Tabarraei Yaser, Azam Kamal, Baghbani Bita, Kazemzadeh Asghar, Rahimi Najme, Dowlatabadi Yousef, Kamranian Houman, Vosoghi Afsaneh
Iranian Research Center on Health Aging, Sabzevar University of Medical Sciences, Sabzevar, Iran.
Department of Epidemiology and Biostatistics, School of Public Health, Tehran University of Medical Sciences, Tehran, Iran.
Adv Biomed Res. 2025 Jul 21;14:61. doi: 10.4103/abr.abr_473_24. eCollection 2025.
Diabetes, which is characterized by an increase in blood sugar levels, costs a lot of money every year for its treatment and complications due to incorrect treatment and improper control. The purpose of this study was to investigate the trend of blood sugar changes in diabetic patients using the latent growth curve model.
In this study, data related to diabetic patients participating in Persian cohort study of Sabzevar city were used. To examine intraindividual variation, due to repeated blood glucose measurements for each individual over time, a latent growth curve model was fitted to the data. Analyses were performed with Mplus software version 6.12.
Diabetic subjects with an average blood sugar of 168.92 were included in the study. During the study period, their blood sugar increased by an average of 1.74 mg/dL. It was also found that people who had lower blood sugar at the beginning of the study experienced less changes in blood sugar during the study.
In this study, the increasing and nonlinear trend of blood sugar in diabetic patients was shown in a longitudinal study with the help of latent growth curve model. Because this model is much easier to interpret the coefficients in it than similar models, it is suggested as a suitable method to find the pattern of variable changes in medical sciences.
糖尿病以血糖水平升高为特征，由于治疗不当和控制不佳，其治疗及并发症每年耗费大量资金。本研究的目的是使用潜在增长曲线模型调查糖尿病患者血糖变化趋势。
在本研究中，使用了与参与萨卜泽瓦尔市波斯队列研究的糖尿病患者相关的数据。为了检验个体内变异，由于对每个个体随时间进行多次血糖测量，对数据拟合了潜在增长曲线模型。使用Mplus软件6.12版进行分析。
平均血糖为168.92的糖尿病受试者被纳入研究。在研究期间，他们的血糖平均升高了1.74mg/dL。还发现研究开始时血糖较低的人在研究期间血糖变化较小。
在本研究中，借助潜在增长曲线模型在纵向研究中显示了糖尿病患者血糖的增加和非线性趋势。由于该模型比类似模型更容易解释其中的系数，建议将其作为在医学科学中寻找变量变化模式的合适方法。
