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. Author manuscript; available in PMC: 2022 Apr 1.
Published in final edited form as: J Neurosci Res. 2022 Feb 20;100(4):1047–1062. doi: 10.1002/jnr.25018

Associations between pain catastrophizing and resting-state functional brain connectivity: Ethnic/race group differences in persons with chronic knee pain

Ellen L Terry 1,2, Jared J Tanner 3, Josue S Cardoso 2, Kimberly T Sibille 4, Song Lai 5,6, Hrishikesh Deshpande 7,8, Georg Deutsch 7,8, Catherine C Price 3, Roland Staud 9, Burel R Goodin 10, David T Redden 11, Roger B Fillingim 2
PMCID: PMC8940639  NIHMSID: NIHMS1787976  PMID: 35187703

Abstract

Chronic pain is a significant public health problem, and the prevalence and societal impact continues to worsen annually. Multiple cognitive and emotional factors are known to modulate pain, including pain catastrophizing, which contributes to pain facilitation and is associated with altered resting-state functional connectivity in pain-related cortical and subcortical circuitry. Pain and catastrophizing levels are reported to be higher in non-Hispanic black (NHB) compared with non-Hispanic White (NHW) individuals. The current study, a substudy of a larger ongoing observational cohort investigation, investigated the pathways by which ethnicity/race influences the relationship between pain catastrophizing, clinical pain, and resting-state functional connectivity between anterior cingulate cortex (ACC), dorsolateral prefrontal cortex (dlPFC), insula, and primary somatosensory cortex (S1). Participants included 136 (66 NHBs and 70 NHWs) community-dwelling adults with knee osteoarthritis. Participants completed the Coping Strategies Questionnaire-Revised Pain Catastrophizing subscale and Western Ontario and McMaster Universities Osteoarthritis Index. Magnetic resonance imaging data were obtained, and resting-state functional connectivity was analyzed. Relative to NHW, the NHB participants were younger, reported lower income, were less likely to be married, and self-reported greater clinical pain and pain catastrophizing (ps < 0.05). Ethnicity/race moderated the mediation effects of catastrophizing on the relationship between clinical pain and resting-state functional connectivity between the ACC, dlPFC, insula, and S1. These results indicate the NHB and NHW groups demonstrated different relationships between pain, catastrophizing, and functional connectivity. These results provide evidence for a potentially important role of ethnicity/race in the interrelationships among pain, catastrophizing, and resting-state functional connectivity.

Keywords: ethnic/race, functional connectivity, knee osteoarthritis, knee pain, neuroimaging, pain catastrophizing

1 |. INTRODUCTION

Chronic pain is a prevalent public health problem that affects more than a third of the adult population in the United States (Zelaya et al., 2020) and causes significant annual economic costs and societal and personal impacts (Gaskin & Richard, 2012; Häuser et al., 2014). Indeed, chronic pain is associated with significant physical and functional disability, deterioration in quality of life, and psychological comorbidities (Lerman et al., 2015). In addition, people with chronic pain often exhibit a pain modulatory imbalance characterized by impaired pain inhibition and enhanced pain facilitation on quantitative sensory testing (Fingleton et al., 2015; Grinberg et al., 2017; Sanchis et al., 2015), evincing hallmark features of central sensitization (i.e., altered central nervous system [CNS] pain processing) (Harte et al., 2018; Woolf, 2011). Indeed, neuroimaging studies reveal changes in cortical thickness and gray matter volume as well as altered resting-state functional connectivity in persons with chronic pain (Davis, 2019; Smallwood et al., 2013), providing neurobiological evidence for the role of brain structure and function in chronic pain pathophysiology.

Multiple areas of the brain (e.g., anterior cingulate cortex [ACC], insular cortex, prefrontal cortex [PFC], primary somatosensory cortex [S1], secondary somatosensory cortex [SII], among others) are activated during the experience of pain (Apkarian et al., 2013; Tracey, 2005). The degree of synchrony in the activation of a set of brain regions is referred to as functional connectivity (Birn, 2007), and these brain networks that show intrinsic connectivity have been shown to become dysfunctional in chronic pain conditions (Coppieters et al., 2016; Davis & Moayedi, 2013; Kregel et al., 2015). Indeed, studies in people with chronic pain have found various patterns of resting brain network connectivity in pain-related brain regions (Cifre et al., 2012; Flodin et al., 2016; Ichesco et al., 2014; Malinen et al., 2010; Napadow et al., 2010; Tagliazucchi et al., 2010), though the functional connectivity reorganization varies in both magnitude and extent of functional coupling within these networks. These inconsistencies may be due to the modulatory influences of psychological states and cognitive demands on brain connectivity (Kucyi & Davis, 2015, 2017; Necka et al., 2019).

