Comparative Study of Ultrasonographic and Anthropometric Measurements of Regional Adiposity in Metabolic Syndrome

Abdominal fat depots and their association with insulin resistance in patients with type 2 diabetes

BACKGROUND

Asian-Indians show thin fat phenotype, characterized by predominantly central deposition of excess fat. The roles of abdominal subcutaneous fat (SAT), intra-peritoneal adipose tissue, and fat depots surrounding the vital organs (IPAT-SV) and liver fat in insulin resistance (IR), type-2 diabetes (T2D) and metabolic syndrome (MetS) in this population are sparsely investigated.

AIMS AND OBJECTIVES

Assessment of liver fat, SAT and IPAT-SV by MRI in subjects with T2D and MetS; and to investigate its correlation with IR, specifically according to different quartiles of HOMA-IR.

METHODS

Eighty T2D and the equal number of age sex-matched normal glucose tolerant controls participated in this study. Abdominal SAT, IPAT-SV and liver fat were measured using MRI. IR was estimated by the Homeostatic Model Assessment for Insulin Resistance (HOMA-IR).

RESULTS

T2D and MetS subjects have higher quantity liver fat and IPAT-SV fat than controls (P = 9 x 10-4 and 4 x 10-4 for T2D and 10-4 and 9 x 10-3 for MetS subjects respectively). MetS subjects also have higher SAT fat mass (P = 0.012), but not the BMI adjusted SAT fat mass (P = 0.48). Higher quartiles of HOMA-IR were associated with higher BMI, W:H ratio, waist circumference, and higher liver fat mass (ANOVA Test P = 0.020, 0.030, 2 x 10-6 and 3 x 10-3 respectively with F-values 3.35, 3.04, 8.82, 4.47 respectively). In T2D and MetS subjects, HOMA-IR showed a moderately strong correlation with liver fat (r = 0.467, P < 3 x 10-5 and r = 0.493, P < 10-7), but not with SAT fat and IPAT-SV. However, in MetS subjects IPAT-SV fat mass showed borderline correlation with IR (r = 0.241, P < 0.05), but not with the BMI adjusted IPAT-SV fat mass (r = 0.13, P = 0.26). In non-T2D and non-MetS subjects, no such correlation was seen. On analyzing the correlation between the three abdominal adipose compartment fat masses and IR according to its severity, the correlation with liver fat mass becomes stronger with increasing quartiles of HOMA-IR, and the strongest correlation is seen in the highest quartile (r = 0.59, P < 10-3). On the other hand, SAT fat mass tended to show an inverse relation with IR with borderline negative correlation in the highest quartile (r = -0.284, P < 0.05). IPAT-SV fat mass did not show any statistically significant correlation with HOMA-IR, but in the highest quartile it showed borderline, but statistically insignificant positive correlation (P = 0.07).

CONCLUSION

In individuals suffering from T2D and MetS, IR shows a trend towards positive and borderline negative correlation with liver fat and SAT fat masses respectively. The positive trend with liver fat tends to become stronger with increasing quartile of IR. Therefore, these findings support the theory that possibly exhaustion of protective compartment's capacity to store excess fat results in its pathological deposition in liver as ectopic fat.

Caution, "normal" BMI: health risks associated with potentially masked individual underweight-EPMA Position Paper 2021

An increasing interest in a healthy lifestyle raises questions about optimal body weight. Evidently, it should be clearly discriminated between the standardised "normal" body weight and individually optimal weight. To this end, the basic principle of personalised medicine "one size does not fit all" has to be applied. Contextually, "normal" but e.g. borderline body mass index might be optimal for one person but apparently suboptimal for another one strongly depending on the individual genetic predisposition, geographic origin, cultural and nutritional habits and relevant lifestyle parameters-all included into comprehensive individual patient profile. Even if only slightly deviant, both overweight and underweight are acknowledged risk factors for a shifted metabolism which, if being not optimised, may strongly contribute to the development and progression of severe pathologies. Development of innovative screening programmes is essential to promote population health by application of health risks assessment, individualised patient profiling and multi-parametric analysis, further used for cost-effective targeted prevention and treatments tailored to the person. The following healthcare areas are considered to be potentially strongly benefiting from the above proposed measures: suboptimal health conditions, sports medicine, stress overload and associated complications, planned pregnancies, periodontal health and dentistry, sleep medicine, eye health and disorders, inflammatory disorders, healing and pain management, metabolic disorders, cardiovascular disease, cancers, psychiatric and neurologic disorders, stroke of known and unknown aetiology, improved individual and population outcomes under pandemic conditions such as COVID-19. In a long-term way, a significantly improved healthcare economy is one of benefits of the proposed paradigm shift from reactive to Predictive, Preventive and Personalised Medicine (PPPM/3PM). A tight collaboration between all stakeholders including scientific community, healthcare givers, patient organisations, policy-makers and educators is essential for the smooth implementation of 3PM concepts in daily practice.