Differentiating between body fat and lean mass—how should we measure obesity?

Arising from: Romero-Corral A et al. (2008) Differentiating between body fat and lean mass—how should we measure obesity? Nat Clin Pract Endocrinol Metab 4: 322–323 doi:10.1038/ncpendmet0809

In their recent article, Romero-Corral et al.¹ report on obesity as a factor of risk assessment in individuals with and without cardiovascular disease. They suggest that the “obesity paradox” is merely based on the inadequacy of BMI to differentiate between lean and fat mass. Against the background of obesity, the authors perceive adipose tissue as a plain cardiovascular risk factor and view lean mass as the protective element. It is argued that the favourable impact of elevated BMI results from the beneficial effects of lean tissue overriding the adverse effects of excess body fat. Romero-Corral et al. assume that accurate fat tissue assessment (such as dual-energy X-ray absorptiometry [DEXA]) may prove its nocuous impact. In chronic diseases, however, we propose to consider a more differentiated view on adipose tissue.

Fat tissue is the most important energy storage of the body providing over 80% of all energy reserves.² Chronic diseases, such as chronic heart failure (CHF), are characterized by an accelerated downward spiral of anabolic/catabolic imbalance and symptomatic status that leads to a particularly poor prognosis.³ Adipose tissue buffers its detrimental impact.

We have recently presented data from a study in 511 CHF patients in which body composition was assessed using DEXA for prognostic reasons.⁴ Notably, total fat mass (16.9 ± 7.9 kg vs 20.4 ± 8.2 kg, P <0.0001) and percent fat (23 ± 7% vs 26 ± 8%, P <0.0001) were significantly lower in non-survivors compared to survivors (median follow-up 29 months, 110 fatal events). In contrast, lean mass and fat distribution (i.e. ratio between central and peripheral fat) did not differ between the two groups. Total fat mass (hazard ratio [HR] 0.95, 95% CI 0.92–0.98; P = 0.0004) and percent fat (HR 0.94, 95% CI 0.91–0.97; P <0.0001) predicted better survival independently of New York Heart Association class, exercise capacity, and BMI. Quartiles of percent fat showed a linear stepwise decrease for risk with the best survival in quartile IV (HR 0.35, 95% CI 0.19–0.64; P = 0.0056) compared to the first quartile. Lean mass did not predict mortality.

Similar results were obtained by Kalantar-Zadeh et al.⁵ in 535 patients with chronic kidney disease receiving maintenance haemodialysis. In these subjects, body fat was assessed via near infrared interactance. After multivariate adjustment for demographics, surrogates for muscle mass and inflammation, the risk of death was 4 times higher for patients with a body fat <12% (n = 46), compared to a body fat content between 24% and 36% (n = 199) (HR 4.01, 95% CI 1.61–9.99; P = 0.003). Fat loss of ≤1%, re-assessed after 6 months, was associated with a doubled mortality risk compared to weight-gainers (≥1%, P = 0.04).

It remains undisputed that increasing body weight worsens cardiovascular and metabolic status in young and middle-aged subjects without co-morbidities. Excess adipose tissue, however, has been shown to improve outcomes in patients with already established chronic disease. Obesity represents anabolic dominance; hence, catabolic stimuli need to be much stronger to shift the metabolic balance towards catabolism. Furthermore, the eventually started catabolic spiral is protracted by an expanded access to energy deposits.