Just Watched: Low-Carb High Fat Diet in Type 1 Diabetes

The origin of this post is that I sent a tweet earlier this week regarding the current crisis in insulin pricing referring to the Banting Diet, which is the precursor of the low-carb high fat diet (or LCHF diet). I sometimes do this (sending unclear messages) assuming that people will figure them out, and usually, that’s not the outcome 🙂 . At least it starts conversation (maybe I do this subconsciously, I don’t know).

In any event, I have been interested in nutrition for a long time and more interested recently (see:Just Read: Why Eating Fat May Not Make You Fat (The Big Fat Surprise) ), as more data is being produced about where our dietary guidelines came from. In the case of diabetes, I have been curious about the ways the medical and other professions counsel patients on diets in ways that may actually increase their risk of diabetes and increase their insulin requirement.

My question, therefore, has been whether the need for insulin could be eliminated in some people and reduced in others, which would blunt the impact of pricing and make living with diabetes more affordable. The other question I have is about the whether reducing the use of specialized insulins for some population would have an added effect, making the pricing power, less powerful.

I’ve read a few papers about this. I don’t feel comfortable doing a literature review myself because these days it’s really hard to interpret papers if hidden biases aren’t known. That and I may be a physician, but I do not know what it is like to live with diabetes. I do know what it is like to live as a former fat person so there is some relevance here for me.

Through the magic of YouTube, Dr. Troy Stapleton (@drtroystapleton) explains his own journey as a person with type 1 diabetes and the LCHF diet. He’s going to to have much more credibility than I and this is a good science-based + authentic overview from a patient perspective. Watch:

A person who produces insulin on this diet is going to have an insulin production curve closer to a person with type 1 diabetes (flat) compared to a person without diabetes (insulin spikes), with the idea that insulin and specifically too much insulin is a requirement for obesity.

#ILN innovating in nutrition, too. #LCHF in Chicago. #ketogenic #ketogenicdiet #lessinsulin

A post shared by Ted Eytan (tedeytan) on

I’m planning to do some more study this summer. At the same time, there are far more experienced researchers, journalists, physicians and scientists engaged in this work, so I’m more interested in dialogue than leadership (they are doing just fine). I always say if there’s a better way to do something, I want to know about it.

This is life in the family medicine revolution (#FMrevolution), where unlimited curiosity reigns in the interest of a person, family, community’s long healthy life. Feel fee to let me know your thoughts in the comments.

Just Read: Does Hyperinsulinemia cause obesity, and academic discourse on Twitter (finally)

As I have been reading a lot about nutrition lately (see this post for background: Search Just Read: Why Eating Fat May Not Make You Fat (The Big Fat Surprise), I happened on this article of relevance.

Templeman NM, Skovsø S, Page MM, Lim GE, Johnson JD. A causal role for hyperinsulinemia in obesity. J Endocrinol [Internet]. 2017 Mar 1;232(3):R173–83 discusses experiments in mice with their insulin production modulated to see what happens to their weight.

The content here is relevant because many health professionals (okay, me) are not trained well in the causes of obesity, and the causes are not actually known in all cases. So this is a good review of what’s known about the physiology, plus the experiment itself, which I’ll discuss in a bit.

Social Media as a platform for academic exchange – finally

In some of the work I do, and the work I am doing now, it is a continual source of marvel that some of the most important scholars in a field (you name it) do not have an identity in social media (Do physicians tweet about environmental stewardship in health care?). I give presentations and talks to them about this…and some of them invite me to give them presentations and talks about this (oh, like this one: Dialogue about #hcsm at the 2013 #AAMCJtMtg – Academic Medicine and Social Media).

In this particular space, I think it’s even more critical because from my perspective, even as a physician, it’s not possible to understand the meaning of a published paper without asking questions.

Why?

  • This is a slightly controversial topic right now
  • Potential for conflict of interest is everywhere
  • There are groups of scientists working to analyze every piece of literature in this space…and they are finding lots of flaws

Back to this article, then, I was pleased to find that

  • The author included his twitter handle on the piece (@JimJohnsonSci – Hooray)
  • The author entertained conversation about the piece on twitter (but any social network would be fine)

This is a tweet that has a thread connected to it about this study (to see the thread you have to click through to it)

…and the answer is

Notwithstanding, the results of this first study demonstrated for the first time in any mammal that
hyperinsulinemia is required for weight gain.

