Risk assessment of diabetes among undergraduate students of Northern Maharashtra using Indian Diabetes Risk Score and its correlation with fasting blood glucose

Autor: Yogita G Bavaskar
Jazyk: angličtina
Rok vydání: 2024
Předmět:
Zdroj: MGM Journal of Medical Sciences, Vol 11, Iss 3, Pp 460-466 (2024)
Druh dokumentu: article
ISSN: 2347-7962
DOI: 10.4103/mgmj.mgmj_29_24
Popis: Background: Diabetes, once primarily associated with old age, is increasingly prevalent among young adults. The Indian Diabetes Risk Score (IDRS) employs four parameters—age, waist circumference, family history of diabetes, and physical activity—to screen for diabetes. This study aims to evaluate the risk and prevalence of diabetes and prediabetes in undergraduate medical students and to correlate these findings with their fasting glucose levels. Materials and Methods: A cross-sectional descriptive study was carried out among 336 undergraduate medical students in the Jalgaon district of Maharashtra. Data on socio-demographic and anthropometric factors were gathered using a structured, pre-tested questionnaire. Each participant’s IDRS score was calculated. Students were then invited to have their fasting blood glucose levels measured after an overnight fast. Results: The study surveyed 336 medical students, comprising 185 males (55.06%) and 151 females (44.94%). According to the IDRS, 5 students (1.49%) were categorized as high risk, 202 students (60.1%) as moderate risk, and 129 students (38.4%) as low risk for diabetes. Fasting blood glucose tests indicated that 3 students (0.90%) had impaired glucose tolerance, and 52 (15.48%) students were pre-diabetic. There was a statistically significant correlation between fasting blood glucose levels and IDRS (R = 0.466, P < 0.001). Conclusion: The risk of diabetes among the participating undergraduate students is alarmingly high, according to the IDRS score. The strong correlation between the IDRS and the blood glucose levels of the study participants demonstrates that the IDRS is a highly effective, cost-efficient tool for predicting diabetes risk.
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