Establishment and Validation of a New Predictive Model for Insulin Resistance based on 2 Chinese Cohorts: A Cross-Sectional Study
Background. Visceral adiposity plays a key role in the development of insulin resistance (IR), so surrogate index that can indicate visceral obesity may have higher predictive value for IR. This study aimed to establish and validate a new predictive model including indicator of visceral obesity for...
Saved in:
| Main Authors: | , , , , , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Wiley
2022-01-01
|
| Series: | International Journal of Endocrinology |
| Online Access: | http://dx.doi.org/10.1155/2022/8968793 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1832565395685376000 |
|---|---|
| author | Shi Zhang Xin-Cheng Wang Jing Li Xiao-He Wang Yi Wang Yan-Ju Zhang Mei-Yang Du Min-Ying Zhang Jing-Na Lin Chun-Jun Li |
| author_facet | Shi Zhang Xin-Cheng Wang Jing Li Xiao-He Wang Yi Wang Yan-Ju Zhang Mei-Yang Du Min-Ying Zhang Jing-Na Lin Chun-Jun Li |
| author_sort | Shi Zhang |
| collection | DOAJ |
| description | Background. Visceral adiposity plays a key role in the development of insulin resistance (IR), so surrogate index that can indicate visceral obesity may have higher predictive value for IR. This study aimed to establish and validate a new predictive model including indicator of visceral obesity for IR. Methods. The study population consisted of two cohorts. The derivation cohort was a group of 667 patients with newly diagnosed type 2 diabetes and the population undergoing a routine health checkup was the validation cohort. The predictive model was established by the logistic regression analysis. Its value for predicting IR was compared with other surrogate indices by the receiver operating characteristic curve. Results. The odds ratio (OR) of age, visceral fat area (VFA), triglyceride (TG), fasting plasma glucose (FPG), and alanine aminotransferase (ALT) for IR was 1.028 (95% CI, 1.008–1.048) (P<0.01), 1.016 (95% CI, 1.009–1.023) (P<0.001), 1.184 (95% CI, 1.005–1.396) (P<0.05), 1.334 (95% CI, 1.225–1.451) (P<0.001), and 1.021 (95% CI, 1.001–1.040) (P<0.05). The formula of the predictive model was (0.0293 × age + 1.4892 × Ln VFA + 0.4966 × Ln TG + 2.784 × Ln FPG + 0.6906 × Ln ALT)/2. The area under the curve was the largest among all the previously reported predictors. Conclusions. This study established and validated a predicting model for IR and confirmed its predictive value in comparison with other surrogate indicators, which will offer a simple and effective tool to measure IR in future large population studies. |
| format | Article |
| id | doaj-art-8a0b65350f1e4da19965db78eaa0de28 |
| institution | Kabale University |
| issn | 1687-8345 |
| language | English |
| publishDate | 2022-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | International Journal of Endocrinology |
| spelling | doaj-art-8a0b65350f1e4da19965db78eaa0de282025-02-03T01:07:57ZengWileyInternational Journal of Endocrinology1687-83452022-01-01202210.1155/2022/8968793Establishment and Validation of a New Predictive Model for Insulin Resistance based on 2 Chinese Cohorts: A Cross-Sectional StudyShi Zhang0Xin-Cheng Wang1Jing Li2Xiao-He Wang3Yi Wang4Yan-Ju Zhang5Mei-Yang Du6Min-Ying Zhang7Jing-Na Lin8Chun-Jun Li9Department of EndocrinologyDepartment of EndocrinologyDepartment of EndocrinologyTianjin Centers for Disease Control and PreventionDepartment of EndocrinologyDepartment of EndocrinologyDepartment of EndocrinologySchool of MedicineDepartment of EndocrinologyDepartment of EndocrinologyBackground. Visceral adiposity plays a key role in the development of insulin resistance (IR), so surrogate index that can indicate visceral obesity may have higher predictive value for IR. This study aimed to establish and validate a new predictive