CUN-BAE adiposity index prediction of incident type 2 diabetes: the Seguimiento Universidad de Navarra prospective cohort
Background: Obesity is currently a pandemic and a cardinal risk factor for incident diabetes, a parallel growing pandemic. Measures commonly used to define obesity, i.e., BMI and waist circumference, do not accurately reflect body fatness. Methods: We examined the prognostic value of body fatness as...
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| Format: | Article |
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Elsevier
2025-05-01
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| Series: | The Journal of Nutrition, Health and Aging |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S1279770725000697 |
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| author | Ligia J. Dominguez Carmen Sayón-Orea Alfredo Gea Estefania Toledo-Atucha Maira Bes-Rastrollo Mario Barbagallo Miguel A. Martínez-González |
| author_facet | Ligia J. Dominguez Carmen Sayón-Orea Alfredo Gea Estefania Toledo-Atucha Maira Bes-Rastrollo Mario Barbagallo Miguel A. Martínez-González |
| author_sort | Ligia J. Dominguez |
| collection | DOAJ |
| description | Background: Obesity is currently a pandemic and a cardinal risk factor for incident diabetes, a parallel growing pandemic. Measures commonly used to define obesity, i.e., BMI and waist circumference, do not accurately reflect body fatness. Methods: We examined the prognostic value of body fatness assessed with the ‘Clínica Universidad de Navarra-Body Adiposity Estimator’ (CUN-BAE, range: 18.4–65.0 %) in 18,594 participants of the ''Seguimiento Universidad de Navarra'' prospective longitudinal cohort (60.5% women) without diabetes at baseline. Participants were followed-up with biennial questionnaires and multivariable-adjusted Cox models were used to estimate incident diabetes. Results: During 13.7 years of median follow-up, 209 participants developed diabetes. Progressively ascending quartiles of CUN-BAE were significantly associated with incident diabetes in multivariable-adjusted models, even after adjusting for BMI > 30 kg/m2. For each 2-unit increment in the CUN-BAE index, diabetes risk relatively increased by 46% in men and women (95% CI: 33%–62%). When comparing ROC AUC for CUN-BAE and BMI the association was stronger for CUN-BAE (p < 0.001). Conclusions: CUN-BAE index, an easy equation that can be used in any clinical setting, predicted better the risk of incident diabetes compared to BMI. Our results emphasize the importance of reducing and maintaining a low adiposity in order to prevent diabetes. |
| format | Article |
| id | doaj-art-1e17ad4c4f55466c8bdd64a43df32b0d |
| institution | Kabale University |
| issn | 1760-4788 |
| language | English |
| publishDate | 2025-05-01 |
| publisher | Elsevier |
| record_format | Article |
| series | The Journal of Nutrition, Health and Aging |
| spelling | doaj-art-1e17ad4c4f55466c8bdd64a43df32b0d2025-08-20T03:52:04ZengElsevierThe Journal of Nutrition, Health and Aging1760-47882025-05-0129510054510.1016/j.jnha.2025.100545CUN-BAE adiposity index prediction of incident type 2 diabetes: the Seguimiento Universidad de Navarra prospective cohortLigia J. Dominguez0Carmen Sayón-Orea1Alfredo Gea2Estefania Toledo-Atucha3Maira Bes-Rastrollo4Mario Barbagallo5Miguel A. Martínez-González6Department of Medicine and Surgery, University Kore of Enna, 94100 Enna, Italy; Geriatric Unit, Department of Internal Medicine and Geriatrics, University of Palermo, 90127 Palermo, Italy; Corresponding author.Department of Preventive Medicine and Public Health, University of Navarra-IdiSNA, 31008 Pamplona, Spain; CIBER Fisiopatologia de la Obesidad y Nutrición (CIBERobn), Instituto de Salud Carlos III, 28029 Madrid, Spain; Public Health Institute, 31003 Navarra, SpainDepartment of Preventive Medicine and Public Health, University of Navarra-IdiSNA, 31008 