Love from my apple loving heart to yours! Muah! Bette
Thursday, September 30, 2010
APPLES~
Loving simple raw! An apple a day.....you know the rest.
Love from my apple loving heart to yours! Muah! Bette
Love from my apple loving heart to yours! Muah! Bette
I am baaaack!
So, I am soooo back. Stay tuned here for all kinds of fun and adventure. Please tolerate all that is here already....amatuer (I will always be,sorry) and volume challenges! eeezazoids!
Anyway keep a lookout! Thankx for watching my "show".
WA Insurance Commissioner describes health care changes
Wondering what health care reforms are coming down the pike? In this video by Comcast, Washington State Insurance Commissioner Mike Kreidler lays out the changes taking effect this fall and at the start of January, as well as some of the longer-term changes we can expect.
Tuesday, September 28, 2010
Top ways to GLOW!
Hey guys! Long time no blog. I know. I'm sorry. I have no real excuse other than, well life is crazy busy. Sprouting Wellness is running full steam, and apparently I am planning a wedding as well. :) So excuses, excuses, excuses. Besides my humble apologies, this blog does have a little content as well. Last week I gave a FREE teleclass called Dazzling Healthy Divas: How to GLOW from the inside out. The teleclass was a lot of fun and went over really well, so I thought I would share a bit of it here!
A Dazzling, Healthy Diva is a woman who glows. Regardless of her age, you see a spark of youthfulness in her eyes, her skin glows, her nails and hair shine and she had a spring of energy in her step. She’s got a magnetic glow. Men are attracted to her and women want to be her. Some of you may think that magnetism is something that some women just “have” and some don’t. In reality, every woman can have it you just have to follow a few key tips!
I have broken down the word GLOW into four quick tips so you can remember to glow. They are: Get Real and Get Fresh, Love yourself up, Organic is Outstanding and Workout and feel Wonderful! Totally simple and easy! Now break them down and see what each is really all about and what it can do to make you GLOW!
Get Real and Get Fresh! The fastest way to GLOW is to Get Real and Get Fresh! I am talking about the foods that you put into your body. Get fresh and get real about food. Crowd out the processed sugary foods with brightly colored fresh fruits and vegetables. Eat the rainbow. Whole fruits and vegetables contain energy from the sun. When consumed, they not only give us the energy for our bodies to run, but they help us glow like the sun as well.
Love yourself up! Pay kind, loving attention to yourself. There are two parts to loving yourself up, you will GLOW when you love yourself up physically and mentally.
Organic is Outstanding! Besides being free of synthetic fertilizers and pesticides, these fruits and vegetables have better textures and are consistently better tasting. Because organic produces isn't waxed or chemically treated, it must be sold fresh, and the fresher produce is, the more nutritious and tasty it is! If you can't afford to go organic, buy locally grown fruits and vegetables when possible. They're bound to be fresher than produce that has been shipped long distances.
Work out and love doing it!
And there you have it. Simple tips to help you glow and become a dazzling healthy diva. Get Real and Get Fresh, Love up on Yourself, Organic is Outstanding and Work out and love doing it. If you follow these guidelines, not only will your health improve, but you’ll have more energy and you’ll begin to glow from the inside out!
Keep it Fresh!~Terra
Regence to stop selling child-only policies in WA; Kreidler "appalled"
Here's a press release our office is putting out this morning:
Regence BlueShield, one of Washington state’s largest health insurers, intends to stop selling new policies for children in Washington under age 19 as of Oct. 1.
The decision followed days of discussions with Insurance Commissioner Mike Kreidler and his staff, who strongly objected to Regence’s decision.
“I’m appalled,” said Insurance Commissioner Mike Kreidler. “We’ve made regulatory concessions to limit Regence’s exposure. Their overreaction will seriously harm Washington families.”
As of Sept. 23, 2010, the federal Affordable Care Act requires many health plans to cover children’s pre-existing conditions. Kreidler’s office issued an emergency rule last week, allowing individual health plans to limit their risk by creating a special open-enrollment period from Nov. 1 – Dec. 15. During this time, parents can add their children to their individual plans without taking a health screen.
According to Kreidler, “A special enrollment period drastically limits the carriers’ risk and should more than address their concerns. By pulling out of this market, Regence just cut off vital coverage for working families.”
People still can buy individual plans from Regence for themselves and their families, but children only can be added between Nov. 1-Dec. 15. Anyone wanting to buy a health plan for just their child must choose a different health insurer.
Child-only policies are unusual in Washington state. Here, if you buy coverage for your family in the individual market, you’re issued one policy for the entire family. Family policies are not available in some states. There, people looking for family coverage must buy a policy for each member.
Regence Blueshield currently has 2,500 child-only policies in the state and they will remain in effect.
“So far, no other health carrier in Washington state has signaled its intent to leave this market,” added Kreidler. “I hope we can expect better from them.”
Parents looking for health insurance for their children can try the other health carriers in the individual market. Or, if they meet income qualifications, they might be eligible for Washington state’s Apple Health for Kids program. Coverage costs $30 a month per child for a family of four earning $66,150.
Income, obesity, and heart disease in US states
The figure below combines data on median income by state (bottom-left and top-right), as well as a plot of heart disease death rates against percentage of population with body mass index (BMI) greater than 30 percent. The data are recent, and have been provided by CNN.com and creativeclass.com, respectively.
Heart disease deaths and obesity are strongly associated with each other, and both are inversely associated with median income. US states with lower median income tend to have generally higher rates of obesity and heart disease deaths.
The reasons are probably many, complex, and closely interconnected. Low income is usually associated with high rates of stress, depression, smoking, alcoholism, and poor nutrition. Compounding the problem, these are normally associated with consumption of cheap, addictive, highly refined foods.
Interestingly, this is primarily an urban phenomenon. If you were to use hunter-gatherers as your data sources, you would probably see the opposite relationship. For example, non-westernized hunter-gatherers have no income (at least not in the “normal” sense), but typically have a lower incidence of obesity and heart disease than mildly westernized ones. The latter have some income.
Tragically, the first few generations of fully westernized hunter-gatherers usually find themselves in the worst possible spot.
Heart disease deaths and obesity are strongly associated with each other, and both are inversely associated with median income. US states with lower median income tend to have generally higher rates of obesity and heart disease deaths.
The reasons are probably many, complex, and closely interconnected. Low income is usually associated with high rates of stress, depression, smoking, alcoholism, and poor nutrition. Compounding the problem, these are normally associated with consumption of cheap, addictive, highly refined foods.
Interestingly, this is primarily an urban phenomenon. If you were to use hunter-gatherers as your data sources, you would probably see the opposite relationship. For example, non-westernized hunter-gatherers have no income (at least not in the “normal” sense), but typically have a lower incidence of obesity and heart disease than mildly westernized ones. The latter have some income.
Tragically, the first few generations of fully westernized hunter-gatherers usually find themselves in the worst possible spot.
Monday, September 27, 2010
Congress gives federal flood-insurance program a one-year extension
The National Flood Insurance Program, which has repeatedly lapsed and been reauthorized by Congress this year, has gotten a one-year extension from Congress. The bill, S-3814, passed the House on Friday, and had earlier gotten the thumbs-up from the Senate. It now awaits the president's signature.
I think I'm in medical school now! by September blogger Lisa Crystal
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| Study area of the Caroline House, where the administrative offices are located as well. My second home! |
Our courses are in the basic medical sciences like biochemistry, immunology, histology, and molecular biology. Since I majored in psychology, most of the subjects are new to me. While I envy the classmates who have already taken some of these classes already, I know that I will eventually learn what I need to know and trust that the extra time I put into the liberal arts will help me understand my patients and their contexts in the future. I certainly am learning a lot, but since we don’t have exams coming up I am not feeling too stressed out yet. I am just trying to set good study habits now as I have more freedom in how I learn the material.
One of the biggest challenges I foresee is difference between the two medical worlds in which I live: the Israeli system, where I am currently receiving my education, and the U.S. system, where I must pass licensing exams and apply for residency. The U.S. standards are very high and require efficient preparation, grounded in organization, details, and facts. The Israeli one is more flexible and informal. A prime example of the Israeli system is the fluid scheduling. We don’t know which classes we have each week until a few days before the week starts. Even then, the frequency and order of the classes seems random. Plus, a lecturer may cancel at the last minute. As students preparing for U.S. standards, though, we have a large amount of information that we need to learn in a finite amount of time.
Somehow MSIH students graduate and get good residency placements, so I know that it works out somehow. Students are also proactive about shaping the curriculum. I think Israel can teach me about improvisation, a valuable skill in global health care. For example, in Emergency Medicine, my TA frequently showed us different ways to perform a procedure depending on what tools are available. I can tell that I will need to be cross-cultural to learn medicine within the Israeli system, yet meet the standards required to practice in the U.S.
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| The new apartment, complete with blazing sun. |
In addition to the biomedical classes, we have started our global health education. It has been pretty basic so far, with introductions to topics so everyone gets on the same page. Electives are coming up, which I have been looking forward to since I learned about MSIH. I am registered for classes on topics like the health of the urban poor and international health organizations. I am told that another great source for global health education comes from our classmates. A group of students have compiled resources to use for our first-year global health course, which I’ve heard is very helpful.
Overall, I am excited for what is ahead. I am also nervous about learning everything -- or at least aware of the hard work it will take to learn everything. Studying here will be a challenge, but will certainly have its rewards. Where else would your professor describe the endoplasmic reticulum described in terms of pita and falafel? (-Lisa Crystal)
Saturday, September 25, 2010
Potatoes and Human Health, Part II
Glycoalkaloids in Commonly Eaten Potatoes
Like many edible plants, potatoes contain substances designed to protect them from marauding creatures. The main two substances we're concerned with are alpha-solanine and alpha-chaconine, because they are the most toxic and abundant. Here is a graph of the combined concentration of these two glycoalkaloids in common potato varieties (1):
We can immediately determine three things from this graph:
Glycoalkaloid Toxicity in Animals
Potato glycoalkaloids are undoubtedly toxic at high doses. They have caused many harmful effects in animals and humans, including (1, 2):
All of the studies I mentioned above, except one, involved doses of glycoalkaloids that exceed what one could get from eating typical potatoes. They used green or blemished potatoes, isolated potato skins, potato sprouts or isolated glycoalkaloids (more on this later). The single exception is the last study, showing that normal doses of glycoalkaloids can aggravate inflammatory bowel disease in transgenic mice that are genetically predisposed to it (3)*.
What happens when you feed normal animals normal potatoes? Not much. Many studies have shown that they suffer no ill effects whatsoever, even at high intakes (1, 2). This has been shown in primates as well (4, 5, 6). In fact, potato-based diets appear to be generally superior to grain-based diets in animal feed. As early as 1938, Dr. Edward Mellanby showed that grains, but not potatoes, aggravate vitamin A deficiency in rats and dogs (7). This followed his research showing that whole grains, but not potatoes, aggravate vitamin D deficiency due to their high phytic acid content (Mellanby. Nutrition and Disease. 1934). Potatoes were also a prominent part of Mellanby's highly effective tooth decay reversal studies in humans, published in the British Medical Journal in 1932 (8, 9).
