Relationship between DXA measured metrics of adiposity and glucose homeostasis; An analysis of the NHANES data

Connections between body composition and dysregulation of islet α- and β-cells in type 2 diabetes

BACKGROUND

Accompanying islet α- and β-cell dysregulation in type 2 diabetes (T2D) at the microscopic scale, alterations in body composition at the macroscopic scale may affect the pathogenesis of T2D. However, the connections between body composition and islet α-cell and β-cell functions in T2D have not been thoroughly explored.

METHODS

For this cross-sectional study, we recruited a total of 729 Chinese Han patients with T2D in a consecutive manner. Dual-energy X-ray absorptiometry (DXA) was used to measure body composition, which included total bone-free mass, total fat and lean mass, trunk fat and lean mass and limb fat and lean mass. Every patient underwent an oral glucose tolerance test to simultaneously detect glucose, C-peptide and glucagon. The indices of islet α-cell function included fasting glucagon levels and the area under the curve of glucagon after a challenge (AUCglucagon), while the indices of β-cell function included the insulin sensitivity index derived from C-peptide (ISIC-peptide) and the area under the curve of C-peptide after a challenge (AUCC-peptide).

RESULTS

Among all patients, fat mass, especially trunk fat mass, was significantly correlated with ISIC-peptide and AUCC-peptide levels (r = - 0.330 and 0.317, respectively, p < 0.001), while lean mass, especially limb lean mass, was significantly correlated with fasting glucagon and AUCglucagon levels (r = - 0.196 and - 0.214, respectively, p < 0.001). Moreover, after adjusting for other relevant variables via multivariate linear regression analysis, increased trunk fat mass was independently associated with decreased ISIC-peptide (β = - 0.247, t = - 3.628, p < 0.001, partial R2 = 10.9%) and increased AUCC-peptide (β = 0.229, t = 3.581, p < 0.001, partial R2 = 8.2%), while decreased limb lean mass was independently associated with increased fasting glucagon (β = - 0.226, t = - 2.127, p = 0.034, partial R2 = 3.8%) and increased AUCglucagon (β = - 0.218, t = - 2.050, p = 0.041, partial R2 = 2.3%). Additionally, when separate analyses were performed with the same concept for both sexes, we found that increased trunk fat mass was still independently associated with decreased ISIC-peptide and increased AUCC-peptide, while decreased limb lean mass was still independently associated with increased fasting glucagon and AUCglucagon.

CONCLUSIONS

Increased trunk fat mass may partly account for decreased insulin sensitivity and increased insulin secretion, while decreased limb lean mass may be connected to increased fasting glucagon and postprandial glucagon secretion.

Estimation of Absolute and Relative Body Fat Content Using Noninvasive Surrogates: Can DXA Be Bypassed?

Dual-energy x-ray absorptiometry (DXA) scanning is used for objective determination of body composition, but instrumentation is expensive and not generally available in customary clinical practice. Anthropometric surrogates are often substituted as anticipated correlates of absolute and relative body fat content in the clinical management of obesity and its associated medical risks. DXA and anthropometric data from a cohort of 9230 randomly selected American subjects, available through the ongoing National Health and Nutrition Examination Survey, was used to evaluate combinations of surrogates (age, height, total weight, waist circumference) as predictors of DXA-determined absolute and relative body fat content. Multiple regression analysis yielded linear combinations of the 4 surrogates that were closely predictive of DXA-determined absolute fat content (R2  = 0.93 and 0.96 for male and female subjects). Accuracy of the new algorithm was improved over customary surrogate-based predictors such as body mass index. However prediction of relative body fat was less robust (R2  less than 0.75), probably due to the nonlinear relation between degree of obesity (based on body mass index) and relative body fat. The paradigm was validated using an independent cohort from the National Health and Nutrition Examination Survey, as well as two independent external subject groups. The described regression-based algorithm is likely to be a sufficiently accurate predictor of absolute body fat (but not relative body fat) to substitute for DXA scanning in many clinical situations. Further work is needed to assess algorithm validity for subgroups of individuals with "atypical" body construction.

Association between Fat Distribution and Chronic Low Back Pain among 10,606 Adults: Data from the Korean National Health and Nutrition Examination Survey

Obesity is associated with chronic low back pain (CLBP), but the association between fat distribution and CLBP is unclear. This cross-sectional study evaluated the relationship using the Korean National Health and Nutrition Examination Survey data. A total of 10,606 adults (average age: 45.4, female: 57.1%) were included. We estimated the regional fat distribution, waist circumference, and body fat proportion, compared the values in people with and without CLBP, and stratified the estimates by sex and obesity status using a multivariable linear model. There were no statistically significant differences in the average waist circumference between the people with and without CLBP (p = 0.731) and the average fat proportion between those with and without CLBP (p = 0.731). The average regional fat distribution was significantly higher in the people with CLBP than in those without CLBP, in the upper limbs (11.4%, 95% confidence interval [CI]: [11.3, 11.5] vs. 11.2%, 95% CI: [11.1, 11.3], p < 0.05) and in the lower limbs (31.9%, 95% CI: [31.6, 32.2] vs. 31.4%, 95% CI: [31.2, 31.6], p < 0.01). More obvious among men, fat distribution in the lower limbs is higher than in people without obesity (p < 0.001). People with CLBP tend to have a higher fat distribution in the limbs than those without it and obese people with CLBP would need to reduce the fat in the lower limbs.