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目的:探讨性罪错妇女尖锐湿疣的影响因素。方法:对深圳市妇教所近5年来5130例性罪错妇女的常规体检资料进行t-检验,x~2-检验和多因素的Logistic回归分析等。结果:深圳市性罪错妇女不同年份尖锐湿疣阳性检出率差异无显著性(x~2=9.398,P=0.052);不同年龄阳性检出率差异有显著性(t=10.5378,P=0.0001),年龄越小的阳性检出率越高(r_s=-0.15057,P=0.0001);不同来源地区的阳性检出率差异无显著性(x~2=2.186,P=0.702);不同原职业的阳性检出率差异有显著性(x~2=29.477,P=0.001),学生阳性检出率最高(11.54％),农民阳性检出率(7.48％)次之;不同现职业的阳性检出率差异有显著性(x~2=5.262,P=0.022),以三陪等危险职业的人群阳性检出率为高(6.96％);不同文化程度的阳性检出率差异有显著性(x~2=17.225,P=0.002),初中文化程度的阳性检出率(7.61％)最高;不同婚姻状况的阳性检出率差异有显著性(x~2=25.982,P=0.001),未婚阳性检出率最高(7.62％);多因素的Logistic回归分析中,年龄和原职业(农民)被引入模型,说明在联合因素的作用下它们是女性尖锐湿疣的影响因素(P<0.01)。结论:年龄、原职业、现职业、文化程度及婚姻状况构成尖锐湿疣的影响因素。
Objective: To explore the influencing factors of sexual congenital warts in women with condyloma acuminatum. Methods: The t-test, x ~ 2 test and multivariate Logistic regression were used to analyze the routine physical examination data of 5130 women with sexual misconduct in the past five years. Results: There was no significant difference in the positive detection rates of genital warts among different sex misconduct cases in Shenzhen (x ~ 2 = 9.398, P = 0.052). There was significant difference in positive detection rate between different sex (t = 10.5378, P = 0.0001) (R_s = -0.15057, P = 0.0001). There was no significant difference in the positive detection rates among different regions (x ~ 2 = 2.186, P = 0.702) (X ~ 2 = 29.477, P = 0.001), the highest positive rate of students (11.54%) and the second highest rate of positive rate of farmers (7.48%), and the positive rate of positive patients (X ~ 2 = 5.262, P = 0.022). The positive detection rate was 6.96% in those who were in dangerous occupations such as triple pregnancy. The positive detection rates of different education levels were significant (x 2 = 17.225, P = 0.002). The positive rate of junior high school education was the highest (7.61%). The positive detection rate of different marital status was significantly different (x ~ 2 = 25.982, P = 0.001) The detection rate was the highest (7.62%). In the multivariate logistic regression analysis, age and former occupational (farmer) were introduced into the model, indicating that they were the influencing factors of female genital warts under the combination of factors (P <0.01). Conclusion: Age, original occupation, current occupation, educational level and marital status constitute the influential factors of genital warts.