Hyperbolic proclamations aside from the conversation below, the two things, the paper, and the conversation among scholars, helps put things in their place mentally. It’s not one or the other.

In this case, this piece of data doesn’t unlock next steps in preventing obesity (follow the conversation … ), it’s helpful though.

Bad News/Good News (mostly good news, glass 3/4 full)

The bad news is, with every paper I read, I now need to go find out where the conversation is happening so I can learn. The good news is, the conversation is happening in a place where I can learn.

Finally.

Just Read: Study – Wearables don’t improve weight loss – can you outrun a bad diet?

I stopped wearing a fitness tracker because it DEmotivated me, by reminding me of the times I was not meeting my activity goals

This is what an attendee said at the recent convening on Making Health Care Measurement Patient-Centered (a proxy for respecting people in health care).

This study published in JAMA a few weeks ago (September, 2016), produced unexpected (and curious) results.

Overweight and obese younger people randomized to receive wearable devices as part of a weight loss program gained back more weight than users who did not receive wearables, after an initial 6 month weight loss.

Both sets of subjects did not have significantly different rates/intensity of physical activity over the 2 year study, and their dietary intake was not statistically significant from each other (calories taken in slightly less for the wearables group at the end). Specifically, the group with the wearable did not exercise more than the group without the wearables.

I was of course curious and decided to look more closely at the data. I produced some charts below.

Here are the things I noticed

  • Subjects were randomized at the very beginning of the study, not at the 6 month mark, when the wearables were initiated. Did they know which group they were in at the beginning and did this shape their behavior?
  • I ask the question above, because the one thing I noticed in charting the data is that the group with the wearables (EWLI – stands for “Enhanced Weight Loss Intervention”), experienced a visible plunge in MVPA: “Nonsupervised moderate-to-vigorous physical activity” even before they got the wearables, that continued well past the time they had the wearables. Overall, though, across the 24 months, there was not found to be a significant difference in physical activity.
  • The subjects were placed on what are essentially high carbohydrate diets with caloric restriction, which remained restricted throughout the 24 months.

Outrunning a bad diet?

I was recently introduced to the work of Tim Noakes (@ProfTimNoakes) (about 5 years behind the rest of the world, but maybe 1-2 years ahead of part of the world) and decided to look more closely at other factors.

Focusing on the diet of the subjects, here’s what it said in the study details (supplemental materials)

All subjects will be prescribed an energy restricted dietary intervention that we have shown to effectively reduce body weight by 8-10% within the initial 6 months of treatment. This will include reducing energy intake to 1200 to 1800 kcal/d based on initial body weight (<200 pounds = 1200 kcal/d; 200 to 250 pounds = 1500 kcal/d; >250 pounds = 1800 kcal/d). Data from our research studies [14, 15] and the National Weight Control Registry [26] indicated that macronutrient composition in the most successful participants consists of 20-30% dietary fat intake, 50-55% carbohydrate intake, and 20-25% protein intake. Therefore, a similar dietary composition will be recommended in this study. However, we do recognize that low carbohydrate/high protein diets are currently popular, have demonstrated some initial efficacy, and some participants may gravitate towards this macronutrient composition, and this will be acceptable provided that total energy intake is within the prescribed range. To facilitate the adoption of the dietary recommendations, individuals will be provided with meal plans (see Appendix B), that will allow them to plan for modifications in their daily and weekly meal plans, and a calorie counter book.

So they were permitted to lower their carbohydrate intake as long as they maintained the same amount of calorie restriction. As a group they did not do this, though. They stuck to their high carbohydrate diets over the long run.

From this paper:

Malhotra A, Noakes T, Phinney S. It is time to bust the myth of physical inactivity and obesity: you cannot outrun a bad diet. Br. J. Sports Med. 2015;49(15):967–8.

