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. 2014 Jan;35(1):75-88.
doi: 10.1002/hbm.22159. Epub 2012 Sep 24.

Cross-sectional and longitudinal association of body mass index and brain volume

Jennifer F Bobb  1 , Brian S Schwartz, Christos Davatzikos, Brian Caffo
Affiliations

Cross-sectional and longitudinal association of body mass index and brain volume

Jennifer F Bobb et al. Hum Brain Mapp. 2014 Jan.

Abstract

Although a link between body mass index (BMI) and brain volume has been established in several cross-sectional studies, evidence of the association between change in BMI over time and changes in brain structure is limited. Using data from a cohort of 347 former lead workers and community controls with two magnetic resonance imaging scans over a period of ~5 years, we estimated cross-sectional and longitudinal associations of BMI and brain volume using both region of interest (ROI) and voxel-based morphometric (VBM) methods. We found that associations of BMI and brain volume were not significantly different in former lead workers when compared with community controls. In the cross-sectional analysis, higher BMIs were associated with smaller brain volumes in gray matter (GM) using both ROI and VBM approaches. No associations with white matter (WM) were observed. In the longitudinal analysis, higher baseline BMI was associated with greater decline in temporal and occipital GM ROI volumes. Change in BMI over the 5-year period was only associated with change in hippocampal volume and was not associated with change in any of the GM ROIs. Overall, higher BMI was associated with lower GM volume in several ROIs and with declines in volume in temporal and occipital GM over time. These results suggest that sustained high body mass may contribute to progressive temporal and occipital atrophy.

Keywords: BMI; MRI; aging; brain structure; obesity.

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Figures

Figure 1
Figure 1
Distribution of baseline BMI and change in BMI. Vertical lines correspond to BMI category cutoffs, Obese: BMI ≥ 30; Overweight: 25 ≤ BMI < 30; Normal: BMI < 25. [Color figure can be viewed in the online issue, which is available at http://wileyonlinelibrary.com.]
Figure 2
Figure 2
Boxplots of the change in ROI volume* across the 347 study participants. *Volume at the second MRI subtracted from volume at the first MRI, divided by the standard deviation of the change in volume across subjects. Mean (SD) of the unscaled ROIs (cm3) shown on right side of plot. GM = gray matter, WM = white matter. [Color figure can be viewed in the online issue, which is available at http://wileyonlinelibrary.com.]
Figure 3
Figure 3
Distribution of sizes of the maximal clusters of the permuted data sets for gray and white matter VBM. Vertical line denotes the size of the largest observed cluster. [Color figure can be viewed in the online issue, which is available at http://wileyonlinelibrary.com.]
Figure 4
Figure 4
Images of the largest (left) and second largest (right) observed gray matter cluster. Red, yellow, and blue regions correspond to unadjusted voxel‐wise p‐values of <10−5, <10−4, and <10−3, respectively.
Figure 5
Figure 5
Residual plots from the longitudinal models. For the temporal GM ROI, left panel shows residuals from linear regression of the longitudinal change in volume y 2–y 1on the set of covariates excluding baseline BMI in model (2) plotted against residuals from linear regression of baseline BMI on the same set of covariates. For the hippocampus ROI, right panel shows residuals from regression of the longitudinal change y 2–y 1 on the set of covariates excluding change in BMI in model (3) plotted against residuals from regression of change in BMI on the same set of covariates. Solid lines correspond to a loess smooth and dashed lines corresponds to a linear trend. [Color figure can be viewed in the online issue, which is available at http://wileyonlinelibrary.com.]
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