Summary: People with lower EPA and DHA in red blood cell membranes, which correlates to lower scores on the Omega-3 index, were found to have an increased risk of cardiovascular disease and ultimately a decrease in lifespan compared to those who scored higher on the omega-3 index.
Source: FARI
A new research paper published in the American Journal of Clinical Nutrition last week showed that a low Omega-3 Index is just as powerful in predicting early death as smoking. This landmark finding is rooted in data pulled and analyzed from the Framingham study, one of the longest running studies in the world.
The Framingham Heart Study provided unique insights into cardiovascular disease (CVD) risk factors and led to the development of the Framingham Risk Score based on eight baseline standard risk factors–age, sex, smoking, hypertension treatment, diabetes status, systolic blood pressure, total cholesterol (TC), and HDL cholesterol.
CVD is still the leading cause of death globally, and risk can be reduced by changing behavioral factors such as unhealthy diet, physical inactivity, and use of tobacco and alcohol. Therefore, researchers in this study say biomarkers integrating lifestyle choices might help identify individuals at risk and be useful to assess treatment approaches, prevent morbidity, and delay death.
Among the diet-based biomarkers are fatty acids (FAs), whether measured in plasma or red blood cell (RBC) membranes. The FAs most clearly associated with reduced risk for CVD and for total mortality (i.e., death from any cause) are the omega-3 FAs, EPA and DHA, which are typically found in fish like salmon and herring, as well as omega-3 supplements like fish and algal oil.
In a 2018 report that included 2500 participants in the Framingham Offspring Cohort followed for a median of 7.3 years (i.e., between ages ?66 and 73), the baseline RBC EPA + DHA content [the omega-3 index (O3I)] was significantly and inversely associated with risk for death from all causes.
In fact, individuals with the highest Omega-3 Index were 33% less likely to succumb during the follow-up years compared with those with the lowest Omega-3 Index. Similar associations have been seen in the Women’s Health Initiative Memory Study, the Heart and Soul Study, and the Ludwigshafen Risk and Cardiovascular Health Study.
The Omega-3 Index measures the amount of EPA and DHA in red blood cell membranes and is a marker of omega-3 status. An optimal Omega-3 Index is 8% or higher, an intermediate Omega-3 Index is between 4% and 8%, and a low Omega-3 Index is 4% and below. Most Americans have an Omega-3 Index below 4%, which puts them a significantly higher risk of early death.
According to researchers in this study, the finding that any FA-based metric would have predictive power similar to that of the well-established standard risk factors was unexpected, and it suggests that RBC FAs–via imperfectly understood mechanisms–somehow reflects an in vivo milieu that consolidates into one measure the impact on the body of all these standard risk factors.
“It is interesting to note that in Japan, where the mean Omega-3 Index is greater than 8%, the expected life span is around five years longer than it is in the United States, where the mean Omega-3 Index is about 5%. Hence, in practice, dietary choices that change the Omega-3 Index may prolong life,” said Michael McBurney, PhD, FCNS-SCN, lead researcher in this study.
“In the final combined model, smoking and the Omega-3 Index seem to be the most easily modified risk factors. Being a current smoker (at age 65) is predicted to subtract more than four years of life (compared with not smoking), a life shortening equivalent to having a low vs. a high Omega-3 Index.”
“The information carried in the concentrations of four red blood cell fatty acids was as useful as that carried in lipid levels, blood pressure, smoking, and diabetic status with regard to predicting total mortality,” said Dr. Bill Harris, who was also an author on this study.
“This speaks to the power of the Omega-3 Index as a risk factor and should be considered just as important as the other established risk factors, and maybe even more so.”
Funding: This work was supported in part by the Institute for the Advancement of Food and Nutrition Sciences (IAFNS) through an International Life Sciences Institute North America Lipid Committee grant. IAFNS is a nonprofit science organization that pools funding from industry collaborators and advances science through the in-kind and financial contributions from public and private sector participants.
About this omega-3 research news
Source: FARI
Contact: William Harris – FARI
Image: The image is in the public domain
Original Research: Closed access.
“Using an erythrocyte fatty acid fingerprint to predict risk of all-cause mortality: the Framingham Offspring Cohort” by William Harris et al. American Journal of Clinical Nutrition
Abstract
Using an erythrocyte fatty acid fingerprint to predict risk of all-cause mortality: the Framingham Offspring Cohort
Background
RBC long-chain omega-3 (n–3) fatty acid (FA) percentages (of total fatty acids) are associated with lower risk for total mortality, but it is unknown if a suite of FAs could improve risk prediction.
Objectives
The objective of this study was to compare a combination of RBC FA levels with standard risk factors for cardiovascular disease (CVD) in predicting risk of all-cause mortality.
Methods
Framingham Offspring Cohort participants without prevalent CVD having RBC FA measurements and relevant baseline clinical covariates (n = 2240) were evaluated during 11 y of follow-up. A forward, stepwise approach was used to systematically evaluate the association of 8 standard risk factors (age, sex, total cholesterol, HDL cholesterol, hypertension treatment, systolic blood pressure, smoking status, and prevalent diabetes) and 28 FA metrics with all-cause mortality. A 10-fold cross-validation process was used to build and validate models adjusted for age and sex.
Results
Four of 28 FA metrics [14:0, 16:1n–7, 22:0, and omega-3 index (O3I; 20:5n–3 + 22:6n–3)] appeared in ≥5 of the discovery models as significant predictors of all-cause mortality. In age- and sex-adjusted models, a model with 4 FA metrics was at least as good at predicting all-cause mortality as a model including the remaining 6 standard risk factors (C-statistic: 0.778; 95% CI: 0.759, 0.797; compared with C-statistic: 0.777; 95% CI: 0.753, 0.802). A model with 4 FA metrics plus smoking and diabetes (FA + Sm + D) had a higher C-statistic (0.790; 95% CI: 0.770, 0.811) compared with the FA (P < 0.01) or Sm + D models alone (C-statistic: 0.766; 95% CI: 0.739, 0.794; P < 0.001). A variety of other highly correlated FAs could be substituted for 14:0, 16:1n–7, 22:0, or O3I with similar predicted outcomes.
Conclusions
In this community-based population in their mid-60s, RBC FA patterns were as predictive of risk for death during the next 11 y as standard risk factors. Replication is needed in other cohorts to validate this FA fingerprint as a predictor of all-cause mortality.
