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Always Be Skeptical Of Nutrition Headlines: Or, What “Red Meat Consumption and Mortality” (Pan et.al.) Really Tells Us

Normally I’d be continuing my ongoing series on the evolutionary history of the human brain. However, there is yet another red meat scare story making the rounds—and many readers have asked me to analyze it. Should we really be eating less red meat?

I don’t like to spend my time debunking specific studies—because as I said in a previous article about bad science, it’s like trying to hold back the ocean with a blue tarp and some rebar. However, I’ve wanted to write an article about the limitations and potential abuses of observational studies for some time, and “Red Meat Consumption And Mortality” is as good a starting point as any.

What Kind Of Study Is This, Anyway? Randomized Controlled Trials Vs. Observational Studies

The first and most important question we must ask is “What actual scientific data is this article based on?” It’s often tricky to find out, because most “news” articles don’t even mention the title of the original scientific paper, let alone link to it. (I usually start with a Pubmed search on the authors and narrow it down by journal.) In the overwhelming majority of cases, we’ll find that the data in question comes from what’s known as a “retrospective cohort study”.

In some cases, there isn’t any data: it’s just a lightly-camouflaged press release from a supplement peddler or drug manufacturer, designed to sell you pills, powders, or extracts. We’ll ignore those for now.

When most of us think of a scientific study, we’re thinking of a randomized controlled trial (RCT). The participants are divided randomly into two groups, matched as well as possible for age, sex, health history, smoking status, and any other factor that might affect the outcome. One group is given the treatment, the other is given no treatment.

In the more rigorous forms of RCT, the “no treatment” group is given a sham treatment (known as “placebo”) so that the subjects don’t know whether they’ve received treatment or not. This is sometimes called a “single-blinded” trial. Since the simple act of being attended to has a positive and significant effect on health (the “placebo effect”), unblinded trials (also known as “open label”) are usually not taken very seriously.

To add additional rigor, some trials are structured so that the clinicians administering the treatment don’t know who’s receiving the real treatment or not. This is sometimes called a “double-blinded” trial. And if the clinicians assessing outcomes don’t know who received the real treatment, it’s sometimes called “triple-blinded”. (These terms are now being discouraged in favor of simply calling a study “blinded” and specifying which groups have been blinded.)

Double-blinded, randomized controlled trials are the gold standard of research, because they’re the only type of trial that can prove the statement “X causes Y”. Unfortunately, RCTs are expensive—especially nutrition studies, which require feeding large groups over extended periods, and to be completely rigorous, isolating the subjects so they can’t consume foods that aren’t part of the experiment. (These are usually called “metabolic ward studies”.)

Result: RCTs are infrequently done, especially in the nutrition field.

What Is An Observational Study? Cohort Studies and Cross-Sectional Studies

Since nutrition RCTs are so rare, almost all nutrition headlines are based on observational studies.

In an observational study, the investigators don’t attempt to control the behavior of the subjects: they simply collect data about what the subjects are doing on their own. There are two main types of observational studies: cohort studies identify a specific group and track it over a period of time, whereas population studies measure characteristics of an entire population at one single point in time.

Cohort studies can be further divided into prospective cohort studies, in which the groups and study criteria are defined before the study begins, and retrospective cohort studies, in which existing data is “mined” after the fact for possible associations. (More.)

As the terminology starts getting intense (e.g. case-control studies vs. nested case-control studies), I’ll stop here.

The overwhelming majority of nutrition headlines are from cohort studies, in which health data has been collected for years (or decades) from a fixed group of people, often with no specific goal in mind. Expressed in the simplest possible language:

“Let’s watch the same group of people for decades, measure some things every once in a while, and see what happens to them. Then we can go back through the data and see if the people with a specific health issue had anything else in common.”

It’s easy to see that looking for statistical associations in data that already exists is far easier and cheaper than performing a randomized clinical trial. Unfortunately, there are several problems with observational studies. The first, and most damning, is that observational studies cannot prove that anything is the cause of anything else! They can only show an association between two or more factors—

—and that association may not mean what we think it means. In fact, it may not mean anything at all!

There are more potential pitfalls of the retrospective observational studies which underlie almost every nutrition headline. Let’s explore some of them.

Problem: Sampling Bias

Here’s the classic example of sampling bias:

Actually, no he didn't.

Going into the 1948 presidential election, polls consistently predicted a Dewey victory, by a substantial margin of 5-15%. Of course, Harry S Truman won by 4.4%. The reason the poll results differed so much from the actual outcome was that the polling was done by telephone—and in 1948, private telephone lines were very expensive. Therefore, the pollsters were unwittingly selecting only the relatively wealthy—who tended to vote Republican—for their survey. (More: DEWEY DEFEATS TRUMAN and Cancer Statistics, J Natl Cancer Inst (2009) 101 (16): 1157.)

In other words, the entire group we’re studying may have inadvertently been selected for certain characteristics that skew our results, making them inapplicable to the population at large.

Selection Bias, or The Healthy Volunteer Problem

“Selection bias” occurs because, unlike an RCT in which the participants are randomly assigned to groups that are matched as well as possible, the people in an observational study choose their own behavior.

