How Science News Outlets Can Lie To You (Yes, Even If They Cite Studies!)
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Each Monday, we’re going to be bringing you cutting-edge research reviews to not only make your health and productivity crazy simple, but also, constantly up-to-date.
But today, in this special edition, we want to lay out plain and simple how to see through a lot of the tricks used not just by popular news outlets, but even sometimes the research publications themselves.
That way, when we give you health-related science news, you won’t have to take our word for it, because you’ll be able to see whether the studies we cite really support the claims we make.
Of course, we’ll always give you the best, most honest information we have… But the point is that you shouldn’t have to trust us! So, buckle in for today’s special edition, and never have to blindly believe sci-hub (or Snopes!) again.
The above now-famous Tumblr post that became a meme is a popular and obvious example of how statistics can be misleading, either by error or by deliberate spin.
But what sort of mistakes and misrepresentations are we most likely to find in real research?
Spin Bias
Perhaps most common in popular media reporting of science, the Spin Bias hinges on the fact that most people perceive numbers in a very “fuzzy logic” sort of way. Do you?
Try this:
- A million seconds is 11.5 days
- A billion seconds is not weeks, but 13.2 months!
…just kidding, it’s actually nearly thirty-two years.
Did the months figure seem reasonable to you, though? If so, this is the same kind of “human brains don’t do large numbers” problem that occurs when looking at statistics.
Let’s have a look at reporting on statistically unlikely side effects for vaccines, as an example:
- “966 people in the US died after receiving this vaccine!” (So many! So risky!)
- “Fewer than 3 people per million died after receiving this vaccine!” (Hmm, I wonder if it is worth it?)
- “Half of unvaccinated people with this disease die of it” (Oh)
How to check for this: ask yourself “is what’s being described as very common really very common?”. To keep with the spiders theme, there are many (usually outright made-up) stats thrown around on social media about how near the nearest spider is at any given time. Apply this kind of thinking to medical conditions.. If something affects only 1% of the population (So few! What a tiny number!), how far would you have to go to find someone with that condition? The end of your street, perhaps?
Selection/Sampling Bias
Diabetes disproportionately affects black people, but diabetes research disproportionately focuses on white people with diabetes. There are many possible reasons for this, the most obvious being systemic/institutional racism. For example, advertisements for clinical trial volunteer opportunities might appear more frequently amongst a convenient, nearby, mostly-white student body. The selection bias, therefore, made the study much less reliable.
Alternatively: a researcher is conducting a study on depression, and advertises for research subjects. He struggles to get a large enough sample size, because depressed people are less likely to respond, but eventually gets enough. Little does he know, even the most depressed of his subjects are relatively happy and healthy compared with the silent majority of depressed people who didn’t respond.
See This And Many More Educational Cartoons At Sketchplanations.com!
How to check for this: Does the “method” section of the scientific article describe how they took pains to make sure their sample was representative of the relevant population, and how did they decide what the relevant population was?
Publication Bias
Scientific publications will tend to prioritise statistical significance. Which seems great, right? We want statistically significant studies… don’t we?
We do, but: usually, in science, we consider something “statistically significant” when it hits the magical marker of p=0.05 (in other words, the probability of getting that result is 1/20, and the results are reliably coming back on the right side of that marker).
However, this can result in the clinic stopping testing once p=0.05 is reached, because they want to have their paper published. (“Yay, we’ve reached out magical marker and now our paper will be published”)
So, you can think of publication bias as the tendency for researchers to publish ‘positive’ results.
If it weren’t for publication bias, we would have a lot more studies that say “we tested this, and here are our results, which didn’t help answer our question at all”—which would be bad for the publication, but good for science, because data is data.
To put it in non-numerical terms: this is the same misrepresentation as the technically true phrase “when I misplace something, it’s always in the last place I look for it”—obviously it is, because that’s when you stop looking.
There’s not a good way to check for this, but be sure to check out sample sizes and see that they’re reassuringly large.
Reporting/Detection/Survivorship Bias
There’s a famous example of the rise in “popularity” of left-handedness. Whilst Americans born in ~1910 had a bit under a 3.5% chance of being left handed, those born in ~1950 had a bit under a 12% change.
Why did left-handedness become so much more prevalent all of a sudden, and then plateau at 12%?
Simple, that’s when schools stopped forcing left-handed children to use their right hands instead.
