Hypertension: development of a prediction model to adjust self-reported hypertension prevalence at the community level.

ABSTRACT:

Background

Accurate estimates of hypertension prevalence are critical for assessment of population health and for planning and implementing prevention and health care programs. While self-reported data is often more economically feasible and readily available compared to clinically measured HBP, these reports may underestimate clinical prevalence to varying degrees. Understanding the accuracy of self-reported data and developing prediction models that correct for underreporting of hypertension in self-reported data can be critical tools in the development of more accurate population level estimates, and in planning population-based interventions to reduce the risk of, or more effectively treat, hypertension. This study examines the accuracy of self-reported survey data in describin

SUBMITTER: Mentz G 

PROVIDER: S-EPMC3483283 | biostudies-literature | 2012 Sep

REPOSITORIES: biostudies-literature