S'abonner

Trajectories of metabolic risk factors during the development of type 2 diabetes in Chinese adults - 20/04/22

Doi : 10.1016/j.diabet.2022.101348 
Zhou-Zheng Tu 1, ±, Yu Yuan 2, ±, Peng-Fei Xia 1, ±, Qi Lu 3, Shuo-Hua Chen 4, Guo-Dong Wang 4, Meng-Yi Zheng 4, Yan-Bo Zhang 1, Jun-Xiang Chen 1, Yan-Feng Zhou 1, Gang Liu 3, Shou-Ling Wu 4, #, , An Pan 1, #,
1 Department of Epidemiology and Biostatistics, Ministry of Education Key Laboratory of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China 
2 Department of Occupational and Environmental Health, Key Laboratory of Environment and Health, Ministry of Education and State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China 
3 Department of Nutrition and Food Hygiene, Hubei Key Laboratory of Food Nutrition and Safety, Ministry of Education Key Lab of Environment and Health, and State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China 
4 Department of Cardiology, Kailuan General Hospital, North China University of Science and Technology, Tangshan, China 

Corresponding authors: Shou-Ling Wu, PhD, Department of Cardiology, Kailuan General Hospital, North China University of Science and Technology, 57 Xinhua East Road, Tangshan 063000, China; Phone: 86-0315-3025655Department of Cardiology, Kailuan General HospitalNorth China University of Science and Technology57 Xinhua East RoadTangshan063000China⁎⁎Corresponding authors: An Pan, PhD, Department of Epidemiology and Biostatistics, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, 13 Hangkong Road, Wuhan 430030, China; Phone: 86-027-83627309Department of Epidemiology and Biostatistics, School of Public Health, Tongji Medical CollegeHuazhong University of Science and Technology13 Hangkong RoadWuhan430030China
Sous presse. Manuscrit accepté. Disponible en ligne depuis le Wednesday 20 April 2022
Cet article a été publié dans un numéro de la revue, cliquez ici pour y accéder

Highlights

Diabetic patients had more adverse levels of most MRFs throughout follow-up.
The natural history of multiple MRFs before diabetes diagnosis was elaborated.
Abrupt increases in multiple MRFs were observed 3 years before diabetes diagnosis.
We identified 3 years before diabetes as the ‘critical period’ for diagnosis.

Le texte complet de cet article est disponible en PDF.

Abstract

Aims

: China has the largest number of adults with diabetes. Although multiple metabolic risk factors (MRFs) are implicated in the development of diabetes, it remains unclear how they progress during the development of diabetes among Chinese. We examined trajectories of multiple MRFs among Chinese and identified the critical period when drastic changes occurred during the development of diabetes.

Methods

: This prospective cohort study included participants since 2006-2007 in the Kailuan study. People attended biennial examinations until 2017 with additions of new participants at each examination cycle. The time when a participant first completed the examination was served as the baseline. A total of 122,659 participants without prevalent diabetes at baseline and with complete follow-up data were included. MRFs were collected via biennial physical examinations and laboratory measures. Incident diabetes cases were identified via biennial fasting glucose tests and self-reported physician-diagnosis.

Results

: During up to 12 years of follow-up, 14,922 incident diabetes cases were identified. Compared with participants who did not develop diabetes, those who developed diabetes had more adverse levels of most MRFs at baseline and during follow-up. Abrupt increases in multiple MRFs (including fasting glucose, surrogate insulin resistance indicators, lipids, systolic blood pressure, pulse pressure, heart rate, alanine aminotransferase, and C-reactive protein) were observed 3 years before the diagnosis of diabetes.

Conclusions

: We identified 3 years before diabetes diagnosis as a critical period when multiple MRFs experienced drastic changes. This would have implications for early monitoring and timely prevention for individuals who experience sudden adverse progression of multiple MRFs.

Le texte complet de cet article est disponible en PDF.

Keywords : Chinese, Cohort study, Diabetes, Metabolic risk factor, Trajectory


Plan


 Zhou-Zheng Tua#, Yu Yuanb#, Peng-Fei Xiaa#, Qi Luc, Shuo-Hua Chend, Guo-Dong Wangd, Meng-Yi Zhengd, Yan-Bo Zhanga, Jun-Xiang Chena, Yan-Feng Zhoua, Gang Liuc, Shou-Ling Wud*, An Pana*


© 2022  Publié par Elsevier Masson SAS.
Ajouter à ma bibliothèque Retirer de ma bibliothèque Imprimer
Export

    Export citations

  • Fichier

  • Contenu

Bienvenue sur EM-consulte, la référence des professionnels de santé.
L’accès au texte intégral de cet article nécessite un abonnement.

Déjà abonné à cette revue ?

Mon compte


Plateformes Elsevier Masson

Déclaration CNIL

EM-CONSULTE.COM est déclaré à la CNIL, déclaration n° 1286925.

En application de la loi nº78-17 du 6 janvier 1978 relative à l'informatique, aux fichiers et aux libertés, vous disposez des droits d'opposition (art.26 de la loi), d'accès (art.34 à 38 de la loi), et de rectification (art.36 de la loi) des données vous concernant. Ainsi, vous pouvez exiger que soient rectifiées, complétées, clarifiées, mises à jour ou effacées les informations vous concernant qui sont inexactes, incomplètes, équivoques, périmées ou dont la collecte ou l'utilisation ou la conservation est interdite.
Les informations personnelles concernant les visiteurs de notre site, y compris leur identité, sont confidentielles.
Le responsable du site s'engage sur l'honneur à respecter les conditions légales de confidentialité applicables en France et à ne pas divulguer ces informations à des tiers.


Tout le contenu de ce site: Copyright © 2024 Elsevier, ses concédants de licence et ses contributeurs. Tout les droits sont réservés, y compris ceux relatifs à l'exploration de textes et de données, a la formation en IA et aux technologies similaires. Pour tout contenu en libre accès, les conditions de licence Creative Commons s'appliquent.