In a similar fashion, countries have generally found that homosexuality became a lot more common once decriminalized. Of course the real incidence almost certainly did not change—it just became more visible to research.
So, these biases are caused when the method of data collection and/or measurement leads to a systematic error in results.
How to check for this: you’ll need to think this through logically, on a case by case basis. Is there a reason that we might not be seeing or hearing from a certain demographic?
And perhaps most common of all…
Confounding Bias
This is the bias that relates to the well-known idea “correlation ≠ causation”.
Everyone has heard the funny examples, such as “ice cream sales cause shark attacks” (in reality, both are more likely to happen in similar places and times; when many people are at the beach, for instance).
How can any research paper possibly screw this one up?
Often they don’t and it’s a case of Spin Bias (see above), but examples that are not so obviously wrong “by common sense” often fly under the radar:
“Horse-riding found to be the sport that most extends longevity”
Should we all take up horse-riding to increase our lifespans? Probably not; the reality is that people who can afford horses can probably afford better than average healthcare, and lead easier, less stressful lives overall. The fact that people with horses typically have wealthier lifestyles than those without, is the confounding variable here.
See This And Many More Educational Cartoons on XKCD.com!
In short, when you look at the scientific research papers cited in the articles you read (you do look at the studies, yes?), watch out for these biases that found their way into the research, and you’ll be able to draw your own conclusions, with well-informed confidence, about what the study actually tells us.
Science shouldn’t be gatekept, and definitely shouldn’t be abused, so the more people who know about these things, the better!
So…would one of your friends benefit from this knowledge? Forward it to them!
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Mammography AI Can Cost Patients Extra. Is It Worth It?
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As I checked in at a Manhattan radiology clinic for my annual mammogram in November, the front desk staffer reviewing my paperwork asked an unexpected question: Would I like to spend $40 for an artificial intelligence analysis of my mammogram? It’s not covered by insurance, she added.
I had no idea how to evaluate that offer. Feeling upsold, I said no. But it got me thinking: Is this something I should add to my regular screening routine? Is my regular mammogram not accurate enough? If this AI analysis is so great, why doesn’t insurance cover it?
I’m not the only person posing such questions. The mother of a colleague had a similar experience when she went for a mammogram recently at a suburban Baltimore clinic. She was given a pink pamphlet that said: “You Deserve More. More Accuracy. More Confidence. More power with artificial intelligence behind your mammogram.” The price tag was the same: $40. She also declined.
In recent years, AI software that helps radiologists detect problems or diagnose cancer using mammography has been moving into clinical use. The software can store and evaluate large datasets of images and identify patterns and abnormalities that human radiologists might miss. It typically highlights potential problem areas in an image and assesses any likely malignancies. This extra review has enormous potential to improve the detection of suspicious breast masses and lead to earlier diagnoses of breast cancer.
While studies showing better detection rates are extremely encouraging, some radiologists say, more research and evaluation are needed before drawing conclusions about the value of the routine use of these tools in regular clinical practice.
“I see the promise and I hope it will help us,” said Etta Pisano, a radiologist who is chief research officer at the American College of Radiology, a professional group for radiologists. However, “it really is ambiguous at this point whether it will benefit an individual woman,” she said. “We do need more information.”
The radiology clinics that my colleague’s mother and I visited are both part of RadNet, a company with a network of more than 350 imaging centers around the country. RadNet introduced its AI product for mammography in New York and New Jersey last February and has since rolled it out in several other states, according to Gregory Sorensen, the company’s chief science officer.
Sorensen pointed to research the company conducted with 18 radiologists, some of whom were specialists in breast mammography and some of whom were generalists who spent less than 75% of their time reading mammograms. The doctors were asked to find the cancers in 240 images, with and without AI. Every doctor’s performance improved using AI, Sorensen said.
Among all radiologists, “not every doctor is equally good,” Sorensen said. With RadNet’s AI tool, “it’s as if all patients get the benefit of our very top performer.”
But is the tech analysis worth the extra cost to patients? There’s no easy answer.
“Some people are always going to be more anxious about their mammograms, and using AI may give them more reassurance,” said Laura Heacock, a breast imaging specialist at NYU Langone Health’s Perlmutter Cancer Center in New York. The health system has developed AI models and is testing the technology with mammograms but doesn’t yet offer it to patients, she said.
Still, Heacock said, women shouldn’t worry that they need to get an additional AI analysis if it’s offered.
