Objectives Antibiotic usage has evolved over the years among the Arab population, and it has also gone under misuse resulting in the development of antimicrobial resistance (AMR). Therefore, the current study aimed to address this issue by evaluating the level of knowledge and attitude of Arab population towards antibiotic usage and AMR to develop a pathway to reduce the risk of antibiotic resistance. Methods A cross-sectional study was carried out among Arab population, including 11 countries from the Middle East and North Africa. A validated and translated questionnaire, consisting of 34 questions, was adopted to achieve the study objectives. Two phases of data collection (online and offline) were performed, and SPSS was used for data analysis. Key findings Three thousand three hundred and nineteen participants were successfully recruited, and the mean age was 37.6 ± 11.73. Approximately 63% of participants wrongly answered they should stop antibiotics when they feel better, and 73.3% of them thought antibiotics could treat cold and flu. Nearly half of the respondents indicated that they were uncertain of how antibiotic resistance affects the body (48.1%), and they were unaware if it could affect them or their families (63.1%). While the majority of the respondents were prescribed antibiotics by a doctor, over half of them were not given any advice on how to take them. Our data showed a significant relationship between respondents’ demographic data (e.g. country, age and education) and their knowledge and attitude. Conclusions Participants had poor knowledge of antibiotics and AMR; thus, efforts are needed to conduct health campaigns in public places and create and implement programmes aiming to raise knowledge and awareness of people in the Arab regions. These could aid to curb the risk of antibiotic resistance and increase the chance of successful treatment for infectious diseases.

Background: Estimating stature is of exceptional value in personal identification and the forensic sciences. At the same time, the literature lacks standardized methods for height estimation. Objectives: To estimate the stature of Iraqi individuals based on the morphometric parameters of both hands. Methods: 101 students recruited from Al-Rafidain University College collected data concerning ethnicity, gender, weight, and height and measured fourteen morphometric parameters for each hand, including the hand length (RHL; LHL), palm length (RPL; LPL), hand breadth (RHB; LHB), maximum handbreadth (RHB; LHB), and the length of each finger (RD1,2,3,4,5; LD1,2,3,4,5). A multivariable linear regression is used to predict stature based on the former variables. Results: The sample included males (48.5%) and females (51.5%) aged 18–23 years of Arabic (95%) and Kurdish (5%) ethnicity. The average weight (65.68±1.32) and height (169.52±1.13) were calculated. Regression analysis (accuracy=74.8%, p<0.001) and the male cohort (65%, p<0.001) possessed higher statistical accuracy than females (47.2%, p<0.001). Stature estimation within the total sample and males assumed similarities concerning parameters allocated to both hands that principally included the length of the right hand, right middle finger, left palm, and left little finger. In contrast, females' stature estimation corresponded to morphometric parameters strictly related to the left hand, including the length of the hand, palm, ring finger, and little finger. The results also aligned with the neural network analyses and qualitative data from ChatGPT version 3.5. Conclusion: Multivariable predictive models that are crucial in personal identification for forensic purposes were predicted, such as catastrophic scenarios due to disfiguring accidents, organized crime, and mass graves that frequently occurred in Iraq during the past two decades. Our results could also interest reconstructive hand surgery experts.