Potatoes partially protect rats against the harmful effects of excessive cholesterol feeding, when compared to wheat starch-based feed (10). Potato feeding leads to a better lipid profile and intestinal short-chain fatty acid production than wheat starch or sugar in rats (11). I wasn't able to find a single study showing any adverse effect of normal potato feeding in any normal animal. That's despite reading two long review articles on potato glycoalkaloids and specifically searching PubMed for studies showing a harmful effect. If you know of one, please post it in the comments section.
In the next post, I'll write about the effects of potatoes in the human diet, including data on the health of traditional potato-eating cultures... and a curious experiment by the Washington State Potato Commission that will begin on October 1.
*Interleukin-10 knockout mice. IL-10 is a cytokine involved in the resolution of inflammation and these mice develop inflammatory bowel disease (regardless of diet) due to a reduced capacity to resolve inflammation.
Like many edible plants, potatoes contain substances designed to protect them from marauding creatures. The main two substances we're concerned with are alpha-solanine and alpha-chaconine, because they are the most toxic and abundant. Here is a graph of the combined concentration of these two glycoalkaloids in common potato varieties (1):
We can immediately determine three things from this graph:- Different varieties contain different amounts of glycoalkaloids.
- Common commercial varieties such as russet and white potatoes are low in glycoalkaloids. This is no accident. The glycoalkaloid content of potatoes is monitored in the US.
- Most of the glycoalkaloid content is in the skin (within 1 mm of the surface). That way, predators have to eat through poison to get to the flesh. Fortunately, humans have peelers.
Glycoalkaloid Toxicity in Animals
Potato glycoalkaloids are undoubtedly toxic at high doses. They have caused many harmful effects in animals and humans, including (1, 2):
- Death (humans and animals)
- Weight loss, diarrhea (humans and animals)
- Anemia (rabbits)
- Liver damage (rats)
- Lower birth weight (mice)
- Birth defects (in animals injected with glycoalkaloids)
- Increased intestinal permeability (mice)
All of the studies I mentioned above, except one, involved doses of glycoalkaloids that exceed what one could get from eating typical potatoes. They used green or blemished potatoes, isolated potato skins, potato sprouts or isolated glycoalkaloids (more on this later). The single exception is the last study, showing that normal doses of glycoalkaloids can aggravate inflammatory bowel disease in transgenic mice that are genetically predisposed to it (3)*.
What happens when you feed normal animals normal potatoes? Not much. Many studies have shown that they suffer no ill effects whatsoever, even at high intakes (1, 2). This has been shown in primates as well (4, 5, 6). In fact, potato-based diets appear to be generally superior to grain-based diets in animal feed. As early as 1938, Dr. Edward Mellanby showed that grains, but not potatoes, aggravate vitamin A deficiency in rats and dogs (7). This followed his research showing that whole grains, but not potatoes, aggravate vitamin D deficiency due to their high phytic acid content (Mellanby. Nutrition and Disease. 1934). Potatoes were also a prominent part of Mellanby's highly effective tooth decay reversal studies in humans, published in the British Medical Journal in 1932 (8, 9).
Potatoes partially protect rats against the harmful effects of excessive cholesterol feeding, when compared to wheat starch-based feed (10). Potato feeding leads to a better lipid profile and intestinal short-chain fatty acid production than wheat starch or sugar in rats (11). I wasn't able to find a single study showing any adverse effect of normal potato feeding in any normal animal. That's despite reading two long review articles on potato glycoalkaloids and specifically searching PubMed for studies showing a harmful effect. If you know of one, please post it in the comments section.
In the next post, I'll write about the effects of potatoes in the human diet, including data on the health of traditional potato-eating cultures... and a curious experiment by the Washington State Potato Commission that will begin on October 1.
*Interleukin-10 knockout mice. IL-10 is a cytokine involved in the resolution of inflammation and these mice develop inflammatory bowel disease (regardless of diet) due to a reduced capacity to resolve inflammation.
Thursday, September 23, 2010
New federal health reforms start today
Beginning today, most health plans sold after March 23, 2010 must include several new benefits when they renew. These provisions, outlined in the federal Affordable Care Act, are designed to increase access to health care. Under the new reforms, plans cannot:
Charge out-of-pocket costs, including co-pays, deductibles and co-insurance, for preventive services.
Cap lifetime benefits.
Cancel or rescind a policy, except in the case of fraud or misrepresentation.
Refuse to cover a child’s pre-existing condition.
If the health plan includes a cap on essential benefits, it can’t be less than $750,000.
And young adults can be covered on their parents’ plan until the age of 26, unless they get a job that offers health insurance.
However, there are some exceptions. Health plans sold before March 23, 2010, when the law was signed, are considered “grandfathered” and are exempt from some of these new protections.
For example, grandfathered individual health plans still can charge out-of-pocket costs for preventive services, cap lifetime benefits, and refuse to cover an enrolled child’s pre-existing condition. Grandfathered group plans (plans purchased by employers for their employees) still can charge out-of-pocket costs for preventive services.
Plans lose their grandfathered status if they significantly reduce benefits or increase deductibles, copayments, and/or an employee’s share of the premium.
Learn more about the fall reform here or see a general timeline of health reform.
Charge out-of-pocket costs, including co-pays, deductibles and co-insurance, for preventive services.
Cap lifetime benefits.
Cancel or rescind a policy, except in the case of fraud or misrepresentation.
Refuse to cover a child’s pre-existing condition.
If the health plan includes a cap on essential benefits, it can’t be less than $750,000.
And young adults can be covered on their parents’ plan until the age of 26, unless they get a job that offers health insurance.
However, there are some exceptions. Health plans sold before March 23, 2010, when the law was signed, are considered “grandfathered” and are exempt from some of these new protections.
For example, grandfathered individual health plans still can charge out-of-pocket costs for preventive services, cap lifetime benefits, and refuse to cover an enrolled child’s pre-existing condition. Grandfathered group plans (plans purchased by employers for their employees) still can charge out-of-pocket costs for preventive services.
Plans lose their grandfathered status if they significantly reduce benefits or increase deductibles, copayments, and/or an employee’s share of the premium.
Learn more about the fall reform here or see a general timeline of health reform.
New Obamacare benefits begin today - These are good changes - check them out
According to Web md in their article published on line today (http://www.webmd.com/medicare/news/20100922/latest-round-of-health-reform-benefits-kicks-in), some of the new health care requirements kick in today. These are good for Americans.
Highlights include
For many people with job-based coverage, the insurance changes will arrive Jan. 1, 2011, at the start of the new benefits year.
At the same time, the resistance is notching up. This week, as the consumer protections kick in, media reports have revealed that some major insurers, at least in part, will sidestep one new provision: denying coverage for children under age 19 who have pre-existing medical conditions.
Why anyone in government (you know who you are) would want to prevent this or repeal this is beyond me.
What do you think? As always, I value your opinion.
Highlights include
- Removing lifetime dollar limits on essential benefits
- Giving people a right to appeal to an external party if denied coverage for a treatment
- Preventing insurers from dropping coverage of people when they get sick
- Limiting the use of annual spending limits of health plans
- Allowing consumers to use ob-gyns in their networks without needing a referral
- Prohibiting extra charges for using emergency care that is out of network
- Guaranteeing full coverage of many preventive services, such as mammograms and colonoscopies, without a co-pay, co-insurance, or deductible
For many people with job-based coverage, the insurance changes will arrive Jan. 1, 2011, at the start of the new benefits year.
At the same time, the resistance is notching up. This week, as the consumer protections kick in, media reports have revealed that some major insurers, at least in part, will sidestep one new provision: denying coverage for children under age 19 who have pre-existing medical conditions.
Why anyone in government (you know who you are) would want to prevent this or repeal this is beyond me.
What do you think? As always, I value your opinion.
My Rosh Ha'shana break...surprisingly eventful! by Lisa Crystal, MSIH September blogger
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| Map of my holiday travels: A. Beer Sheva B. Ein Gedi/Dead Sea D. Organic Goat Farm E. Tiberias on Sea of Galilee F. Mount of Beatitudes G. Nazereth H. Tel Aviv |
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| Oasis at Ein Gedi |
We returned from the Dead Sea with enough time to join about half our class for a New Year’s dinner hosted by another classmate. The next evening, after a three-hour tour of the Israeli countryside, we arrived at an organic goat farm in the verdant Galilee region, where we spent the night in large geodesic dome tents. The next morning, we drove to the Sea of Galilee and hiked around scenic Mount Arbel, which overlooks the lake and has ruins from a fortress in its cliffs and caves.
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| Rosh Ha'shana dinner |
From peaceful Galilee, we headed to Nazareth, which the guidebooks warned was sometimes a disappointment. It is a busy little city and as far as historical sites go, only has a few traditional commemorative churches (my favorite name was “The Basilica of Jesus the Adolescent”). The town almost seemed irreverent; people went about their everyday business as if they didn’t care that this place was revered around the world. I felt like modern Nazareth gave me a taste of Jesus’ Nazareth: it was not terribly prosperous and had a bad reputation with the tourists. But we’ll give it another chance next time.
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| Tracing amino acids in the sand in Tel Aviv |
On the way back to Be’er Sheva, we stopped by the beach in Tel Aviv to dip our feet in the Mediterranean. Since we just can’t escape med school, we practiced writing amino acid structures in the sand. We were quiet as we neared the end of our whirlwind road trip -- returning to Be’er Sheva is a little depressing. It’s is hot, dry, sandy, dirty, and run-down. There are certainly more depressing cities in the world, but Be’er Sheva is so close to so many exciting places, which people envision when I say I’m studying in Israel. My new goal is to find the beauty that must exist here.
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| Classic Dead Sea photo (Lisa and Claire) |
Wednesday, September 22, 2010
Low nonexercise activity thermogenesis: Uncooperative genes or comfy furniture?
The degree of nonexercise activity thermogenesis (NEAT) seems to a major factor influencing the amount of fat gained or lost by an individual. It also seems to be strongly influenced by genetics, because NEAT is largely due to involuntary activities like fidgeting.
But why should this be?
The degree to which different individuals will develop diseases of civilization in response to consumption of refined carbohydrate-rich foods can also be seen as influenced by genetics. After all, there are many people who eat those foods and are thin and healthy, and that appears to be in part a family trait. But whether we consume those products or not is largely within our control.
So, it is quite possible that NEAT is influenced by genetics, but the fact that NEAT is low in so many people should be a red flag. In the same way that the fact that so many people who eat refined carbohydrate-rich foods are obese should be a red flag. Moreover, modern isolated hunter-gatherers tend to have low levels of body fat. Given the importance of NEAT for body fat regulation, it is not unreasonable to assume that NEAT is elevated in hunter-gatherers, compared to modern urbanites. Hunter-gatherers live more like our Paleolithic ancestors than modern urbanites.
True genetic diseases, caused by recent harmful mutations, are usually rare. If low NEAT were truly a genetic “disease”, those with low NEAT should be a small minority. That is not the case. It is more likely that the low NEAT that we see in modern urbanites is due to a maladaptation of our Stone Age body to modern life, in the same way that our Stone Age body is maladapted to the consumption of foods rich in refined grains and seeds.
What could have increased NEAT among our Paleolithic ancestors, and among modern isolated hunter-gatherers?
