Monday, November 28, 2011

Trim & Regimen Experiment

I'm trimming 3/4" of an inch.  My method is to put my hair in jumbo twists and trim the ends of the twists.  (I recommend doing smaller twists for a more accurate trim.)  This is my first trim in months.

Normally, I twist my hair for 3-4 weeks at a time during the cooler months.  This time, I'll maintain my summer regimen and twist biweekly.  My hair is getting harder to detangle (as it grows), so doing so 1x every 2 weeks instead of 4 weeks will make life easier.  It'll also be easier on my hair.

Guest Commentary: Translational Research for Actuaries

This is the first of a series of four blog postings summarizing issues, methods and results from current research in the Center for Value in Healthcare. We will be presenting a JSPH Forum entitled “Translating Research into Policy and Practice” on January 11, 2012 with more details of the Center’s work.

Rob Lieberthal, PhD
Faculty, Jefferson School of Population Health

I will be talking about my research project funded by the Society of Actuaries (SOA) at the JSPH Center for Value in Healthcare Forum on January 11, 2012. The project is “Validating the PRIDIT method for determining hospital quality with outcomes data.” The goal of our project is to determine hospital quality using publicly available Hospital Compare data.

After funding the project, the SOA organized a project oversight group, comprised of practicing actuaries volunteering to serve the profession by supervising our research project. Actuaries are the professionals who are responsible for calculating and managing the cost of health insurance. They have always played a crucial role in benefit design. In the era of managed care, that has meant more and more involvement in creating and managing provider networks.

Given their professional interest, the oversight group was intrigued by my prior findings and was interested in using these findings to reduce cost and increase quality. I explained that, from my perspective, one of the barriers to putting my results into practice was that healthcare professionals did not seem interested in using my results. Their feedback was that my method might be inaccessible, even to a group as mathematically inclined as actuaries.

As a result of our discussions, our work has become literally translational: they are helping me translate my work from my language into theirs. If we can pair actionable results on hospital quality with an instruction book for how to use the PRIDIT method, we can increase the chance that actuaries put our findings and our methodology into practice.

I have previously noted that actuaries could be the ideal group to bridge healthcare quality and safety data with financial and nonfinancial incentives. This could drive patient behavior and improve population health. This is very much a work in progress, so stay tuned for an update from me on January 11, 2012!

Triglycerides, VLDL, and industrial carbohydrate-rich foods

Below are the coefficients of association calculated by HealthCorrelator for Excel (HCE) for user John Doe. The coefficients of association are calculated as linear correlations in HCE (). The focus here is on the associations between fasting triglycerides and various other variables. Take a look at the coefficient of association at the top, with VLDL cholesterol, indicated with a red arrow. It is a very high 0.999.

Whoa! What is this – 0.999! Is John Doe a unique case? No, this strong association between fasting triglycerides and VLDL cholesterol is a very common pattern among HCE users. The reason is simple. VLDL cholesterol is not normally measured directly, but typically calculated based on fasting triglycerides, by dividing the fasting triglycerides measurement by 5. And there is an underlying reason for that - fasting triglycerides and VLDL cholesterol are actually very highly correlated, based on direct measurements of these two variables.

But if VLDL cholesterol is calculated based on fasting triglycerides (VLDL cholesterol  = fasting triglycerides / 5), how come the correlation is 0.999, and not a perfect 1? The reason is the rounding error in the measurements. Whenever you see a correlation this high (i.e., 0.999), it is reasonable to suspect that the source is an underlying linear relationship disturbed by rounding error.

Fasting triglycerides are probably the most useful measures on standard lipid panels. For example, fasting triglycerides below 70 mg/dl suggest a pattern of LDL particles that is predominantly of large and buoyant particles. This pattern is associated with a low incidence of cardiovascular disease (). Also, chronically high fasting triglycerides are a well known marker of the metabolic syndrome, and a harbinger of type 2 diabetes.

Where do large and buoyant LDL particles come from? They frequently start as "big" (relatively speaking) blobs of fat, which are actually VLDL particles. The photo is from the excellent book by Elliott & Elliott (); it shows, on the same scale: (a) VLDL particles, (b) chylomicrons, (c) LDL particles, and (d) HDL particles. The dark bar at the bottom of each shot is 1000 A in length, or 100 nm (A = angstrom; nm = nanometer; 1 nm = 10 A).

