Karri Anjan Kumar, Guthi Visweswara Rao, Githa P Sri Sai
Department of Community Medicine, SVIMS-Sri Padmavathi Medical College for Women, Tirupati, Andhra Pradesh, India.
J Family Med Prim Care. 2024 Nov;13(11):5312-5319. doi: 10.4103/jfmpc.jfmpc_929_24. Epub 2024 Nov 18.
Approximately 500 million individuals worldwide are known to have diabetes, representing roughly 1 out of every 11 adults in the world. Approximately 45.8% of adult diabetes cases are believed to be undiagnosed.
This study aimed to identify the predictors for high blood glucose and to develop a risk score which helps in early detection of high blood glucose among Indian men (15-54 years) and women (15-49 years).
This study utilised data from the National Family Health Survey-5, which were gathered between 2019 and 2021. The study population comprises women aged 15-49 years and men aged 15-54 years in India.
A logistic regression analysis was conducted to determine the predictors of high blood glucose. The results were expressed as odds ratios with 95% confidence intervals. The risk score for high blood glucose was derived through variable shrinking and by employing regression coefficients obtained from the standard logistic regression model. Data were analysed using IBM SPSS version 26.
The prevalence of high blood glucose in India was 9.3%. The study findings indicated an association between age and the occurrence of high blood glucose levels. The prevalence of high blood glucose was higher among males (11.1% vs 7.5%), individuals living in urban areas (10.7% vs 8.9%), those with a waist circumference exceeding the specified limit (11.7% vs 5.9%), and individuals who were overweight or obese (11.3%). The prevalence of high blood glucose was higher among alcoholics (13.2% vs 8.8%) and various forms of tobacco users (12.1% vs 8.4%).
Age, sex, place of residence (urban), consumption of alcohol, hypertension, and waist circumference were found to be the significant predictor variables and were used to develop the risk prediction score using the logistic regression model.
全球约有5亿人患有糖尿病，约占全球每11名成年人中的1人。据信，约45.8%的成年糖尿病病例未被诊断出来。
本研究旨在确定高血糖的预测因素，并制定一个风险评分，以帮助早期发现印度15至54岁男性和15至49岁女性中的高血糖情况。
本研究利用了2019年至2021年期间收集的全国家庭健康调查-5的数据。研究人群包括印度15至49岁的女性和15至54岁的男性。
进行逻辑回归分析以确定高血糖的预测因素。结果以95%置信区间的比值比表示。高血糖风险评分是通过变量收缩并采用从标准逻辑回归模型获得的回归系数得出的。使用IBM SPSS 26版对数据进行分析。
印度高血糖的患病率为9.3%。研究结果表明年龄与高血糖水平的发生之间存在关联。男性（11.1%对7.5%）、居住在城市地区的人（10.7%对8.9%）、腰围超过规定限值的人（11.7%对5.9%）以及超重或肥胖的人（11.3%）中高血糖的患病率较高。酗酒者（13.2%对8.8%）和各类烟草使用者（12.1%对8.4%）中高血糖的患病率也较高。
年龄、性别、居住地点（城市）、饮酒、高血压和腰围被发现是重要的预测变量，并用于使用逻辑回归模型制定风险预测评分。
