Identification of determinant factors for crash severity levels occurred in Addis Ababa City, Ethiopia, from 2017 to 2020: using ordinal logistic regression model approach.

BACKGROUND: Road traffic Injuries (RTI) are multifaceted occurrences determined by the combination of multiple factors. Also, severity levels of injuries from road traffic accidents are determined by the interaction of the composite factors. Even though most accidents are severe to fatal in developing countries, there is still a lack of extensive researches on crash severity levels and factors associated with these accidents. Hence, this study was intended to identify severity levels of road traffic injuries and determinant factors in Addis Ababa City, Ethiopia. METHODS: The study was conducted in Addis Ababa, the capital city of Ethiopia, using secondary data obtained from the Addis Ababa Police Commission office. The ordinal logistic regression model was used to investigate road traffic injury severity levels and factors worsening injury severity levels using the recorded dataset from October 2017 to July 2020. RESULTS: A total of 8458 car accidents were considered in the study, of which 15.1% were fatal, 46.7% severe, and 38.3% were slight injuries. The results of the ordinal logistic regression analysis estimation showed that being a commercial truck, college and above level educated driver, rollover crash, motorbike passengers, the crash day on Friday, and darkness were significantly associated factors with crash injury severity levels in the study area. On the contrary, driving experience (> 10 years), passenger of the vehicle, two-lane roads, and afternoon crashes were found to decrease the severity of road traffic injuries. CONCLUSIONS: Road traffic injury reduction measures should include strict law enforcement in order to maintain road traffic rules especially among commercial truckers, motorcyclists, and government vehicle drivers. Also, it is better to train drivers to be more alert and conscious in their travels, especially on turning and handling their vehicles while driving.

Evaluation of the Amharic version of the London measure of unplanned pregnancy in Ethiopia.

BACKGROUND: Unplanned pregnancy is an important public health problem in both the developing and developed world, as it may cause adverse social and health outcomes for mothers, children, and families as a whole. London Measure of Unplanned Pregnancy (LMUP) has been formally and informally validated in multiple and diverse settings. However, there is a dearth of literature on the validation of LMUP in Ethiopia either in the Amharic version or other languages. OBJECTIVE: The general objective of this study was to translate the LMUP into Amharic and evaluate its psychometric properties in a sample of Amharic-speaking women receiving antenatal care (ANC) service at public health facilities in Arbaminch and Birbir towns. METHODS: A cross-sectional study design was used for the study. Forward and backward translation of original English LMUP to Amharic was done. A cognitive interview using a pretested structured questionnaire was used to collect the data from respondents. The collected data was analyzed using SPSS version 25. Reliability was assessed using Cronbach's alpha, inter-item correlations, and corrected item-total correlations while construct validity was assessed using principal components analysis and hypothesis testing. RESULTS: Data was collected from 320 women attending antennal care services at selected public health care facilities. LMUP range of 1to 11 was captured. The prevalence of unplanned pregnancies was 19(5.9%), while 136(42.5 were ambivalent and 165(51.6%) were planned pregnancies. The reliability testing demonstrated acceptable internal consistency (Cronbach's alpha = 0.799) and the validity testing confirmed the unidimensional structure of the scale. In addition, all hypotheses were confirmed. CONCLUSIONS: Amharic version of LMUP is a valid and reliable tool to measure pregnancy intention so that it can be used by Amharic speaking population in Ethiopia. It can also be used in research studies among Amharic-speaking women to measure unplanned pregnancy.