The biopsychosocial model of pain provides a framework for conceptualizing how the dynamic interactions among biological (e.g., neural connectivity), psychological (e.g., pain catastrophizing), and social (e.g., ethnicity/race) factors contribute to the initiation and maintenance of chronic pain (Fillingim, 2017; Gatchel et al., 2007). Psychological processes, including cognitive and emotional factors, can influence the appraisal and perception of nociceptive signals and the meaning that is attributed to pain (Bushnell et al., 2013; Villemure & Bushnell, 2002). One cognitive and emotional factor with compelling evidence for negatively influencing pain is pain catastrophizing (Gatchel, 2017; Wertli et al., 2014).

Pain catastrophizing is an increasingly controversial term applied to a pattern of cognitive and affective appraisal of pain characterized by a tendency to negatively evaluate one’s ability to cope with pain and to respond to anticipated or actual pain in a heightened negative cognitive and emotional manner (Keefe et al., 2004; Quartana et al., 2009; Sullivan et al., 2001). The central mechanisms whereby pain catastrophizing influences pain are not fully known, but evidence suggests supraspinal processes play a critical role (Rhudy et al., 2011; Terry et al., 2015). The brain networks that play a role in pain perception and pain modulation appear to overlap with neural correlates of pain catastrophizing (including S1, SII, insula, ACC, thalamus, and dorsolateral prefrontal cortex [dlPFC]) (Galambos et al., 2019). Therefore, rather than using intrinsic resting-state networks (e.g., default mode and salience, among others), the current study will focus on theoretically driven between-region connectivity involving S1, insula, ACC, and dlPFC, as these brain areas overlap with both pain and pain catastrophizing. Furthermore, pain catastrophizing is associated with alterations in resting-state functional connectivity (Gupta et al., 2015; Hubbard et al., 2014; Kucyi et al., 2014; Lazaridou et al., 2017).

Notably, the levels of pain catastrophizing appear to differ across population groups. Specifically, non-Hispanic blacks (NHBs) report higher levels of pain catastrophizing than other ethnic/racial groups (Hastie et al., 2004; Meints et al., 2016), and catastrophizing has been shown to mediate race differences in chronic pain (Meints et al., 2018). In addition, NHBs are disproportionally affected by pain, and report higher levels of pain compared with non-Hispanic Whites (NHWs) (Vaughn et al., 2019). In addition, research from our laboratory reported significant interactions between ethnicity/race, pain catastrophizing, and pain-related brain structure (i.e., insula and S1) (Terry, Tanner, et al., 2020). Therefore, given higher rates of pain catastrophizing and pain in NHBs, and given the relationship that pain and pain catastrophizing have with functional connectivity, it is possible that ethnicity/race could play a role in these relationships.

We had one primary aim with the current study: investigate the pathways by which ethnicity/race influences the relationship between pain catastrophizing, clinical pain, and resting-state functional connectivity in key cortical regions previously associated with pain and pain catastrophizing relationships (i.e., S1, insula, ACC, and dlPFC). Hypothesis: We hypothesized that ethnic/race group would moderate the pathways among clinical pain, pain catastrophizing, and resting-state functional connectivity.

2 |. METHODS

2.1 |. Design

The current research is a substudy of a larger ongoing observational cohort investigation which aims to elucidate the mechanisms underlying ethnic/race group differences in knee OA pain. The parent study is a multisite investigation conducted at the University of Florida (UF) and the University of Alabama at Birmingham (UAB). All procedures were reviewed and approved by the Institutional Review Boards at the UF and UAB and followed the guidelines of the Declaration of Helsinki.

2.2 |. Study participants

Participants were 136 community-dwelling adults between ages 45 and 85 years old who self-identified as NHB (N = 66) or NHW (N = 70), presented with unilateral or bilateral knee pain, and screened positive for clinical knee OA (Altman et al., 1986). The total sample size in the moderated mediation analyses was 134 due to two participants being excluded: one participant was excluded for not completing the pain catastrophizing questionnaire and one participant was excluded for not completing the Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) questionnaire.

2.3 |. Procedures

Participants completed a standardized telephone screening whereby sociodemographic and physical health data were obtained to determine initial eligibility. Sociodemographic information included self-reported question about potential participant’s sex, age, ethnic/racial identity, and a brief health history screening including symptoms of knee OA. This screening questionnaire used to determine the symptoms of knee OA showed 87% sensitivity and 92% specificity for radiographically confirmed symptomatic knee OA (Roux et al., 2008).

