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Trajectories of Metabolic Risk Factors and Biochemical Markers Prior to the Onset of Type 2 Diabetes: the Population-based Longitudinal Doetinchem Study

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Journal Nutr Diabetes
Date 2017 May 9
PMID 28481339
Citations 9
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Abstract

Background: Risk factors often develop at young age and are maintained over time, but it is not fully understood how risk factors develop over time preceding type 2 diabetes. We examined how levels and trajectories of metabolic risk factors and biochemical markers prior to diagnosis differ between persons with and without type 2 diabetes over 15-20 years.

Methods: A total of 355 incident type 2 diabetes cases (285 self-reported, 70 with random glucose ⩾11.1 mmol l) and 2130 controls were identified in a prospective cohort between 1987-2012. Risk factors were measured at 5-year intervals. Trajectories preceding case ascertainment were analysed using generalised estimating equations.

Results: Among participants with a 21-year follow-up period, those with type 2 diabetes had higher levels of metabolic risk factors and biochemical markers 15-20 years before case ascertainment. Subsequent trajectories were more unfavourable in participants with type 2 diabetes for body mass index (BMI), HDL cholesterol and glucose (P<0.01), and to a lesser extent for waist circumference, diastolic and systolic blood pressure, triglycerides, alanine aminotransferase, gamma glutamyltransferase, C-reactive protein, uric acid and estimated glomerular filtration rate compared with participants without type 2 diabetes. Among persons with type 2 diabetes, BMI increased by 5-8% over 15 years, whereas the increase among persons without type 2 diabetes was 0-2% (P<0.01). The observed differences in trajectories of metabolic risk factors and biochemical markers were largely attenuated after inclusion of BMI in the models. Results were similar for men and women.

Conclusions: Participants with diabetes had more unfavourable levels of metabolic risk factors and biochemical markers already 15-20 years before diagnosis and worse subsequent trajectories than others. Our results highlight the need, in particular, for maintenance of a healthy weight from young adulthood onwards for diabetes prevention.

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References
1.
Lyssenko V, Almgren P, Anevski D, Perfekt R, Lahti K, Nissen M . Predictors of and longitudinal changes in insulin sensitivity and secretion preceding onset of type 2 diabetes. Diabetes. 2004; 54(1):166-74. DOI: 10.2337/diabetes.54.1.166. View

2.
Kodama S, Saito K, Yachi Y, Asumi M, Sugawara A, Totsuka K . Association between serum uric acid and development of type 2 diabetes. Diabetes Care. 2009; 32(9):1737-42. PMC: 2732137. DOI: 10.2337/dc09-0288. View

3.
Inker L, Schmid C, Tighiouart H, Eckfeldt J, Feldman H, Greene T . Estimating glomerular filtration rate from serum creatinine and cystatin C. N Engl J Med. 2012; 367(1):20-9. PMC: 4398023. DOI: 10.1056/NEJMoa1114248. View

4.
Kahn S . The relative contributions of insulin resistance and beta-cell dysfunction to the pathophysiology of Type 2 diabetes. Diabetologia. 2003; 46(1):3-19. DOI: 10.1007/s00125-002-1009-0. View

5.
Sattar N, McConnachie A, Ford I, Gaw A, Cleland S, Forouhi N . Serial metabolic measurements and conversion to type 2 diabetes in the west of Scotland coronary prevention study: specific elevations in alanine aminotransferase and triglycerides suggest hepatic fat accumulation as a potential contributing factor. Diabetes. 2007; 56(4):984-91. DOI: 10.2337/db06-1256. View