Over the summer, I had a friend ask me how to address a common problem: he found his chicken dinners less and less inspiring. This is nothing to be ashamed of. It can happen to anyone. The best solution is to spice it up...literally.
I can relate to running out of inspiration. For those of us who restrict foods because of food-reaction, diet, or food-quality reasons, it's good to have an arsenal of flavorings ready. I've come to eating hamburger steaks very often during the week because it's a satisfying carb restricted meal, and because I can afford the grass-fed ground beef - more than steaks, anyway. So, I've been relying heavily on different spice rubs for the burgers.
Costco BBQ rubbed hamburgers.
As a general rule, I think rubs, both dry rubs and wet rubs, also called pastes, are far superior to marinades. Dry rubs taste great when you cook the meat immediately after applying the rub, but they also get better with time. Putting a dry rub on meat the night before is spectacular. Marinades, on the other hand, seem to need an unnecessary amount of time to do their work.
The most important thing, though, is that rubs consistently accomplish what they are supposed to do - impart a desired flavor. Marinades are alluring, they immediately make you think of garlic infused chicken breasts or juicy lemon-pepper fish, but they rarely come through for me. My marinades always result in bland-tasting, albeit well salted, meat that doesn't brown well due to the extra moisture. Rubs always deliver. Jerk rub will taste like a Jamaican vacation, and an herbed garlic paste will make your palate sing.
Now, that's not to say that marinades never work. They just don't work as often as I would like them to. So instead of marinading the same old chicken, here are a few of the rubs that I like to employ. Also great on pork, and some will work on beef (Jerk rub and Costo BBQ rub).
Multi-pepper rub (during last minute of grilling, brush maple syrup on meat to add a touch of sweat):
And don't forget, you can always buy rubs at the store. I like Costco's mesquite rub - smokey, spicy, and sweet. Yes, it's very strong. So it's great to use on pork and beef, or dark-meat chicken, rather than fish or white meat chicken, and it does well with a healthy dose of lime juice after cooking.
Costco Mesquite BBQ seasoning.
Hopefully my friend will recover from his chicken-woes. Although I can't help him with his first resistance to using rubs, as astute as the observation is, that raw chicken is gross to touch.
I've recently developed an obsession with 88% dark chocolate that I can find on sale at Sprouts. It has about as much fiber as it does sugar, and it's bitterness verges on espresso. I've prescribed myself to a near-nightly dose of it after dinner. And one night, while I was medicating, I came across a new study and some responses to the study that got me thinking about how easy it is to be critical about data that do not conform to our preconceived notions.
A meta-analysis was recently published on the effects of chocolate consumption and cardiovascular disease (the full text article can be found here). The analysis only included 7 studies: 6 cohort studies, one cross-sectional study, and no randomized controlled trials. Needless to say, I was surprised by the relative strength and consistency of the findings.
Source: Buitrago-Lopez et. al British Medical Journal 2011.
The various levels of chocolate intake were associated with a 37% decrease in the risk of any cardiovascular disease, and a 29% decrease in the risk of stroke. This is indicated in the figure by the diamond-shaped confidence intervals, which represent the risk of the combined studies, stratified by cardiovascular outcome, hovering around estimated relative risks. There was no association between chocolate intake and heart failure, as you can see by the respective diamond crossing the relative risk axis of 1. Unfortunately, none of these studies measured CVD mortality or total mortality, so we don't know if this reduced CVD risk was associated with a longer lifespan.
If you've been following my previous posts, then hopefully you've taken note that all of these studies are observational rather than randomized and interventional. This makes this type of data prone to confounding variables (although many of these studies corrected for numerous confounders) and bias. The bias is especially worrisome given that chocolate is somewhat of a luxury that probably associates with discerning palates, and because of all the marketing buzz regarding cocoa's abundance of antioxidants.
