Table Info

Table 3.

Final analytic model of pain interference using two-part regression modeling

Variables within hierarchical models	First part—logistic regression (n = 701) Any pain interference (binary)					Second part—OLS regression (n = 459) Magnitude of pain interference				Overall model stats
Variables within hierarchical models	OR	SE	95% CI	P	Pseudo R²	b	SE	95% CI	P	R²	AIC	LR test
Base covariates				< 0.0001	0.222				< 0.0001	0.183	3,751	Base
Age	1.02	0.01	1.00–1.04	0.02		–0.10	0.03	–0.16––0.05	< 0.001
Gender (ref. female)
Male	0.65	0.18	0.38–1.11	0.12		1.09	0.93	–0.74–2.92	0.24
Transgender, non-binary, gender non-conforming, or other	1.21	0.88	0.29–5.06	0.80		–2.12	1.91	–5.86–1.63	0.27
Education (ref. ≤ HS)
Associates degree or some college	0.13	0.11	0.03–0.65	0.01		–0.86	1.23	–3.27–1.55	0.47
Bachelor’s degree	0.09	0.07	0.02–0.44	< 0.01		–2.88	1.22	–5.26––0.50	0.02
Master’s degree or above	0.08	0.07	0.02–0.40	< 0.01		–3.43	1.23	–5.83––1.03	< 0.01
MS subtype (ref. RRMS)
PPMS	1.44	0.69	0.57–3.67	0.44		0.33	1.37	–2.37–3.02	0.81
SPMS	1.57	0.54	0.81–3.07	0.18		2.58	0.91	0.80–4.36	< 0.01
PRMS	1.35	1.29	0.21–8.8	0.75		5.71	2.36	1.08–10.35	< 0.02
Unsure	1.13	0.63	0.38–3.35	0.82		2.81	1.70	–0.52–6.14	0.10
DMT (ref. no therapy)
First line	1.49	0.43	0.85–2.61	0.17		–0.63	0.91	–2.39–1.14	0.49
Second line	2.22	0.65	1.25–3.95	< 0.01		–1.32	0.86	–3.01–0.38	0.13
Pain med count	2.31	0.23	1.90–2.80	< 0.001		1.02	0.24	0.56–1.48	< 0.001
Childhood stressors				< 0.0001	0.245				< 0.0001	0.215	3,719	< 0.0001
Child stressor count	1.19	0.22	0.83–1.71	0.34		–0.58	0.54	–1.63–0.47	0.28
Child stressor severity	0.99	0.04	0.91–1.07	0.73		0.14	0.12	–0.10–0.38	0.24
Adult stressors				< 0.0001	0.258				< 0.0001	0.267	3,685	< 0.0001
Adult stressor count	1.04	0.02	1.00–1.08	0.07		0.06	0.05	–0.04–0.16	0.24
Adult stressor severity	1.00	0.01	0.98–1.02	0.92		0.04	0.02	–0.01–0.08	0.10

≤ 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.

Author contributions

CSP: Conceptualization, Formal analysis, Writing—original draft. TJB: Conceptualization, Resources, Writing—review & editing. RPS: Conceptualization, Formal analysis, Writing—review & editing. CMC: Conceptualization, Writing—review & editing. AW: Writing—review & editing. SAS: Conceptualization, Supervision, Writing—review & editing.

Conflicts of interest

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.

Copyright

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