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2011年至2016年印度泰米尔纳德邦道路交通事故数据管理系统(RADMS)数据的流行病学分析:综合国家数据库的未来方向。

Epidemiological analysis of Road Accident Data Management System (RADMS) data in Tamil Nadu, India from 2011 to 2016: Future directions for an integrated national database.

作者信息

Raghavan Kowshick, Muthappan Sendhilkumar, Ravi Karunya, Jothi Kathirvel, Shanmugasundaram Devika, Venkatasamy Vettrichelvan, Parasuraman Ganeshkumar, Ponnaiah Manickam

机构信息

Division of Online Courses, ICMR-National Institute of Epidemiology, Tamil Nadu, India.

Department of Public Health, Directorate of Public Health and Preventive Medicine, Tamil Nadu, India.

出版信息

J Family Med Prim Care. 2024 Oct;13(10):4560-4568. doi: 10.4103/jfmpc.jfmpc_63_24. Epub 2024 Oct 18.

DOI:10.4103/jfmpc.jfmpc_63_24
PMID:39629407
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11610803/
Abstract

INTRODUCTION

Globally, road traffic injuries (RTIs) are the eighth leading cause of death, with an estimated 1.35 million deaths yearly. In India, road traffic accidents (RTAs) are one of the major causes of mortality among the younger generation. We analyzed Tamil Nadu's comprehensive Road Accident Data Management System (RADMS) data and described the epidemiological indicators of RTI in this setting.

METHODS

We obtained the data from the RADMS database for 2011-2016 and used 2011 population census data to project and standardize for different age groups and genders to calculate incidence. We calculated average annual percentage changes (AAPC) with a 95% confidence interval for the whole period. We computed Joinpoint regression analysis for trends and calculated the age-adjusted incidence rate with standard error (SE) using R statistical computing software.

RESULTS

We included 3,67,094 RTAs and 5,50,447 RTIs. We observed that the incidence of RTAs and RTIs declined between 2011 and 2016. Most injured were males (82%) and aged 20-39 years (49%). The highest number of accidents occurred on the state highways (65.2%) and on Sundays (17%). Age-adjusted incidence (per 1,00,000) declined from 121.87 (SE 0.4) in 2011 to 92.73 (SE 0.34) in 2016 (AAPC = -4.5% (95% CI = -7.8 to -1)). The age groups 30-39 and 20-29 were 9.82 (z = 8.98; < 0.05) and 9.02 (z = 8.65; < 0.05) times at a higher risk compared to 0-9 years old. The motorcyclists (14-27 times; < 0.05) and pedestrians (12-23 times; < 0.05) had the maximum risk of RTIs.

CONCLUSION

Young adults, drivers, motorcyclists, and pedestrians remain vulnerable populations for RTIs. More accidents occurred in the state highways and on Sundays. The analysis provides insights on RTIs and RTAs, which will be used to reduce the burden of RTIs and save millions of lives.

摘要

引言

在全球范围内,道路交通伤害(RTIs)是第八大死因,估计每年有135万人死亡。在印度,道路交通事故(RTAs)是年轻一代死亡的主要原因之一。我们分析了泰米尔纳德邦综合道路事故数据管理系统(RADMS)的数据,并描述了该地区道路交通伤害的流行病学指标。

方法

我们从RADMS数据库获取了2011 - 2016年的数据,并使用2011年人口普查数据对不同年龄组和性别的数据进行推算和标准化,以计算发病率。我们计算了整个时期的平均年度百分比变化(AAPC)及其95%置信区间。我们使用R统计计算软件对趋势进行Joinpoint回归分析,并计算年龄调整发病率及其标准误差(SE)。

结果

我们纳入了367,094起道路交通事故和550,447起道路交通伤害事件。我们观察到2011年至2016年间道路交通事故和道路交通伤害的发病率有所下降。大多数伤者为男性(82%),年龄在20 - 39岁之间(占49%)。事故发生最多的是在国道上(65.2%),且在周日(占17%)。年龄调整发病率(每10万人)从2011年的121.87(SE 0.4)降至2016年的92.73(SE 0.34)(AAPC = -4.5%(95% CI = -7.8至 -1))。与0 - 9岁年龄组相比,30 - 39岁和20 - 29岁年龄组发生道路交通伤害的风险分别高9.82倍(z = 8.98;P < 0.05)和9.02倍(z = 8.65;P < 0.05)。骑摩托车者(14 - 27倍;P < 0.05)和行人(12 - 23倍;P < 0.05)发生道路交通伤害的风险最高。

结论

年轻人、驾驶员、骑摩托车者和行人仍然是道路交通伤害的脆弱人群。国道和周日发生的事故更多。该分析提供了有关道路交通伤害和道路交通事故的见解,将用于减轻道路交通伤害负担并拯救数百万人的生命。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2750/11610803/31c154b74315/JFMPC-13-4560-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2750/11610803/1091932194a0/JFMPC-13-4560-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2750/11610803/6d91917b763f/JFMPC-13-4560-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2750/11610803/740f26561fca/JFMPC-13-4560-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2750/11610803/6384661739fd/JFMPC-13-4560-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2750/11610803/31c154b74315/JFMPC-13-4560-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2750/11610803/1091932194a0/JFMPC-13-4560-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2750/11610803/6d91917b763f/JFMPC-13-4560-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2750/11610803/740f26561fca/JFMPC-13-4560-g003.jpg
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