Preserving a Family

Adoption Ministry 1:27 was established to partner with the church in Ethiopia to meet the needs of the most vulnerable widows, orphans and families, with the ultimate goal of orphan prevention and family preservation.

International adoption is not the answer to this crisis in Ethiopia.  With the monthly support of ministry partners and by linking arms with the body of Christ in Ethiopia, we strive to help prevent the collapse of vulnerable families.

On this blog in the coming months, we will be highlighting families who are waiting to be ‘adopted’ for $40 per month, which will help to provide the basic needs of food, medicine, shelter and clothing.

Meet Bethlehem**

Family K-0037

Bethlehem (pictured above in the orange scarf) is a young woman in a desperate spot.  She is a full-time care-giver for her mother who is a leper and has lost her arms and legs to that terrible disease.  Little Ephrata is her 3-year-old daughter who she loves so much.  Securing food for three people is a daily struggle for this young mother living in the community at the city dump in Addis Ababa.  Helping this family monthly will provide for their basic food needs and Bethlehem will give praise to God for you and your kind generosity!

**Bethlehem and her daughter have been adopted!  But there are many more families like hers who are waiting...  For $40 per month, you can adopt this family or another one like hers in our Adoption Ministry 1:27 program.  Please contact us at:


Just Pinning It

Not quite sure if I'll turn this into a weekly thing but I was Pinning(v.)  today. I've actually not been on Pinterest in over a week. Not sure if you believe me or not but there were actually no withdrawal symptoms. I'm shocked, too.

So, here are a few of my most recent pins.
Click to see all of my Classroom Pins
1. Remind 101
Send a mass text or email to parents without divulging your phone number.
"Pajama Day tomorrow"
"Permission Slips Due"
"Field Trip Thursday!"

2. Daily 5 Rotation Cards

3. BookRetriever
(I haven't downloaded this  yet, but I plan on it. I just really like that I can add levels and print labels)
iPhone Screenshot 1

This is the Classroom Library Company's accompanying app for managing book borrowing between teachers, parents, and 


It allows you to scan, level, and inventory your entire Classroom Library as well. There's even a handy label printing function that allows you to print through a wireless connection! We have over 178,000 titles loaded with as much reading level information as we can find. We're constantly updating Guided Reading Levels, Lexile, Accelerated Reader, Reading Counts, DRA, and Reading Recovery and we are adding more every day

4. Dollar Store Photo Album
I'm going to put flashcards into a cheap photo album....POOF...instant dry erase flashcards

5. Spiral Bind books

What was your favorite pin this week?

Pinned Image

Awesome Give Away from fellow bloggerS

Head on over to Life in First Grade

Life in First Grade

Ms. Leslie Ann is giving away a HearALL Assessment Recorder from Learning Resources 
"It's seriously the neatest thing, y'all. You simply place it wherever you want to recorder and hit the red button. That's it! It records what the kids are saying so you can hear for yourself. To hear what was recorded, just plug it into your computer and click on the file. It has five speakers, so it really picks up the kids voices and allows you to hear exactly what is recorded. And the best part? NO BATTERIES. That's a huge plus in my book. "

So, check out her blog to learn how to enter! I'm not sure about you but I have a ton of ideas of what I could do with this nifty gadget. 


I was flipping through FlipBoard  and saw that another fabu (faboo?) (I dunno, you get it though) blogger is celebrating her 500 Followers with an awesome give away sponsored by other awesome bloggers. You know what that means, right?  Teacher jackpot in give-aways.
My Photo
Here's hoping I have some Rafflecopter luck!

Check them BOTH out.Awesome sauce!

Will The Polypill Prevent Your Heart Attack?

Giving the polypill to everybody above the age of 55 kills two birds with one stone: cardiovascular risk and preventive medicine. That's what the proponents of the polypill say. The medical establishment is in uproar. Here is why you should be, too. But for a different reason. [tweet this].
We are typically sold on the notion, that heart disease and stroke have become today's major killer, for one simple reason: We live far longer than our ancestors of a hundred years ago, whose major cause of death were infectious diseases. Their eradication has brought upon us the blessings of longer lives, and with it the detriments of aging related cardiovascular disease. It's root cause is elevated cholesterol, a theory enshrined in the so-called lipid hypothesis. Questioning it is to the medical establishment what Galileo's theories were to the catholic church: plain heresy. After all, cholesterol lowering drugs, the statins, are a blessing to mankind and substantial reducer of cardiovascular death. 
This is what nearly everyone believes.
The Chinese Tao has a quote for such situations. It goes something like this: "when everyone knows something is good, this is bad already." You might reject my suggestion that such ancient wisdom could possibly apply to modern medicine.  So, let's get cracking at those facts which everyone knows. 

Claim 1: Heart disease, stroke and cancer are today's major killers 
Undeniably.  Cardiovascular disease accounts for roughly one in three deaths (30%), followed by cancer, which kills another one in four (23%) [1]. Which means your chance of dying of any one of those two clusters is fifty-fifty. By the way, these data, and the ones which follow, are drawn from U.S. statistics. Unfortunately they are typical for the rest of the developed world and pretty close to what the developing nations experience, too. 

Claim 2: One hundred years ago, Infectious diseases were the main killers
Yes, indeed. In 1900, one third of all deaths were due to tuberculosis and influenza alone. 