If you consume an excessive amount of carbohydrates, my theory is that your liver will produce an abnormally large number of small VLDL particles (also shown on the photo above), a proportion of which will end up as small and dense LDL particles. The liver will do that relatively quickly, probably as a short-term compensatory mechanism to avoid glucose toxicity. It will essentially turn excess glucose, from excess carbohydrates, into fat. The VLDL particles carrying that fat in the form of triglycerides will be small because the liver will be in a hurry to clear the excess glucose in circulation, and will have no time to produce large particles, which take longer to produce individually.

This will end up leading to excess triglycerides hanging around in circulation, long after they should have been used as sources of energy. High fasting triglycerides will be a reflection of that. The graphs below, also generated by HCE for John Doe, show how fasting triglycerides and VLDL cholesterol vary in relation to refined carbohydrate consumption. Again, the graphs are not identical in shape because of rounding error; the shapes are almost identical.

Small and dense LDL particles, in the presence of other factors such as systemic inflammation, will contribute to the formation of atherosclerotic plaques. Again, the main source of these particles would be an excessive amount of carbohydrates. What is an excessive amount of carbohydrates? Generally speaking, it is an amount beyond your liver’s capacity to convert the resulting digestion byproducts, fructose and glucose, into liver glycogen. This may come from spaced consumption throughout the day, or acute consumption in an unnatural form (a can of regular coke), or both.

Liver glycogen is sugar stored in the liver. This is the main source of sugar for your brain. If your blood sugar levels become too low, your brain will get angry. Eventually it will go from angry to dead, and you will finally find out what awaits you in the afterlife.

Should you be a healthy athlete who severely depletes liver glycogen stores on a regular basis, you will probably have an above average liver glycogen storage and production capacity. That will be a result of long-term compensatory adaptation to glycogen depleting exercise (). As such, you may be able to consume large amounts of carbohydrates, and you will still not have high fasting triglycerides. You will not carry a lot of body fat either, because the carbohydrates will not be converted to fat and sent into circulation in VLDL particles. They will be used to make liver glycogen.

In fact, if you are a healthy athlete who severely depletes liver glycogen stores on a regular basis, excess calories will be just about the only thing that will contribute to body fat gain. Your threshold for “excess” carbohydrates will be so high that you will feel like the whole low carbohydrate community is not only misguided but also part of a conspiracy against people like you. If you are also an aggressive blog writer, you may feel compelled to tell the world something like this: “Here, I can eat 300 g of carbohydrates per day and maintain single-digit body fat levels! Take that you low carbohydrate idiots!”

Let us say you do not consume an excessive amount of carbohydrates; again, what is excessive or not varies, probably dramatically, from individual to individual. In this case your liver will produce a relatively small number of fat VLDL particles, which will end up as large and buoyant LDL particles. The fat in these large VLDL particles will likely not come primarily from conversion of glucose and/or fructose into fat (i.e., de novo lipogenesis), but from dietary sources of fat.

How do you avoid consuming excess carbohydrates? A good way of achieving that is to avoid man-made carbohydrate-rich foods. Another is adopting a low carbohydrate diet. Yet another is to become a healthy athlete who severely depletes liver glycogen stores on a regular basis; then you can eat a lot of bread, pasta, doughnuts and so on, and keep your fingers crossed for the future.

Either way, fasting triglycerides will be strongly correlated with VLDL cholesterol, because VLDL particles contain both triglycerides (“encapsulated” fat, not to be confused with “free” fatty acids) and cholesterol. If a large number of VLDL particles are produced by one’s liver, the person’s fasting triglycerides reading will be high. If a small number of VLDL particles are produced, even if they are fat particles, the fasting triglycerides reading will be relatively low. Neither VLDL cholesterol nor fasting triglycerides will be zero though.

Now, you may be wondering, how come a small number of fat VLDL particles will eventually lead to low fasting triglycerides? After all, they are fat particles, even though they occur in fewer numbers. My hypothesis is that having a large number of small-dense VLDL particles in circulation is an abnormal, unnatural state, and that our body is not well designed to deal with that state. Use of lipoprotein-bound fat as a source of energy in this state becomes somewhat less efficient, leading to high triglycerides in circulation; and also to hunger, as our mitochondria like fat.

This hypothesis, and the theory outlined above, fit well with the numbers I have been seeing for quite some time from HCE users. Note that it is a bit different from the more popular theory, particularly among low carbohydrate writers, that fat is force-stored in adipocytes (fat cells) by insulin and not released for use as energy, also leading to hunger. What I am saying here, which is compatible with this more popular theory, is that lipoproteins, like adipocytes, also end up holding more fat than they should if you consume excess carbohydrates, and for longer.

