Association between life’s essential 8 and risk of heart failure: A prospective community-based study

To the Editor: Heart failure (HF) is a major health problem with high mortality rates despite advances in major therapeutic strategies. Cardiometabolic markers such as insulin sensitivity and resistance contribute to the occurrence and less favorable prognosis of HF, despite the availability of advanced therapies. Adherence to healthy lifestyle behaviors has been shown to significantly improve cardiometabolic markers and reduce the risk of HF. Recent guidelines recommended lifestyle modifications such as increased physical activity (PA), healthy diet, weight loss, and smoking cessation as primary strategies for preventing HF and reducing mortality in individuals with HF. In 2010, the concept of “Life’s Simple 7 (LS7)” was reinforced by the American Heart Association (AHA), with a focus on the prevention of lifestyle and metabolic risk factors to reduce the global burden of cardiovascular diseases (CVDs).[1] The LS7 metrics have been shown to be associated with changes in left ventricular (LV) structure and function and attributed 77.1–88.8% to developing HF. In 2022, the AHA introduced “Life’s essential 8 (LE8)”, a revised version of LS7, providing updated measurement methods for the seven health components (PA, blood glucose, blood lipids, blood pressure [BP], smoking, body mass index [BMI], and diet) and adding sleep health as the eighth component to enhance the accuracy of cardiovascular health (CVH) assessments.[2] The CVH score constructed using the LE8 metrics ranges from 0 to 100, simplifying interpretation and increasing the sensitivity for detecting inter-individual differences and longitudinal change in CVH within an individual. In our previous study, we found that a higher CVH score based on the LE8 metrics was associated with a 67% reduction in stroke risk in the Kailuan study.[3] To investigate whether greater adherence to the AHA LE8 metric was associated with altered future risk of HF and post-HF mortality, we conducted a large-scale prospective study among approximately 69,000 participants in two ongoing Chinese cohorts. The data of the current study were collected from the Kailuan study I, established in 2006, and the Kailuan study II, established in 2008.[4] A standardized questionnaire was administered at baseline and during subsequent biennial follow-ups to collect information on demographic details, socioeconomic characteristics, medication use, and the presence of chronic diseases. All participants underwent clinical and laboratory examinations at baseline and in the follow-up surveys. In 2014, a validated food-frequency questionnaire and a PA questionnaire, both including key components of the LE8, were administrated, and we thus treated the 2014 as the baseline for analysis in this study. Finally, we included 68,885 participants with complete CVH information and free of CVDs or cancers in this study [Supplementary Figure 1, https://links.lww.com/CM9/C416]. The study protocol followed guidelines from the World Medical Association Declaration of Helsinki and was approved by the Ethics Committee of Kailuan Hospital (No. 2006-05). All participants have given written informed consent. The overall CVH score, ranging from 0 to 100, was calculated as the summed points of the eight known risk factors of CVDs, according to the AHA Presidential Advisory, divided by eight. The primary outcome was the incidence of fatal or non-fatal HF cases (up to December 31, 2020) and the secondary outcome was all-cause mortality after incident HF (up to December 31, 2021). Hospitalized HF events and death events were retrieved by reviewing medical records and discharge summaries in the 11 Kailuan Hospitals’ Discharge Register. We further searched the death certificates from local death registration centers or contacted participants’ families to identify fatal or non-fatal HF cases that occurred outside the hospitals. The Kailuan endpoint committee consisted of three physicians who annually ascertained all HF events and vital status. HF was diagnosed according to the European Society of Cardiology (ESC) guideline.[5] The person-time of follow-up was calculated from the end date of the 2014 survey to the date of HF occurrence, death, or the end of follow-up, whichever came first. All participants were classified based on clinical cut-offs for the CVH score (<50 points as inadequate, 50–69 points as average, and ≥70 points as optimal scores). In a secondary analysis, we examined the association between the CVH score with LE8 metrics and post-HF mortality. Each LE8 component was categorized as poor (<50 points), intermediate (50–69 points), or ideal (≥70 points) to assess the association between the number of ideal LE8 metrics (seven categories, groups as ≤1, 2, 3, 4, 5, and ≥6) and incident HF. Participants were further classified into three groups based on the number of ideal behavior factors (cigarette smoking, diet quality, PA, and sleep health) and three groups based on the number of metabolic factors (BMI, BP, blood lipids, and glucose): ≤1, 2, and ≥3. We investigated the synergistic effect of ideal behavior factors and ideal metabolic factors on incident HF using Cox regression models. Continuous variables were represented as the mean ± standard deviation while categorical variables were shown as n (%). Cox proportional hazards model was