive development of children. The analysis was conducted using machine learning techniques on the 2014 health behavior school children dataset, consisting of 6373 schoolchildren aged 10-15 from public and United Nations Relief and Works Agency schools in Palestine. The dataset included 31 features related to socioeconomic characteristics, lifestyle, mental health, exposure to political violence, social support, and cognitive ability. The data was balanced and weighted by gender and age. DiscussionThe findings can inform evidence-based strategies for preventing and mitigating the detrimental effects of political violence on individuals and communities, highlighting the importance of addressing the needs of children in conflict-affected areas and the potential of using technology to improve their well-being.Öğe Machine learning techniques for predicting depression and anxiety in pregnant and postpartum women during the COVID-19 pandemic: a cross-sectional regional study(F1000 Research Ltd, 2022) Qasrawi, Radwan; Amro, Malak; VicunaPolo, Stephanny; Abu Al-Halawa, Diala; Agha, Hazem; Abu Seir, Rania; Hoteit, Maha; Hoteit, Reem; Allehdan, Sabika; Behzad, Nouf; Bookari, Khlood; AlKhalaf, Majid; Al-Sabbah, Haleama; Badran, Eman; Tayyem, ReemaBackground: Maternal depression and anxiety are significant public health concerns that play an important role in the health and well-being of mothers and children. The COVID-19 pandemic, the consequential lockdowns and related safety restrictions worldwide negatively affected the mental health of pregnant and postpartum women. Methods: This regional study aimed to develop a machine learning (ML) model for the prediction of maternal depression and anxiety. The study used a dataset collected from five Arab countries during the COVID-19 pandemic between July to December 2020. The population sample included 3569 women (1939 pregnant and 1630 postpartum) from five countries (Jordan, Palestine, Lebanon, Saudi Arabia, and Bahrain). The performance of seven machine learning algorithms was assessed for the prediction of depression and anxiety symptoms. Results: The Gradient Boosting (GB) and Random Forest (RF) models outperformed other studied ML algorithms with accuracy values of 83.3% and 83.2% for depression, respectively, and values of 82.9% and 81.3% for anxiety, respectively. The Mathew's Correlation Coefficient was evaluated for the ML models; the Naïve Bayes (NB) and GB models presented the highest performance measures (0.63 and 0.59) for depression and (0.74 and 0.73) for anxiety, respectively. The features' importance ranking was evaluated, the results showed that stress during pregnancy, family support, financial issues, income, and social support were the most significant values in predicting anxiety and depression. Conclusion: Overall, the study evidenced the power of ML models in predicting maternal depression and anxiety and proved to be an efficient tool for identifying and predicting the associated risk factors that influence maternal mental health. The deployment of machine learning models for screening and early detection of depression and anxiety among pregnant and postpartum women might facilitate the development of health prevention and intervention programs that will enhance maternal and child health in low- and middle-income countries.Öğe Machine learning techniques for the identification of risk factors associated with food insecurity among adults in Arab countries during the COVID?19 pandemic(BioMed Central, 2023) Qasrawi, Radwan; Hoteit, Maha; Tayyem, Reema; Bookari, Khlood; Al Sabbah, Haleama; Kamel, Iman; Dashti, Somaia; Allehdan, Sabika; Bawadi, Hiba; Waly, Mostafa; Ibrahim, Mohammed O.; The Regional Corona Cooking Survey Group; Polo, Stephanny Vicuna; Al?Halawa, Diala AbuBackground A direct consequence of global warming, and strongly correlated with poor physical and mental health, food insecurity is a rising global concern associated with low dietary intake. The Coronavirus pandemic has further aggravated food insecurity among vulnerable communities, and thus has sparked the global conversation of equal food access, food distribution, and improvement of food support programs. This research was designed to identify the key features associated with food insecurity during the COVID-19 pandemic using Machine learning techniques. Seven machine learning algorithms were used in the model, which used a dataset of 32 features. The model was designed to predict food insecurity across ten Arab countries in the Gulf and Mediterranean regions. A total of 13,443 participants were extracted from the international Corona Cooking Survey conducted by 38 different countries during the COVID -19 pandemic. Results The findings indicate that Jordanian, Palestinian, Lebanese, and Saudi Arabian respondents reported the highest rates of food insecurity in the region (15.4%, 13.7%, 13.7% and 11.3% respectively). On the other hand, Oman and Bahrain reported the lowest rates (5.4% and 5.5% respectively). Our model obtained accuracy levels of 70%-82% in all algorithms. Gradient Boosting and Random Forest techniques had the highest performance levels in predicting food insecurity (82% and 80% respectively). Place of residence, age, financial instability, difficulties in accessing food, and depression were found to be the most relevant features associated with food insecurity. Conclusions The ML algorithms seem to be an effective method in early detection and prediction of food insecurity and can profoundly aid policymaking. The integration of ML approaches in public health strategies could potentially improve the development of targeted and effective interventions to combat food insecurity in these regions and globally.Öğe Machine learning techniques for tomato plant diseases clustering, prediction and classification(IEEE, 2021) Qasrawi, Radwan; Amro, Malak; Zaghal, Raid; Sawafteh, Mohammad; Vicuna Polo, StephannyThe agriculture sector in Palestine faces several challenges that affect the quality of crop yields, including plant diseases. Plant diseases may be caused by bacteria, viruses, and fungus, among others. Early detection and classification of these diseases allow farmers to reduce the instances and control the effect that the disease may have on their crops. Therefore, this study utilizes machine learning models for the clustering, prediction, and classification of tomato plant diseases in Palestine. The study used 3000 smartphone digital images of five tomato plant diseases (Alternaria Solani; Botrytis Cinerea; Panonychus Citri; Phytophthora Infestans; Tuta Absoluta) collected from three districts across the West Bank (Tulkarem, Jenin, and Tubas). The machine learning models used image embedding and hierarchical clustering techniques in clustering, and the neural network, random Forest, naïve Bayes, SVM, Decision Tree, and Logistic regression for prediction and classification. The models’ accuracy was validated in reference to a tomato plant diseases database created by plant pathogens experts. The clustering model provided 7 diseases clustering with an accuracy rate of 70%, while the neural network and logistic regression models reported performance accuracies of 70.3% and 68.9% respectively. The findings demonstrate that the proposed approach provides acceptable accuracy rates in the clustering, detection, and classification of tomato plant disease. Thus, the deployment of machine learning techniques in the agriculture sector might help Palestinian farmers better manage and control tomato diseases.
