Assessing Secular Trends in Blood Pressure: A Multiple-Imputation Approach
评估血压长期趋势:多重插补方法AI 解读 ↓
本页整理公开书目信息,不生成学术质量评分。AI 解读根据题名及所注明的摘要或原文片段生成,未完成全文核验,可能有误;具体假设、证明与结论请核对原文。摘要保留来源文本,未经模型改写。
DOI 首次登记不等于接收或发表日期。部分更正、评论等条目没有独立摘要;缺少可靠材料时保留待补状态。
引用量采用 OpenAlex 单条关联记录,不合计多个记录;关联记录可能包含正式发表版本,不等于此版本单独引用。缺失不视为零,引用指标不代表论文质量。
关注作者按书目中的完整姓名匹配,同名和姓名变体需人工辨别。相关论文先按共享细分方向和具体方法排列,再参考通用方法与发表日期。
AI 根据所提供的论文材料归类:摘要聚焦健康调查中的缺失数据与趋势插补,未明确提出因果效应或所列其他细分方向的研究。
反馈分类问题评估血压长期趋势:多重插补方法AI 解读 ↓
正在核对关联版本…
正在核对对应版本的资源…
The National Center for Health Statistics makes available data from three national health evaluation surveys that it has conducted since 1960: NHES I (1960-1962), NHANES I (1971-1975), and NHANES II (1976-1980). There has been considerable interest in using these data to assess secular trends in cardiovascular risk factors such as blood pressure (BP). Unfortunately, underlying trends in BP are confounded with trends in physician treatment of hypertension over the same period; in the early 1960s it was rare to treat hypertension, whereas by the late 1970s it had become quite common. Our approach to estimating the underlying trends is to take untreated BP to be the variable of interest and to consider it missing in those subjects who are under treatment. We then use a multiple-imputation scheme to construct estimates of trend parameters that adjust for the incompleteness of the original data. Because our imputations depend on certain model features that the data cannot address, we form estimates under different models and compare the results. Our analyses suggest that trend estimates are sensitive to the assumed model, and naive estimates that do not adjust for treatment trends appear to be overly optimistic.