When assessing secular trends in blood pressure, failing to adjust for the increasing prevalence of hypertension treatment over time leads to overly optimistic estimates.
Abstract 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. Key Words: Bayesian bootstrapHot deckIncomplete dataMissing dataObservational studyPredictive-mean matching
Heitjan et al. (Thu,) studied this question.
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