Non-communicable diseases (NCDs) are the leading causes of global death. It was estimated that 40.5 million (71% of all deaths) of the 56.9 million deaths globally were from NCDs (1). And among NCDs, cardiovascular disease (CVD), cancers, respiratory diseases and diabetes are the top four killers (2). Population-based prevention strategies are critical for mitigating the global prevalence of NCDs, notably CVD, cancer, diabetes and its associated burdens. Key modifiable risk factors including obesity, sedentary lifestyle, poor diet, smoking, hypertension, hyperglycemia, dyslipidemia are strongly linked to the development of CVD and its related mortality. Addressing these determinants through systematic interventions is essential for reducing disease incidence, improving management outcomes, and alleviating the socioeconomic costs tied to NCDs.

In 2010, the American Heart Association (AHA) proposed the conception of cardiovascular health (CVH) based on seven health behaviors and factors. The seven components[diet, physical activity, smoking, body mass index (BMI), fasting blood glucose, total cholesterol and blood pressure] were subsequently called Life's Simple 7(LS7) (3). Each metric was classified as poor, intermediate, or ideal according to the thresholds provided by AHA. During the past decade, studies suggested strong, stepwise, inverse associations between the number of ideal CVH metrics with incident CVD, cancers, dementia, diabetes and mortality (4–15). However, there are several limitations of LS7. For example, some features of CVH component(i.e., diet) do not cover the full scope and the current quantification of metrics is less sensitive to interindividual differences (16). To overcome these limitations, the AHA introduced Life's Essential 8(LE8). LE8 added sleep as new metric and updated four metrics (diet, smoking exposure, blood lipids and blood glucose). A major difference between LE8 and LS7 is the scoring system of the components. Whereas each component in the LS7 score system ranged from 0 to 2, the new LE8 scoring system for each component ranges from 0 to 100 points, allowing generation of a new composite CVH score. In addition, compared with LS7, LE8 is more sensitive to changes in individual or population CVH when behaviors change (16).

According to a previous meta-analysis, people with the greatest number of ideal CVH metrics have a 45% lower risk of all-cause mortality, a 75% decline in CVD mortality and 80% lower risk of incident CVD compared those with the least number of ideal CVH metrics (17). Similar results were identified by another meta-analysis (18). Further exploration of the dose-response relationships is essential to determine optimal CVH thresholds that can inform evidence-based public health recommendations. Both Guo et al (18) and Aneni et al (19) suggested a strong inverse linear dose-response relationship between the number of ideal CVH metrics and all-cause, CVD mortality. Even one unit increase in ideal CVH metrics can result in 11% decline of all-cause mortality, 19% lower risk of CVD mortality (18). In addition, previous meta-analysis also identified an inverse linear dose-response relationship between the number of ideal CVH metrics and incident type 2 diabetes (20). However, the association between LE8 and the risk of major NCDs or mortality remains underexplored. A systematic evaluation of the associations between CVH assessed by LE8 score with mortality and major NCDs will aid in the promotion of CVH for public health.

To address this gap, we performed a systematic review and meta-analysis synthesizing evidence from prospective cohort studies on the association between Life's Essential 8 (LE8) scores and risks of mortality and major NCDs in adults ≥18 years. Beyond comparative assessments of health benefits between optimal LE8 and poor CVH, we further conducted dose-response analysis to quantify gradient relationships between LE8 scores and these outcomes.

This systematic review was performed following the PRISMA 2020 guidelines (21) and was registered a priority in the PROSPERO database (CRD42024494354).