Want to improve your health? Consider replacing things like bread and cereal with butter and eggs in your diet (). And also go see you doctor (); if he disagrees with this recommendation, ask him to read this post and explain why he disagrees.

Thursday, November 24, 2011

Black Friday Natural Hair Sales!

11/25 thru 11/26
30% off w/ coupon code BLKFRI30

Anita Grant
11/24 7pm to 11/30 7pm
20% off entire store with free global shipping.

Bee Mine
11/25 midnight to 1:00am
30% off w/ coupon code 1HR30

For more sales (Carol's Daughter, Darcy's Botanicals, Butters-n-Bars, etc.), check out this blog.

Wednesday, November 23, 2011

Monday, November 21, 2011

My transformation: How I looked 10 years ago next to a thin man called Royce Gracie

The photos below were taken about 10 years ago. The first is at a restaurant near Torrance, California. (As you can see, the restaurant was about to close; we were the last customers.) I am standing next to Royce Grace, who had by then become a sensation (). He became a sensation by easily defeating nearly every champion fighter that was placed in front of him. In case you are wondering, Royce is 6’1” and I am 5’8”. The second photo also has Royce’s manager in it – that is his wife. Their children’s names both start with the letter “K”. I wonder how big they are right now.

I think that at the time these photos were taken I weighed around 200-210 lbs. Even though I am much shorter than Royce, I outweighed him by around 40 lbs. Now I weigh 150 lbs, at about 11 percent body fat, and look like the photo on the top-right area of this blog - essentially like a thin guy who does some manual labor for a living, I guess. A post is available discussing the "how" part of this transformation (). I only put a shirtless photo here after several readers told me that my previous photo looked out of place in this blog.

My day job is not even remotely related to fitness instruction. I am a college professor, and like to think of myself as a scholar. I don’t care much about my personal appearance; never did. At least in my mind, putting up shirtless photos on the web should not be done gratuitously. If you are a fitness instructor, or an athlete, that is fine. In my case, it is acceptable in the context of telling people that a few minutes of mid-day sun exposure, avoiding sunburn, yields 10,000 IU of skin-produced vitamin D, which is about 20 times more than one can get through most "fortified" industrial foods.

Royce is such a nice guy that, after much insistence, he paid for the dinner, and then we drove to his house and talked until about midnight. He had told me of a flight the next morning to Chicago, so I ended the interview and thanked him for the wonderful time we had spent together. I had to talk him out of driving ahead of me to I-405; he wanted to make sure I was not going to get lost at that time of the night. This was someone who was considered a demigod at the time in some circles. A humble, wonderful person.

Royce helped launch what is today the mega-successful Ultimate Fighting Championship franchise (), which was then still a no holders barred mixed martial arts tournament. At the time the photos were taken I was interviewing him for my book Compensatory Adaptation, which came out in print soon after (). The book has a full chapter on the famous Gracie Family, including his father Helio and his brother Rickson.

I talked before about the notion of compensatory adaptation and how it applies to our understanding of how we respond to diet and lifestyle changes (). In this context, I believe that the compensatory adaptation notion is far superior to that of hormesis (), which I think is interesting but overused and overrated.

The notion of compensatory adaptation has been picked up in the field of information systems, my main field of academic research. In this field, which deals with how people respond to technologies, it is part of a broader theory called media naturalness theory (). There are already several people who have received doctorates by testing this theory from novel angles. There are also several people today who call themselves experts in compensatory adaptation and media naturalness theory.

The above creates an odd situation, and something funny that happened with me a few times already. I do some new empirical research on compensatory adaptation, looking at it from a new angle, write an academic paper about it (often with one or more co-authors who helped me collect empirical data), and submit it to a selective refereed journal. Then an "expert" reviewer, who does not know who the authors of the paper are (this is called a "blind" review), recommends rejection of the paper because “the authors of this paper clearly do not understand the notion of compensatory adaptation”. Sometimes something like this is added: “the authors should read the literature on compensatory adaptation more carefully, particularly Kock (2004)” - an article that has a good number of citations to it ().

