Abstract P300: Cluster Analysis of Discrepancies Between Self-Reported and Investigator-Assessed Biomeasures of Cardiovascular Disease Risk

Abstract

Introduction: Hypertension and obesity are major cardiovascular disease (CVD) risk factors that affect huge numbers of Americans. Although hypertension and obesity are largely preventable and manageable, national statistics evidence that these CVD risks are not effectively managed. Patterns of personal under-estimates of individual risk, i.e., discrepancies between one’s perceived health (self-reported biomeasures) relative to actual health (investigator-assessed biomeasures) may contribute to delays in seeking care that could result in CVD risk detection and management. Hypothesis: We hypothesized that personal patterns of awareness reflecting a higher degree of self-reported underestimation of biomeasures of CVD risk would reveal personal profiles of greater CVD risk. Methods: Adults, aged 18 and over were recruited at a large community event. Self-reported systolic and diastolic blood pressure (SBP, DBP; mmHg), weight (lb.) were collected before objective investigator-obtained assessments of SBP, DBP, and weight. K-means (non-hierarchical) cluster analysis was used to divide data into clusters. The z-score of mean differences between self-reported and measured SBP, DBP, and weight were included in the cluster analysis. ANOVA was used to examine differences in variables among clusters. Results: A total of 61 subjects were eligible and included in the cluster analysis. The mean age of the sample was 55.2 yrs (range 21 to 73; SD: 12.9) and mostly female (63.9%). Mean SBP, DBP, and weight were 133.8, 77.6, and 176.8, respectively. Three clusters from k-means cluster analysis were identified. Cluster 1 (n=22) had moderate discrepancies, with mean differences in SBP, DBP, weight of 14.0, 3.2, -0.5, respectively. Cluster 2 (n=17) had low discrepancies, with mean differences in SBP, DBP, weight: 3.0, -2.6, 7.1, respectively. Cluster 3 (n=22) showed high discrepancies, with mean differences in SBP, DBP, weight of 27.2, 10.5, 4.5, respectively. There were significant mean differences between Cluster 2 (low discrepancies) and Cluster 3 (high discrepancies) in investigator-obtained SBP and DBP (p<0.01, p<0.05, respectively). Conclusions: A wide range of accuracy in personal awareness of biomeasures of risk was uncovered with patterns of discrepancy ranging from low to high; those having a pattern of greatest inaccuracy had significantly higher SBP and DBP (key risk factors for CVD) than those with least inaccuracy. These data highlight the importance of regular objective screening of biomeasures and suggests that relying on personal awareness or self-report of biomeasures is ineffective. The greater discrepancy between self-perceived and investigator-assessed numbers was associated with greater blood pressure-related CVD risks underscoring the potential benefit of arming individuals with information to “know their numbers.”