Fish Oil and Atrial Fibrillation

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Researchers recently published an observational study on over 415,000 subjects in the UK Biobank database who took a fish oil supplement. During a follow-up period of almost 12 years, they statistically demonstrated a 13% increased hazard ratio (a measure over time of how often a particular event happens in one group compared to another group) in the development of atrial fibrillation in subjects. Atrial fibrillation is a type of arrhythmia, or abnormal heartbeat, that can result in extremely fast and irregular beats from the upper chambers of the heart. In those subjcts, there was a 5% increased risk of stroke.

The resultant impact was an attack on dietary supplements for being too easily available, leading to overconsumption, and questionable because of the lack of purity in dietary supplements. The Medscape Cardiology online section put out a video by a reputable researcher explaining who should take fish oil supplements. But if they’re so bad, why would she recommend them at all?

The other part of the results showed that if someone already had cardiovascular disease (CVD), the hazard ratio of developing major cardiac events was reduced if they took fish oil supplements. That’s why the expert made the video, taking the good and trying to make sense of it. Still, it gave the appearance of being a pitch for a pharmaceutical solution.

That’s the set-up for this week’s Memos. I’ll give you at least one of the questions you might have: Yes, this study tested only supplement use (and dietary intake) upon entrance to the study and nothing the rest of the 11.9 years, just like the multivitamin study from last week. But there’s so much more that I’ll cover on Saturday about the problems with this study. Just so you know, I’m still taking my fish oil supplements.

What are you prepared to do today?

        Dr. Chet

Reference: BMJMED 2024;3:e000451.doi:10.1136/ bmjmed-2022-000451

Nothing to Fear from the Multivitamin Study

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If you’re concerned about taking your multivitamin, I think you can lower the concern. Is it still possible that there may be individuals who may have a unique set of genes and covariates that may increase the risk? Sure, it’s possible, but this study brought us no closer to finding out if that’s true. Here’s why.

The Issues with the Study

The problems lie in what the researchers didn’t do.

While the researchers used 13 different covariates, they didn’t break the data down by macronutrient or micronutrient. They used the Healthy Eating Index, but that ranks the quality of the diet from 0 to 100; that’s not the same as breaking the subjects’ diets down by intake of vegetables or antioxidants. It’s possible that someone who ate more vegetables could have higher antioxidant levels, which could contribute to getting too much of a nutrient by taking a multivitamin. The same would be true if they also were taking a complete multivitamin-multimineral and getting too much calcium or iron. That might have given valuable information to the people most at risk if there were such a relationship.

The researchers also did not give any explanation for mechanisms through which a multivitamin could increase mortality. That’s not unusual, because they didn’t examine any nutrient factors—but still, what was the point of saying there may be an increase in mortality, but nothing more than that?

The most likely explanation is that the results happened by chance because they tested multivitamin intake only twice early in the studies. Think of what you were eating 20 years ago. Has that changed? It’s reasonable to expect that some peoples’ habits changed, just as their dietary intake may have changed. We don’t know because they couldn’t go back and do the questionnaires every year or two, or even every five years. They suggest that this was a problem due to the latency of the data, and they were correct in my opinion.

The Bottom Line

This study illustrates the problem with going back to analyze data collected decades ago: you’re limited by the data you have rather than actually planning the study from the beginning. It’s an interesting observation after chunking lots of numbers, but it’s not meaningful in the real world due to the lack of ability to do an adequate analysis of the data.

What are you prepared to do today?

        Dr. Chet

Reference: JAMA Network Open. 2024;7(6):e2418729.

Will Taking a Multivitamin Increase Your Risk of Death?

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Close to a month ago, the health headlines were full of warnings about multivitamins. A long-time researcher even did a video to explain the study. This headline was based on a study that demonstrated an increase in Hazard Ratio if a person took a multivitamin every day, compared to occasionally or never. On the face of it, this seemed to be a compelling study. Data were combined from three large studies that totaled over 390,000 participants. The data were taken from health and nutrition questionnaires first given more than 20 years ago, with the mean follow up time of about 21 years. The questionnaires asked about a variety of demographic data as well as health and nutrition habits; the nutrition data were the old-style FFQ form.

After analyzing the data, researchers found a 4% increase in mortality risk in those participants who took a multivitamin every day compared to those who did not. Should you be worried? Aside from the number of covariates they considered, and you know how those combinations can add up, there were at least two problems. I’ll cover those on Saturday.