Claim 3: Since we eliminated those infectious diseases we have a longer life expectancy and therefore we simply die of aging related diseases.
This is where it starts to get hairy. First, you must NOT confuse life expectancy with life span. Life expectancy is typically quoted as life expectancy at birth. It is an average value of all the years lived divided by the number of those born alive. You can imagine how this number is very sensitive to the rate of infant deaths and of deaths during the early adult years. Particularly when one third of all newborns die within the first 12 months. Which was a typical infant death rate, not only in ancient Rome but throughout most of modern history until the 17th century. While this infant mortality rate made Roman's have an average life expectancy at birth of a little less than 30 years, a considerable part of the population lived to their sixties and seventies. In fact, very few people will have died at age 30, most either having done so way earlier or much later. Back to 1900. 

In 1900, U.S. females had a life expectancy at birth of 51 years, whereas those who reached 50 had a remaining life expectancy of another 22 years, to reach 72. Today these numbers stand at 80 years life expectancy at birth and 82 years at the age of 50. Which means two things: First, while life expectancy at birth has increased dramatically by more than 30 years over the past 100 years, life span hasn't increased that much. Second, life expectancies at birth and at age 50 have become virtually the same. The reason is a substantial reduction in infectious diseases, which killed considerable numbers of infants, of women giving birth, and of young adults. Which brings us to ...

Claim 4: Cardiovascular disease and cancer are diseases of old age, which is why they are more prominent today than 100 years ago. 
When we compare today's death rates with those of the past, we need to keep in mind that the age distribution in 1900 was substantially different to what it is today. In 1900 there were a lot less people of age 65 and older than there are today. So, we need to answer the question, what would the CVD mortality have been in 1900 if the population had had the same age distribution as ours has today. Thankfully, the U.S. CDC provides us with a standardization tool, which allows us to answer this question. They simply use the U.S. population at the year 2000 as the standard to which all other population data can be standardized. The process is called "adjustment for age" and, when applied to mortality rates, they become truly comparable as  so-called age-adjusted mortality rates. So, in the future, when you read something about mortality rates or disease rates, make sure to check which rates he uses for comparison. If he doesn't say which is which, you need to be very skeptical about his interpretation. 

Now here comes the surprise: The mortality rate for cardiovascular disease in 1900 was 22% vs. today's 31%. At first blush, this doesn't sound that much different. But think about it: If CVD is merely the disease of old age, why should there be a difference at all? And if there is a difference, why should we be dying of this disease at a 50% higher rate when we have all the medical technology, and the statins, which our grand parents didn't have.  

The entire issue becomes even weirder when you look at the development of the CVD mortality rate over the 11 decades from 1900 to today (Figure 1). CVD rose to a 60% prominence in 1960 before steeply falling to today's level. You can see that in the 1950s and 1960s people died of "age-related" heart attacks and strokes at a 50% higher rate than 50 years earlier. Another 60 years later we die at a quarter the rate of the 1960s. Which begs the question: What happened?
Figure 1

Actually, there are two parts to this question: If heart disease is age-related, why was there such a dramatic rise in age-adjusted mortality over the first half of the past century, when there should have been none. I have my theories, but I will keep them for one of my next posts.

Far more pertinent to this post's subject is the second part of the question: What did happen in the 1960s and thereafter? If you think the answer is "statins happened, stupid", then you are in for a surprise. The first statin to hit the market was Merck's Lovastatin. In 1987! Its the red vertical line in the chart of figure 1. Almost 30 years after CVD mortality rate began its steep descent. A descent, which did not accelerate with the introduction of statins to the market.  

Now, don't get me wrong, I'm not saying statins do not reduce the risk of dying from CVD, or the risk of experiencing a non-fatal heart attack or stroke. There is quite some evidence to their benefits. My point is that, whatever statins do, they do not show up on our mortality radar as the grand reducer of CVD death. Not within the current medical practice of risk estimation and subsequent risk-based treatment. 

Enter the proponents of the polypill, which contains a statin, a blood pressure lowering medication, and an aspirin. Are these proponents right to say, give a statin to everyone, who has hit the age of 55? Well, they have a point. Wald and colleagues ran a computer simulation to compare the most simple of all screenings, age, vs. the UK's National Institute of Health guidelines, which recommend screening everybody from age 40 at five-yearly intervals until people reach the risk threshold of a 20% chance of a cardiovascular event in the next 10 years [2]. That's the cut-off for treatment. Astonishingly, the benefits are virtually the same. What this screening routine buys at the costs for doctor visits and blood tests, we get free of charge with the age threshold.  

This paper was so counterintuitive to the established way of medical thinking, that the authors' paper, first submitted to the British Medical Journal in 2009, went through a 2-years Odyssey of being rejected by 4 Journals and 24 reviewers, before finally being published in PLoS One in 2011. 

But costs from a societal perspective are not the costs which interest you. You might be more interested to know, that even at an elevated risk of CVD, 25 people would have to swallow a statin for 5 years to prevent just 1 heart attack. How much larger will this number be, the number needed to treat (NNT), as we call it, if you are simply 55 but with no other CVD risk factor? You won't get an answer anytime soon. Big Pharma is not interested to finance a study, which could deliver the answer. They don't earn much money from polypills which only use generic statins, those whose patent protection has expired. 

To me the NNT is definitely too high. I won't take the polypill, though I just crossed that age threshold a few days back. I pursue another path to health and longevity. And I believe, you might want to look at my reasoning for that path. I will introduce it progressively over the next few posts. Not that I evangelize it, not to worry. I simply believe there is a third alternative to the risk-oriented practice of preventive medicine and to the kitchen-sink approach of its polypill wielding opponents. This third alternative is heresy to both. But with heresy I'm in good company. Dr. Ignaz Semmelweis was a heretic when he suggested in the mid 1800s that the high rate of deadly childbed fever was due to physicians not washing their hands between dissecting dead bodies and helping women deliver their children. It took about 50 years for his ideas to become medical mainstream. 

