Tuesday, December 17, 2019

She lost 30 pounds in 3 months and dropped 3 pants sizes

Alicia embraced macros as a lifestyle tool, not just another diet. 

Alicia is the mom of 2 little girls and works full-time. She came to me after feeling frustrated with her weight loss progress, despite her efforts in the gym.

“I started tracking macros when I wasn’t feeling my best. My progress was lacking despite my efforts in the gym; I needed to revamp my nutrition. 

The best thing about the 1:1 coaching was the accountability. Hands down, it was the best thing for me. I needed someone to check in and see how I was doing. I needed someone to keep me accountable until I was accountable to myself. 

In the first 90 days, I saw some amazing results, and it was great to attain those, but the best thing was the fact that I’ve maintained those results for 10.5 months now. I was stricter in the beginning, but, lately, I’m just eyeballing things. It’s really a lifestyle for me now. 

It’s been a great experience working with Tina. I’d highly recommend her to anyone else. I certainly learned a lot about myself, a lot about counting macros, staying consistent, and how to make it a lifestyle instead of a fad diet that gets boring after a while. 

Macros are definitely something busy people can obtain and customize to your lifestyle. I can’t speak more highly about the program. I’ve had great success, and I hope you do too!” 

[ALICIA’S TESTIMONIAL]

When you strap in for the long haul, it’s much easier to create an eating strategy that works for you. Like Alicia, if you have patience with the process, you’ll be able to uncover the things that are most important to you when it comes to your personal preferences, unique metabolism, and lifestyle habits. Macros aren’t a quick fix, but instead a complete lifestyle change that leads to sustainable and long-lasting results.

I only have a limited number of coaching spots open for the new year, so if you’re interested, please click here to sign up.

Let me know what questions you have – happy to connect with you on anything!

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7 Mistakes to Avoid When You’re Reading Research

A couple weeks ago I wrote a post about how to read scientific research papers. That covered what to do. Today I’m going to tell you what NOT to do as a consumer of research studies.

The following are bad practices that can cause you to misinterpret research findings, dismiss valid research, or apply scientific findings incorrectly in your own life.

1. Reading Only the Abstract

This is probably the BIGGEST mistake a reader can make. The abstract is, by definition, a summary of the research study. The authors highlight the details they consider most important—or those that just so happen to support their hypotheses.

At best, you miss out on potentially interesting and noteworthy details if you read only the abstract. At worst, you come with a completely distorted impression of the methods and/or results.

Take this paper, for example. The abstract summarizes the findings like this: “Consumption of red and processed meat at an average level of 76 g/d that meets the current UK government recommendation (less than or equal to 90g/day) was associated with an increased risk of colorectal cancer.”

Based on this, you might think:
1. The researchers measured how much meat people were consuming. This is only half right. Respondents filled out a food frequency questionnaire that asked how many times per week they ate meat. The researchers then multiplied that number by a “standard portion size.” Thus, the amount of meat any given person actually consumed might vary considerably from what they are presumed to have eaten.

2. There was an increased risk of colorectal cancers. It says so right there after all. The researchers failed to mention that there was only an increased risk of certain types of colon cancer (and a small one at that—more on this later), not for others, and not for rectal cancer.

3. The risk was the same for everyone. Yet from the discussion: “Interestingly, we found heterogeneity by sex for red and processed meat, red meat, processed meat and alcohol, with the association stronger in men and null in women.” Null—meaning not significant—in women. If you look at the raw data, the effect is not just non-significant, it’s about as close to zero as you can get. To me, this seems like an important detail, one that is certainly abstract-worthy.

Although it’s not the norm for abstracts to blatantly misrepresent the research, it does happen. As I said in my previous post, it’s better to skip the abstract altogether than to read only the abstract.

2. Confusing Correlation and Causation

You’ve surely heard that correlation does not imply causation. When two variables trend together, one doesn’t necessarily cause the other. If people eat more popsicles when they’re wearing shorts, that’s not because eating popsicles makes you put on shorts, or vice versa. They’re both correlated with the temperature outside. Check out Tyler Vigen’s Spurious Correlations blog for more examples of just how ridiculous this can get.

As much as we all know this to be true, the popular media loves to take correlational findings and make causal statements like, “Eating _______ causes cancer!” or “To reduce your risk of _______, do this!” Researchers sometimes use sloppy language to talk about their findings in ways that imply causation too, even when their methods do not support such inferences.

The only way to test causality is through carefully controlled experimentation where researchers manipulate the variable they believe to be causal (the independent variable) and measure differences in the variable they hypothesize will be affected (the dependent variable). Ideally, they also compare the experimental group against a control group, replicate their results using multiple samples and perhaps different methods, and test or control for confounding variables.

As you might imagine, there are many obstacles to conducting this type of research. It’s can be expensive, time consuming, and sometimes unethical, especially with human subjects. You can’t feed a group of humans something you believe to be carcinogenic to see if they develop cancer, for example.

