A better measure of health? Waist Circumference over BMI

People do say the strangest things to me and the other day was no exception.  I was standing poolside, about to enter a lane, when a man already in the pool, in an adjacent lane, looked up at me - speedo clad, in cap and goggles - and said, "I'd like your body mass index please."  Seriously, those were his exact words.  I wasn't sure what to say or how to interpret what he said.  It reminded me of how police say, "I'd like your ID please."  In other words, I didn't know if he wanted me to tell him what my body mass index number was or if he wanted to have the same number as I had.  In response, as I laughed and jumped in the pool, I said, "No you don't, it's too low."  And so the discussion began.. as I pointed out to my new "friend" that BMI is helpful for understanding weight changes and obesity in the population, but is usually less helpful for me and you.  "OH?," he said. I explained, "waist circumference or waist to hip ratio might be better indicators of health."  To which he replied, "Ok, so what is it you do for a living?"  Well....

The next day, I ran across a research study on waist circumference and health. The study is published in the journal Mayo Clinic Proceedings.  I have previously discussed the different measures of weight status, e.g., BMI, Waist Circumference, and Waist to Hip Ratio.  A less discussed measure is the Waist to Height Ratio, which I mention again at the end of this post.

The man in the pool, like many of us, was not aware of the BMI debate.  Researchers and obesity specialists offer reasons why the BMI may not accurately measure a single persons' health status (related to weight) and also why the BMI may not accurately measure the number of persons who have health related levels of adiposity (fatness).  BMI is determined by a formula that uses a persons weight and height to create a ratio (i.e., weight(kg)/height(m)^2).  A person is said to be overweight if their BMI is over 25 and obese if it is over 30, but it is possible to be lean and fit and have a high BMI (in other words, a person might be 'heavy' and not have a lot of body fat, or they may have body fat in the legs which is not as harmful to health as body fat in the waist area, and the BMI doesn't catch those distinctions (see Snijder et al, 2006 ).  A popular example of when a BMI may be inaccurate is seen in athletes.  A fit football player may be heavy because he is solid muscle and his BMI could be 30, such that on paper he is qualified as obese.  Still, BMI can be a good measure of weight related health risk for most of us.  

In regards to trying to capture the rate of obesity for whole populations, BMI is tricky. Every year or so we are told the % of people in a state or country who are overweight or obese.  That number is not a true average of the population but one estimated from a sample of people who were probably called on the telephone and asked their height and weight.  (Some surveys, like the NHANES in the US do collect actual measurements in lab settings).  The usual way of telling researchers in writing, in person, on line or on the phone, ones height and weight, is called self report.  Self reported BMI is said to be a limited measure of overweight and obesity because people can make mistakes and people can, well.... many of us want to be thinner and taller, and might fudge our numbers on purpose.  So even if we aren't athletes, and our BMI accurately reflects our health status, we might not provide researches with the right numbers.  This probably means that the estimated overweight and obesity rates of the population are HIGHER than the reports indicate.

As BMI does not accurately reflect weight related health status for individuals with less common body types and can be incorrectly calculated from 'bad' data, some researchers suggest that waist measurements (waist circumference, waist to hip ratio, and the waist to height ratio) are better indicators of health than the BMI. (See for example, Czernichow et al , 2011; Bener et al, 2013; Vazquez et al, 207).  These studies do indicate that waist circumference (WC) is a better predictor of heart disease, diabetes and mortality than BMI.

To be fair,  some of the studies involve self report of waist measurement and could also have errors, but the WC does capture belly fat and that is what is currently seen as the instigator of disease.  I would expect that and some evidence supports this, people are less likely to purposefully misstate their waist circumference than their height or weight.

The most recent study* (the one I saw in the journal Mayo Clinic Proceedings) on waist circumference found a positive relationship with waist circumference and all causes of death, heart disease death, respiratory death (i.e., COPD) and cancer.  In other words, as the inches (or centimeters) of a persons waist increased beyond a baseline reference number (85 cm for men, 65 cm for women) so did the risk of dying from any disease during the study period.  The researchers compared the likelihood of dying from any cause at 5 cm intervals, or a couple of inches.  For women (all white people in this study), the increased risk of death was pronounced even at the first 5 cm mark (i.e., 70 cm), but for men, the increased risk of death did not become evident until 100 cm.  The effect size - amount of increased risk - was bigger for heart and respiratory disease than for cancer.

