基于贝叶斯网络模型的HIV感染者无保护性行为影响因素分析

王建萍; 武媛婷; 姚添; 蓝光华; 鲁鸿燕; 向绍密; 李淑珍; 冯永亮; 王素萍

doi:10.16462/j.cnki.zhjbkz.2022.08.015

基于贝叶斯网络模型的HIV感染者无保护性行为影响因素分析

doi: 10.16462/j.cnki.zhjbkz.2022.08.015

王建萍^{1, 2},
武媛婷^{1, 3},
姚添^{1, 3},
蓝光华⁴,
鲁鸿燕⁴,
向绍密⁵,
李淑珍^1, ,,
冯永亮^{1, 3, ,},
王素萍^{1, 2, 3}

1.
030001 太原，山西医科大学公共卫生学院流行病学教研室
2.
037000 大同，国药同煤总医院超声科
3.
030001 太原，山西医科大学临床流行病学与循证医学中心
4.
530028 南宁，广西壮族自治区疾病预防控制中心艾滋病防制所
5.
532500 宁明，广西壮族自治区宁明县疾病预防控制中心

基金项目:

国家科技重大专项 2018ZX10721202

国家科技重大专项 2012ZXl0002001

详细信息

通讯作者:
李淑珍，E-mail: lszlym@163.com

冯永亮，E-mail: yongliang.feng@sxmu.edu.cn

中图分类号: R181.3
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- 文章访问数: 360
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出版历程
- 收稿日期: 2021-10-12
- 修回日期: 2022-04-10
- 网络出版日期: 2022-08-23
- 刊出日期: 2022-08-10

The influencing factors of unprotected sexual behavior among HIV-infected patients: a study based on Bayesian network model

WANG Jian-ping^{1, 2},
WU Yuan-ting^{1, 3},
YAO Tian^{1, 3},
LAN Guang-hua⁴,
LU Hong-yan⁴,
XIANG Shao-mi⁵,
LI Shu-zhen^{1
, ,},
FENG Yong-liang^{1, 3
, ,},
WANG Su-ping^{1, 2, 3}

1.
Department of Epidemiology, School of Public Health, Shanxi Medical University, Taiyuan 030001, China
2.
Department of Ultrasound, Tongmei General Hospital of Sinopharm, Datong 037000, China
3.
Center of Clinical Epidemiology and Evidence Based Medicine, Shanxi Medical University, Taiyuan 030001, China
4.
Institute for HIV/AIDS Prevention and Control, Guangxi Zhuang Autonomous Regional Center for Disease Control and Prevention, Nanning 530028, China
5.
Ningming County Center for Disease Control and Prevention of Guangxi Zhuang Autonomous Regional, Ningming 532500, China

Funds:

National Science and Technology Major Project of China 2018ZX10721202

National Science and Technology Major Project of China 2012ZXl0002001

More Information

Corresponding author: LI Shu-zhen, E-mail: lszlym@163.com; FENG Yong-liang, E-mail: yongliang.feng@sxmu.edu.cn

