基于二元Logistic回归船舶修造事故伤害模型

doi:10.16265/j.cnki.issn1003-3033.2024.12.0350

摘要/Abstract

摘要：

为探究船舶修造企业(SRBE)事故伤害的影响因素,基于1 411起某造船集团事故数据,构建二元Logistic回归(LR)模型,并借助让步比(OR)量化企业、时间、地点、人员、环境和事故类型等因素对事故伤害的影响。结果表明:共有11个因素显著影响事故伤害。非合同工事故伤害风险显著高于合同工;非审批的危险作业项目事故伤害风险是审批项目的3.246倍;男性肇事者事故伤害风险显著高于女性;事故中作业人员受教育水平集中在初中,相较于初中学历,作业人员受教育程度越高,事故伤害风险越低;事故伤害呈现季节性特征,第2季度事故频发,第1季度事故较少且风险较低;高峰时段及工作日事故伤害风险分别显著高于非高峰时段和非工作日;物体打击是主要事故类型,而机械伤害显著增加作业人员受伤风险;厂区内船舶和车间是事故伤害高发地点;随着工龄增加,事故造成人员伤害风险降低,然而温度上升,发生事故伤害风险增加。

关键词: Logistic回归(LR), 船舶修造企业(SRBE), 事故伤害, 影响因素, 让步比(OR)

Abstract:

In order to explore the factors influencing accident injuries in SRBE, a binary LR model was constructed based on data from 1 411 accidents from a Chinese shipbuilding group. OR were used to quantify the impact of factors such as enterprise, time, location, personnel, environment, and accident types to accident injuries. The result identifies 11 significant factors influencing accident injuries. Non-contract workers face significantly higher risks of injury compared to contract workers. Non-approved hazardous operations pose 3.246 times the risk of accident injuries compared to approved hazardous operations. Male perpetrators present a significantly higher risk of causing accident injuries than female perpetrators. The education level of the workers is predominantly at junior high school, and higher education levels are associated with a lower risk of causing accident injuries compared to those with junior high school education. Accident injuries exhibit seasonal characteristics, with accidents occurring frequently in the second quarter, while relatively fewer and less risky in the first quarter. Peak working hours and workdays significantly increase injury risks compared to off-peak hours and non-working days. Object strikes are the primary type of accidents, and mechanical injuries significantly increase the risk of accident injuries. Ships and workshops are the most likely locations for accident injuries within the shipyards. Longer years of service reduce the risk of accident injuries, while higher temperatures increase it.

Key words: Logistic regression (LR), ship repair and building enterprises (SRBE), accident injuries, influencing factor, odds ratio (OR)

中图分类号:

X928.4机械伤害事故

李显, 焦宇, 史旦达, 吴建军, 康与涛. 基于二元Logistic回归船舶修造事故伤害模型[J]. 中国安全科学学报, 2024, 34(12): 120-128.

LI Xian, JIAO Yu, SHI Danda, WU Jianjun, KANG Yutao. Accident injuries model of ship repair and building enterprises based on binary Logistic regression[J]. China Safety Science Journal, 2024, 34(12): 120-128.

图/表 7

表1

表2

表3

表4

表5

表6

连续变量分箱描述性统计与编码结果

变量名称	分箱方式	编码=类别(频数,占比/%)
$A 1$	自定义	1=熟练工(1 240, 87.88) 0=新手(171, 12.12)
$A 2$	等距	1=0~10(909, 64.42) 2=10~20(313, 22.18) 3=20~30(157, 11.13) 4=30~40(33, 2.27)
$B 1$	自定义	1=非高温(1 353, 95.89) 0=高温(58, 4.11)
$B 2$	等距	1=20~30(603, 42.74) 2=10~20(379, 26.86) 3=0~10(252, 17.86) 4=30~40(125, 8.86) 5=小于0(52, 3.69)

表6

表7

分箱变量组合模型对比结果

编号	模型	H-L检验p值	-2LL	AUC
1	$A - B -$	0.407	1 102.038	0.852
2	$A 1 B -$	0.273	1 108.014	0.850
3	$A 2 B -$	0.273	1 108.014	0.850
4	$A - B 1$	0.252	1 116.673	0.847
5	$A 1 B 1$	0.082	1 121.395	0.845
6	$A 2 B 1$	0.082	1 121.395	0.845
7	$A - B 2$	0.079	1 107.755	0.850
8	$A 1 B 2$	0.559	1 111.497	0.848
9	$A 2 B 2$	0.559	1 111.497	0.848

表7

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变量维度	变量名称	平均值	标准差	最小值	中位数	最大值
人员	年龄/岁	38.04	9.16	19	38	60
	工龄/a	10.22	8.48	1	8	40
	本工种工龄/a	6.83	5.74	1	5	38
环境	最低温度/℃	13.66	9.46	-17	15	36
	最高温度/℃	20.90	9.61	-13	23	40
	正弦温度/℃	18.64	9.66	-14.5	20.5	39.8