In the same study, the researchers compared mortality rates between high and low waist circumference groups.  The low group for women included those with waist circumferences less than 70 centimeters and the low group for men included those with waist circumference less than 90 centimeters.  To be clear, the researchers created 6 WC categories for men and 7 for women.  The differences in likelihood of death during the study period were seen between the 'referent' low category and the high category (50% higher likelihood of death), but there was no difference between the categories of normal or slightly elevated waist circumference and the low category.  That is why it is important to look at the continuous scale  - the 5 cm increments discussed in the above paragraph.  Those data show that a persons risk increases with every couple of inches they add to their waist.  

IMPORTANT NOTE: Remember the comments at the start of this post?  BMI does not accurately reflect health risk when the weight part of the equation is misleading.  An athlete may have a high BMI because of lean tissue, but a low weight person could have excess stomach fat.  This is especially true for older persons, the number on a scale may not reflect the extra inches on a person's waist. That is why the researchers in the Cerhan study, even after confirming that BMI told pretty much the same story as the WC, suggested that at all levels of BMI and especially in the old old adult (i.e., over age 75), WC also be measured by clinicians.  In some people the WC is going to be a better indicator of disease or death risk than BMI and it looks like WC is just as good as BMI in the other cases.. 

You can see the summary for the study here.  The data came from 11 different studies and in all but one of the studies, the people measured their own waists and reported the results to research staff.

*Cerhan, James R. et al.  A Pooled Analysis of Waist Circumference and Mortality in 650,000 Adults

Mayo Clinic Proceedings , Volume 89 , Issue 3, 335 - 345

 (There is some discrepancy among health agencies on what normal or low risk is for the waist circumference; the CDC, AHA, and NHLBI in the US say 35 inches or less for women and 40 inches or less for men, this would be ~ 88 cm for women and 102 cm for men, much higher than the low group used for comparison in the Cerhan study, but remember what I said about the categorical analysis and the incremental analysis.  For women in the study, the risk increased at the first 5cm point (70cm) where as for men, the risk first increased at the second increment.  The International Diabetes Federation suggests a lower target waist circumference; 80 cm women and 90 cm men). 

There is also the waist to height ratio which has gotten a lot of praise for being able to accurately predict disease.  You can calculate yours by using the tools on this website. [be aware of the ads on the waist to height calculator page, or better yet beware them - they seem spamy]

The Sunshine Study: Does it do your weight good?

A couple of weeks ago I heard a news story which referenced the power of sunshine.  Readers who have met me know that my favorite thing in life is sunshine.  I was delighted to hear that science supports something I knew anecdotally (i.e., by my personal experiences); the sun does a mind good.  It follows that what does the mind good will do the body good (tanning excluded!).

The headlines were even better – tantalizing even… early morning sun aids in weight control… or those who spent time in the sun between  8 and 11 a.m. weigh less (smaller BMI) than those who do not get out in the early sun. REALLY?!  I exercise outside almost every morning (walk, bike, run) after 8am but before 12.  Yay!

I do have a low BMI, but I know it is because of my dietary intake and physical activity (it certainly isn’t my genes), I am not inclined to believe that the sun I adore is keeping me thin.  Still, I wanted to learn more about this study so I could give my favorite ‘element’ the kudos and promotion it deserved.

I located the referenced study – referenced in the popular press and linked for you below – and read every single word.  I read and read, paragraph after paragraph, I read and searched and waited… until I got to the very end, past the introduction, the methods, results, discussion, limitations, acknowledgement and the references.  I even used ‘word find’ for goodness sakes FIND: Sunlight or Sunshine.  Nada, nil, zilch.  Sunshine is not mentioned once in the study.

