This study aimed to identify new clinical biomarkers that may improve the follow-up and health outcomes of adolescents with type 1 diabetes. The current clinical practice includes a standard set of measurements for monitoring glycemic control and general health. However, other parameters such as phase angle (obtained through a fast, simple, and painless body composition analysis) might also provide valuable insight into the metabolic status of these patients. This is a cross-sectional observational study that involved a one-time data collection process. Participants underwent a single body composition measurement (10 seconds, using a bioimpedance analyzer). No interventions or follow-up visits were required. Additional data was extracted from medical records, including clinical information (e.g., age of diabetes onset, HbA1c, anthropometrics) and results from recent blood tests. The goal is to determine whether indicators such as the phase angle and triglyceride-glucose (TyG) index could serve as non-invasive tools to assess glycemic control, glycaemic control and cardiovascular risk in adolescents with type 1 diabetes. The study was conducted at two hospitals from Alicante (Spain) and included patients with a confirmed diagnosis of type 1 diabetes who met the inclusion criteria. Participation was entirely voluntary with informed consent obtained from legal guardians. All collected data were anonymized to prevent reidentification and unauthorized access. This research seeks to expand scientific knowledge on diabetes management and support the development of more precise, individualized monitoring tools for young people living with type 1 diabetes.
This cross-sectional study was conducted in the General Hospital of Elche and the San Juan Hospital (Alicante, Spain). The assessment of glycemic control was conducted through the analysis of variables derived from continuous glucose monitoring (CGM), specifically focusing on metrics such as time in range (TIR) and the coefficient of glucose variability (CV), which provide detailed insights into glucose fluctuations and stability over time. Additionally, glycated hemoglobin (HbA1c) was taken into account and measured directly during the medical appointment using the Alere Afinion AS100 Analyzer (Abbott, Illinois, United States) device. Body composition was evaluated using a bioelectrical impedance device (Biody-Xpert) and cardiovascular risk was estimated by calculating established indices based on biochemical markers, including the triglyceride to high-density lipoprotein cholesterol (TG/HDL) ratio, as well as anthropometric and body composition-derived indices, such as the fat mass index (FMI), defined as fat mass normalized to height squared (kg/m²). These multidimensional approaches allowed for a comprehensive evaluation of metabolic control, body composition and cardiovascular risk factors in adolescents with type 1 diabetes, facilitating the exploration of phase angle and the triglyceride-glucose (TyG) index as potential non-invasive biomarkers.
Study Type
OBSERVATIONAL
Enrollment
73
This is an observational, cross-sectional study with no intervention. Data were collected through a single body composition measurement without any treatment or manipulation. Biochemical, clinical and anthropometric data was collected directly from the patient's clinical records. No intervention was needed.
Hospital General Universitario de Elche
Elche, Alicante, Spain
Phase angle
Measurement of the phase angle using bioelectrical impedance analysis to assess body composition and cellular health in adolescents with type 1 diabetes by using the portable device Biody-Xpert (Aminogram SAS, La Ciotat, France).
Time frame: Day 1.
Triglyceride-glucose index (TyG index)
Calculation of the TyG index from recent fasting blood samples to evaluate insulin resistance and glycaemic control. The TyG index was calculated as Ln\[fasting triglycerides (mg/dl) x fasting glucose (mg/dl)/2\].
Time frame: Day 1
Predictive variable: Fat mass
Includes body fat mass (total amount of fat tissue in the body) in two measurements: % and Kg. These variables were measured using a bioelectrical impedance device and analyzed for their correlation with primary outcomes (phase angle and TyG index).
Time frame: Day 1.
Predictive variable: Skeletal muscle mass
Includes skeletal muscle mass (mass of muscles attached to bones for movement) in two measurements: % and Kg. These variables were measured using a bioelectrical impedance device and analyzed for their correlation with primary outcomes (phase angle and TyG index).
Time frame: Day 1.
Predictive variable: Fat free mass
Includes body fat-free mass (total body mass excluding all fat tissue) in two measurements: % and Kg. These variables were measured using a bioelectrical impedance device and analyzed for their correlation with primary outcomes (phase angle and TyG index).
Time frame: Day 1.
Predictive variable: Lean mass
Includes lean body mass (all non-fat components, including muscles and organs) in two measurements: % and Kg. These variables were measured using a bioelectrical impedance device and analyzed for their correlation with primary outcomes (phase angle and TyG index).
Time frame: Day 1.
Predictive variable: Total body water
Total body water (total amount of water in the body) was assessed in liters (L) using a bioelectrical impedance device and analyzed for its correlation with the primary outcomes: phase angle and TyG index.
Time frame: Day 1.
Predictive variable: Intracellular water
Intracellular water (water contained within cells) was assessed inn liters (L) using a bioelectrical impedance device and analyzed for its correlation with the primary outcomes: phase angle and TyG index
Time frame: Day 1
Predictive variable: Extracellular water
Extracellular water (water found outside cells, including plasma and interstitial fluid) was assessed in liters (L) using a bioelectrical impedance device and analyzed for its correlation with the primary outcomes: phase angle and TyG index
Time frame: Day 1
Predictive variables: Biochemical Variables
Includes HbA1c, total cholesterol, HDL cholesterol, LDL cholesterol, triglycerides and fasting blood glucose. These values were obtained from the participant's most recent clinical laboratory results and analyzed for correlation with the primary outcomes (phase angle and TyG index).
Time frame: Day 1
Predictive variable: Weight
Wight (body mass measured in kilograms (kg)) was measured using a Seca brand scale.
Time frame: Day 1.
Predictive variable: Height
Height (body length measured in centimeters (cm)) was measured using a Seca brand scale.
Time frame: Day 1.
Predictive variable: Body Mass Index (BMI)
Body mass index (BMI) was calculated as weight (kg) divided by height squared (m²) and serves as an indicator of body fatness. This measurement was obtained at the study visit and analyzed as a potential predictor of the primary outcomes (phase angle and TyG index).
Time frame: Day 1.
Predictive variable: BMI Percentile.
Relative position of BMI compared to a reference population, expressed as a percentile (%). This measurement was obtained at the study visit and analyzed as a potential predictor of the primary outcomes (phase angle and TyG index).
Time frame: Day 1.
Predictive variable: BMI Z-score
Standard deviation score indicating how far BMI deviates from the population mean. This measurement was obtained at the study visit and analyzed as a potential predictor of the primary outcomes (phase angle and TyG index).
Time frame: Day 1
Predictive variable: Time in Range (TIR)
Average percentage of time blood glucose levels remained within the target range over the past 3 months. This measurement was obtained at the study visit and analyzed as a potential predictor of the primary outcomes (phase angle and TyG index).
Time frame: Day 1
Predictive variable: Coefficient of Glycaemic Variation (CV)
Average measure of fluctuations in blood glucose levels over the past 3 months. This measurement was obtained at the study visit and analyzed as a potential predictor of the primary outcomes (phase angle and TyG index).
Time frame: Day 1
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