Final analytic model of fatigue using two-part regression modeling
Variables within hierarchical models
First part—logistic regression(n = 600)Any fatigue (binary)
Second part—OLS regression(n = 576)Magnitude of fatigue
Overall model stats
OR
SE
95% CI
P
Pseudo R2
b
SE
95% CI
P
R2
AIC
LR test
Base covariates
< 0.04
0.074
< 0.0001
0.086
4,192
Base
Age
1.00
0.02
0.96–1.03
0.83
–0.07
0.03
–0.12–0.01
0.02
Gender (ref. female)
Male
0.72
0.39
0.25–2.07
0.54
–0.94
0.92
–2.73–0.86
0.31
Education (ref. ≤ HS)
Bachelor’s degree
0.14
0.14
0.02–1.07
0.06
–2.48
0.82
–4.09–0.88
0.002
Master’s degree or above
0.16
0.17
0.02–1.25
0.08
–4.51
0.81
–6.10––2.92
< 0.001
DMT (ref. no therapy)
First line
0.60
0.41
0.16–2.27
0.45
–1.34
0.97
–3.23–0.56
0.17
Second line
1.84
1.45
0.39–8.58
0.44
0.25
0.97
–1.65–2.15
0.80
MS subtype (ref. RRMS)
SPMS
1.50
1.22
0.31–7.35
0.62
2.55
0.99
0.62–4.48
0.01
Childhood stressors
0.01
0.105
< 0.0001
0.138
4,160
< 0.0001
Child stressor count
0.51
0.19
0.24–1.07
0.07
–1.23
0.59
–2.38––0.08
< 0.04
Child stressor severity
1.24
0.12
1.02–1.51
0.03
0.47
0.13
0.21–0.74
< 0.001
Categories within variables dropped from the model based on collinearity: 1) transgender, non-binary, gender non-conforming, or other, 2) associate degree or some college, 3) PPMS, 4) PRMS, 5) unsure. ≤ HS: high school equivalency or below; PPMS: primary progressive MS; PRMS: progressive-relapsing MS; ref.: reference; SPMS: secondary progressive MS. Blank cells indicate not applicable to individual variables
Declarations
Acknowledgments
Disclaimer: The content is solely the responsibility of the authors and does not necessarily represent the official views of Duke CTSI or the VA.
The authors have no conflicts of interest to declare.
Ethical approval
This study was approved by the University of Michigan IRB (HUM00200716).
Consent to participate
Participants read informed consent materials during the screening process and agreed to an implied consent statement to proceed with the study.
Consent to publication
Not applicable.
Availability of data and materials
Data is available upon request to corresponding author or Harvard Dataverse repository.
Funding
CSP was supported by NIH/NINR grant [T32NR016914], “Complexity: Innovations for Promoting Health and Safety”, Rackham Graduate School, Duke Clinical and Translational Science Institute (CTSI), and Durham VA. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
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