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Hypertension

  • Mark A. Supiano

Abstract

The classification of high blood pressure is identical in older and younger adults. Thus, despite a general age-associated increase in blood pressure, there is no age-adjustment to normalize the threshold value that defines high blood pressure in the elderly. The classification of blood pressure outlined by the Joint National Committee on Detection, Evaluation, and Treatment of High Blood pressure is shown in Table 27.1.1 These values have been defined based on the risks for morbidity (e.g., coronary heart disease, congestive heart failure, stroke, peripheral vascular disease, and renal disease) and mortality for a given blood pressure level. Contrary to a former viewpoint that held that high blood pressure is an expected “normal” aspect of aging, it is now evident that hypertension in the elderly defined according to these blood pressure levels should be viewed as a disease state that is associated with these adverse outcomes. Therefore, although common, high blood pressure in the elderly should not be considered benign. It is also important to note that for any level of diastolic blood pressure the risk for these adverse events is progressively greater at higher levels of systolic blood pressure.2 This is of particular importance in older individuals given the relationship between blood pressure and age that has been observed in epidemiologic studies. Diastolic blood pressure appears to increase with age up to approximately age 60 and thereafter to decrease, while there appears to be a progressive, continuous increase in systolic blood pressure with increasing age.3 Therefore, the age-associated increase in systolic blood pressure is an important contributor to the morbidity and mortality associated with hypertension in the elderly.

Keywords

Blood Pressure Hypertensive Patient High Blood Pressure Nursing Home Resident Systolic Hypertension 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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  • Mark A. Supiano

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