One thing that comes to mind is lack of comfortable furniture, particularly comfortable chairs (photo below from: prlog.org). It is quite possible that our Paleolithic ancestors invented some rudimentary forms of furniture, but they would have been much less comfortable than modern furniture used in most offices and homes. The padding of comfy office chairs is not very easy to replicate with stones, leaves, wood, or even animal hides. You need engineering to design it; you need industry to produce that kind of thing.
I have been doing a little experiment with myself, where I do things that force me to sit tall and stand while working in my office, instead of sitting back and “relaxing”. Things like putting a pillow on the chair so that I cannot rest my back on it, or placing my computer on an elevated surface so that I am forced to work while standing up. I tend to move a lot more when I do those things, and the movement is largely involuntary. These are small but constant movements, a bit like fidgeting. (It would be interesting to tape myself and actually quantify the amount of movement.)
It seems that one can induce an increase in NEAT, which is largely due to involuntary activities, by doing some voluntary things like placing a pillow on a chair or working while standing up.
Is it possible that the unnaturalness of comfy furniture, and particularly of comfy chairs, is contributing (together with other factors) to not only making us fat but also having low-back problems?
Both obesity and low-back problems are widespread among modern urbanites. Yet, from an evolutionary perspective, they should not be. They likely impaired survival success among our ancestors, and thus impaired their reproductive success. Evolution “gets angry” at these things; over time it wipes them out. In my reading of studies of hunter-gatherers, I don’t recall a single instance in which obesity and low-back problems were described as being widespread.
But why should this be?
The degree to which different individuals will develop diseases of civilization in response to consumption of refined carbohydrate-rich foods can also be seen as influenced by genetics. After all, there are many people who eat those foods and are thin and healthy, and that appears to be in part a family trait. But whether we consume those products or not is largely within our control.
So, it is quite possible that NEAT is influenced by genetics, but the fact that NEAT is low in so many people should be a red flag. In the same way that the fact that so many people who eat refined carbohydrate-rich foods are obese should be a red flag. Moreover, modern isolated hunter-gatherers tend to have low levels of body fat. Given the importance of NEAT for body fat regulation, it is not unreasonable to assume that NEAT is elevated in hunter-gatherers, compared to modern urbanites. Hunter-gatherers live more like our Paleolithic ancestors than modern urbanites.
True genetic diseases, caused by recent harmful mutations, are usually rare. If low NEAT were truly a genetic “disease”, those with low NEAT should be a small minority. That is not the case. It is more likely that the low NEAT that we see in modern urbanites is due to a maladaptation of our Stone Age body to modern life, in the same way that our Stone Age body is maladapted to the consumption of foods rich in refined grains and seeds.
What could have increased NEAT among our Paleolithic ancestors, and among modern isolated hunter-gatherers?
One thing that comes to mind is lack of comfortable furniture, particularly comfortable chairs (photo below from: prlog.org). It is quite possible that our Paleolithic ancestors invented some rudimentary forms of furniture, but they would have been much less comfortable than modern furniture used in most offices and homes. The padding of comfy office chairs is not very easy to replicate with stones, leaves, wood, or even animal hides. You need engineering to design it; you need industry to produce that kind of thing.
I have been doing a little experiment with myself, where I do things that force me to sit tall and stand while working in my office, instead of sitting back and “relaxing”. Things like putting a pillow on the chair so that I cannot rest my back on it, or placing my computer on an elevated surface so that I am forced to work while standing up. I tend to move a lot more when I do those things, and the movement is largely involuntary. These are small but constant movements, a bit like fidgeting. (It would be interesting to tape myself and actually quantify the amount of movement.)
It seems that one can induce an increase in NEAT, which is largely due to involuntary activities, by doing some voluntary things like placing a pillow on a chair or working while standing up.
Is it possible that the unnaturalness of comfy furniture, and particularly of comfy chairs, is contributing (together with other factors) to not only making us fat but also having low-back problems?
Both obesity and low-back problems are widespread among modern urbanites. Yet, from an evolutionary perspective, they should not be. They likely impaired survival success among our ancestors, and thus impaired their reproductive success. Evolution “gets angry” at these things; over time it wipes them out. In my reading of studies of hunter-gatherers, I don’t recall a single instance in which obesity and low-back problems were described as being widespread.
U.S. Senate votes to re-authorize federal flood insurance program, insurers urging House to act quickly
The National Flood Insurance Program, which has repeatedly expired this year, only to be reauthorized by Congress for short stints, is slated to expire on Sept. 30. To prevent that, the U.S. Senate yesterday voted to extend the program through Sept. 30, 2011.
Insurers and insurance associations are now urging the House of Representatives to quickly do the same thing.
Congress created the program in 1968 as a way of getting a handle on the increasing public costs of providing aid to flood victims.
Many homeowners assume that flood damage is covered by standard homeowners coverage. It is not. The same is true for standard renters- and commercial property policies. If you want flood coverage, you have to specifically get flood coverage. (There's one exception to this general rule: comprehensive auto insurance coverage tends to cover flood damage to the vehicle.)
Flood insurance has been a major issue in south King County's Green River Valley, where the Army Corps of Engineers says there's a higher-than-normal risk of flooding due to weakness in an abutment to the Howard Hanson Dam. Work by the Corps and its contractors has dramatically reduced the risk of serious flooding (it was 1 in 3 last fall, now the Corps says its about 1 in 60), but we're still urging property owners and renters in the area to seriously consider getting at least the federal flood coverage.
For businesses, the federal coverage (capped at $500k/building and $500k contents) will not be enough. Many insurers stopped writing coverage in the area last fall. To help, our office has organized the Washington Flood Market Assistance Plan, which acts like a matchmaker between Green River Valley businesses needing coverage and insurers selling it.
The Insurance Information Institute has prepared a lot of flood-related information, including a list of major floods, how to prepare for a flood, what to do during a flood, and how to recover from a flood.
(Post modified 9/23 to add the info and a link for the state's flood Market Assistance Plan.)
Insurers and insurance associations are now urging the House of Representatives to quickly do the same thing.
Congress created the program in 1968 as a way of getting a handle on the increasing public costs of providing aid to flood victims.
Many homeowners assume that flood damage is covered by standard homeowners coverage. It is not. The same is true for standard renters- and commercial property policies. If you want flood coverage, you have to specifically get flood coverage. (There's one exception to this general rule: comprehensive auto insurance coverage tends to cover flood damage to the vehicle.)
Flood insurance has been a major issue in south King County's Green River Valley, where the Army Corps of Engineers says there's a higher-than-normal risk of flooding due to weakness in an abutment to the Howard Hanson Dam. Work by the Corps and its contractors has dramatically reduced the risk of serious flooding (it was 1 in 3 last fall, now the Corps says its about 1 in 60), but we're still urging property owners and renters in the area to seriously consider getting at least the federal flood coverage.
For businesses, the federal coverage (capped at $500k/building and $500k contents) will not be enough. Many insurers stopped writing coverage in the area last fall. To help, our office has organized the Washington Flood Market Assistance Plan, which acts like a matchmaker between Green River Valley businesses needing coverage and insurers selling it.
The Insurance Information Institute has prepared a lot of flood-related information, including a list of major floods, how to prepare for a flood, what to do during a flood, and how to recover from a flood.
(Post modified 9/23 to add the info and a link for the state's flood Market Assistance Plan.)
Tuesday, September 21, 2010
UN Foundation in conjunction with the MDG Summit: Digital Media Lounge
A seemingly limitless supply of facts and figures about the state of the Millennium Development Goals (MDG's) can be found from a myriad of global health organizations by performing a quick internet search, yet many of us do not have the chance to witness or interact with the lives those numbers represent, to know what the lack of access means to them. Experts from India, Iraq, the United Kingdom and others underscored the need to address the whole picture of girls’ and women’s lives through access to education, family planning, and jobs rather than providing only medical assistance. MDG's 4, 5 and 6 will only be achieved they said, if girls and women have hope. Zainab Salbi, Founder of Women for Women International, said that girls and women must have “…hope in humanity,” and asked, “How do we restore that hope? How do we keep it alive?” Kimberly Perry, director of Girl Up, suggested new methods to inspire hope through peer group connections such as teenage girls in American connecting with teenage girls in Tanzania. These women argued that hope will be the driving force behind successfully achieving MDG's 4, 5 and 6. They said something needs to be done now, not tomorrow, next week or next year, and aid efforts should be targeted towards linking services to underserved populations.
Estimates from global health organizations such as UNICEF and Save the Children state that between fifteen and sixteen million women and children under five years of age could be saved between now and 2015 if MDG's 4, 5, and 6 are achieved. Today, leaders from major donor countries (USA, UK, and Australia) as well as Melinda Gates from the Bill and Melinda Gates Foundation agreed with the panelists here at the 92|Y; something must be done now. They collectively pledged over $5billion dollars over the next five years to specifically address maternal and child health.
The Yale Global Health Leadership Institute works directly on maternal, newborn and child issues through the Ethiopian Millennium Rural Initiative (EMRI) The EMRI initiative is a health system strengthening initiative implemented by the Clinton Health Access Initiative (CHAI) in rural Ethiopia. Yale tracks indicators relating to childhood immunizations (measles and pentavalent 3) in addition to indicators on institutional delivery and childhood nutrition in its evaluation of the EMRI program.
Gabe Forrey, GHLI Project Manager
Personal Business Commitments are all about working as a team
By Rik Ganderton
President and CEO
We call it alignment.
But another way to describe our annual Personal Business Commitments (PBCs) is teamwork.
My PBCs set out the direction for all other team members, vice-presidents, directors and everyone throughout the hospital. As autumn begins, this is a good time of year for us to refocus on our commitments to our hospital.
As you can read in my PBCs, which we publish publicly each year, we are focused on quality and constant improvement at Rouge Valley Health System.
I’m proud to report that our Deficit Elimination Plan of 2008-11 is drawing to a successful completion during the next six months, with our promises kept – to maintain patient volumes and improve overall patient care, while ending all overspending.
The plan enabled us to jump over other equally high hurdles, through our collective ongoing implementation of the Lean management philosophy.
As CEO, I focus on challenges ahead. But allow me to pause here and reflect on the sweeping achievements you have all made for our patients. Because of your application of Lean our patients now:
• Go home sooner – as a result of improved patient flow and your discharge planning;
• Get lab and diagnostic imaging results faster, in hours rather than days;
• Wait less time for care in our emergency department;
• Walk less distance in pre-admit clinics, because our professionals now come to them;
• Cancel fewer surgeries thanks to enhanced pre-surgical screening; and
• Waste less of their time filling in forms.
The successful teamwork of the Deficit Elimination Plan and Lean initiatives have also set the platform on which we all stand today. Now our focus moves more toward our four dimensions: Access to Care; Service Excellence; Fiscal Responsibility; and Team Engagement.
The PBC process provides us all with an important checklist on those dimensions. As we check off our achievements throughout the fiscal year, we can see our individual and team goals coming to fruition for our patients.
There is something cathartic about putting a check mark next to an item on a to-do list isn’t there? Our PBCs are our team checklists. Yours will be different from mine. But all PBCs focus on the same set of objectives and targets found in mine.
You’ll also notice that the PBCs are now lined up with our overall leadership tools, as shown on the Strategic Linkage page, which directly aligns our: Mission Vision Values; Strategic Plan-On-A-Page; Transformation Themes; and Dimensions.