That's because new ideas become accepted in medicine not upon proof of being better than the old ones, but upon the old professors, who have built their careers on the old ideas, dying out. So, let's try to survive them. 

1. Kochanek, K.D., et al., Deaths: Preliminary Data for 2009, in National Vital Statistics Reports 2011, U.S. Department of Health And Human Services.

2. Wald, N.J., M. Simmonds, and J.K. Morris, Screening for future cardiovascular disease using age alone compared with multiple risk factors and age. PLoS ONE, 2011. 6(5): p. e18742.

Wald NJ, Simmonds M, & Morris JK (2011). Screening for future cardiovascular disease using age alone compared with multiple risk factors and age. PloS one, 6 (5) PMID: 21573224

Making Adoption Affordable - What YOU can do!

H.R. 4373, the Making Adoption Affordable Act, is a bipartisan bill that would extend the current Adoption Tax Credit that is set to expire at the end of this year.  

From the executive director of Show Hope on their blog:

All over the world, including here in the United States, millions of orphans are waiting, longing for a forever family to take them home. However, adoption can cost between $10,000, and $45,000, and many families with room in their hearts and homes are unable to overcome the financial barriers. Show Hope recognizes this need to help defray the expenses of adoption and get children into forever families. The United States Adoption Tax Credit currently provides up $12,650 to adoptive families. However, the Adoption Tax Credit is set to expire at the end of 2012. If Congress does not act, the size and applicability of this tax credit will shrink dramatically.
If the adoption tax credit helped you or someone you know to adopt a child, or if it could help you in the future to adopt a child, please call your House Representative todayand urge that he or she cosponsor the bipartisan bill H.R. 4373, the Making Adoption Affordable Act. You can reach your Representative by calling the U.S. Capitol Operator at 202-225-3121 and asking for your Representative’s office. If you don’t know your Representative’s name, click here and enter your zip code in the box provided.
As you call your Representative, consider sharing these messages:
• I am a constituent in your district and the adoption tax credit is important to me because…
• I urge the Representative to become a co-sponsor of The Making Adoption Affordable Act, H.R. 4373.
• If Congress does not act – the credit as we now know it – will expire in December 2012.
• H.R. 4373 is bipartisan and it supports all types of adoptions (domestic private, foster care, and international adoptions).
• This tax credit has made adoption a more viable option for many parents who might not otherwise have been able to afford adoption, allowing them to provide children with loving, permanent families.
• Thank you for your support of H.R. 4373.
If you want to learn more about the adoption tax credit go to
And “like” the Save the Adoption Tax Credit Facebook page
Thank you for taking a few minutes to make this important phone call!

Many thanks to our friends at Show Hope and to all of you who will take action today!

Why Risk Screening For Heart Disease Is As Good As Crystal Ball Gazing

If weather forecasts were as reliable as cardiovascular risk prediction tools, meteorologists would miss two thirds of all hurricanes, expect rain for 8 out of 10 sunny days, and fail to see the parallels to fortune telling.    

When you are older than 35 and visit your doctor, there is a good chance he will evaluate your risk of suffering a heart attack or stroke over the next 10 years. The motivation behind this risk scoring is to prevent such an event while you still can. After all, these cardiovascular diseases are the number one causes of disability and death. In Europe alone 1.8 Million people die from it every year. In fact, they die prematurely, which means at an age younger than 75. [tweet this].

That's why, at first blush, it sounds reasonable to develop risk prediction scores to help doctors identify the high-risk patient whose asymptomatic state makes him blissfully unaware of being a walking time bomb. Forewarned is forearmed, or something like that the reasoning goes. But what if the forewarning part is as reliable as a six weeks weather forecast and the forearming as effective as the wish for world peace?

As with any medical technology, risk prediction tools should be judged by their ability to improve YOUR health outcome before they are used on YOU. While the latest publication about the UK QRISK score is an upbeat evaluation of its improved performance, it fails to convince me that using these tools actually makes sense [1]. 

Let's look at the data first: 
The QRISK score was developed for the UK population, because the grand dame of risk prediction scores, the Framingham Risk Score (FRS), doesn't do so hot in northern European people. FRS was seen to over-predict the risk in the UK population by up to 50%. In an effort to do better than that, QRISK was developed. It packs a lot more variables into its score than FRS. In its latest version, QRISK includes the risk factors age, smoking status (with a 5-level differentiation), ethnicity, blood pressure, cholesterol, BMI, family history, socioeconomic status, and various disease diagnoses. An algorithm calculates your risk, expressed as a %-chance to suffer a heart attack or stroke over the next 10 years. 

In clinical practice a 20% risk is defined as the critical threshold that separates the high-risk person from those in the low-to-moderate risk categories. 20% is an entirely arbitrary number, selected simply for convenience's sake and economic reasons. Set it too high, and you identify too few at-risk people, set it too low and you have to deal with too many false positives, that is, people who you would treat for elevated risk but who will not suffer an event even if you didn't treat them. The latter is clearly a strain on limited health budgets.

Now, let's see how QRISK at a threshold of 20% risk would work for you, provided you are between 30 and 84 years old, which is the age range to which QRISK is applicable. Let's also assume you are female.  

For every 1000 women, 40 will suffer a first heart attack or stroke over the next 10 years. Of these 40 obviously high-risk, women, QRISK identifies 17 correctly. Which means the remaining 23, or 60% of all those who will suffer a heart attack or stroke, fly below the QRISK radar. But that's not the intriguing part. We get to that by looking at the group of women who are identified as high-risk. 
If the 20% risk score threshold predicts correctly, then about 20 of every 100 women identified as high-risk will suffer a first event over the next 10 years. After all, that's what a 20% risk means: Of a hundred women having the same profile, 20 will eventually suffer a first heart attack or stroke over the next 10 years. Which brings us to the really juicy part: In the population from which QRISK was developed, 16% of the high-risk women actually did suffer that predicted heart attack or stroke. 

