Back

External Causes of Death in Sulaymaniyah City in 2022

Rasul, K. S.; Hassan, H. R.; Abdalla, E. F.; Hamaamin, L. F.; Ahmed, S. J.; Reza, X. O.; Tahir, F. F.; Faraj, P. O.

2025-01-27 public and global health
10.1101/2025.01.25.25321120 medRxiv
Show abstract

BackgroundExternal causes of death like injuries, violence, and accidents have a great impact on population and depletion of health resources. Accurate and precise data on external causes is important for informing public health policies. This study analyzed the most common external causes of death in Sulaymaniyah city during 2022 and examined characteristics of the deceased individuals. MethodsThis cross-sectional study included 499 cases of death from external causes in Sulaymaniyah in the year 2022. These data were obtained from the Medico-Legal Institute. Descriptive statistics, cross-tabulations, and chi-square tests were performed to find out common causes, sex differences, and age patterns. ResultsOut of 499 cases, road traffic accidents (36.1%) were the most common cause, followed by burn injuries (17.2%) and gunshot wounds (16.8%). Males predominated with a 2.4:1 ratio over females. Road accidents were more common among males, while burn injuries were higher in females. All age-groups were affected mainly by road traffic accidents, and the age group of 25-44 years was most affected. Burn injuries and gunshot wounds were prevalent causes across age-groups 15-44. ConclusionRoad traffic accidents, burn injuries, and gunshot wounds were the major external causes of death in Sulaymaniyah in 2022, with distinct sex and age patterns. Findings suggest prompt needs for improving road safety, applying burn prevention strategies, and planning interventions for vulnerable groups to reduce this preventable mortality burden

Matching journals

The top 3 journals account for 50% of the predicted probability mass.

50% of probability mass above

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.