Participants who met the inclusion criteria were brought to the laboratory and were consented prior to data collection. Prior to the collection of self-reported sociodemographic information, we administered the Rapid Estimate of Adult Literacy in Medicine-revised (REALM-R; an instrument designed to screen for potential health literacy problems) to ensure that participants understood the questionnaires and could complete the protocol. Participants then provided additional sociodemographic information (e.g., educational level obtained, current income, employment status) as part of a series of questionnaires inquiring about the participant’s health and pain history. Anthropometric measurements were obtained, specifically height and weight measurements for calculating body mass index (BMI). Questionnaires assessing pain catastrophizing, clinical pain, and pain-related disability were administered electronically via email prior to the subsequent visits of this multisession protocol (i.e., three laboratory visits) to reduce participant burden. However, if the participant did not have access to a computer to complete the questionnaires electronically, the questionnaires were completed at the beginning of the next laboratory visit. Participants completed several questionnaires (i.e., CSQ-R pain catastrophizing subscale, WOMAC pain) prior to or at the beginning of Visit 2. MRI data were acquired during Visit 3.

Participants were recruited through the community via multiple advertisement methods and clinic-based methods. Participants were excluded for the following self-reported conditions: (1) prosthetic knee replacement or other clinically significant surgery to the arthritic knee; (2) uncontrolled hypertension; (3) heart disease; (4) peripheral neuropathy in which pain testing was contraindicated; (5) systemic rheumatic disorders including rheumatoid arthritis, systemic lupus erythematosus, gout, and fibromyalgia; (6) neurological diseases such as Parkinson’s, multiple sclerosis, stroke with loss of sensory or motor function, or uncontrolled seizures; (7) significantly greater pain in body sites other than in the knee; (8) daily opioid use; (9) hospitalization within the preceding year for psychiatric illness; (10) pregnant or nursing; or (11) contraindications to magnetic resonance imaging (MRI) scanning (e.g., presence of metal implants, claustrophobia).

2.3.1 |. Questionnaires

3.1.1 |. Coping strategies questionnaire-revised

The Coping strategies questionnaire-revised (CSQ-R) Pain Catastrophizing subscale assesses the helplessness dimension of catastrophizing. The reliability and validity of the CSQ-R subscales have previously been shown to be acceptable (Jensen et al., 2003; Rosenstiel & Keefe, 1983). The CSQ-R has previously been validated and found to have similar factor structure in NHB and NHW adults (Hastie et al., 2004).

3.1.2 |. WOMAC pain intensity subscale

The WOMAC is a reliable (Cronbach’s alpha ≥ 0.80) and well-validated measure of lower extremity pain and function in persons with OA (Bellamy et al., 1988; Theiler et al., 2002). WOMAC assesses symptoms of knee OA in the past 48 hours.

2.4 |. MRI acquisition

MRI data from 87 participants were acquired at UF (39 NHBs and 48 NHWs) with the remaining 49 participants acquired at UAB (27 NHBs and 22 NHWs). Both sites (UF and UAB) acquired MRI data using a 3 Tesla Philips Achieva scanner (32 channel head coil at UF and an 8 channel at UAB). T1-weighted MP-RAGE images were acquired and used for analyses (TR: 7.0 ms, TE: 3.2 ms, flip angle: 8°, 1 mm iso voxels, FOV: 240 × 240 × 176.). To study brain functional connectivity, resting-state total between-region images were acquired using a single-shot gradient echo EPI sequence sensitized to the blood oxygenation level–dependent (BOLD) contrast (TR/TE/α = 2.5 s/35 ms/90°; 3.5 × 3.5 × 3.5 mm3 isotropic voxels, 42 interleaved axial slices without interslice gap). The resting-state scan lasted 8 min.

2.5 |. Resting-state fMRI methods

Preprocessing and quality assurance of functional and structural MRI data were performed using the default pipeline implemented in the CONN Toolbox (19.c; https://web.conn-toolbox.org/home; Whitfield Gabrieli & Nieto-Castanon, 2012). Briefly, this included functional scan realignment, interleaved slice-timing correction, co-registration to T1w, spatial normalization, and smoothing according to a full-width half-maximum (FWHM) isotropic Gaussian kernel filter of 8 mm. T1w images were then tissue-type segmented into gray matter, white matter, and cerebrospinal fluid. Nonlinear normalization to Montreal Neurological Institute (MNI) space (MNI152) was then performed. All preprocessing used Statistical Parametric Mapping version 12 (SPM12) software (https://www.fil.ion.ucl.ac.uk/spm/software/spm12/). Functional scans were then subjected to artifact and motion outlier identification using the Artifact Detection Toolbox according to conservative settings (95th percentile of normative sample). These settings identified time points as outliers if movement from a preceding image exceeded 0.5 mm or if the global mean signal intensity exceeded 3 standard deviations. Six participants had greater than 50% of their time points identified as outliers, so these participants were removed from the analyses. Outlier time points were included as regressors along with principal components delineated from anatomical noise regions (10 components for white matter and five components for cerebrospinal fluid) and realignment parameters during a denoising step. Finally, a 0.008–0.09 Hz band-pass filter was applied to the functional data (Hallquist et al., 2013). Functional connectivity was calculated using weighted seed-based connectivity (wSBC) maps.

