摘要
目的了解北京市重复人工流产妇女流产后避孕方法坚持使用情况及其影响因素。方法采用卡方检验和多元Logistic回归方法对问卷调查结果进行分析。结果被调查妇女中30.29%接受过2次及以上人工流产手术,90.47%选择人工流产的原因是非意愿妊娠。55.54%的妇女在人工流产4周后恢复月经,平均首次使用避孕方法的时间是在流产后5.11周。在本次流产前3个月,30.54%的妇女没有避孕。采取避孕措施的妇女中,仅有30.12%妇女自述能够坚持每次性生活都使用避孕方法。多元Logistic回归分析结果显示:妇女自身学历高、知道人工流产危害且丈夫对避孕态度积极的妇女坚持每次使用避孕方法的发生比是低学历妇女、不清楚人工流产危害以及丈夫避孕态度不积极妇女的1.702倍、3.377倍和4.076倍。结论妇女重复人工流产现象值得引起关注,通过提供流产后服务可以降低重复人工流产,其关键在于落实避孕方法的使用。在为育龄妇女提供生殖健康服务的同时,也应重视男性参与生殖健康服务,从而更好地提高服务效果。
Objective To investigate the consistent use of contraceptive and its influencing factors among women who received recurrent abortion in Beijing. Methods Data were collected by questionnaires.The survey results were analyzed by Chi-squared test and multinomial Logistic regression. Results Among the surveyed women,30.29% received induced abortion at least twice and above,90.47% of them selected induced abortion because of unwanted pregnancy.55.54% of the women resumed menses 4 weeks after induced abortion,while first contraception used was 5.11 weeks later.3 months before latest induced abortion,30.54% of the women did not use any contraception.For the rest,only 30.12% could consistently use the contraception each sexual intercourse.By multinomial Logistic regression analysis,we found that the rates of contraception consistent use among women with higher educational level,being aware of the harm of induced abortion and the husband being active for contraception were 1.702,3.377 and 4.076 folds than those with lower educational level,being unaware of the harm of induced abortion and the husband being inactive for contraception. Conclusions More attention should be paid to recurrent abortion.Post abortion services could be helpful for recurrent abortion reduction,and the key point is correct and consistent contraception use.Meanwhile,male involvement could play an important role.
出处
《实用预防医学》
CAS
2012年第10期1521-1524,共4页
Practical Preventive Medicine
关键词
育龄妇女
重复流产
流产后服务
避孕方法
坚持使用
多元LOGISTIC回归
Bearing-aged women
Recurrent abortion
Post-abortion care services
Contraception
Consistent use
Multinomial Logistic regression
