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FMI possibly more useful than BMI for rapid assessment of Metabolic syndrome

metabolic syndrome

An interesting, limited study published this year observes higher Fat Mass Index (FMI) levels appear to be independently and positively associated with the presence of Metabolic syndrome (MetS) regardless of Body Mass Index (BMI) and body fat percentage (BF%). FMI appears to be a better screening tool in prediction of the presence of metabolic syndrome than BMI and percentage of body fat in men and women.¹  Please note that due to the cross-sectional design, the study itself is not exploring a causal relationship between body composition and metabolic syndrome, and is limited in that it did not include a variety of ethnic groups in the cohort.

Along with the growing popularity and proven accuracy of bioelectrical impedance analysis (BIA) technology for the measurement of body composition, BMI is still widely used for the rapid assessment of obesity, and is easily calculated. However, it cannot reflect body fat mass and body fat distribution due to the differences of age, sex and ethnic groups and obese types when BMI is used alone. Although some studies [2,3] found that high BF% was associated with increased cardiovascular risk regardless of BMI whose categorization resulted in an underestimation of subjects with cardiovascular risk factors, people with the same BMI reading may have very different body composition, which may result in people with the same BMI or percentage of body fat exposing to different metabolic conditions.  Therefore, it can be better to measure and express body composition as FMI and Fat Free Mass Index (FFMI) than either BMI or BF%.

The study showed that high FMI had significantly higher odds ratio for metabolic syndrome than the low FMI in both sexes, which was similar to one previous study⁴, in which body composition was measured by DeXA. This study also showed that high FMI level was strongly associated with the presence of MetS after adjusting BMI and BF% in both men and women, and the adjusted odds ratios of the risk of MetS were higher than that of BMI and BF.

References

 ¹Liu, Pengju et al. “The Utility of Fat Mass Index vs. Body Mass Index and Percentage of Body Fat in the Screening of Metabolic Syndrome.”

BMC Public Health 13 (2013): 629. PMC. Web. 1 June 2016.

 ²Zeng Q, Dong SY, Sun XN, Xie J, Cui Y. Percent body fat is a better predictor of cardiovascular risk factors than body mass index. Braz J Med Biol Res. 2012;45:591–600. doi: 10.1590/S0100-879X2012007500059.

³Cho YG, Song HJ, Kim JM, Park KH, Paek YJ, Cho JJ, Caterson I, Kang JG. The estimation of cardiovascular risk factors by body mass index and body fat percentage in Korean male adults. Metabolism. 2009;58:765–771. doi: 10.1016/j.metabol.2009.01.004.

Wang J, Rennie KL, Gu W, Li H, Yu Z, Lin X. Independent associations of body-size adjusted fat mass and fat-free mass with the metabolic syndrome in Chinese. Ann Hum Biol. 2009;36:110–121. doi: 10.1080/03014460802585079. 

Use of body composition analysis in cardiac function evaluations

cardiac function evaluationsAn interesting study from 2007 incorporated the use of body composition analysis using bioelectrical impedance analysis (BIA)1  In the study, multiple body components such as water, fat, mineral, protein and intracellular and extracellular liquid, were measured.  Levels of serum glucose, high-density lipoprotein-cholesterol, triglycerides, creatinine and uric acid were measured to evaluate the cardiovascular risk of the participants.  In summary, a metric in the form of Body Fat Rate (BFR;  body fat mass/weight) was identified to have a high coefficient correlations associated with both systolic and diastolic cardiac function, pointing to a potential application of BIA in clinical prediction of cardiovascular disease.

The study was conducted with a total of 325 healthy volunteers (217 men, 108 women) with an average age of 48 years.  Body fat mass and BFR were significantly lower in subjects with normal systolic function than those with defective arterial compliance.

1Zeng, Q., Sun, X.-N., Fan, L. and Ye, P. (2008), CORRELATION OF BODY COMPOSITION WITH CARDIAC FUNCTION AND ARTERIAL COMPLIANCE. Clinical and Experimental Pharmacology and Physiology, 35: 78–82. doi: 10.1111/j.1440-1681.2007.04749.x

 

Nutritional Status Screening of Hospital Inpatients Should Include Body Composition Analysis

seca mBCA 525 body composition analyzer

seca mBCA 525 body composition analyzer

Poor nutritional status is an especially important factor in adult periprocedural care, particularly elder patients. Assessment screening tools can include history and exam, labs (for serum proteins), body composition analysis using the latest technologies, anthropometrics and functional data (such as the subjective global assessment of nutrition (SGA) and mini-nutritional assessment (MNA).  Validated screening tools should be used in tandem, two or preferably more, for nutrition status assessment.