Figure 1 shows the systematic search and study selection process. A total of 6,007 records were identified (Supplementary Table S1). And another 33 studies were retrieved by other sources. After removing 2,468 duplicates and an additional 3,572 records were screened through title and abstracts. Finally, 45 studies met the inclusion criteria. Among them, 22 outcomes (all-cause mortality, CVD mortality, total cancer mortality, CVD, total cancer, stroke, heart failure, myocardial infarction, coronary heart disease, atrial fibrillation, venous thromboembolism, pancreas cancer, diabetes, NAFLD, all-cause dementia, Alzheimer's disease, vascular dementia, CKD, asthma, depression and anxiety, inflammatory bowel disease) were eligible for meta-analysis synthesis (Figure 1). Some outcomes were excluded for analysis due to limited literatures (Supplementary Table S3).

This systematic review demonstrates significant cardiometabolic and other health benefits associated with optimal CVH as quantified by the LE8 metric. Our results indicate that participants in the highest CVH score category experienced a 56% lower risk of all-cause mortality, a 67% lower risk of CVD mortality, a 49% lower risk of total cancer mortality, a 64% lower risk of CVD, a 25% lower risk of total cancer incidence, 46% lower risk of NAFLD and 88% lower risk of type 2 diabetes and a 35% lower risk of all-cause dementia compared to those in the lowest CVH score category. Most of these findings were consistent across sensitivity analyses. However, the reliability of some results requires further validation with more prospective cohort studies in future, particularly for those with high heterogeneity. In addition, A clear linear association was observed between CVH scores and the risk of all-cause mortality, total cancer mortality. In contrast, a non-linear relationship was identified between CVH scores and the risk of CVD mortality, CVD, stroke, myocardial infarction, and CKD.

The association between CVH and the risk of all-cause mortality, CVD mortality, and incident CVD has been previously reviewed using old definition of CVH, namely the LS7 metrics (17–19, 70). For instance, Fang et al. demonstrated that achieving a highest number of ideal CVH metrics (5–7) was associated with a significantly lower risk of all-cause mortality (RR = 0.55), CVD mortality (RR = 0.25), and incident CVD (RR = 0.20) compared to achieving the lowest number of ideal CVH metrics(0–2) (17). Guo et al. reported similar findings, with overall RRs of 0.54 for all-cause mortality, 0.30 for CVD mortality, and 0.22 for incident CVD when comparing the greatest to the lowest categories of ideal CVH metrics (18). The newly proposed LE8 framework not only incorporates sleep health into the CVH construct based on strong evidence linking sleep duration and cardiometabolic health (71), but also introduces a novel scoring algorithm to assess CVH. The present study systematically examined the association between CVH scores rather than the number of ideal metrics achieved, and the risk of all-cause, CVD, and total cancer mortality. We found that participants in the highest CVH score category exhibited significantly lower risks of all-cause mortality (RR = 0.44), CVD mortality (RR = 0.33), and CVD (RR = 0.36). And we for the first time revealed that high CVH score is associated with lower risk of total cancer mortality (RR = 0.51). These findings highlighted the fact that participants with higher CVH scores experience a substantial reduction in mortality and CVD incidence risk. These results are consistent with those of a recently published systematic review, which also reported that higher CVH was associated with significantly lower risks of all-cause mortality, CVD mortality, and incident CVD (72).

However, the high heterogeneity undermined the reliability of the results of all-cause mortality and incident CVD analysis. It also compromised the generalizability and translational impact of this study. Meta-regression did not identify any source of heterogeneity for the all-cause mortality. The variability in covariate adjustments across included studies might bias the polled estimates. For instance, the study led by Rempakos (62) only adjusted age and sex while other important covariates were not considered. In addition, most of the eligible 17 studies adjusted educational level (n = 12), race or ethnicity (n = 11), economic-related covariates (n = 11) while only 7 adjusted drinking status, CVD or cancer history. Marital status was adjusted only in four studies while it has been proved to be related to all-cause and cause-specific mortality (73). Moreover, in addition to these environmental exposures, genetics are known to play important roles in shaping health and mortality. There are only one studies that adjusted the polygenic risk scores (65). These unadjusted covariates residual confounding could bias the estimates. In addition, the subgroup analysis stratified by key study characteristics demonstrated no significant differences among different age, sample size, length of follow-up subgroups. It's noteworthy that studies conducted in Asia and developing countries showed less reduction of all-cause mortality risk. Meta-regression suggested that age was the source of heterogeneity for the CVD outcome. And there are significant differences among age subgroups with younger aged subgroups having larger reduction of risk. It's possible that younger participants have better health status that having small number of events. Moreover, subgroup analysis suggested that studies conduced in North America have the largest reduction of CVD risk. Because studies in subgroup shares same studies in the younger age subgroups.