Regular physical activity reduces the risk of developing cardiovascular disease, type 2 diabetes, dementia and some cancers by at least 30%. However, physical activity does not promote weight loss.

And there was the September 12, 2016 cover story of Time Magazine:

For all its merits, however, exercise is not an effective way to lose weight, research has shown. In a cruel twist, many people actually gain weight after they start exercising, whether from new muscle mass or a fired up appetite.

This study is about wearables, not exercise, because both groups of people exercised about the same over time.

However, because both groups were on a high-carbohydrate diet throughout the intervention, it’s possible that even if the wearables “worked” (they exercised more), that the results would be the same.

Still pro exercise…

I, like Bob Sallis, MD, who is quoted in the Time magazine article, support exercise for the numerous health benefits it offers – just look up any of my presentations on the topic, oh like this one:

Presentation/Photos: Quantified Community, Population Sensors at WalkHackNight, Transportation Techies

What if listening to a wearable device isn’t as effective as listening to your body? I’m going to post on another approach tomorrow….

Charts from Effect of Wearable Technology on Weight Loss
Charts from “Effect of Wearable Technology Combined With a Lifestyle Intervention on Long-term Weight Loss. JAMA. 2016;316(11):1161.” (View on Flickr.com)

New Maps of DC health data – Not yet one culture of health

Catching up on social innovation I haven’t yet posted about…

I have complained previously about the fact that data purporting to show Washington, DC’s health status as a county is usually wrong (see: Do national numbers inaccurately represent Washington, DC’s obesity condition? | Ted Eytan, MD – Answer: YES) because DC has 8 wards within it that are not accounted for in the County Health Rankings’ of the world (@CHRankings). This makes these tools less useful in a place like our nation’s capital. What if you live here and love this city and want to make a difference?

Community Commons (@CommunityCommon) to the rescue. Earlier this year they so very nicely agreed to add Washington, DC ward boundaries to their most awesome mapping system , and some key health data points based on DC-level data. They even created a special hub “Center for Total Health” that’s invite only so I can bring community health activists to map their city, collaboratively.

Here’s the obesity map for Washington, DC:

Obesity by Ward, Washington, DC USA 51195

Here’s the smoking status map for Washington, DC by Ward:

Smoking Status by Ward, Washington, DC USA 51194

These are new; previously there was no way to understand DC’s health using an interactive system because all of the data is clumped at the county level. As you can tell from the above, if you see an obesity rate of 21 % for “Washington, DC” you’ll miss important distinctions.

Now, here’s the race / ethnicity map for Washington, DC, available by census tract:

Race/Ethnicity by Tract, US Census 2010, with Ward Boundaries  51203

Do you see a picture of different health status on the left side of the map vs the right side of the map?

Wanna play? Click on either map

The new capabilities provided by Community Commons allow us to map any sub-county level data over ward boundaries so we can understand our city better. I even created a few interactive ones that you can play with here. Just click through, you’ll need to create an account on communitycommons.org to make any changes. Up to you.

While I was at it, I also created a map using DC-data-whiz Michael Schade’s (@mvs202) interactive Google Places map, plotting presence of what Google labels “gyms” in a 4-metro station radius of Shaw/Howard University Station:

Heat Map - Gyms in Washington DC 51193

You can see that gym businesses in the Google places database encircle Dupont Circle (14.4 % obesity rate), with a lot less presence east of Shaw/Howard University Metro (17.4 % obesity rate heading into 35 % obesity rate). These distinctions are important – people who spend their time in the western half of the city may believe they own a culture of health, but it’s only they that do.

I mention Shaw/Howard, because I recently read the excellent book S Street Rising: Crack, Murder, and Redemption in D.C. by Ruben Castaneda (@RCastanedaWP) which has stimulated tons of thinking about how a city creates and loses health. More on that later…

Yesterday, I happened upon a ribbon cutting ceremony by our Mayor (@MayorVinceGray) (who has done incredible things for human rights) in that neighborhood. I asked a bystander if she was here during the riots that destroyed this part of the city in 1968. She said, she was, and it was a scary and sad time. I believe her.

