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https://www.imim.cat/news/view.php?ID=410
Having higher levels of omega-3 acids in the blood increases life expectancy by almost five years
A 1% increase in this substance in the blood is associated with a change in mortality risk similar to that of quitting smoking
Levels of omega-3 fatty acids in the blood are as good a predictor of mortality from any cause as smoking, according to a study involving the Hospital del Mar Medical Research Institute (IMIM), in collaboration with The Fatty Acid Research Institute in the United States and several universities in the United States and Canada. The study, published in The American Journal of Clinical Nutrition, used data from a long-term study group, the Framingham Offspring Cohort, which has been monitoring residents of this Massachusetts town, in the United States, since 1971.
Researchers have found that omega-3 levels in blood erythrocytes (the so-called red blood cells) are very good mortality risk predictors. The study concludes that "Having higher levels of these acids in the blood, as a result of regularly including oily fish in the diet, increases life expectancy by almost five years", as Dr. Aleix Sala-Vila, a postdoctoral researcher in the IMIM's Cardiovascular Risk and Nutrition Research Group and author of the study, points out. In contrast, "Being a regular smoker takes 4.7 years off your life expectancy, the same as you gain if you have high levels of omega-3 acids in your blood", he adds.
2,200 people monitored over eleven years
The study analysed data on blood fatty acid levels in 2,240 people over the age of 65, who were monitored for an average of eleven years. The aim was to validate which fatty acids function as good predictors of mortality, beyond the already known factors. The results indicate that four types of fatty acids, including omega-3, fulfil this role. It is interesting that two of them are saturated fatty acids, traditionally associated with cardiovascular risk, but which, in this case, indicate longer life expectancy. "This reaffirms what we have been seeing lately", says Dr Sala-Vila, "not all saturated fatty acids are necessarily bad." Indeed, their levels in the blood cannot be modified by diet, as happens with omega-3 fatty acids.
These results may contribute to the personalisation of dietary recommendations for food intake, based on the blood concentrations of the different types of fatty acids. "What we have found is not insignificant. It reinforces the idea that small changes in diet in the right direction can have a much more powerful effect than we think, and it is never too late or too early to make these changes", remarks Dr Sala-Vila.
The researchers will now try to analyse the same indicators in similar population groups, but of European origin, to find out if the results obtained can also be applied outside the United States. The American Heart Association recommends eating oily fish such as salmon, anchovies or sardines twice a week because of the health benefits of omega-3 acids.
Reference article
Michael I McBurney, Nathan L Tintle, Ramachandran S Vasan, Aleix Sala-Vila, William S Harris, Using an erythrocyte fatty acid fingerprint to predict risk of all-cause mortality: the Framingham Offspring Cohort, The American Journal of Clinical Nutrition 2021; nqab195, https://doi.org/10.1093/ajcn/nqab195
https://www.sciencedirect.com/science/article/pii/S0002916522004737
https://archive.is/1fUTW
Using an erythrocyte fatty acid fingerprint to predict risk of all-cause mortality: the Framingham Offspring Cohort
ABSTRACT
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.