Table 3.
Longitudinal associations of white matter connectivity measures with incident depressive symptoms
| Model | Incident depressive symptoms n = 373 cases Hazard ratio (95% CI) | p value |
|---|---|---|
| Number of connectionsa | ||
| Lower global node degree (per s.d.) | ||
| Model 1 | 1.05 (0.95–1.17) | 0.344 |
| Model 2 | 1.06 (0.95–1.19) | 0.264 |
| Model 3 | 1.06 (0.95–1.18) | 0.334 |
| White matter organizationa | ||
| Lower clustering coefficient (per 1 s.d.) | ||
| Model 1 | 0.92 (0.79–1.07) | 0.268 |
| Model 2 | 0.91 (0.78–1.06) | 0.202 |
| Model 3 | 0.91 (0.78–1.06) | 0.217 |
| Lower local efficiency (per 1 s.d.) | ||
| Model 1 | 0.93 (0.78–1.11) | 0.403 |
| Model 2 | 0.91 (0.76–1.08) | 0.273 |
| Model 3 | 0.91 (0.76–1.08) | 0.282 |
| Higher characteristic path length (per 1 s.d.) | ||
| Model 1 | 0.99 (0.89–1.10) | 0.806 |
| Model 2 | 0.97 (0.87–1.08) | 0.578 |
| Model 3 | 0.97 (0.87–1.08) | 0.550 |
| Lower global efficiency (per 1 SD) | ||
| Model 1 | 1.01 (0.91–1.12) | 0.892 |
| Model 2 | 1.00 (0.90–1.11) | 0.985 |
| Model 3 | 1.00 (0.90–1.11) | 0.944 |
PHQ-9, indicates 9-item patient health questionnaire; CI indicates confidence interval; s.d., standard deviation. Incident depressive symptoms is defined as no depressive symptoms (PHQ-9 < 10) at baseline and depressive symptoms (PHQ-9 ⩾ 10) on at least one follow-up moment.
n = 4417 in model 1. Longitudinal data are evaluated using Cox proportional hazard regressions.
Model 1: adjusted for global node degree (graph measures), age, sex, MRI date, educational level, and T2DM.
Model 2: additionally adjusted for waist circumference, total/high-density cholesterol ratio, lipid-modifying medication, systolic blood pressure, antihypertensive medication, history of cardiovascular disease, and history of the cardiovascular accident. Data missing n = 50.
Model 3: additionally adjusted for smoking behavior and alcohol use. Additional data missing n = 2.
Global node degree, clustering coefficient, local efficiency, and global efficiency are inversed (i.e. multiplying it by − 1) to reflect structural dysconnectivity.