Oh well, the beauty of the academic refereeing process …

Sunday, November 20, 2011

The American Israel Commerce Committee Meeting

This past week I had the privilege of playing co host for the American Israel Commerce Committee meeting on "Healthcare Information Technology". Nearly a dozen amazing young Israeli companies came to Philadelphia to make their "pitches" to raise money AND awareness about their work in the IT sphere of healthcare. Each firm did an incredible job discussing their software and related new tools for building a better infrastructure in our crazy business. The meeting was "bookended" by two panel discussions that I moderated. The first panel of experts tackled the question of "Funding Opportunities" and the second panel discussed "Power Collaborations". The keynote luncheon talk was delivered by David Jones Jr., my colleague and friend. David is the managing director of Chrysalis Ventures in Louisville KY and for many years, has been a driving force behind HUMANA as an active Board Member.

The conference drew more than 100 persons from around the Delaware Valley and the sprited conversations were peppered with Israeli wit and wisdom too. For such a small country Israel produces a disproportionate share of leading IT firms and being able to bring them to our home town was a real treat. The mission of our School of Population Health, and the mission of the AICC, were totally aligned for this important event. To learn more go to We would welcome your feedback about any of the firms, or the content of the two panels as well. DAVID NASH

Friday, November 18, 2011

Guest Commentary: Reflections on the 2011 APHA Conference

From left, Kevin Scott, MD, Manisha Verna, MD,
MPH, and Rob Simmons, DrPH, MPH, MCHES,
CPH, director of JSPH's Master of Public Health

Kevin Scott, MD
Instructor & Primary Care Research Fellow
Department of Family & Community Medicine
Thomas Jefferson University

I was fortunate enough to attend the annual American Public Health Association (APHA) conference for the third time and, with each visit, I am more impressed (and less overwhelmed!) by the diversity and quality of programs that are offered.

As a family medicine physician and primary care research fellow interested in improving access to care for marginalized populations, I came to the meeting with a few goals.

First, to take part in the activities of the Refugee and Immigrant Health Caucus and to (hopefully) earn a spot within the Caucus' leadership.

Second, to attend sessions addressing the capacity of Community Health Workers and experiences with their deployment in different environments.

Finally, I also was looking forward to the sessions detailing Canada's truly enormous Housing First project, which evaluated different programs in 5 cities in Canada.

I developed these goals prior to the meeting because the breadth of interesting content can paralyze you unless you are ready for it (and have a plan!).

I was also happy to have the opportunity to meet many luminaries in the public health world (former APHA president, high-level mental health researchers, many CA researchers) while working the Jefferson School of Population Health booth with Rob Simmons, director of Jefferson’s Master of Public Health program. Additionally, I had the opportunity to meet a graduate of the program and her mentor who had piloted some very exciting work with same-site legal services (a program that I hope to adapt for use with the refugees we see in family medicine).

I was elected secretary of the Refugee and Immigrant Caucus and am excited for what promises to be an exciting year of developing high-quality programming, improving intra- and inter-caucus coordination, and planning additional activities before the next annual meeting.

Fortunately, I was also able to network with a number of service providers and fellow researchers in the areas of homelessness, refugee/immigrant care, and community health worker deployment. Hopefully, this momentum will help springboard our efforts to develop a national refugee research network as well as local efforts to evaluate the efficacy of a hybrid community health worker-patient navigator.

Just like the meeting itself, it's hard to contain the entire experience in one short piece, but to summarize, it's a great way to share your research, meet others in your field, learn about cutting-edge techniques, and re-charge your inspiration battery!

Manisha Verna, MD, MPH

Attending the 2011 Annual APHA meeting – my first – was an exciting opportunity.

My capstone project was accepted as an oral presentation in the vision care section (Knowledge and perceived barriers about diabetic retinopathy among patients with diabetes in an urban academic environment). There was a discussion about the availability of onsite optometry in primary care practice- benefits and costs associated with it. This is a take home message to improve the practice.

Volunteering at the Jefferson School of Population Health booth was quite fascinating, as it allowed a chance to meet and greet like-minded people. Discussing our school’s educational programs, the faculty and courses with students and public health leaders provided a venue to feel proud of the Jefferson community.

I met with one of our new faculty members – Dr. John Oswald – who teaches a course on International Health, a subject of great interest to me. I volunteered to give a guest lecture on the health care system of India, and now will also give presentations on some other developing and developed countries (China, Russia, Cuba, and Congo).

I highly recommend attending the APHA meeting; it provides a doorway to meet the public health workforce and learn from their experiences.