As a reader, it’s extremely important to distinguish between descriptive studies where the researchers measure variables and use statistical tests to see if they are related, and experimental research where they assign participants to different conditions and control the independent variable(s).

Finally, don’t be fooled by language like “X predicted Y.” Scientists can use statistics to make predictions, but that also doesn’t imply causality unless they employed an experimental design.

3. Taking a Single Study, or Even a Handful of Studies, as PROOF of a Phenomenon

When it comes to things as complex as nutrition or human behavior, I’d argue that you can never prove a hypothesis. There are simply too many variables at play, too many potential unknowns. The goal of scientific research is to gain knowledge and increase confidence that a hypothesis is likely true.

I say “likely” because statistical tests can never provide 100 percent proof. Without going deep into a Stats 101 lesson, the way statistical testing actually works is that you set an alternative hypothesis that you believe to be true and a null hypothesis that you believe to be incorrect. Then, you set out to find evidence to support the null hypothesis.

For example, let’s say you want to test whether a certain herb helps improve sleep. You give one experimental group the herb and compare them to a group that doesn’t get the herb. Your null hypothesis is that there is no effect of the herb, so the two groups will sleep the same.

You find that the group that got the herb slept better than the group that didn’t. Statistical tests suggest you can reject the null hypothesis of no difference. In that case, you’re really saying, “If it was true that this herb has no effect, it’s very unlikely that the groups in my study would differ to the degree they did.” You can conclude that it is unlikely—but not impossible—that there is no effect of the herb.

There’s always the chance that you unwittingly sampled a bunch of outliers. There’s also a chance that you somehow influenced the outcome through your study design, or that another unidentified variable actually caused the effect. That’s why replication is so important. The more evidence accumulates, the more confident you can be.

There’s also publication bias to consider. We only have access to data that get published, so we’re working with incomplete information. Analyses across a variety of fields have demonstrated that journals are much more likely to publish positive findings—those that support hypotheses—than negative findings, null findings (findings of no effect), or findings that conflict with data that have been previously published.

Unfortunately, publication bias is a serious problem that academics are still struggling to resolve. There’s no easy answer, and there’s really nothing you can do about it except to maintain an open mind. Never assume any question is fully answered.

4. Confusing Statistical Significance with Importance

This one’s a doozy. As I just explained, statistical tests only tell you whether it is likely that your null hypothesis is false. They don’t tell you whether the findings are important or meaningful or worth caring about whatsoever.

Let’s take that study we talked about in #1. It got a ton of coverage in the press, with many articles stating that we should all eat less red meat to reduce our cancer risk. What do the numbers actually say?

Well, in this study, there were 2,609 new cases of colorectal cancer in the 475,581 respondents during the study period—already a low probability. If you take the time to download the supplementary data, you’ll see that of the 113,662 men who reported eating red or processed mean four or more times per week, 866 were diagnosed. That’s 0.76%. In contrast, 90 of the 19,769 men who reported eating red and processed meat fewer than two times per week were diagnosed. That’s 0.45%.

This difference was enough to be statistically significant. Is it important though? Do you really want to overhaul your diet to possibly take your risk of (certain types of) colorectal cancer from low to slightly lower (only if you’re a man)?

Maybe you do think that’s important. I can’t get too worked up about it, and not just because of the methodological issues with the study.

There are lots of ways to make statistical significance look important, a big one being reporting relative risk instead of absolute risk. Remember, statistical tests are just tools to evaluate numbers. You have to use your powers of logic and reason to interpret those tests and decide what they mean for you.

5. Overgeneralizing

It’s a fallacy to think you can look at one piece of a jigsaw puzzle and believe you understand the whole picture. Any single research study offers just a piece of the puzzle.

Resist the temptation to generalize beyond what has been demonstrated empirically. In particular, don’t assume that research conducted on animals applies perfectly to humans or that research conducted with one population applies to another. It’s a huge problem, for example, when new drugs are tested primarily on men and are then given to women with unknown consequences.

6. Assuming That Published Studies are Right and Anecdotal Data is Wrong

Published studies can be wrong for a number of reasons—author bias, poor design and methodology, statistical error, and chance, to name a few. Studies can also be “right” in the sense that they accurately measure and describe what they set out to describe, but they are inevitably incomplete—the whole puzzle piece thing again.

Moreover, studies very often deal with group-level data—means and standard deviations. They compare the average person in one group to the average person in another group. That still leaves plenty of room for individuals to be different.

It’s a mistake to assume that if someone’s experience differs from what science says it “should” be, that person must be lying or mistaken. At the same time, anecdotal data is even more subject to biases and confounds than other types of data. Anecdotes that run counter to the findings of a scientific study don’t negate the validity of the study.

Consider anecdotal data another piece of the puzzle. Don’t give it more weight than it deserves, but don’t discount it either.

7. Being Overly Critical

As I said in my last post, no study is meant to stand alone. Studies are meant to build on one another so a complete picture emerges—puzzle pieces, have I mentioned that?

