Tabarraei Yaser, Keshtkar Abbas Ali, Yekaninejad Mir Saeed, Rahimi Najme, Dowlatabadi Yousef, Azam Kamal
Department of Epidemiology and Biostatistics, School of Public Health, Tehran University of Medical Sciences, Tehran, Iran.
Department of Biostatistics and Epidemiology, Sabzevar University of Medical Sciences, Sabzevar, Iran.
Adv Biomed Res. 2024 Apr 27;13:30. doi: 10.4103/abr.abr_406_23. eCollection 2024.
Diabetes mellitus is a chronic metabolic disorder with substantial implications for public health. Understanding the factors influencing blood sugar fluctuations is crucial for effective diabetes management and prevention. This study aimed to evaluate factors associated with blood sugar changes in diabetic patients and healthy individuals attending the Sabzevar Persian Cohort Center, employing the growth curve model.
Data related to 589 diabetic patients and 589 non-diabetic patients participating in the Persian cohort study of Sabzevar were used. Due to the repetition of blood sugar measurements for each individual over time, we use the conditional latent growth curve model to examine intra-individual changes and variables that affect these changes over time.
The linear latent growth curve model, fitted with independent variables, exhibited a superior fit. The slope of the line for the diabetic group was measured at 1.78, while for the non-diabetic group, it was estimated to be -0.29. Within the diabetic group, the influence of age, the presence of fatty liver, and history of congenital heart disease (CHD) had a significant impact on the baseline (the intercept), and the effect of body mass index (BMI) on the changing trend of the response variable (slope) was also significant. In the non-diabetic group, significant effects were observed for age variables, BMI, family history of diabetes, and history of stroke in the family.
Overall, the linear latent growth curve model showed good performance in the evaluation of the factors related to blood sugar changes in diabetic patients and healthy people.
糖尿病是一种慢性代谢紊乱疾病，对公众健康有重大影响。了解影响血糖波动的因素对于有效的糖尿病管理和预防至关重要。本研究旨在采用生长曲线模型评估参加萨卜泽瓦尔波斯队列中心的糖尿病患者和健康个体血糖变化的相关因素。
使用了与参加萨卜泽瓦尔波斯队列研究的589名糖尿病患者和589名非糖尿病患者相关的数据。由于每个个体的血糖测量随时间重复进行，我们使用条件潜在生长曲线模型来检查个体内部变化以及随时间影响这些变化的变量。
拟合自变量的线性潜在生长曲线模型显示出更好的拟合效果。糖尿病组直线的斜率测量值为1.78，而非糖尿病组估计为-0.29。在糖尿病组中，年龄、脂肪肝的存在以及先天性心脏病（CHD）病史对基线（截距）有显著影响，体重指数（BMI）对响应变量变化趋势（斜率）的影响也很显著。在非糖尿病组中，年龄变量、BMI、糖尿病家族史以及家族中风病史有显著影响。
总体而言，线性潜在生长曲线模型在评估糖尿病患者和健康人群血糖变化相关因素方面表现良好。
