Chinese General Practice ›› 2022, Vol. 25 ›› Issue (35): 4418-4424.DOI: 10.12114/j.issn.1007-9572.2022.0375
• Article·Research Methodology • Previous Articles Next Articles
Received:
2022-01-05
Revised:
2022-06-25
Published:
2022-12-15
Online:
2022-08-18
Contact:
WU Jianhui
About author:
通讯作者:
武建辉
作者简介:
基金资助:
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URL: https://www.chinagp.net/EN/10.12114/j.issn.1007-9572.2022.0375
一般资料 | 例数 | 听力受损检出率 | χ2(χ2趋势)值 | P值 | 一般资料 | 例数 | 听力受损检出率 | χ2(χ2趋势)值 | P值 | ||
---|---|---|---|---|---|---|---|---|---|---|---|
年龄(岁) | 17.098 | <0.001 | 劳动强度 | 8.102 | 0.017 | ||||||
20~ | 111 | 23(20.72) | 低 | 131 | 43(32.82) | ||||||
30~ | 783 | 188(24.01) | 中 | 736 | 176(23.91) | ||||||
40~ | 244 | 73(29.91) | 高 | 556 | 166(29.86) | ||||||
50~ | 285 | 101(35.39) | 体育锻炼 | 4.513 | 0.034 | ||||||
性别 | 4.122 | 0.042 | 无 | 871 | 253(29.05) | ||||||
男 | 1 015 | 290(28.57) | 有 | 552 | 132(23.91) | ||||||
女 | 408 | 95(23.28) | 耳毒性化学毒物暴露 | 11.041 | 0.001 | ||||||
文化程度 | 2.057 | 0.358 | 无 | 826 | 196(23.73) | ||||||
小学及以下 | 229 | 58(25.33) | 有 | 597 | 189(31.66) | ||||||
初中及高中(中专) | 647 | 187(28.90) | 睡眠障碍 | 8.214 | 0.016 | ||||||
本科(大专)及以上 | 547 | 140(25.59) | 无障碍 | 484 | 117(24.17) | ||||||
婚姻状况 | 2.889 | 0.236 | 可疑失眠 | 679 | 180(26.51) | ||||||
未婚 | 67 | 19(28.36) | 失眠 | 260 | 88(33.85) | ||||||
已婚 | 1 305 | 347(26.59) | 倒班情况 | 11.742 | 0.003 | ||||||
其他 | 51 | 19(37.25) | 从不倒班 | 749 | 180(24.03) | ||||||
家庭月收入(元) | 8.890 | 0.031 | 曾经倒班 | 404 | 111(27.48) | ||||||
2 000~ | 587 | 168(28.62) | 现在倒班 | 270 | 94(34.81) | ||||||
5 000~ | 608 | 173(28.45) | 高温暴露 | 4.182 | 0.041 | ||||||
8 000~ | 116 | 25(21.55) | 无 | 542 | 130(23.99) | ||||||
11 000~ | 112 | 19(16.96) | 有 | 881 | 255(28.94) | ||||||
BMI | 0.167 | 0.683 | 工龄(年) | 14.238a | <0.001 | ||||||
正常 | 808 | 222(27.48) | 0~ | 223 | 48(21.52) | ||||||
超重/肥胖 | 615 | 163(26.50) | 10~ | 96 | 20(20.83) | ||||||
糖尿病史 | 4.751 | 0.029 | 20~ | 895 | 235(26.26) | ||||||
否 | 1 168 | 302(25.86) | 30~ | 209 | 82(38.23) | ||||||
是 | 255 | 83(32.55) | 累积噪声暴露量〔dB(A)·年〕 | 55.843a | <0.001 | ||||||
高血压史 | 2.722 | 0.099 | <80 | 188 | 21(11.17) | ||||||
否 | 790 | 200(25.32) | 80~ | 220 | 38(17.27) | ||||||
是 | 633 | 185(29.23) | 85~ | 347 | 52(14.99) | ||||||
吸烟 | 2.312 | 0.315 | 90~ | 258 | 96(37.21) | ||||||
从不吸烟 | 763 | 197(25.82) | 95~ | 410 | 178(43.41) | ||||||
既往吸烟 | 110 | 27(24.55) | 血红蛋白 | 0.007 | 0.934 | ||||||