To further reinforce our four dimensions, we are labeling each our stories in the Echo magazine with the relevant dimension to demonstrate how everyone is working toward the same set of objectives.
By harnessing your focused efforts to constantly improve health care for our patients we will achieve our vision to be the best at what we do.
Thank you for your engagement, your creativity and your daily commitment to Rouge Valley Health System.
Monday, September 20, 2010
Global Mala 2010 - Asbury Park, NJ
This weekend was the Yoga Festival by the Sea in Asbury Park, NJ. It was an exciting weekend of yoga, yummy vegan food and great people! =) Read my blog post here.The Global Mala was founded by Shiva Rea to unite the global yoga community from every continent to form a "mala around the earth" by spreading peace in hopes that it has a ripple effect throughout the world. On Sunday, we gathered and practiced 108 sun salutations together on the Asbury Park boardwalk.
All of the money raised for this event will go towards bringing yoga into Asbury Park Schools.
The image above was shot by Kiersten Rowland of Prema Photographic
(she got so many lovely shots of the day!).
Keep it Fresh!
- Lauren
Healthy Happy Hour - 9/23 @ Watermark
3 Healthy Chicks are hosting their first Healthy Happy Hour this Thursday at the Watermark in Asbury Park, NJ. We'll be hanging out from 5-7pm and hope that you can stop in for a cocktail or some food. There aren't many more nights to enjoy outside with the Fall rolling in so we figured the Watermark would be the perfect place to enjoy the full moon over the ocean this Thursday. Please join! In the meantime, Keep it Fresh!After happy hour we'll be heading over to AP Dance Arts for Terra's 7pm hoop class! Hooping after a few doozies...too fun!
Sunday, September 19, 2010
Potatoes and Human Health, Part I
Potatoes: an Introduction
Over 10,000 years ago, on the shores of lake Titicaca in what is now Peru, a culture began to cultivate a species of wild potato, Solanum tuberosum. They gradually transformed it into a plant that efficiently produces roundish starchy tubers, in a variety of strains that suited the climactic and gastronomic needs of various populations. These early farmers could not have understood at the time that the plant they were selecting would become the most productive crop in the world*, and eventually feed billions of people around the globe.
Wild potatoes, which were likely consumed by hunter-gatherers before domestication, are higher in toxic glycoalkaloids. These are defensive compounds that protect against insects, infections and... hungry animals. Early farmers selected varieties that are low in bitter glycoalkaloids, which are the ancestors of most modern potatoes, however they didn't abandon the high-glycoalkaloid varieties. These were hardier and more tolerant of high altitudes, cold temperatures and pests. Cultures living high in the Andes developed a method to take advantage of these hardy but toxic potatoes, as well as their own harsh climate: they invented chuños. These are made by leaving potatoes out in the open, where they are frozen at night, stomped underfoot and dried in the sun for many days**. What results is a dried potato with a low glycoalkaloid content that can be stored for a year or more.
Nutritional Qualities
From a nutritional standpoint, potatoes are a mixed bag. On one hand, if I had to pick a single food to eat exclusively for a while, potatoes would be high on the list. One reason is that they contain an adequate amount of complete protein, meaning they don't have to be mixed with another protein source as with grains and legumes. Another reason is that a number of cultures throughout history have successfully relied on the potato as their principal source of calories, and several continue to do so. A third reason is that they're eaten in an unrefined, fresh state.
Potatoes contain an adequate amount of many essential minerals, and due to their low phytic acid content (1), the minerals they contain are well absorbed. They're rich in magnesium and copper, two minerals that are important for insulin sensitivity and cardiovascular health (2, 3). They're also high in potassium and vitamin C. Overall, they have a micronutrient content that compares favorably with other starchy root vegetables such as taro and cassava (4, 5, 6). Due to their very low fat content, potatoes contain virtually no omega-6, and thus do not contribute to an excess of these essential fatty acids.
On the other hand, I don't have to eat potatoes exclusively, so what do they have to offer a mixed diet? They have a high glycemic index, which means they raise blood sugar more than an equivalent serving of most carbohydrate foods, although I'm not convinced that's a problem in people with good blood sugar control (7, 8). They're low-ish in fiber, which could hypothetically lead to a reduction in the number and diversity of gut bacteria in the absence of other fiber sources. Sweet potatoes, an unrelated species, contain more micronutrients and fiber, and have been a central food source for healthy cultures (9). However, the main reasons temperate-climate cultures throughout the world eat potatoes is they yield well, they're easily digested, they fill you up and they taste good.
In the next post, I'll delve into the biology and toxicology of potato glycoalkaloids, and review some animal data. In further posts, I'll address the most important question of all: what happens when a person eats mostly potatoes... for months, years, and generations?
* In terms of calories produced per acre.
** A simplified description. The process can actually be rather involved, with several different drying, stomping and leaching steps.
Over 10,000 years ago, on the shores of lake Titicaca in what is now Peru, a culture began to cultivate a species of wild potato, Solanum tuberosum. They gradually transformed it into a plant that efficiently produces roundish starchy tubers, in a variety of strains that suited the climactic and gastronomic needs of various populations. These early farmers could not have understood at the time that the plant they were selecting would become the most productive crop in the world*, and eventually feed billions of people around the globe.
Wild potatoes, which were likely consumed by hunter-gatherers before domestication, are higher in toxic glycoalkaloids. These are defensive compounds that protect against insects, infections and... hungry animals. Early farmers selected varieties that are low in bitter glycoalkaloids, which are the ancestors of most modern potatoes, however they didn't abandon the high-glycoalkaloid varieties. These were hardier and more tolerant of high altitudes, cold temperatures and pests. Cultures living high in the Andes developed a method to take advantage of these hardy but toxic potatoes, as well as their own harsh climate: they invented chuños. These are made by leaving potatoes out in the open, where they are frozen at night, stomped underfoot and dried in the sun for many days**. What results is a dried potato with a low glycoalkaloid content that can be stored for a year or more.
Nutritional Qualities
From a nutritional standpoint, potatoes are a mixed bag. On one hand, if I had to pick a single food to eat exclusively for a while, potatoes would be high on the list. One reason is that they contain an adequate amount of complete protein, meaning they don't have to be mixed with another protein source as with grains and legumes. Another reason is that a number of cultures throughout history have successfully relied on the potato as their principal source of calories, and several continue to do so. A third reason is that they're eaten in an unrefined, fresh state.
Potatoes contain an adequate amount of many essential minerals, and due to their low phytic acid content (1), the minerals they contain are well absorbed. They're rich in magnesium and copper, two minerals that are important for insulin sensitivity and cardiovascular health (2, 3). They're also high in potassium and vitamin C. Overall, they have a micronutrient content that compares favorably with other starchy root vegetables such as taro and cassava (4, 5, 6). Due to their very low fat content, potatoes contain virtually no omega-6, and thus do not contribute to an excess of these essential fatty acids.
On the other hand, I don't have to eat potatoes exclusively, so what do they have to offer a mixed diet? They have a high glycemic index, which means they raise blood sugar more than an equivalent serving of most carbohydrate foods, although I'm not convinced that's a problem in people with good blood sugar control (7, 8). They're low-ish in fiber, which could hypothetically lead to a reduction in the number and diversity of gut bacteria in the absence of other fiber sources. Sweet potatoes, an unrelated species, contain more micronutrients and fiber, and have been a central food source for healthy cultures (9). However, the main reasons temperate-climate cultures throughout the world eat potatoes is they yield well, they're easily digested, they fill you up and they taste good.
In the next post, I'll delve into the biology and toxicology of potato glycoalkaloids, and review some animal data. In further posts, I'll address the most important question of all: what happens when a person eats mostly potatoes... for months, years, and generations?
* In terms of calories produced per acre.
** A simplified description. The process can actually be rather involved, with several different drying, stomping and leaching steps.
Friday, September 17, 2010
Strong causation can exist without any correlation: The strange case of the chain smokers, and a note about diet
Researchers like to study samples of data and look for associations between variables. Often those associations are represented in the form of correlation coefficients, which go from -1 to 1. Another popular measure of association is the path coefficient, which usually has a narrower range of variation. What many researchers seem to forget is that the associations they find depend heavily on the sample they are looking at, and on the ranges of variation of the variables being analyzed.
A forgotten warning: Causation without correlation
Often those who conduct multivariate statistical analyses on data are unaware of certain limitations. Many times this is due to lack of familiarity with statistical tests. One warning we do see a lot though is: Correlation does not imply causation. This is, of course, absolutely true. If you take my weight from 1 to 20 years of age, and the price of gasoline in the US during that period, you will find that they are highly correlated. But common sense tells me that there is no causation whatsoever between these two variables.
So correlation does not imply causation alright, but there is another warning that is rarely seen: There can be strong causation without any correlation. Of course this can lead to even more bizarre conclusions than the “correlation does not imply causation” problem. If there is strong causation between variables B and Y, and it is not showing as a correlation, another variable A may “jump in” and “steal” that “unused correlation”; so to speak.
The chain smokers “study”
To illustrate this point, let us consider the following fictitious case, a study of “100 cities”. The study focuses on the effect of smoking and genes on lung cancer mortality. Smoking significantly increases the chances of dying from lung cancer; it is a very strong causative factor. Here are a few more details. Between 35 and 40 percent of the population are chain smokers. And there is a genotype (a set of genes), found in a small percentage of the population (around 7 percent), which is protective against lung cancer. All of those who are chain smokers die from lung cancer unless they die from other causes (e.g., accidents). Dying from other causes is a lot more common among those who have the protective genotype.
(I created this fictitious data with these associations in mind, using equations. I also added uncorrelated error into the equations, to make the data look a bit more realistic. For example, random deaths occurring early in life would reduce slightly any numeric association between chain smoking and cancer deaths in the sample of 100 cities.)
The table below shows part of the data, and gives an idea of the distribution of percentage of smokers (Smokers), percentage with the protective genotype (Pgenotype), and percentage of lung cancer deaths (MLCancer). (Click on it to enlarge. Use the "CRTL" and "+" keys to zoom in, and CRTL" and "-" to zoom out.) Each row corresponds to a city. The rest of the data, up to row 100, has a similar distribution.
The graphs below show the distribution of lung cancer deaths against: (a) the percentage of smokers, at the top; and (b) the percentage with the protective genotype, at the bottom. Correlations are shown at the top of each graph. (They can vary from -1 to 1. The closer they are to -1 or 1, the stronger is the association, negative or positive, between the variables.) The correlation between lung cancer deaths and percentage of smokers is slightly negative and statistically insignificant (-0.087). The correlation between lung cancer deaths and percentage with the protective genotype is negative, strong, and statistically significant (-0.613).
Even though smoking significantly increases the chances of dying from lung cancer, the correlations tell us otherwise. The correlations tell us that lung cancer does not seem to cause lung cancer deaths, and that having the protective genotype seems to significantly decrease cancer deaths. Why?
If there is no variation, there is no correlation
The reason is that the “researchers” collected data only about chain smokers. That is, the variable “Smokers” includes only chain smokers. If this was not a fictitious case, focusing the study on chain smokers could be seen as a clever strategy employed by researchers funded by tobacco companies. The researchers could say something like this: “We focused our analysis on those most likely to develop lung cancer.” Or, this could have been the result of plain stupidity when designing the research project.
