Submit manuscript...
MOJ
eISSN: 2374-6939

Orthopedics & Rheumatology

Research Article Volume 14 Issue 4

Trend over six years of incidence of mortality related to road traffic accidents in six cities of the Democratic Republic of the Congo: A retrospective survey in population based

Joachim Ndongila Moba,1 Aliocha Natuhoyila Nkodila,2,3 Luc Bakumobatane Mokassa,1 Mathieu Nkumu Loposso,4 Désiré Kulimba Mashinda,5 Glennie Eba Nsambi,6 Dieudonné Molamba Moningo,4 Anatole Kapay Kibadi, Kibadi,7 Benjamin Longo Mbenza3,8

1Department of orthopedics and traumatology, University of Kinshasa, Democratic Republic of Congo
2Department of Family Medicine and Primary Health Care, Protestant University in Congo, Democratic Republic of Congo
3Department of Public Health, Lomo University of Research, Democratic Republic of Congo
4Department of Urology, University of Kinshasa, Democratic Republic of Congo
5School of Public Health, University of Kinshasa, Democratic Republic of Congo
6Department of Neurosurgery, University of Kinshasa, Democratic Republic of Congo
7Department of Plastic and Reconstructive surgery, University of Kinshasa, Democratic Republic of Congo
8Department of Internal Medicine, University of Kinshasa, Democratic Republic of Congo

Correspondence: Aliocha Natuhoyila Nkodila, Department of Family Medicine and Primary Health Care, Protestant University in Congo, Democratic Republic of Congo, Tel +243812726941

Received: June 15, 2022 | Published: July 1, 2022

Citation: Moba JN, Nkodila AN, Mokassa LB, et al. Trend over six years of incidence of mortality related to road traffic accidents in six cities of the Democratic Republic of the Congo: A retrospective rurvey in population based. MOJ Orthop Rheumatol. 2022;14(4):87-90. DOI: 10.15406/mojor.2022.14.00584

Download PDF

Abstract

Background and objective: Despite the reduction in the risks incurred, obtained thanks to the constant improvement of the road networks, the mortality rate by road accidents had doubled in 20 years in the world. The objective of this study is to evaluate the evolutionary trend of mortality due to road traffic accidents in 6 cities of the Democratic Republic of Congo.

Methods: This was an analytical cross-sectional study of road traffic accident data in 6 cities in the DRC over a period from 2011 to 2016, based on data from the police stations of these 6 cities. It took into account all the accidents on the public highway having been the subject of a report by the police officers. Mortality and injuries due to road accidents were the dependent variables while socio-demographic characteristics, behavioral and environmental determinants were the independent variables.

Results: A total of 4635 road traffic accidents were recorded during 6 years in six cities of the Democratic Republic of Congo. Road traffic accidents evolved linearly over the years with a high frequency in 2016 (1415 cases). The overall incidence of mortality in the six cities was 3.4/100P-Y. This incidence of mortality increased more and more over the wyears, going from 1.6/100PA in 2011 to 5.1/100P-Y in 2016. The incidence of mortality per year and per city, it is noted that mortality increased over the years in each city, with very high and significant mortality in Kinshasa and Lubumbashi.

Conclusion: these data have shown that road traffic accidents increased over the years and the incidence of mortality varied from one city to another.

Keywords: incidence, trend, mortality, road traffic accident, DRC

Introduction

Road accidents pose serious public health problems all over the world. Road fatalities, road accidents and disabilities are among the main concerns in this regard.1 Traffic accidents refer to the number of people who have suffered bodily injuries in a traffic accident. The level of injury or property damage caused by a crash is referred to as “crash severity” in the road safety manual.2 Every year more than 1.25 million people lose their lives in road accidents worldwide. As reported by the World Health Organization (WHO) in 2018, road accidents cost 3% of Gross Domestic Product (GDP) for most countries.3

Studies in developing countries have shown that 85% of deaths and 90% of disabilities are related to road accidents. Accidents are expected to increase by 80% in developing countries.4,5 Therefore, the pattern of road traffic fatalities and injuries in developing countries will be different from that in developed countries, which require dedicated models and strategies to improve the accuracy of predictions.6 In addition, the development of active intervention policies should be implemented as the main factor in reducing TMRs and RTIs.7

Despite the reduction in the risks incurred, obtained thanks to the constant improvement of the road networks, the mortality rate by road accidents had doubled in 20 years in the world.8–11 In a previous study, dealing with the evolution of mortality and morbidity due to traffic accidents, the authors had emphasized the reversal of the trend, thanks to the safety measures taken then and reinforced in favor of the oil crisis.12–16 Without making the road a means of transport or even the road itself in other countries, these measures, taken in a favorable psychological context, had made it possible to reduce by more than a quarter the number of deaths in the "open countryside".1

If in the other countries the reversal and the new security measures had led to a drop in morbidity and mortality linked to road accidents, in the Democratic Republic of the Congo, the trend in this morbidity and mortality from road traffic accidents is not known. The objective of this study is to evaluate the evolutionary trend of mortality due to road traffic accidents in 6 cities of the Democratic Republic of Congo.

Material and methods

Our study took place in 6 cities in the DRC. These are the city of Kinshasa, Goma, Matadi, Mbandaka, Lubumbashi and Kananga. The data was compiled in these different towns by the military service providing roadside checks. These reports of accidents came from two sources: the national police for accidents occurring in urban areas and the gendarmerie for accidents occurring in open country. Accident reports are drawn up by police officers from the autonomous district police stations in the various cities, who first register them at the police station level before transmitting them to the police headquarters, which compiles all the data. This accident data is actively collected by police officers on a weekly basis to collect this data in the registers and retrieve the report sheets.

This was a cross-sectional study for analytical purposes that took place from 2011 to 2016 and focused on road traffic accidents that occurred in the 5 aforementioned cities. The data was obtained from data from the census of all road accidents recorded in different police stations in 6 cities. Before the analysis, these data were cleaned by excluding the variables for which there were many missing data (missing data on the VPs). Were included in the study all the accidents having been the subject of a report by the forces of order.

The variable of interest studied was the occurrence of a fatal road traffic accident. The explanatory variables were:

  1. socio-demographic characteristics (gender, age, season);
  2. the behavioral risk factors of road users (speeding, reckless driving, wrong manoeuvre, bad crossing and drunk driving)
  3. environmental risk factors (time of occurrence of the accident, type of road, road condition, category of machine, type of accident, accidents involving at least one pedestrian, in built-up areas, in open country, accident according to the day of the week, accident according to the type of day, accident according to the month, accident according to the year).

Statistical analyzes

Analyzes were performed on SPSS 21.0. The descriptive statistics consisted in calculating the mean and the standard deviation for the quantitative data and the proportions for the categorical data. Pearson's chi-square or Fisher's exact test was used to compare proportions. The value of p<0.05 was considered as the threshold of statistical significance.

Results

A total of 4635 road traffic accidents were recorded over 6 years in six cities of the Democratic Republic of Congo. The data relating to its distribution are analyzed in the following lines (Table 1).

 Variables

Kinshasa
n=1761

Lubumbashi
n=603

Goma
n=741

Matadi
n=1113

Kananga
n=278

Mbandaka n=139

Age

33.8±16.1

34.2±15.8

33.9±16.2

34.1±15.7

33.6±16.4

35.9±15.5

1-10 years

60(3.4)

17(2.8)

27(3.6)

34(3.1)

9(3.2)

3(2.2)

11-20 years

329(18.7)

105(17.4)

139(18.8)

190(17.1)

60(21.6)

17(12.2)

21-30 years

483(27.4)

169(28.0)

197(26.6)

309(27.8)

71(25.5)

41(29.5)

31-40 years

341(19.4)

125(20.7)

142(19.2)

230(20.7)

46(16.5)

31(22.3)

41-50 years

229(13.0)

76(12.6)

100(13.5)

142(12.8)

41(14.7)

17(12.2)

51-60 years

194(11.0)

66(10.9)

83(11.2)

139(12.5)

32(11.5)

21(15.1)

>60 years

125(7.1)

45(7.5)

53(7.2)

69(6.2)

19(6.8)

9(6.5)

Gender

 

 

 

 

 

 

Male

942(53.5)

321(53.2)

395(53.3)

595(53.5)

155(55.8)

72(51.8)

Female

819(46.5)

282(46.8)

346(46.7)

518(46.5)

123(44.2)

67(48.2)

Season

 

 

 

 

 

 

Rain

1154(65.5)

339(56.2)

509(68.7)

685(61.5)

212(76.3)

56(40.3)

Dried

607(34.5)

264(43.8)

232(31.3)

428(38.5)

66(23.7)

83(59.7)

head and neck

857(48.7)

290(48.1)

362(48.9)

533(47.9)

131(47.1)

77(55.4)

Member and belt

699(39.7)

252(41.8)

285(38.5)

444(39.9)

101(36.3)

74(53.2)

Trunk

927(52.6)

296(49.1)

392(52.9)

571(51.3)

150(54.0)

74(53.2)

Death

349(19.8)

138(22.9)

139(18.8)

226(20.3)

42(15.1)

51(36.7)

Wound

1187(67.4)

405(67.2)

493(66.5)

739(66.4)

184(66.2)

107(77.0)

Fracture

200(11.4)

142(23.5)

87(11.7)

138(12.4)

91(32.7)

39(28.1)

Contusion

177(10.1)

53(8.8)

174(23.5)

141(12.7)

32(11.5)

3(2.2)

Sprain

44(2.5)

11(1.8)

21(2.8)

24(2.2)

10(3.6)

0(0.0)

Polytraumatized

596(33.8)

220(36.5)

248(33.5)

378(34.0)

76(27.3)

77(55.4)

Table 1 General characteristics of the study population

The average age of the population in each province was almost similar, males predominated and most accidents occurred during the rainy season. The death rate was generally high in all provinces.

Frequency of accidents per year per city. The majority of accidents occurred in Kinshasa, followed by Matadi, Goma and Lubumbashi.

Evolution of accidents over the years (Figure 1).

This figure shows that road traffic accidents evolved linearly over the years (Figure 2).

Overall 6-year incidence of mortality in the 6 cities

The incidence of mortality increased more and more over the years, going from 1.6/100P-Y in 2011 to 5.1/100PA in 2016 (Figure 3).

Figure 1 Frequency of accidents per year by city.

Figure 2 Evolution of accidents over the years.

Figure 3 Overall 6-year incidence of mortality in the 6 cities.

Comparing the incidences of mortality by year and by city, we note that mortality increased over the years in each city, with very high and significant mortality in Mbandaka and Lubumbashi (Table 2).

Année

Kinshasa
Ie/100P-Y

Lubumbashi
Ie/100P-Y

Goma
Ie/100P-Y

Matadi
Ie/100P-Y

Kananga
Ie/100P-Y

Mbandaka
Ie/100P-Y

p

2011

6,0

4,1

2,7

2,8

1,2

3,0

0,012

2012

6,0

3,6

1,8

2,4

6,0

3,1

0,001

2013

13,2

6,1

5,2

5,8

2,4

5,3

<0,001

2014

12,0

6,6

6,3

6,6

3,6

6,4

<0,001

2015

9,6

6,6

4,0

5,7

2,4

4,5

<0,001

2016

14,4

11,1

11,2

10,5

9,6

10,6

0,159

Table 2 Comparison of mortality incidences by city by year
Comparing the incidences of mortality by year and by city, we note that mortality increased over the years in each city, with very high and significant mortality in Kinshasa and Lubumbashi.

Discussion

The number of accidents has a considerably increasing trend over the years, going from 435 in 2011 to 1415 in 2016, probably due to non-enforcement of the traffic code and the harassment of police officers from the traffic on the roads as well as the lack of road safety campaigns by the national road safety council.17 When interpreting this data, it should be noted that the DRC, like many other developing countries, does not have a reliable unified real-time system at the national level for recording injuries or reporting systems to a later stage. For example, the World Health Organization in its Global Road Safety Report18 classifies the DRC as a country with no eligible death registration data. Research shows that for every traffic fatality, at least 20 people sustain non-fatal injuries.19 So the numbers in the traffic police data would be much higher. The results of this study are consistent with those of other published reports which have shown that there is an overall increase in road traffic accidents in the African region or globally.18,20 Other reports indicate that there are countries that have actually succeeded in reducing the number of road traffic accidents, although this is not always the case.21, 22

Mortality in the 6-year-old set has also increased and in each city as well. We observed a very high incidence of mortality in Kinshasa compared to other cities. This high incidence should challenge the authorities of the city of Kinshasa in order to find the causes of this high incidence compared to other cities in the country. If we refer to the data, such as the recent report by Kazeem,23 it can be seen that the mortality rates due to road traffic accidents in sub-Saharan Africa are always similar and evolve in the same way. This exponentially increasing mortality could be explained in our context by variations in traffic intensity. This can be seen by relating the latter to the monthly estimates of the number of vehicle-km traveled on the network of national roads and motorways. We find the general trend (indicated by the annual figures) of an increase in the risk incurred per km travelled. This increase is due to the constant improvement of the road network which allows drivers to drive at high speed without controlling their speed.

Limitations of the study

Despite its local character, facilitating access to data, this study has some limitations. Biases in the reporting of data on accidents due to the refusal of a report by some users (amicable report) or the unavailability of the agents responsible for the reports, which meant that certain aspects were not addressed.

Conclusion

The intensification of road traffic in the DRC over the past six years in the 6 cities of the DRC, generates an exponential increase in the number of accidents and incidence of mortality in the 6 cities of the study. This documentary study, which consisted of a census of road accidents over a period of six years in six cities of the DRC, made it possible to show that, on the one hand, road traffic accidents increased over the years.

Declaration

Ethics approval and consent to participate

The study protocol was approved by National Ethics Committee of the DRC (n°343/CNES/BM/PMMF/2022). The study has been performed in accordance with the ethical standards laid down in the 1964 Declaration of Helsinki and its later amendments. Written informed consent was requested from the people at the beginning of the study. The informed consents included that data from the participants can be published in scientific journals in an anonymized format in which individual responses never are made visible or possible to identify.

Consent for publication

This is not an experimental study but a transversal study and hence, no separate consent for publication is needed.

Availability of data and materials

The data the study is based on contains personal and intimate information that according to initial agreements with the participants from the start of the study cannot be transferred to third parties or outside the borders of Lubumbashi. Theoretically some subsets of data could on reasonable request be delivered but unfortunately, in most cases it probably would be evaluated as not possible along with this. The datasets used and analyzed during the current study are available from the corresponding author on reasonable request: nkodilaaliocha@gmail.com

Conflicts of interest

The authors declare no conflict of interest.

Funding

This research received no external funding.

Acknowledgments

We thank all who participated in the study.

Author’s contributions

JMN and ANN designed and analyzed the statistical data for the study. MLN, DMK, LMB, GN, AKK, DMB and LMB supervised the study. All authors have read and approved the final and revised version of the manuscript.

References

  1. WHO. Global status report on road safety:time for action. WHO; 2009.
  2. Bonneson JB. The highway safety manual (HSM), Washington DC: american association of state highway and transportation officials; 2014.
  3. WHO. Fact Sheet: WHO; 2018.
  4. Kopits E, Cropper M. Traffic fatalities and economic growth. Accident Analysis Prevention. 2005;37(1):169–178.
  5. WHO. World health statistics 2008. Geneva. WHO; 2008.
  6.  Zhang X, Pang Y, Cui M, et al. Forecasting mortality of road traffic injuries in China using seasonal autoregressive integrated moving average model. Annals of Epidemiology. 2015;25(2):101–106.
  7. Bru¨de U, Elvik R. The turning point in the number of traffic fatalities: twohypotheses about changes in underlying trends. Accident Analysis and Prevention. 2015;74:60–68.
  8. Linthicum KJ, Anyamba A, Tucker CJ, et al. Climate and satellite indicators to forecast Rift Valley fever epidemics in Kenya. Science. 1999;285(5426):397–4000.
  9. Nobre FF, Soares Monteiro AB, Telles PR, et al. Dynamic linear model and SARIMA: a comparison of their forecasting performance in epidemiology. Statistics in medicine. 2001;20(20):3051–3069.
  10. Hu W, Tong S, Mengersen K, et al. Weather variability and the incidence of cryptosporidiosis: comparison of time series Poisson regression and SARIMA models. Ann Epidemiol. 2007;17(9):679–688.
  11. Weisent J, Seaver W, Odoi A, et al Comparison of three time-series models for predicting campylobacteriosis risk. Epidemiol Infect. 2010;138(6):898–906.
  12. Jere S, Moyo E. Modelling Epidemiological Data Using Box-Jenkins Procedure. Open Journal of Statistics. 2016;6:295–302.
  13. Bahadorimonfared A, Soori H, Mehrabi Y, et al. Trends of Fatal Road Traffic Injuries in Iran (2004–2011). PLoS ONE. 2013;8(5):e65198.
  14. Choi K, Thacker SB. An evaluation of influenza mortality surveillance, 1962–1979. I. Time series forecasts of expected pneumonia and influenza deaths. Am J Epidemiol. 1981;113(3):215–226.
  15. Que´nel P, Dab W. Influenza A and B epidemic criteria based on timeseries analysis of surveillance data. European Journal of Epidemiology. 1999;14(3):275–285.
  16. Ganguly KS, Modak S, Chattopadhyay AK, et al. Forecasting Based On a SARIMA Model of Urban Malaria for Kolkata. American Journal of Epidemiology and Infectious Disease. 2016;4(2):22–33.
  17. Fell M, Jones A, Mallow P, et al. Improvement of Road Safetyin Tanzania Mainland (No. 4). Surface and Marine Transport Regulatory Authority (SUMATRA), Denmark. 2017.
  18. WHO. Global status report on road safety. WHO. 2013.
  19. Save LIVES - a road safety technical package. Geneva: World Health Organization. 2017. Licence: CC BY-NC-SA 3.0iGO. 
  20. Toroyan T, Peden MM, Laych K. WHO launches second global status report on road safety. Inj Prev. 2013;19(2):150. 
  21. Hughes BP, Newstead S, Anund A, et al. A review of Models Relevant to Road Safety. Accid Anal Prev. 2015;74:250–270. 
  22. Steininger KW, Bachner G. Extending car-sharing to serve commuters: animplementationin Austria. Ecol Econ. 2014;101:64–66. 
  23. Kazeem. Average of 12 people died daily in 2019 road accidents across Nigeria - FRSC. 2019.
Creative Commons Attribution License

©2022 Moba, et al. This is an open access article distributed under the terms of the, which permits unrestricted use, distribution, and build upon your work non-commercially.