Singh Radha Raman, Das Rajiv Ranjan, Kabirpanthi Vikrant, Singh Akash Ranjan, Bakshi Sanjeev, Datta Debranjan, Shiralkar Milind
Department of Forensic Medicine and Toxicology, Nalanda Medical College and Hospital Patna, Bihar, India.
Department of Community Medicine Government Medical College Shahdol, Madhya Pradesh, India.
J Family Med Prim Care. 2023 Jul;12(7):1261-1267. doi: 10.4103/jfmpc.jfmpc_550_22. Epub 2023 Jul 14.
Women of reproductive age group (WoRAG) are among the most vulnerable groups to suicide in India. The present study intended to develop a mathematical model to differentiate suicides from homicides among WoRAG.
It was a cross-sectional study based on a record review of autopsy at Patna, India, from 2016 to 2021. The cause of deaths was ascertained by autopsies and other records independently by two investigators to reduce the interobserver bias. Independent variables were tested with confirmed suicides to calculate statistically significant association. These variables were further used for developing prediction models for the suicides by multivariate logistic regression analysis.
Out of total of 520 autopsies of WoRAG performed by investigators, the cause of death has been confirmed for 62. Of them, 30 were confirmed as suicides. In univariate analysis, suicides were associated with the menstrual bleed (OR 35 CI 6.9,179), gastric emptying (OR 3.9 CI 1.2,12.8), hanging, poisoning, and drowning as mode of death (OR 435 CI 37.4,5061.9). By logistic regression, three prediction models were built to predict suicide; Model I: gastric emptying, Model II: menstrual bleed, and Model III: including both. The area under the curve (AUC) for Models I, II, and III was 0.67 (95%CI 0.34,0.99), 0.92 (95%CI 0.75,1.00), and 0.94 (95%CI 0.82,1.00), respectively. The AUC of Model III differs significantly from that of Model I ( value 0.03) but not with Model II ( value 0.11).
Menstrual bleed, gastric emptying, and mode of death may be used as a supplement tool in ascertaining the cause of death among WoRAG in medical and legal proceedings.
育龄期女性是印度自杀风险最高的群体之一。本研究旨在建立一个数学模型,以区分育龄期女性自杀和他杀。
这是一项横断面研究,基于对印度巴特那2016年至2021年尸检记录的回顾。由两名调查人员独立通过尸检和其他记录确定死因,以减少观察者间偏差。对自变量与确诊自杀案例进行测试,以计算具有统计学意义的关联。这些变量进一步用于通过多因素逻辑回归分析建立自杀预测模型。
在调查人员进行的520例育龄期女性尸检中,62例的死因已得到确认。其中,30例被确认为自杀。在单因素分析中,自杀与月经出血(比值比35,可信区间6.9,179)、胃排空(比值比3.9,可信区间1.2,千2.8)、缢死、中毒和溺水死亡方式(比值比435,可信区间37.4,5061.9)相关。通过逻辑回归,建立了三个预测自杀的模型;模型I:胃排空;模型II:月经出血;模型III:包括两者。模型I、II和III的曲线下面积(AUC)分别为0.67(95%可信区间0.34,0.99)、0.92(95%可信区间0.75,1.00)和0.94(95%可信区间0.82,1.00)。模型III的AUC与模型I的AUC有显著差异(P值0.03),但与模型II的AUC无显著差异(P值0.11)。
月经出血、胃排空和死亡方式可作为在医学和法律程序中确定育龄期女性死因的补充工具。