Tag Archive for: mortality

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

Flavonols: Eat, Drink, and Maybe Live Longer

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The analyses of the NHANES study on flavonols and mortality did more than just look at a class of phytonutrients; researchers also looked at the individual flavonols and how they impacted mortality. A little background first.

Flavonoids

Flavonoids are a group of phytonutrients made up of six classes of nutrients. They are flavan-3-ols, flavones, flavanones, anthocyanidins, and the previously mentioned flavonols. Each of those classes are made up of individual phytonutrients. Flavonols have four primary phytonutrients in its class: quercetin, kaempferol, myricetin, and isorhamnetin. We’ll skip the rest of the individual phytonutrients in the other classes because they weren’t part of the study.

The researchers examined the reduction in mortality for each flavonol phytonutrient. When comparing the first quartile (lowest) with the fourth quartile (highest) intake, not every phytonutrient reduced the mortality from all conditions. In other words, the overall reduction in mortality was greatest when looking at total flavonol intake, not in any single phytonutrient. Too often research focuses on single phytonutrients as potential treatments of conditions and diseases, so it’s great to see a study that looks at total intake of a class of nutrients.

Absorption

As mentioned, flavonols are one part of the flavonoids. One characteristic is that they seem to be poorly absorbed. Or are they? It could be that there are unknown genetic factors that impact absorption and/or utilization of those nutrients. It may be that when isolated from a plant, the absorption is interfered with in some way that’s not apparent. It may be that the microbiome has a role to play in absorption.

What is most likely is that when eaten or drunk in its natural or prepared state, it is the interaction of all the flavonols that help absorption. Or it may be the combinations of flavonoids found in specific foods that work together for absorption.

What foods have the highest flavonol content? When looking at mg/100 grams, raw onions, cooked onions, apples with the peel, brewed black decaf tea, and brewed black tea top the list. When looking at the top three consumed? Onions, black tea, and apples top the list, but beer comes in fourth place. While the amount per 100 grams is low, we consume a lot of it.

The Bottom Line

At the end of the day, the most important thing to know is that we have to consume flavonols to get the benefits. In reality, your mama was right: eat your fruits and vegetables. They’re good for you. And if you chase them down with a beer, that’s probably okay as well.

What are you prepared to do today?

        Dr. Chet

Reference: Nature Reports. 2024. https://doi.org/10.1038/s41598-024-55145-y2. Arch

How Flavonols Affect Mortality

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Observational studies are just what the title indicates: observing something over time. In the case of the National Health and Nutrition Examination Survey (NHANES), one of the objectives is to observe the relationship between diet and whether it impacts how long we live. I recently came across a paper that examined the relationship between flavonol intake and mortality. Observational studies cannot give cause and effect; they can only suggest a relationship, which would then be followed up with randomized controlled trials. That doesn’t happen often enough in nutrition studies; how do you blind subjects to the foods they’re eating? Therefore, we take what we can get.

Researchers wanted to find out the relationship between one class of flavonoids called flavonols and mortality. They used data from the volunteers in three different NHANES data collection periods who completed a 24-hour dietary recall with an in-person interview and telephone follow-up. This is about as good as it gets when collecting dietary data in such large studies—over 11,000 subjects.

After accounting for age, gender, and other factors, there was a clear relationship between flavonol intake and mortality. Total flavonol intake was associated with an overall decrease in all-cause, cancer-specific, and CVD-specific mortality risks. The decrease in hazard ratio was as much as cutting the risk in half (cancer-specific) and by one-third from CVD and all-cause mortality; results were not as clear for diabetes and Alzheimer’s disease. There’s more to this study, and I’ll cover it on Saturday including the foods with the highest flavonol levels.

What are you prepared to do today?

        Dr. Chet

Reference: Nature Reports. 2024. https://doi.org/10.1038/s41598-024-55145-y2. Arch

Less Can Be More If…

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Let’s dig into the results of the National Health Interview Survey analysis to see if less really can be more: does mortality decrease even with fewer than 30 minutes per day most days of the week as long as part of the workouts was vigorous? We’re not examining other potential health benefits of exercise such as the risk of type 2 diabetes, weight loss, or gaining strength—just risk of death.

I examined the Hazard Ratios for the number of minutes spent in vigorous physical exercise per week and the total minutes of exercise per week. For those who exercised 1 to 149 minutes per week (less than the national recommendations), if 1 to 74 minutes of the total were spent in vigorous exercise, there was a 29% decrease in all-cause mortality. For CVD, there was a 20% decrease in mortality and a 24% decrease in mortality from cancer. There were additional benefits when a greater number of minutes were spent in vigorous activity, especially from CVD. Clearly, less can be more.

But…

A person must be fit enough to be able to do vigorous exercise. The survey defined vigorous exercise as hard enough to raise the heartrate and breathing rate and to increase sweating. The older you are, the less you may be able to sustain that type of effort, whether due to a lack of fitness or pre-existing CVD or orthopedic issues; the same holds true for someone who is overweight or obese. If you’re in any of those categories, you must get your physician’s approval before doing intense exercise.

