Forensic Assessment of Alcohol-Related Deaths among Road Users in Nairobi: Implications for Public Safety and Policy

Authors

Wangai Kiama

Department of Pathology, Egerton University, Egerton-Njoro (Kenya)

FRC PATH

Department of Pathology, Egerton University, Egerton-Njoro (Kenya)

Article Information

DOI: 10.51244/IJRSI.2025.1210000223

Subject Category: Medicine

Volume/Issue: 12/10 | Page No: 2574-2581

Publication Timeline

Submitted: 2025-10-18

Accepted: 2025-10-28

Published: 2025-11-15

Abstract

Background: Road traffic accidents (RTAs) are a significant public health challenge globally, especially in low- and middle-income countries, where they contribute to high rates of injury and death. Alcohol consumption is a major risk factor for RTAs, impairing driving skills like judgment and reaction time. While much of the research has focused on drivers, other vulnerable road users such as passengers, pedestrians, and cyclists remain underexplored. This study investigates the prevalence of alcohol in RTA fatalities across different road user categories in Nairobi, Kenya, using forensic postmortem toxicological analysis.
Methods: A cross-sectional study analyzed 100 RTA fatalities from the City Mortuary in Nairobi between January and March 2007. Postmortem vitreous humour samples were tested for alcohol using standard forensic techniques. After excluding five cases with potential postmortem ethanol formation, 95 valid samples were analyzed. Victims were categorized into four road user groups: drivers, passengers, pedestrians, and cyclists. Alcohol presence and demographic factors were examined to assess prevalence patterns.
Results: Among the 95 valid cases, 15 (15.8%) tested positive for alcohol. Males comprised 66.7% (n = 10) of alcohol-positive victims. A Chi-square test showed a significant gender difference in alcohol positivity (χ² = 4.45, p = 0.035), with males more likely to test positive. Passengers had the highest alcohol positivity rate (46.7%), followed by pedestrians and cyclists (20% each), and drivers (13.3%). ANOVA revealed a significant difference in alcohol prevalence across road user groups (F = 6.81, p = 0.001). Among intoxicated individuals, 57% of passengers and all alcohol-positive pedestrians showed severe intoxication. The highest blood alcohol concentration was 0.52 g% in a pedestrian. Logistic regression found that age was not a significant predictor (p = 0.267), but gender remained significant.

Keywords

Road traffic accidents, alcohol-related deaths, postmortem toxicology, vitreous humour

Downloads

References

1. Adeloye, D., Basquill, C., & Aderemi, A. V. (2016). Estimates of mortality from road traffic injuries in Sub-Saharan Africa: A systematic analysis. plos one, 11(10), e0163474. (https://doi.org/10.1371/journal.pone.0163474] (https://doi.org/10.1371/journal.pone.0163474) [Google Scholar] [Crossref]

2. Aldred, R., & Jungnickel, K. (2014). Gender and cycling. In Cycling and Society (pp. 133-152). Edward Elgar Publishing. [Google Scholar] [Crossref]

3. Drummer, O. H. (2004). Postmortem toxicology of alcohol and drugs. Forensic Science International, 142(1), 99-109. [https://doi.org/10.1016/j.forsciint.2004.04.004] (https://doi.org/10.1016/j.forsciint.2004.04.004) [Google Scholar] [Crossref]

4. Hunter, M., Sloane, S., & Rattenbury, R. (2015). Forensic toxicology: Postmortem ethanol and microbiological contamination. Journal of Forensic Sciences, 60(1), 66-71. [https://doi.org/10.1111/1556-4029.12640] (https://doi.org/10.1111/1556-4029.12640) [Google Scholar] [Crossref]

5. Hyder, A. A., Peden, M., & Racioppi, F. (2017). The Global Status Report on Road Safety 2015. World Health Organization. [https://www.who.int/publications/i/item/9789241565060] (https://www.who.int/publications/i/item/9789241565060) [Google Scholar] [Crossref]

6. NACADA (National Authority for the Campaign Against Alcohol and Drug Abuse). (2022). National survey on alcohol and drug use in Kenya 2021. Nairobi: NACADA. [https://www.nacada.go.ke] (https://www.nacada.go.ke) [Google Scholar] [Crossref]

7. Odero, W., Khayesi, M., & Heda, P. M. (1997). Road traffic injuries in Kenya: Magnitude, patterns and trends. Injury Control and Safety Promotion, 4 (1), 41-48. [https://doi.org/10.1080/15660979708403993] (https://doi.org/10.1080/15660979708403993) [Google Scholar] [Crossref]

8. Peltzer, K., & Phaswana-Mafuya, N. (2018). Prevalence and risk factors of alcohol use and abuse in South Africa. South African Journal of Psychiatry, 24(1), 1-8. [https://doi.org/10.4102/sajpsychiatry.v24i1.1185] (https://doi.org/10.4102/sajpsychiatry.v24i1.1185) [Google Scholar] [Crossref]

9. Pfeiffer, R. M., & Meyer, P. M. (2005). Postmortem alcohol detection: Contamination and the need for accurate testing. Forensic Science Review, 17(1), 31-38. [https://doi.org/10.1007/s00414-005-0617-2] (https://doi.org/10.1007/s00414-005-0617-2) [Google Scholar] [Crossref]

10. Peden, M., Scurfield, R., Sleet, D., Mohan, D., & Hyder, A. A. (2004). World report on road traffic injury prevention. World Health Organization. [https://www.who.int/publications/i/item/world-report-on-road-traffic-injury-prevention] (https://www.who.int/publications/i/item/world-report-on-road-traffic-injury-prevention) [Google Scholar] [Crossref]

11. Siliquini, R., Ghisi, M., & Milioto, S. (2011). Pedestrians and alcohol: Risk analysis of accidents in an urban area. Traffic Injury Prevention, 12(1), 80-83. [https://doi.org/10.1080/15389588.2010.530186] (https://doi.org/10.1080/15389588.2010.530186) [Google Scholar] [Crossref]

12. WHO (World Health Organization). (2018). Global status report on road safety 2018. Geneva: World Health Organization. [https://www.who.int/publications/i/item/9789241565688] (https://www.who.int/publications/i/item/9789241565688) [Google Scholar] [Crossref]

13. Zador, P. L., Krawchuk, S. A., & Voas, R. B. (2000). Alcohol-related crashes: The role of alcohol-impaired drivers in the fatalities of non-drivers. Accident Analysis & Prevention, 32(6), 745-752. [https://doi.org/10.1016/S0001-4575(00)00047-4] (https://doi.org/10.1016/S0001-4575%2800%2900047-4) [Google Scholar] [Crossref]

Metrics

Views & Downloads

Similar Articles