Prevalence of Ideal Cardiovascular Health Metrics in the Million Veteran Program

Abstract

No data exist on the prevalence of ideal cardiovascular health metrics in a national sample of U.S. veterans. We assessed the prevalence of ideal Life's Simple Seven (LSS) metrics in a cross-sectional study of 554,855 U.S. veterans enrolled in the Million Veteran Program (MVP) from 2011 to 2017. We used the American Heart Association's established criteria to categorize each LSS metric as either poor, intermediate, or ideal for a veteran at time of MVP enrollment. Information on adiposity/body mass index, smoking status, diet, and physical activity was obtained from self-reported survey data, and clinical measurements for total cholesterol, blood pressure, and plasma glucose were obtained from electronic health records. Complete data on all LSS health factors were available for 201,745 veterans. The prevalence of having 0, 1, 2, 3, 4, 5, 6, and 7 ideal cardiovascular health metrics was 29.2%, 34.6%, 22.6%, 10.0%, 3.0%, 0.6%, <0.1%, and 0%, respectively. The frequency of ideal body mass index, physical activity, smoking status, total cholesterol, blood pressure, and plasma glucose was 19.4%, 3.8%, 27.0%, 21.8%, 17.8%, and 34.5%, respectively, in our study population. Among the 7 metrics, MVP participants were least likely to achieve ideal diet (0.4%), particularly the recommendation for fruit and vegetable (at least 4.5 cups/day) intake. Our data show an extremely low prevalence of ideal cardiovascular health factors among veterans in the MVP, especially for diet and physical activity. These findings underscore the need to improve adherence to modifiable lifestyle factors that could result in subsequent reduction in cardiovascular disease burden among veterans.

Assessment and Utilization of Patient-Reported Outcomes Measures to Improve Cardiovascular Disease Prevention

“…Our findings may have important implications for ASCVD risk mitigation at the individual- and population-level. First, despite receiving care from cardiovascular or cerebrovascular specialists, the prevalence of ideal status across all health-related factors and behaviors is similar to reports in the general population 6-10 . Optimal status for these factors is associated with reduced cardiovascular disease risk in a dose-dependent manner 21 .…”

“…These health factors are associated with greater life expectancy, decreased incidence of CVD, increased health-related quality-of-life, and lower individual healthcare costs 5 . However, the prevalence of ideal health factors generally among American adults is extremely low, with <1% achieving ideal status across all 7 health factors [6][7][8][9][10][11] . In a setting where patients are seeking care with cardiovascular and cerebrovascular specialists, the prevalence of these factors are unknown.…”

Ideal cardiovascular health in urban Jamaica: prevalence estimates and relationship to community property value, household assets and educational attainment: a cross-sectional study

“…This approach reduces potential bias when compared with a complete case analysis and improves the power of the study to show significant associations. 36 59 We also performed sensitivity analyses using only complete cases and found that the direction of association and effect sizes were generally similar, thus indicating that the use of multiple imputation, while improving the power of the study, did not alter the inferences made in the study. Finally, the crosssectional design limits our ability to make causal inference; however, the findings make a useful contribution to our understanding of the associations between SES and cardiovascular health.…”

Ideal Cardiovascular Health in Urban Jamaica: Prevalence Estimates and Relationship to Community Property Value, Household Assets and Educational Attainment

“…We were, however, able to use multiple imputation to fill in missing data and perform analyses using the multiple imputed data. This approach reduces potential bias when compared to a complete case analysis and improves the power of the study to show significant associations (42, 64). We also performed sensitivity analyses using only complete cases and found that the direction of association and effect sizes were generally similar, thus indicating that the use of multiple imputation, while improving the power of the study, did not alter the inferences made in the study.…”