Most women will be familiar with the classic story of selection bias: the saga of hormone replacement therapy, or HRT.

1991: “Every woman should get on HRT immediately, because it prevents heart attacks!”
2002: “Every woman should get off HRT immediately, because it causes heart attacks!”

What happened?

Int. J. Epidemiol. (2004) 33 (3): 464-467.
The hormone replacement–coronary heart disease conundrum: is this the death of observational epidemiology?
Debbie A Lawlor, George Davey Smith and Shah Ebrahim

“…the pooled estimate of effect from the best quality observational studies (internally controlled prospective and angiographic studies) inferred a relative reduction of 50% with ever [sic] use of HRT and stated that ‘overall, the bulk of the evidence strongly supports a protective effect of estrogens that is unlikely to be explained by confounding factors’.4

By contrast, recent randomized trials among both women with established CHD and healthy women have found HRT to be associated with slightly increased risk of CHD or null effects.1,2 For example, the large Women’s Health Initiative (WHI) randomized trial found that the hazards ratio for CHD associated with being allocated to combined HRT was 1.29 (95% CI: 1.02, 1.63), after 5.2 years of follow-up.1″

How did a 50% reduction in CHD (coronary heart disease) turn into a 30% increase in CHD?

It’s because the initial data from 1991 was from the Nurses’ Health Study, an associative cohort study which could only answer the question “What are the health characteristics of nurses who choose to undergo HRT versus nurses who don’t?” The followup data from 2002 was from a randomized clinical trial, which answered the much more relevant question “What happens to two matched groups of women when one undergoes HRT and the other doesn’t?”

It turns out that the effect of selection bias—women voluntarily choosing to be early adopters of a then-experimental procedure—completely overwhelmed the actual health effects of HRT. In other words, nurses who were willing to undergo cutting-edge medical treatment were far healthier than nurses who weren’t.

Is The Data Any Good? Garbage In = Garbage Out

This huge pitfall of observational studies is often neglected: in large cohort studies, data is often self-reported, and self-reported data is often wildly inaccurate.

Since we’re already discussing the Nurses’ Health Study, let’s take a closer look at its food consumption data. This study attempted to rigorously evaluate the accuracy of the FFQs (Food Frequency Questionaire) filled out by study participants:

Int J Epidemiol. 1989 Dec;18(4):858-67.
Food-based validation of a dietary questionnaire: the effects of week-to-week variation in food consumption.
Salvini S, Hunter DJ, Sampson L, Stampfer MJ, Colditz GA, Rosner B, Willett WC.

“The reproducibility and validity of responses for 55 specific foods and beverages on a self-administered food frequency questionnaire were evaluated. One hundred and seventy three women from the Nurses’ Health Study completed the questionnaire twice approximately 12 months apart and also recorded their food consumption for seven consecutive days, four times during the one-year interval.”

In other words, the standard FFQ for the Nurses’ Health Study consists of “Try to remember what you ate last year, on average.” We might expect this not to be terribly accurate…

…and we’d be right.

“They found that the FFQ predicted true intake of some foods very well and true intake of other foods very poorly. True intake of coffee could explain 55 percent of the variation in answers on the FFQ, while true intake of beer could explain almost 70 percent. True intake of skim milk and butter both explained about 45 percent, while eggs followed closely behind at 41 percent.

But the ability of the FFQ to predict true intake of meats was horrible. It was only 19 percent for bacon, 14 percent for skinless chicken, 12 percent for fish and meat, 11 percent for processed meats, 5 percent for chicken with skin, 4 percent for hot dogs, and 1.4 percent for hamburgers.

If your jaw just dropped, let me assure you that you read that right and it is not a typo. The true intake of hamburgers explained only 1.4 percent of the variation in people’s claims on the FFQ about how often they ate hamburgers!
“Will Eating Meat Make Us Die Younger?”, Chris Masterjohn, March 27, 2009

Stop for a moment and wrap your mind around this fact: the intake of meat reported by the hundreds of studies which use data mined from the Nurses’ Health Study is almost completely unrelated to how much meat the study participants actually ate.

Here’s a graph of the ugly truth, again from Chris Masterjohn:

The left-hand bars are the first questionaire, which we'd expect to be closer to the reported data in the NHS than the second questionaire (right-hand bars).

Why might this be the case?

“Focusing on the second questionnaire, we found that butter, whole milk, eggs, processed meat, and cold breakfast cereal were underestimated by 10 to 30% on the questionnaire. In contrast, a number of fruits and vegetables, yoghurt and fish were overestimated by at least 50%. These findings for specific foods suggest that participants over-reported consumption of foods often considered desirable or healthy, such as fruit and vegetables, and underestimated foods considered less desirable.” –Salvini et.al., via Chris Masterjohn

In support, I note that reported intake of yellow squash and spinach was also correlated by less than 10% with actual intake. Additionally, I’ll point you towards this article, which begins with a startling statistic: 64% of self-reported ‘vegetarians’ in the USA ate meat on at least one of the two days on which their dietary intake was surveyed.