2.6 |. MRI statistical analysiss

Based on previous work demonstrating an overlap in brain regions supporting pain catastrophizing and pain processing (Galambos et al., 2019), we a priori selected key nodes [bilateral middle frontal gyrus (dlPFC), insula, postcentral gyrus (S1), and anterior cingulate gyrus (ACC)] for analysis. The process for deriving the brain region of interest (ROI) connectivity values is presented in Figure 1. First, a mean signal time course for each node was calculated, then wSBC values were calculated by examining the correlations between the ROI signal time course and the time series of every other seed. The correlations in time series between the seeds were Fisher’s r-to-z transformed and then each pair of correlation coefficients was exported for each participant. We then took the absolute value of each connectivity value to maintain magnitude without directionality. These wSBC connectivity values were then used to calculate the mean total between-region connectivity as well as the mean from each node to every other node (ACC, dlPFC, insula, and S1). These ROIs might not constitute an intrinsic resting network; therefore, we refer to this as between-region connectivity rather than a network. The term total between-region connectivity will be used to refer to mean connectivity between all four ROIs, while each individual node will refer to mean connectivity to every other node (e.g., ACC connectivity = connectivity between the ACC and the three other ROIs: dlPFC, insula, and S1).

FIGURE 1.

FIGURE 1

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Process for creating ROI-to-ROI connectivity values. Column A shows the regions of interest (ROIs) as well as the raw group-level connectivity matrix (T scores) for the ROIs: left and right dorsolateral prefrontal cortex (DLPFC), anterior cingulate cortex (ACC), left and right insula cortex, and left and right primary somatosensory cortex (S1). Column B shows how the absolute values of ROI-to-ROI correlation values were used to create final connectivity values used in the statistical models: absolute value of the mean connectivity between ROIs. Matched (left/right) ROIs are in red

2.7 |. Data analysis

All data were analyzed using SPSS 25.0 (IBM, Chicago, IL), and data were checked for normality, outliers, and missing values. Ethnic/racial differences in sociodemographic and clinical characteristics were assessed using chi-square (χ2) for dichotomous variables and independent samples t tests for continuous variables. Hayes’ PROCESS macro (Model 15) (Hayes, 2018) was used to estimate direct and indirect (mediation) effects, as well as moderated mediation. This statistical approach uses a bootstrapping procedure to conduct inference tests for the indirect effects (Hayes, 2018). The 95% bias-corrected bootstrap confidence interval is based on 5,000 bootstrap samples to generate the path estimates and the indirect effects. There was evidence of a positive or negative indirect effect when the bootstrap 95% confidence interval for the indirect effect (ab) was entirely above or below zero. Moderated mediation attempts to model the mechanisms at work linking the independent variable (X) to the outcome variable (Y) via a mediator variable (M), while simultaneously allowing those effects to be contingent on a moderator variable (W) (Hayes, 2018). The current study examined whether WOMAC pain (X) would influence resting-state brain connectivity (Y) operating through pain catastrophizing (M), and whether this mediational relationship would vary at the level of a fourth variable—participant ethnicity/race (W). Study site, age, sex, and education were included as covariates in all PROCESS analyses.

3 |. RESULTS

3.1 |. Participant characteristics by ethnic/race group

Participant characteristics are presented in Table 1 for the overall sample, as well as separately for NHB and NHW sample. A total of 136 participants from two study sites with symptomatic knee osteoarthritis recruited from the University of Florida (n = 87) and the University of Alabama at Birmingham (n = 49) were included in this analysis. The ethnic/racial and sex composition of the sample were 66 NHBs (48.5%) and 70 NHWs (51.5%), with 90 females (66.2%; [NHBs = 41 NHWs = 49]) and 46 males (33.8%; [NHBs = 25; NHWs = 21]). NHB participants were younger (56.1 years, [SD = 6.3]) than NHW participants (60.5 years, [SD = 9.1]) and participants’ age ranged from 45 to 78 years. NHW participants reported higher income (χ2 = 21.30, p = 0.01) and were more likely to be married (χ2 = 13.17, p < 0.02) compared with NHB participants. NHB participants reported greater clinical pain (M = 8.8, SD = 4.1) compared with NHW participants (M = 6.0, SD = 4.1) and NHB participants reported higher pain catastrophizing (M = 1.6, SD = 1.3) compared with NHW participants (M = .8, SD = 1.0).

