On this episode of Lifespan News, we discuss research that describes how four fatty acids are correlated with increased or decreased longevity.
The results of a long-term human study published in the American Journal of Clinical Nutrition have shown that a model built on the concentration of four fatty acids predicts mortality in older people at least as well as a model that uses smoking and diabetes.
The study included well over 2000 participants from the Framingham Offspring Cohort with an average age of 65, and monitored them for eleven years in order to measure which characteristics are most likely to lead to survival or death during that time frame.
Myristic acid, which is found in coconut milk, dairy, and some baked products, was shown to increase average lifespan by 1.4 years per quintile, meaning that the 20% of people with the highest levels myristic acid in the bloodstream lived an average of over 5.6 years longer than people in the bottom 20%.
Previous research has shown that behenic acid, which is found in peanuts, macadamia nuts, and canola oil in addition to being produced in the human body, is negatively correlated with coronary heart disease. In this study, the people with behenic acid levels in the top quintile lived an average of nearly 3.2 years longer than people in the bottom quintile.
Regarding the popular supplement omega-3, commonly found in fish, the 20% of people with the highest levels of omega-3 were found to live over 4.7 years longer than the lowest 20%. While the three previous fatty acids were positively correlated with lifespan, palmitoleic acid, which is found in macadamia oil, has a strongly negative correlation. People with an upper quintile of palmitoleic acid in the bloodstream were found to have a lifespan an average of 6.6 years shorter than people in the lower quintile.
While it might be tempting to assume that this study means that coconut milk, peanuts, and canola oil will lead to a beneficial increase in lifespan while macadamia oil should be avoided, it’s far too early, and there are far too many variables, to draw those conclusions. There are important questions that this study does not answer, such as why these correlations exist and what the causation is, so it is up to other studies to build on this work.