Even the authors are dubious of their findings since chocolate has more than just antioxidant-rich cocoa. "The high energy density of commercially available chocolate (about 500 kcal/100 g) means excessive consumption will probably induce weight gain, a risk factor for hypertension, dyslipidaemia, diabetes, and cardiometabolic disorders in general." And they didn't even mention sugar, which I'm more concerned about than calories. And others are quick to point out that the association may very well not be due to the chocolate, as I mentioned above. Marion Nestle, at FoodPolitics, concurs: "wisely, the authors point out that much more research is needed to confirm these benefits, not least because the studies were observational, not clinical trials."
I agree with all of these issues. And personally, I need substantial evidence to convince me that a food is not just food, but is actually therapeutic. But if we are going to be skeptical about chocolate because of insufficient evidence, shouldn't we be just as skeptical of other foods or nutrients with similar insufficient evidence?
My last post on meta-analyses featured a study by Siri-Tarino et al. that concluded that prospective cohort studies show no association between saturated fat intake and CVD*. Chocolate, on the other hand, does show a benefit, even in studies with similar design. Furthermore, the reduction in the risk of stroke appears greater than might be expected from abstaining from processed meat. Despite these difference, recommendations to reduce saturated fat abound, while poor chocolate only gets criticism.
Again, we have to be skeptical about all of these studies until there is either sufficint clinical trial data, overwhelming epidemiological data, or preferrably, a combination of clinical trials, epidemiology, and laboratory experiments. It's imprudent to disparage a study because chocolate "just can't be healthy" or quickly agree with an association becuase processed meats "must be bad for you." We have to be equally critical of all studies of the same methodology, regardless of the outcome.
As with coffee, I'm not convinced that chocolate is a health food or will prevent heart disease; although if you can restrain yourself, it certainly doesn't appear harmful. And with more investigation, perhaps chocolate will be definitively healthy. So until we have more conclusive evidence, eat chocolate because it is divine, because we can mull over the richness of it will friends at the dinner table, and because it is the perfect end to a meal. And be equally skeptical of claims for all foods, regardless of how sweet, sweet, delicious they may be.
*As I described in the previous post, and to be accurate, there have been clinical trials to investigate the benefit of saturated fat reduction. Replacing saturated fat with polyunsaturated fat does indeed lower the risk of cardiovascular disease. Although it does not appear to reduce CVD mortality or total mortality.
"The great tragedy of Science (is) the slaying of a beautiful hypothesis by an ugly fact"
- Thomas Henry Huxley
I eat butter. Plenty of it. And I also started rendering lard and beef tallow for cooking. Not many people my age (26) have ever seen someone render lard, let alone use it readily. The reason I use these fats is because they are delicious, and because I can buy them at the farmers market. The conventional wisdom is that I should be scared - or nearly terrified - of saturated fat. Just take a look at this YouTube video from the U.K (see below).* The eerie lighting and tone of the television announcer is enough to make me worry, but let's take a look at some recent evidence regarding saturated fat and heart disease to see if the sink analogy is apropos.
The reason that saturated fat has been demonized by the nutrition community is because it is the cornerstone of the Lipid Hypothesis. The Lipid Hypothesis, which is more of a concept than a working hypothesis, proposes that dietary saturated fat elevates cholesterol in the blood, specifically LDL cholesterol, which in turn causes atherosclerosis. Cardiovascular disease (CVD) is characterized by atherosclerosis (plaque in the arteries) and includes coronary heart disease (CHD; atherosclerosis of blood vessels in the heart) and cerebrovascular disease (atherosclerosis of blood vessels in the brain leading to stroke).
Source: Wikipedia. Myristic acid, a saturated fat
The Lipid Hypothesis has always had its critics, but it has generally been accepted as fact. However, the totality of evidence is a bit fuzzy, as many studies are contradictory or only show a small benefit from restricting saturated fat. But since CVD is the leading cause of death in the U.S., public health authorities argue that any intervention, even if it's small or somewhat uncertain, will be beneficial to the health of the population. These circumstances are ideal for what medical researchers call a "meta-analysis."
