A recent study published in the journal Nature Reviews Endocrinology summarized the challenges associated with adiposity assessment in clinical settings.
Obesity increases cardiometabolic risks and decreases life expectancy. Nevertheless, elevated adiposity might not solely underlie this increased risk, as adipose tissue distribution in the body influences the risk of disease independent of weight. Thus, understanding adipose tissue distribution can provide insights into obesity pathophysiology and assist therapeutic approaches.
This requires accurate measurement of adipose tissue and its distribution, which is challenging, particularly in clinical settings. Several measurement techniques exist, and each offers different insights. Therefore, it is challenging to select a single, universal method. As such, the present study discussed how these challenges influence the interpretation of research data in the context of obesity and the design/implementation of clinical guidelines.
Perspective: The challenges of assessing adiposity in a clinical setting. Image Credit: Lightspring / Shutterstock
Adiposity differences across populations
Adipose tissue function varies based on its anatomical location. Besides, its function and distribution can differ between adults and children, ethnic groups, and males and females, warranting age-, sex-, and ethnicity-specific standards to analyze body composition. Assessing body composition changes associated with children’s growth is challenging as it occurs in spurts.
However, elevated body mass index (BMI) in adolescence is associated with a higher risk of disease later in life. Further, sex and ethnicity influence adiposity distribution and obesity prevalence in children. Patterns of adipose tissue distribution vary across ethnic groups, albeit the underlying mechanisms remain unclear.
Asian individuals typically have more visceral adipose tissue (VAT) than Europeans or Africans within the same obesity category, which might explain the increased T2DM risk in some Asian populations than in other ethnic populations. Notably, randomized trials reveal benefits from weight loss in all ethnic groups. Nevertheless, unreported ethnicity/race remains a problem; besides, White individuals are overrepresented in many clinical trials and risk-association studies.
Furthermore, females live longer with obesity or overweight without developing T2DM than males. This might primarily be due to adipose tissue distribution differences, as females have more gluteal and subcutaneous adipose tissue (SAT) with a pear-shaped distribution. In contrast, males have an apple-shaped distribution with more VAT.
Sex differences in adiposity appear during puberty and diminish at menopause. Menopause shifts the adipose tissue function and distribution towards a pattern reminiscent of males. Therefore, the biological actions of estrogen and its receptor are crucial to sex differences in adiposity. Moreover, females with elevated testosterone are at a higher risk of T2DM than those with normal testosterone levels, regardless of BMI and age.
Adiposity measurement in the clinic
Various methods and tools have been introduced to quantify body composition and adiposity, each with advantages and limitations. Their relevance relies on factors, including the required level of accuracy, specific population, and accessibility. BMI and other surrogate measures are poor predictors of metabolic risks and adipose tissue distribution. As such, measures that estimate the relative placement and proportion of adipose tissue, bone, and muscle are more valuable.
Anthropometrics are quantitative measures of the body to evaluate physical characteristics, such as weight, height, BMI, skinfold thickness, and circumference of the waist, limbs, and hip. BMI is easy to calculate and has been extensively used in obesity research and clinical practice. However, BMI has limitations; for instance, because BMI does not account for muscle mass, individuals with higher muscle mass may be misclassified as overweight or obese.
BMI is also not sensitive to lipid and adipose tissue distribution, which is critical to assessing metabolic health. Consequently, BMI is poorly associated with cardiometabolic outcomes. Further, while waist-to-height and waist-to-hip ratios and waist circumference are superior to BMI in cardiometabolic risk prediction, their clinical implementation is challenging.
For example, waist circumference is measured at the navel, but a drooping belly can displace the navel after weight loss. As such, repeat measures over time can be inaccurate. Sagittal abdominal diameter (SAD), the anteroposterior diameter of the abdomen, could be a promising alternative to these methods. SAD has been strongly associated with visceral adiposity, regardless of obesity, age, and sex.
Assessment of body composition
Body composition is the distribution and amount of lean tissue, bone, and adipose tissue. Bioelectrical impedance analysis (BIA) is the easiest and quickest method to predict body adiposity. However, BIA has limitations, which tend to overestimate adipose tissue percentage in children and underestimate it in adults.
Nevertheless, hydrostatic weighing is more accurate than BIA to assess total fat content. Notwithstanding, these techniques have limitations due to bone mineral density variations. Tomographic imaging methods are the best to assess the distribution of adipose tissue. Dual-energy X-ray absorptiometry (DXA) is the most used imaging technique.
While it is practical to use DXA due to its availability and accuracy, it has limitations regarding muscle quantity and VAT, as regional volumes are estimated using anatomical models and not measured. Besides, DXA cannot measure ectopic fat. Magnetic resonance imaging (MRI), unlike DXA and computed tomography (CT), does not involve ionizing radiation, allowing for longer acquisition times. However, a limitation of MRI is that scanning and image analysis are time-consuming.
Concluding remarks
Together, the challenges for adiposity measurement in clinical settings are profound. Using only BMI for adiposity measurement is not an option. While MRI and DXA are highly accurate for ectopic and visceral adiposity, it is challenging to deploy them at scale compared to anthropometric measures. The authors contend that SAD is the best and most straightforward measure of visceral adiposity. Overall, the debate on the best clinical adiposity measures ensues, and the team believes that improved strategies that better reflect adiposity distribution will be developed.
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