ArticleAdvanced biomedical research2024
A Longitudinal Examination of Blood Sugar Dynamics in Diabetes and Non-Diabetes Using Growth Curve Model: The Sabzevar Persian Cohort Study.
Article in Advanced biomedical research, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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1 citing paper in PubMed.
- Estimating the Trend of Blood Sugar Changes in Diabetic Patients Using the Latent Growth Curve Model a Longitudinal Cohort Study.Advanced biomedical research · 2025Article
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6 authors.
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Abstract
Background: 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. Materials and Methods: 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. Results: 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. Conclusion: 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.
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