Simply put, a meta-analysis is a single study that combines the results from numerous smaller studies to form an artifical mega-study that will have enough statistical power (ability to detect a difference between the control and experimental group) to determine what the true impact of an intervention is. The goal is to walk away with an actual number, such as a relative risk or mortality statistic. For a meta-analysis to be valid, the included studies must be sufficiently similar and test the same exposure-outcome hypothesis, e.g. dietary saturated fat causes heart disease. And researchers will further restrict their inclusion criteria to well designed studies. But even with these criteria, you might ask: if I lump all these studies together, doesn't that falsely give equal credibility to both good and not-so-good studies?
Researchers address the issue of good, better, and best studies by "weighting" the different study results. This means that each study will have more or less impact on the final outcome measurement - again, such as the relative risk for heart disease - depending on the quality of the study. What makes one study better than another? Usually the size of the study (10,000 subjects is likely more accurate than 1,000), the number of confounders adjusted for (older studies might only correct for age and smoking status, whereas a newer study might have adjusted for age, smoking, socioeconomic status, cholesterol, fasting glucose, etc.), and the quality of the methods used (in a diet study, a trial that provided all of the food for the subjects is much more reliable than giving subjects a questionnaire to determine what they ate). Once you have all the studies tabulated and weighted, then you can get a summary outcome measurement and a neat graph that looks something like this:
Fig 1. Anatomy of a meta-analysis
Every meta-analysis has a graphic like this (Fig. 1), and usually they have several more depending on how many hypotheses are being investigated. The x-axis represents the relative risk. If you remember from my last post, a relative risk of 1 means no difference in risk between groups, whereas a relative risk greater than 1 indicates that the "experimental" group has more risk than the control group. Each study included in the graph is represented by a hash; the length of the hash represents the 95% confidence interval for the relative risk of that study. If you are unfamiliar with statistics, the 95% confidence interval shows the range of numbers that we are reasonably confident includes the true effect of the experiment. A smaller interval means you are more confident of the real number. All you need to know is that if the confidence interval intersects the vertical line, then our safest bet is to conclude that there is no difference between the groups, since the relative risk is likely to be 1. If the confidence interval does not intersect the vertical line, then we can conclude with reasonable certainty that there is a difference in risk between the groups. At the bottom of the graph there is a diamond that represents the confidence interval derived from all the (weighted) studies included in the meta-analysis. As you can see in the example, the diamond does not intersect the vertical line, and so the relative risk of all the studies combined is 0.85. This would mean that the totallity of the evidence, based on this meta-analysis, indicates that the treatment reduces the risk of whatever outcome by 15%.
This is virtually all that you need to know in order to interpret a meta-analysis. And if you are still reading this post, now it's time to talk about saturated fat. Several large meta-analyses have been published in the past couple of years, and they all seem to give roughly the same answer.
In 2010, Siri-Tarino et al., published a meta-analysis on prospective cohort studies that evaluated the assocation of saturated fat with cardiovascular disease. Based on 21 studies, they find no difference in the risk of CVD (the confidence interval contained 1), and conclude that "there is insufficient evidence from prospective epidemiologic studies to conclude that dietary saturated fat is associated with an increased risk of CHD, stroke, or CVD." Interestingly, they assert that there is evidence of publication bias.** But as the authors correctly point-out, this meta-analysis was limited to cohort studies and not powered enough (not large enough) to analyze the effect of replacing saturated fat with specific nutrients, such as carbohydrates or polyunsaturated fats (PUFA; think walnuts and seed oils). Fortunately, other meta-analyses have.
Mozaffarian et. al performed a meta-analysis on randomized controlled trials that replaced dietary saturated fat with PUFA. They only looked at myocardial infarction (heart attack) and CHD death; these are known as "hard endpoints," as heart attacks and death are not usually mis-diagnosed. They show that increased PUFA intake (from 5% of daily calories to 15%) in place of saturated fat reduces the combined risk of heart attack and CHD death by 19% (Fig 2). However, when the analysis isolated people who did not have pre-existing CHD, the aforementioned benefit disappeared (became statistically insignificant). And there was no benefit seen in total mortality. That is, replacing saturated fat with PUFA did reduce CHD and CHD death, but the risk of dying from all causes remained the same.
