Risk factor redistribution of the national HIV/AIDS surveillance data: An alternative approach
Risk factor redistribution of the national HIV/AIDS surveillance data: An alternative approach
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DOI：
10.1177/003335490812300512
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发表时间：
2008-09-01
影响因子：
3.3
通讯作者：
Song, Ruiguang
中科院分区：
文献类型：
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作者：
Harrison, Kathleen Mcdavid;Kajese, Tebitha;Song, Ruiguang
Objective.本研究的目的是评估一种替代的统计方法-多重插补-在全国人类免疫缺陷病毒（HIV）/获得性免疫缺陷综合征（AIDS）监测系统中的风险因素再分布，作为一种调整缺失风险因素信息的方法。我们使用了一个近似模型，将随机变化的值插补为2000年至2004年诊断的艾滋病毒和艾滋病病例的缺失风险因素。该过程重复M次以生成M个数据集。我们结合数据集的结果来计算总体多重插补估计值和标准误（SE），然后比较多重插补和风险因素再分布的结果。插补模型中的变量包括诊断时的年龄、种族/民族、诊断机构类型、居住地区、国籍、诊断后6个月内的CD-4 T淋巴细胞计数和报告年份。在艾滋病毒数据中，男性与男性的性接触占67.3%的风险因素重新分配和70.4%（SE=0.45）的多重插补的情况下。同样在男性中，通过危险因素再分布和多重插补，注射吸毒（IDU）分别占11.6%和10.8%（SE=0.34），高危异性性接触分别占15.1%和13.0%（SE=0.34）。在女性中，经危险因素再分布和多重插补，IDU和高危异性性接触分别占18.2%和17.9%（SE =0.61），80.8%和80.9%（SE=0.63）。由于多重插补产生的亚组估计值偏差较小，并提供了客观性和半自动化的方法，我们建议考虑使用它来调整缺失的风险因素信息。
Objective. The purpose of this study was to assess an alternative statistical approach-multiple imputation-to risk factor redistribution in the national human immunodeficiency virus (HIV)/acquired immunodeficiency syndrome (AIDS) surveillance system as a way to adjust for missing risk factor information.Methods. We used an approximate model incorporating random variation to impute values for missing risk factors for HIV and AIDS cases diagnosed from 2000 to 2004. The process was repeated M times to generate M datasets. We combined results from the datasets to compute an overall multiple imputation estimate and standard error (SE), and then compared results from multiple imputation and from risk factor redistribution. Variables in the imputation models were age at diagnosis, race/ethnicity, type of facility where diagnosis was made, region of residence, national origin, CD-4 T-lymphocyte cell count within six months of diagnosis, and reporting year.Results. In HIV data, male-to-male sexual contact accounted for 67.3% of cases by risk factor redistribution and 70.4% (SE=0.45) by multiple imputation. Also among males, injection drug use (IDU) accounted for 11.6% and 10.8% (SE=0.34), and high-risk heterosexual contact for 15.1% and 13.0% (SE=0.34) by risk factor redistribution and multiple imputation, respectively. Among females, IDU accounted for 18.2% and 17.9% (SE=0.61), and high-risk heterosexual contact for 80.8% and 80.9% (SE=0.63) by risk factor redistribution and multiple imputation, respectively.Conclusions. Because multiple imputation produces less biased subgroup estimates and offers objectivity and a semiautomated approach, we suggest consideration of its use in adjusting for missing risk factor information.