By restricting their study to chain smokers the researchers dramatically reduced the variability in one particular variable: the extent to which the study participants smoked. Without variation, there can be no correlation. No matter what statistical test or software is used, no significant association will be found between lung cancer deaths and percentage of smokers based on this dataset. No matter what statistical test or software is used, a significant and strong association will be found between lung cancer deaths and percentage with the protective genotype.
Of course, this could lead to a very misleading conclusion. Smoking does not cause lung cancer; the real cause is genetic.
A note about diet
Consider the analogy between smoking and consumption of a particular food, and you will probably see what this means for the analysis of observational data regarding dietary choices and disease. This applies to almost any observational study, including the China Study. (Studies employing experimental control manipulations would presumably ensure enough variation in the variables studied.) In the China Study, data from dozens of counties were collected. One may find a significant association between consumption of food A and disease Y.
There may be a much stronger association between food B and disease Y, but that association may not show up in statistical analyses at all, simply because there is little variation in the data regarding consumption of food B. For example, all those sampled may have eaten food B; about the same amount. Or none. Or somewhere in between, within a rather small range of variation.
Statistical illiteracy, bad choices, and taxation
Statistics is a “necessary evil”. It is useful to go from small samples to large ones when we study any possible causal association. By doing so, one can find out whether an observed effect really applies to a larger percentage of the population, or is actually restricted to a small group of individuals. The problem is that we humans are very bad at inferring actual associations from simply looking at large tables with numbers. We need statistical tests for that.
However, ignorance about basic statistical phenomena, such as the one described here, can be costly. A group of people may eliminate food A from their diet based on coefficients of association resulting from what seem to be very clever analyses, replacing it with food B. The problem is that food B may be equally harmful, or even more harmful. And, that effect may not show up on statistical analyses unless they have enough variation in the consumption of food B.
Readers of this blog may wonder why we explicitly use terms like “suggests” when we refer to a relationship that is suggested by a significant coefficient of association (e.g., a linear correlation). This is why, among other reasons.
One does not have to be a mathematician to understand basic statistical concepts. And doing so can be very helpful in one’s life in general, not only in diet and lifestyle decisions. Even in simple choices, such as what to be on. We are always betting on something. For example, any investment is essentially a bet. Some outcomes are much more probable than others.
Once I had an interesting conversation with a high-level officer of a state government. I was part of a consulting team working on an information technology project. We were talking about the state lottery, which was a big source of revenue for the state, comparing it with state taxes. He told me something to this effect:
Our lottery is essentially a tax on the statistically illiterate.
A forgotten warning: Causation without correlation
Often those who conduct multivariate statistical analyses on data are unaware of certain limitations. Many times this is due to lack of familiarity with statistical tests. One warning we do see a lot though is: Correlation does not imply causation. This is, of course, absolutely true. If you take my weight from 1 to 20 years of age, and the price of gasoline in the US during that period, you will find that they are highly correlated. But common sense tells me that there is no causation whatsoever between these two variables.
So correlation does not imply causation alright, but there is another warning that is rarely seen: There can be strong causation without any correlation. Of course this can lead to even more bizarre conclusions than the “correlation does not imply causation” problem. If there is strong causation between variables B and Y, and it is not showing as a correlation, another variable A may “jump in” and “steal” that “unused correlation”; so to speak.
The chain smokers “study”
To illustrate this point, let us consider the following fictitious case, a study of “100 cities”. The study focuses on the effect of smoking and genes on lung cancer mortality. Smoking significantly increases the chances of dying from lung cancer; it is a very strong causative factor. Here are a few more details. Between 35 and 40 percent of the population are chain smokers. And there is a genotype (a set of genes), found in a small percentage of the population (around 7 percent), which is protective against lung cancer. All of those who are chain smokers die from lung cancer unless they die from other causes (e.g., accidents). Dying from other causes is a lot more common among those who have the protective genotype.
(I created this fictitious data with these associations in mind, using equations. I also added uncorrelated error into the equations, to make the data look a bit more realistic. For example, random deaths occurring early in life would reduce slightly any numeric association between chain smoking and cancer deaths in the sample of 100 cities.)
The table below shows part of the data, and gives an idea of the distribution of percentage of smokers (Smokers), percentage with the protective genotype (Pgenotype), and percentage of lung cancer deaths (MLCancer). (Click on it to enlarge. Use the "CRTL" and "+" keys to zoom in, and CRTL" and "-" to zoom out.) Each row corresponds to a city. The rest of the data, up to row 100, has a similar distribution.
The graphs below show the distribution of lung cancer deaths against: (a) the percentage of smokers, at the top; and (b) the percentage with the protective genotype, at the bottom. Correlations are shown at the top of each graph. (They can vary from -1 to 1. The closer they are to -1 or 1, the stronger is the association, negative or positive, between the variables.) The correlation between lung cancer deaths and percentage of smokers is slightly negative and statistically insignificant (-0.087). The correlation between lung cancer deaths and percentage with the protective genotype is negative, strong, and statistically significant (-0.613).
Even though smoking significantly increases the chances of dying from lung cancer, the correlations tell us otherwise. The correlations tell us that lung cancer does not seem to cause lung cancer deaths, and that having the protective genotype seems to significantly decrease cancer deaths. Why?
If there is no variation, there is no correlation
The reason is that the “researchers” collected data only about chain smokers. That is, the variable “Smokers” includes only chain smokers. If this was not a fictitious case, focusing the study on chain smokers could be seen as a clever strategy employed by researchers funded by tobacco companies. The researchers could say something like this: “We focused our analysis on those most likely to develop lung cancer.” Or, this could have been the result of plain stupidity when designing the research project.
By restricting their study to chain smokers the researchers dramatically reduced the variability in one particular variable: the extent to which the study participants smoked. Without variation, there can be no correlation. No matter what statistical test or software is used, no significant association will be found between lung cancer deaths and percentage of smokers based on this dataset. No matter what statistical test or software is used, a significant and strong association will be found between lung cancer deaths and percentage with the protective genotype.
Of course, this could lead to a very misleading conclusion. Smoking does not cause lung cancer; the real cause is genetic.
A note about diet
Consider the analogy between smoking and consumption of a particular food, and you will probably see what this means for the analysis of observational data regarding dietary choices and disease. This applies to almost any observational study, including the China Study. (Studies employing experimental control manipulations would presumably ensure enough variation in the variables studied.) In the China Study, data from dozens of counties were collected. One may find a significant association between consumption of food A and disease Y.
There may be a much stronger association between food B and disease Y, but that association may not show up in statistical analyses at all, simply because there is little variation in the data regarding consumption of food B. For example, all those sampled may have eaten food B; about the same amount. Or none. Or somewhere in between, within a rather small range of variation.
Statistical illiteracy, bad choices, and taxation
Statistics is a “necessary evil”. It is useful to go from small samples to large ones when we study any possible causal association. By doing so, one can find out whether an observed effect really applies to a larger percentage of the population, or is actually restricted to a small group of individuals. The problem is that we humans are very bad at inferring actual associations from simply looking at large tables with numbers. We need statistical tests for that.
However, ignorance about basic statistical phenomena, such as the one described here, can be costly. A group of people may eliminate food A from their diet based on coefficients of association resulting from what seem to be very clever analyses, replacing it with food B. The problem is that food B may be equally harmful, or even more harmful. And, that effect may not show up on statistical analyses unless they have enough variation in the consumption of food B.
Readers of this blog may wonder why we explicitly use terms like “suggests” when we refer to a relationship that is suggested by a significant coefficient of association (e.g., a linear correlation). This is why, among other reasons.
One does not have to be a mathematician to understand basic statistical concepts. And doing so can be very helpful in one’s life in general, not only in diet and lifestyle decisions. Even in simple choices, such as what to be on. We are always betting on something. For example, any investment is essentially a bet. Some outcomes are much more probable than others.
Once I had an interesting conversation with a high-level officer of a state government. I was part of a consulting team working on an information technology project. We were talking about the state lottery, which was a big source of revenue for the state, comparing it with state taxes. He told me something to this effect:
Our lottery is essentially a tax on the statistically illiterate.
Is "vitamin C" really a vitamin?
After 40 years of research, Dr. Irwin Stone stated his conclusion that an ancient genetic mutation left the primate virtually alone among animals in not producing ascorbic acid in his own body. By labeling ascorbic acid a "vitamin" and attaching to it a "minimum daily requirement," most people exist in a state of sub-clinical scurvy-the symptoms of which are attributed to other ailments.
By the 1950s Dr. Stone's work with ascorbates had explained the success of Dr. Klenner's use of ascorbic acid to treat polio. By the 1960s, Dr. Stone's work had attracted the attention of Nobel laureate Dr. Linus Pauling . Dr. Pauling was then able to successfully apply "mega-ascorbate therapy" to a variety of ailments-including cancer, heart disease and diabetes.
The answer is to change our thinking about vitamin C-which is really a metabolite that is essential to health and healing at the molecular level. Dr. Stone's foundational research has provided us with the knowledge to ward off disease, counteract the ill effects of pollution and prolong our lives-easily and inexpensively.
By the 1950s Dr. Stone's work with ascorbates had explained the success of Dr. Klenner's use of ascorbic acid to treat polio. By the 1960s, Dr. Stone's work had attracted the attention of Nobel laureate Dr. Linus Pauling . Dr. Pauling was then able to successfully apply "mega-ascorbate therapy" to a variety of ailments-including cancer, heart disease and diabetes.
The answer is to change our thinking about vitamin C-which is really a metabolite that is essential to health and healing at the molecular level. Dr. Stone's foundational research has provided us with the knowledge to ward off disease, counteract the ill effects of pollution and prolong our lives-easily and inexpensively.
Osteoporosis drugs causing fractures - another promise that does not add up
I was reading in the Star Ledger about how the often prescribed osteoporosis drugs like Boneva and Fosamax have been found to create fractures (http://www.allvoices.com/contributed-news/6786125-osteoporosis-drugs-like-fosamax-and-boniva-linked-to-hip-fractures).
Years ago, we would spot osteoporosis on an x ray and it would tell us that certain people are prone to having possible problems with fractures. Hip fractures in the elderly can be devastating. Earlier generations in many ways were less active in retirement ( I remember my grandmother and her card games as activities vs. my parents who played tennis and go to the gym.). We had less sophisticated tools to look at this such as x rays vs. our Dexxa Scanners that are much more sensitive to detecting early bone loss. The drug companies worked on medications they could sell us as being preventative for bone loss when loss was occurring as per these very sensitive scanners and they sold doctors on the idea through their drug reps. Many people now found their doctors managing their health by the numbers on the scan. I have seen hundreds of people who were placed on these drugs to prevent the yet disease (the one that did not happen or may never happen yet). Many of our patients who went on these drugs promptly went off when the side effects hit. I am sure these numbers are underreported.
The bottom line is that this is clearly interventional, not preventative and dispite the billions made by the drug companies on this supposedly preventative health regimen, in the end, it is side effects, over doctoring and then having pecuilar types of fractures that may not have occurred if you were not on the drug.
I have a better protocol; Stay active, eat right and play the odds (very few people actually have problems related to osteoporosis when considering the entire populace) In other words, leave it alone.