used to assess the hazard ratio (HR) and 95% confidence interval (CI) for the association of the CVH score with HF incidence. All analyses were performed in STATA software version 12.0 ( StataCorp, College Station, TX, USA) and SAS software version 9.4 (SAS Institute, Cary, NC, USA), and a two-sided P-value <0.05 was considered statistically significant. Participants with better CVH scores were generally younger, women, white collars, non-drinkers, and had a lower proportion of family history of myocardial infarction or stroke, a high level of education and eGFR, and low levels of resting heart rate, waist circumference, and high sensitivity C-reactive protein (hs-CRP) [Supplementary Table 1, https://links.lww.com/CM9/C416]. During a mean follow-up period of 5.61 and 6.59 years, we identified 532 HF events and 123 post-HF death cases, respectively. The adjusted HRs of incident HF and post-HF mortality were 0.46 (95% CI: 0.33, 0.64) and 0.38 (95% CI: 0.18, 0.80) for the optimal vs. inadequate CVH scores [Figure 1]. The association between CVH and HF was more pronounced in women, participants aged <65 years or those with chronic kidney diseases. The results did not materially change in the sensitivity analyses [Supplementary Tables 2 and 3, https://links.lww.com/CM9/C416]. The area under the receiver operating characteristic curve of CVH with LE8 metrics (79.1%; 95% CI: 77.4%, 80.8%) was slightly better but did not statistically differ from that with LS7 metrics (78.8%; 95% CI: 77.1%, 80.5%) (Pdifference = 0.24).Figure 1: Cumulative incidence of heart failure (A) and all-cause mortality after heart failure (B) across clinical cut-offs of CVH scores (giving <50 points for inadequate, 50–69 points for average, and ≥70 points for optimal scores) considering the competing-risks due to death derived from other diseases. CVH: Cardiovascular health.The incidence of HF lowered as the number of ideal LE8 metrics increased, with an HR of 0.44 (95% CI: 0.24, 0.80) for the most (≥6) vs. least (≤1) ideal LE8 metrics [Supplementary Figure 2, https://links.lww.com/CM9/C416]. Participants with both ≥3 ideal metabolic factors and ≥3 ideal behavior factors had a lower risk of HF than those with ≤1 ideal metabolic factor and ≤1 ideal behavior factor [Supplementary Table 4, https://links.lww.com/CM9/C416]. The associations between individual LE8 factors and incident HF and post-HF mortality are shown in Supplementary Figure 3, https://links.lww.com/CM9/C416. In this Chinese cohort study with 68,885 participants and 5.61 and 6.59 years of follow-up, we found that the higher CVH score constructed by LE8 metrics was associated with a lower risk of HF and all-mortality after HF onset. The incidence of HF lowered as the number of ideal LE8 metrics increased. Our study extended existing knowledge based on published studies that reported the high CVH score with LS7 metrics was associated with a lower risk of HF. Greater achievement of CVH with LS7 metrics in middle age was associated with a lower lifetime risk of HF and greater preservation of cardiac structure and function in the Atherosclerosis Risk in Communities Study cohort.[6] A higher CVH score was cross-sectionally associated with a lower prevalence of abnormal LV structure, LV concentric remodeling, and concentric hypertrophy. In the Framingham Offspring Study, the CVH score was inversely associated with HF incidence but attenuated after adjustment for LV mass and interim myocardial infarction.[7] We found that in populations with a high risk of HF (e.g., chronic kidney diseases), the association between CVH and HF morbidity and mortality was more significant. Healthy lifestyle behaviors may help to slow the process of HF or death among individuals with a high HF risk, probably due to its potential benefit to these factors. Several pathways, independent of atherosclerosis, involved in endothelial dysfunction, vascular stiffness, inflammation, and renin–angiotensin–aldosterone, have been shown to be associated with CVH and HF.[8] The detailed mechanism underlying the association between CVH and incident HF warrants further investigation. Attainment of all eight ideal LE8 metrics might be a great challenge, as shown in a very low prevalence (0.37%) in our cohort. Therefore, it is of interest whether modest improvement in some but not all CVH components could decrease the risk for HF. We found that even modest improvements in four individual LE8 components (e.g., ≥3 ideal metabolic factors and ≥1 ideal behavior factors) yielded a reasonable risk reduction in HF. Considering primary care is the first healthcare given by a healthcare provider, achieving CVH might be a feasible and effective approach to the prevention of HF in the primary prevention setting. Better CVH with LE8 metrics was associated with a lower risk of HF incidence and all-cause mortality after HF, especially in populations with high HF risk. Targeting strategies to improve CVH in the community could provide a primordial prevention benefit against HF risk in Chinese adults. Funding Dr. Z.Wu was supported by the Shanghai Municipal Education Commission—Gaofeng Clinical Medicine Grant Support (No. 20172004). Dr. X.Gao was supported by the key projects in the 3-year plan of Shanghai municipal public health system (2023–2025) (Nos. GWVI-4 and GWVI-11.1-42), and the National Natural Science Foundation of China (No. 82473622). Conflict of interests None.