Two Distinct Groups Are Shown to Be at Risk of Diabetes by Means of a Cluster Analysis of Four Variables
Recent attempts to classify adult-onset diabetes using only six diabetes-related variables (GAD antibody, age at diagnosis, BMI, HbA1c, and homeostatic model assessment 2 estimates of b-cell function and insulin resistance (HOMA2-B and HOMA2-IR)) showed that diabetes can be classified into five clus...
| Main Authors: | , , , , , , , , , , , , , |
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| Format: | Article |
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MDPI AG
2023-01-01
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| Series: | Journal of Clinical Medicine |
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| Online Access: | https://www.mdpi.com/2077-0383/12/3/810 |
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| author | Ryoma Ito Satoru Mizushiri Yuki Nishiya Shoma Ono Ayumi Tamura Kiho Hamaura Akihide Terada Jutaro Tanabe Miyuki Yanagimachi Kyi Mar Wai Yutaro Kudo Kazushige Ihara Yoshiko Takahashi Makoto Daimon |
| author_facet | Ryoma Ito Satoru Mizushiri Yuki Nishiya Shoma Ono Ayumi Tamura Kiho Hamaura Akihide Terada Jutaro Tanabe Miyuki Yanagimachi Kyi Mar Wai Yutaro Kudo Kazushige Ihara Yoshiko Takahashi Makoto Daimon |
| author_sort | Ryoma Ito |
| collection | DOAJ |
| description | Recent attempts to classify adult-onset diabetes using only six diabetes-related variables (GAD antibody, age at diagnosis, BMI, HbA1c, and homeostatic model assessment 2 estimates of b-cell function and insulin resistance (HOMA2-B and HOMA2-IR)) showed that diabetes can be classified into five clusters, of which four correspond to type 2 diabetes (T2DM). Here, we classified nondiabetic individuals to identify risk clusters for incident T2DM to facilitate the refinement of prevention strategies. Of the 1167 participants in the population-based Iwaki Health Promotion Project in 2014 (baseline), 868 nondiabetic individuals who attended at least once during 2015–2019 were included in a prospective study. A hierarchical cluster analysis was performed using four variables (BMI, HbA1c, and HOMA2 indices). Of the four clusters identified, cluster 1 (n = 103), labeled as “obese insulin resistant with sufficient compensatory insulin secretion”, and cluster 2 (n = 136), labeled as “low insulin secretion”, were found to be at risk of diabetes during the 5-year follow-up period: the multiple factor-adjusted HRs for clusters 1 and 2 were 14.7 and 53.1, respectively. Further, individuals in clusters 1and 2 could be accurately identified: the area under the ROC curves for clusters 1and 2 were 0.997 and 0.983, respectively. The risk of diabetes could be better assessed on the basis of the cluster that an individual belongs to. |
| first_indexed | 2024-03-11T09:39:16Z |
| format | Article |
| id | doaj.art-c8cc274db364413b92b5c87bb6f03671 |
| institution | Directory Open Access Journal |
| issn | 2077-0383 |
| language | English |
| last_indexed | 2024-03-11T09:39:16Z |
| publishDate | 2023-01-01 |
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| record_format | Article |
| series | Journal of Clinical Medicine |
| spelling | doaj.art-c8cc274db364413b92b5c87bb6f036712023-11-16T17:07:30ZengMDPI AGJournal of Clinical Medicine2077-03832023-01-0112381010.3390/jcm12030810Two Distinct Groups Are Shown to Be at Risk of Diabetes by Means of a Cluster Analysis of Four VariablesRyoma Ito0Satoru Mizushiri1Yuki Nishiya2Shoma Ono3Ayumi Tamura4Kiho Hamaura5Akihide Terada6Jutaro Tanabe7Miyuki Yanagimachi8Kyi Mar Wai9Yutaro Kudo10Kazushige Ihara11Yoshiko Takahashi12Makoto Daimon13Department of Endocrinology and Metabolism, Hirosaki University Graduate School of Medicine, Hirosaki 036-8562, JapanDepartment of Endocrinology and Metabolism, Hirosaki University Graduate School of Medicine, Hirosaki 036-8562, JapanDepartment of Endocrinology and Metabolism, Hirosaki University Graduate School of Medicine, Hirosaki 036-8562, JapanDepartment of Endocrinology and Metabolism, Hirosaki