现在吸烟 | 550 | 161(29.27) | 正常 | 855 | 232(27.13) | ||||||
饮酒 | 1.391 | 0.499 | 异常 | 568 | 153(26.94) | ||||||
从不饮酒 | 872 | 227(26.03) | 尿酸 | 0.445 | 0.505 | ||||||
既往饮酒 | 39 | 10(25.64) | 正常 | 1 093 | 291(26.62) | ||||||
现在饮酒 | 512 | 148(28.90) | 异常 | 330 | 94(28.48) | ||||||
丙氨酸氨基转移酶 | 0.019 | 0.892 | |||||||||
正常 | 1 161 | 315(27.13) | |||||||||
异常 | 262 | 70(26.72) |
Table 1 Analysis of the basic situation of hearing loss in oil workers
一般资料 | 例数 | 听力受损检出率 | χ2(χ2趋势)值 | P值 | 一般资料 | 例数 | 听力受损检出率 | χ2(χ2趋势)值 | P值 | ||
---|---|---|---|---|---|---|---|---|---|---|---|
年龄(岁) | 17.098 | <0.001 | 劳动强度 | 8.102 | 0.017 | ||||||
20~ | 111 | 23(20.72) | 低 | 131 | 43(32.82) | ||||||
30~ | 783 | 188(24.01) | 中 | 736 | 176(23.91) | ||||||
40~ | 244 | 73(29.91) | 高 | 556 | 166(29.86) | ||||||
50~ | 285 | 101(35.39) | 体育锻炼 | 4.513 | 0.034 | ||||||
性别 | 4.122 | 0.042 | 无 | 871 | 253(29.05) | ||||||
男 | 1 015 | 290(28.57) | 有 | 552 | 132(23.91) | ||||||
女 | 408 | 95(23.28) | 耳毒性化学毒物暴露 | 11.041 | 0.001 | ||||||
文化程度 | 2.057 | 0.358 | 无 | 826 | 196(23.73) | ||||||
小学及以下 | 229 | 58(25.33) | 有 | 597 | 189(31.66) | ||||||
初中及高中(中专) | 647 | 187(28.90) | 睡眠障碍 | 8.214 | 0.016 | ||||||
本科(大专)及以上 | 547 | 140(25.59) | 无障碍 | 484 | 117(24.17) | ||||||
婚姻状况 | 2.889 | 0.236 | 可疑失眠 | 679 | 180(26.51) | ||||||
未婚 | 67 | 19(28.36) | 失眠 | 260 | 88(33.85) | ||||||
已婚 | 1 305 | 347(26.59) | 倒班情况 | 11.742 | 0.003 | ||||||
其他 | 51 | 19(37.25) | 从不倒班 | 749 | 180(24.03) | ||||||
家庭月收入(元) | 8.890 | 0.031 | 曾经倒班 | 404 | 111(27.48) | ||||||
2 000~ | 587 | 168(28.62) | 现在倒班 | 270 | 94(34.81) | ||||||
5 000~ | 608 | 173(28.45) | 高温暴露 | 4.182 | 0.041 | ||||||
8 000~ | 116 | 25(21.55) | 无 | 542 | 130(23.99) | ||||||
11 000~ | 112 | 19(16.96) | 有 | 881 | 255(28.94) | ||||||
BMI | 0.167 | 0.683 | 工龄(年) | 14.238a | <0.001 | ||||||
正常 | 808 | 222(27.48) | 0~ | 223 | 48(21.52) | ||||||
超重/肥胖 | 615 | 163(26.50) | 10~ | 96 | 20(20.83) | ||||||
糖尿病史 | 4.751 | 0.029 | 20~ | 895 | 235(26.26) | ||||||
否 | 1 168 | 302(25.86) | 30~ | 209 | 82(38.23) | ||||||
是 | 255 | 83(32.55) | 累积噪声暴露量〔dB(A)·年〕 | 55.843a | <0.001 | ||||||
高血压史 | 2.722 | 0.099 | <80 | 188 | 21(11.17) | ||||||
否 | 790 | 200(25.32) | 80~ | 220 | 38(17.27) | ||||||
是 | 633 | 185(29.23) | 85~ | 347 | 52(14.99) | ||||||
吸烟 | 2.312 | 0.315 | 90~ | 258 | 96(37.21) | ||||||
从不吸烟 | 763 | 197(25.82) | 95~ | 410 | 178(43.41) | ||||||
既往吸烟 | 110 | 27(24.55) | 血红蛋白 | 0.007 | 0.934 | ||||||