What do you think? As always, I value your opinion
Years ago, we would spot osteoporosis on an x ray and it would tell us that certain people are prone to having possible problems with fractures. Hip fractures in the elderly can be devastating. Earlier generations in many ways were less active in retirement ( I remember my grandmother and her card games as activities vs. my parents who played tennis and go to the gym.). We had less sophisticated tools to look at this such as x rays vs. our Dexxa Scanners that are much more sensitive to detecting early bone loss. The drug companies worked on medications they could sell us as being preventative for bone loss when loss was occurring as per these very sensitive scanners and they sold doctors on the idea through their drug reps. Many people now found their doctors managing their health by the numbers on the scan. I have seen hundreds of people who were placed on these drugs to prevent the yet disease (the one that did not happen or may never happen yet). Many of our patients who went on these drugs promptly went off when the side effects hit. I am sure these numbers are underreported. The bottom line is that this is clearly interventional, not preventative and dispite the billions made by the drug companies on this supposedly preventative health regimen, in the end, it is side effects, over doctoring and then having pecuilar types of fractures that may not have occurred if you were not on the drug.
I have a better protocol; Stay active, eat right and play the odds (very few people actually have problems related to osteoporosis when considering the entire populace) In other words, leave it alone.
What do you think? As always, I value your opinion
Wednesday, September 15, 2010
Speaking at Wise Traditions 2010
I'm happy to announce that I'll be presenting at the Weston A. Price foundation's 2010 Wise Traditions conference. The conference will be held in King of Prussia, Pennsylvania, Nov 12-14. The theme is the politics of food.Sally Fallon Morell has invited me to give a talk on the diet and health of Pacific islanders. The talk will be titled "Kakana Dina: Diet and Health in the Pacific Islands", and it will take place on Sunday, November 14th from 4:00 to 5:20 pm. In preparation for the talk, I've read eight books and countless journal articles. Although some of the material will be familiar to people who follow the blog, I will not be rehashing what I've already published. I have nearly an hour and a half to talk, so I'll be going into some depth on the natural history and traditional food habits of Pacific island populations. Not just macronutrient breakdowns... specific foods and traditional preparation methods.
Learn about the health of traditional Pacific island populations, and what has changed since Western contact. Learn about traditional cooking and fermentation techniques. See unpublished photos from the Kitava study, courtesy of Dr. Staffan Lindeberg. Learn about the nutritional and ceremonial role of mammals including pork... and the most gruesome food of all.
I hope to see you there!
Kitava photo courtesy of Dr. Staffan Lindeberg
Tuesday, September 14, 2010
How -- and why -- to become a "group of one"
In a couple of weeks, changes to Washington state law will make it easier for sole proprietors and some self-employed individuals to get affordable health insurance coverage.
The change involves small group coverage, which under state law in recent years has meant entities (such as small businesses) of 2 to 50 employees. They could qualify for health coverage in the small group market, which doesn't require a health screening.
One-person businesses, however, have had to seek coverage in the individual insurance market, where health screening is the norm and coverage can be hard to find (and expensive) for folks with pre-existing medical conditions.
By Oct. 1, 2010, however, state law will consider 1 person a "group" for insurance purposes. This means that sole proprietors, for example, will be able to qualify for the group coverage.
There are some provisions to ensure that the business is bona fide, however. In general, the law requires people to show that:
-they've been employed by (or run) the same business for at least the last 12 months,
-they've made at least 75 percent of their income (or 51 percent for agricultural businesses) from the business or trade.
The bill changing the law was Senate Bill 6538, prime-sponsored by Sen. Karen Keiser and co-sponsored by Sen. Cheryl Pflug. Similar changes to federal law have been approved by Congress and signed by the president -- they're included in the federal health reform legislation passed this spring -- but don't take effect until 2014.
To find out more, talk to your insurance agent or broker, or call us -- the Washington state insurance commissioner's office -- at 1-800-562-6900.
Note: This post was corrected to indicate that the federal changes don't take effect until 2014.
The change involves small group coverage, which under state law in recent years has meant entities (such as small businesses) of 2 to 50 employees. They could qualify for health coverage in the small group market, which doesn't require a health screening.
One-person businesses, however, have had to seek coverage in the individual insurance market, where health screening is the norm and coverage can be hard to find (and expensive) for folks with pre-existing medical conditions.
By Oct. 1, 2010, however, state law will consider 1 person a "group" for insurance purposes. This means that sole proprietors, for example, will be able to qualify for the group coverage.
There are some provisions to ensure that the business is bona fide, however. In general, the law requires people to show that:
-they've been employed by (or run) the same business for at least the last 12 months,
-they've made at least 75 percent of their income (or 51 percent for agricultural businesses) from the business or trade.
The bill changing the law was Senate Bill 6538, prime-sponsored by Sen. Karen Keiser and co-sponsored by Sen. Cheryl Pflug. Similar changes to federal law have been approved by Congress and signed by the president -- they're included in the federal health reform legislation passed this spring -- but don't take effect until 2014.
To find out more, talk to your insurance agent or broker, or call us -- the Washington state insurance commissioner's office -- at 1-800-562-6900.
Note: This post was corrected to indicate that the federal changes don't take effect until 2014.
3HC's September Newsletter
September newsletter all about back to school, apples and other fun stuff! Check it out by clicking the picture of us above and Keep it Fresh!
Love,
3HCs
Love,
3HCs
WA court ruling says that insurance value of property includes sales tax
Jason Anderson, a Seattle lawyer and longtime author of the Washington State Insurance Law Blog, has put up a post re: a recent Washington State Supreme Court ruling that "actual cash value" of insured property includes sales tax, even if the policyholder hasn't yet purchased replacement property.
The case involves a woman named Laura Holden, who had rental insurance when a fire struck the home she was renting. She had coverage with Farmers, including an extra endorsement for replacement cost coverage. The insurer didn't want to pay sales tax until after Holden had purchased replacement items; she said she couldn't afford to pay first and then wait for reimbursement. Click here for Anderson's blog post summarizing the case and the court's ruling, which reversed a lower court's decision.
While we're at it, we might as well mention that there's at least one other longtime regional insurance law blog, the Northwest Insurance Law Blog, written by lawyers in Seattle and Portland. Both summarize recent rulings in insurance law. (And our usual disclaimer applies: mentioning an entity on this blog ≠ endorsement. But you knew that.)
The case involves a woman named Laura Holden, who had rental insurance when a fire struck the home she was renting. She had coverage with Farmers, including an extra endorsement for replacement cost coverage. The insurer didn't want to pay sales tax until after Holden had purchased replacement items; she said she couldn't afford to pay first and then wait for reimbursement. Click here for Anderson's blog post summarizing the case and the court's ruling, which reversed a lower court's decision.
While we're at it, we might as well mention that there's at least one other longtime regional insurance law blog, the Northwest Insurance Law Blog, written by lawyers in Seattle and Portland. Both summarize recent rulings in insurance law. (And our usual disclaimer applies: mentioning an entity on this blog ≠ endorsement. But you knew that.)
Small business fair coming up in Renton
More than 30 federal, state and local government agencies -- including us -- and business and trade associations are hosting a Washington Small Business Fair in Renton on Sept. 25.
Here's the slogan, which sums it up nicely: "One day, one place - learn what you need to run a small business."
Our folks will be there with specifics on business insurance, and can answer questions about a wide variety of other insurance topics as well.
The event is free, parking is free, and no advance registration is required. It's from 8 a.m. to 3:30 p.m. at Renton Technical College, 3000 NE 4th Street, in Renton. The fair offers dozens of seminars, covering things like how to start a startup, legal and tax issues, marketing and PR, government contracts, etc.
Here's the event's website, and here's its Facebook page.
Here's the slogan, which sums it up nicely: "One day, one place - learn what you need to run a small business."
Our folks will be there with specifics on business insurance, and can answer questions about a wide variety of other insurance topics as well.
The event is free, parking is free, and no advance registration is required. It's from 8 a.m. to 3:30 p.m. at Renton Technical College, 3000 NE 4th Street, in Renton. The fair offers dozens of seminars, covering things like how to start a startup, legal and tax issues, marketing and PR, government contracts, etc.
Here's the event's website, and here's its Facebook page.
Monday, September 13, 2010
Survey finds that few Americans are familiar with upcoming health care reform changes
Many Americans are confused about the details and timing of health care reforms, according to a new survey released today by the National Association of Insurance Commissioners.
Only 14 percent of 1,000 representative American adults surveyed by phone could identify Sept. 23 as the start date for major reform provisions. They were given a choice of four dates.
Interestingly, 72 percent knew that many plans will no longer be able to exclude children with pre-existing conditions. Nearly as many -- 70 percent -- knew that parents will generally be able to keep their adult children on the parent's health plan until age 26. (There are exceptions, such as grandfathered plans.)
There are, however, some significant misperceptions out there, judging by the survey results. Half of the respondents thought tht employers with less than 50 workers will have to offer coverage to employees under the new law. In reality, those small companies will NOT be required to do so.
For a timeline of what happens when in health care reform, click here.
Only 14 percent of 1,000 representative American adults surveyed by phone could identify Sept. 23 as the start date for major reform provisions. They were given a choice of four dates.
Interestingly, 72 percent knew that many plans will no longer be able to exclude children with pre-existing conditions. Nearly as many -- 70 percent -- knew that parents will generally be able to keep their adult children on the parent's health plan until age 26. (There are exceptions, such as grandfathered plans.)
There are, however, some significant misperceptions out there, judging by the survey results. Half of the respondents thought tht employers with less than 50 workers will have to offer coverage to employees under the new law. In reality, those small companies will NOT be required to do so.
For a timeline of what happens when in health care reform, click here.
September Blogger, Lisa Crystal......my first six weeks!
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| Common street scene in Be'er Sheva, although this tree is looking particularly healthy! |
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| Using all the Hebrew I know to buy dried dates at the Bedouin Market. |
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| The courtyard at the hospital. One of the rare green areas, which helps keep me sane in the deserts |
Two weeks of real medical school under my belt, plus a month of orientation classes. I don’t quite feel like a real medical student yet (although I officially passed my first class!), but it’s getting closer. Right now, I just feel like an immigrant. It’s tough. Before coming to Israel, I knew I was choosing a challenging path in attending medical school in a foreign culture. Older MSIH students had also warned me of this. I chose to go here so I could learn how to live and heal in new cultures -- and I do not regret my choice. However, expecting difficulty won’t necessarily ease the pain when you are experiencing it.
John, the previous blogger, described a classic frustration here: the bank. Or think about setting up your own wireless router; in the U.S., it can easily bring out the worst in people. Then, when the internet still doesn’t connect, try calling tech support and pressing every single number on several automatic phone menus because you don’t understand any of the options and just want to talk to a human being who might possibly speak English. Then you get transferred to five different people before being told that someone will call you back in five minutes. He never does. I will never complain about pressing “1 for English” again.
