Comparing the “Life's Essential 8” Scores of Older Adults Living With Cardiovascular Diseases: NHANES, 2013 to 2018
Bibliographic record
Abstract
Background The American Heart Association's Life's Essential 8 (LE8) framework quantifies cardiovascular health. Prior studies have focused on individuals without clinical cardiovascular disease (CVD). We sought to examine recent trends in LE8 scores among older adults with prevalent CVD. Methods We included noninstitutionalized older US adults (ages 65+) from NHANES (National Health and Nutrition Examination Survey 2013–18). Overall LE8 scores (range 0–100; higher is better cardiovascular health) were calculated for all participants. CVD diagnoses were self‐reported, including coronary heart disease, stroke, heart failure, hypertension, angina, and myocardial infarction. Percent change in LE8 scores from 2013 to 2018 was calculated for each diagnosis group, and a linear regression tested for significance of changes within groups. Results The 3050 participants represented 37 908 305 US adults (54.7% women; mean age 72.6). LE8 scores tended to stay stable or decline between 2013 to 2014 and 2017 to 2018 for those with and without CVD. Significant decreases in mean LE8 scores occurred in those with hypertension, with a 4.1% decline (from 59.6 to 57.1 [ P <0.01]); stroke, with an 11.5% decline (from 60.6 to 53.6 [ P =0.01]); and heart failure, with a 15.2% decline (from 60.9 to 51.6 [ P <0.001]). Conclusions LE8 scores remained stable or declined for older US adults before the COVID‐19 pandemic. Populations with hypertension, stroke, and heart failure had significant LE8 score declines. Because LE8 metrics include behavioral and physiologic metrics associated with CVD risk, these data indicate concerning trends and primary and secondary prevention opportunities in older US adults, who are at highest risk for incident and recurrent CVD events.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".