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Purpose <p>To characterize participants with diabetes in the Chilean National Health Survey (ENS) 2016–2017 by grouping them into different typologies based on their biological and psychosocial factors. </p> Methods <p>A cross-sectional secondary analysis of ENS 2016–2017 data was conducted. The records of 652 participants aged 15 years old and older who reported having a health-professional diagnosis of diabetes were included. Twenty-two questions were chosen to represent factors associated with diabetes onset, health conditions, and psychosocial variables. Participants were grouped into typologies using cluster analysis, which were characterized statistically. </p> Results <p>7 clusters were identified and interpreted as typologies of participants with diabetes distinguished by the distribution of the selected biopsychosocial variables. Two remarkably contrasting clusters were described in detail, highlighting differences in general health, life habits, educational level, and socioeconomic situation. </p> Conclusion <p>Participants with diabetes in ENS 2016–2017 exhibit heterogeneous biopsychosocial profiles. The contrast between high-risk and lower-risk clusters highlights that psychosocial and structural determinants co-occur with biological risk, supporting their inclusion in diabetes stratification and generating hypotheses for targeted prevention and management strategies.</p>

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Cluster analysis of national survey data identifies biopsychosocial profiles of adults with diabetes in Chile

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年2月20日

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  • Rosario Callejas-Calvo,
  • Martín J. Campos-Silva,
  • Andrés Iturriaga-Jofré,
  • Sandra Flores-Alvarado,
  • Felipe A. Medina-Marín

摘要

Purpose

To characterize participants with diabetes in the Chilean National Health Survey (ENS) 2016–2017 by grouping them into different typologies based on their biological and psychosocial factors.

Methods

A cross-sectional secondary analysis of ENS 2016–2017 data was conducted. The records of 652 participants aged 15 years old and older who reported having a health-professional diagnosis of diabetes were included. Twenty-two questions were chosen to represent factors associated with diabetes onset, health conditions, and psychosocial variables. Participants were grouped into typologies using cluster analysis, which were characterized statistically.

Results

7 clusters were identified and interpreted as typologies of participants with diabetes distinguished by the distribution of the selected biopsychosocial variables. Two remarkably contrasting clusters were described in detail, highlighting differences in general health, life habits, educational level, and socioeconomic situation.

Conclusion

Participants with diabetes in ENS 2016–2017 exhibit heterogeneous biopsychosocial profiles. The contrast between high-risk and lower-risk clusters highlights that psychosocial and structural determinants co-occur with biological risk, supporting their inclusion in diabetes stratification and generating hypotheses for targeted prevention and management strategies.