In other words, the observational studies that cite meat intake data from the Nurses’ Health Study are not telling you about the health of nurses who actually eat meat: they’re telling you about the health of nurses who are willing to admit to eating meat on a written questionaire—and the two are almost completely unrelated. Furthermore, I see no basis to claim that any other data set based on occasional self-reported dietary intake will be substantially more accurate.

Thanks again to Chris Masterjohn for his work: “Will Eating Meat Make Us Die Younger?” and the classic “New Study Shows that Lying About Your Hamburger Intake Prevents Disease and Death When You Eat a Low-Carb Diet High in Carbohydrates.”

“Correlation Does Not Imply Causation”: What Does That Mean?

The logical fallacy of “correlation proves causation” is extremely common—because it’s very easy to slide into.

It’s called “cum hoc ergo propter hoc” in Latin, if you want to impress people at the risk of being pedantic. Literally translated, it means “with this, therefore because of this.”

You can entertain yourself for hours with this long list of logical fallacies, both formal and informal.

In plain language, “correlation does not imply causation” means “Just because two things vary in a similar way over time doesn’t mean one is causing the other.” Since observational studies can only prove correlation, not causation, almost every nutrition article which claims “X Causes Y” is factually wrong. The only statements we can make from an observational study are “X Associated With Y” or “X Linked With Y”.

We’ve already covered the cases in which sampling bias and selection bias skew the results, and the cases in which the data is inaccurate: let’s look at the purely logical pitfalls.

First, we could be dealing with a case of reverse causation. (“I always see lots of firemen at fires: therefore, firemen cause fires and we should outlaw firemen.”)

Second, we could be dealing with a third factor. “Sleeping with one’s shoes on is strongly correlated with waking up with a headache. Therefore, sleeping with one’s shoes on causes headaches.” Obviously, in this case, being drunk causes both…but when we’re looking at huge associative data sets and trying to learn more about diseases we don’t understand, the truth isn’t so obvious.

The third factor is often one of the pitfalls we’ve previously discussed: sampling bias, selection bias, or inaccurate data. Another example of selection bias: “Playing basketball is strongly correlated with being tall. Therefore, everyone should play basketball so they grow taller.” (Hat tip to Tom Naughton for the analogy.)

Or, the relationship could be a spurious relationship—pure coincidence.

Hmmm....I never thought of that!

Personally, I blame M. Night Shyamalan.

Complete Bunk: It Happens

There is also the possibility that the truth is being stretched or broken…that the data is being misrepresented. This isn’t as common with peer-reviewed science as it is with books and popular media (see Denise Minger’s debunking of “The China Study” and “Forks Over Knives”), but it can and has occurred.

“Red Meat Blamed For 1 In 10 Early Deaths”: Where’s The Science?

Now that we understand the limitations and potential pitfalls of observational studies, we can rationally evaluate the claims of the news articles based on them. For example, here’s the actual study on which the latest round of “Red Meat Will Kill You” stories is based:

Arch Intern Med. doi:10.1001/archinternmed.2011.2287
Red Meat Consumption and Mortality: Results From 2 Prospective Cohort Studies
An Pan, PhD; Qi Sun, MD, ScD; Adam M. Bernstein, MD, ScD; Matthias B. Schulze, DrPH; JoAnn E. Manson, MD, DrPH; Meir J. Stampfer, MD, DrPH; Walter C. Willett, MD, DrPH; Frank B. Hu, MD, PhD

“Prospective cohort study?” Apparently this is yet another observational study—and therefore, it cannot be used to prove anything or claim that anything “causes” anything else. Correlation is not causation.

Unfortunately, while the study authors maintain this distinction, it’s quickly lost when it comes time to write newspaper articles. Here’s a typical representative:

Headline: “Red meat is blamed for one in 10 early deaths” (The Daily Telegraph)
    [False. Since Pan et.al. is an observational study, we can’t assign blame.]

“Eating steak increases the risk of early death by 12%.”
    [Another false statement: associational studies cannot prove causation.]

“The study found that cutting the amount of red meat in peoples’ diets to 1.5 ounces (42 grams) a day, equivalent to one large steak a week, could prevent almost one in 10 early deaths in men and one in 13 in women.”
    [Note the weasel words “could prevent”. Just like playing basketball could make you taller, but it won’t. And just like HRT could have prevented heart attacks: instead, it caused them.]

“Replacing red meat with poultry, fish or vegetables, whole grains and other healthy foods cut the risk of dying by up to one fifth, the study found.”
    [No, it didn’t. The risk of dying was associated with self-reported intake of red meat and “healthy foods”.]

“But that’s just definitional nitpicking,” you say. “What about that 12% association?” It’s not nitpicking at all—because we’ve just opened the door to explaining that association in many other ways.

What Does “Red Meat Consumption and Mortality” (Pan et.al.) Really Tell Us?

“We prospectively observed 37 698 men from the Health Professionals Follow-up Study (1986-2008) and 83 644 women from the Nurses’ Health Study (1980-2008) who were free of cardiovascular disease (CVD) and cancer at baseline. Diet was assessed by validated food frequency questionnaires and updated every 4 years.”
Pan et.al.

