TY - JOUR
T1 - Adiponectin index to assess metabolic syndrome and insulin resistance in obese adolescents
AU - Widjaja, Nur Aisiyah
AU - Irawan, Roedi
AU - Hanindita, Meta Herdiana
AU - Ardianah, Eva
N1 - Publisher Copyright:
© Open Access Article published under the Creative Commons Attribution CC-BY License
PY - 2024
Y1 - 2024
N2 - Background: Adiponectin level is decreased in obesity, and is suspected to be the cause of metabolic syndrome (MetS) and even linked with the onset of insulin resistance (IR). Adiponectin index (AI) has been used to determine IR and MetS in polycystic ovary syndrome (POCS). Objectives: To assess the usefulness of AI to determine IR and MetS in obese adolescents. Method: A cross sectional study was performed in obese adolescents from January to May 2020 in Sidoarjo and Surabaya Junior/High School, Indonesia. Results: AI had a weak negative correlation with body weight, waist circumference, hip circumference and body mass index. AI also correlated with triglyceride, systolic blood pressure, fasting insulin, Homeostatic Model Assessment for IR (HOMA-IR) and high-density lipoprotein cholesterol (HDL-c). Obese adolescent with MetS had bigger AI than non-MetS (0.21±0.18 vs. 0.13±0.09, p=0.0000). A similar phenomenon was seen in obese adolescents with IR (0.37±0.51 vs. 0.11±0.07, p=0.000). AI had a better prognostic value to determine IR than MetS, with larger area under curve (AUC), 0.890 vs. 0.606. Cut-off value to determine IR was <0.17, with sensitivity 81.3% and specificity 88.5%. Conclusions: AI is better to determine IR than MetS with a cut-off of <0.17 in obese adolescents.
AB - Background: Adiponectin level is decreased in obesity, and is suspected to be the cause of metabolic syndrome (MetS) and even linked with the onset of insulin resistance (IR). Adiponectin index (AI) has been used to determine IR and MetS in polycystic ovary syndrome (POCS). Objectives: To assess the usefulness of AI to determine IR and MetS in obese adolescents. Method: A cross sectional study was performed in obese adolescents from January to May 2020 in Sidoarjo and Surabaya Junior/High School, Indonesia. Results: AI had a weak negative correlation with body weight, waist circumference, hip circumference and body mass index. AI also correlated with triglyceride, systolic blood pressure, fasting insulin, Homeostatic Model Assessment for IR (HOMA-IR) and high-density lipoprotein cholesterol (HDL-c). Obese adolescent with MetS had bigger AI than non-MetS (0.21±0.18 vs. 0.13±0.09, p=0.0000). A similar phenomenon was seen in obese adolescents with IR (0.37±0.51 vs. 0.11±0.07, p=0.000). AI had a better prognostic value to determine IR than MetS, with larger area under curve (AUC), 0.890 vs. 0.606. Cut-off value to determine IR was <0.17, with sensitivity 81.3% and specificity 88.5%. Conclusions: AI is better to determine IR than MetS with a cut-off of <0.17 in obese adolescents.
KW - Adiponectin index
KW - Insulin resistance
KW - Metabolic syndrome
KW - Obese adolescents
UR - http://www.scopus.com/inward/record.url?scp=85188426907&partnerID=8YFLogxK
U2 - 10.4038/sljch.v53i1.10678
DO - 10.4038/sljch.v53i1.10678
M3 - Article
AN - SCOPUS:85188426907
SN - 1391-5452
VL - 53
SP - 9
EP - 14
JO - Sri Lanka Journal of Child Health
JF - Sri Lanka Journal of Child Health
IS - 1
ER -