You are forgiven if you don't immediately see, why I call this the juicy part. But think about it this way: The QRISK numbers were not plugged from an observational study, which simply observes and follows women for 10 years, without doing anything to or with them. These numbers represent women who were identified to be at high risk by the very health care system, which claims to do the risk scoring to protect them from such events in the first place. So, what happened to actually preventing those events? 16% vs. 20% doesn't sound like a terrific preventive job. 

By the way, for men the figures are very much the same. The reason why I chose women is because there is an inconsistency in the study's published tables which compare the events in two age groups - the 35-74 year old men, and the 30-80 year old men. The number of heart attacks and strokes is given as 54 and 50 for the first and second group respectively. But it can't be that there are less events in the 30-80 year range than in the 35-74 year range. Since there is no such detectable inconsistency in the numbers for women, I chose them as the example.  

Back to the risk score and a summary of its performance. First, the score misses 60% of all cases right off the bat. Second, among the correctly identified future sufferers of heart attacks and strokes, the subsequent treatment only prevents a small minority of events, which amounts to about 4% of all cases happening over the 10-year period.  If our preventive interventions were worth their salt, we should see no, or only a few, cases happening in the high-risk group. Because this is the group, which is supposed to benefit from intensive treatment and intervention. 

This public health strategy of targeting the high-risk part of the population with an intervention is appropriately called the high-risk strategy. As we have seen, it makes public health miss the majority of disease events, which it set out to prevent in the first place. So what is the alternative? It's called the population strategy. And, yes, it means targeting the entire population in an effort to reduce all people's exposure to whatever are the causes of the disease. That entails necessarily a one-size-fits-all approach to health. Which you encounter in the form of those exercise and diet recommendations preached to us from every public health pulpit. 

In theory, this strategy could potentially have a large effect on the health of the entire population, materializing as a substantial reduction in the number of heart attacks and strokes. But when you look at it from YOUR point of view, you have to invest the sizeable effort of changing your eating and exercising habits, while you'll find the benefits hardly perceivable. After all, health is when you don't feel it. A prevented disease is never perceived as such. In public health, this situation, where an individual's large perceived sacrifice yields only an imperceptibly small personal benefit, is called the prevention paradox. It's a more academic way of saying it doesn't work either.
The data are certainly there to prove my case. In my previous post I highlighted how little change in health behaviors has happened over the past 20 years. And the little change, that did happen, went mostly into the wrong direction. 

Which is why we will continue to see most of us dying, ironically, from preventable diseases: heart disease, stroke, diabetes, many cancers. Which is why I'm questioning the current clinical practice of risk scoring. After all, it costs money and time.

It's this question which has lead some researchers to suggest giving everybody above the age of 50 a so-called polypill. A pill which reduces blood pressure and cholesterol, and which delivers a low dose of aspirin. It aims at killing three birds with one stone: hypertension, hypercholesterolemia and thrombotic events, all of which are causally related to heart attack and stroke. But to me, the polypill is preventive medicine's declaration of bankruptcy.

In my next post, I will talk about this, about how preventive medicine may really work, and, most importantly, what it means to you. Practically and presently. Because we already have the tools to help you prevent your heart attack or stroke. And those tools don't go by the name of any known risk score. if you are still keen on scoring your risk, we have a tool on our website for you to do that. It also shows you, how your risk would be if all risk factors were in the green zone, or how your risk will be if you maintain your current status over the next ten years. You can play around with it here, and make a couple of other tests, too. But don't get fooled by numbers. Your greatest risk is to take those risk scores too seriously. 


1. Collins, G.S. and D.G. Altman, Predicting the 10 year risk of cardiovascular disease in the United Kingdom: independent and external validation of an updated version of QRISK2. BMJ, 2012. 344.

Collins GS, & Altman DG (2012). Predicting the 10 year risk of cardiovascular disease in the United Kingdom: independent and external validation of an updated version of QRISK2. BMJ (Clinical research ed.), 344 PMID: 22723603

Tucker Signing Strategies

The former Special Ed teacher at my school, Mrs. H,  has many years of experience and a special way of reaching the kids. I'm always amazed and excited to see the growth in the kiddos that she sees. One of the things that she uses is called Tucker Signing Strategies. She teaches these hand cues to the kids to remember the sounds that the letters make.

Now, I'll be honest I do not know all of the signs and I do not teach all of  the signs to my kiddos. I know that in order for it to be effective I should implement the strategies with fidelity. I wasn't trained on it and I was just talking with Mrs. H about them one day. I asked her to show me the signs for the vowels. For many of my kids short o and u are so difficult to remember and differentiate from other sounds. It was so neat to see when they were sounding out a letter and I knew they were confused and I would show them a sign with my hands and they'd remember. Do any of you use them?

(I found this on Pinterest. The teacher goes through the alphabet but there are also signs for digraphs, r-controlled vowels, etc.)

Take-Home Books for Tucker Signing Strategies for Reading 
Click to go to Amazon and see the book.

Making Smiles

Alexander fam

Moody and Emily Alexander adopted a beautiful little girl from one of YWAM’s orphanages in Ethiopia in 2011, which was our introduction to this amazing couple and their ministry in Ethiopia.  Moody and Emily had already adopted two boys from Ethiopia before they brought Gigi home. 

