Diala Abu Al-Halawa
Biographic Data
| ID | 7804316 |
|---|---|
| NAME | Diala Abu Al-Halawa |
| GIVEN NAMES | Diala Abu |
| FAMILY NAME | Al-Halawa |
| SIGNATURE | AL-HALAWA D A |
| AFFILIATIONS | Al-Quds University |
| ORCID | 0000-0001-5422-9781 |
| VERIFIED | Yes |
| TOTAL WORKS | 7 |
| TOTAL CITATIONS | 0 |
| AUTHOR COUNT | 7 |
| EDITOR COUNT | 0 |
| FIRST PUBLICATION YEAR | 2022 |
| LATEST PUBLICATION YEAR | 2025 |
| H-INDEX | 0 |
Determinants of Child Growth in Palestine (Ages 5–17): A Structural Equation Modeling Approach to Food Insecurity, Nutrition, and Socioeconomic Factors
Background : The growth patterns of children and adolescents are influenced by multiple factors. This study employed structural equation modeling (SEM) to determine the primary factors influencing the growth of Palestinian children and adolescents in the West Bank (WB). Methods : A cross-sectional survey conducted in 2022 in the WB collected data from 1400 households, of which 500 with children aged 5-17 years and were selected for analysis. The …
Investigating the Association between Nutrient Intake and Food Insecurity among Children and Adolescents in Palestine Using Machine Learning Techniques
Food 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…
Machine Learning Approach for Predicting the Impact of Food Insecurity on Nutrient Consumption and Malnutrition in Children Aged 6 Months to 5 Years
This study provides insights into the differential risks for growth issues among children, offering valuable information for targeted interventions and policymaking
Machine learning techniques for identifying mental health risk factor associated with schoolchildren cognitive ability living in politically violent environments
The 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
Machine learning techniques for the identification of risk factors associated with food insecurity among adults in Arab countries during the Covid-19 pandemic
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
Sex disparities in food consumption patterns, dietary diversity and determinants of self-reported body weight changes before and amid the Covid-19 pandemic in 10 Arab countries
Background The COVID-19 pandemic along with its confinement period boosted lifestyle modifications and impacted women and men differently which exacerbated existing gender inequalities. The main objective of this paper is to assess the gender-based differentials in food consumption patterns, dietary diversity and the determinants favoring weight change before and amid the COVID-19 pandemic among Arab men and women from 10 Arab countries. Methods …
The Impact of Covid-19 on Physical (In)Activity Behavior in 10 Arab Countries
Insufficient 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 t…
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Sex disparities in food consumption patterns, dietary diversity and determinants of self-reported body weight changes before and amid the Covid-19 pandemic in 10 Arab countries
Background The COVID-19 pandemic along with its confinement period boosted lifestyle modifications and impacted women and men differently which exacerbated existing gender inequalities. The main objective of this paper is to assess the gender-based differentials in food consumption patterns, dietary diversity and the determinants favoring weight change before and amid the COVID-19 pandemic among Arab men and women from 10 Arab countries. Methods …
The Impact of Covid-19 on Physical (In)Activity Behavior in 10 Arab Countries
Insufficient 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 t…
Machine learning techniques for identifying mental health risk factor associated with schoolchildren cognitive ability living in politically violent environments
The 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
Machine learning techniques for the identification of risk factors associated with food insecurity among adults in Arab countries during the Covid-19 pandemic
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
Investigating the Association between Nutrient Intake and Food Insecurity among Children and Adolescents in Palestine Using Machine Learning Techniques
Food 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…
Machine Learning Approach for Predicting the Impact of Food Insecurity on Nutrient Consumption and Malnutrition in Children Aged 6 Months to 5 Years
This study provides insights into the differential risks for growth issues among children, offering valuable information for targeted interventions and policymaking
Determinants of Child Growth in Palestine (Ages 5–17): A Structural Equation Modeling Approach to Food Insecurity, Nutrition, and Socioeconomic Factors
Background : The growth patterns of children and adolescents are influenced by multiple factors. This study employed structural equation modeling (SEM) to determine the primary factors influencing the growth of Palestinian children and adolescents in the West Bank (WB). Methods : A cross-sectional survey conducted in 2022 in the WB collected data from 1400 households, of which 500 with children aged 5-17 years and were selected for analysis. The …
Environmental health (7 works) · Medicine (7 works) · Agriculture (5 works) · Food security (5 works) · Geography (5 works) · Food insecurity (4 works) · Food Security and Health in Diverse Populations (4 works) · Biology (3 works) · Child Nutrition and Water Access (3 works) · Economics (3 works)