What saturated fat is replaced with is not trivial. Mozaffarian et al. also analyzed studies that replaced saturated fat with carbohydrates and monounsaturated fat (think olive oil). The single randomized controlled trial showed that replacing saturated fat with carbohydrate had no benefit, and in cohort studies, carbohydrates appear to increase the risk of CHD. Monounsaturated fat is expected to lower the risk of CHD because of its beneficial effects on the cholesterol profile, but this has not been tested in a randomized controlled trial, and pooled analysis of available cohort data show a borderline increased risk of CHD (Fig. 3). Weird, huh?
And lastly, The Cochrane Collaboration has recently published an updated meta-analysis on the effect of dietary fat reduction and/or modification (PUFA instead of saturated fat) interventions, in randomized controlled trials, on cardiovascular outcomes. Similar to their previous study and the aforementioned meta-analyses, they find that reducing and/or modifying dietary fat intake, for greater than six months, reduces the risk of CVD (events, not deaths) by 14%. This decrease is attributable to:
"studies of fat modification and reduction (not studies of fat reduction alone), seen in studies of at least two years duration, in studies of men (and not those of women), and in those with moderate or high cardiovascular risk at baseline (not general population groups)."
This means that there is a small benefit from replacing some dietary saturated fat with unsaturated fats, but this may only apply to men and those who are at risk of or already have CVD. And again, with a "high quality of evidence" given the shear number and size of the studies included, reduction of fat intake or modification of fat intake did not decrease the risk of CVD mortality or total mortality.
To be a bit critical, meta-analyses are far from perfect. Remember, they are simply a pooling of results that improves statistical power in order to weed-out a result. They do not improve the quality of the data or the individual studies themselves. An accurate colloquialism is that a meta-analysis of garbage is still garbage. Given their difficulties, I wouldn't go out and replace all of my butter with vegetable oil and expect a precisely 14% decrease in my risk of CVD. But they give a nice summary of the evidence.
In the case of saturated fat, there is consistency between these analyses. Total dietary fat is irrelevant to heart disease. Replacing saturated fat with polyunsaturated fat modestly reduces the risk of cardiovascular disease, whereas replacing saturated fat with carbohydrate has no effect and may be harmful (if it's refined carbohydrates or sugar). But at the end of the day, modifying or decreasing saturated fat likely does not decrease the risk of dying from heart disease and certainly has no effect on total mortality. So after looking over these meta-analyses and bouncing it off of my current understanding of diet and diease, here is my conclusion: there is clearly no over-whelming evidence that saturated fat is bad, and in fact, there doesn't really seem to be any evidence. And if it replaces sugar (butter instead of jam on toast), then it might actually be "healthy." And yes, I'm aware of how crazy that notion sounds. So what is one to do?
There are plenty of people who have given up butter and whole fat milk because of trepidation about saturated fat bringing them to an early grave. Or in the words of Michael Pollan from In Defense of Food, "over the last several decades, mom lost much of her authority over the dinner menu, ceding it to scientists and food marketers (p. 3)." Since the message to restrict saturated fat was loud enough to disrupt dinner, it is shocking that the evidence seems to have vanished. And this is why the conventional wisdom will not change overnight. Marion Nestle, a nutrition professor whose schtick I otherwise like, wrote a post on her blog to acknowledge these recent publications, but she inexplicably fell short of saying that saturated fat is probably harmless. So in my opinion, it seems that the facts have ruined yet another hypothesis, because clearly, butter isn't out to get you.
* Ignore the impossibility that the "saturated fat" in the video is liquid in the refrigerator but solid at room temperature in the drain. Saturated fats (coconut oil, beef tallow, butter) are solid in the refrigerator AND at room temperature.
