Payam Roshanfekr; Mohammad-Reza Khodaie-Ardakani; Hossein Malek Afzali Ardakani; Homeira Sajjadi
Volume 7, Issue 1 , January 2019, , Pages 60-66
Abstract
Objective: To determine the prevalence and socio-economic disparity among victims with disabilities caused by RTAs in Iran as country with a high rate of accidents.Method: The source of data was the Iranian Multiple Indicator Demographic and Health Survey, a nationwide cross-sectional study. The ...
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Objective: To determine the prevalence and socio-economic disparity among victims with disabilities caused by RTAs in Iran as country with a high rate of accidents.Method: The source of data was the Iranian Multiple Indicator Demographic and Health Survey, a nationwide cross-sectional study. The sampling framework was based on the population and housing census for Iran in 2006. Provincial samples ranged from 400 to 6,400 households. The target sample was 3,096 clusters consisting of 2,187 urban and 909 rural clusters. In the present study, all but a few indicators are reported at provincial levels. Mortality indicators, accident and disability rates, low birth weight rate and young age at marriage rates are presented at the national level only. Logistic regression was performed to investigate the individual and family factors influencing RTAs that lead to disability in Iran.Results: The period prevalence (12 months) of road traffic accident disabilities (RTADs) in the total population of 111415 was 30.52 (95% CI: 21.13.41.64) per 100,000 individuals. Among those who had been injured during the year leading up to the study, the proportion of disabilities caused by RTAs was 31.67 (95% CI; 8.51.54.97) per 1000 pedestrians, 20.99 (95% CI: 13.37.30.75) per 1000 motorcyclists, 18.64 (95% CI: 7.71.29.57) per 1000 vehicle drivers. Multivariate logistic regression analysis showed that the risk of RTADs differed significantly in relation to age (AOR 50-59 vs. 0-9=10. 78, p-value:0.05); activity status (AOR unemployed vs. employed=4.72, p-value:0.001) and family income (AOR q2 vs. q1=0.37, p-value:0.048) of the victim.Conclusion: In addition to the risks associated with socio-economic groups, particularly vulnerable groups, RTADs have consequences which can lead to further marginalization of individuals, can affect their quality of life and damage the community as a whole.
Mahnaz Yadollahi; Narges Rahmanian; Kazem Jamali
Volume 6, Issue 4 , October 2018, , Pages 349-354
Abstract
Objective: To determine the indicators predicting the hospital mortality in pedestrian injured patients admitted to a level I trauma center in Southern Iran.Methods: This case control study was conducted in a Level-I trauma hospital in Shiraz. We selected all survived pedestrians who were admitted in ...
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Objective: To determine the indicators predicting the hospital mortality in pedestrian injured patients admitted to a level I trauma center in Southern Iran.Methods: This case control study was conducted in a Level-I trauma hospital in Shiraz. We selected all survived pedestrians who were admitted in the hospital with duration of admission more than 24 hours in one year from March 2016 to February 2017 as control group and compared with all non-survived pedestrian patients who expired in the hospital according to clinical from March 2012 to February 2017. Multiple logistic regression was performed to identify factors of hospital effect on pedestrian mortality and results expressed by Odds Ratios and their confidence intervals (CI) of 95%.Results: A total of 424 survived pedestrian injured patients were compare to 117 non-survived one. Their mean of survived and non-survived patients were 43.79 ± 19.37 and 56.76 ± 18.55 years respectively of which 361 (66.7%) and 180 (33.3%) were men and women, respectively. We found that the gender does not have any relation with hospital mortality (p=0.275). Followed by, age is in relevance with mortality. Glasgow Coma Scale(GCS), Injury Severity Score (ISS), blood urea nitrogen (BUN), platelet (PLT), potassium (K) and hemoglobin (Hb) are significant factor which are associated with mortality. According to logistic analysis GCS ≤8 (p
