Combining information from two surveys to estimate county-level prevalence rates of cancer risk factors and screening
Combining information from two surveys to estimate county-level prevalence rates of cancer risk factors and screening
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DOI：
10.1198/016214506000001293
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发表时间：
2007-06-01
影响因子：
3.7
通讯作者：
Feuer, Eric J.
中科院分区：
文献类型：
--
作者：
Raghunathan, Trivellore E.;Xie, Dawei;Feuer, Eric J.
癌症监测研究需要估计癌症风险因素的流行程度，并对小区域（如县）进行筛查。两种流行的数据来源是行为风险因素监测系统（BRFSS），一种由国家机构进行的电话调查，以及全国健康访谈调查（NHIS），一种通过面对面访谈进行的地区概率抽样调查。这两种数据源各有优缺点。BRFSS是一个更大的调查，几乎每个县都包括在调查范围内，但与电话调查一样，它的回复率较低，而且它不包括生活在没有电话的家庭中的调查对象。另一方面，NHIS是一个较小的调查，没有包括大多数县；但它包括电话和非电话家庭，并且有更高的回复率。初步分析表明，在电话和非电话家庭中，癌症筛查和危险因素的分布是不同的。因此，来自两个调查的信息可以结合起来解决无响应和无覆盖的错误。将两项调查的信息结合起来的分层贝叶斯方法用于构建县级估计。该模型结合了BRFSS中潜在的非覆盖和非反应偏差，以及这两项调查的复杂样本设计特征。采用马尔可夫链蒙特卡罗方法模拟了基于设计的直接估计和县级协变量模型中未知量的联合后验分布。49个州县级的年度患病率估计。以及整个阿拉斯加州和哥伦比亚特区，利用BRFSS和NHIS从1997年至2000年的数据为六个结果开发了。结果包括吸烟和使用常见的癌症筛查程序。国家卫生信息系统/BRFSS综合的县级估计与单独基于BRFSS的估计有很大不同。
Cancer surveillance research requires estimates of the prevalence of cancer risk factors and screening for small areas such as counties. Two popular data sources are the Behavioral Risk Factor Surveillance System (BRFSS), a telephone survey conducted by state agencies, and the National Health Interview Survey (NHIS), an area probability sample survey conducted through face-to-face interviews. Both data sources have advantages and disadvantages. The BRFSS is a larger survey and almost every county is included in the survey, but it has lower response rates as is typical with telephone surveys and it does not include subjects who live in households with no telephones. On the other hand, the NHIS is a smaller survey, with the majority of counties not included; but it includes both telephone and nontelephone households, and has higher response rates. A preliminary analysis shows that the distributions of cancer screening and risk factors are different for telephone and nontelephone households. Thus, information from the two surveys may be combined to address both nonresponse and noncoverage errors. A hierarchical Bayesian approach that combines information from both surveys is used to construct county-level estimates. The proposed model incorporates potential noncoverage and nonresponse biases in the BRFSS as well as complex sample design features of both surveys. A Markov chain Monte Carlo method is used to simulate draws from the joint posterior distribution of unknown quantities in the model that uses design-based direct estimates and county-level covariates. Yearly prevalence estimates at the county level for 49 states. as well as for the entire state of Alaska and the District of Columbia, are developed for six outcomes using BRFSS and NHIS data from the years 1997-2000. The outcomes include smoking and use of common cancer screening procedures. The NHIS/BRFSS combined county-level estimates are substantially different from those based on the BRFSS alone.