Pamplona, Spain; CIBER Fisiopatologia de la Obesidad y Nutrición (CIBERobn), Instituto de Salud Carlos III, 28029 Madrid, SpainDepartment of Preventive Medicine and Public Health, University of Navarra-IdiSNA, 31008 Pamplona, Spain; CIBER Fisiopatologia de la Obesidad y Nutrición (CIBERobn), Instituto de Salud Carlos III, 28029 Madrid, SpainDepartment of Preventive Medicine and Public Health, University of Navarra-IdiSNA, 31008 Pamplona, Spain; CIBER Fisiopatologia de la Obesidad y Nutrición (CIBERobn), Instituto de Salud Carlos III, 28029 Madrid, SpainGeriatric Unit, Department of Internal Medicine and Geriatrics, University of Palermo, 90127 Palermo, ItalyDepartment of Preventive Medicine and Public Health, University of Navarra-IdiSNA, 31008 Pamplona, Spain; CIBER Fisiopatologia de la Obesidad y Nutrición (CIBERobn), Instituto de Salud Carlos III, 28029 Madrid, Spain; Department of Nutrition, Harvard TH Chan School of Public Health, Boston, MA 02115, United StatesBackground: Obesity is currently a pandemic and a cardinal risk factor for incident diabetes, a parallel growing pandemic. Measures commonly used to define obesity, i.e., BMI and waist circumference, do not accurately reflect body fatness. Methods: We examined the prognostic value of body fatness assessed with the ‘Clínica Universidad de Navarra-Body Adiposity Estimator’ (CUN-BAE, range: 18.4–65.0 %) in 18,594 participants of the ''Seguimiento Universidad de Navarra'' prospective longitudinal cohort (60.5% women) without diabetes at baseline. Participants were followed-up with biennial questionnaires and multivariable-adjusted Cox models were used to estimate incident diabetes. Results: During 13.7 years of median follow-up, 209 participants developed diabetes. Progressively ascending quartiles of CUN-BAE were significantly associated with incident diabetes in multivariable-adjusted models, even after adjusting for BMI > 30 kg/m2. For each 2-unit increment in the CUN-BAE index, diabetes risk relatively increased by 46% in men and women (95% CI: 33%–62%). When comparing ROC AUC for CUN-BAE and BMI the association was stronger for CUN-BAE (p < 0.001). Conclusions: CUN-BAE index, an easy equation that can be used in any clinical setting, predicted better the risk of incident diabetes compared to BMI. Our results emphasize the importance of reducing and maintaining a low adiposity in order to prevent diabetes.http://www.sciencedirect.com/science/article/pii/S1279770725000697ObesityAdiposityCUN-BAEDiabetesLongitudinal |
| spellingShingle | Ligia J. Dominguez Carmen Sayón-Orea Alfredo Gea Estefania Toledo-Atucha Maira Bes-Rastrollo Mario Barbagallo Miguel A. Martínez-González CUN-BAE adiposity index prediction of incident type 2 diabetes: the Seguimiento Universidad de Navarra prospective cohort The Journal of Nutrition, Health and Aging Obesity Adiposity CUN-BAE Diabetes Longitudinal |
| title | CUN-BAE adiposity index prediction of incident type 2 diabetes: the Seguimiento Universidad de Navarra prospective cohort |
| title_full | CUN-BAE adiposity index prediction of incident type 2 diabetes: the Seguimiento Universidad de Navarra prospective cohort |
| title_fullStr | CUN-BAE adiposity index prediction of incident type 2 diabetes: the Seguimiento Universidad de Navarra prospective cohort |
| title_full_unstemmed | CUN-BAE adiposity index prediction of incident type 2 diabetes: the Seguimiento Universidad de Navarra prospective cohort |
| title_short | CUN-BAE adiposity index prediction of incident type 2 diabetes: the Seguimiento Universidad de Navarra prospective cohort |
| title_sort | cun bae adiposity index prediction of incident type 2 diabetes the seguimiento universidad de navarra prospective cohort |
| topic | Obesity Adiposity CUN-BAE Diabetes Longitudinal |
| url | http://www.sciencedirect.com/science/article/pii/S1279770725000697 |
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