The Winners of the Challenge

Everyone who responded to the 4th of July challenge did an amazing job—no one had fewer than 20 vegetables and fruits. Where it got a little murky was in the herbs and spices; I’ll take the blame for that as I didn’t explain it as well as I should. For the overall total, I’m going to declare a tie between RE and KB; they each had close to 60 foods that qualified! For vegetables alone, VK topped the list with 23 and MW topped the fruit list with 13. Great job, everybody!

What are you prepared to do today?

        Dr. Chet

Reference: JAMA Network Open. 2024;7(6):e2418729.

Nutritional Epidemiology: Still Confusing

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Remember where we began: frustrated with the conflicting studies on nutrition and their impact on our health. The researchers used specification curve analysis to illustrate several issues. The most important point is that there are many ways to analyze large datasets in nutritional epidemiology. Reviewing 15 studies in 24 papers, they found that the number of ways to analyze the data could reach 10 quadrillion (that’s 10,000,000,000,000,000). Obviously, that’s not realistic.

Instead, the approach that could be used by researchers doing these types of studies in any field is to select a randomized sample of different analytical approaches and present the results in the way I did in Tuesday’s Memo. Using that approach showed that fewer than 4% of the studies reached statistical significance. But how much of that could be just dumb luck? Setting the probability of significance at less than .05 (which is most common) means that out of 100 statistical approaches, five could show significance just by chance alone.

This paper addresses a long-standing problem in nutritional research and other areas as well. Researchers who do these types of longitudinal studies already use different analytic techniques in a haphazard way. They just keep chunking data until they find an analytic approach that’s statistically significant, and that’s the one they publish, sort of like a thief checking car doors until he finds one unlocked. Journals won’t publish results that don’t demonstrate significance, even though that would be beneficial for others to find out what not to do. “Publish or perish” just doesn’t work that way.

The Bottom Line

In this series of Memos, I’ve tried to lay out one of the reasons that long-term nutritional studies that look at morbidity and mortality can be flawed, if not contradictory. To be sure, the statistical analyses I’ve talked about are complicated, but that wasn’t my purpose. It’s to let you know that because of the lack of hard and fast rules for outlining the statistical approaches before looking at the data (as is done in randomized controlled trials), the results and the interpretation of those results will always be suspect.

In plain words, never get too excited about longitudinal studies, whether positive or negative. In the coming weeks, I’ll examine some studies on fish oil and multivitamins to illustrate the points I’ve tried to make.

By the way, for those of you really wanting to know whether you should eat red meat based on the analytic study the researchers tested as an example, they stated that there were some holes in the NHANES data that could impact the outcomes they reported. For now, it seems that women may benefit more from eating red meat than men will, but there’s no definitive answer yet.

What are you prepared to do today?

        Dr. Chet

References:
1. https://www.sensible-med.com/p/the-definitive-analysis-of-observational
2. Journal of Clinical Epidemiology 168 (2024) 111278

Nutritional Epidemiology: Specification Curve Analysis

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Did you look up quadrillion? It’s a 1 with a whole lot of 0s—15 to be exact.

When I finished Saturday’s Memo, the researchers had chosen an area of nutritional epidemiology to focus on: the analytics used to analyze the data. They began with the premise that there are many ways to analyze any data set. They then identified published research studies that examined the consumption of red meat and mortality. They identified 15 publications reporting on 24 studies that examined the effect of red meat on all-cause mortality.

They weren’t doing a meta-analysis to see all the results of all the studies combined; they used a newer technique called specification curve analysis. They identified the type of data used in the analysis, the number of variables, the number of covariates, as well as demographic data. From that information, they then calculated the total number of ways each data set could be analyzed—the specification curve analysis. Turns out that number is 10 quadrillion! That exceeds the capacity of the computing power of a small country, and I can’t even imagine how much electricity that would consume.

They decided to take a randomized sample of the possible ways to analyze the data with specific variables and covariates in each and came up with 1,440 different approaches to analyzing the data. They ran additional tests on the data and eliminated 232 approaches because the data exceeded norms.

Then they ran the remaining analytic approaches on data from several years of the NHANES study. What did they find?

  • The median hazard ratio (HR) was 0.94 for the effect of red meat on all-cause mortality. That means the mortality risk was decreased 6% if the subject ate red meat.
  • HRs ranged from 0.51 to 1.75; 435 approaches yielded HRs more than 1.0 (increased risk) and 773 less than 1.0 (decreased risk). Most analyses showed that eating red meat reduced the HR, and thus reduced the risk of dying.
  • Of all the results, 48 (almost 4%) were statistically significant; of those, 40 indicated that red meat reduced all-cause mortality and 8 that red meat increased all-cause mortality.

Does this mean that eating red meat decreases your risk of dying early? We’re not done yet. We’ll put it all in perspective on Saturday.

What are you prepared to do today?

        Dr. Chet

References:
1. https://www.sensible-med.com/p/the-definitive-analysis-of-observational
2. Journal of Clinical Epidemiology 168 (2024) 111278

Nutritional Epidemiology: The Problem

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The health headline shouts: “Fish oil increases your risk of heart disease.” The next week, “Fish oil beneficial for reducing risk of Alzheimer’s disease.” It makes one wonder what is going on in research. I’ve felt that way for a long time, and I know you have as well. I think I’ve found part of the problem, and I’m going to talk about in the next three Memos. As I said, this involves statistics, but I’ll keep it as simple as I can; we’ll be talking about some heavy duty statistical analytics, but there’s no math in my approach.

The frustration with conflicting research outcomes is especially prevalent in nutrition studies. It also happens in other fields as well including treatments for cardiovascular disease. Dr. John Mandrola, a cardiologist, wrote about a paper that examined why nutritional epidemiology is subject to conflicting results. After reading his post, I listened to the interview he had with the principal investigator of that study; then I read the paper itself. Statistics are not my forte but putting aside the high-level math, what they did was pretty amazing. By reviewing the paper here, I think you’ll get a better understanding of why research papers yield differing results even when using the same database of subjects.

Let’s begin with what has become accepted in the nutritional literature: eating red meat increases your risk of all-cause mortality. I know that many readers have given up or severely restricted red meat because so many physician, dietetic, and other health organizations have said it’s bad for your heart, among other organs. But is it really?

I used the phrase “nutritional epidemiology.” Those are studies that use some form of diet record, usually a Food Frequency Questionnaire, to track the food intake of a large group of people. Then they are tracked for 5, 10, even 20 or more years to see the differences in mortality between groups who ate red meat and those who did not. This contrasts with randomized controlled trials; they generally have as few as six subjects up to several hundred. They’re difficult to do because of the labor intensity of collecting data and ensuring subjects adhere to the protocol, whether a diet, specific foods, or dietary supplement.

With that in mind, the researchers examined all the nutritional epidemiological studies on the relationship of eating red meat and all-cause mortality. They then calculated all the ways that the data could be analyzed given the number of outcome variables and covariates used. We’ll pick it up on Tuesday, but as a tease, look up how much a quadrillion is.

What are you prepared to do today?

        Dr. Chet

References:
1. https://www.sensible-med.com/p/the-definitive-analysis-of-observational
2. Journal of Clinical Epidemiology 168 (2024) 111278

How Did You Do in the Holiday Challenge?

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Did you keep track of the fruits and veggies you ate over the holiday weekend (or July 4–7 for those of you outside the U.S.)? Remember to email me your results. Some people didn’t need reminding—I have already gotten replies.

I didn’t do as well as I would have liked. Here are my lists:

  • Vegetables: tomatoes (multiple varieties), lettuce, asparagus, artichokes, cucumber, red onion, shallots, avocado, mushrooms, prickly pear, basil.
  • Fruit: oranges, grapes, cherries, apples, blueberries, raspberries, watermelon, corn on the cob, potatoes, raisins, garlic.
  • Condiments: ketchup and mustard

I know that technically tomatoes and avocado are fruit, but savory is savory in my head. I bought a couple that I haven’t used before, fresh ginger and daikon radish, but then never worked them into the menu. Both last, so I’ll have them soon. That brings my total to 24 for the weekend. I’m guessing many of you are going to exceed my attempt—and that would be great.

Saturday I’m going to begin a three-Memo arc on statistics. This applies to the study on ultra-processed food as well as the recent one on multivitamins. Even though it’s about statistics, you’ll be able to understand it. It’s important for you to have this foundation to make sense of the studies that you hear about these days.

What are you prepared to do today?

        Dr. Chet

Start Your Lists!

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A reminder that today is the beginning of the Holiday Fruit and Vegetable Challenge. There will be three prizes this time:

  • The most plant-based foods (but you have to exceed JB’s record of 28 vegetables, fruits, and herbs)
  • The greatest number of different vegetables
  • The greatest number of different fruits

Start keeping track this morning and keep going until bedtime Sunday. I’m keeping my list as well.

Winners can choose between a free six-month Insider membership or the digital Optimal Performance program.

What are you prepared to do today?

        Dr. Chet

The Holiday Challenge, Part 2

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I enjoyed the Memorial Day Challenge so much, I want to see if you can do better. I want more of you to respond this time, so I’m going to make it a little more enticing for you by handing out more prizes. This time, I’m going to reward the person who eats the most plant-based foods, but because there is an extra day, you have to exceed the past winner’s record of 28 vegetables, fruits, and herbs. I’ll also reward the person with the greatest number of different vegetables as well as the greatest number of different fruits. Just start keeping track the morning of July 4th and keep going. It was almost all women who responded last time—men, you need to step up and get in the game.

Expand your horizons and try some new veggies. Challenge yourself to eat something other than Romaine or iceberg lettuce for salads, although they certainly count. Try arugula or bok choy, or switch it up and grill some peaches or eggplant. For this challenge, corn on the cob counts as a vegetable instead of a grain. Melon, tomatoes, berries of all types, as well as bananas and apples count.

The goal is to increase your phytonutrient intake by a massive amount. Vegetables and fruit all have some nutrients you need, and summer is the easiest time to get them. You can prepare them any way you want; grill watermelon or pineapple or caramelize onions for your burgers. Creamy coleslaw also works. Cooked or raw doesn’t matter; cooking may change the form of phytonutrients but doesn’t destroy them. Remember that condiments count. Ketchup, mustard, and relish—sweet or dill—all have specific phytonutrients in them. People are becoming obsessed with pickled veggies. They count, of course.

As for how much of each food counts, use common sense. You might reasonably count the sprinkling of chives on your eggs, but adding one leaf of basil isn’t how people cook (except for maybe the tweezer-wielding chefs on TV).

Using the honor system, send me a list of everything you ate with the total fruits and veggies, the number of vegetables, and the number of fruits. I’ll offer a free six-month Insider membership or the digital Optimal Performance program to the person with the highest total in each category. Have fun, be safe, and I’ll be back next week.

Stocking up on podcasts for this holiday weekend? You can binge my podcast Straight Talk on Health, available on Spotify and other podcast sites.

What are you prepared to do today?

        Dr. Chet

A Closer Look at Ultra-Processed Food Risk

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I think the results of the UK Biobank ultra-processed food (UPF) study were interesting, as I relayed on Tuesday, but the researchers went further. They estimated how substituting non-UPF plant-sourced foods for any of the other three sources of food resulted in a reduction of cardiovascular disease (CVD) morbidity and mortality. Further, and what got the headlines, substituting UPF plant-sourced foods for any of the other three increased the risk of CVD morbidity and mortality.

That led some experts to speculate about how processing destroyed fiber and phytonutrients and may even increase the amounts of negative chemicals that have been associated with disease in UPF plant-sourced foods. The problem is that there are no randomized-controlled trials to prove that. Here are a few things that stood out to me.

Theoretically…

The most important issue was this: The determination made about UPF increasing or decreasing the risk of CVD was theoretical and based on calculations. They used a 10% substitution for the non-UPF or UPF plant-sourced foods to calculate the expected raising or lowering of risk. What they could have done was divide the subjects into actual groups based on percentage of nutrients they actually ate instead of running theoretical statistical formulae. My impression is that so few people were diagnosed or died from CVD during the nine-year observational period that they wouldn’t have enough subjects for each group.

So few subjects were diagnosed or died? In the entire subject population—over 118,000 subjects followed for nine years—there were only 7,806 people diagnosed with CVD and only 529 deaths from CVD. Only? Most of the subjects were between 40 and 70, prime time for being diagnosed with some form of CVD.

When looking at the percentage of UPF-plant-sourced foods, the highest percentages were from industrialized packaged breads (9.9%),

pastries, buns, and cakes (6.9%) and biscuits (the kind called cookies in the U.S.) at 3.9%. That’s over half the amount of UPF-plant based foods on the list provided in the research paper. While wheat and other grains were certainly stripped of nutrients in the ultra-processing, that’s nothing new—that’s been happening to flour for over 100 years. What was missing were any fruits or vegetables processed in that manner.

The Bottom Line

Should you take the corn chips and vegan burgers out of your cart? Don’t get the impression that I think UPF plant-based foods should be eaten in mass quantities. I don’t. But I don’t think this study provided much direction in a reasonable response to the issue. On top of that, the analysis of the data may be just plain wrong. We’re not done yet, but we’ll get to that after the 4th of July. One more holiday challenge coming up on Tuesday.

What are you prepared to do today?

        Dr. Chet

Reference: DOI:
https://doi.org/10.1016/j.lanepe.2024.100948