** Smaller studies showed an increased risk of CVD from dietary saturated fat, but larger studies, which will always be published since they are well-known and anticipated, showed an equal distribution of increased, decreased, and neutral risk. The implication is that smaller studies that showed a detrimental effect of saturated fat were published, whereas smaller studies that showed no effect or a beneficial effect of saturated fat were either not submitted for publication or not accepted for publication.
This meal was actually about a month ago, but the memory still remains. When we were visiting the girlfriend's parents, we made a Thai dinner to enjoy on the patio on a mild NorCal summer evening. Talking about isolated nutrients can get you into trouble because they are naturally part of a whole food. But the same is true for foods. They are normally a part of a meal. I want to share our entire meal (recipes) because I think that it was truly greater than the sum of its parts.
Grilled chicken with red curry sauce
Sauce:
In a medium bowl, combine 10 oz. of coconut milk, juice from 2 limes and 1/2 tsp of lime zest, 1 tbsp fish sauce, and 1 tbsp red curry paste. In a heavy-bottomed sauce pan, heat 1/3 water and 1/3 sugar and allow to boil for 3 minutes - this will create a nice thick simple syrup. Remove pan from heat, add coconut mixture, and return to heat and allow to simmer just under 10 minutes; whisk frequently to ensure syrup does not lump together. Retain 1/3 cup of sauce for serving.
Chicken
Prepare 1.5 lb bone-in (1 lb boneless) chicken thighs by drying with a paper towel, and liberally seasoning with salt and pepper.
Grill on a pre-heated grill to your liking. I personally grill chicken thighs on medium-high until a rich dark brown; turning relatively frequently. Cooking thighs until roughly 180°F will render them less gummy, and they will not dry out at this temperature like breast meat will.
Once the chicken is a dark golden-brown, baste red curry sauce onto each piece, flip and cook for one minute, baste the opposite side, and then flip once again for another minute. Repeat if there is extra sauce.
4. Serve chicken with grilled zucchini (from the garden if you have it!) and the reserved red curry sauce. Garnish with limes and scallions.
Asian-style cucumber salad
Peel and thinly slice 4 cucumbers. Set in the fridge to chill while preparing dressing.
Simmer 1/3 cuprice wine vinegar until reduced to 2 tbsp; pour into bowl to cool.
While vinegar is cooking, whisk in juice from 1/2 of a lime, 2 tsp. honey, 1 tbsp. fish sauce, and 2 tsp. olive oil.
Mince 1-2 seeded serrano chiles, and finely chop 1/4 cup of fresh mint and 1/4 cup fresh basil.
In a large bowl, combine cucumbers, dressing, and chopped chiles and herbs. Season with salt and pepper, to taste.
Coconut rice
I used this recipe. Garnish with cilantro and scallions. Full-fat coconut milk, please.
I occasionally eat white rice. But to mitigate its nasty effects on blood sugar, I drowned it in coconut milk and crowded it out with meats and veggies :)
A nuclear bomb is far scarier than a fire cracker. Both are dangerous, but a nuclear bomb is clearly more destructive. Not exactly rocket science. In science-speak, the magnitude of this destruction is called the effect size. Researchers spend a lot of time determining if an effect is real and how big the effect actually is. Unfortunately, this information tends to distill down to "there was an effect" or "there was no effect." This post is inspired by a lunch conversation with the girlfriend's parents, as it seems that nearly every food is out to get us. It is one thing to say that a food has an effect on our health, but it's just as important to ask how big the effect actually is.
Effect size is an easy concept to measure in the laboratory. A treated neuron can depolarize 5 times per second while a control neuron can depolarize 2 times per minute - an increase of 3 times per minute. Differences in blood concentrations of a hormone, weight gain in rodents, and increased muscle mass are all easily recognized as an effect size. In nutritional epidemiology, and epidemiology in general, the effect size is the strength of the association between an exposure (a food) and an outcome (a disease or mortality). This is often measured as a relative risk.