I could give you a discouraging list of the frustrations, but that would not be entirely representative of my first few weeks here. Some problems simply take a time investment that I would make if I were in the U.S. Anyone needs to learn how to turn the key just right in a finicky lock. Furnishing an apartment takes time, even when you have more than two suitcases worth of belongings or own a car. Thankfully, we also have resources that ease the burden of living in a foreign country. There are the Israeli “student liaisons” who have helped us find apartments and overcome some language barriers. The second- and third-year students have advice (sometimes an overabundance) since they struggled through the same things. Techies in my class finally got the wireless internet working in my apartment -- after the internet company said the modem was broken.
Since life in Be’er Sheva does not end with frustration, I’ll mention some victories.
I am learning how wait in line like an Israeli. “Waiting in line” is a bit of a misnomer since Israelis don’t really stand in lines. From my Minnesotan perspective, when I go to the bank, I see a sea of people and watch them push to get the next opening. Cute old women cut in line at the grocery store. However, I have discovered that Israelis usually have a sense of who is ahead of them in line. I even heard them ask who is last in line when I went to the post office yesterday. If I know approximately what place I am in line, then confidently and swiftly move forward when it is my turn, I can generally get through the line quickly, fairly, and with only a small amount of yelling and pushing.
My roommate and I have a washing machine! To give a context for that victory, here’s how you find a used washer in Be’er Sheva based on our experience:
- Track used washing machine prices and find a few possibilities.
- E-mail a seller, translate her e-mail into English, call her, get vague directions from her friend since she doesn’t really speak English, and walk thirty minutes to the market across from her apartment.
- Spend an hour trying to find her apartment. Look for a building number that does not appear to be displayed anywhere (Israelis somehow don’t believe in consistently labeling buildings). Stumble through conversations in Hebrew with people on the street and with the seller.
- Keep wandering until you find her. Follow her through a narrow path to her apartment building and find that her washing machine looks great.
- Discover that she will be returning her keys to her landlord at 4 pm the following day.
- Head home since you have class from 8 am to 5pm tomorrow, have no car, can’t find a professional mover with such short notice, and have not been lifting enough weights to wrangle a washing machine all by yourself tonight.
- Go to bed. Repeat.
Eventually, we ended up finding a good washing machine and hired a mover to transport it for a reasonable price. Of course, it involved another night of absolutely no studying, but classes are pretty slow right now. Apparently things don’t really get going in Israel until after the fall holidays, so we have some grace during the move-in period.
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| Sometimes Be'er Sheva,doesn't seem like a different place; it is also in a time of its own. |
Life really is getting easier as we settle in. My roommate and I have acquired most of the furniture we need. My classmates continue to be great sources of inspiration and laughter. I am getting oriented to my new neighborhood and am developing some running routes. And, after I had a long conversation with the vegetable man over soup ingredients, he gave me a good deal -- a sign that I may be moving beyond the tourist phase.
Sunday, September 12, 2010
The China Study II: Wheat flour, rice, and cardiovascular disease
In my last post on the China Study II, I analyzed the effect of total and HDL cholesterol on mortality from all cardiovascular diseases. The main conclusion was that total and HDL cholesterol were protective. Total and HDL cholesterol usually increase with intake of animal foods, and particularly of animal fat. The lowest mortality from all cardiovascular diseases was in the highest total cholesterol range, 172.5 to 180; and the highest mortality in the lowest total cholesterol range, 120 to 127.5. The difference was quite large; the mortality in the lowest range was approximately 3.3 times higher than in the highest.
This post focuses on the intake of two main plant foods, namely wheat flour and rice intake, and their relationships with mortality from all cardiovascular diseases. After many exploratory multivariate analyses, wheat flour and rice emerged as the plant foods with the strongest associations with mortality from all cardiovascular diseases. Moreover, wheat flour and rice have a strong and inverse relationship with each other, which suggests a “consumption divide”. Since the data is from China in the late 1980s, it is likely that consumption of wheat flour is even higher now. As you’ll see, this picture is alarming.
The main model and results
All of the results reported here are from analyses conducted using WarpPLS. Below is the model with the main results of the analyses. (Click on it to enlarge. Use the "CRTL" and "+" keys to zoom in, and CRTL" and "-" to zoom out.) The arrows explore associations between variables, which are shown within ovals. The meaning of each variable is the following: SexM1F2 = sex, with 1 assigned to males and 2 to females; MVASC = mortality from all cardiovascular diseases (ages 35-69); TKCAL = total calorie intake per day; WHTFLOUR = wheat flour intake (g/day); and RICE = and rice intake (g/day).
The variables to the left of MVASC are the main predictors of interest in the model. The one to the right is a control variable – SexM1F2. The path coefficients (indicated as beta coefficients) reflect the strength of the relationships. A negative beta means that the relationship is negative; i.e., an increase in a variable is associated with a decrease in the variable that it points to. The P values indicate the statistical significance of the relationship; a P lower than 0.05 generally means a significant relationship (95 percent or higher likelihood that the relationship is “real”).
In summary, the model above seems to be telling us that:
- As rice intake increases, wheat flour intake decreases significantly (beta=-0.84; P<0.01). This relationship would be the same if the arrow pointed in the opposite direction. It suggests that there is a sharp divide between rice-consuming and wheat flour-consuming regions.
- As wheat flour intake increases, mortality from all cardiovascular diseases increases significantly (beta=0.32; P<0.01). This is after controlling for the effects of rice and total calorie intake. That is, wheat flour seems to have some inherent properties that make it bad for one’s health, even if one doesn’t consume that many calories.
- As rice intake increases, mortality from all cardiovascular diseases decreases significantly (beta=-0.24; P<0.01). This is after controlling for the effects of wheat flour and total calorie intake. That is, this effect is not entirely due to rice being consumed in place of wheat flour. Still, as you’ll see later in this post, this relationship is nonlinear. Excessive rice intake does not seem to be very good for one’s health either.
- Increases in wheat flour and rice intake are significantly associated with increases in total calorie intake (betas=0.25, 0.33; P<0.01). This may be due to wheat flour and rice intake: (a) being themselves, in terms of their own caloric content, main contributors to the total calorie intake; or (b) causing an increase in calorie intake from other sources. The former is more likely, given the effect below.
- The effect of total calorie intake on mortality from all cardiovascular diseases is insignificant when we control for the effects of rice and wheat flour intakes (beta=0.08; P=0.35). This suggests that neither wheat flour nor rice exerts an effect on mortality from all cardiovascular diseases by increasing total calorie intake from other food sources.
- Being female is significantly associated with a reduction in mortality from all cardiovascular diseases (beta=-0.24; P=0.01). This is to be expected. In other words, men are women with a few design flaws, so to speak. (This situation reverses itself a bit after menopause.)
Wheat flour displaces rice
The graph below shows the shape of the association between wheat flour intake (WHTFLOUR) and rice intake (RICE). The values are provided in standardized format; e.g., 0 is the mean (a.k.a. average), 1 is one standard deviation above the mean, and so on. The curve is the best-fitting U curve obtained by the software. It actually has the shape of an exponential decay curve, which can be seen as a section of a U curve. This suggests that wheat flour consumption has strongly displaced rice consumption in several regions in China, and also that wherever rice consumption is high wheat flour consumption tends to be low.
As wheat flour intake goes up, so does cardiovascular disease mortality
The graphs below show the shapes of the association between wheat flour intake (WHTFLOUR) and mortality from all cardiovascular diseases (MVASC). In the first graph, the values are provided in standardized format; e.g., 0 is the mean (or average), 1 is one standard deviation above the mean, and so on. In the second graph, the values are provided in unstandardized format and organized in terciles (each of three equal intervals).
The curve in the first graph is the best-fitting U curve obtained by the software. It is a quasi-linear relationship. The higher the consumption of wheat flour in a county, the higher seems to be the mortality from all cardiovascular diseases. The second graph suggests that mortality in the third tercile, which represents a consumption of wheat flour of 501 to 751 g/day (a lot!), is 69 percent higher than mortality in the first tercile (0 to 251 g/day).
Rice seems to be protective, as long as intake is not too high
The graphs below show the shapes of the association between rice intake (RICE) and mortality from all cardiovascular diseases (MVASC). In the first graph, the values are provided in standardized format. In the second graph, the values are provided in unstandardized format and organized in terciles.
Here the relationship is more complex. The lowest mortality is clearly in the second tercile (206 to 412 g/day). There is a lot of variation in the first tercile, as suggested by the first graph with the U curve. (Remember, as rice intake goes down, wheat flour intake tends to go up.) The U curve here looks similar to the exponential decay curve shown earlier in the post, for the relationship between rice and wheat flour intake.
In fact, the shape of the association between rice intake and mortality from all cardiovascular diseases looks a bit like an “echo” of the shape of the relationship between rice and wheat flour intake. Here is what is creepy. This echo looks somewhat like the first curve (between rice and wheat flour intake), but with wheat flour intake replaced by “death” (i.e., mortality from all cardiovascular diseases).
What does this all mean?
- Wheat flour displacing rice does not look like a good thing. Wheat flour intake seems to have strongly displaced rice intake in the counties where it is heavily consumed. Generally speaking, that does not seem to have been a good thing. It looks like this is generally associated with increased mortality from all cardiovascular diseases.
- High glycemic index food consumption does not seem to be the problem here. Wheat flour and rice have very similar glycemic indices (but generally not glycemic loads; see below). Both lead to blood glucose and insulin spikes. Yet, rice consumption seems protective when it is not excessive. This is true in part (but not entirely) because it largely displaces wheat flour. Moreover, neither rice nor wheat flour consumption seems to be significantly associated with cardiovascular disease via an increase in total calorie consumption. This is a bit of a blow to the theory that high glycemic carbohydrates necessarily cause obesity, diabetes, and eventually cardiovascular disease.
- The problem with wheat flour is … hard to pinpoint, based on the results summarized here. Maybe it is the fact that it is an ultra-refined carbohydrate-rich food; less refined forms of wheat could be healthier. In fact, the glycemic loads of less refined carbohydrate-rich foods tend to be much lower than those of more refined ones. (Also, boiled brown rice has a glycemic load that is about three times lower than that of whole wheat bread; whereas the glycemic indices are about the same.) Maybe the problem is wheat flour's gluten content. Maybe it is a combination of various factors, including these.
Reference
Kock, N. (2010). WarpPLS 1.0 User Manual. Laredo, Texas: ScriptWarp Systems.
Acknowledgment and notes
- Many thanks are due to Dr. Campbell and his collaborators for collecting and compiling the data used in this analysis. The data is from this site, created by those researchers to disseminate their work in connection with a study often referred to as the “China Study II”. It has already been analyzed by other bloggers. Notable analyses have been conducted by Ricardo at Canibais e Reis, Stan at Heretic, and Denise at Raw Food SOS.
- The path coefficients (indicated as beta coefficients) reflect the strength of the relationships; they are a bit like standard univariate (or Pearson) correlation coefficients, except that they take into consideration multivariate relationships (they control for competing effects on each variable). Whenever nonlinear relationships were modeled, the path coefficients were automatically corrected by the software to account for nonlinearity.
- The software used here identifies non-cyclical and mono-cyclical relationships such as logarithmic, exponential, and hyperbolic decay relationships. Once a relationship is identified, data values are corrected and coefficients calculated. This is not the same as log-transforming data prior to analysis, which is widely used but only works if the underlying relationship is logarithmic. Otherwise, log-transforming data may distort the relationship even more than assuming that it is linear, which is what is done by most statistical software tools.