Remember the Nurses’ Health Study?

The same study we talked about above—which was used to claim that HRT decreased heart disease by 50%, while a controlled trial showed that HRT actually increased heart disease by 30%?

The same study we talked about above—for which we’ve already proven, using peer-reviewed research, that the self-reported meat consumption data from the “food frequency questionaires” was unrelated to how much meat the nurses actually ate? And that the nurses, like most of us, exaggerated their intake of foods they thought were healthy by over 50%, and decreased their intake of foods they thought were unhealthy (like red meat) by up to 30%?

Yes, we’ve just kicked the legs out from under this entire study. It’s pinning a 12% variation in death rate on data we’ve already proven to be off by -30% to +50%—and more importantly, to be unrelated to the nurses’ actual consumption of red meat. (Or of meat in general…even chicken was only recalled with 5-14% accuracy.)

So much for the headlines! Here’s an accurate statement, based on the actual data from Pan et.al.:

“If you are a nurse or other health professional, telling the truth about how much red meat you eat, on a survey you fill out once every four years, is associated with a 12% increased risk of early death.”

And just to nail this down, here’s another study—also from the Harvard School Of Public Health—which comes to the opposite conclusion:

Circulation. 2010 Jun 1;121(21):2271-83. Epub 2010 May 17.
Red and processed meat consumption and risk of incident coronary heart disease, stroke, and diabetes mellitus: a systematic review and meta-analysis.
Micha R, Wallace SK, Mozaffarian D.
Department of Epidemiology, Harvard School of Public Health, Boston, MA, USA.

Red meat intake was not associated with CHD (n=4 studies; relative risk per 100-g serving per day=1.00; 95% confidence interval, 0.81 to 1.23; P for heterogeneity=0.36) or diabetes mellitus (n=5; relative risk=1.16; 95% confidence interval, 0.92 to 1.46;

But Wait, There’s More

We’re done, and I could easily stop here—but there’s more to talk about! Note this surprising statement from the “Results” section:

“Additional adjustment for saturated fat and cholesterol moderately attenuated the association between red meat intake and risk of CVD death, and the pooled HR (95% CI) dropped from 1.16 (1.12-1.20) to 1.12 (1.07-1.18).”
Pan et.al. (Credit to “wildwabbit” at Paleohacks for catching this one.)

And the data from Table 1 clearly shows that the people who admitted to eating the most red meat had, by far, the lowest cholesterol levels.

Wait, what? Aren’t saturated fat and cholesterol supposed to cause heart disease? This is another clue that the story, and the data, isn’t quite as advertised.

Here’s another trick that’s been played with the data: contrary to the statement “replacing 1 serving of total red meat with 1 serving of fish, poultry, nuts, legumes, low-fat dairy products, or whole grains daily was associated with a lower risk of total mortality”, the curve they draw in Figure 1 has been dramatically, er, “smoothed.” The source data, in Table 2, shows that the age-adjusted quintiles of reported unprocessed red meat intake from the Nurses’ Health Study (remember, we’ve already proven these numbers aren’t real) have hazard ratios of 1.00, 1.05, 0.98, 1.09, and 1.48.

In other words, the data isn’t a smooth curve…it’s a hockey stick, and the relative risk is basically 1.0 except for the top quintile. (Credit to Roger C at Paleohacks for catching this one.)

This is important because it helps us to explain the 12% increase based on reported red meat consumption. We already know that the subjects of the study weren’t truthfully reporting their meat intake of any kind—and that foods perceived unhealthy were underreported on average, while foods reported healthy were overreported on average.

Table 1 shows that the highest quintile of reported red meat consumption was strongly associated with other behaviors and characteristics known to be associated with poor health: smoking, drinking, high BMI. Most impressively, it was associated with a 69% increase (NHS data) or 44% increase (HPF data) in reported total calories per day, which lends weight to the idea that the lower quintiles were simply underreporting their intake of foods they considered “unhealthy”, including red meat…

…unless we accept that 1/5 of nurses live on 1200 calories per day (and coincidentally report the lowest red meat intake) while 1/5 eat over 2000 calories per day (and coincidentally report the highest red meat intake).

Calorie consumption is our smoking gun. The average American female aged 20-59 consumes approximately 1900 calories/day, and not all nurses are female. (Source: NHANES 1999-2000, through the CDC.)

Therefore, a reported average consumption of 1200 calories/day is extremely implausible. It’s even less plausible that nurses who reported the lowest intake of red meat just happened to be on a 1200-calorie semi-starvation diet; that total reported calorie intake just happened to rise dramatically with reported red meat intake; and that only the nurses who reported eating the most red meat consumed a statistically average number of total calories.

Since we already know from Salvini et.al. that actual consumption is unrelated to reported consumption, underreporting of red meat and other foods perceived as “unhealthy” by the lower quintiles is a far more reasonable explanation.

So What’s The Real Story?

