Association Between Obesity and Microvascular Diseases in Patients With Type 2 Diabetes Mellitus

Abstract

This study aimed to evaluate the association between obesity, evaluated by fat mass index (FMI) with the risk of microvascular diseases in patients with type 2 diabetes mellitus (T2DM) and compare the magnitude of associations of FMI, body mass index (BMI), and waist circumference (WC) with the risk of microvascular diseases. We performed a post-hoc analysis of the Action to Control Cardiovascular Risk in Diabetes study. The primary microvascular outcomes of the present study included chronic kidney disease (CKD) progression, retinopathy, and neuropathy. Cox proportional-hazards models were performed to evaluate the association of FMI with microvascular diseases. A discordant analysis was performed to compare the magnitude of associations of FMI, BMI, and WC with the risk of microvascular diseases. Our study included 10,251 T2DM participants with a median of 5 years (interquartile range, 4.2-5.7) of follow-up. A total of 6,184 participants developed CKD progression, 896 participants had retinopathy, and 3,213 participants developed neuropathy (Michigan Neuropathy Screening Instrument, >2.0). After the confounding factors were adjusted for, patients in the highest FMI quartile had a higher risk of CKD progression (HR: 1.26, 95%CI: 1.16-1.36) and neuropathy (HR: 1.93, 95% CI: 1.74-2.15), except for retinopathy (HR: 1.17, 95% CI: 0.96-1.43), than those in the lowest quartile. Discordant analyses found that FMI and WC are better in identifying individuals with obesity-related risk of neuropathy, compared with BMI; neither is better in identifying individuals with obesity-related risk of CKD progression and retinopathy. Obesity is associated with CKD progression and neuropathy in T2DM participants. Further randomized trials are needed to test whether obesity control can improve the outcomes of T2DM participants with CKD or neuropathy. FMI and WC are more useful in identifying obesity-related risk of neuropathy compared with BMI in T2DM patients.

Clinical trial registration: http://www.clinicaltrials.gov, NCT00000620.

Keywords: chronic kidney disease progression; microvascular diseases; neuropathy; retinopathy; type 2 diabetes mellitus.

Conflict of interest statement

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Copyright © 2021 Gao, Zhang, Long and Xing.

Figures

Figure 1

Hazard ratio per one standard deviation increase in the FMI for the primary and secondary endpoints. Adjusted for model 3, including age, race, sex, treatment effect, duration of diabetes, proteinuria, current smoking, weekly alcohol consumption, height, glomerular filtration rate, total cholesterol, low-density lipoprotein cholesterol, high-density lipoprotein cholesterol, systolic blood pressure, and hemoglobin A1C. CKD, chronic kidney disease; HR, hazard ratio; FMI, fat mass index; MNSI, Michigan Neuropathy Screening Instrument.

Figure 2

Restricted cubic spline analysis of the fat mass index for the estimation of the risk of the primary endpoints after adjusting for multivariate covariates. Hazard ratios are indicated by solid lines and the 95% confidence intervals by shaded areas. The reference point is the inflection point for each FMI (8.8 kg/m2 for CKD progression, 16.4 kg/m2 for retinopathy, and 18.5 kg/m2 for neuropathy), with knots placed at the fifth, 35th, 65th, and 95th percentiles of each FMI distribution. The hazard ratios shown are adjusted for model 3, including age, race, sex, treatment effect, diabetes duration, proteinuria, current smoking, weekly alcohol consumption, height, glomerular filtration rate, total cholesterol, low-density lipoprotein cholesterol, high-density lipoprotein cholesterol, systolic blood pressure, and hemoglobin A1C. CKD, chronic kidney disease; FMI, fat mass index; HR, hazard ratio.

Figure 3

Hazard ratios per one standard deviation increase in the fat mass index for the primary endpoints. Each stratification was adjusted for all factors in model 3 (age, race, sex, treatment effect, diabetes duration, proteinuria, current smoking, weekly alcohol consumption, height, glomerular filtration rate, total cholesterol, low-density lipoprotein cholesterol, high-density lipoprotein cholesterol, systolic blood pressure, and hemoglobin A1C), except for the stratification factor itself. CKD, chronic kidney disease; FMI, fat mass index; MNSI, Michigan Neuropathy Screening Instrument.

Figure 4

Multivariable-adjusted hazard ratios of primary endpoints by discordant versus concordant categories of fat mass index, body mass index, and waist circumference in type 2 diabetes mellitus patients. Adjusted for model 3: age, race, sex, glucose control, diabetes duration, proteinuria, current smoking, weekly alcohol consumption, height, glomerular filtration rate, total cholesterol, low density lipoprotein cholesterol, high density lipoprotein cholesterol, systolic blood pressure, and hemoglobin A1C. HR, hazard ratios; CI, confidence interval; CKD, chronic kidney disease.