“At the end of the day, you still have an expert breast imager interpreting your mammogram, and that is the standard of care,” she said.
About 1 in 8 women will be diagnosed with breast cancer during their lifetime, and regular screening mammograms are recommended to help identify cancerous tumors early. But mammograms are hardly foolproof: They miss about 20% of breast cancers, according to the National Cancer Institute.
The FDA has authorized roughly two dozen AI products to help detect and diagnose cancer from mammograms. However, there are currently no billing codes radiologists can use to charge health plans for the use of AI to interpret mammograms. Typically, the federal Centers for Medicare & Medicaid Services would introduce new billing codes and private health plans would follow their lead for payment. But that hasn’t happened in this field yet and it’s unclear when or if it will.
CMS didn’t respond to requests for comment.
Thirty-five percent of women who visit a RadNet facility for mammograms pay for the additional AI review, Sorensen said.
Radiology practices don’t handle payment for AI mammography all in the same way.
The practices affiliated with Boston-based Massachusetts General Hospital don’t charge patients for the AI analysis, said Constance Lehman, a professor of radiology at Harvard Medical School who is co-director of the Breast Imaging Research Center at Mass General.
Asking patients to pay “isn’t a model that will support equity,” Lehman said, since only patients who can afford the extra charge will get the enhanced analysis. She said she believes many radiologists would never agree to post a sign listing a charge for AI analysis because it would be off-putting to low-income patients.
Sorensen said RadNet’s goal is to stop charging patients once health plans realize the value of the screening and start paying for it.
Some large trials are underway in the United States, though much of the published research on AI and mammography to date has been done in Europe. There, the standard practice is for two radiologists to read a mammogram, whereas in the States only one radiologist typically evaluates a screening test.
Interim results from the highly regarded MASAI randomized controlled trial of 80,000 women in Sweden found that cancer detection rates were 20% higher in women whose mammograms were read by a radiologist using AI compared with women whose mammograms were read by two radiologists without any AI intervention, which is the standard of care there.
“The MASAI trial was great, but will that generalize to the U.S.? We can’t say,” Lehman said.
In addition, there is a need for “more diverse training and testing sets for AI algorithm development and refinement” across different races and ethnicities, said Christoph Lee, director of the Northwest Screening and Cancer Outcomes Research Enterprise at the University of Washington School of Medicine.
The long shadow of an earlier and largely unsuccessful type of computer-assisted mammography hangs over the adoption of newer AI tools. In the late 1980s and early 1990s, “computer-assisted detection” software promised to improve breast cancer detection. Then the studies started coming in, and the results were often far from encouraging. Using CAD at best provided no benefit, and at worst reduced the accuracy of radiologists’ interpretations, resulting in higher rates of recalls and biopsies.
“CAD was not that sophisticated,” said Robert Smith, senior vice president of early cancer detection science at the American Cancer Society. Artificial intelligence tools today are a whole different ballgame, he said. “You can train the algorithm to pick up things, or it learns on its own.”
Smith said he found it “troubling” that radiologists would charge for the AI analysis.
“There are too many women who can’t afford any out-of-pocket cost” for a mammogram, Smith said. “If we’re not going to increase the number of radiologists we use for mammograms, then these new AI tools are going to be very useful, and I don’t think we can defend charging women extra for them.”
KFF Health News is a national newsroom that produces in-depth journalism about health issues and is one of the core operating programs at KFF—an independent source of health policy research, polling, and journalism. Learn more about KFF.
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How To En-Joy Life (With Long-Term Benefits)
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New Year’s Dissolutions?
We have talked previously about:
The Science Of New Year’s Pre-Resolutions
…and here we are now at the end of the first week of January; how’s it going?
Hopefully, based on that article, it’s been going just great since December! For most people, statistically speaking, it hasn’t.
Around now is typically when many people enter the “bargaining” stage of New Year’s Resolutions, which at this point are often in serious danger of becoming New Year’s Dissolutions.
What’s important, really?
When trying to juggle potentially too many new items, it’s important to be able to decide where to focus one’s efforts in the case of needing to drop a ball or two.
First, the laziest way…
The path of least resistance
This is perhaps most people’s go-to. It, without too much thought, drops whatever feels most onerous, and continues with what seems easiest.
This is not a terrible approach, because what we enjoy, we will be more likely to continue. But it can be improved upon, while still getting that benefit.