- The R-squared values reflect the percentage of explained variance for certain variables; the higher they are, the better the model fit with the data. In complex and multi-factorial phenomena such as health-related phenomena, many would consider an R-squared of 0.20 as acceptable. Still, such an R-squared would mean that 80 percent of the variance for a particularly variable is unexplained by the data.
- The P values have been calculated using a nonparametric technique, a form of resampling called jackknifing, which does not require the assumption that the data is normally distributed to be met. This and other related techniques also tend to yield more reliable results for small samples, and samples with outliers (as long as the outliers are “good” data, and are not the result of measurement error).
- Only two data points per county were used (for males and females). This increased the sample size of the dataset without artificially reducing variance, which is desirable since the dataset is relatively small. This also allowed for the test of commonsense assumptions (e.g., the protective effects of being female), which is always a good idea in a complex analysis because violation of commonsense assumptions may suggest data collection or analysis error. On the other hand, it required the inclusion of a sex variable as a control variable in the analysis, which is no big deal.
- Since all the data was collected around the same time (late 1980s), this analysis assumes a somewhat static pattern of consumption of rice and wheat flour. In other words, let us assume that variations in consumption of a particular food do lead to variations in mortality. Still, that effect will typically take years to manifest itself. This is a major limitation of this dataset and any related analyses.
- Mortality from schistosomiasis infection (MSCHIST) does not confound the results presented here. Only counties where no deaths from schistosomiasis infection were reported have been included in this analysis. Mortality from all cardiovascular diseases (MVASC) was measured using the variable M059 ALLVASCc (ages 35-69). See this post for other notes that apply here as well.
This post focuses on the intake of two main plant foods, namely wheat flour and rice intake, and their relationships with mortality from all cardiovascular diseases. After many exploratory multivariate analyses, wheat flour and rice emerged as the plant foods with the strongest associations with mortality from all cardiovascular diseases. Moreover, wheat flour and rice have a strong and inverse relationship with each other, which suggests a “consumption divide”. Since the data is from China in the late 1980s, it is likely that consumption of wheat flour is even higher now. As you’ll see, this picture is alarming.
The main model and results
All of the results reported here are from analyses conducted using WarpPLS. Below is the model with the main results of the analyses. (Click on it to enlarge. Use the "CRTL" and "+" keys to zoom in, and CRTL" and "-" to zoom out.) The arrows explore associations between variables, which are shown within ovals. The meaning of each variable is the following: SexM1F2 = sex, with 1 assigned to males and 2 to females; MVASC = mortality from all cardiovascular diseases (ages 35-69); TKCAL = total calorie intake per day; WHTFLOUR = wheat flour intake (g/day); and RICE = and rice intake (g/day).
The variables to the left of MVASC are the main predictors of interest in the model. The one to the right is a control variable – SexM1F2. The path coefficients (indicated as beta coefficients) reflect the strength of the relationships. A negative beta means that the relationship is negative; i.e., an increase in a variable is associated with a decrease in the variable that it points to. The P values indicate the statistical significance of the relationship; a P lower than 0.05 generally means a significant relationship (95 percent or higher likelihood that the relationship is “real”).
In summary, the model above seems to be telling us that:
- As rice intake increases, wheat flour intake decreases significantly (beta=-0.84; P<0.01). This relationship would be the same if the arrow pointed in the opposite direction. It suggests that there is a sharp divide between rice-consuming and wheat flour-consuming regions.
- As wheat flour intake increases, mortality from all cardiovascular diseases increases significantly (beta=0.32; P<0.01). This is after controlling for the effects of rice and total calorie intake. That is, wheat flour seems to have some inherent properties that make it bad for one’s health, even if one doesn’t consume that many calories.
- As rice intake increases, mortality from all cardiovascular diseases decreases significantly (beta=-0.24; P<0.01). This is after controlling for the effects of wheat flour and total calorie intake. That is, this effect is not entirely due to rice being consumed in place of wheat flour. Still, as you’ll see later in this post, this relationship is nonlinear. Excessive rice intake does not seem to be very good for one’s health either.
- Increases in wheat flour and rice intake are significantly associated with increases in total calorie intake (betas=0.25, 0.33; P<0.01). This may be due to wheat flour and rice intake: (a) being themselves, in terms of their own caloric content, main contributors to the total calorie intake; or (b) causing an increase in calorie intake from other sources. The former is more likely, given the effect below.
- The effect of total calorie intake on mortality from all cardiovascular diseases is insignificant when we control for the effects of rice and wheat flour intakes (beta=0.08; P=0.35). This suggests that neither wheat flour nor rice exerts an effect on mortality from all cardiovascular diseases by increasing total calorie intake from other food sources.
- Being female is significantly associated with a reduction in mortality from all cardiovascular diseases (beta=-0.24; P=0.01). This is to be expected. In other words, men are women with a few design flaws, so to speak. (This situation reverses itself a bit after menopause.)
Wheat flour displaces rice
The graph below shows the shape of the association between wheat flour intake (WHTFLOUR) and rice intake (RICE). The values are provided in standardized format; e.g., 0 is the mean (a.k.a. average), 1 is one standard deviation above the mean, and so on. The curve is the best-fitting U curve obtained by the software. It actually has the shape of an exponential decay curve, which can be seen as a section of a U curve. This suggests that wheat flour consumption has strongly displaced rice consumption in several regions in China, and also that wherever rice consumption is high wheat flour consumption tends to be low.
As wheat flour intake goes up, so does cardiovascular disease mortality
The graphs below show the shapes of the association between wheat flour intake (WHTFLOUR) and mortality from all cardiovascular diseases (MVASC). In the first graph, the values are provided in standardized format; e.g., 0 is the mean (or average), 1 is one standard deviation above the mean, and so on. In the second graph, the values are provided in unstandardized format and organized in terciles (each of three equal intervals).
The curve in the first graph is the best-fitting U curve obtained by the software. It is a quasi-linear relationship. The higher the consumption of wheat flour in a county, the higher seems to be the mortality from all cardiovascular diseases. The second graph suggests that mortality in the third tercile, which represents a consumption of wheat flour of 501 to 751 g/day (a lot!), is 69 percent higher than mortality in the first tercile (0 to 251 g/day).
Rice seems to be protective, as long as intake is not too high
The graphs below show the shapes of the association between rice intake (RICE) and mortality from all cardiovascular diseases (MVASC). In the first graph, the values are provided in standardized format. In the second graph, the values are provided in unstandardized format and organized in terciles.
Here the relationship is more complex. The lowest mortality is clearly in the second tercile (206 to 412 g/day). There is a lot of variation in the first tercile, as suggested by the first graph with the U curve. (Remember, as rice intake goes down, wheat flour intake tends to go up.) The U curve here looks similar to the exponential decay curve shown earlier in the post, for the relationship between rice and wheat flour intake.
In fact, the shape of the association between rice intake and mortality from all cardiovascular diseases looks a bit like an “echo” of the shape of the relationship between rice and wheat flour intake. Here is what is creepy. This echo looks somewhat like the first curve (between rice and wheat flour intake), but with wheat flour intake replaced by “death” (i.e., mortality from all cardiovascular diseases).
What does this all mean?
- Wheat flour displacing rice does not look like a good thing. Wheat flour intake seems to have strongly displaced rice intake in the counties where it is heavily consumed. Generally speaking, that does not seem to have been a good thing. It looks like this is generally associated with increased mortality from all cardiovascular diseases.
- High glycemic index food consumption does not seem to be the problem here. Wheat flour and rice have very similar glycemic indices (but generally not glycemic loads; see below). Both lead to blood glucose and insulin spikes. Yet, rice consumption seems protective when it is not excessive. This is true in part (but not entirely) because it largely displaces wheat flour. Moreover, neither rice nor wheat flour consumption seems to be significantly associated with cardiovascular disease via an increase in total calorie consumption. This is a bit of a blow to the theory that high glycemic carbohydrates necessarily cause obesity, diabetes, and eventually cardiovascular disease.
- The problem with wheat flour is … hard to pinpoint, based on the results summarized here. Maybe it is the fact that it is an ultra-refined carbohydrate-rich food; less refined forms of wheat could be healthier. In fact, the glycemic loads of less refined carbohydrate-rich foods tend to be much lower than those of more refined ones. (Also, boiled brown rice has a glycemic load that is about three times lower than that of whole wheat bread; whereas the glycemic indices are about the same.) Maybe the problem is wheat flour's gluten content. Maybe it is a combination of various factors, including these.
Reference
Kock, N. (2010). WarpPLS 1.0 User Manual. Laredo, Texas: ScriptWarp Systems.
Acknowledgment and notes
- Many thanks are due to Dr. Campbell and his collaborators for collecting and compiling the data used in this analysis. The data is from this site, created by those researchers to disseminate their work in connection with a study often referred to as the “China Study II”. It has already been analyzed by other bloggers. Notable analyses have been conducted by Ricardo at Canibais e Reis, Stan at Heretic, and Denise at Raw Food SOS.
- The path coefficients (indicated as beta coefficients) reflect the strength of the relationships; they are a bit like standard univariate (or Pearson) correlation coefficients, except that they take into consideration multivariate relationships (they control for competing effects on each variable). Whenever nonlinear relationships were modeled, the path coefficients were automatically corrected by the software to account for nonlinearity.
- The software used here identifies non-cyclical and mono-cyclical relationships such as logarithmic, exponential, and hyperbolic decay relationships. Once a relationship is identified, data values are corrected and coefficients calculated. This is not the same as log-transforming data prior to analysis, which is widely used but only works if the underlying relationship is logarithmic. Otherwise, log-transforming data may distort the relationship even more than assuming that it is linear, which is what is done by most statistical software tools.
- The R-squared values reflect the percentage of explained variance for certain variables; the higher they are, the better the model fit with the data. In complex and multi-factorial phenomena such as health-related phenomena, many would consider an R-squared of 0.20 as acceptable. Still, such an R-squared would mean that 80 percent of the variance for a particularly variable is unexplained by the data.
- The P values have been calculated using a nonparametric technique, a form of resampling called jackknifing, which does not require the assumption that the data is normally distributed to be met. This and other related techniques also tend to yield more reliable results for small samples, and samples with outliers (as long as the outliers are “good” data, and are not the result of measurement error).
- Only two data points per county were used (for males and females). This increased the sample size of the dataset without artificially reducing variance, which is desirable since the dataset is relatively small. This also allowed for the test of commonsense assumptions (e.g., the protective effects of being female), which is always a good idea in a complex analysis because violation of commonsense assumptions may suggest data collection or analysis error. On the other hand, it required the inclusion of a sex variable as a control variable in the analysis, which is no big deal.
- Since all the data was collected around the same time (late 1980s), this analysis assumes a somewhat static pattern of consumption of rice and wheat flour. In other words, let us assume that variations in consumption of a particular food do lead to variations in mortality. Still, that effect will typically take years to manifest itself. This is a major limitation of this dataset and any related analyses.
- Mortality from schistosomiasis infection (MSCHIST) does not confound the results presented here. Only counties where no deaths from schistosomiasis infection were reported have been included in this analysis. Mortality from all cardiovascular diseases (MVASC) was measured using the variable M059 ALLVASCc (ages 35-69). See this post for other notes that apply here as well.
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