This kind of screening is especially important given that individuals in certain patient populations with less than 80% expected total body protein levels have demonstrated increased morbidity, and 10% or greater unintentional weight loss has been associated with adverse outcomes and prolonged hospitalizations. In lean, healthy subjects, weight loss over 35%, protein loss over 30%, and fat loss over 70% from baseline has been associated with death.

Current bioelectrical impedance analysis (BIA) body composition analysis technology allows for a precise, medically-validated assessment of body composition to support nutritional status screenings of patients in supine position, such as needed with a typical inpatient.  This combined with other validated tools such as labs for example can provide clear guidance for periprocedural care.

Ref:  Nutritional Status Assessment in Adults Technique

Author: W Aaron Hood, DO; Chief Editor: Vikram Kate, MBBS, PhD, MS, FRCS, FRCS(Edin), FRCS(Glasg), FACS, FACG, FIMSA, MAMS, MASCRS

Body composition and metabolic changes following bariatric surgery

basal-metabolic-rate

A quick summary about interesting research results in regard to basal metabolic rate differences in pre and post-operative bariatric surgery patients.

Body composition analysis using convenient, clinical-grade bioelectrical impedance analysis (BIA) technology can provide clinicians and researchers accurate, medically-validated measurements of patient basal metabolic rate (BMR), percent fat, fat mass in absolute values, and lean body mass among others.

These measurements are very helpful to know prior to surgery, with a view to post-surgical care, planning and nutrition counseling. A recent study looked at the Analysis of Variance using the general linear model with a research cohort of bariatric patients1. Prior to surgery the baseline values were measured in a rapid, non-invasive manner by means of BIA.  After  surgery the same measurements of BMR, fat mass and lean mass were taken at intervals of 1, 3 and 6 months. The resulting analysis showed significant changes in all body composition measures, including lean body mass, and an average reduction in BMR for the cohort in a range of 330-440 kcal one month after surgery.  This is an expected and significant reduction in BMR, and points to it being helpful to measure a patient’s score in regard to post-surgical nutrition counseling as it applies to total daily caloric intake.  Subsequent measures at the 3 and 6-month intervals showed no significant changes in BMR, indicating no adaptation of an energy-conservation mechanism in the cohort patients.

 

Citations

1Body Composition and Metabolic Changes Following Bariatric Surgery: Effects on Fat Mass, Lean Mass and Basal Metabolic Rate  Daniel Gene Carey, German J Pliego, Robert L Raymond, Kelley Brooke Skau  Obesity Surgery April 2006, Volume 16, Issue 4, pp 469-477

seca mBCA praised at Overcoming Obesity 2015

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seca recently exhibited at the Overcoming Obesity Conference in Washington, D.C. The conference was hosted by the Obesity Medicine Association and it attracted over 600 physicians from the U.S. that specialize in obesity medicine.

At the conference, the seca medical Body Composition Analyzer (mBCA) 514 was praised for its ability to help boost patient satisfaction.

Keeping patients happy is no easy task for any doctor. Crowded waiting rooms and short doctor-patient interactions can often hurt patient satisfaction scores. Less obvious things such as medical equipment that’s inaccessible to overweight patients could make a visit to the doctor unpleasant.

The unique design of the mBCA helps to maximize patient satisfaction by easily accommodating larger patients. The mBCA is equipped with handrails that offer patients both stability and support, while providing contact points for the stainless steel electrodes to measure the body. These handrails also provide fixed body positioning which ensures valid and reproducible results.

The low-profile glass platform of the mBCA makes it easily accessible for overweight and handicapped patients. At 3.25 inches tall, this sleek platform appoints the mBCA as the most accessible body composition analyzer on the market. All of these features assist physicians in improving patient satisfaction scores.
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mBCA Demo at Prestigious Anschutz Health & Wellness Center at Colorado University

Anschutz Center building

Anschutz Center building

This week seca performed a demonstration for the clinical nutrition research department at the world-renowned Anschutz Center in Colorado, a top-tier health and wellness research center that also provides programs for weight loss, fitness, and innovative medical wellness protocols.  The Anschutz research staff will soon be attending the upcoming Obesity Week conference in nearby Los Angeles where seca will be an exhibitor, and plans are being made to continue discussions and socialize together at the conference in regard to additional opportunities in early 2016 for research, mBCA sales, and possibly published studies.

seca mBCA with Hologic DEXA device

seca mBCA with Hologic DEXA device

Are you TOFI?

tofi_mri_image

Coronal image of a TOFI subject (left) with 5.86 l of internal fat, and a Normal Control subject (right) with 1.65 l.

A new buzzword is making waves in news and the healthcare community – “TOFI”, a term you’re sure to come across if you haven’t already.

