Study Affirms that Central Obesity has Higher Mortality Risk

November 21st, 2015 No comments »

A new article reaffirms earlier studies showing that in persons with a normal Body Mass Index (BMI) had the worst long-term survival compared to others with a similar BMI but no central obesity and twice the mortality risk of persons who were overweight or obese according to BMI.


The Obesity-Alzheimer’s Disease Connection

September 3rd, 2015 No comments »

A recent article by Dr. M. Thambisetty of the National Institute on Aging studied the effect of mid-life obesity on the age of onset of Alzheimer’s Disease (AD). Using data from the Baltimore Longitudinal Study of Aging of 1,394 cognitively normal subjects followed for over 13 years, the research team found each BMI unit increase in mid-life predicts the onset of AD by over 6 months. The study did not indicate whether weight loss in mid-life would normalize the development of AD.

Another study has examined the literature for risk factors for developing AD. Nine risk factors were examined including current smoking, carotid artery narrowing, type 2 diabetes, low educational attainment, high levels of homocysteine, depression, high blood pressure and frailty. High or low BMI in mid-life and low educational attainment were associated with increased risk, whereas high BMI in later life, exercising one’s brain, current smoking (except for the Asian population) light to moderate drinking and stress were associated with lowered risk.

Recent research has identified an association between obesity and Type 2 Diabetes with cognitive decline and Alzheimer’s disease. (For background, see Health Effects.) Yet another study has found an accumulation of fat droplets in the brain of patients who died from Alzheimer’s disease. The researchers concluded that the build-up of fatty acids in the brain is not a consequence but a cause of the disease.

ADA Urges Lower BMI Cutoff for Asian-Americans

January 5th, 2015 No comments »

The American Diabetes Association (ADA) is lowering the Body Mass Index (BMI) cutpoint for screening Asian-Americans for type 2 diabetes to a BMI of >23kg/m2. In the new article, the evidence for a lower BMI cutpoint is discussed.  The authors note the presence of Asian-Americans and the projections for their increasing population, especially in 10 states, including California, New York, Texas, New Jersey, Hawaii, Illinois, Washington, Florida, West Virginia, and Pennsylvania.  The authors also note the limitations of current measurement techniques, observing that  BMI does not into account the relative proportions of fat and lean tissue and cannot distinguish the location of fat distribution. There is a propensity for Asians to develop visceral versus peripheral adiposity which is more closely associated with insulin resistance and type 2 diabetes. The new standard is not a measure of increased mortality or morbidity but a guide how to use BMI to screen for the presence of type 2 diabetes, with a focus on reacting to BMI cut-offs for eligibility of weight-reduction services or treatment reimbursable by payers.

There a couple of points. First, it is unfortunate that the ADA is not taking on the use of BMI for criteria for products (such as anti-obesity drugs) or services. Changing the BMI cut-offs to accommodate a poor public policy only adds to the distortion of our understanding of excess adipose tissue. The paper understates the fact that the BMI is such a poor standard for use in clinical settings. Third, aside from the literature about cut-offs, the problem is “Who is an Asian-American?” In addition to covering a number of various ethnic groups, determining whether one is “Asian-American” has a host of problems, including the issue of inter-marriage. Demographers are having a hard time determining just what “Asian-American” means. The problem originates with the Census Bureau criteria, as well as the problem of inter-marriage and self-identification as Asian-American versus White. Historically, the Census Bureau has combined Asians, Native Hawaiians and other Pacific Islanders, even though there are significant differences in physiology and body composition between Asians and the other two groups. Listen to this interesting discussion on the Diane Rehm Show on NPR on January 5, 2015 on this very topic.


Problems With Defining Diabetes

November 13th, 2014 No comments »

Folks familiar with obesity conversations know that the Body Mass Index (BMI) has many problems as a reliable indicator of excess adipose tissue (which is the definition of obesity). However, many may be somewhat surprised that the use of glycosylated hemoglogin (HbA1c) test with a cutoff value of >6.5% also has several problems. In a recent paper,  Juarez, Demaris, Goo et al reviewed 47 studies looking at HbA1c as a diagnostic tool. They concluded that HbA1c is useful for its convenience and effectiveness, especially in community-based and acute-care settings where tests requiring fasting are not practical. However, HbA1c may underestimate the prevalence of diabetes among whites, children, women with gestational diabetes, patients with HIV and those with pre-diabetes.  While these findings are pretty significant on their own, it is sobering to consider that the familiar Obesity-Diabetes axis or BMI- HbA1c Axis has so much, what to say, “flexibility” in interpreting results of studies, such as the Diabetes Prevention Program or Look AHEAD. As many of these studies, (consider the SCOUT trial of sibutramine, see Sept 20, 2010 statement to the FDA), draw large conclusions from relatively small differences, the “flexibility” or error-room of mistakes by relying on BMI- HbA1c has serious implications for personal and public health.


Keeping Up with Obesity and Liver Disease

June 14th, 2014 No comments »

New York Times is carrying a page-one-above-the-fold story on liver disease. It stresses the rise of non-alcoholic fatty liver disease related to the rise in obesity as the leading cause of liver transplants and the rise in NASH, non-alcoholic steatohepatitis. While high sugar consumption is clearly involved, a particular gene, widespread in the Hispanic population, has increased its prevalence.


More evidence on obesity and mortality. Where did the obesity paradox go?

January 15th, 2014 No comments »

The January 16, 2013 issue of the New England Journal of Medicine contains an article by Frank Hu and colleagues looking at mortality among adults with incident type 2 diabetes by Body Mass Index (BMI). Using two large databases, they found a J-shaped association between BMI and mortality among those who had ever smoked and a direct, linear relationship among those who had never smoked. They found no evidence of an “obesity paradox,” the supposed protective effective of overweight. They concluded, “…given the relationship of overweight and obesity to other critical public health end points (e.g. cardiovascular disease and cancer), the maintenance of a healthy body weight should remain the cornerstone of diabetes management, irrespective of smoking cessation.” The article is a contribution to the understanding of obesity’s relationship with premature mortality but will surely not be the last word on this topic.


Cancer Patients with Obesity Undertreated

September 24th, 2013 No comments »

The Washington Post carries an article today on physicians under-treating cancer patients with obesity by giving lower doses of chemotherapy than appropriate for their weight. A recent paper in Nature by Lyman and  Sparreboom highlighted the problem. The American Society of Clinical Oncology has issued new guidelines urging full, weight-based doses for persons with obesity. This problem is not unique to chemotherapy by any means. An article by 10 FDA scientists in 2011 found “specific dosing recommendations for these (obese) patients are often absent in drug product labels.”


Obesity Mortality Estimate Sharply Up

August 22nd, 2013 No comments »

In a new analysis, researchers have determined that mortality due to obesity is much greater than previously estimated, perhaps some 4 times as higher as previous estimates. The new analysis is based on looking at age, race and gender cohorts between 1986 and 2006.