TABLE 1.

Demographics and clinical characteristics of participants across ethnicity/race

Overall NHB NHW
N = 136 N = 66 N = 70
M or N M or N M or N
(SD or %) (SD or %) (SD or %) p
Age (years)* 58.4 (8.2) 56.1 (6.3) 60.5 (9.1) 0.01
Study site 0.25
 UF 87 (64.0) 39 (59.1) 48 (68.6)
 UAB 49 (36.0) 27 (40.9) 22 (31.4)
Sex 0.33
 Female 90 (66.2) 41 (62.1) 49 (70.0)
 Male 46 (33.8) 25 (37.9) 21 (30.0)
Ethnicity/Race
 Non-Hispanic Black 66 (48.5) 66 (48.5) –
 Non-Hispanic White 70 (51.5) – 70 (51.5)
Income* 0.01
 $0–$9,999 32 (24.1) 23 (35.9) 9 (13.0)
 $10,000 – $19,999 16 (12.0) 10 (15.6) 6 (8.7)
 $20,000 – $29,999 20 (15.0) 11 (17.2) 9 (13.0)
 $30,000 – $39,999 6 (4.5) 4 (6.3) 2 (2.9)
 $40,000 – $49,999 12 (9.0) 3 (4.7) 9 (13.0)
 $50,000 – $59,999 14 (10.5) 3 (4.7) 11 (15.9)
 $60,000 – $79,999 11 (8.3) 4 (6.3) 7 (10.1)
 $80,000 – $99,999 8 (6.0) 3 (4.7) 5 (7.2)
 $100,000 – $149,999 9 (6.8) 2 (3.1) 7 (10.1)
 ≥150,000 5 (3.8) 1 (1.6) 4 (5.8)
Education 0.09
 Some school, <high school 9 (6.6) 7 (10.6) 2 (2.9)
 High school degree 53 (39.0) 31 (47.0) 22 (31.4)
 Associate degree 24 (17.6) 11 (16.7) 13 (18.6)
 Bachelor’s degree 28 (20.6) 9 (13.6) 19 (27.1)
 Master’s degree 16 (11.8) 6 (9.1) 10 (14.3)
 Doctoral/Professional 6 (4.4) 2 (3.0) 4 (5.7)
Marital status* 0.02
 Married 57 (42.5) 19 (29.7) 38 (54.3)
 Widowed 8 (6.0) 4 (6.3) 4 (5.7)
 Divorce 36 (26.9) 19 (29.7) 17 (24.3)
 Separated 5 (3.7) 4 (6.3) 1 (1.4)
 Never married 24 (17.9) 17 (26.6) 7 (10.0)
 Living with partner 4 (3.0) 1 (1.6) 3 (4.3)
Employment* 0.01
 Employed 57 (41.9) 33 (50.0) 24 (34.3)
 Temporary leave 4 (2.9) 3 (4.5) 1 (1.4)
 Not employed 14 (10.3) 7 (10.6) 7 (10.0)
 Retired 36 (26.5) 7 (10.6) 29 (41.4)
 Disabled 19 (14) 14 (21.2) 5 (7.1)
 Other 6 (4.4) 2 (3.0) 4 (5.7)
Insurance status 0.89
 No 18 (13.2) 9 (13.6) 9 (12.9)
 Yes 118 (86.8) 57 (86.4) 61 (87.1)
Knee pain duration 0.39
 <6 months 9 (6.7) 3 (4.5) 6 (8.7)
 6 to 12 months 7 (5.2) 4 (6.1) 3 (4.3)
 1 to 3 years 38 (28.1) 23 (34.8) 15 (21.7)
 3 to 5 years 22 (16.3) 11 (16.7) 11 (15.9)
 >5 years 59 (43.7) 25 (37.9) 34 (49.3)
BMI (kg/m2) 31.3 (6.5) 32.1 (6.0) 30.5 (6.8) 0.16
WOMAC pain* 7.3 (4.3) 8.8 (4.1) 6.0 (4.1) 0.01
Pain catastrophizing* 1.2 (1.3) 1.6 (1.3) 0.8 (1.0) 0.01
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Note: Chi-square (χ2) analysis used for dichotomous variables and independent samples t tests analysis used for continuous variables.