While we’ll probably never know the truth, I believe the most parsimonious explanation is this:

Nurses and other health professionals know intimately the mainstream advice on health, and cannot fail to have given it to thousands of patients over the decades: “eat less, stop smoking, drink less alcohol, avoid cholesterol, avoid saturated fat, avoid red meat.” Therefore, any health professional willing to admit in writing to smoking, drinking, and eating over three servings of red meat per day (see the NHS data in Table 1) most likely doesn’t care very much about their own state of health.

And just as we saw with the HRT data—where a theoretical 50% decrease in heart disease was later proven to mask a real 30% increase, due to the selection bias inherent in the very same dataset (Nurses’ Health Study) used here—I think that we’ll someday find out through controlled, randomized trials that eating plenty of red meat, eggs, and other whole, natural foods high in cholesterol and saturated fat is the real “heart-healthy diet.”

Live in freedom, live in beauty.


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Foolproof Prime Rib! How To Buy, Cut, And Cook A Standing Rib Roast: The Easiest Prime Rib Recipe On The Internet

Prime rib is an intimidating entree to cook for many of us, because the meat itself costs so much. It’s easy to have over $75 worth of meat in the oven—at which point mistakes become extremely expensive.

Fear not! Here’s how to buy, cut, and cook a prime rib roast that comes out perfectly every time. Not only is this recipe easier than most because I omit needless steps—it produces a tastier roast than most restaurants.

How To Buy A “Prime Rib Roast”

“Prime rib” is actually a colloquial name: the proper name is a “standing rib roast”, because not all rib roasts are USDA Prime grade beef. So the easiest way to start is to roll up to your local butcher’s counter and ask for a bone-in standing rib roast.

Bone-In Or Boneless?

Buy a bone-in roast if you can: the bones impart a bit of extra flavor to the meat. However, if you find a great deal on a boneless roast, that’s fine too.

Prime or Choice?

Prime grade will indeed be more tender…but I’ve never had a tough prime rib, even at Choice grade (the standard), and there’s a lot of Choice beef out there that doesn’t miss Prime by much. Look for the roast with the most ‘marbling’ (fatty streaks inside the meat).

Bone-in rib roasts are sold by how many ribs they span. Two ribs is the minimum (one rib isn’t a roast, it’s a steak), and a two-rib roast will weigh anywhere from four to six pounds, depending on the size of the beef and which end of the primal they’re cut from. Each rib adds another 2-3 pounds.

How To Buy (And Store) An Entire Rib Primal

You can often save a lot of money if you buy an entire rib primal at once—and if ribeye steaks are on sale, whole rib primals are usually even cheaper.

A “primal cut” is one of the large pieces of meat into which a carcass is first disassembled during butchering.

Beef primal cuts (US version)

In the old days, your local butcher would start with a whole carcass (or quarters, in the case of beef—a whole beef is too heavy to lift), disassemble it into primal cuts, and then cut the primals as their customers desired. Nowadays, most beef is disassembled into primal cuts at the packing plant, vacuum-packed, and shipped to your local supermarket in the plastic, whereupon the butcher opens the package and cuts it into the steaks and roasts you see at the counter.

Note that, strictly speaking, a “rib primal” includes the short ribs. However, in practice, every US packing plant I’m familiar with splits the short ribs into a different primal from the ribeye (called “fore ribs” in the UK), probably because it’s much smaller and easier to pack for transport. (Short ribs plus the ribeye are a long and awkward shape: see below.)

An entire grass-fed rib primal. Yes, it was delicious!

An entire grass-fed rib primal. Note the ribeye on the right, the short ribs on the left, and the scrap of inside skirt stuck to the ribs. Yes, the meat from it was delicious!

A bone-in rib primal will contain seven ribs’ worth of rib meat. Depending on the size of the beef, it can weigh anywhere from 14-22 pounds—but 18-20 is typical in my experience. Anyway, it’ll most likely come in a big vacuum pack, like this:

Whole rib primal, in the plastic

That's about twenty pounds of beef.

How To Cut A Rib Primal Into Standing Rib Roasts

I usually cut the primal into two 2-rib roasts and one 3-rib roast, taking the 3-rib roast from the small end (the loin end). Just cut straight through the plastic, like this:

Right through the plastic!

The large end of the rib primal comes from the front of the beef, towards the chuck, and the small end comes from the rear, towards the loin. Yes, this one is boneless. Hey- it was on sale!

(Note that there’s only one place to cut a bone-in primal, and sometimes it’s a bit tricky to get your knife between the bones. Look for the gap on the bottom. Sometimes that doesn’t work, and you have to make the cut all the way through from the top and then fudge the last part a bit.)

Then, once you’ve split the primal into three roasts, lay three sheets of plastic cling wrap out on a big table. Put one of the roasts on one of the sheets and roll it up. Then repeat for the other two sheets, alternating the direction you wrap it each time.

Wrapping a prime rib/standing rib roast

Just leave the original plastic wrap on as the inner layer.

Repeat this step for the second roast. Make sure the plastic wrap is well-sealed, write the date on each roast with a permanent marker, and put them both in the freezer.

It’s always a good idea to write the date on meat you put in your freezer. Vacuum-packed meat will last over a year, but paper-wrapped or cling-wrapped meat should be eaten before six months pass.

“But what do we do with the third roast?” you ask.