How high CVH contribute to lower risk of mortality and CVD should be deeply understood. Previous studies have suggested that adults with high (12–14 points) or even moderate (8–11 points) LS7 scores exhibit significantly lower odds of coronary artery calcium, reduced carotid intima-media thickness, and lower left ventricular mass compare to adults with low LS7 scores (74). Biologically mechanism investigations have identified several potential pathways involving inflammation, endothelial function, atherosclerosis, cardiac stress, and epigenetics (75, 76). In fact, all four health behaviors (smoking, diet, physical activity and sleep) and the four health factors (BMI, cholesterol, glucose and blood pressure) contribute to the risks of health outcomes and have been jointly or independently associated with cardiometabolic health (77–80). Furthermore, these factors are also recognized as common risk factors for the global disease burden. In 2021, high systolic blood pressure, smoking, high fasting plasma glucose, and high BMI contributed 7.8%, 5.7%, 5.4%, and 4.5% to the total disability-adjusted life-years (DALYs), respectively (81). Therefore, achieving a high score in CVH metrics would significantly reduce the risk of all-cause mortality, CVD mortality, and CVD events.

Additionally, our study is the first to identify a linear dose-response relationship between LE8 score and all-cause mortality. This finding aligns with the linear dose-response relationship between CVH metrics and all-cause mortality reported in previous reviews base on the number of ideal CVH metrics (18, 19). However, unlike those reviews which found a linear dose-response relationship between the number of ideal CVH metrics and outcomes (18, 19), we observed a non-linear dose-response relationship between LE8 score and CVD mortality. We also analyzed the association between CVH and individual CVD events, including stroke, myocardial infarction, coronary heart disease (CHD), heart failure(HF), and atrial fibrillation(AF). Similar to Sebastian's study (72), which found that a high LE8 score was associated with a 48% lower risk of stroke and a 56% lower risk of CHD, our analysis identified a 54% lower risk of stroke and a 67% lower risk of CHD, respectively. Our study also identified a 64% and 80% lower risk of HF and AF, respectively.

Moreover, several studies have explored the association between the LE8 metrics and risk of type 2 diabetes. A previous meta-analysis indicated that individuals with the highest number of ideal CVH metrics had a 64% lower risk of developing diabetes compared to those in the lowest category. Additionally, a nonlinear dose-response meta-analysis suggested a monotonic reduction in the risk of diabetes (20). Similarly, our finding revealed that participants in the highest LE8 score category exhibited a significant lower risk of diabetes. It's rational that high CVH has a positive effect on risk of diabetes. It is reasonable to infer that high CVH scores have a positive effect on reducing the risk of diabetes, given that CVD and diabetes share considerable common risk factors, such as physical inactivity, obesity and unhealthy diet. However, due to the limited availability of eligible literatures, the heterogeneity is very high and hard to explore source of heterogeneity.

In addition, no meta-analyses have assessed the relationship between the ideal CVH status and the risk of cancer. A previous prospective cohort study reported that after a median follow-up of 13 years, individuals with the lowest number of ideal CVH metrics had a 52% greater risk of incident cancer compared to those with highest number of CVH metrics (15). Our finding similarly indicated a modestly lower risk of incident cancer among individuals with high CVH scores. Several components of LE8 are also recognized as risk factors of cancer. For instance, globally in 2019, the leading risk factors contributing to cancer deaths were smoking, followed by alcohol use, high BMI, high fasting plasma glucose, and unhealthy diet (82). Additionally, physical inactivity is a common risk factor for various cancers, including colon and lung cancer (83). The relationship between physical activity, sedentary behavior, and obesity with cancer incidence can be explained by the interaction involving endogenous sex steroids and metabolic hormones, insulin sensitivity, and chronic inflammation (84). However, due to the limited availability of relevant literatures, a dose-response meta-analysis was not feasible in our study.