University Graduate School of Medicine, Hirosaki 036-8562, JapanDepartment of Endocrinology and Metabolism, Hirosaki University Graduate School of Medicine, Hirosaki 036-8562, JapanDepartment of Endocrinology and Metabolism, Hirosaki University Graduate School of Medicine, Hirosaki 036-8562, JapanDepartment of Endocrinology and Metabolism, Hirosaki University Graduate School of Medicine, Hirosaki 036-8562, JapanDepartment of Endocrinology and Metabolism, Hirosaki University Graduate School of Medicine, Hirosaki 036-8562, JapanDepartment of Endocrinology and Metabolism, Hirosaki University Graduate School of Medicine, Hirosaki 036-8562, JapanDepartment of Social Medicine, Hirosaki University Graduate School of Medicine, Hirosaki 036-8562, JapanDepartment of Social Medicine, Hirosaki University Graduate School of Medicine, Hirosaki 036-8562, JapanDepartment of Social Medicine, Hirosaki University Graduate School of Medicine, Hirosaki 036-8562, JapanCenter of Innovation Research Initiatives Organization, Hirosaki 036-8562, JapanDepartment of Endocrinology and Metabolism, Hirosaki University Graduate School of Medicine, Hirosaki 036-8562, JapanRecent attempts to classify adult-onset diabetes using only six diabetes-related variables (GAD antibody, age at diagnosis, BMI, HbA1c, and homeostatic model assessment 2 estimates of b-cell function and insulin resistance (HOMA2-B and HOMA2-IR)) showed that diabetes can be classified into five clusters, of which four correspond to type 2 diabetes (T2DM). Here, we classified nondiabetic individuals to identify risk clusters for incident T2DM to facilitate the refinement of prevention strategies. Of the 1167 participants in the population-based Iwaki Health Promotion Project in 2014 (baseline), 868 nondiabetic individuals who attended at least once during 2015–2019 were included in a prospective study. A hierarchical cluster analysis was performed using four variables (BMI, HbA1c, and HOMA2 indices). Of the four clusters identified, cluster 1 (n = 103), labeled as “obese insulin resistant with sufficient compensatory insulin secretion”, and cluster 2 (n = 136), labeled as “low insulin secretion”, were found to be at risk of diabetes during the 5-year follow-up period: the multiple factor-adjusted HRs for clusters 1 and 2 were 14.7 and 53.1, respectively. Further, individuals in clusters 1and 2 could be accurately identified: the area under the ROC curves for clusters 1and 2 were 0.997 and 0.983, respectively. The risk of diabetes could be better assessed on the basis of the cluster that an individual belongs to.https://www.mdpi.com/2077-0383/12/3/810cluster analysisincident type 2 diabetesnondiabetic population |
| spellingShingle | Ryoma Ito Satoru Mizushiri Yuki Nishiya Shoma Ono Ayumi Tamura Kiho Hamaura Akihide Terada Jutaro Tanabe Miyuki Yanagimachi Kyi Mar Wai Yutaro Kudo Kazushige Ihara Yoshiko Takahashi Makoto Daimon Two Distinct Groups Are Shown to Be at Risk of Diabetes by Means of a Cluster Analysis of Four Variables Journal of Clinical Medicine cluster analysis incident type 2 diabetes nondiabetic population |
| title | Two Distinct Groups Are Shown to Be at Risk of Diabetes by Means of a Cluster Analysis of Four Variables |
| title_full | Two Distinct Groups Are Shown to Be at Risk of Diabetes by Means of a Cluster Analysis of Four Variables |
| title_fullStr | Two Distinct Groups Are Shown to Be at Risk of Diabetes by Means of a Cluster Analysis of Four Variables |
| title_full_unstemmed | Two Distinct Groups Are Shown to Be at Risk of Diabetes by Means of a Cluster Analysis of Four Variables |
| title_short | Two Distinct Groups Are Shown to Be at Risk of Diabetes by Means of a Cluster Analysis of Four Variables |
| title_sort | two distinct groups are shown to be at risk of diabetes by means of a cluster analysis of four variables |
| topic | cluster analysis incident type 2 diabetes nondiabetic population |
| url | https://www.mdpi.com/2077-0383/12/3/810 |
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