Dr. Alexander is an orthodontist in Texas who regularly takes teams of dental professionals and volunteers to serve the essentially unmet needs of widows, families and children in several communities in and around the capital city of Addis Ababa.  You can read more about these very dedicated servants of Christ on the website:  EthiopiaSmile 

Adoption Ministry has had the privilege of partnering with the Alexanders and their ‘Smile’ teams to serve both the widows in our Widows & Orphans Home community outreach and also some of the families in our Adoption Ministry 1:27 program.  (You can read about the October 2011 team on our blog here.)  Just this last week, a 54-member EthiopiaSmile team conducted dental clinics for the AM 1:27 families from the Meseret Christos and Bole Bulbula churches in Addis.  Several widows even received eye exams from an eye doctor present on the team and were given free eye glasses. 

We are so grateful to the Alexanders and their giant hearts of compassion!  Love in action = Ethiopia Smiles!

Be sure to read Emily’s blog soli deo gloria to read in more detail about their latest team and see some great video of their time in the village of Dube Bute.

Let's Make a Deal...

I'm still new to all of this. I have a few people that have commented (thanks btw) and told me that they're following me. I appreciate that so much. To the right I've added the "Google Friend Connect". I didn't really understand it at first but I followed my first blog on it today and it automatically put it in my Google Reader. Before I manually went to Google Reader to add. So nifty!


If you have a blog and would like a copy of my Classroom Management packet for *FREE* please comment, follow, and let me know. I'll email you a copy. If you like it or think others would like it please give me a shout out on your blog. (If there is something else in my TpT store that you'd rather have let me know)

So if you're interested comment and leave your email and a blog link and I'll email it (or whatever you choose from my store) asap. 

DEAL IS GOOD UP TO MY 20th Follower!

Are You A Unique Medical Case?

Research says yes, public health doesn't listen, and you suffer the consequences: too little benefits from generic interventions. And it could be so simple.

Different people always react differently to the same type of treatment. In my previous post I showed you the wide range of blood pressure changes in over 700 participants of the HERITAGE study's 20-weeks endurance exercise program (Figure 1). Unfortunately, most studies do not present their results in a way, which would allow us to construct such charts as in figure 1. But when they do, the charts look virtually the same. Figure 2 shows you how 30 obese men changed their bodyweight and fat weight as a consequence of a 12-weeks supervised exercise program [1]. As you can see, the mean change of 3.7 kg for both values (the horizontal red line) doesn't tell you anything about how these 30 men reacted INDIVIDUALLY to the program.

Figure 1

When your doctor tells you what exercise to do, what diet to follow or what drug to take, she refers to studies, which report their outcomes in terms of mean values for groups of participants. But as you know now, these values don't answer your question: What would my outcome have been, had I participated in this study? Which is the same as asking, what your results will be if you follow your doctor's advice. 

Figure 2

The honest answer is: nobody knows.  Augmented by: in all likelihood you will see some benefit; if you are very lucky you'll see an extremely large benefit. Or you might be unlucky and see no benefit at all. Call this the uncertainty principle of medicine. 

You won't hear your doctor talking about it. Particularly not when he recommends lifestyle change as your first line of defense against heart attack, stroke or diabetes. For two reasons: First, public health is not concerned with your point of view. I'll get to this in a moment. Second, doctors know that lifestyle change is hard to sell as it is. So, why make it even harder by telling you the truth about the uncertainty of  benefits. Think about it, we all like to enjoy now and pay later, if at all. That's certainly the case when it comes to cigarettes, salt, sugar and a sedentary lifestyle. To forgo these pleasures in favor of health benefits, which may or may not materialize decades from now, is simply not how we are wired. 

But public health does not seem to get it. Even the American Heart Association's (AHA) latest invention, the seven health metrics, is nothing but the same song and dance, which has not had any impact on the health of the population. Let's look at it in a little more detail: 
The AHA has defined 7 metrics to help you navigate your way to chronic health. 4 of those metrics are behavioral - smoking, physical activity, BMI and diet. The remaining 3 are biomarkers: blood pressure, fasting glucose and total cholesterol. 

Have all 7 in the green zone and you should do well with health. Exactly how well, that was the question Dr. Yang and colleagues had asked in a study which investigated (a) how many U.S. residents meet how many of those metrics and (b) how much of the U.S. population's death burden can be attributed to these risk factors [2]. Fast forward to the results. More than half of the population, 52.2%, meet only 3 or less of those 7 metrics. That's a 4 % increase compared to 20 years ago. Another 25% meet just 4 metrics. At the same time the percentage of people who meet at least 6 of the 7 metrics has gone down from 10.3% to 8.7%. The percentage of obese people has increased by 50%, and the rate of physical inactivity (that is, people who do not exercise at all!) has doubled from 15.6% to 31.9%. Compared with people who meet no more than 1 metric, those who meet at least 6 reduce their risk of dying by 50%. 

When you look at these correlations, you'll certainly agree with the researchers' statement that "the presence of a greater number of cardiovascular health metrics was associated with a graded and significantly lower risk of total and CVD mortality". That's nice to know, but you are probably not so much interested in the number of deaths in the population, which are attributable to whatever health metric score is the flavor of the day. You are interested to know the answer to three questions:  (a) what does it mean to you, if you don't meet those metrics, (b) how does your effort of getting these metrics into the green zone reduce your risk, and (c) which strategy should you use to lower your risk most effectively.

Fortunately, with a little bit of digging into published numbers, we can get fairly good answers to these questions. So, let's start with the first one: 
Dong and colleagues had done a fairly similar investigation asking how the number of AHA health metrics correlated with cardiovascular events (heart attack and stroke) in the Northern Manhattan Study Cohort [3]. The study's almost 3000 persons were on average 69 years old when they entered the study, and they were followed up for 11 years. Of those who had met at least 4 health metrics, 28% suffered a cardiovascular event during that time, vs. 32% of those who only met 3 or less metrics. 
That's a 4% improvement. 