Before I can talk about relative risk, I should explain absolute risk. Absolute risk is the probability that an individual will develop a health outcome during a stated period of time (Fig 1). Absolute risk, often measured as an incidence rate, is only meaningful if we have the number of outcomes AND the size of the population at risk AND a period of time. The statements "4 men had heart attacks" and "4 out of 10 men had heart attacks," do not contain enough information to draw meaningful conclusions. Rather, we need to know that "4 out of 10 men had heart attacks over the 5 year study period." If we have the valid rate information about one group of people, we can compare it to another group's. Absolute risk is vital for the real world impact of some exposure, but we rely on relative risk to get a grasp on the effect size of an exposure.
Fig 1. Absolute Risk
Relative risk is simply the ratio of the absolute risk in the exposed group compared to a non-exposed group (i.e. control group). If there is no difference in incidence rates of disease, then the RR will be 1. If the exposed group has a higher rate, then the RR will be greater than 1. And if the exposed group has a lower rate, then the RR is less than 1. They are often discussed as percents (e.g. an RR of 1.3 means a %30 increased risk in the experimental group compared to the control). Scientific journals will report rate ratios, hazard ratios, observed-to-expected ratios, and odds ratios - all of which are permutations of relative risk that are particular to different study designs. Now that we're up to speed on relative risk, let's talk about effect size.
Fig 2. Relative Risk
Effect size can help determine if an association seen in a study is causal. Provided that the study is reasonably well conducted, a large relative risk suggests a causal association between the exposure and the outcome. But how large is large? Smoking and lung cancer are a textbook example of this principle. Lung cancer is exceedingly rare in populations that do not smoke, especially if there are no industrial hazards. Based upon an average of relative risks derived from several cohort studies (remember the limitations), men and women who smoke more than 20 cigarettes per day are 16 times more likely to die of lung cancer than non-smokers. That's a whopping 1,500% percent increase in the risk of dying from lung cancer! More moderate smokers have a considerably lower risk than the heaviest smokers, but are still far more susceptible with a relative risk of 5.0 and 9.0 for women and men, respectively. The shear size of the effect provides evidence that smoking can cause lung cancer. So what about not-so-large effects?
Because nutritional epidemiology relies heavily on observation rather than randomized controlled trials, the strength of an association can be distorted by confounding variables. In fact, chances are that every observed effect is confounded by myriad unmeasured variables; many are insignificant, but some are important. A study from the Health Professionals Follow-Up cohort demonstrated that men who consumed the most sugar-sweetend beverages had a 25% increased risk of developing type 2 diabetes over the 20 year follow-up. Men who drank the most artificially-sweetend beverages (e.g. diet soda) were 91% more likely to develop the disease compared to those who drank the least. However, after adjusting for the known confounding variables, the sugar-sweetened beverages still increased the risk by 24%, whereas the risk seen in the diet-rinkers was completely abolished. It is easy to see how a relatively large effect size suggests causality, but does not prove it. But what if the effect persists after adjusting for confouners?
Source: Wikipedia: Processed meat
A relatively recent article in the American Journal of Clinical Nutrition reported that men who reported eating the most processed meat (2 ounces or greater per day) compared to those who ate the least (less than 0.7 ounces per day) had a 23% greater chance of having a stroke over the course of the 10 year study. Fresh red meat had no effect. 23% sounds fairly alarming; should we go to our fridge and throw out all of our salami and deli meat? Looking at it another way, the average man in this study had a 6% chance (2409 out of 40, 291 men) of having a stoke over an average follow-up of 10.1 years. By eating the highest amount of processed meat, his chances now increase to 7.4% (6% x 1.23). His absolute risk increased by 1.4%*.
This may seem like a lot to you. But also bear in mind that obesity and heavy smoking increase the risk of stroke by 100% compared to lean persons and non-smokers, respectively. Using the average Swedish man above, each factor would increase the risk of stroke from 6% to 12%. Trading processed meat for fresh meat surely doesn't cause any harm, and this potential risk may simply be worth avoiding. But think about how we need to approach this as scientific evidence. Given that this has all the standard caveats of a prospective cohort study; and that the food record was based on a single survey given at the beginning of the study; and that you can never meaasure all of your confounders (they forgot sugar); are studies like this actually capable of detecting a true 23% increase in the risk of a specific mortality from a single type of food? And is it worth constantly changing our diets when we're presented with these kinds of results?
