Scientists at the University of Alabama at Birmingham, USA, have conducted a study to compare the efficacy of Life’s Essential 8 scores and Life’s Simple 7 scores in predicting the risks of all-cause mortality and cardiovascular disease-related mortality in the general US population.
The study is published in the Journals of the American College of Cardiology: Advances (JACC: Advances).
Study: Association of Life’s Essential 8 and Simple 7 Scores With Mortality: Comparison With Pooled Cohort Equation. Image Credit: Brian A Jackson / Shutterstock
Background
Cardiovascular disease is a leading cause of mortality in the US, affecting about 10% of US adults. A number of risk factors are associated with the development of cardiovascular disease, including obesity, diabetes, hypertension, hyperlipidemia, lack of physical activity, unhealthy diet, and smoking.
The Life’s Simple 7 (LS7) is a metric developed by the American Heart Association (AHA), which combined these seven risk factors to generate a composite score of cardiovascular health. The LS7 score is considered to be an effective tool for predicting the risks of all-cause mortality and cardiovascular mortality.
In addition to these seven risk factors, sleep has been found to be significantly associated with cardiovascular disease and related mortality. Given the significance of sleep, the AHA has developed Life’s Essential 8 (LE8) score, a new cardiovascular health metric that includes sleep as an additional component. The LE8 score also accounts for medication use.
The pooled cohort equation (PCE) is the gold-standard tool for predicting the 10-year risk of cardiovascular disease in individuals aged 40 to 79. Apart from considering traditional cardiovascular risk factors, the PCE includes demographic characteristics (age, sex, and race) into its risk prediction algorithm.
In this study, scientists have compared the effectiveness of PCE, LS7, and LE8 scores in predicting cardiovascular and all-cause mortality risk among individuals aged 40 to 79.
Study design
The study utilized the National Health and Nutrition Examination Survey (NHANES) data collected between 2007 and 2018. The NHANES recruits a nationally representative population to estimate population-level health and nutritional status in the US.
This study population included a total of 21,721 individuals from the NHANES. The LS7 and LE8 scores were calculated in the overall cohort. The PCE was calculated in a subset of 12,943 individuals aged 40 to 79 years.
All-cause and cardiovascular mortality were determined by linking the participants to the National Death Index. Appropriate statistical analyses were carried out to compare the risk prediction value of LS7 and LE8 scores and PCE.
Important observations
The comparison between LS7 and LE8 scores was conducted on 21,721 individuals, representing approximately 157 million individuals in the US population.
During the average study follow-up period of 6.5 years, the LS7 and LE8 scores showed similar efficacy in predicting all-cause mortality and cardiovascular mortality in the US general population.
The comparison between LS7, LE8, and PCE was conducted on 12,943 individuals, who represented approximately 94 million individuals in the US population.
During the average study follow-up period, the PCE-based model showed higher efficacy in predicting all-cause mortality and cardiovascular mortality in individuals aged 40 to 79, compared to LS7 and LE8 scores.
Study significance
The study finds that the LS7 and LE8 scores are equally effective in predicting all-cause and cardiovascular mortalities in the overall US population. However, PCS appears to be a potentially better risk tool for mortality prediction than LS7 and LE8 scores for individuals aged 40 to 79.
Cardiovascular risk factors included in LS7 and LE8 scores are mostly identical except for sleep. The risk of mortality attributed to sleep may be captured by the increased risk of hypertension, diabetes, and obesity. This explains the similarities in mortality risk prediction by LS7 and LE8 scores.
The inclusion of individuals’ age, sex, and race in the PCE algorithm might be responsible for its better efficacy in predicting mortality risk.
Considering the study findings, scientists advise that future studies focus on refining PCE’s risk prediction value and limiting the use of LS7 and LE8 scores to determine cardiovascular health.