Marie Kondo your
resolutionsvaluesInstead of throwing out the new habits that “don’t spark joy”, ask yourself:
“What brings me joy?”
…because often, the answer is something that’s a result of a thing that didn’t “spark joy” directly. Many things in life involve delayed gratification.
Let’s separate the [unwanted action] from the [wanted result] for a moment.
Rather than struggling on with something unpleasant for the hope of joy at the end of the rainbow, though, give yourself permission to improve the middle bit.
For example, if the idea of having lots of energy and good cardiovascular fitness is what prompted you to commit to those 6am runs each morning (but they’re not actually joyous in your experience), what would be more fun and still give you the same benefit?
Now that you know “having lots of energy and good CV fitness” is what sparks joy, not “getting up to run at 6am”, you can change lanes without pulling off the highway entirely.
Maybe a dance class will be more your speed, for example.
The key here is: you’ll have changed your resolution, without breaking it in any way that mattered
Want more ways to keep on track without burning out?
Who doesn’t? So, check out:
How To Keep On Keeping On… Long Term!
Enjoy!
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Coconut & Lemongrass Protein Soup
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The main protein here is pea protein, but the soup’s health benefits don’t stop there. With healthy MCTs from the coconut, as well as phytochemical benefits from the ginger and chili, this wonderfully refreshing soup has a lot to offer.
You will need
- 1 can coconut milk
- 1 cup vegetable stock (making your own, or buying a low-sodium option)
- 1 cup frozen petits pois
- 1 oz fresh ginger, roughly chopped
- ½ oz lemongrass stalk, crumpled without being broken into multiple pieces
- 1 red chili, roughly chopped
- 1 tbsp white miso paste
- zest and juice of 1 lime
- Optional: garnish of your choice
Method
(we suggest you read everything at least once before doing anything)
1) Mix the coconut milk, vegetable stock, ginger, and chili in a saucepan, and simmer for 15 minutes
2) Remove the lemongrass and ginger (and the chili if you don’t want more heat), and add the petit pois. Bring back to a simmer for about 2 minutes more, stir in the miso paste and lime, then take off the heat.
3) Blend the soup to a smooth purée. Since it is hot, you will need to either use a stick blender, or else a food processor that is ok with blending hot liquids (many are not, so don’t use yours unless you’re sure, as it might explode if it’s not made for that). Alternatively, you can let it cool, blend it, and then reheat it.
4) Serve, adding a garnish if you so wish:
Enjoy!
Want to learn more?
For those interested in some of the science of what we have going on today:
- Can Saturated Fats Be Healthy?
- Ginger Does A Lot More Than You Think
- Capsaicin For Weight Loss And Against Inflammation
Take care!
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Taking A Trip Through The Evidence On Psychedelics
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In Tuesday’s newsletter, we asked you for your opinions on the medicinal use of psychedelics, and got the above-depicted, below-described, set of responses:
- 32% said “This is a good, evidence-based way to treat many brain disorders”
- 32% said “There are some benefits, but they don’t outweigh the risks”
- 20% said “This can help a select few people only; useless for the majority”
- 16% said “This is hippie hogwash and hearsay; wishful thinking at best”
Quite a spread of answers, so what does the science say?
This is hippie hogwash and hearsay; wishful thinking at best! True or False?
False! We’re tackling this one first, because it’s easiest to answer:
There are some moderately-well established [usually moderate] clinical benefits from some psychedelics for some people.
If that sounds like a very guarded statement, it is. Part of this is because “psychedelics” is an umbrella term; perhaps we should have conducted separate polls for psilocybin, MDMA, ayahuasca, LSD, ibogaine, etc, etc.
In fact: maybe we will do separate main features for some of these, as there is a lot to say about each of them separately.
Nevertheless, looking at the spread of research as it stands for psychedelics as a category, the answers are often similar across the board, even when the benefits/risks may differ from drug to drug.
To speak in broad terms, if we were to make a research summary for each drug it would look approximately like this in each case:
- there has been research into this, but not nearly enough, as “the war on drugs” may well have manifestly been lost (the winner of the war being: drugs; still around and more plentiful than ever), but it did really cramp science for a few decades.
- the studies are often small, heterogenous (often using moderately wealthy white student-age population samples), and with a low standard of evidence (i.e. the methodology often has some holes that leave room for reasonable doubt).