Answer: we’re going to cook it! But first, we need some tools.

Temperature Control Is Important: Your Mandatory Shopping List For Cooking A Standing Rib Roast

You absolutely must have an accurate meat thermometer! The ones with the dial are not acceptable, as they’re often wildly inaccurate, and they usually don’t register below 130 °F (54.4 °C). Here’s the one I use: your mother probably used one just like it when you were little. They’re perhaps $6 with free shipping, so you have no excuse to skimp.

Old-school Taylor meat thermometer

US readers can buy one here.

(Note: If you have a fancy digital stove with the built-in temperature probe, that’s fine too.)

Calibrating Your Thermometer

It’s always best to verify the accuracy of your meat thermometer by testing it in boiling water. However, water only boils at 212 °F (100 °C) at sea level! I live over 6000′ (1830m) above sea level, where water boils at perhaps 201 °F (94 °C). Here’s a table, in both English and Metric units:

Altitude, m Boiling point of water, °C
0 (0 ft) 100 (212 °F)
300 (984 ft) 99.1 (210.3 °F)
600 (1969 ft) 98.1 (208.5 °F)
1000 (3281 ft) 96.8 (206.2 °F)
2000 (6562 ft) 93.3 (199.9 °F)
4000 (13123 ft) 87.3 (189.1 °F)

Second, you must have an oven thermometer. Accuracy isn’t as critical here…but it’s a good idea to have one, as the settings on your oven dial can be completely unrelated to the actual temperature inside your oven. I bought mine at the hardware store…but this one should work fine.

Oven thermometer

US readers can buy one here.

Finally, you’ll need a roasting pan with a rack. I discourage the disposable aluminum ones, as they have an alarming tendency to collapse when you’re taking them out of the oven. Here’s something cheap that will work, and here’s a more serious piece of equipment. Or, if you already have a 12″ cast iron or stainless steel skillet, this rack will most likely fit inside it.

Do you have everything? Great! Let’s go!


If you’re fixing a roast fresh from the butcher, you can skip this section. However, if you need to defrost it first, you’ll need to plan ahead.

Note that the more slowly you can defrost meat, the less it’ll “bleed” and the better it’ll taste. (There is also the danger of bacterial growth at room temperature.) To that end, you’ll need to move a two-bone roast out of the freezer and into the refrigerator at least two days before you intend to cook it. Three and four-bone roasts will take three days: six hours per pound is a good general rule.

If you forget this rule, you may suffer defrostration—the realization that your guests arrive this evening, but the center of your roast is still frozen solid.

Defrosting on a tray

It's always smart to defrost on a tray or in a pan, as the meat is likely to leak some juices as it thaws. Even a vacuum-sealed bag can end up with little pinholes from being knocked around in the freezer.

How To Cook A Prime Rib/Standing Rib Roast

Now that you have all the tools, this is the easy part! First, decide how you want your roast cooked, as this will determine the temperature at which you remove it.

Rare: 115 °F (46 °C). Any lower and the fat doesn’t really cook.
Medium rare: 130 °F (55 °C).
Medium: 145 °F (63 °C)…but why would you want to do that?

Step 1: Turn your oven to “BAKE”, and set the temperature to 275 °F (135 °C).

I’ve experimented with lower cooking temperatures—but the cooking times start getting ridiculously long. Also, the fat doesn’t taste right to me, as if it never really melted. 250 °F (121 °C) is as low as I like to go.

Some recipes insist you need to tie the roast with string before cooking, but there’s no need. Rib roasts stay together by themselves, and all the string does is make you dig it out later.

There are a lot of recipes that tell you to use higher temperatures, or to start with a “sear”. That just makes the outside hard and crusty. And I’ve experimented with several different herbal rubs and crusts—but frankly, prime rib is so delicious by itself that I’d rather taste the meat.

Step 2: Remove the roast from the plastic wrap. Rinse the outside and pat it dry.
Step 3: Place the roast on the roasting rack, bone side down. (If the roast is boneless, put the side down where the bones used to be.)
Step 4: Insert the tip of the meat thermometer in the exact center of the roast, or as close as you can manage.

Ready to go into the oven

Ready for the oven! This particular roast is boneless, but the bone would be on the bottom if it weren't.

Step 5: Put the roast in the oven, with the thermometer facing outward so you can see it. Set a timer for 30 minutes. Note that it is not necessary to pre-heat the oven!

Step 6: When the timer goes off, double-check that the temperature is approximately 275 °F (135 °C). If not, adjust accordingly.
Step 7: Now that the outside of the roast is warm, take the roast out of the oven and lightly baste it with butter, coconut oil, tallow, or any other solid fat. This will keep the outside from developing a hard crust.
Step 8: Put the roast back in the oven. Set a timer for one hour.

Step 9: After one hour, check the temperature reading on the meat thermometer. Double-check the oven temperature, and adjust if necessary. Note that the internal temperature of the roast will start rising rapidly once it hits about 100 °F—so you’ll want to start checking it fairly often.

A four-pound roast takes about two hours to reach 115 °F (46 °C) in my kitchen…but your experience may vary. Remember, there’s a very expensive piece of meat in the oven! It’s worth keeping a close eye on it.

