This section addresses the methodology used in prioritizing modifiable risk factors for intervention. The committee’s selection of priority interventions was based primarily on the potential impact on the population if the risk factor were eliminated (population attributable risk). One method to compute population attributable fractions for hypertension is to identify prospective observational studies that have analyzed the association between a given risk factor and the incidence of hypertension. Using the relative risk (RR) between a given risk factor and incident hypertension, as well as the prevalence of that risk factor in the population, the attributable fraction can be computed as follows, where Pe is the prevalence of the exposure in the population:
To compute the attributable fractions for various risk factors, the committee used dichotomized RR estimates and estimates of the prevalence of these risk factors in the population.
Prospective studies pertaining to each of the modifiable risk factors (i.e., overweight and obesity, physical inactivity, heavy alcohol use, high salt intake, low potassium intake, and Western-style diet) were examined. A range of relative risks or odds ratios were extracted from these analyses, and accordingly, a range of attributable fractions for hypertension were computed. In addition, an aggregate relative risk was derived from the available literature, and a corresponding aggregate attributable fraction was computed.
A second method to compute population attributable fractions for hypertension is to identify randomized controlled trials, which report the effect of lifestyle modification interventions on blood pressure. Preferably, large-scale systemic reviews that pool the data from multiple randomized trials could provide a useful aggregate effect estimate (and range of estimates). In order to use these effect estimates to compute attributable fractions, a estimation of the mean blood pressure (and standard deviation) among the exposed population (i.e., the population with the risk factor) must be made, and two assumptions must also then be made: (1) that the blood pressure follows a normal distribution and (2) that applying the intervention to the exposed population would lead to a change in the mean blood pressure of that population that is identical to the pooled estimates reported from meta-analyses. Using a normal distribution function for systolic blood pressure (because most hypertension is systolic hypertension) and computing the percent of exposed individuals with a systolic blood pressure ≥140 mm Hg, the change in hypertension prevalence as a result of the intervention