Next time you hear a claim about a foods effect on health, or read another headline, make sure you find out how strong the effect actually is. More often than not, you will only have access to the relative effect. So keep in mind that if a disease is exceptionally rare, it will take a very high relative risk to have any real impact. The risk of non-Hodgkin's lymphoma is .003 per 1,000 people over 1 year, which is so unlikely that an increased risk of 15% probably doesn't reflect a true association, and even if it does, it is virtually irrelevant. The relative risk allows us to better comprehend the effect, but the absolute risk is what matters to the individual.
The problem with nutrition is that when you change something in your diet, it has to be replaced by something else. How can you know you are making a change for the better? And enjoying your food is important as well. There are few things better than salami with cheese and wine, and bacon is arguably the best food there is. The goal is not to disparage every study, but for the sake of health and culture, be skeptical about small numbers.
*The baseline risk I am using for this example is a crude estimate. By simply using the number of strokes dived by the number of study participants over 10.1 years, I am ignoring the fact that some men were followed for less while some where followed for more. However, this crude estimate approximated stroke statistics in the U.S. that I came across. So don't hate!
I've been fairly consistent about getting my weekday ground beef from the farmers market, but I wanted to get something different for saturday night. I enjoy staying home for a nice saturday dinner for several reasons: I have more control over the quality and quantity of my food, my girlfriend doesn't have to worry about gluten contamination, and I am more comfortable about eating medium-rare beef. The latter is especially appealing after recently reading Fast Food Nation. Eesh But I have to make sure that I can out-do any steak house.
The more enticing cuts of grass-fed beef can be prohibitively expensive for a graduate student. So to lower the cost, I was looking for something esoteric. A shoulder clod* costs much less than steaks and is even cheaper than some other roasts, AND it happened to be on sale. You just have to deal with the toughness of the cut.
Shoulder clod (far) and neck bones (near; a previous post...)
The entire goal of this recipe is to cook low-and-slow while still achieving medium rare, as both will improve tenderness. As you'll see, wrapping the nearly finished roast in aluminum foil and a kitchen towel will allow the roast to finish cooking (medium-rare) and maintain enough heat to continue tenderizing the meat. You'll sacrifice the texture of the crust, but it's well worth it.
Roast Shoulder Clod
Use a 2.5 lbshoulderclodroast. Pat the roast dry and season liberally with salt and pepper, and a bit of garlic powder. Cover tightly with plastic wrap and store in the fridge for 12-24 hours (although I only did 3!).
Preheat the oven to 225°F**, and let the roast rest at room temperature for 30 minutes.
Heat some beef tallow, or other high-heat cooking fat, in a heavy-bottomed pan. Sear all four sides of the roast.
Place beef on a baking sheet and roast for 90 minutes, or until internal temperature reaches 135°F (for medium-rare). Remove from the oven and wrap roast in heavy-duty aluminum foil, and then wrap in a kitchen towel. Allow roast to rest like this for another 30 minutes.
While resting, open a nice Cab that you essentially forgot that you had. And fry-up some gluten-free squash blossoms, for good measure.
5. Slice as thin as possible. Impossibly thin if you can...
Serve with some market vegetables. Make sure to arrange food in a pretentious "man, I gotta' blog about this meal" sort of way.
*From what I can tell, the shoulder clod that I bought was only part of a true shoulder clod. Technically, beef clod refer to an entire beef shoulder. Similar to the Boston Butt of a pig.
**I'm aware that it is generally a poor idea to rely on the oven in the summer, especially if you don't live in mild California. This should work just as well on a grill or in a smoker. However, if using a grill, roast meat on the unlit side of the grill and do your best to maintain this low temperature; this will mimic an oven.