Abbreviations: BMI, body mass index; NHB, non-Hispanic black; NHW, non-Hispanic White; UAB, University of Birmingham at Alabama; UF, University of Florida; WOMAC, Western Ontario and McMaster Universities Osteoarthritis Index.

*

p < 0.05.

3.2 |. Associations between pain catastrophizing and resting-state functional connectivity

3.2.1 |. Total between-region connectivity

As shown in Figure 2, the index of moderated mediation was significant (B = 0.006, SE = 0.002; CI = [0.0021, 0.0106]), providing evidence that the indirect effect of WOMAC pain on total between-region connectivity through pain catastrophizing was moderated by participant ethnicity/race. These results indicate the NHB and NHW groups demonstrated different relationships between pain, catastrophizing, and the magnitude of total between-region functional connectivity. Specifically, this indirect effect was significant only for NHB adults (B = −0.004, SE = 0.001; CI = [−0.0069, −0.0013]) and not for NHW adults (B = 0.002, SE = 0.002; CI = [−0.0007, 0.0054]).

FIGURE 2.

FIGURE 2

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Moderated mediation model shows how clinical pain influences the total between-region connectivity, mediated through pain catastrophizing and moderated by ethnicity/race. WOMAC, Western Ontario and McMaster Universities Osteoarthritis Index. Total between-region connectivity = [anterior cingulate cortex (ACC), bilateral dorsolateral prefrontal cortex (dlPFC), bilateral insula, and bilateral primary somatosensory cortex (S1)]. *Present if bootstrap confidence interval does not include zero and is considered statistically significant. Covariates include study site, age, sex, and education

Results showed that WOMAC pain was not a significant predictor of total between-region connectivity (Path c1′; B = 0.000, SE = 0.002; CI = [−0.0032, 0.0041]). In addition, the relationship between WOMAC pain and total between-region connectivity was not moderated by ethnicity/race (Path c2′; B = −0.006, SE = 0.004; CI = [−0.0131, 0.0015]). Therefore, there is insufficient evidence to suggest that the direct effect of WOMAC pain on total between-region connectivity is related to participant ethnicity/race.

3.2.2 |. ACC connectivity

As shown in Table 2, the index of moderated mediation was significant (B = 0.005, SE = 0.003; CI = [0.0000, 0.0107]), suggesting that the indirect effect of WOMAC pain on ACC connectivity through pain catastrophizing varies according to participant ethnicity/race. Specifically, the mediational role of pain catastrophizing was in opposite directions in the two ethnicity/race groups; however, the indirect effect was not significant within either group: NHB adults (B = −0.002, SE = 0.002; CI = [−0.0053, 0.0015]) and NHW adults (B = 0.003, SE = 0.002; CI = [−0.0005, 0.0075]).

TABLE 2.

Moderated mediation model shows how clinical pain influences different functional connectivity, mediated through pain catastrophizing and moderated by ethnicity/race

Outcome functional connectivity WOMAC → Catas (path a) Catas → Functional connectivity (path b1) WOMAC → Functional connectivity (path c1′) WOMAC → Ethnicity/Race → Functional connectivity (path c2′) Catas → Ethnicity/Race → Functional connectivity (path b2)
B(SE) B(SE) B(SE) B(SE) B(SE)
ACC 0.139* (0.022) 0.003 (0.009) 0.002 (0.003) −0.004 (0.005) 0.034 (0.018)
dIPFC 0.139* (0.022) −0.007 (0.007) 0.000 (0.002) −0.010* (0.004) 0.049* (0.014)
Insula 0.139* (0.022) −0.012 (0.008) 0.002 (0.002) −0.004 (0.005) 0.037* (0.016)
SI 0.139* (0.022) −0.006 (0.010) −0.001 (0.003) −0.006 (0.005) 0.049* (0.018)
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Note: S1 = Primary Somatosensory Cortex. Covariates include study site, age, sex, and education.

Abbreviations: ACC, anterior cingulate cortex; Catas, pain catastrophizing; dlPFC, dorsolateral prefrontal cortex; WOMAC, Western Ontario and McMaster Universities Osteoarthritis Index.

*

Present if bootstrap confidence interval does not include zero and is considered statistically significant.

Results showed that WOMAC pain was not a significant predictor of ACC connectivity (Path c1′; B = 0.002, SE = 0.003; CI = [−0.0032, 0.0067]). In addition, the relationship between WOMAC pain and ACC connectivity was not moderated by ethnicity/race (Path c2′; B = −0.004, SE = 0.005; CI = [−0.0142, 0.0055]). Therefore, the direct effect of WOMAC pain on the ACC connectivity is not significantly related to participant ethnicity/race.