I don't know, how you feel about it, but my experience with our health lab's clients is that a 4% risk reduction doesn't make them go nuts about exercise and health food. I sympathize, because life is not all about self-flagellation with veggie burgers, tofu swill and weekly marathons. Which is why it is justified to go for the biggest possible health benefit that is achievable with the smallest possible effort. The answer hinges around the question of what is the most critical health metric. Back to Yang's investigation. 

He had asked the question, which of the seven metrics, if met, would yield the largest reduction in deaths? 
If your bet was on smoking and obesity, you might be surprised to hear that blood pressure turned out to be a far more effective executioner, being responsible for 30% of the deaths in this cohort. With 24%, smoking took 2nd place, and obesity didn't show up as a killer at all. Which does not mean obesity doesn't cause death. You have to keep in mind that the average age of the Yang study cohort was 45 years, and the median observation period was 14 years.  

Again, what does all that mean for you? Principally you decide for yourself. I can only tell you what I practice with our clients in our health lab. For each case we define a benchmark biomarker depending on the individual's health profile. In many cases that's blood pressure or, better still, a biomarker of arterial function (I'll talk about the amazing role of arterial function in one of my next posts). We then agree on a certain exercise and dietary strategy, the effect of which we carefully measure in terms of change of the chosen biomarker. If that change does happen, and if it goes into the right direction, that's fine. If the client turns out to be one of the fringe cases, we need to adjust the strategy. We do that until we get it right. That's individualized prevention. While it does not eliminate the uncertainty principle of medicine, it makes prevention efforts far more effective and much more rewarding. It certainly beats following some generic advice drawn from studies, whose mean effect values conceal a wide range of possible effects. 

Let's see when public health will finally see the light. Fortunately you don't need to wait for that to happen. Arm yourself with one of those home measurement devices, and actively measure and chart your progress against your chosen lifestyle change strategy. You'll see very soon, how unique you are as a medical case. 

1. King, N.A., et al., Individual variability following 12 weeks of supervised exercise: identification and characterization of compensation for exercise-induced weight loss. Int J Obes (Lond), 2007.

2. Yang, Q., et al., Trends in Cardiovascular Health Metrics and Associations With All-Cause and CVD Mortality Among US Adults. JAMA: The Journal of the American Medical Association, 2012.

3. Dong, C., et al., Ideal Cardiovascular Health Predicts Lower Risks of Myocardial Infarction, Stroke, and Vascular Death across Whites, Blacks and Hispanics: the Northern Manhattan Study. Circulation, 2012.


King NA, Hopkins M, Caudwell P, Stubbs RJ, & Blundell JE (2008). Individual variability following 12 weeks of supervised exercise: identification and characterization of compensation for exercise-induced weight loss. International journal of obesity (2005), 32 (1), 177-84 PMID: 17848941

Yang, Q., Cogswell, M. E., Flanders, W. D., Hong, Y., Zhang, Z., Loustalot, F., Gillespie, C., Merritt, R., & Hu, F. B. (2012). Trends in Cardiovascular Health Metrics and Associations With All-Cause and CVD Mortality Among US Adults JAMA : the journal of the American Medical Association DOI: 10.1001/jama.2012.339

Dong C, Rundek T, Wright CB, Anwar Z, Elkind MS, & Sacco RL (2012). Ideal cardiovascular health predicts lower risks of myocardial infarction, stroke, and vascular death across whites, blacks, and hispanics: the northern Manhattan study. Circulation, 125 (24), 2975-84 PMID: 22619283

Cleaning out my camera phone

I've had my phone for about a year and a half and I literally have hundreds of photos on there. Most of which are my nephew, my dogs, and my students. I was doing some camera phone cleaning out and I came across some pictures I took from our insect unit. We did a ton of things and I was fortunate to find so many resources. Since I'm at home I do not have the author's name of this great idea. If you know please comment so I can give credit where credit is due. As soon as I go into my classroom I will look it up so I can share it with you all and of course credit the amazing author. 

The packet came with labels for each body part of an insect and it even came with a variety of fun shapes to use. I had my kiddos draw their own but I wanted them to use the provided labels and come up with a name for their new insect.

This kiddo was perhaps my best artist.

"Prae Butter Bee" I think it's supposed to be 1/3 praying mantis, 1/3 butterfly, 1/3 bumble bee. So Creative!

This is "Terminator"
It's made up of vicious parts of several powerful insects. 

I think next year we'll do more labeling practice but I think that they all got really into it. I don't think I had any kiddos rush through and they all kept asking so many questions. "Is a scorpion an insect? What does a bee head look like?" I projected Google images and we discussed what we saw to answer these questions.

Links for you

Help With Language

Amen at Home
An Amharic-English First Words Book

Amharic to English Dictionary
Do an easy search for those daily-use words that will help ease
the transition to English.

Oromo-English Dictionary
Help with the Oromifa language

Six Things Adoption Has Taught Me
by Shaun Groves
Just six of the zillion things adoption has taught me 

Grief and Loss

A Journey of Loss, Healing and Redemption
@Babe of My Heart
Little did I know as not one of these online classes really prepare you for what the journey really requires… We couldn’t wait to one day adopt. And how beautiful it would be to open our home and hearts to a child that needed a family. Sure there would be sacrifices we knew…BUT eventually that child would be a “YOUNG” through and through–and it would be easy peasy in the end as our child smoothly fit in our groove as we were consistent and…LOVE would heal all the wounds. We’d have the most beautiful Christmas card you could imagine. Honestly–writing that now…makes me have to take a deep, slow breath…

And Finally, A Post
In the last five months I’ve realized anew that adoption is not a cause, it is a daily commitment. A commitment to run the marathon of healing and redemption alongside the child that God is grafting into your family. (I say ‘grafting’ because it is a process.) It is also a commitment to let Jesus do his therapeutic work in us too as parents.