Below I offer a little information from the study, and then the email response from the corresponding author, because of course I emailed her.  I had to be doubly sure I didn’t overlook the part where the people talked about the time they spent in the sunlight.

Participants (54 people) agreed to wear a special light and activity sensor on their wrist (on the outside of their clothing) for 7 days.  This device generated data that the researchers could review, i.e., when the person fell asleep, how long they slept, when they were exposed to light – background, ambient light – and the level of intensity of that light.  The unit of measure for light is LUX.  The participants also completed a 7 day food intake diary and gave their heights and weights (for BMI calculation).  The goal was to see if timing and intensity of light was associated with sleep, eating, or BMI. 

The only finding that was considered ‘real’ was that people exposed to higher levels of light i.e., > 500 lux had lower BMI numbers than people not exposed to light above 500 lux.  This correlation only held if the exposure occurred in the early morning hours. 

It is probable that the light at > 500 lux was from the sun, but there is absolutely no way to confirm this.  Researcher Phyllis Zee kindly responded to my email inquiry and said that with a lux over 200 it is expected that sunlight was ‘involved,’ but the source of light was indeed unknown. Also, I think it is important to note that a BMI even if accurately representing excess adipose tissue is not something associated with the last 7 days!  One BMI point = 6 pounds and well, my BMI is about my last 7 years, not 7 days.

All that being said, Sunshine Makes Me Happy and that is all I need to know.

Reid, K. J., Santostasi, G., Baron, K.G., Wilson, J., Kang, J., & Zee, P. C. (2014). Timing and Intensity ofLight Correlate with Body Weight in Adults. PloS one, 9(4),e92251.

Does a BMI number cause Breast Cancer Death?

   The headlines read that obesity increases the risk of cancer recurrence and death in women who are diagnosed with breast cancer.  The actual study involved an evaluation of several groups of women who had stage 1, 2 or 3 breast cancer and were themselves enrolled in clinical research trails.  The purpose of those research trials was not to determine if weight impacted recurrence or mortality, but to evaluate the efficacy of new chemotherapy drugs.  This is important.  Who were the women in the sample, how much are you like them, and how much are other breast cancer patients like them?
    The women who were studied all received chemotherapy and had operable cancers (I do not know if they had surgery, only that they had operable tumors and received chemotherapy).  A consideration to make is whether or not the people who chose to enroll in the study are different from people who did not enroll.  Also, only certain types of people were allowed to participate.  Usually, and it is true here, the people in drug studies have the condition the drug is trying to treat, but are usually otherwise healthy.  This study left out people with "significant" co-morbidities (other diseases occurring at the same time), but I do not know what 'significant' includes.
   The headlines refer to BMI as the risk factor, but having a BMI of 30 or higher isn't the problem.  What that number might reflect is the problem.  For most people BMI mirrors waist circumference (WC) - they mean the same thing.  However, in some people the BMI does not reflect their weight status well.  Waist circumference over 35 inches or higher is a very good indicator that a person also has insulin resistance, high triglycerides and high blood pressure.  It is those issues - collectively called 'metabolic dysfunction', that puts people at greater risk of disease and death.  Consider that those conditions; high blood pressure, trouble with sugar, high blood fats,  make the body less robust, less able to fight off infection, less able to rebound from injury and disease.  Metabolic dysfunction is deconditioning and a person with these conditions (including a WC 35+ and a high BMI) is at a disadvantage before treatment for cancer ever begins.
   This way, obesity and smoking are similar - both increase the risk of disease and death from any disease - just know that BMI and obesity are not the cause - it is the metabolic dysfunction.  Maybe they are the cause of the cause.
    Here is a link to the study regarding the outcomes of the 3 drug trials that were used for the headline making stories.

Study reference:
 Sparano, J. A., Wang, M., Zhao, F., Stearns, V., Martino, S., Ligibel, J. A., Perez, E. A., Saphner, T., Wolff, A. C., Sledge, G. W., Wood, W. C., Fetting, J. and Davidson, N. E. (2012), Obesity at diagnosis is associated with inferior outcomes in hormone receptor-positive operable breast cancer. Cancer.