Welcome to Straight Talk on Health. I’m your host Dr. Chet Zelasko. Straight Talk on Health is a joint production with WGVU in Grand Rapids MI. I examine the world of health: Nutrition, exercise, diet, supplementation. If there’s something new, I look at the science behind them, and let you know whether it’s real or not. You can check out other things that I do on my website Drchet.com and sign up for my free emails.
Scientists continue to research the causes of obesity. In the study I’m going to review this week, the researchers are going pre-natal. The Copenhagen Prospective Studies on Asthma in Childhood 2010 is an ongoing longitudinal study to examine the effects of omega-3 supplementation in the third trimester of pregnancy on a number of factors. The primary objective was to see if allergies and asthma were reduced in the offspring of women who took the omega-3s versus those who took a placebo. Asthma or persistent wheeze showed a 31% reduction in risk in the group receiving fish oil compared to 23% the placebo group. Not overwhelming but a positive benefit.
The researchers also collected a variety of anthropometric data, assessed body composition, and took blood samples for metabolic and blood lipid measures. In a prior paper when the children were age 6, the omega-3 group were about 1 pound heavier but with a proportional increase in lean and fat mass.
In the current analyses at age 10, the omega group were determined to have an increased BMI, increased risk of being overweight, a tendency of increased fat percentage and higher metabolic syndrome score when compared to the placebo group. That doesn’t sound good. Does this mean women should avoid omega-3 fish oil during pregnancy, especially the third trimester? Let’s dig deeper.
These are excellent researchers. There is nothing questionable about the design of this study for the most part, or in the way they collected and analyzed data. What I would question are some of their methodologies, and the way they interpreted the data to arrive at their conclusions. I think the best place to begin is by reading the conclusion statement of the abstract. Let's take a look at what they said and then examine the data from the paper to see if it supports it. Here we go:
“In this randomized clinical trial, children of mothers receiving n–3 LCPUFA supplementation had increased BMI at age 10 y, increased risk of being overweight, and a tendency of increased fat percentage and a higher metabolic syndrome score. These findings suggest potential adverse health effects from n–3 LCPUFA supplementation during pregnancy and need to be replicated in future independent studies.”
Let's break this down a little bit. I like to start with the means and standard deviations. When you look at the difference in body weight, there was a 2 pound difference between the fish oil group weighing more than the placebo group. Neither group was classified as being overweight by the international standards. With height being equal, that meant that the BMI would be higher in the fish oil group. Is that meaningful in the real world? The BMI of both groups were considered to be healthy at 17.4 versus 16.9 looking at the raw numbers. In fact when you consider the range of BMI for 5 to 10 year olds, one could argue that they were below normal weight.
The increased risk of being overweight has to do with the rate of change in weight over time. It's called Adiposity Rebound and it was not significantly different. The comment “increased risk of being overweight” isn't necessarily supported by that data in any way I can see.
I'm going to skip the tendency of increased percentage of body fat for now and move to the higher metabolic syndrome score. Metabolic Syndrome is the risk of developing diabetes. The researchers calculated the score using an algorithm that considered waist circumference, systolic BP, negative HDL cholesterol, the log of triglycerides, and the Homeostatic Model Assessment for Insulin Resistance or HOMA-IR for short. I'll be the first to admit that I'm not a statistical whiz but this is why I question the outcome. There was a 3/10 of an inch difference in waist circumference with the fish oil group being slightly higher. There was no difference in triglyceride levels and the fish oil group had a higher HDL cholesterol level then the control group. There was no difference in systolic blood pressure between the groups. That leaves us with the HOMA-IR Calculation.
Here's what I question: typically, serum insulin would need to be used in the calculation to determine the HOMA-IR number. They did not assess that data from the blood collected. Therefore they used another indicator of insulin levels in calculating the HOMA-IR. The problem is this: when I looked up the reference for using that calculation, that algorithm was based on 21 adult subjects and it was never validated in a larger group nor in children. To use that on children doesn't seem like a reasonable thing to do. In my mind, the entire calculation done to assess risk is suspect as there were no meaningful differences in any variable. But looking at means and SD only can hide things. So, for arguments sake, let's say that despite the modification of how the HOMA-IR was calculated, that could even itself out.
The real problem that I have is with the remark about a tendency towards increased percent body fat. At six years old, they used what's called a DEXA scan to assess body composition. That has become the state-of-the-art. But when they assessed body composition at 10 years of age, they used Bioelectrical Impedance Analysis or BIA for short. You may actually own a scale that calculates body fat in that way. I worked on BIA when I was a graduate student. There are two things that are concerning when using BIA to assess body composition. First, the algorithm is 95% dependent on height and weight. It could be that there are new algorithms today but a 2 pound difference in body weight in children could impact the calculation. Secondly, BIA is extraordinarily sensitive to fluid levels of the body. It was first developed to assess total body water in people with congestive heart failure. It assesses total body water and calculates fat mass by making assumption about the water content of the remaining tissues. Under those controlled hospital conditions, it can work quite well. It doesn’t seem like the best way to assess body fat in a major study and especially when assessing children.
How? I hear that a lot when my grandson plays a video game. When something happens that he doesn't anticipate or understand, he screams out How? And that's what I screamed when I read the conclusions. The most frustrating part of this research paper is that their conclusion is that omega-3 supplementation in the last trimester of pregnancy may result in adverse effects to the children. What frustrates me is that they give absolutely no mechanism of action. How would supplementing with omega-3 fatty acids cause the offspring to have an increased risk of being overweight or obese, especially when the supplementation began in the third trimester? Perhaps in the first trimester as the fetus is developing but in the third? What genes would be activated or mutated that would result in obesity?
There are other questions that I have as well. There was no nutritional data taken on the mothers. We don't know how many omega-3 fatty acids they got from their normal dietary intake that they ate during the study. Also, they didn't use an omega-3 blend from plant sources and they didn't use omega-3s from food sources either. Those would certainly make the study more complex but as it stands now we really don't know much more then we did in 2010 when the study began other than the kids whose mother took omega-3 fatty acid had fewer serious asthma and allergy symptoms. As for body composition and the impact on future obesity? Not so much. But the observations will continue through adulthood so time will tell. As for me, I’m all out of time so until next time, this is Dr. Chet Zelasko saying health is a choice. Choose wisely today and every day.
Reference:
1. BMJ 2018. doi: https://doi.org/10.1136/bmj.k3312
2. AJCN. 2024. doi.org/10.1016/j.ajcnut.2023.12.015