When conducting a study, researchers have to make a lot of decisions:

  • Who or what will their subjects be? If using human participants, what is the population of interest? How will they be sampled?
  • How will variables of interest be operationalized (defined and assessed)? If the variables aren’t something discrete, like measuring levels of a certain hormone, how will they be measured? For example, if the study focuses on depression, how will depression be evaluated?
  • What other variables, if any, will they measure and control for statistically? How else will they rule out alternative explanations for any findings?
  • What statistical tests will they use?

And more. It’s easy as a reader to sit there and go, “Why did they do that? Obviously they should have done this instead!” or, “But their sample only included trained athletes! What about the rest of us?”

There is a difference between recognizing the limitations of a study and dismissing a study because it’s not perfect. Don’t throw the baby out with the bathwater.

That’s my top seven. What would you add? Thanks for reading today, everybody. Have a great week.

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Regenerative Agriculture: Are We Walking The Walk, Or Talking The Talk?

Last week, I talked with Will Harris of White Oak Pastures as part of our Guest Expert Interview Series in The Healthy Rebellion. I knew it was going to be an interesting interview but wow did he impress beyond expectations.

Will is an amazingly interesting and smart individual who opened our eyes to the challenges facing farmers practicing real, sustainable agriculture. 

One Healthy Rebellion community member said this after watching:

“Every time I talk to a wise farmer, I always walk away with my cup flowing over. People who manage animals, and listen to those animals when they make clear what is needed, are infinitely wise. Thanks for sharing this conversation.” 

Why am I telling you this? 

Well, it had such a profound impact on us that I felt the need to share. 

Nicki and I buy a good deal of our meat from local farmers, but often supplement with grass fed options from Costco and other grocery stores. Hearing Will talk about how these multinational companies are purchasing beef overseas at the cheapest prices they can find and shipping it to the states, thereby destroying the local markets…well, it made me realize we can do better.

I often talk about not letting perfectionism get in the way of “good enough” but we have committed to buying as much as possible from local producers. 

We have a decent sized chest freezer and we have talked to folks that are interested in going in on future purchases. This does not mean I’m going to scrutinize the hamburger I have when eating out (although I may bend the proprietors ear about local sourcing) but, frankly, I’ve been lazy on this topic. No more. 

Will’s commitment to the re-enrichment of rural America and the effect his farm (and others like his) are having on local communities was an amazing eye opener on the impact we can have when we choose to only buy local meat. 

Yes, it’s work. 

Yes, sometimes it costs a bit more.

But if you can swing shifting even a portion of what you consume to locally produced, it WILL have an effect. 

Given the power of media, the Information Monopolies, and government it can often feel like peeing into the wind to affect any change…but voting with our dollars not only matters, it matters in the most important place: our local communities. 

Anyways, I hope this post inspires at least one person to change their ways and just do a little bit better as you can. It will have profound impact. 

If you want to learn more about Will Harris, White Oak Farms, and sustainable, regenerative agriculture, please visit https://www.whiteoakpastures.com/ or check them out on Instagram @whiteoakpastures

If you want to see the full interview, it’s live in The Vault in The Healthy Rebellion. Click here to join us. 



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Powdered Bums + Toilet Paper

Recycled Toilet Paper Round II

Remember back in July I did a sponsored post with a toilet paper company called Who Gives A Crap? They make 100% recycled TP that is conveniently shipped to your door and donate 50% of profits to sanitation projects around the world. Well it’s been FIVE months and we just ran out!! As promised, I ordered more. I really do love this TP, and this post is of no obligation to them. Also: I used my own promo code to order. It still works for $10 off – click here.

More than anything else, I really loved how long my box lasted. I really haven’t thought about toilet paper in five months. I keep the pretty papered rolls on the top shelf of the kids’ bathroom in a basket. And I take rolls to our other two bathrooms every few weeks as needed to store right there.

Of course, Birch thought the rolls were for him to play with when I unpacked them. The crinkly paper is worth its weight in gold because it kept him entertained for about 20 minutes!

They also make paper towels!

I also tried the paper towels and ordered a six pack. I think the transition from Target toilet paper to WGAC’s was a bit easier to make than going from Bounty to WGAC paper towels. The WGAC paper towels are really smooth. I do like that the roll is a bit shorter than Bounty so I’m using less per sheet without really realizing it. I am all for making swaps that force me to use recycled and use less.  Because it’s a little shorter, if you have a countertop roll holder that sits vertically you might see the inside part a bit, FYI.

Holiday Bottoms Up!

In other bum news, look at the new holiday prints from Hello Bello!

I love these diapers for many reasons, but these prints are so cute.

Here’s a cute pic!

And if you’re someone who doesn’t really care about TP or diapers, here’s a pic of the boys for you! They have been playing together so well <3

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Vegan Pesto Recipe With Basil And Cashews

This vegan pesto is a delicious, dairy free, basil pesto recipe that’s super easy to make and will leave you wanting more! This is my favorite vegan…



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