Not Easy
I can tell you that it is a rare thing when I meet a post-institutionalized, post-trauma child who does not have significant cognitive or behavioral challenges resulting from their life experiences.

@Ordinary Miracles & The Crazy 8


Hey! I hope every one is having a great break so far. I've been soaking up some rays at the pool and I go on vacation in two weeks! Super excited.

I'm trying to keep school off my brain but it's just not working. I have however had the will power to not drive to school and go into my room. It doesn't hurt that it's about 30 minutes away and I'm not sure how much the custodians have done. I certainly don't want to get in their way.

I just wanted to mention one of the sites our librarian/tech teacher shared with us last year. It's pretty neat. I modeled some of it on the projector for my kiddos.

As you can see there are reading/seasonal/math activities for K-5

So check it out this summer and maybe you can integrate it into computer centers or lab time. 

Oh, there are abcya apps for iPad, too. They aren't free but many were just 99 cents. 

10 Good Reasons Not To Exercise?

Exercise may actually be bad for you! A professor says he stumbled upon this "potentially explosive" insight. The New York Times has been quick to peddle it. And couch potatoes descend on it like vultures on road kill. But professors can get it wrong, too. 

Before we judge the verity of the "exercise may be bad" claim, let's first look at how the media present it to us. We shall use the recent article in The New York Times, headlined "For Some, Exercise May Increase Heart Risk". The first paragraph confronts us with a journalist's preferred procedure for feeding us contentious scientific claims: presenting an authoritative author with stellar academic credentials and a publication list longer than your arm. While that is certainly better than having, say, Paris Hilton as the source of scientific insights, it is a far cry from actually investigating such claims. Which is what we want to do now.

The basis of the exercise-may-be-bad claim is a study which investigated the question "whether there are people who experience adverse changes in cardiovascular risk factors" in response to exercise [1]. The chosen risk factors in question were some of the usual suspects: systolic blood pressure, HDL-cholesterol, triglycerides and insulin. The research question: Are there people whose risk factors actually get worse when they change from sedentary to more active lifestyles? 

Sounds simple enough to investigate. Put a group of couch potatoes on a work-out program for a couple of weeks and see how their risk factors change. Only it is not that simple. In the realm of biomedicine, every measurement of every biomarker is subject to (a) errors in measurement and (b) other sources of variability. This makes it virtually impossible for you to see exactly the same results on your lab report for, say, blood pressure, cholesterol, glucose or any other parameter, when you get them measured two or more days in a row. Even if you were to eat exactly the same food every day and to perform exactly the same activities.  

Now imagine, if you conducted an intervention study on your couch-potato subjects and you found their risk factors changed after a couple of weeks of doing exercise, you could theoretically be seeing nothing else but a random variation caused by the error inherent in such measurement. 

To avoid falsely interpreting such a variation as a change into one or the other direction, it makes good sense to know the bandwidth of these errors for each biomarker, before you embark on interpreting the results of your study. Which is what the authors of this particular study did. They took 60 people and measured their risk factors three times over three weeks. From these measurements they were able to calculate the margin of error. Actually, they didn't do this for this particular paper, they had done this measurement as an ancillary study in the HERITAGE study performed earlier. The HERITAGE study had investigated the effects of a 20-weeks endurance training program on various risk factors in previously sedentary adults. Whether heritability plays a role in this response was a key question. That's why this study recruited entire families, that is, parents up to the age of 65, together with their adult children. 

I mention this because the paper, which we are deciphering now, is a re-hash of the HERITAGE study's results, to which the authors added the data of another 5 exercise studies. That's what is called a meta-analysis. In this case it covers more than 1600 people, with the HERITAGE study delivering almost half of them. 

Fast forward to answering the question of how many of those participants had experienced a worsening of at least 1 risk factor. Close to 10%. That is, about 10% of the participants had an adverse change of a risk factor in excess of the margin of error, which I mentioned earlier. I'm going to demonstrate the results, using systolic blood pressure and the Heritage study as the example. I do this exemplification for three reasons: First, blood pressure is the more serious of the investigated risk factors. Secondly, the HERITAGE study delivers most of the participants, and thirdly, the effects seen and discussed with respect to blood pressure and HERITAGE apply similarly to the other 5 studies and risk factors. 
But before we go there I need to familiarize you with a basic concept of statistics. It is called the "normal distribution of data". It is an amazing observation of how data are distributed when you take many measurements. Let's take blood pressure as an example. 

If you were to measure the blood pressure values for every individual living in your village, city or country, you could easily calculate the average blood pressure for this group of people. You could put all those data into a chart such as the one in figure 1. 

Figure 1
On the x-axis, the horizontal axis, you write down the blood pressure values, and on the y-axis (the vertical axis) you write down the number of observations, that is, how often a particular blood pressure reading has been observed. You will find that most people have a blood pressure value pretty close to the average. Fewer people will have values, which lie further away from this average, and very few people will have extreme deviations from the average. 

It so turns out, that when you map almost any naturally occurring value, be it blood pressure, IQ or the number of hangovers over the past 12 months, the curve, which you get from connecting all the data points in your graph, will look very similar in shape. Some curves are a bit flatter and broader, while others are a bit steeper and narrower. But the underlying shape is called the "normal distribution", and it means just that: It's how data are normally distributed over a range of possible values. The curve's shape being reminiscent of a bell, has lead to this curve being called the "bell curve". 

