Longitudinal Metabolic Risk Factors Are Associated With Microvascular Complications
- 1Department of Epidemiology and Biostatistics Michigan State University East Lansing Michigan USA
- 2Department of Neurology University of Michigan Ann Arbor Michigan USA
Abstract
Objective: Determine associations between summaries of longitudinal metabolic risk factors and microvascular complications.
Methods: We performed a secondary analysis of participants with and without diabetes enrolled within the Atherosclerosis Risk in Communities Study that completed metabolic risk factors assessments four times across 11 years. We calculated slope and area under the curve (AUC) as summaries of longitudinal data for fasting glucose, systolic blood pressure (SBP), high‐density lipoprotein, triglycerides and waist circumference. We assessed Chronic Kidney Disease (CKD) with estimated Glomerular Filtration Rate, Peripheral Neuropathy (PN) with monofilament testing and Retinopathy (RN) with the Early Treatment Diabetic Retinopathy Study scale. Area under the receiver operating characteristic curve (AUROC) determined discriminatory capability of models based on slope and AUC compared to models based on metabolic risk factors at baseline.
Results: We identified 4204, 2788 and 1792 persons with assessments of CKD, PN and RN, respectively. The mean age was 52.3, 57.1% were female, and 21.0% had diabetes. Logistic regression revealed fasting glucose AUC (1.09, 1.05–1.15) and SBP AUC (1.27, 1.19–1.36) associated with CKD, triglyceride AUC (1.14, 1.04–1.25) and waist AUC (1.11, 1.07–1.15) associated with PN and fasting glucose AUC (1.13, 1.04–1.22) associated with RN. Longitudinal metabolic summaries only improved AUROC by 0.001–0.01 versus models with cross‐sectional metabolic assessments.
Conclusion: AUCs of longitudinal metabolic risk factors, but not slopes, were associated with microvascular complications. This finding highlights the importance that sustained metabolic impairment has for the development of microvascular complications. Surprisingly, however, in this cohort, summaries of longitudinal metabolic risk factors did not meaningfully add discriminatory capability beyond models based on metabolic assessments at baseline.
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BibTeX
@article{makinson2026longitudinal,
title = {{Longitudinal Metabolic Risk Factors Are Associated With Microvascular Complications}},
author = {Cody H. Makinson and Jihyun Park and Eva L. Feldman and Brian C. Callaghan and Evan L. Reynolds},
journal = {Diabetes, Obesity \& Metabolism},
year = {2026},
month = sep,
doi = {10.1111/dom.71338},
url = {https://doi.org/10.1111/dom.71338},
note = {CC BY 4.0},
}
RIS
TY - JOUR
TI - Longitudinal Metabolic Risk Factors Are Associated With Microvascular Complications
AU - Cody H. Makinson
AU - Jihyun Park
AU - Eva L. Feldman
AU - Brian C. Callaghan
AU - Evan L. Reynolds
PY - 2026
DA - 2026/09/13
JO - Diabetes, Obesity & Metabolism
DO - 10.1111/dom.71338
UR - https://doi.org/10.1111/dom.71338
AB - Objective: Determine associations between summaries of longitudinal metabolic risk factors and microvascular complications. Methods: We performed a secondary analysis of participants with and without diabetes enrolled within the Atherosclerosis Risk in Communities Study that completed metabolic risk factors assessments four times across 11 years. We calculated slope and area under the curve (AUC) as summaries of longitudinal data for fasting glucose, systolic blood pressure (SBP), high‐density lipoprotein, triglycerides and waist circumference. We assessed Chronic Kidney Disease (CKD) with estimated Glomerular Filtration Rate, Peripheral Neuropathy (PN) with monofilament testing and Retinopathy (RN) with the Early Treatment Diabetic Retinopathy Study scale. Area under the receiver operating characteristic curve (AUROC) determined discriminatory capability of models based on slope and AUC compared to models based on metabolic risk factors at baseline. Results: We identified 4204, 2788 and 1792 persons with assessments of CKD, PN and RN, respectively. The mean age was 52.3, 57.1% were female, and 21.0% had diabetes. Logistic regression revealed fasting glucose AUC (1.09, 1.05–1.15) and SBP AUC (1.27, 1.19–1.36) associated with CKD, triglyceride AUC (1.14, 1.04–1.25) and waist AUC (1.11, 1.07–1.15) associated with PN and fasting glucose AUC (1.13, 1.04–1.22) associated with RN. Longitudinal metabolic summaries only improved AUROC by 0.001–0.01 versus models with cross‐sectional metabolic assessments. Conclusion: AUCs of longitudinal metabolic risk factors, but not slopes, were associated with microvascular complications. This finding highlights the importance that sustained metabolic impairment has for the development of microvascular complications. Surprisingly, however, in this cohort, summaries of longitudinal metabolic risk factors did not meaningfully add discriminatory capability beyond models based on metabolic assessments at baseline.
SN - 1462-8902
SN - 1463-1326
ER -