Introduction
The role of insulin resistance in diabetic chronic complications among individuals with type 1 diabetes (T1D) has not been clearly defined. The aim of this study was to examine the performance of insulin resistance, evaluated using the estimated glucose disposal rate (eGDR) for the identification of metabolic syndrome (MS) and diabetic chronic complications.
Methods
Cross‐sectional study in a tertiary care centre. We included patients of 18 years and older, with at least 6 months of T1D duration. Anthropometric, clinical and biochemical data were collected.
Results
Seventy patients, 41 (58.6%) women, with a median age of 36.6 years (range 18–65). Mean age of onset and duration of diabetes was 13.5 ± 6.5 and 23.6 ± 12.2 years, respectively. Twenty‐one (30%) patients met the metabolic syndrome (MS) criteria. Patients with MS had lower eGDR compared to patients without (5.17 [3.10–8.65] vs. 8.86 [6.82–9.85] mg/kg/min, respectively, p = .003). Median eGDR in patients with nephropathy, retinopathy and neuropathy compared with those without was 6.75 (4.60–8.20) versus 9.53 (8.57–10.3); p < .001, 6.45 (4.60–7.09) versus 9.50 (8.60–10.14); p < .001, 5.56 (4.51–6.81) versus 9.49 [8.19–10.26] mg/kg/min; p < .001, respectively. The eGDR showed an area under the curve of 0.909, 0.879, 0.897 and 0.836 for the discrimination of MS, retinopathy, neuropathy and nephropathy, respectively.
Conclusions
Patients with T1D diabetic complications have higher insulin resistance. The eGDR discriminates patients with chronic diabetic complications and MS. While more ethnic‐specific studies are required, this study suggests the possibility to incorporate eGDR into routine diabetes care.
Aging is believed to occur across multiple domains, one of which is body composition; however, attempts to integrate it into biological age (BA) have been limited. Here, we consider the sex‐dependent role of anthropometry for the prediction of 10‐year all‐cause mortality using data from 18,794 NHANES participants to generate and validate a new BA metric. Our data‐driven approach pointed to sex‐specific contributors for BA estimation: WHtR, arm and thigh circumferences for men; weight, WHtR, thigh circumference, subscapular and triceps skinfolds for women. We used these measurements to generate AnthropoAge, which predicted all‐cause mortality (AUROC 0.876, 95%CI 0.864–0.887) and cause‐specific mortality independently of ethnicity, sex, and comorbidities; AnthropoAge was a better predictor than PhenoAge for cerebrovascular, Alzheimer, and COPD mortality. A metric of age acceleration was also derived and used to assess sexual dimorphisms linked to accelerated aging, where women had an increase in overall body mass plus an important subcutaneous to visceral fat redistribution, and men displayed a marked decrease in fat and muscle mass. Finally, we showed that consideration of multiple BA metrics may identify unique aging trajectories with increased mortality (HR for multidomain acceleration 2.43, 95%CI 2.25–2.62) and comorbidity profiles. A simplified version of AnthropoAge (S‐AnthropoAge) was generated using only BMI and WHtR, all results were preserved using this metric. In conclusion, AnthropoAge is a useful proxy of BA that captures cause‐specific mortality and sex dimorphisms in body composition, and it could be used for future multidomain assessments of aging to better characterize the heterogeneity of this phenomenon.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.