The neglected epidemic-Risk factors associated with road traffic injuries in Mozambique: Results of the 2016 INCOMAS study

Abstract

In 2019, 93% of road traffic injury related mortality occurred in low- and middle-income countries, an estimated burden of 1.3 million deaths. This problem is growing; by 2030 road traffic injury will the seventh leading cause of death globally. This study both explores factors associated with RTIs in the central region of Mozambique, as well as pinpoints geographical "hotspots" of RTI incidence. A cross-sectional, population-level survey was carried out in two provinces (Sofala and Manica) of central Mozambique where, in addition to other variables, the number of road traffic injuries sustained by the household within the previous six months, was collected. Urbanicity, household ownership of a car or motorcycle, and socio-economic strata index were included in the analysis. We calculated the prevalence rate ratios using a generalized linear regression with a Poisson distribution, as well as the spatial prevalence rate ratio using an Integrated Nested Laplace Approximation. The survey included 3,038 households, with a mean of 6.29 (SD 0.06) individuals per household. The road traffic injury rate was 6.1% [95%CI 7.1%, 5.3%]. Urban residence was associated with a 47% decrease in rate of injury. Household motorbike ownership was associated with a 92% increase in the reported rate of road traffic injury. Higher socio-economic status households were associated with a 26% increase in the rate of road traffic injury. The rural and peri-urban areas near the "Beira corridor" (national road N6) have higher rates of road traffic injuries. In Mozambique, living in the rural areas near the "Beira corridor", higher household socio-economic strata, and motorbike ownership are risk factors for road traffic injury.

Fig 1. Prevalence risk ratio of having someone in the household injured by a road traffic injury in the last 6 months.

Fig 2. Map of prevalence rate ratio of road traffic injuries in Sofala and Manica, Mozambique 2017.

We sourced United Nations maps for the Mozambique map, and World Bank maps for Mozambique roads. The maps were created in R using the packages tidyverse (ggplot2), sf, and Maps. To our best knowledge all the materials used are open source.