摘要

摘要: 目的了解HIV感染者无保护性行为发生情况，探讨其无保护性行为的影响因素及因素间的网络关系。方法采用横断面研究方法，于2015年3月―2015年7月，对广西壮族自治区两所疾病预防控制中心的HIV感染者进行面对面问卷调查，收集其一般人口学特征、HIV治疗情况、近三月的性行为、健康状况和吸毒情况等。采用单因素、多因素非条件logistic回归分析模型进行变量的初步筛选，采用“bnlearn”贝叶斯网络软件包进行模型构建，Netica软件进行模型推理。结果 HIV感染者无保护性行为发生率为47.47%(441/929)。多因素logistic回归分析模型分析结果显示，年龄大、多性伴、文化程度低、家庭人均月收入低和未接受抗反转录病毒治疗(antiretroviral therapy, ART)是无保护性行为的危险因素。贝叶斯网络模型结果显示，多性伴、接受ART、文化程度、家庭人均月收入及年龄与无保护性行为直接相关，目前已婚或同居通过影响多性伴与无保护性行为间接相关，职业通过影响家庭人均月收入与无保护性行为间接相关。结论 HIV感染者无保护性行为发生率较高，对多性伴、未接受ART、文化程度较低、家庭人均月收入较低、年龄较大、单身及无业者应加强健康教育，减少其无保护性行为的发生。
- 贝叶斯网络模型 /
- HIV感染者 /
- 无保护性行为 /
- 影响因素
Abstract: Objective To investigate the prevalence of unprotected sexual behavior among HIV-infected patients, and to explore the influencing factors of unprotected sexual behavior and their network relationships. Methods HIV-infected patients managed by two centers for Disease Control and Prevention in Guangxi were selected from March to July 2015 in a cross-sectional study. Data of general demographic characteristics, HIV treatment status, sexual behavior in the last three months, health status and drug use status were collected through face-to-face interview. Single-factor analysis and multi-factor logistic regression were used to initially screen the variables, "bnlearn" Bayesian network software package was used for model construction, and Netica software was used for model inference. Results The incidence of unprotected sexual behavior among HIV-infected patients was 47.47% (441/929). The results of multi-factor logistic regression analysis showed that age, multiple partners, education level, per capita monthly income of family, and receiving ART were influencing factors of unprotected sexual behavior. The results of Bayesian network model showed that multiple sexual partners, receiving ART therapy, education level, per capita monthly income of family, and age were directly related to unprotected sexual behavior, currently being married or cohabiting was indirectly related to unprotected sexual behavior through affecting multiple sexual partners, and occupation was indirectly related to unprotected sexual behavior through affecting per capita monthly income of family. Conclusions HIV-infected patients have a high incidence of unprotected sexual behavior. Health education should be strengthened for those having multiple sexual partners, not receiving ART, with low level of education, having low per capita monthly income of family, being older, being currently single and being unemployed, so as to reduce the occurrence of unprotected sexual behavior.
- Bayesian network model /
- HIV-infected patients /
- Unprotected sexual behavior /
- Influencing factors

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图 1 HIV感染者无保护性行为影响因素贝叶斯网络模型分析

Figure 1. Bayesian network model analysis for the influencing factors of unprotected sexual behavior in HIV-infected patients

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表 1 HIV感染者无保护性行为相关因素单因素分析[n(%)]

Table 1. Univariate analysis of factors related to unprotected sexual behavior in HIV-infected patients [n(%)]

变量	例数(N=929)	无保护性行为		χ²值	P值
变量	例数(N=929)	是(n=441)	否(n=488)	χ²值	P值
年龄(岁)				17.194	< 0.001
< 35	327(35.20)	153(34.69)	174(35.66)
35~<50	447(48.12)	236(53.52)	211(43.24)
≥50	155(16.68)	52(11.79)	103(21.10)
性别				1.473	0.224
男	605(65.12)	296(67.12)	309(63.32)
女	324(34.88)	145(32.88)	179(36.68)
BMI(kg/m²)				4.078	0.130
<18.5	161(17.33)	65(14.74)	96(19.68)
18.5~<24	627(67.49)	309(70.07)	318(65.16)
≥24	141(15.18)	67(15.19)	74(15.16)
婚姻状况				26.579	< 0.001
已婚/同居	582(62.65)	312(70.75)	270(55.33)
未婚	199(21.42)	82(18.59)	117(23.98)
离异/丧偶	148(15.93)	47(10.66)	101(20.70)
民族				0.656	0.720
汉族	388(41.77)	190(43.08)	198(40.57)
壮族	442(47.58)	204(46.26)	238(48.77)
其他	99(10.65)	47(10.66)	52(10.66)
文化程度				8.838	0.012
初中及以下	204(21.96)	80(18.14)	124(25.41)
高中或中专	541(58.23)	277(62.81)	264(54.10)
大专及以上	184(19.81)	84(19.05)	100(20.49)
职业				1.646	0.199
有业	599(64.48)	275(62.36)	324(66.39)
无业	330(35.52)	166(37.64)	164(33.61)
家庭人均月收入(元)				5.665	0.058
< 3 000	668(71.90)	301(68.25)	367(75.20)
3 000~<5 000	184(19.81)	100(22.68)	84(17.21)
≥5 000	37(8.29)	40(9.07)	37(7.58)
HIV感染年限(年)				7.983	0.018
<5	533(57.37)	240(54.42)	293(60.04)
5~<10	326(35.09)	157(35.60)	169(34.63)
≥10	70(7.53)	44(9.98)	26(5.33)
性伴类型				1.376	0.502
同性	86(9.26)	46(10.43)	40(8.20)
异性	813(87.51)	381(86.39)	432(88.52)
双性	30(3.23)	14(3.17)	16(3.28)
多性伴				3.006	0.082
是	237(25.51)	101(22.90)	136(27.87)
否	692(74.49)	340(77.10)	352(72.13)
接受ART				7.466	0.006
是	802(86.33)	46(10.43)	81(16.60)
否	127(13.67)	395(89.57)	407(83.40)
吸毒				1.122	0.289
是	79(8.50)	42(9.52)	37(7.58)
否	850(91.50)	399(90.48)	451(92.42)

