Framingham model predicts hypertension in young adults

By Eleanor McDermid, Senior medwireNews Reporter

The Framingham Heart Study (FHS) model for predicting short-term risk for hypertension has good discriminatory ability in a biracial population of young adults, say researchers.

The FHS model includes age, gender, body mass index, smoking habit, parental history of hypertension, systolic blood pressure (SBP), diastolic blood pressure (DBP), and the interaction between age and DBP.

As reported in Hypertension, the model performed better than one based solely on the presence of prehypertension in 4388 adults aged 18 to 30 years from the Coronary Artery Risk Development in Young Adults (CARDIA) Study.

“Risk prediction models that go beyond the prehypertension classification may be used to better identify young adults with an increased risk of hypertension, who may benefit from the adoption of preventive measures early in life,” say lead study author April Carson (University of Alabama at Birmingham, USA) and co-workers.

“The ability to identify young adults at high risk for hypertension will provide the opportunity to efficiently apply risk reduction interventions in addition to population-based approaches for the prevention of hypertension.”

Between baseline and the 25th year of follow-up, 1179 CARDIA participants received a first diagnosis of hypertension, and 7.8% of the cohort developed hypertension that lasted at least 5 years. The FHS model was 84% accurate for discriminating between participants who did and did not develop hypertension, and was effective for both Black and White participants, with respective accuracies of 81% and 87%.

The most accurate individual components of the model were SBP, DBP, and the interaction between age and DBP, at 78%, 78%, and 81%, respectively. Prehypertension alone was just 71% accurate.

Carson et al note that, despite its accuracy, the FHS model consistently underestimated the actual incidence of hypertension. However, this markedly improved when the team recalibrated the model using the hypertension incidence rates from the CARDIA population.

“Applying the FHS model to external populations is likely to result in a systematic overestimation or underestimation of predicted hypertension risk for a particular population when differences in incidence rates and mean levels of risk factors occur,” write the researchers.

They say: “[T]hese observed differences highlight the importance of properly adjusting prediction models for use in external populations to prevent an overestimation or underestimation of risk.”

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