3.2.3 |. dlPFC connectivity

As shown in Table 2, the index of moderated mediation was significant (B = 0.007, SE = 0.002; CI = [0.0029, 0.0120]), providing evidence that the indirect effect of WOMAC pain on dlPFC connectivity through pain catastrophizing was moderated by participant ethnicity/race. Within groups, the relationship between catastrophizing and dlPFC connectivity was significant only for NHB adults (B = −0.004, SE = 0.002; CI = [−0.0076, −0.0018]), but not for NHW adults (B = 0.002, SE = 0.002; CI = [−0.0003, 0.0060]).

Results showed that WOMAC pain was not a significant predictor of dlPFC connectivity (Path c1′; B = 0.000, SE = 0.002; CI = [−0.0038, 0.0039]). However, the association of WOMAC pain and dlPFC connectivity was moderated by ethnicity/race (Path c2′; B = −0.010, SE = .004; CI = [−0.0179, −0.0026]). Specifically, the direct effect of WOMAC pain on dlPFC connectivity indicated opposite patterns for the ethnic/race groups: NHB participants (B = 0.005, SE = 0.003; CI = [−0.0001, 0.0107]) and NHW participants (B = −0.005, SE = 0.003; CI = [−0.0104, 0.0005]). In a post hoc analysis without catastrophizing as a mediator variable, ethnicity/race did not moderate the relationship between WOMAC pain and dlPFC connectivity (B = −0.003, SE = .004; CI = [−0.0093, 0.0044]).

3.2.4 |. Insula connectivity

As shown in Table 2, the index of moderated mediation was significant (B = 0.005, SE = 0.003; CI = [0.0004, 0.0108]), providing evidence that the indirect effect of WOMAC pain on insula connectivity through pain catastrophizing was moderated by participant ethnicity/race. Within groups, the relationship between catastrophizing and insula connectivity was significant only for NHB adults (B = −0.004, SE = 0.002; CI = [−0.0074, −0.0013]), but not for NHW adults (B = 0.001, SE = 0.002; CI = [−0.0032, 0.0053]).

Results showed that WOMAC pain was not a significant predictor of insula connectivity (Path c1′; B = 0.002, SE = 0.002; CI = [−0.0029, 0.0062]). In addition, the relationship between WOMAC pain and insula connectivity was not moderated by ethnicity/race (Path c2′; B = −0.004, SE = 0.005; CI = [−0.0133, 0.0049]).

3.2.5 |. Primary somatosensory cortex (S1) connectivity

As shown in Table 2, the index of moderated mediation was significant (B = 0.007, SE = 0.003; CI = [0.0015, 0.0127]), providing evidence that the indirect effect of WOMAC pain on S1 connectivity through pain catastrophizing was moderated by participant ethnicity/race. Within groups, the relationship between catastrophizing and S1 connectivity was significant only for NHB adults (B = −0.004, SE = 0.002; CI = [−0.0081, −0.0008]), but not for NHW adults (B = 0.003, SE = 0.002; CI = [−0.0012, 0.0066]).

Results showed that WOMAC pain was not a significant predictor of S1 connectivity (Path c1′; B = −0.001, SE = 0.003; CI = [−0.0056, 0.0047]). In addition, the relationship between WOMAC pain and S1 connectivity was not moderated by ethnicity/race (Path c2′; B = −0.006, SE = 0.005; CI = [−0.0164, 0.0042]).

4 |. DISCUSSION

The primary aim of the current study was to investigate the pathways by which ethnicity/race influences the relationship between pain catastrophizing, clinical pain, and resting-state functional connectivity in several regions of interest (ROIs) (i.e., S1, insula, ACC, and dlPFC). Consistent with Hypothesis 1, our results showed that ethnicity/race influenced the relationships between clinical pain, pain catastrophizing, and the magnitude of resting-state functional connectivity between a priori defined ROIs (i.e., ACC, dlPFC, insula, and S1). In other words, higher pain was associated with higher catastrophizing but the relationship between catastrophizing and between-region functional connectivity demonstrated different patterns based on ethnicity/race groups. Specifically, higher catastrophizing in the NHB group was significantly associated with lower between-region connectivity, but in the NHW group, while not significant, higher catastrophizing associated with higher between-region connectivity. An additional finding was that for dlPFC connectivity, while WOMAC pain did not associate with connectivity, ethnicity/race significantly moderated the relationship between pain and connectivity when controlling for catastrophizing. These findings provide evidence for the important role that sociodemographic factors (e.g., ethnic/race group) play in the interrelationships among pain, pain catastrophizing, and resting-state functional connectivity. These results should be interpreted with caution because the study was not designed to test mediational models and the direction of causality is unknown due to the use of cross-sectional data in the present study.