The acronym TOFI[1][2] “thin-outside-fat-inside” is used to describe individuals who appear lean but actually have a disproportionate amount of internal fat (adipose tissue) stored within their abdomen, also called “VAT” visceral adipose tissue.  This is distinct from subcutaneous fat which is found under the skin.  VAT is found internally and also surrounds internal organs such as the liver.  Persons defined as TOFI have increased levels of risk factors associated with “metabolic syndrome”, the cluster of symptoms consisting of increased blood pressure, high blood sugar level, excess body fat around the waist (VAT), and elevated cholesterol levels.  Current statistics for this condition are not fully developed yet, but research to date performed on individuals with BMI’s between 20 and 25 found the instance of TOFI in the control group to be 14% of the men and 12% of the women[1].

TOFI classification is a further refinement of the “metabolically-obese but normal-weight” (MONW)[3][4][5] category, another acronym that does a good job pointing to the surprising fact that a person can appear fit yet actually be at health risk due to the effects associated with excessive internal fat.

To illustrate this, the Coronal scan image on the left shows two men, both 35 years old and each with a BMI of 25. Despite their very similar size, the TOFI subject (left side in red colors) had 5.86 liters of internal fat, while the healthy control subject (right side) had only 1.65 liters.

Persons with TOFI are described as being at higher risk of developing insulin resistance and type II diabetes due to the fact that they have reduced physical activity/VO2max, reduced insulin sensitivity, and higher abdominal VAT.  Another important characteristic is excessive levels of liver fat.

Larger statistical sets of data in regard to the prevalence of TOFI from a public health perspective are certainly in the works, but large scale data has been slow to develop.  This is because the classification of a person as TOFI is based on measuring internal fat, performed by MRI or CT scan methods, which are both time-consuming and expensive.  Waist circumference by itself is not sufficient, in that persons with identical waist measurements can have vastly differing amounts of internal fat.

In response to this health challenge and the clinical need for accurate diagnostics, seca’s introduced ground-breaking body composition technology, medically-validated to the MRI method, for the measurement of VAT using bioimpedance analysis (BIA).  Our pioneering device, the seca mBCA body composition analyzer, produces the closest medically-validated correlation to MRI for the measurement of VAT of any BIA device on the market.

It turns out there is more to internal fat than meets the eye.  Scientists are beginning to think of fat as an organ in the way that it produces chemicals and hormones.  Fat cells are sort of like “chemical factories” producing other substances which can cause health problems long-term, contributing to diabetes, heart disease, high blood pressure, strokes and other illnesses, including some cancers. As you put on more weight, the internal fat cells grow bigger, sending out chemical “messages” to nearby cells which start to divide to produce more fat cells.  A lean adult is estimated to have somewhere around 40 billion fat cells, an obese person two to three times more.  The first step to addressing TOFI is accurately measuring what’s there, and possibly tracking progress of internal fat and/or specifically VAT reduction by means of accurate BIA analysis combined with a supervised medical weight loss program.

References

1. Thomas, E. Louise; Frost, Gary; Taylor-Robinson, Simon D.; Bell, Jimmy D. (2012). “Excess body fat in obese and normal-weight subjects”. Nutrition Research Reviews 25 (1): 150–161. doi:10.1017/S0954422412000054. PMID 22625426.

2. Jump up ^ Thomas, E. Louise; Parkinson, James R.; Frost, Gary S.; Goldstone, Anthony P.; Doré, Caroline J.; McCarthy, John P.; Collins, Adam L.; Fitzpatrick, Julie A.; Durighel, Giuliana; Taylor-Robinson, Simon D.; Bell, Jimmy D. (2011). “The Missing Risk: MRI and MRS Phenotyping of Abdominal Adiposity and Ectopic Fat”. Obesity 20 (1): 76–87. doi:10.1038/oby.2011.142. PMID 21660078.

3. Ruderman Neil B.; Schneider, S. H.; Berchtold, P. (August 1981). “The “metabolically-obese,” normal-weight individual”. American Journal of Clinical Nutrition 34 (8): 1617–1621.

4. Jump up^ Conus, Florence; Rabasa-Lhoret, Rémi; Péronnet, François (2007). “Characteristics of metabolically obese normal-weight (MONW) subjects”.Applied Physiology, Nutrition, and Metabolism 32 (6): 4–12.doi:10.1139/H07-926. PMID 17332780.

5. Jump up^ De Lorenzo, A.; Martinoli, R.; Vaia, F.; Di Renzo, L. (December 2006). “Normal weight obese (NWO) women: an evaluation of a candidate new syndrome”. Nutrition, Metabolism & Cardiovascular Diseases 16 (8): 513–523. doi:10.1016/j.numecd.2005.10.010. PMID 17126766