现在吸烟 | 550 | 161(29.27) | 正常 | 855 | 232(27.13) | ||||||
饮酒 | 1.391 | 0.499 | 异常 | 568 | 153(26.94) | ||||||
从不饮酒 | 872 | 227(26.03) | 尿酸 | 0.445 | 0.505 | ||||||
既往饮酒 | 39 | 10(25.64) | 正常 | 1 093 | 291(26.62) | ||||||
现在饮酒 | 512 | 148(28.90) | 异常 | 330 | 94(28.48) | ||||||
丙氨酸氨基转移酶 | 0.019 | 0.892 | |||||||||
正常 | 1 161 | 315(27.13) | |||||||||
异常 | 262 | 70(26.72) |
变量 | β | SE | Waldχ2值 | P值 | OR(95%CI) | |
---|---|---|---|---|---|---|
年龄(岁) | ||||||
30~ | 0.027 | 0.277 | 0.009 | 0.923 | 1.027(0.597,1.766) | |
40~ | 0.453 | 0.297 | 2.320 | 0.128 | 1.573(0.878,2.817) | |
50~ | 0.742 | 0.293 | 6.413 | 0.011 | 2.101(1.183,3.732) | |
家庭月收入(元) | ||||||
5 000~ | 0.088 | 0.144 | 0.369 | 0.543 | 1.092(0.823,1.448) | |
8 000~ | -0.234 | 0.268 | 0.763 | 0.382 | 0.791(0.468,1.338) | |
11 000~ | -0.634 | 0.291 | 4.750 | 0.029 | 0.530(0.300,0.938) | |
糖尿病 | 0.386 | 0.168 | 5.266 | 0.022 | 1.472(1.058,2.047) | |
中等劳动强度 | -0.487 | 0.231 | 4.444 | 0.035 | 0.615(0.391,0.966) | |
高等劳动强度 | -0.161 | 0.246 | 0.427 | 0.513 | 0.851(0.526,1.379) | |
耳毒性化学毒物暴露 | 0.381 | 0.134 | 8.033 | 0.005 | 1.463(1.125,1.903) | |
睡眠障碍 | ||||||
可疑失眠 | -0.070 | 0.150 | 0.220 | 0.639 | 0.932(0.649,1.251) | |
失眠 | 0.379 | 0.187 | 4.107 | 0.043 | 1.462(1.013,2.110) | |
倒班情况 | ||||||
曾经倒班 | 0.334 | 0.159 | 4.392 | 0.036 | 1.396(1.022,1.907) | |
现在倒班 | 0.346 | 0.174 | 3.962 | 0.047 | 1.414(1.005,1.989) | |
工龄(年) | ||||||
10~ | -0.059 | 0.325 | 0.033 | 0.856 | 0.943(0.498,1.782) | |
20~ | 0.078 | 0.206 | 0.143 | 0.706 | 1.081(0.721,1.620) | |
30~ | 0.689 | 0.251 | 7.521 | 0.006 | 1.992(1.217,3.260) | |
累积噪声暴露量〔dB(A)·年〕 | ||||||
80~ | 0.477 | 0.304 | 2.459 | 0.117 | 1.611(0.888,2.926) | |
85~ | 0.405 | 0.285 | 2.016 | 0.156 | 1.499(0.857,2.620) | |
90~ | 1.684 | 0.279 | 36.456 | <0.001 | 5.387(3.188,9.305) | |
95~ | 1.885 | 0.266 | 50.340 | <0.001 | 6.589(3.914,11.091) |
Table 2 Unconditional multivariable Logistic regression analysis of factors associated with hearing loss in oil workers
变量 | β | SE | Waldχ2值 | P值 | OR(95%CI) | |
---|---|---|---|---|---|---|
年龄(岁) | ||||||
30~ | 0.027 | 0.277 | 0.009 | 0.923 | 1.027(0.597,1.766) | |
40~ | 0.453 | 0.297 | 2.320 | 0.128 | 1.573(0.878,2.817) | |
50~ | 0.742 | 0.293 | 6.413 | 0.011 | 2.101(1.183,3.732) | |
家庭月收入(元) | ||||||
5 000~ | 0.088 | 0.144 | 0.369 | 0.543 | 1.092(0.823,1.448) | |
8 000~ | -0.234 | 0.268 | 0.763 | 0.382 | 0.791(0.468,1.338) | |
11 000~ | -0.634 | 0.291 | 4.750 | 0.029 | 0.530(0.300,0.938) | |