If you’ve got one of those fancy digital ovens with temperature probes, you can usually set an alarm to go off—but test it to make sure that it works (and that you can hear the alarm) before counting on it.

Step 10: Once you see the internal temperature reach your target (115 °F – 130 °F), remove the roast from the oven.
Step 11: Let it sit for about ten minutes. Drool.


It's difficult not to just tear into it with your hands and teeth.

Step 12: You can optionally shave some of the brown “crust” off the ends—but if you’ve basted it at 30 minutes as per step 7, it won’t be hard and shouldn’t affect the taste much.

Step 13: Slice, serve, and enjoy! If you’re bored with salt and pepper, horseradish is a delicious traditional topping.

Medium-rare prime rib

Medium-rare, cooked to an internal temperature of 130 °F (55 °C).

Rare prime rib

Rare. This one was cooked to 110-115 degrees.

Executive Summary

tl;dr Bake at 275 °F until the center hits 115-130 °F. Yes, it’s that simple.

Live in freedom, live in beauty.


Do you have suggestions for condiments? Special recipes for “jus”? (It’s just beef broth in its simplest form.) Favorite side dishes? Leave a comment!

Trans Fat Is Good For You, But Only If It’s From Meat and Butter: Vaccenic Acid and the Conjugated Linoleic Acids

We’ve been bombarded for years with the evils of trans fat…

…and for once, the mainstream advice appears to be mostly correct. Trans fats cause coronary heart disease, they’re strongly associated with obesity, depression, infertility in women, and breast cancer, and they interfere with critical liver enzymes. (More.)

I’ve written about trans fats before: if you want to learn their basic chemistry—and more importantly, how to avoid them when shopping for food—read my article Eat More “Heart-Healthy” Trans Fats! (We hid them in plain sight).

“Help! There’s Trans Fat In My Grass-Fed Beef!”

However, an alert commenter (Steven) pointed out that beef contains a significant amount of trans fat. And while his estimate was a bit high, it is absolutely true that one ounce of beef fat (28.3g) usually contains 0.5g-1.4g of trans fat.

In fact, the meat and milk of ruminants contains a significant amount of trans fat—roughly 2-5% of the total. Even worse, grass-fed milk and meat contains even more trans fat than grain-fed milk and meat!

Journal of Dairy Science
Volume 82, Issue 10 , Pages 2146-2156, October 1999
Conjugated Linoleic Acid Content of Milk from Cows Fed Different Diets
T.R. Dhiman, G.R. Anand, L.D. Satter, M.W. Pariza

“Cows grazing pasture and receiving no supplemental feed had 500% more conjugated linoleic acid in milk fat than cows fed typical dairy diets.”

What’s going on here?

Trans-Vaccenic Acid and the Conjugated Linoleic Acids

No, I haven’t just named an obscure prog rock band from the 1970s. I’ve named the culprits: vaccenic acid and rumenic acid (a conjugated linoleic acid). Though vaccenic acid comprises most of the total, our bodies convert vaccenic acid directly to rumenic acid (just as they convert stearic acid directly to oleic acid), so nutritionally, we only need to investigate the effects of rumenic acid.

(This conversion is not reflected in American nutritional labeling—which requires stearic acid to be counted as saturated fat and vaccenic acid to be counted as trans fat, despite the fact that our bodies immediately convert them to different forms.)

A Short Biochemistry Excursion

Rumenic acid is known formally as (9Z,11E)-octadeca-9,11-dienoic acid, and informally as cis-9, trans-11 18:2. Vaccenic acid is known formally as (E)-Octadec-11-enoic acid, and informally as 18:1 trans-11.

Interestingly, the enzyme that converts vaccenic acid to rumenic acid—delta-9-desaturase—is the same enzyme that converts stearic acid (a saturated fat, 18:0) to oleic acid (a monounsaturated fat, 18:1 cis-9). That’s because delta-9-desaturase creates a cis-handed double bond at the 9th position. If you look at their informal names (or their chemical structure), you’ll see that the difference between vaccenic and rumenic acid is a cis-9 double bond, just the same as the difference between stearic and oleic acid is a cis-9 double bond.

Rumenic acid is part of a family of fats known as conjugated linoleic acids. “Conjugated” means that it contains both cis- and trans- bonds, just as its name (cis-9, trans-11 18:2) says.

Where Do The Trans Fats In Beef and Milk Come From?

Multicellular animals create only cis-handed fats with their enzymes…so where do trans-rumenic and trans-vaccenic acid come from?

Answer: they come from bacteria.

Cows, and other ruminants, can’t digest grass any more than we can. However, they have extra “stomachs” that are basically big microbial fermentation vats, in which bacteria digest the grass for them. (Whereupon they burp it up again, “chew the cud”, and finally swallow it into the regular digestive system once the rumen bacteria are done working.) Trans-rumenic and trans-vaccenic acid are created by these rumen bacteria via biohydrogenation of polyunsaturated fats (link).

Ruminant anatomy and physiology: click for details

To learn more about the ruminant digestive system, click the picture.