You don’t have to wait, though; work up to it over a period of months with the guidance of a professional exercise specialist. Just as with any goal, you approach it in a stepwise manner. If you can walk for exercise, it may be something as simple as walking fast for 15 seconds every 3 minutes. Progress from there, increasing the fast walking by 15 seconds every week or every few days. If your body isn’t ready yet, it will let you know.

If you can get 20 to 30 minutes most days with over half of those minutes being vigorous, you may reap the benefit of lower risk of death, according to the data. Just proceed with caution and remember, this doesn’t include time working on strength, endurance, or flexibility.

What are you prepared to do today?

        Dr. Chet

References: JAMA Int Med. doi:10.1001/jamainternmed.2020.6331

Exercise: It All Counts

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Here’s something to ponder the rest of the week: why do you exercise? If you don’t, what would your purpose be if you did? I think there are two primary reasons. First, burning calories helps lose weight. Second, if you exercise regularly, you might live longer. But then you hit those exercise recommendations: 150 minutes per week—30 minutes a day five days a week. Who has that much continuous time? Maybe it doesn’t have to be continuous.

A recent published study used data from the NHANES database to determine whether exercise had to be continuous or whether it could be done in shorter segments they called bouts in order to have benefit. They looked at a single outcome: mortality. The subjects wore accelerometers to determine activity levels throughout the day. It turns out that whether you do your 30 minutes of exercise continuously or break the 30 minutes into bouts or segments lasting at least five minutes at a time, there was no difference in the reduction in mortality. Of course, the more total minutes per week were associated with continuing decreases in mortality, but it didn’t matter whether it was in shorter bursts or continuous minutes.

If you want to exercise to live longer, just get moving at least five minutes at a time several times per day. Whether bouted exercise will get you fitter is a different question, but if you want to live longer, get moving.

I know you’ll be busy buying chocolate this weekend no matter what your religious affiliation, so no memo on Saturday. I’ll be back next Tuesday.

What are you prepared to do today?

Dr. Chet

 

Reference: J Am Heart Assoc. 2018;7:e007678. DOI: 10.1161/JAHA.117.007678.

 

The Truth Behind the Obesity Paradox

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In my opinion, the short answer to the obesity paradox is that it doesn’t really exist. But what fun would that be? That doesn’t teach you anything. Let’s take a look at the problems with the research that contributed to this paradox.
 

Study One: Dialysis, BMI, and Mortality

A study of dialysis patients led to the first observation that people with higher BMIs lived longer (1). After tracking over 1,300 subjects on dialysis for a year, researchers found that those who were overweight had a decreased risk of dying and had fewer hospital stays when compared to those who were underweight. This may have been the study that yielded the name The Obesity Paradox. The problem? The study lasted only one year. Trying to generalize what will happen to all overweight and obese people on dialysis from a study that lasted only one year and at only a single location isn’t realistic. It raises an intriguing question, but we’ll need a much more extensive study to really make a solid prediction.
 

Study Two: The Rotterdam Study

I described this study on Thursday (2). While the study appeared to show a protective benefit from being overweight or obese, the subjects were elderly with an average age of 77 at the study’s beginning. One risk factor that you cannot change is age: the older you are, the more likely you are to die. But that’s not the whole story. We can probably say that older people may live longer with a little extra weight, but to extend that prediction to all age groups isn’t valid.
 

Study Three: BMI and Mortality

While this study claimed to analyze the data on over two million people, it was still a meta-analysis (3), which doesn’t yield cause and effect, just a statistical association. Further, they used studies of varying lengths without necessarily knowing exact causes of deaths. They also did not have precise BMIs on everyone; some studies included metrics such as BMI under 27.5 and over 27.5. They tried to include the highest number of subjects, but the quality of data varied and that made it a mess. Researchers chose too many different types of studies in the meta-analysis, and it just doesn’t work. I wouldn’t bet my life on it.
 

Study Four: A Broader Look

The real problem with every approach is the lack of acknowledgement that people with advanced disease may have lost weight before they were included in the study; diseases such as heart failure, diabetes, or renal disease will often lead to weight loss. Those who were heavier when disease hit had the benefit of extra energy stored as fat to deal with the disease, and that could explain the outcomes of those studies. It had nothing to do with being obese; it was a matter of timing.

A study published last month appears to confirm that (4). Researchers in the Cardiovascular Disease Lifetime Risk Pooling Project obtained data from 10 different longitudinal studies, including individual-level data and accurate mortality data. They found that as BMI increased, the death rate from all forms of CVD increased. For those who carried extra weight while younger, CVD occurred earlier, making it more likely they would die before their time.
 

The Bottom Line

As I said, there really is no obesity paradox. Being overweight or obese carries with it risks of degenerative disease. Some people may have better genes and may gain protection for a few years. But in the end, being overweight or obese carries a higher risk of various diseases than the limited protection from an advanced disease you may gain by carrying extra weight. So my advice is the same as it always was: if you’re overweight, your best bet for a long, healthy life is to lose it.

What are you prepared to do today?

Dr. Chet

 

References:
1. Kidney International, Vol. 55 (1999), pp. 1560–1567.
2. European Heart Journal (2001) 22, 1318–1327.
3. JAMA. 2013; 309(1): 71–82.
4. JAMA Cardiol. doi:10.1001/jamacardio.2018.0022.