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Prevalence and risk factor for injury in sub-Saharan Africa: a multicountry study
Megan B Diamond1, Shona Dalal1, Clement Adebamowo2,3
1Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, USA.
Introduction:
Injury-related morbidity is a neglected health concern in many low-income and middle-income countries. Most injury data in Africa have been collected from hospital-based studies, and few studies have occurred across multiple countries. Using data from a novel cohort, we examined the prevalence and incidence of serious injuries and associated risk factors across five sites in sub-Saharan Africa (SSA).
Methods:
A common baseline and follow-up survey was administered to participants. The study population included 1316 persons at baseline and 904 persons at follow-up. Frequencies were calculated, and logistic regression models were used to assess risk factors for injury.
Results:
A total of 233 (17.7%) persons reported a serious injury at baseline and 60 (6.6%) reported a serious injury 6 months later at follow-up. Sixty-nine per cent of participants responded to the follow-up questionnaire. At baseline and follow-up, the most common cause of serious injury at urban sites was transport related, followed by poison/overdose. In rural Uganda, sharp instruments injuries were most common, followed by transport-related injuries. Living at an urban site was associated with an increased odds for serious injury compared with those at the rural site (OR: 1.83, 95% CI 1.15 to 2.90). Participants who consumed above a moderate amount of alcohol were at a higher risk of serious injury compared with those who did not consume alcohol (OR: 1.86, 95% CI 1.02 to 3.41). High level of education was an important risk factor for injury.
Conclusion:
At baseline and follow-up, common causes of serious injury were transport related, sharp instrument and poison/overdose. Alcohol consumption, urban location and education are important risk factors for injury. It is feasible to collect longitudinal injury data using a standardised questionnaire across multiples sites in SSA. Longitudinal data collection should be leveraged to obtain robust data on risk factors for injury in SSA.
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