In statistics, especially when we use them to interpret study data, we always go through quite some effort to ensure that the data we measure are normally distributed. That's because many statistic tools don't give us reliable answers if the distribution is not normal.

Back to our famous study. What you see in figure 2 is how the authors present their results for the blood pressure response of the HERITAGE participants. 

Figure 2
For each individual (x-axis) they drew a thin bar representing the height of that person's change in blood pressure after 20 weeks of exercise. Bars extending below the x-axis represent reduced blood pressure, and those extending above the x-axis represent increased blood pressure. The bars in red are those of the people whose blood pressure increase was in excess of the error margin of about 8mmHg. 

Now, Claude Bouchard, the lead author of the paper, is being quoted in the NYT as saying that the counterintuitive observation of exercise causing systolic blood pressure to worsen "is bizarre". 
Here is why it is neither counterintuitive nor bizarre: When we accept the blood pressure values of our study population to be distributed normally, we have every reason to expect the change in blood pressure to be distributed normally, too. Specifically, since all participants went through the same type of intervention. 

Figure 3

If we now run a computer simulation, using the same number of people, the same mean change in blood pressure, and the same error values, then we can construct a curve for this group, too. Which is what you see in figure 3. Eerily similar to the one in figure 2, isn't' it? 

That's because we are looking at a normal distribution of the biomarker called 'blood pressure change'. It is an inevitable fact of nature that a few of our participants will change "for the worse". And I'm putting this in inverted comma because we don't really know whether this change is for the worse. 
After all, we are talking risk factors, not actual disease events. In the context of this study you need to keep in mind, that all participants had normal blood pressure values to begin with. The average was about 120mmHg. The mean change was reported as 0.2 mmHg. That's not only clinically insignificant, that's way below the measurement capability of clinical devices. 

When I started to dig deeper into this study, I found quite a number of inconsistencies with earlier publications. For example, in the latest paper, the one discussed in the NYT, the number of HERITAGE participants was stated as 723. In a 2001 paper, which investigated participants' blood pressure change at a 50-Watt work rate, the number was stated as 503 [2].  In the same year Bouchard had published a paper putting this number at 723 [3]. Anyway, the observation that the blood pressure change during exercise was significantly larger (about -8 mmHg) than the marginal change of resting blood pressure indicates that there probably was some effect of exercise. 

So, what's the take-home point of all this? With the "normal distribution" being a natural phenomenon that underlies so many biomarkers, it is neither bizarre nor in any other way astonishing to find "adverse" reactions in everything from pharmaceutical to behavioral interventions and treatments.  Whether such reactions are truly adverse can't be answered by a study like the one, which is now bandied about in the media. That's because risk factors are not disease endpoints. They are actually very poor predictors of the latter, as I have explained in my post "Why Risk Factors For Heart Attack Really Suck". 

So, keep in mind, that there is no treatment or intervention, which has the same effect on everybody. Pharmaceutical research uses this knowledge, for example, when determining the toxicity of a substance. This toxicity is often defined as the LD50 value, that is, the lethal dose, which kills 50% of the experimental animals.  Meaning, the same dose which kills half the animals, leaves the other half alive and kicking. 
And correspondingly, the same dose of exercise, which cures your neighbor from hypertension, may have no effect on you. Because you belong to those 10% who react differently. But are these 10 good reasons not to exercise? How to deal with this question will be the subject of my next post. Until then, stay skeptical. 

1. Bouchard, C., et al., Adverse Metabolic Response to Regular Exercise: Is It a Rare or Common Occurrence? PLoS ONE, 2012. 7(5): p. e37887.

2. Wilmore, J.H., et al., Heart rate and blood pressure changes with endurance training: the HERITAGE Family Study. Medicine and Science in Sports and Exercise, 2001. 33(1): p. 107-16.

3. BOUCHARD, C. and T. RANKINEN, Individual differences in response to regular physical activity. Medicine and Science in Sports and Exercise, 2001. 33(6): p. S446-S451.

Bouchard C, Blair SN, Church TS, Earnest CP, Hagberg JM, Häkkinen K, Jenkins NT, Karavirta L, Kraus WE, Leon AS, Rao DC, Sarzynski MA, Skinner JS, Slentz CA, & Rankinen T (2012). Adverse metabolic response to regular exercise: is it a rare or common occurrence? PloS one, 7 (5) PMID: 22666405

Wilmore, J. H., Stanforth, P. R., Gagnon, J., Rice, T., Mandel, S., Leon, A. S., Rao, D. C., Skinner, J. S., & Bouchard, C. (2001). Heart rate and blood pressure changes with endurance training: the HERITAGE family study. Medicine and Science in Sports and Exercise DOI: 10.1097/00005768-200101000-00017

Bouchard, C., & Rankinen, T. (2001). Individual differences in response to regular physical activity Med Sci Sports Exerc DOI: 10.1097/00005768-200106001-00013


PicMonkey Collage
He Knows Who He Is
I am acutely aware that I haven’t gotten everything right as a dad, much less an adoptive dad.  But when my kids can be comfortable in their own skin; when they can talk with me about things that are a big deal and it’s not a big deal – I know that somehow, someway, and often in spite of me, we are headed in the right direction.

A Challenge for Adoptive Dads
@Empowered To Connect
Watch as Michael Monroe talks about the need for adoptive dads to partner with their wives to work together as they lead their children toward hope and healing.

We are incredibly grateful and have deep respect for the adoptive dads who have adopted from our YWAM orphanages.

Happy Father’s Day to each of you!