摘要
目的探索用同伴推动抽样法(respondent-driven sampling,RDS)结合乘数法进行吸毒人群基数估计的可行性。方法 2008年,采用RDS招募东莞市社区吸毒人群进行面对面的问卷调查,获得样本所占接触强制戒毒所和美沙酮维持治疗(methadone maintenance treatment,MMT)门诊的比例,用RDS分析软件进行权重处理;结合当地强制戒毒所和MMT门诊的数据,估计吸毒人群基数。结果经过15周,共招募303名吸毒者。以强制戒毒所为基础,估计东莞市吸毒人群为52 028(90%CI:35 196~81 590)人,是在册登记数的2.67(90%CI:1.81~4.19)倍;估计注射吸毒人群43 651(90%CI:29 529~68 454)人,占常住成年人口数的0.87%(90%CI:0.59%~1.36%)。以MMT门诊为基础,估计东莞市吸毒人群为7 058(90%CI:3 555~13 162)人。结论 RDS结合乘数法对吸毒人群进行基数估计是可行的;但基于MMT门诊数据的估计结果可能会被低估,在应用时应注意选择合适的接触机构以及接触时间。
Objective To explore the feasibility of respondent-driven sampling(RDS) with multiplier in estimating the number of drug users. Methods In 2008,RDS was applied to recruit community-based drug users in Dongguan.A structured questionnaire guided face to face interview was applied to get the proportions of ever in the compulsive detoxification center and in the methadone maintenance treatment(MMT);RDS analysis tool was adopted to adjust the data.The number of drug users was estimated based on the local data of the compulsive detoxification center and MMT.Results A total of 303 drug users were recruited within 15 weeks' periods.Based on the compulsive detoxification center,the estimated number of drug users in Dongguan was 52 028(90% CI:35 196~81 590),which was 2.67(90% CI:1.81~4.19) times of the registration number;the estimated number of injection drug users was 43 651(90% CI:29 529~68 454),which accounted for 0.87%(90% CI:0.59%~1.36%) of the population aged 15~64 years.Based on the MMT clinics,the estimated number of drug users was 7 058(90% CI:3 555~13 162).Conclusions RDS with multiplier is an effective way to estimate the number of drug users,but the number of drug users may be underestimated based on MMT.It is necessary to select appropriate targeted organizations and periods of contacting the targeted organizations.
出处
《中华疾病控制杂志》
CAS
2011年第3期203-206,共4页
Chinese Journal of Disease Control & Prevention
基金
中美艾滋病防治项目
关键词
吸毒人群
基数估计
乘数法
同伴推动抽样法
Drug users
Estimation of population size
Multiplier method
Respondent-driven sampling