model including indicator of visceral obesity for IR. Methods. The study population consisted of two cohorts. The derivation cohort was a group of 667 patients with newly diagnosed type 2 diabetes and the population undergoing a routine health checkup was the validation cohort. The predictive model was established by the logistic regression analysis. Its value for predicting IR was compared with other surrogate indices by the receiver operating characteristic curve. Results. The odds ratio (OR) of age, visceral fat area (VFA), triglyceride (TG), fasting plasma glucose (FPG), and alanine aminotransferase (ALT) for IR was 1.028 (95% CI, 1.008–1.048) (P<0.01), 1.016 (95% CI, 1.009–1.023) (P<0.001), 1.184 (95% CI, 1.005–1.396) (P<0.05), 1.334 (95% CI, 1.225–1.451) (P<0.001), and 1.021 (95% CI, 1.001–1.040) (P<0.05). The formula of the predictive model was (0.0293 × age + 1.4892 × Ln VFA + 0.4966 × Ln TG + 2.784 × Ln FPG + 0.6906 × Ln ALT)/2. The area under the curve was the largest among all the previously reported predictors. Conclusions. This study established and validated a predicting model for IR and confirmed its predictive value in comparison with other surrogate indicators, which will offer a simple and effective tool to measure IR in future large population studies.http://dx.doi.org/10.1155/2022/8968793 |
| spellingShingle | Shi Zhang Xin-Cheng Wang Jing Li Xiao-He Wang Yi Wang Yan-Ju Zhang Mei-Yang Du Min-Ying Zhang Jing-Na Lin Chun-Jun Li Establishment and Validation of a New Predictive Model for Insulin Resistance based on 2 Chinese Cohorts: A Cross-Sectional Study International Journal of Endocrinology |
| title | Establishment and Validation of a New Predictive Model for Insulin Resistance based on 2 Chinese Cohorts: A Cross-Sectional Study |
| title_full | Establishment and Validation of a New Predictive Model for Insulin Resistance based on 2 Chinese Cohorts: A Cross-Sectional Study |
| title_fullStr | Establishment and Validation of a New Predictive Model for Insulin Resistance based on 2 Chinese Cohorts: A Cross-Sectional Study |
| title_full_unstemmed | Establishment and Validation of a New Predictive Model for Insulin Resistance based on 2 Chinese Cohorts: A Cross-Sectional Study |
| title_short | Establishment and Validation of a New Predictive Model for Insulin Resistance based on 2 Chinese Cohorts: A Cross-Sectional Study |
| title_sort | establishment and validation of a new predictive model for insulin resistance based on 2 chinese cohorts a cross sectional study |
| url | http://dx.doi.org/10.1155/2022/8968793 |
| work_keys_str_mv | AT shizhang establishmentandvalidationofanewpredictivemodelforinsulinresistancebasedon2chinesecohortsacrosssectionalstudy AT xinchengwang establishmentandvalidationofanewpredictivemodelforinsulinresistancebasedon2chinesecohortsacrosssectionalstudy AT jingli establishmentandvalidationofanewpredictivemodelforinsulinresistancebasedon2chinesecohortsacrosssectionalstudy AT xiaohewang establishmentandvalidationofanewpredictivemodelforinsulinresistancebasedon2chinesecohortsacrosssectionalstudy AT yiwang establishmentandvalidationofanewpredictivemodelforinsulinresistancebasedon2chinesecohortsacrosssectionalstudy AT yanjuzhang establishmentandvalidationofanewpredictivemodelforinsulinresistancebasedon2chinesecohortsacrosssectionalstudy AT meiyangdu establishmentandvalidationofanewpredictivemodelforinsulinresistancebasedon2chinesecohortsacrosssectionalstudy AT minyingzhang establishmentandvalidationofanewpredictivemodelforinsulinresistancebasedon2chinesecohortsacrosssectionalstudy AT jingnalin establishmentandvalidationofanewpredictivemodelforinsulinresistancebasedon2chinesecohortsacrosssectionalstudy AT chunjunli establishmentandvalidationofanewpredictivemodelforinsulinresistancebasedon2chinesecohortsacrosssectionalstudy |