Introduction:
Premature fatal cardiovascular disease rates have plateaued in the US. Identifying population distributions of short- and long-term predicted risk for atherosclerotic cardiovascular disease (ASCVD) can inform interventions and policy to improve cardiovascular health over the life course.
Methods:
Among nonpregnant participants age 30-59 years without prevalent CVD from the National Health and Nutrition Examination Surveys 2015-18, continuous 10 year (10Y) and 30 year (30Y) predicted ASCVD risk were assigned using the Pooled Cohort Equations and a 30-year competing risk model, respectively. Intermediate/high 10Y risk was defined as ≥7.5%, and high 30Y risk was chosen a priori as ≥20%, based on 2019 guideline levels for risk stratification. Participants were combined into low 10Y/low 30Y, low 10Y/high 30Y, and intermediate/high 10Y categories. We calculated and compared risk distributions overall and across race-sex, age, body mass index (BMI), and education using chi-square tests.
Results:
In 1495 NHANES participants age 30-59 years (representing 53,022,413 Americans), median 10Y risk was 2.3% and 30Y risk was 15.5%. Approximately 12% of individuals were already estimated to have intermediate/high 10Y risk. Of those at low 10Y risk, 30% had high 30Y predicted risk. Distributions differed significantly by sex, race, age, BMI, and education (P<0.01,
Figure
). Black males more frequently had high 10Y risk compared with other race-sex groups. Older individuals, those with BMI ≥30 kg/m
2
, and with ≤high school education had a higher frequency of low 10Y/high 30Y risk.
Conclusions:
More than one-third of middle-aged U.S. adults have elevated short- or long-term predicted risk for ASCVD. While the majority of middle-aged US adults are at low 10Y risk, a large proportion among this subgroup are at high 30Y ASCVD risk, indicating a substantial need for enhanced clinical and population level prevention earlier in the life course.
Serious Falls in Middle‐Aged Veterans: Development and Validation of a Predictive Risk Model