So, ignore the name of my blog for this post. That's right. It's time for some food science. But in my defense, it involves traditional food (kefir) and good ol' falsifiable science. That's right. I did a an experiment to determine whether or not one should rinse kefir grains before adding them to a fresh batch of milk.
Kefir is not a popular food, at least not compared to its yogurt-y cousin. So when you decide to go out and make it on your own, you have to rely on what you can dig up on the internet. And true to the internet's reputation, you can find any possible answer for whatever question you are asking. One simple question that I had was whether or not I should be rinsing the grains between batches. The information I received with my grains said I should not rinse them. However, Nourishing Traditions seems to suggest that they should be rinsed. There was only one way to find out. I hypothesized that rinsing the grains would blunt their capacity for producing kefir, and therefore produce a milder kefir.
Fig 1. Separated and weighed to 10 grams
Methods
The grains were rinsed and randomized. Two groups, each weighing 10 grams (g) and containing 18 grains (Fig 1), were formed. Most batches were made with 8 ounces of organic pasteurized whole milk; the last couple of batches were a bit over 8 ounces to accommodate the increased fermentation. Fermentation was 12-14 hours per day. Clean jars were used each time.
Fig 2. Kefir preparation. Clean jars, 8 oz. milk, cover with paper towel.
The time and temperature were not always consistent. However, because the jars were adjacent to each other at all times, any day-to-day variation would affect each group equally, and would therefore not bias the results. The only difference between the groups was that the experimental (washed) group was rinsed under cold tap water in a stainless steel strainer until curds were removed, roughly 10 seconds. The control group was simply placed in a new batch of fresh milk. The experiment ran for 11 days, and on the 7th and 11th days, both groups of grains were washed and weighed, and the two different batches were tasted by a blind taster a.k.a. the girlfriend.
Results
Both groups increased in weight at the same rate. However, the grains in the unwashed group were more dense than the washed group on day 7 (0.67 g/grain vs. 0.48 g/grain) and on day 11 (0.74 g/grain vs. 0.51 g/grain). Thus, rinsing reduced the density of the grains by 30%, and produced many small grains (Figs. 3-5).
Fig 3. Unwashed (left) and washed (right) groups at the end of the study.
Fig. 4 Results of control (unwashed)
Fig 5. Results of experimental (washed) group.
Tasting results were consistent between the 7th and 11th day. Both batches of kefir reportedly tasted as kefir should, and both batches were similarly thick, both in the glass and in mouthfeel. However, the unwashed kefir was "definitely more sour." Furthermore, the washed kefir had a lighter effervescence with smaller bubbles and "a more full kefir taste." The unwashed group appears to ferment faster, as there was usually more whey present (Fig 6).
Fig 6. The unwashed (left) was usually more fermented.
Discussion
This experiment demonstrates that rinsing kefir grains between batches produces more and smaller grains than when grains are left unwashed. Furthermore, these rinsed grains tend to produce a milder kefir. While I can surmize that this occurs because the unwashed grains produce kefir at a faster rate (and therefore make a more kefir, kefir), that will require another experiment.
I'm definitely confident in these results, but I would love to hear other peoples' experience with washing their grains. The results might have been more dramatic had I not rinsed and weighed the grains mid-experiment, but then again, this added a bit of reproducibility within the study. Unfortunately, I was not blinded to the treatment group. And come to think of it, the kefir wasn't blinded with a placebo. I already anthropomorphize my kefir grains enough as it is, but perhaps they knew what group they were in...
So, what can we take away from this bit of food science? There are likely many recommendations for treating kefir grains because there is no obvious best way. While I would argue that the density produced by leaving the grains unwashed is evidence of "healthier" grains, if you prefer the taste of a mild kefir, then you would be better off rinsing them, at least occasionally. Or, as I've started doing, rinse the grains on warmer days or when you might make it home late and risk over fermenting the kefir. Either way, it's between you and your kefir.
Now, it's time for a kefir smoothy. Theory into practice, I suppose. Cheers!