- the benefits recorded are often small and transient.
- in their favor, though, the risks are also generally recorded as being quite low, assuming proper safe administration*.
*Illustrative example:
Person A takes MDMA in a club, dances their cares away, has had only alcohol to drink, sweats buckets but they don’t care because they love everyone and they see how we’re all one really and it all makes sense to them and then they pass out from heat exhaustion and dehydration and suffer kidney damage (not to mention a head injury when falling) and are hospitalized and could die;
Person B takes MDMA in a lab, is overwhelmed with a sense of joy and the clarity of how their participation in the study is helping humanity; they want to hug the researcher and express their gratitude; the researcher reminds them to drink some water.
Which is not to say that a lab is the only safe manner of administration; there are many possible setups for supervised usage sites. But it does mean that the risks are often as much environmental as they are risks inherent to the drug itself.
Others are more inherent to the drug itself, such as adverse cardiac events for some drugs (ibogaine is one that definitely needs medical supervision, for example).
For those who’d like to see numbers and clinical examples of the bullet points we gave above, here you go; this is a great (and very readable) overview:
NIH | Evidence Brief: Psychedelic Medications for Mental Health and Substance Use Disorders
Notwithstanding the word “brief” (intended in the sense of: briefing), this is not especially brief and is rather an entire book (available for free, right there!), but we do recommend reading it if you have time.
This can help a select few people only; useless for the majority: True or False?
True, technically, insofar as the evidence points to these drugs being useful for such things as depression, anxiety, PTSD, addiction, etc, and estimates of people who struggle with mental health issues in general is often cited as being 1 in 4, or 1 in 5. Of course, many people may just have moderate anxiety, or a transient period of depression, etc; many, meanwhile, have it worth.
In short: there is a very large minority of people who suffer from mental health issues that, for each issue, there may be one or more psychedelic that could help.
This is a good, evidence-based way to treat many brain disorders: True or False?
True if and only if we’re willing to accept the so far weak evidence that we discussed above. False otherwise, while the jury remains out.
One thing in its favor though is that while the evidence is weak, it’s not contradictory, insofar as the large preponderance of evidence says such therapies probably do work (there aren’t many studies that returned negative results); the evidence is just weak.
When a thousand scientists say “we’re not completely sure, but this looks like it helps; we need to do more research”, then it’s good to believe them on all counts—the positivity and the uncertainty.
This is a very different picture than we saw when looking at, say, ear candling or homeopathy (things that the evidence says simply do not work).
We haven’t been linking individual studies so far, because that book we linked above has many, and the number of studies we’d have to list would be:
n = number of kinds of psychedelic drugs x number of conditions to be treated
e.g. how does psilocybin fare for depression, eating disorders, anxiety, addiction, PTSD, this, that, the other; now how does ayahuasca fare for each of those, and so on for each drug and condition; at least 25 or 30 as a baseline number, and we don’t have that room.
But here are a few samples to finish up:
- Psilocybin as a New Approach to Treat Depression and Anxiety in the Context of Life-Threatening Diseases—A Systematic Review and Meta-Analysis of Clinical Trials
- Therapeutic Use of LSD in Psychiatry: A Systematic Review of Randomized-Controlled Clinical Trials
- Efficacy of Psychoactive Drugs for the Treatment of Posttraumatic Stress Disorder: A Systematic Review of MDMA, Ketamine, LSD and Psilocybin
- Changes in self-rumination and self-compassion mediate the effect of psychedelic experiences on decreases in depression, anxiety, and stress.
- Psychedelic Treatments for Psychiatric Disorders: A Systematic Review and Thematic Synthesis of Patient Experiences in Qualitative Studies
- Repeated lysergic acid diethylamide (LSD) reverses stress-induced anxiety-like behavior, cortical synaptogenesis deficits and serotonergic neurotransmission decline
In closing…
The general scientific consensus is presently “many of those drugs may ameliorate many of those conditions, but we need a lot more research before we can say for sure”.
On a practical level, an important take-away from this is twofold:
- drugs, even those popularly considered recreational, aren’t ontologically evil, generally do have putative merits, and have been subject to a lot of dramatization/sensationalization, especially by the US government in its famous war on drugs.
- drugs, even those popularly considered beneficial and potentially lifechangingly good, are still capable of doing great harm if mismanaged, so if putting aside “don’t do drugs” as a propaganda of the past, then please do still hold onto “don’t do drugs alone”; trained professional supervision is a must for safety.