Wednesday, November 16, 2011

HHB Does Not Promote Misinformation

A comment was left by one of my readers stating that Afro-textured hair is drier because the scalp produces less sebum than those with naturally straighter hair.  This is not true.  In actuality, African Americans produce more sebum in the scalp than Caucasians and Asians.  HHB does not promote misinformation.  I do my best to blog the facts when blogging facts.  The myth that the scalp of African Americans is naturally dry has been busted by scientific research.



Tuesday, November 15, 2011

Moisture: An Oldie But Goodie

Here is a repost from July 26, 2009!!  Just in time for the Fall.

What causes these dry ends?

Sebum is the hair and scalp's natural conditioner. In straight hair, this oily substance can generally move down the shaft to the ends fairly easily because of the direct path. The hair's close proximity to the scalp as well as continual brushing and combing also aid in the transport process. As for textured hair? That is another story.

The coilier your hair, the harder it is for sebum to travel down to the ends. Here's my analogy: Imagine oil running along a straight road versus a path full of turns and twists. In the latter case, the oil may slow down or even get caught at each curve. By the time it reaches its destination, only a fraction of the oil will remain. There is also the possibility that it may never reach its destination. This process is basically what curly, coily, and kinky hairs experience. Additionally, factor in a minimal brushing/combing routine and the reality that some natural hair works against gravity (i.e., stands up and out away from the scalp). We ultimately have a case in which sebum just barely reaches the ends of our hair, if at all.

Now the explanation above is just one of many causes of dry ends. Other reasons are listed in this post on moisture and length retention.

How do you stop dry ends (due to inadequate sebum)?
Since sebum may barely, if at all, reach the ends of textured hair, it is necessary to quench and condition those ends. Here are some methods that work for me and may hopefully work for others:

*Discard harsh regular shampoos
Shampoos with SLS and other strong ingredients strip my hair (including my ends) of their natural oils. The shampoo I use on a regular basis contains more gentle substances. Other options to explore are conditioner washing or using homemade natural cleansers instead of a shampoo. Some people also do a treatment with oil at a warm or room temperature prior to washing to minimize sebum loss from their strands. (Click here for hot oil treatments.)

*Lather once when you shampoo
Minimal lathering equals minimal loss of whatever sebum is on my ends.

*No direct shampoo on the ends
I rarely expose my ends to direct shampoo. I just focus on the scalp and let the water and lather run down the rest of my hair.

*Saturate the ends with moisture and conditioner
Pay the most attention to your ends while conditioning and moisturizing.

*Invest in good products
Each individual head of hair is different, but this post may be a place to start in terms of what sealants, moisturizers, and conditioners to try.

*Eat foods containing omega-3 and vitamin A
Few people realize that foods, such as salmon, cantaloupe, and flaxseeds contribute to sebum production. For the omega-3 post, click here. For the vitamin A post, click here.

*Airdry the hair in a protective style
Protective styling isn't reserved for the protection of the ends. It has the added benefit, in my case, of helping my ends absorb and retain moisture post a washing session.

*Sleep with a silk scarf/pillowcase
The same added benefit applies here too.

How do you stop dry ends (due to porosity)?

I believe that another major contributor to dry ends in black hair is high porosity. What causes high porosity? Well, a number of things including gradual wear and tear of the hair. I really encourage anyone who believes they might have this issue to read this extremely informative article: Part 1 . For solutions to the porosity issues, do check out Part 2 as well: Part 2 .


SEBUM & TEXTURED HAIR 2: Randy Schueller, Perry Romanowski. "Conditioning agents for hair and skin".

Friday, November 11, 2011

Guest Commentary: Translating Public Health Systems Research into Practice

Tamar Klaiman, PhD, MPH
Assistant Professor
Jefferson School of Population Health

As part of the On Saturday, October 29, I attended a Public Health Systems and Services Research (PHSSR) lunch n’ learn in Washington, DC, an affiliate meeting of the American Public Health Association’s Annual meeting. The lunch n’ learn focused on translating research into practice.

The field of PHSSR seeks “to explore the impact of specific public health strategies on the quality and performance of the United States public health system.” PHSSR is distinct from -- but related to -- the established field of Health Services Research (HSR), which has traditionally focused on the delivery of medical services.

Those of us who are trained researchers talk a lot about translating our research into practice; however, for most scientists it takes over 15 years for our work to be used practically. This session gave specific examples of how PHSSR is impacting the work public health agencies conduct across the country. One example was the use of social networking analysis, which can help us better understand how organizations work and pinpoint areas for improvement. The results of social network analysis include depictions of how different departments communicate and cooperate. This work allows managers to see where problems lie in their departments and address them. Data collected before and after a social network analysis show that the analysis leads to measurable improvements in health department activities.