When Trans Fats Are Good For You: Our Friend Rumenic Acid

As with most rules of thumb, “trans fats are bad” is an oversimplification. “Molecules found nowhere in real food are bad” is the correct statement. People have been eating ruminants for millions of years, so one might expect that our bodies might have a nutritional use for rumenic acid.

This is, in fact, the case. The health benefits of rumenic acid are well-established—to the point where conjugated linoleic acid supplements (usually labeled “CLA” in big letters) are found in every vitamin store!

Conjugated linoleic acids (CLA) are a group of positional and geometric isomers of linoleic acid with proven beneficial influence on health. They show e.g. anticarcinogenic, antiobesity, and antiatherogenic effect. Milk, dairy products and meat of poligastric animals are their most valuable dietary sources, with cis-9, trans-11 CLA (RA – rumenic acid) being the predominant isomer.
This group of fatty acids has been extensively studied for recent years, in both in vivo and in vitro models, because of their beneficial biological effects: protection against cancer [7-10], prevention of atherosclerosis [11-14], reduction of obesity [15-17] and hypertension [18].
Bialek et.al.

Since vaccenic acid (which becomes rumenic acid) and rumenic acid comprise 2-5% of beef and milk fat, this gives us yet another excellent reason to consume fatty meat and butter. Sign me up!

CLA Supplements: Not The Same As Real Food

It’s easy to get trapped in “nutritionism”: the idea that we can eat whatever junk we want, and take supplements to replace the nutrients we’re not getting from our food. This rarely works…and in the case of CLA supplements, we know why.

Recall that “conjugated linoleic acid” can mean a whole host of different fats, depending on the positions of the double bonds. Most CLA supplements are derived from safflower oil—

—and they contain equal parts rumenic acid (cis-9, trans-11 18:2) and an unnamed trans-10, cis-12 18:2 isomer. In other words, half of a CLA supplement is an entirely different chemical than what you’re getting from meat and butter.

Unfortunately, trans-10, cis-12 doesn’t have all the same beneficial effects. While it still seems to have anti-cancer properties in mice, it doesn’t have the same effects on human metabolism as rumenic acid:

Circulation. 2002; 106: 1925-1929
Supplementation With Conjugated Linoleic Acid Causes Isomer-Dependent Oxidative Stress and Elevated C-Reactive Protein: A Potential Link to Fatty Acid-Induced Insulin Resistance
Ulf Risérus, MMed; Samar Basu, PhD; Stefan Jovinge, MD, PhD; Gunilla Nordin Fredrikson, PhD; Johan Ärnlöv, MD; Bengt Vessby, MD, PhD

“The significant increase from baseline in 8-iso-PGF2α, 15-K-DH-PGF2α and CRP after t10c12 CLA was 1.04±0.7 (578%), 0.30±0.31 (77%), and 2.89±3.66 (110%), respectively.
This randomized, double-blind, placebo-controlled trial demonstrates that dietary supplementation with t10c12CLA causes isomer-specific oxidative stress that is related to induced insulin resistance.

Diabetes Care September 2002 vol. 25 no. 9 1516-1521
Treatment With Dietary trans10cis12 Conjugated Linoleic Acid Causes Isomer-Specific Insulin Resistance in Obese Men With the Metabolic Syndrome
Ulf Risérus, MMED1, Peter Arner, MD, PHD2, Kerstin Brismar, MD, PHD3 and Bengt Vessby, MD, PHD1

“This randomized placebo-controlled trial has revealed unexpected metabolic actions by conjugated fatty acids in humans—actions that seem isomer-specific. The t10c12 CLA isomer, but not a CLA mixture, significantly increased insulin resistance, fasting glucose, and dyslipdemia in abdominally obese men.

[I can’t resist an editorial comment at this point: why did neither study test rumenic acid alone, the way it occurs in real food? Might it have actually reduced oxidative stress and decreased insulin resistance, when not forced to fight equal amounts of the imposter t10c12?]

It’s important to note that many of the studies that claim benefits for t10c12 are on mice or rats. As Risérus et.al. note:

“Conjugated linoleic acid (CLA) is a group of dietary fatty acids with antiobesity and antidiabetic effects in some animals. The trans10cis12 (t10c12) CLA isomer seems to cause these effects, including improved insulin sensitivity.”

Unfortunately, as their experiment proved, the safflower-derived t10c12 doesn’t have the same benefits for humans as it does for rodents. And perhaps we shouldn’t be surprised that ingesting a chemically extracted fraction of a seed oil doesn’t produce the same benefit as eating real food.

Conclusion: Keep Eating Like a Predator, Keep Eating Real Food

Our conclusions should be obvious, but I’ll restate them:

  • If we’ve eaten something for millions of years, the odds are very good that we’re adapted to eating it.
  • Be skeptical of studies that feed fat to mice—herbivores that naturally subsist on plants and seeds.
  • Whenever possible, eat real food, not supplements. You might not be getting the same benefits…or even the same nutrients.
  • Most importantly: keep eating delicious fatty red meat and butter!


Spend money on vitamins...

...or prime rib?

Live in freedom, live in beauty.


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