糖尿病 | 0.386 | 0.168 | 5.266 | 0.022 | 1.472(1.058,2.047) | |
中等劳动强度 | -0.487 | 0.231 | 4.444 | 0.035 | 0.615(0.391,0.966) | |
高等劳动强度 | -0.161 | 0.246 | 0.427 | 0.513 | 0.851(0.526,1.379) | |
耳毒性化学毒物暴露 | 0.381 | 0.134 | 8.033 | 0.005 | 1.463(1.125,1.903) | |
睡眠障碍 | ||||||
可疑失眠 | -0.070 | 0.150 | 0.220 | 0.639 | 0.932(0.649,1.251) | |
失眠 | 0.379 | 0.187 | 4.107 | 0.043 | 1.462(1.013,2.110) | |
倒班情况 | ||||||
曾经倒班 | 0.334 | 0.159 | 4.392 | 0.036 | 1.396(1.022,1.907) | |
现在倒班 | 0.346 | 0.174 | 3.962 | 0.047 | 1.414(1.005,1.989) | |
工龄(年) | ||||||
10~ | -0.059 | 0.325 | 0.033 | 0.856 | 0.943(0.498,1.782) | |
20~ | 0.078 | 0.206 | 0.143 | 0.706 | 1.081(0.721,1.620) | |
30~ | 0.689 | 0.251 | 7.521 | 0.006 | 1.992(1.217,3.260) | |
累积噪声暴露量〔dB(A)·年〕 | ||||||
80~ | 0.477 | 0.304 | 2.459 | 0.117 | 1.611(0.888,2.926) | |
85~ | 0.405 | 0.285 | 2.016 | 0.156 | 1.499(0.857,2.620) | |
90~ | 1.684 | 0.279 | 36.456 | <0.001 | 5.387(3.188,9.305) | |
95~ | 1.885 | 0.266 | 50.340 | <0.001 | 6.589(3.914,11.091) |
随机森林模型预测值 | 实际值 | 合计 | |
---|---|---|---|
听力受损 | 非听力受损 | ||
听力受损 | 352 | 24 | 376 |
非听力受损 | 33 | 1 014 | 1 047 |
合计 | 385 | 1 038 | 1 423 |
Table 3 Classification of hearing loss risk assessment in oil workers by the random forest model
随机森林模型预测值 | 实际值 | 合计 | |
---|---|---|---|
听力受损 | 非听力受损 | ||
听力受损 | 352 | 24 | 376 |
非听力受损 | 33 | 1 014 | 1 047 |
合计 | 385 | 1 038 | 1 423 |
XG Boost模型预测值 | 实际值 | 合计 | |
---|---|---|---|
听力受损 | 非听力受损 | ||
听力受损 | 343 | 26 | 369 |
非听力受损 | 42 | 1 012 | 1 054 |
合计 | 385 | 1 038 | 1 423 |
Table 4 Classification of hearing loss risk assessment in oil workers by the XG Boost model
XG Boost模型预测值 | 实际值 | 合计 | |
---|---|---|---|
听力受损 | 非听力受损 | ||
听力受损 | 343 | 26 | 369 |
非听力受损 | 42 | 1 012 | 1 054 |
合计 | 385 | 1 038 | 1 423 |
BP神经网络模型预测值 | 实际值 | 合计 | |
---|---|---|---|
听力受损 | 非听力受损 | ||
听力受损 | 270 | 47 | 317 |
非听力受损 | 115 | 991 | 1 106 |
合计 | 385 | 1 038 | 1 423 |
Table 5 Classification of hearing loss risk assessment in oil workers by the BP neural network model
BP神经网络模型预测值 | 实际值 | 合计 | |
---|---|---|---|
听力受损 | 非听力受损 | ||
听力受损 | 270 | 47 | 317 |
非听力受损 | 115 | 991 | 1 106 |
合计 | 385 | 1 038 | 1 423 |
评价指标 | 随机森林模型 | XG Boost模型 | BP神经网络模型 |
---|---|---|---|
准确率(%) | 95.99 | 95.22 | 88.62 |
灵敏度(%) | 91.43 | 89.09 | 70.13 |
特异度(%) | 97.69 | 97.50 | 95.47 |
约登指数 | 0.89 | 0.87 | 0.66 |
F1分数 | 0.74 | 0.73 | 0.73 |
AUC(95%CI) | 0.95(0.94,0.97) | 0.93(0.92,0.95) | 0.83(0.81,0.84) |