It is helpful for me to attend similar sessions periodically to remind me not only how important research is to practice, but to find inspiration in what others are doing. I am hopeful for the future of PHSSR and its impact on public health practice!

Saturday, November 5, 2011

The China Study II: How gender takes us to the elusive and deadly factor X

The graph below shows the mortality in the 35-69 and 70-79 age ranges for men and women for the China Study II dataset. I discussed other results in my two previous posts () (), all taking us to this post. The full data for the China Study II study is publicly available (). The mortality numbers are actually averages of male and female deaths by 1,000 people in each of several counties, in each of the two age ranges.

Men do tend to die earlier than women, but the difference above is too large.

Generally speaking, when you look at a set time period that is long enough for a good number of deaths (not to be confused with “a number of good deaths”) to be observed, you tend to see around 5-10 percent more deaths among men than among women. This is when other variables are controlled for, or when men and women do not adopt dramatically different diets and lifestyles. One of many examples is a study in Finland (); you have to go beyond the abstract on this one.

As you can see from the graph above, in the China Study II dataset this difference in deaths is around 50 percent!

This huge difference could be caused by there being significantly more men than women per county included the dataset. But if you take a careful look at the description of the data collection methods employed (), this does not seem to be the case. In fact, the methodology descriptions suggest that the researchers tried to have approximately the same number of women and men studied in each county. The numbers reported also support this assumption.

As I said before, this is a well executed research project, for which Dr. Campbell and his collaborators should be commended. I may not agree with all of their conclusions, but this does not detract even a bit from the quality of the data they have compiled and made available to us all.

So there must be another factor X causing this enormous difference in mortality (and thus longevity) among men and women in the China Study II dataset.

What could be this factor X?

This situation helps me illustrate a point that I have made here before, mostly in the comments under other posts. Sometimes a variable, and its effects on other variables, are mostly a reflection of another unmeasured variable. Gender is a variable that is often involved in this type of situation. Frequently men and women do things very differently in a given population due to cultural reasons (as opposed to biological reasons), and those things can have a major effect on their health.

So, the search for our factor X is essentially a search for a health-relevant variable that is reflected by gender but that is not strictly due to the biological aspects that make men and women different (these can explain only a 5-10 percent difference in mortality). That is, we are looking for a variable that shows a lot of variation between men and women, that is behavioral, and that has a clear impact on health. Moreover, as it should be clear from my last post, we are looking for a variable that is unrelated to wheat flour and animal protein consumption.

As it turns out, the best candidate for the factor X is smoking, particularly cigarette smoking.

The second best candidate for factor X is alcohol abuse. Alcohol abuse can be just as bad for one’s health as smoking is, if not worse, but it may not be as good a candidate for factor X because the difference in prevalence between men and women does not appear to be just as large in China (). But it is still large enough for us to consider it a close second as a candidate for factor X, or a component of a more complex factor X – a composite of smoking, alcohol abuse and a few other coexisting factors that may be reflected by gender.

I have had some discussions about this with a few colleagues and doctoral students who are Chinese (thanks William and Wei), and they mentioned stress to me, based on anecdotal evidence. Moreover, they pointed out that stressful lifestyles, smoking, and alcohol abuse tend to happen together - with a much higher prevalence among men than women.

What an anti-climax for this series of posts eh?

With all the talk on the Internetz about safe and unsafe starches, animal protein, wheat bellies, and whatnot! C’mon Ned, give me a break! What about insulin!? What about leucine deficiency … or iron overload!? What about choline!? What about something truly mysterious, related to an obscure or emerging biochemistry topic; a hormone du jour like leptin perhaps? Whatever, something cool!

Smoking and alcohol abuse!? These are way too obvious. This is NOT cool at all!

Well, reality is often less mysterious than we want to believe it is.

Let me focus on smoking from here on, since it is the top candidate for factor X, although much of the following applies to alcohol abuse and a combination of the two as well.

One gets different statistics on cigarette smoking in China depending on the time period studied, but one thing seems to be a common denominator in these statistics. Men tend to smoke in much, much higher numbers than women in China. And this is not a recent phenomenon.

For example, a study conducted in 1996 () states that “smoking continues to be prevalent among more men (63%) than women (3.8%)”, and notes that these results are very similar to those in 1984, around the time when the China Study II data was collected.