变量维度	变量名称	编码=类别(频数,占比/%)	变量维度	变量名称	编码=类别(频数,占比/%)
事故伤害	人员伤害	1=人员伤害(1 078, 76.40) 0=无人员伤害(333, 23.60)	时间	星期	1=星期三(233, 16.51) 2=星期五(217, 15.38) 3=星期六(217, 15.38) 4=星期四(205, 14.53) 5=星期二(200, 14.17) 6=星期一(182, 12.90) 7=星期日(157, 11.13)
企业	用工形式	1=非合同制(1 206, 85.47) 2=合同制(205, 14.53)		星期
	人员规模	1=[1 000, +∞)(862, 61.09) 2=[0, 1 000)(549, 38.91)		季节	1=第二季度(412, 29.20) 2=第三季度(370, 26.22) 3=第一季度(327, 23.18) 4=第四季度(302, 21.40)
	人员规模	1=[1 000, +∞)(862, 61.09) 2=[0, 1 000)(549, 38.91)		是否工作日	1=是(1 007, 71.37) 0=否(404, 28.63)
	危险作业审批项	1=否(1 130, 80.09) 0=是(281, 19.91)		高峰事故时刻	1=[8, 12) & [14,18)(1 024, 72.57) 0=其他(387, 27.43)
人员	性别	1=男(1 331, 94.33) 0=女(80, 5.67)	环境	天气	1=晴(876, 62.08) 2=雨雪雾霾(283, 20.06) 3=阴(252, 17.86)
	婚姻状态	1=已婚(1 219, 86.39) 0=未婚(192, 13.61)		风向	1=东南风(377, 26.72) 2=西北风(197, 13.96) 3=南风(192, 13.61) 4=北风(173, 12.26) 5=东北风(172, 12.19) 6=东风(152, 10.77) 7=西南风(90, 6.38) 8=西风(58, 4.11)
	受教育水平	1=初中(966, 68.46) 2=高中(287, 20.34) 3=专科(69, 4.89) 4=小学(53, 3.76) 5=本科及以上(36, 2.55)		风向
	新工人	1=否(1 148, 81.36) 0=是(263, 18.64)		风力	1=3级(466, 33.03) 2=5级(290, 20.55) 3=4级(278, 19.70) 4=2级(229, 16.23) 5=6级+(91, 6.45) 6=1级(57, 4.04)
事故	事故性质	1=责任事故(1 029, 72.93) 0=非责任事故(382, 27.07)	空间	事故地点	1=内场(468, 33.17) 2=船舶(406, 28.77) 3=码头或坞(390, 27.64) 4=车间(132, 9.36) 5=厂区外(15, 1.06)
事故	事故类型	1=物体打击(462, 32.74) 2=其他伤害(374, 26.51) 3=机械伤害(162, 11.48) 4=高处坠落(144, 10.21) 5=起重伤害(102, 7.23) 6=合并类别(167, 11.83)	空间	事故地点

变量名称	卡方值	自由度	显著性	VIF
年龄	—	—	0.140	1.757
工龄	—	—	0.025^*	2.089
本工种工龄	—	—	0.047^*	1.598
正弦温度	—	—	0.030^*	1.415
危险作业审批项	63.308	1	0.000^*	1.047
用工形式	7.722	1	0.005^*	1.015
人员规模	0.685	1	0.408	1.197
事故地点	31.121	4	0.000^*	1.045
事故性质	1.019	1	0.313	1.168
事故类型	59.263	5	0.000^*	1.018
性别	9.087	1	0.003^*	1.057
婚姻状态	0.944	1	0.331	1.401
新老工人	2.132	1	0.144	1.071
教育水平	16.520	4	0.002^*	1.042
季节	13.882	3	0.003^*	1.330
工作日与休息日	6.694	1	0.010^*	1.073
星期	14.870	6	0.021^*	1.069
高峰事故时刻	4.788	1	0.029^*	1.014
风级	15.231	5	0.009^*	1.030
风向	23.545	7	0.001^*	1.086
天气	3.542	2	0.170	1.042

变量维度	变量名称	变量类别	回归系数	标准误差	df	Sig.	OR	OR的 95%
企业	用工形式		0.355	0.181	1	0.047	1.427	1.000	2.036
企业	危险作业审批项		1.177	0.160	1	0.000	3.246	2.373	4.441
人员	性别		0.956	0.264	1	0.000	2.602	1.550	4.368
	工龄		-0.030	0.013	1	0.026	0.970	0.945	0.996
	受教育程度	初中^a			4	0.001
		高中	-0.478	0.170	1	0.005	0.620	0.444	0.866
		专科	-0.907	0.289	1	0.002	0.404	0.229	0.710
		大学	-0.965	0.432	1	0.025	0.381	0.163	0.888
时间	季节	第二季度^a			3	0.001
	季节	第一季度	-0.499	0.184	1	0.007	0.607	0.424	0.871
	高峰事故时刻		0.376	0.166	1	0.023	1.457	1.053	2.017
	是否工作日		0.356	0.145	1	0.015	1.462	1.073	1.898
事故	事故类型	物体打击^a			5	0.000
		其他伤害	-0.825	0.176	1	0.000	0.438	0.310	0.619
		合并类别	-0.477	0.227	1	0.035	0.621	0.398	0.968
		机械伤害	0.616	0.303	1	0.042	1.851	1.022	3.352
空间	事故地点	内场^a			4	0.000
		船舶	0.383	0.185	1	0.039	1.467	1.020	2.108
		码头或坞	-0.353	0.169	1	0.036	0.702	0.504	0.978
		车间	0.852	0.297	1	0.004	2.345	1.310	4.198
		厂区外	-1.611	0.733	1	0.028	0.200	0.047	0.840
环境	正弦温度		0.058	0.009	1	0.000	1.060	1.041	1.079
常数项			-0.293	0.450	1	0.515	0.746