الفهرس 
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Abstract
Prior data on iron deficiency anemia’s (IDA) prevalence and associated risk factors among female university students are scarce in the Egyptian context. This study therefore recruited a sample of female students at the University of Ain Shams, Egypt, to investigate IDA prevalence and risk factors and fill the identified research gap.
A cross-sectional study was conducted on all female students from database of the Nutritional Assessment of Medical Students of Ain Shams University (NAMES-ASU) Project. 850 apparently healthy female students aged between 19 and 24 years during the period of April 2018 and April 2019 was obtained from the database and interviewed. After applying the inclusion and exclusion criteria, and excluding the dropout students, only 83 female students were anemic and fit the criteria then comparative non-anemic female group was selected randomly to conduct a comparative study between those anemic and non-anemic to find out the possible risk factors for iron deficiency anemia among females and develop a prediction score for these risk factors.
Data on the participants’ sociodemographics, diet, health, anthropometry, nutritional status and hematological and biochemical iron status indices were gathered. A logistic regression analysis revealed the most significant IDA risk factors and a prediction score was developed for them.
The IDA prevalence was 11.82%. The risk factors statistically significant with an elevated anemia risk were increased duration of menstruation, increased intake of cooked vegetables, increased intake of stimulant drinks (tea and coffee), decreased intake of processed meat and fresh meat and poultry, decreased intake of white bread with subsequent increased intake of whole grains, decreased intake of vit C, Zn, vit A,Mg,Fe, vit B1,vit B2.
Binary Logistic Multi-Regression analysis was done for Iron Deficiency Anemia and of parameter variables. It showed that Duration of menstruation, RBC, MCH, Cooked vegetables, White bread, Ash, Protein, Fiber, Mg and VitA have predictors and significance of Iron Deficiency Anemia.
Receiver operating characteristics (ROC) curve was used to define the best cut off value of prediction score which was >19, with sensitivity of 77.1% specificity of 64.3% positive predictive value of 68.1%, negative predictive value of 74.3% with diagnostic accuracy of 83.9%.
A prediction score can help us better predict patient’s liability to develop iron deficiency anemia and so improving their dietary habits early to prevent future risk.