Brier得分 | 0.04 | 0.04 | 0.11 |
O/E ratio | 1.02 | 1.04 | 1.21 |
校准曲线的截距 | 0.029 | 0.032 | 0.097 |
Table 6 Comparison of the performance of the random forest,XG Boost,and BP neural network models in assessing hearing loss risk in oil workers
评价指标 | 随机森林模型 | XG Boost模型 | BP神经网络模型 |
---|---|---|---|
准确率(%) | 95.99 | 95.22 | 88.62 |
灵敏度(%) | 91.43 | 89.09 | 70.13 |
特异度(%) | 97.69 | 97.50 | 95.47 |
约登指数 | 0.89 | 0.87 | 0.66 |
F1分数 | 0.74 | 0.73 | 0.73 |
AUC(95%CI) | 0.95(0.94,0.97) | 0.93(0.92,0.95) | 0.83(0.81,0.84) |
Brier得分 | 0.04 | 0.04 | 0.11 |
O/E ratio | 1.02 | 1.04 | 1.21 |
校准曲线的截距 | 0.029 | 0.032 | 0.097 |
模型 | AUC差值 | 标准差 | 95%CI | Z值 | P值 |
---|---|---|---|---|---|
随机森林模型与XG Boost模型 | 0.02 | 0.010 | (0.003,0.041) | 2.282 | 0.023 |
随机森林模型与BP神经网络模型 | 0.12 | 0.012 | (0.066,0.113) | 7.432 | <0.001 |
XG Boost模型与BP神经网络模型 | 0.10 | 0.012 | (0.045,0.090) | 5.780 | <0.001 |
Table 7 Comparison of the AUC of the random forest,XG Boost,and BP neural network models in assessing hearing loss risk in oil workers
模型 | AUC差值 | 标准差 | 95%CI | Z值 | P值 |
---|---|---|---|---|---|
随机森林模型与XG Boost模型 | 0.02 | 0.010 | (0.003,0.041) | 2.282 | 0.023 |
随机森林模型与BP神经网络模型 | 0.12 | 0.012 | (0.066,0.113) | 7.432 | <0.001 |
XG Boost模型与BP神经网络模型 | 0.10 | 0.012 | (0.045,0.090) | 5.780 | <0.001 |
[1] |
|
[2] |
|
[3] |
|
[4] |
|
[5] |
|
[6] |
|
[7] |
|
[8] |
|
[9] |
|
[10] |
张显燕,孙章皓,徐子涵,等. 职业性高强度噪声对人耳各频段听力受损情况的研究分析[J]. 现代预防医学,2021,48(3):420-422,434.
|
[11] | |
[12] |
狄翠萍. 河南省15岁及以上居民吸烟及饮酒现况研究[D]. 郑州:郑州大学,2019.
|
[13] | |
[14] |
|
[15] |
张生奎,王镇德,杨荔,等. 倒班作业与高尿酸血症的剂量反应关系研究[J]. 中华疾病控制杂志,2018,22(11):1123-1127. DOI:10.16462/j.cnki.zhjbkz.2018.11.008.
|
[16] |
薛昌红,陶志民,苏艺伟,等. 某汽车制造企业噪声作业工人听力状况及影响因素[J]. 中华劳动卫生职业病杂志,2018,36(3):204-207. DOI:10.3760/cma.j.issn.1001-9391.2018.03.011.
|
[17] |
中国高血压防治指南修订委员会,高血压联盟(中国),中华医学会心血管病学分会,等.中国高血压防治指南(2018年修订版)[J].中国心血管杂志,2019,24(1):24-56. DOI:10.3969/j.issn.1007-5410.2019.01.002.
|
[18] |
中华医学会糖尿病学分会. 中国糖尿病足防治指南(2019版)(V)[J]. 中华糖尿病杂志,2019,11(6):387-397. DOI:10.3760/cma.j.issn.1674-5809.2019.06.005.
|
[19] |
|
[20] |
|
[21] |
|
[22] |
|
[23] |
|
[24] |
|
[25] |
|
[26] |
|
[27] |
|
[28] |
|
[29] |
|
[30] |
|
[31] |
蓝潞杭,蒋炫东,王茂峰,等. 随机森林模型预测急性心肌梗死后急性肾损伤[J]. 中华急诊医学杂志,2021,30(4):491-495. DOI:10.3760/cma.j.issn.1671-0282.2021.04.021.
|
[32] |
|
[33] |
张睿,王晓风,张业武,等. 随机森林和SARIMA模型预测我国布鲁氏菌病发病率效果研究[J]. 公共卫生与预防医学,2022,33(1):1-5. DOI:10.3969/j.issn.1006-2483.2022.01.001.
|
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