Photos: S Street, 1968 and 2014 – next to Shaw/Howard Street Metro

She told me that her friends told her she should have taken photos of the before and after, because so much had changed. I responded that there were still plenty of photos to take – even though the buildings look new, there’s plenty of “before” to be found, the maps show it.

Thanks a ton, again, to Community Commons for being responsive/interested/supportive and no negative vibes meant to County Health Rankings – we are all friends and the two resources go together in the most useful way. Sometimes you have to go to the places that no one else goes to find and create innovation in health. That’s what social innovators do 🙂 .

If you’d like to do some DC mapping, drop me a line/comment/tweet and I’ll invite you to the hub on Community Commons.

 

Now Reading: The Obesity Paradox – should lack of physical fitness be considered a medical emergency?

My answer to the above is yes. I have told people at the Center for Total Health (@kptotalhealth) that I consider a patient who presents to their doctor without any physical activity a medical emergency. I get looks of surprise when I say this, sometimes a slight chuckle.

In preparation for October’s Mobility Lab (@MobilityLabTeam) Lunch and Learn (see: Health and Transportation Connect During “Lunch At the Lab” — Mobility Lab), I followed up on the wisdom of our Bob Sallis, MD, who has been writing about “The Obesity Paradox.”

Here’s what he’s said recently: Active Voice: The AMA Says Obesity is a Disease; Now We Need to Inform Them How to Best Treat It, and the figure above is what I created for the presentation (which I’ll post about separately).

Bob passed me this paper, which shows, in a study of 14,345 men, assessed over 7 years, that weight was not associated with death. Level of physical activity is, across all weights.

I have believed that lack of physical activity is a medical emergency long before this study. There are several reasons for this. Before I say what those are for me, I’ll see if you agree or what you think of this concept – post in the comments, or on your favorite social network, please…

Slide above adapted for social network clarity, from PPT Slides of All Figures from the study above.

Now Reading: Neighborhoods, Obesity, and Diabetes – A Randomized Social Experiment

Neighborhoods, Obesity, and Diabetes — A Randomized Social Experiment

As compared with the control group, the group with a randomly assigned opportunity to use a voucher to move to a neighborhood with a lower poverty rate had lower prevalences of a BMI of 35 or more, a BMI of 40 or more, and a glycated hemoglobin level of 6.5% or more, representing relative reductions of 13.0%, 19.1%, and 21.6%, respectively. The magnitudes of the associations with health were larger still for participants who moved with a voucher that was restricted to use in a low-poverty area than they were for the intention-to-treat estimates for all participants who received the restricted voucher and are consistent with the effect sizes reported in previous observational studies.3 Because we generated estimates for several BMI cutoff points, our estimates for the associations between program participation and extreme obesity may be marginally significant.

Is moving to a different neighborhood as powerful or more powerful an intervention than health care, health education, apps, reminders, games and other individually-directed behavior change strategies people are talking about with obesity? It seems to have an impact.

What an interesting study – randomizing families (via incentive vouchers) to either move to a neighborhood with a low poverty rate, a neighborhood of their choice, or no intervention, between 1994 and 1998, with a 10-12 year follow-up. How often does that happen.

Not every family offered the voucher to move actually moved, and the analysis takes this into account (via intention-to-treat). It appears to my eyes that all families that did move (low poverty or move-where-you-want) went to neighborhoods that were less-poor and higher education levels, and there was an association with the impact on their health (weight, HbA1c).

Interestingly, at interview, none of the study groups reported having better access to non-emergency room health care, so that part of their neighborhood experience didn’t change, while their health experience did.

I recommend looking at Tables 2-3 – I can’t reproduce here to respect copyright, but the article is open access.

This is all related to research on the impact of location (see: Now Reading: Place, not race: disparities dissipate when blacks and whites live under similar conditions ) combined with modern tools to assess what’s happening in locations (see: Pioneering Idea: Your Patient’s Community Health Needs Assessment on the Desktop – Robert Wood Johnson Foundation)

I think this is a well done study. I am in the habit of reviewing disclosures – the study itself wasn’t funded by pharmaceutical, device, or food manufacturers, however authors of this publication or their institution(s) have received funding from those sources.