A 1995 study () reports similar percentages: “A total of 2279 males (67%) but only 72 females (2%) smoke”. Another study () notes that in 1976 “56% of the men and 12% of the women were ever-smokers”, which together with other results suggest that the gap increased significantly in the 1980s, with many more men than women smoking. And, most importantly, smoking industrial cigarettes.

So we are possibly talking about a gigantic difference here; the prevalence of industrial cigarette smoking among men may have been over 30 times the prevalence among women in the China Study II dataset.

Given the above, it is reasonable to conclude that the variable “SexM1F2” reflects very strongly the variable “Smoking”, related to industrial cigarette smoking, and in an inverse way. I did something that, grossly speaking, made the mysterious factor X explicit in the WarpPLS model discussed in my previous post. I replaced the variable “SexM1F2” in the model with the variable “Smoking” by using a reverse scale (i.e., 1 and 2, but reversing the codes used for “SexM1F2”). The results of the new WarpPLS analysis are shown on the graph below. This is of course far from ideal, but gives a better picture to readers of what is going on than sticking with the variable “SexM1F2”.

With this revised model, the associations of smoking with mortality in the 35-69 and 70-79 age ranges are a lot stronger than those of animal protein and wheat flour consumption. The R-squared coefficients for mortality in both ranges are higher than 20 percent, which is a sign that this model has decent explanatory power. Animal protein and wheat flour consumption are still significantly associated with mortality, even after we control for smoking; animal protein seems protective and wheat flour detrimental. And smoking’s association with the amount of animal protein and wheat flour consumed is practically zero.

Replacing “SexM1F2” with “Smoking” would be particularly far from ideal if we were analyzing this data at the individual level. It could lead to some outlier-induced errors; for example, due to the possible existence of a minority of female chain smokers. But this variable replacement is not as harmful when we look at county-level data, as we are doing here.

In fact, this is as good and parsimonious model of mortality based on the China Study II data as I’ve ever seen based on county level data.

Now, here is an interesting thing. Does the original China Study II analysis of univariate correlations show smoking as a major problem in terms of mortality? Not really.

The table below, from the China Study II report (), shows ALL of the statistically significant (P<0.05) univariate correlations with mortality in 70-79 age range. I highlighted the only measure that is directly related to smoking; that is “dSMOKAGEm”, listed as “questionnaire AGE MALE SMOKERS STARTED SMOKING (years)”.

The high positive correlation with “dSMOKAGEm” does not even make a lot of sense, as one would expect a negative correlation here – i.e., the earlier in life folks start smoking, the higher should be the mortality. But this reverse-signed correlation may be due to smokers who get an early start dying in disproportionally high numbers before they reach age 70, and thus being captured by another age range mortality variable. The fact that other smoking-related variables are not showing up on the table above is likely due to distortions caused by inter-correlations, as well as measurement problems like the one just mentioned.

As one looks at these univariate correlations, most of them make sense, although several can be and probably are distorted by correlations with other variables, even unmeasured variables. And some unmeasured variables may turn out to be critical. Remember what I said in my previous post – the variable “SexM1F2” was introduced by me; it was not in the original dataset. “Smoking” is this variable, but reversed, to account for the fact that men are heavy smokers and women are not.

Univariate correlations are calculated without adjustments or control. To correct this problem one can adjust a variable based on other variables; as in “adjusting for age”. This is not such a good technique, in my opinion; it tends to be time-consuming to implement, and prone to errors. One can alternatively control for the effects of other variables; a better technique, employed in multivariate statistical analyses. This latter technique is the one employed in WarpPLS analyses ().

Why don’t more smoking-related variables show up on the univariate correlations table above? The reason is that the table summarizes associations calculated based on data for both sexes. Since the women in the dataset smoked very little, including them in the analysis together with men lowers the strength of smoking-related associations, which would probably be much stronger if only men were included. It lowers the strength of the associations to the point that their P values become higher than 0.05, leading to their exclusion from tables like the one above. This is where the aggregation process that may lead to ecological fallacy shows its ugly head.

No one can blame Dr. Campbell for not issuing warnings about smoking, even as they came mixed with warnings about animal food consumption (). The former warnings, about smoking, make a lot of sense based on the results of the analyses in this and the last two posts.

The latter warnings, about animal food consumption, seem increasingly ill-advised. Animal food consumption may actually be protective in regards to the factor X, as it seems to be protective in terms of wheat flour consumption ().