Take care!
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Be Your Future Self Now – by Dr. Benjamin Hardy
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Affirmations in the mirror are great and all, but they can only get you so far! And if you’re a regular reader of our newsletter, you probably know about the power of small daily habits adding up and compounding over time. So what does this book offer, that’s different?
“Be Your Future Self Now” beelines the route “from here to there”, with a sound psychological approach. On which note…
The book’s subtitle mentions “the science of intentional transformation”, and while Dr. Hardy is a psychologist, he’s an organizational psychologist (which doesn’t really pertain to this topic). It’s not a science-heavy book, but it is heavy on psychological rationality.
Where Dr. Hardy does bring psychology to bear, it’s in large part that! He teaches us how to overcome our biases that cause us to stumble blindly into the future… rather than intentfully creating our own future to step into. For example:
Most people (regardless of age!) acknowledge what a different person they were 10 years ago… but assume they’ll be basically the same person 10 years from now as they are today, just with changed circumstances.
Radical acceptance of the inevitability of change is the first step to taking control of that change.
That’s just one example, but there are many, and this is a book review not a book summary!
In short: if you’d like to take much more conscious control of the direction your life will take, this is a book for you.
Click here to get your copy of “Be Your Future Self Now” from Amazon!
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Pomegranate’s Health Gifts Are Mostly In Its Peel
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Pomegranate Peel’s Potent Potential
Pomegranates have been enjoying a new surge in popularity in some parts, widely touted for their health benefits. What’s not so widely touted is that most of the bioactive compounds that give these benefits are concentrated in the peel, which most people in most places throw away.
They do exist in the fruit too! But if you’re discarding the peel, you’re missing out:
Food Applications and Potential Health Benefits of Pomegranate and its Derivatives
“That peel is difficult and not fun to eat though”
Indeed. Drying the peel, especially freeze-drying it, is a good first step:
❝Freeze drying peels had a positive effect on the total phenolic, tannins and flavonoid than oven drying at all temperature range. Moreover, freeze drying had a positive impact on the +catechin, -epicatechin, hesperidin and rutin concentrations of fruit peel. ❞
Once it is freeze-dried, it is easy to grind it into a powder for use as a nutritional supplement.
“How useful is it?”
Studies with 500mg and 1000mg per day in people with cases of obesity and/or type 2 diabetes saw significant improvements in assorted biomarkers of cardiometabolic health, including blood pressure, blood sugar levels, cholesterol, and hemoglobin A1C:
- Effects of pomegranate extract supplementation on inflammation in overweight and obese individuals: A randomized controlled clinical trial
- Beneficial effects of pomegranate peel extract on plasma lipid profile, fatty acids levels and blood pressure in patients with diabetes mellitus type-2: A randomized, double-blind, placebo-controlled study
It also has anticancer properties:
- Punicalagin, a polyphenol from pomegranate fruit, induces growth inhibition and apoptosis in human PC-3 and LNCaP cells
- Punica granatum (Pomegranate) activity in health promotion and cancer prevention
- The extract from Punica granatum (pomegranate) peel induces apoptosis and impairs metastasis in prostate cancer cells
…and neuroprotective benefits:
- Long-term (15 mo) dietary supplementation with pomegranates attenuates cognitive and behavioral deficits
- Neuroprotective Effects of Pomegranate Peel Extract
- An Evaluation of the Effects of a Non-caffeinated Energy Dietary Supplement on Cognitive and Physical Performance
…and it may protect against osteopenia and osteoporosis, but we only have animal or in vitro studies so far, for example:
- Pomegranate Peel Extract Prevents Bone Loss in a Preclinical Model of Osteoporosis and Stimulates Osteoblastic Differentiation in Vitro
- Pomegranate and its derivatives can improve bone health through decreased inflammation and oxidative stress in an animal model of postmenopausal osteoporosis
Want to try it?
We don’t sell it, but you can buy pomegranates at your local supermarket, or buy the peel extract ready-made from online sources; here’s an example on Amazon for your convenience
(the marketing there is for use of the 100% pomegranate peel powder as a face mask; it also has health benefits for the skin when applied topically, but we didn’t have time to cover that today)
Enjoy!
Don’t Forget…
Did you arrive here from our newsletter? Don’t forget to return to the email to continue learning!
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