Obesity is known to have an insidious onset and predisposes toward several metabolic disturbances that threaten human health. Excessive ectopic accumulation of adipose tissue in the body and changes in body composition are crucial factors in the development of obesity-related insulin resistance and T2DM, as well as affect the glycemic control. A retrospective cohort study indicated that baseline BMI is one of the most accurate predictors of the future glycemic control in T2DM patients. Previous cross-sectional study has also showed that HbA1c was significant and positive associated with increased waist circumference in T2DM participants. However, the parameter of BMI or waist circumference to assess obesity-related complications is not enough. In this study, we elaborated on the correlation between body composition, assessed by bioelectrical impedance analyzer (BIA), and TIR assessed by CGM in T2DM patients during short-term intensive insulin pump therapy. Our findings showed that body composition, particularly high body fat percentage may contribute to decreased TIR in obese T2DM population. To the best of our knowledge, this was the first study to evaluate the association between body composition and CGM-assessed TIR especially during short-term intensive insulin pump therapy in Chinese obese T2DM patients.
As a convenient, practical and less invasive method to assess body composition, BIA was widely used in clinical practice. A cross-sectional study has demonstrated that total body fat mass assessed by BIA were strongly associated with insulin resistance in T2DM. Besides, Hameed EK et al. studied the impact of visceral fat in T2DM and found that visceral adiposity index was positively associated with the presence of T2DM and had a significant negative outcome over glycemic control[24, 25]. Since ectopic fat accumulation was significantly related to body fat percentage measured by BIA in a previous study, it is possible that body fat percentage can reflect ectopic fat quantity and may become an optimal predictor of T2DM glycemia management. Currently, the results of our study showed that body fat percentage was significantly and independently correlated with glycemia control. We also found a poor controlled glycemia in T2DM patients with relatively high body fat percentage during intensive hypoglycemic therapy, suggesting the accumulation of body fat may be the main cause of the poor glycemia control in obese T2DM populations.
Intensive insulin pump therapy has been of value in T2DM who fail to achieve optimal glycemic control. More physiological delivery of insulin by the pump has been proven for reduction of glucose toxicity, resulting in improvement of insulin resistance in obese T2DM patients. With advances in CGM technology, time in range (TIR) of 3.9–10 mmol/L has been introduced by the 2020 ADA guidelines as an intuitive and key parameter of short-term glycemic management. A series of previous studies have also shown that TIR not only could be used to assess the risk of microvascular complications[9, 11, 29], but also predict the all-cause mortality from cardiovascular events in T2DM, further supporting TIR as an acceptable glucose metric as well as a reasonable end point for clinical trials. In the current study, with ascending tertiles of TIR, the percentage of overfat patients classified by body fat percentage decreased as compared to other grouping methods (such as BMI, waist circumference or visceral fat area), suggesting body fat percentage may had a more significant negative outcome over glycemic control during intensive insulin pump therapy. Recently, a study demonstrated that regardless of mean glucose, HbA1c or glycemic variability metrics had an impact on TIR[31, 32]. Based on the previous study, we further found a robust correlation between body fat percentage and TIR even after adjusting for these above factors. Besides, the effect of body fat percentage on TIR was also independent of other body composition parameters, including waist circumference, visceral fat area and muscle quantity. However, it is notable that the adjustment for BMI, to some extent attenuated the association of body fat percentage with TIR. A possible explanation could be a significant correlation between body fat percentage and BMI in our study samples (r = 0.492; P<0.001; data not shown), resulting in multicollinearity in the linear regression model and thereby affect the result. Nevertheless, our study provides evidence of an independent effect of body fat percentage on TIR.
Furthermore, glycemic variability was also taken into consideration in our study when evaluating quality of glycemic control during insulin pump therapy in T2DM. A previous cross-sectional study reported that subjects with a higher BMI or waist circumference had higher levels of 72-h MBG assessed by CGM system. Our study was in consistent with the result of previous study, demonstrating a higher levels of 72-h MBG in obese T2DM patients than that of non-obese ones during insulin pump therapy. However, the decreased of glycemic variability CV was observed in patients with high body fat percentage. Among glycemic variability parameters, CV was significantly correlated with the risk of hypoglycemia. In the current study, TBR, defined as the percentage of time spent below the target glucose range (༜3.9 mmol/L), was lower in participants with higher body fat percentage, indicating the risk of hypoglycemic was relatively decreased during intensive insulin pump therapy in obese subjects. A previous study reported that obese patients exhibited a little bit better pancreatic β-cell function in comparison with that observed in the non-obese subjects, which may contribute to decreased glucose fluctuation in T2DM individual with relatively high body fat percentage.
Several limitations of this study should be addressed. First, this was a cross-sectional study, and thus we could not examine the causal relationship between body composition and TIR. In addition, the measurement of TIR for a 72-h period may not represent the glycemic control of the participants during the whole period of intensive insulin pump therapy. Besides, considering the small overall sample size in our study, the results be replicated in larger study populations is warranted. Finally, we estimated body composition based on the BIA, not by the “gold standard” method, such as computer tomography (CT) and Magnetic resonance imaging (MRI); however, CT or MRI is expensive and not easily feasible in a relatively large-scale study, and we believe that proxy measures are reliable according to the previous studies.