Associations of Psychologic Factors with Multiple Chronic Overlapping Pain Conditions

Abstract

Aims: To characterize psychologic functioning across five chronic overlapping pain conditions (COPCs)-temporomandibular disorders, fibromyalgia, low back pain, headache, and irritable bowel syndrome-and their overlaps.

Methods: Participants were 655 adults in the OPPERA study. Psychologic variables were standardized in separate logistic regression models to compare their relative strength of association with each COPC. Random forest regression was used to explore the association of all psychologic measures with COPCs simultaneously. Linear regression analyses examined whether the count of COPCs was associated with psychologic measures.

Results: In univariate and multivariable analyses, measures of somatic symptom burden showed the strongest associations with individual COPCs and with the number of COPCs. Additional psychologic variables that showed significant associations with individual COPCs and their overlap included negative mood, perceived stress, and pain catastrophizing.

Conclusion: These findings highlight the importance of psychologic functioning in the assessment and management of these overlapping pain conditions.

Fig 1

The blue heat map depicts psychologic measure z-score differences according to the number of COPCs, based on data presented in Appendix 1. For example, the first cell in the top row depicts the mean SCL-90-R somatization subscale z-score difference between groups with 1 COPC vs 0 COPCs. Rows are ordered in descending strength of association, as determined by beta coefficients (standard error), reported in Appendix 2. The orange heat map depicts standardized odds ratios (SORs), reported in Table 4, that quantify the strength of association between psychologic measures and each individual COPC. SCL-90-R = Symptom Checklist 90-Revised; PILL = Pennebaker Inventory of Limbic Languidness; PSS = Perceived Stress Scale; STAI = Stait-Trait Anxiety Inventory; MPSS = Modified Posttraumatic Stress Disorder Symptom Scale; LES = Life Experiences Survey; POMS = Profile of Mood States-Bipolar; (r) = reverse scoring (negative z scores used for standardized odds ratios represent increase in odds of being a case associated with reduction of 1 SD in the value of the variable); CSQ-R = Coping Strategies Questionnaire-Revised.

Fig 2

Multivariable contributions of psychologic measures to COPCs in the OPPERA-2 study (n = 655 participants). Random forest modeling explored multivariable contributions of all psychologic measures to each binary COPC case classification, with study site, age, gender, and race/ethnicity also included as covariates. Contributions of individual variables in the random forest models were quantified using variable importance scores, which estimate the relative contribution of each predictor to the model’s classification of true positives and true negatives. Other health measures were included in the models, but are not plotted because their variable importance factors did not exceed 0.0004. Filled symbols = COPC cases; open symbols = controls; PILL = Pennebaker Inventory of Limbic Languidness; SCL-90-R = Symptom Checklist 90-Revised; PSS = Perceived Stress Scale; STAI = State-Trait Anxiety Inventory; MPSS = Modified Posttraumatic Stress Disorder Symptom Scale; LES = Life Experiences Survey; CSQ-R = Coping Strategies Questionnaire-Revised.

Fig 3

Relationships between number of COPCs and psychologic measures in OPPERA-2 (n = 655 participants). (a) SCL-90-R: Somatization. (b) SCL-90-R: Depression. (c) Perceived Stress Scale. (d) Coping Strategies Questionnaire-Revised: Catastrophizing. (e) State-Trait Anxiety Inventory: Trait anxiety. (f) Modified Posttraumatic Stress Disorder Symptom Scale. Each psychologic measure was the dependent variable in separate linear regression models that used weighted estimates from generalized estimating equations with robust error variance calculation. Each model was adjusted for study site, age, gender, and race/ethnicity. Each plot summarizes results from three linear regressions: (1) Plotted values are adjusted means of the z-transformed health measure ± standard error from models in which the number of COPCs was the categorical predictor variable. (2) The beta (b) estimate (standard error [SE]) represents the amount of change in the dependent variable associated with a one-unit increase in number of COPCs, modeled as a continuous variable. ^aP < .05 for the null hypothesis that b = 0. (3) In the micro-table, each COPC was modeled as a separate binary predictor in a multivariable linear regression model to show independent contributions of COPCs to each psychologic measure. Tabulated numbers are parameter estimates for COPCs denoted as T = temporomandibular disorders, H = headache, I = IBS, B = low back pain, and F = fibromyalgia. ^bP < .05 for the null hypothesis that parameter estimate for the dummy variable equals 0.