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表 2 HIV感染者无保护性行为影响因素logistic回归分析

Table 2. Logistic regression analysis of influencing factors of unprotected sexual behavior in HIV-infected patients

变量	OR(95% CI)值	aOR(95% CI)值^a
年龄(岁)
< 35	1.000	1.000
35~<50	0.786(0.591~1.046)	0.844(0.612~1.165)
≥50	1.742(1.170~2.593)	1.784(1.139~2.794)
文化程度
初中及以下	1.000	1.000
高中或中专	0.615(0.443~0.853)	0.649(0.457~0.923)
大专及以上	0.768(0.513~1.150)	0.460(0.387~0.533)
家庭人均月收入(元)
<3 000	1.000	1.000
3 000~<5 000	0.689(0.496~0.956)	0.672(0.471~0.960)
≥5 000	0.459(0.437~0.721)	0.455(0.446~0.924)
接受ART
否	1.000	1.000
是	0.585(0.397~0.862)	0.590(0.394~0.882)
多性伴
否	1.000	1.000
是	1.301(0.966~1.751)	1.474(1.075~2.021)
注：^a为调整变量, 即BMI、民族、职业、HIV感染年限、性伴类型、是否吸毒。

下载: 导出CSV

表 3 无保护性行为的条件概率分布(%)

Table 3. Conditional probability distribution of unprotected sexual behavior (%)

父节点					无保护性行为
文化程度	家庭人均月收入(元)	接受ART	多性伴	年龄(岁)	是	否
大专及以上	≥5 000	是	否	< 35	31.82	68.18
初中及以下	< 3 000	否	是	≥50	88.89	11.11

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基于贝叶斯网络模型的HIV感染者无保护性行为影响因素分析

doi: 10.16462/j.cnki.zhjbkz.2022.08.015

通讯作者:
李淑珍，E-mail: lszlym@163.com

冯永亮，E-mail: yongliang.feng@sxmu.edu.cn

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The influencing factors of unprotected sexual behavior among HIV-infected patients: a study based on Bayesian network model

Corresponding author: LI Shu-zhen, E-mail: lszlym@163.com; FENG Yong-liang, E-mail: yongliang.feng@sxmu.edu.cn

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基于贝叶斯网络模型的HIV感染者无保护性行为影响因素分析

doi: 10.16462/j.cnki.zhjbkz.2022.08.015

通讯作者: 李淑珍，E-mail: lszlym@163.com 冯永亮，E-mail: yongliang.feng@sxmu.edu.cn

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出版历程

The influencing factors of unprotected sexual behavior among HIV-infected patients: a study based on Bayesian network model

Corresponding author: LI Shu-zhen, E-mail: lszlym@163.com; FENG Yong-liang, E-mail: yongliang.feng@sxmu.edu.cn

计量

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目录

通讯作者:
李淑珍，E-mail: lszlym@163.com

冯永亮，E-mail: yongliang.feng@sxmu.edu.cn