Obesity and Weight Loss
Diagnosis and Assessment of Obesity
Obesity is typically diagnosed and defined by analysis of body size, weight, and composition. Body mass index (BMI) is the most commonly accepted metric for defining obesity; it is a surrogate measurement of adiposity, calculated as body mass (in kilograms) divided by height squared (in meters). Alternatively, it can be calculated in Imperial units as [weight (in pounds) / height2 (in inches)] x 703 (Expert Treatment Panel 1998). The World Health Organization (WHO) definitions of overweight and obese are BMIs of ≥25 and ≥30 kg/m2, respectively (World Health Organization 1998).
WHO Classification of weight status by BMI: (World Health Organization 2000)
|Obese class I||30-34.9|
|Obese class II||35-39.9|
|Obese class III/Morbid obesity||≥40|
Although BMI is strongly correlated with total body fat, it is not without limitations. For example, there are significant racial considerations that can influence its interpretation (eg, Asians typically carry more body fat, and Africans less, than Caucasians at any particular BMI). BMI overestimates body fat content for individuals with high muscle mass (such as athletes). Additionally, BMI cannot measure some changes in body composition; for example, the concurrent loss of lean muscle and increase in body fat in aging individuals might not result in a change in their BMI (Prentice 2001). Alternative measurements (eg, skin-fold thickness and waist-to-hip ratio) have been suggested as more accurate methods for body fat estimation, but in terms of predicting clinical outcomes, BMI has shown similar accuracy to these techniques and remains an acceptable measurement despite its shortcomings (Thomas 2011). BMI can be combined with waist circumference measurements, which can estimate an individual’s abdominal fat content (abdominal or visceral fat is a greater risk factor for obesity-related diseases than total body fat). Waist circumference measurements of >102 cm (40 in.) for men, and >88 cm (35 in.) for women carry high risk of obesity-associated disease (eg, type 2 diabetes, cardiovascular disease, and hypertension) (Expert Treatment Panel 1998).
Study funded by Life Extension Foundation® Reveals Inadequacies of Conventional BMI Measurements
The most widely used tool to assess weight-related health status is the calculated body mass index (BMI), despite several shortcomings. Although a number of studies and analyses have established relatively consistent associations between various BMI ranges and risk of several diseases, the technique is unable to provide an accurate determination of body fat percentage (Owen 2009; Corley 2006). This leads to inevitable oversights as to obesity-related risks given the variation in adipose tissue distribution between individuals.
Scientists at the frontiers of obesity research recognize the inadequacy of relying on calculated BMI measurements and are vigorously investigating methods to circumvent its shortcomings.
A groundbreaking 2012 study supported by a grant from the non-profit Life Extension Foundation® meticulously examined the discrepancy between BMI-diagnosed obesity and obesity determined as a function of body fat content assessed by dual energy x-ray absorptiometry (DXA), a highly accurate, albeit expensive and cumbersome method of measuring body fat. This study evaluated 11 years of records pertaining to nearly 1400 patients for whom DXA-determined body fat and BMI measurements had been captured.
The results showed that BMI was a poor indicator of body fat content and may result in the underdiagnosis and undertreatment of individuals at risk for obesity-related diseases. Measurement of BMI alone was shown to be especially prone to underestimation of obesity in aging women: 48% of women classified non-obese by BMI calculation were found to be obese when body fat percentage was determined by DXA.
The authors of this study simultaneously examined correlates between blood levels of leptin and DXA-determined body fat content; they found that leptin levels emulated the DXA findings in many cases.
Therefore, the researchers suggest blood levels of leptin can complement calculated BMI measurements to improve detection of obesity. For example, if a person has a “normal” BMI, but has very high leptin levels, they may still be at risk for obesity-related diseases and may benefit from anti-obesity intervention. Likewise, if a person with a BMI typically classified as “overweight” has low leptin levels, they may be at lower risk and not require aggressive anti-obesity intervention (Shah 2012).
While direct measurement of body fat by DXA remains a premium choice for determination of obesity-related disease, its high cost and limited availability make it an unreasonable option for many people. Emerging evidence suggests, however, that augmenting a calculated BMI measurement with leptin blood testing may help physicians determine patients’ risks with improved clarity.