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Cluster analysis based on fasting and postprandial plasma glucose and insulin concentrations

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International Journal of Diabetes in Developing Countries Aims and scope Submit manuscript

Abstract

Objective

Plasma glucose and insulin concentrations are clinical markers used to diagnose metabolic diseases, particularly prediabetes and diabetes. In this paper, we conducted a cluster analysis using plasma glucose and insulin data collected during both fasting and 2-h postprandial periods.

Methods

Different clustering experiments were performed by changing the attributes, from one (fasting glucose) to four (fasting and postprandial glucose and insulin) attributes input to a k-means clustering algorithm. Based on the elbow and silhouette methods, three clusters were chosen to perform the clustering experiments. The Pearson correlation coefficient was utilized to evaluate the association between the levels of glucose and insulin within each created cluster.

Results

Results show that one cluster comprised individuals with prediabetes, another cluster consisted of individuals with diabetes, while subjects without prediabetes and diabetes were assigned to a separate cluster. Despite not being used as an attribute, we observed varying age ranges among subjects in the three clusters. Furthermore, significant correlations were found between fasting and postprandial insulin levels, as well as between fasting and postprandial glucose levels, suggesting a consistent relationship between these variables, and highlighting their interdependence in the context of glucose metabolism.

Conclusion

The clustering analysis successfully differentiated individuals into distinct clusters based on their metabolic conditions, confirming that the approach effectively captured the underlying patterns in the plasma glucose and insulin data. Furthermore, despite not being a considered attribute, the varying age ranges observed within the clusters indicate that age may play a role in the development and progression of diabetes. Additionally, the fasting and postprandial associations in insulin and glucose levels exhibited greater strength in the cluster encompassing individuals with diabetes, where insulin production or action is compromised.

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Data availability

The dataset used in this study is freely available at https://ieee-dataport.org/documents/fasting-and-postprandial-glucose-and-insulin-dataset.

Code availability

The code used in this study is freely available at https://doi.org/10.24433/CO.7408455.v1 and at https://github.com/miguelaltuve/ClusterAnalysisBasedFastingPostprandialGlucoseInsulin.

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Authors and Affiliations

  1. Valencian International University, Valencia, Spain

    Miguel Altuve & Erika Severeyn

  2. Applied Biophysics and Bioengineering Group, Simon Bolivar University, Caracas, Venezuela

    Miguel Altuve & Erika Severeyn

Authors
  1. Miguel Altuve
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  2. Erika Severeyn
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Contributions

Miguel Altuve carried out the experiments and contributed to the conception of the study and the writing and revising of the manuscript. Erika Severeyn contributed to the conception of the study, the analysis of the results, and the writing and revising of the manuscript.

Corresponding author

Correspondence to Miguel Altuve.

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All the procedures performed in the study were adjusted to the ethical standards of the University Hospital of Caracas and the Declaration of Helsinki of 1964 and its subsequent amendments or comparable ethical standards.

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The authors declare no competing interests.

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Altuve, M., Severeyn, E. Cluster analysis based on fasting and postprandial plasma glucose and insulin concentrations. Int J Diabetes Dev Ctries (2024). https://doi.org/10.1007/s13410-024-01322-8

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