Similarly, no meta-analyses have evaluated the relationship between ideal CVH status and the risk of NAFLD. NAFLD is a major cause of liver disease worldwide, with its global prevalence increasing rapidly. The estimated global incidence of NAFLD is 4,613 cases per 100,000 person years, and overweight/obese individuals are approximately threefold more likely to develop NAFLD compared to those with normal weight. Additionally, smokers had higher NAFLD incidence than non-smokers (85). NAFLD is associated with an increased risk of CVD (86) and T2DM (87). Numerous studies have demonstrated that lifestyle modification, such as healthy diet, physical activity, and weight loss, are effective strategies for the prevention and management of NAFLD in clinical practice (88). Therefore, it is reasonable to hypothesize that ideal CVH status have a positive effect on reducing the risk of NAFLD. Our results indicated that individuals in the highest CVH score category had a substantially lower risk of new incident NAFLD compared to those in the lowest CVH score category. Although there are only two studies eligible for NAFLD analysis, they consistently reported protective effects of ideal CVH status. Previous studies have shown that NAFLD is significantly associated with metabolic syndrome and healthy lifestyles which are intrinsic components of LE8 (89, 90). Obesity and related inflammation promote insulin resistance which induces inappropriate lipolysis and lead to elevated free fatty acid in the circulation. These fatty acids were uptaken by the liver and hepatic de-novo lipogenesis together contribute to the NAFLD.

The relationship between CVH and dementia has been previously analyzed. Wu et al. (91) suggested that following the LS7, individuals with the highest number of ideal CVH metrics had a 6% lower risk of dementia, showing a linear association with late-life dementia risk. However, a J-shaped association was observed between late-life CVH scores and dementia risk. Our study found a 35% lower risk of all-cause dementia. We also analyzed vascular dementia and AD, and high CVH scores were consistently negatively associated with incidence of both vascular dementia and AD. It is reasonable to conclude that all four health behaviors (smoking, diet, physical activity, and sleep) and the four health factors (BMI, cholesterol, glucose, and blood pressure) contribute to the risks of dementia. Previous studies have provided strong evidence that physical inactivity, smoking, unhealthy diet, obesity, and high blood pressure are independently or jointly associated with dementia (92, 93).

One of the strengths of this study is the quantification of the dose-response association between the newly proposed LE8 and various health outcomes. However, our meta-analysis has several limitations. First, there is significant heterogeneity among the included studies, with the sources of this heterogeneity remaining unclear. Second, considerable differences exist in the confounders adjusted across studies, which may compromise the reliability of the results. Some studies adjusted only for age and sex, while important potential risk factors such as educational level, history of CVD, alcohol intake were not considered. In addition, the small sample size in some studies might bias the pooled estimates. Finally, due to limited availability of eligible literatures, the robustness of some outcomes required further validation. In addition, dose-response meta-analysis could not be performed for some outcomes.

This meta-analysis suggested that ideal CVH status is associated with a reduced risk of all-cause mortality, CVD mortality, total cancer mortality and incident CVD. It also demonstrated a trend of lower risk of several chronic diseases including NAFLD, all cause dementia, etc. And each 10 points increase in CVH can result in substantial reductions in risk of all-cause mortality, CVD mortality, incident CVD and all-cause dementia. There's a linear dose-response relationship between CVH score and all-cause mortality, total cancer mortality and a nonlinear dose-response relationship between CVH score and CVD mortality, incident CVD, NAFLD, stroke, myocardial infarction.