Friday, November 4, 2011

Guest Commentary: Reflections from the SOPHE 62nd Annual Meeting “Leveraging the Power of Health Education: Changing Systems”

Rob Simmons, DrPH, MPH, MCHES, CPH
Clinical Associate Professor
Program Director, Master of Public Health
Jefferson School of Population Health

I had the privilege to participate in the 62nd Society for Public Health Education (SOPHE) Annual Meeting in Washington, DC last week. Over 400 professional health promotion professionals and students attended the meeting. The theme was “Leveraging the Power of Health Education: Changing Systems”. Some of the highlights included:

• An opening presentation on the National Prevention Strategy by the US Department of Health and Human Services (HHS) Secretary Kathleen Sebelius, who presented the first-ever HHS 2011 Healthy Living Innovation Awards. National and local organizations and agencies were honored for their efforts in preventive health programming in such categories as healthy workplace for large and small employers, non-profits, local and state government, schools, health care, and community health initiatives.

• Transforming Systems for Health presentations by Karen Lee, Director of New York City’s Healthy Eating and Living Initiative, and Larry Cohen, Executive Director of the Prevention Institute in Oakland, California.

• Seeking Synergy to Enhance Health, Well-Being, and Performance presentation by James Prochaska, developer of the Transtheoretical Model of Change (Stages of Change).

• The Perspectives of a Grassroots Advocate presentation by Michael O’Donnell, noted national leader on workforce health promotion and editor of the American Journal of Health Promotion

• Panel presentation on Building Capacity of Health Professionals and Workers for the 21st Century featuring Dr. Jim Plumb of the Jefferson Medical College, Department of Family and Community Medicine on Jefferson’s innovative Population Health College within the College program for Jefferson medical students.

In addition to all the excellent sessions and networking, I was able to participate in a pre-conference workshop on evaluation of health promotion programs and policies by Richard Windsor, noted national and international behavioral science researcher and author of Evaluation of Health Promotion and Disease Prevention and Management Programs: Improving Population Health Through Evidenced-Based Practice. We look forward to working with Richard here in Philadelphia as Jefferson will be part of a national research study on the use of smoking cessation for pregnant women in our clinical practices over the next few years.

A wonderful, entertaining closing session was led by Todd Park, Chief Technology Officer for the “Open Government Initiative” for the US Dept. of Health and Human Services. Todd, a founder of the innovative data company, AthenaHealth, described the plethora of health initiatives using data technology and innovation linking data developers and health information users in the creation of open data sources for health. Todd led us through the maze of rapidly changing health data innovations, including “Blue Button” technology, health quality indicators, health data “Paloozas”, Health 2.0 developer challenges, and health education initiatives and games such as “Asthmapolis” and “Farmville.” The national link is

Having been a member of SOPHE since 1974 and having served as its national president and treasurer, I could not have been prouder to experience the tremendous growth of this national organization representing the field and profession of health promotion and health education. I look forward to SOPHE’s Annual Meeting next year in San Francisco and The Silicon Valley with its expected theme of advancing technologies to promote health.

Thursday, November 3, 2011

Playlist for November

On repeat: Braided bun

Sounds like: Sade

Interlude: bi-weekly washes & detangling; weekly moisturizing

Wednesday, November 2, 2011

m a n i f e s t o

So here it is: m a n i f e s t o: part 1

It's been a while in the making and is the first of two parts.

A colourful version is available here alongside a straight black and white word version. A short animated film and podcast version will be available shortly.

I know that it's what some of you expected, because we’ve talked about it.
I know that it's not what some of you expected, because we’ve talked about it.

So respond to it, talk about it and share it, and we’ll get some of these thoughts into part 2 and see how it grows!

Thank you everyone who’s been involved.

And of course, I’ll give some presentations around it, and encourage some debate.

No more round-robins for November, whilst I am away at the 3rd International Conference for Arts, Health and Well-being, but there may be the odd conference posting if you have a moment to visit this blog.

Please post all comments around the m a n i f e s t o to and excuse the brief silence.

...and for those of you who haven't taken part in the process, it may be worth looking at the references first!

On Friday 7th October, the Marmot Review Team launched a consultation on the European Review of the Social Determinants of Health & the Health Divide in the WHO European Region. At the present moment, this consultation makes no reference to the role of the arts and creative interventions on health inequalities, and the time is right for our input. I will be making some comments on this consultation, but if you want to read more and contribute yourself, click on the logo above or follow this link: