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| BRIEF RESEARCH ARTICLE |
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| Year : 2021 | Volume
: 65
| Issue : 2 | Page : 203-205 |
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Epidemiological profiling of fatal road crashes in Puducherry, South Coastal India
N Anand1, Biju Soman2, Manivel Prakash3
1 PhD Scholar (Health Sciences), Achutha Menon Centre for Health Sciences Studies, Sree Chitra Tirunal Institute for Medical Sciences and Technology, Thiruvananthapuram, Kerala, India
2 Professor and Associate Dean (Health Sciences), Achutha Menon Centre for Health Sciences Studies, Sree Chitra Tirunal Institute for Medical Sciences and Technology, Thiruvananthapuram, Kerala, India, India
3 Assistant Professor, Department of Community Medicine, Indira Gandhi Medical College and Research Institute, Puducherry, India
| Date of Submission | 13-Dec-2020 |
| Date of Decision | 28-Jan-2021 |
| Date of Acceptance | 30-Mar-2021 |
| Date of Web Publication | 14-Jun-2021 |
Correspondence Address:
N Anand
Achutha Menon Centre for Health Sciences Studies, Sree Chitra Tirunal Institute for Medical Sciences and Technology, Thiruvananthapuram, Kerala
India
 Source of Support: None, Conflict of Interest: None  | Check |
DOI: 10.4103/ijph.IJPH_1436_20
 Abstract | | |
Road crash fatalities form leading cause of deaths in India. Streamlining road crash data systems are essential for building robust prevention strategies. This study explores epidemiological profile of fatal road crashes in a south Indian urban setting. Between April and June 2019, secondary data on fatal road crashes in Puducherry district for 3-year period (2016, 2017, and 2018) were accessed from traffic police records and analyzed. Raw data accessed in descriptive format was converted to analyzable objective format by self-developed data extraction template. 154 fatal crashes happened in Puducherry during this period. Most victims were males (85.7%), in productive age group (41.5%), with higher rates in monsoon and winter seasons (35.1% each), during evening-to-night hours (41.6%), and during weekends (42%). Most offenders (91.2%) were men, elder than victims, with heavy motor vehicles (91.2%) being the culprit vehicle. Rash driving led to most deaths (53.2%).
Keywords: Epidemiology, fatal crashes, profile, road traffic
How to cite this article:
Anand N, Soman B, Prakash M. Epidemiological profiling of fatal road crashes in Puducherry, South Coastal India. Indian J Public Health 2021;65:203-5 |
How to cite this URL:
Anand N, Soman B, Prakash M. Epidemiological profiling of fatal road crashes in Puducherry, South Coastal India. Indian J Public Health [serial online] 2021 [cited 2023 Mar 26];65:203-5. Available from: https://www.ijph.in/text.asp?2021/65/2/203/318361 |
Road crashes are a significant public health problem, causing 1.5 million deaths and 5 million injuries annually worldwide. In spite of many control measures adopted, fatalities continue to rise, especially in low- and medium-income countries which account for 90% of all road traffic casualties.[1] Road crash fatalities, presently the seventh leading cause of mortality worldwide, are expected to become the third leading cause by 2030, if present trends continue. Approximately 1.5 lakh deaths and 4.5 lakh injuries annually result from road crashes in India. “Vulnerable road users,” i.e., pedestrians, cyclists, and two-wheeler users, bear the brunt of fatalities.[2] This calls for radical change in preventive strategies.
The focus of road safety strategies is changing from Haddon's matrix, to “Safe Systems Approach,” which considers people's vulnerability to serious injuries in road crashes. Therefore, systems and processes must be designed to be forgiving of human error. While crashes cannot be completely eradicated, postcrash deaths are preventable. In this approach, data system management is oriented around objective, action-oriented models for operational and translational usage.[3] Studies exploring the major epidemiological features of road crashes under a single gamut will enrich road safety data systems.
This study aimed to create epidemiological profile of fatal road crashes in an urban south Indian setting. Fatal road crash was defined as “Any road traffic crash resulting in a person killed immediately or dying within 30 days as a result of the crash.” Epidemiological profile was defined as “outline description of epidemiological facets (frequency, distribution, determinants, and preventive modalities) of a public health problem, to aid in prioritization of interventions and provide policy guidance for stakeholders."
A cross-sectional study was carried out between April and June 2019, wherein traffic police records of all fatal road crashes under South Traffic Police Station, Puducherry, over 3-year period (2016, 2017, and 2018) were analyzed. These raw data were mainly in alpha-numeric format/descriptive terms and had many variables related to road crash epidemiology. Data extraction template was applied onto these data, wherein it was converted into analyzable/objective format. Epidemiological profile of fatal road crashes in the setting was analyzed subsequently using this objective format.
Ethical clearance from the Institutional Ethics Committee of research institute and administrative approval for access to records from concerned authorities in study setting were obtained. Confidentiality of study participants was maintained, since only anonymized records were analyzed. Data were entered in MS Excel and analyzed using R software.
A total of 154 fatal road crashes occurred under jurisdiction of South Traffic Police station from 2016 to 2018. Maximum deaths (56) took place in 2017. Most victims were males (85.7%). Predominant proportion of deaths (41.5%) was in productive age group (16–45 years), while children and adolescents <15 years formed the smallest age group (4.5%) of victims. Mean age of alleged offenders (32.6 years, standard deviation [SD]: 9.9 years) was less than that of victims (48.3 years, SD: 18.2 years). Age of victims ranged from 7 years (youngest) to 80 years (eldest) while that of alleged offenders ranged from 17 to 56 years.
Monsoon and winter seasons witnessed equal share of fatalities (35.1% each). Most fatal crashes happened in evening-to-night hours (41.6%), with least in morning hours. Most fatal crashes (42.3%) took place in weekends, followed by week beginning (30.6%); middle days of a week (Wednesday, Thursday, and Friday) witnessed 27.1% of all fatal crashes.
Most victims (98.7%) were vulnerable road users, i.e., pedestrians and two and three-wheeler users. Pillion riders (85.6%) formed the largest group of victims as per vehicle occupancy distribution. 91.2% of alleged offenders were men (91.2%). Offending vehicle data were available for 126 fatal road crashes; of which nearly two-fifths (39.7%) were due to heavy motor vehicles, while more than one-third (34.1%) were caused by two wheelers. Nearly, two-fifths (40.3%) of offenders were in middle age group (31–45 years) while under one-third (31.2%) proportion were in 16–30-year age group. [Table 1] and [Table 2] depict epidemiological profile of fatal road crashes both of victims and alleged offenders. | Table 2: Epidemiological profile of alleged offenders in fatal road crashes
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Rash driving was the most important risk factor, being the cause in 82 out of 154 fatal crashes. More than three-fourths (79.0%) of this subgroup were due to rashness on part of the victims themselves. Overspeeding (43.3%) and negligent driving, i.e., not following rules (25.2%), were subdeterminants among this factor that led to most deaths. Nearly, one-third (32.2%) of fatalities resulted from victims not wearing helmet at the time of crash. Minor risk factors included no streetlight and speed breaker (1% each). 3% of road crash deaths were due to combination of rash driving while not wearing helmet.
Puducherry district, located in South coastal India, with a total population of nearly 9.5 lakhs is the largest of the four districts of Puducherry (union territory). Its traffic jurisdiction is divided into four zones: North, East, South, and West. We analyzed data from South Traffic PS as a representative sample. Study finding of male preponderance in fatal crashes is substantiated by many official reports and earlier studies on the participant, with males comprising 74.4%–90% of accident victims. On an average, males were 5.7 times more commonly involved than females in such fatal crashes. This could be due to more outdoor activity practices of males as compared to females.
Mean age of the victims in the present study was 32.6 years, a finding broadly validated by official reports.[4] However, few studies pegged the mean age of victim either higher[5] or lower.[6] Younger age has the risk-taking tendency which could be the probable explanation for this.
The present study found pillion riders formed the largest group of victims as per vehicle occupancy distribution, with 85.6% fatalities. Few studies support these findings,[5],[7] whereas other studies have found that drivers are more affected as compared to pillion riders.[6],[7] The current study observed that nearly two-fifths (39.7%) of the offending vehicle were due to heavy motor vehicles, which is similar to other study findings.[5],[7],[8] Misra et al. found that majority of the victims' vehicle was motorized 2 wheeler (53.4%) and the offending vehicle was four wheeler (39.3%).[7] This finding is very important as such impact could be very fatal.
Studies in variegated settings such as New Delhi, Himachal Pradesh, and Andhra Pradesh found results similar to this study, with respect to both timings and days of fatal road crashes, i.e., between late afternoon and evening until night, and more on weekends, respectively.[6],[8],[9] This is the time when vehicular congestion would be high in the city. This may also be expected since Puducherry is one of the popular tourist destination sites, especially for people from neighboring districts and states of Tamil Nadu, Kerala, Karnataka, and Andhra Pradesh, especially in weekends.
Overspeeding and rash driving, risk factors identified by this study, are also flagged as prime determinants by other reports.[2],[4] Helmet use and seat belt use were found to be low in several studies.[5],[8],[9] Human factor as the most significant determinant (74.2%) in road crashes and injuries thereof (both fatal and nonfatal) is a finding supported by many reports and independent studies on the participant.[4],[6],[9]
The findings indicate need for proper implementation of road traffic regulations and creating awareness among drivers and pillion riders. Two features are unique to this study. They are: Firstly, comparison of age profile of victim with offender. Secondly, comparison of transport mode (vehicle) of victim with that of alleged offender. Limitations of this study were access/analysis of data from only traffic police one zone and the lack of a proper denominator in the form of data on nonfatal road crashes. Only traffic police records were analyzed, whereas that from other stakeholders (such as health department, insurance companies, and transport department) were not explored.
Lower age of offender compared to victims, and more heavy motor vehicles involved in crashes as culprit vehicle indicates that preventive modalities need to be focused around such findings, by analyzing minor variables of fatal crash epidemiological profile in such settings.
Raw data on fatal road crashes need to be captured in a standardized and readily analyzable format. Data processing cycle through the stages of raw data capture, collation, entry into software, analysis, computation of results and interpretation thereof, merits smoothening out, and streamlining between individual components and compartments. Deeper studies encompassing sociodemographic and clinical aspects of fatal road crashes under a single ambit will enable more robust road crash data systems, toward optimization of road safety in developing countries.
Acknowledgments
The contributions of Mr. Pudumai Balakrishnan, Resource Person Transport Department and Chief Traffic Warden Puducherry, and Mr. Balaji, Writer, Traffic Police Puducherry, are gratefully acknowledged.
Financial support and sponsorship
Nil.
Conflicts of interest
There are no conflicts of interest.
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[Table 1], [Table 2]
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