Increasing evidence demonstrates significant relationships between pain catastrophizing and pain-related neural activity during pain processing [for reviews, see Galambos et al. (2019); Malfliet et al. (2017)] in both people with chronic pain (Ellingson et al., 2018; Gracely et al., 2004; Loggia et al., 2015) and healthy individuals (Berna et al., 2010; Seminowicz & Davis, 2006), including associations with resting-state functional connectivity (Christidi et al., 2020; Coulombe et al., 2017; Jiang et al., 2016; Kim et al., 2015; Kucyi et al., 2014; Lazaridou et al., 2017; Lee et al., 2018). However, less is known about underrepresented ethnic/race groups and to date, few brain imaging studies have investigated the relationships between psychosocial factors (e.g., pain catastrophizing) and pain-related neural correlates (Losin et al., 2020; Terry, Tanner, et al., 2020). A previous functional neuroimaging study that investigated neural and psychosocial mediators and their relationship with experimental pain in healthy young adults from different ethnic/racial groups did not find pain catastrophizing to be a statistically significant contributor to ethnic group differences in pain. However, discrimination frequency and lower trust in the experimenter were associated with greater frontostriatal activation during painful heat among African American individuals, but not among the NHW and Hispanic groups (Losin et al., 2020). The divergent findings related to pain catastrophizing and neural connectivity may stem from differences in sample composition and neural activity being examined in the two studies. Specifically, Losin et al. (2020) studied younger pain-free individuals in contrast to our study participants who were older adults with chronic knee pain. In addition, Losin et al. (2020) did not investigate the demographic effects on neural connectivity.

The current study revealed sociodemographic differences (e.g., income, employment status, marital status) between ethnic/racial groups, which might confer greater health risk due to social stressors and may contribute to changes in brain structure and function. Indeed, psychosocial and economic stressors have been associated with neurobiological differences (Bagby et al., 2019; Chan et al., 2018; Myers, 2009). Specifically, Tanner et al. (2021) found that sociodemographic factors contributed to differences in pain-related brain structure. Further, African Americans experience high frequencies of negative stressful events, including discrimination and the multiple threats imposed by structural racism (Churchwell et al., 2020; Hatch & Dohrenwend, 2007). The experiences of discrimination are conceptualized as a “social stressor” that negatively impact health outcomes (Clark et al., 1999; Pascoe & Smart Richman, 2009; Turner, 2010). Discrimination has also been associated with greater experimental pain sensitivity (Goodin et al., 2013; Losin et al., 2020; Mathur et al., 2016) and poorer chronic pain outcomes (Brown et al., 2018; Burgess et al., 2009; Edwards, 2008; Taylor et al., 2018; Walker et al., 2016). Furthermore, perceived stress and pain catastrophizing appear to serially mediate the relationship between discrimination and pain-related outcomes in women (Terry, Fullwood, et al., 2020).

One correlate of increased pain severity is central sensitization, a mechanism by which altered CNS pain processing confers pain hypersensitivity (e.g., hyperalgesia) (Harte et al., 2018; Woolf, 2011). Indeed, several studies have found evidence of altered pain processing in patients with chronic pain (Arendt-Nielsen et al., 2010; Fingleton et al., 2015; Sanchis et al., 2015). King et al. (2013) demonstrated that among persons with symptomatic knee osteoarthritis, those with moderate to severe pain exhibited greater sensitivity to painful stimuli (i.e., central sensitization) compared with persons with low knee osteoarthritis symptoms, who, interestingly, showed similar pain sensitivity to the pain-free control group on most pain tests. Furthermore, studies that investigated pain sensitivity in individuals with chronic pain from different ethnic/race groups consistently find that NHBs are more pain sensitive during quantitative sensory testing compared with NHWs (Cruz-Almeida et al., 2014; Goodin et al., 2014; Ostrom et al., 2017). Furthermore, changes in central pain processing have been shown to be partially mediated by increased pain catastrophizing (Meints et al., 2019), specifically in NHB compared with NHW participants (Meints et al., 2018). Therefore, greater pain severity likely contributes to higher pain catastrophizing in NHBs compared with NHWs. Given the changes in central pain processing due to increased pain levels and higher pain catastrophizing, these factors may drive neurobiological changes including alterations in neural functioning.

Multiple studies have demonstrated alterations in pain-related brain function in adults with osteoarthritis, including evidence of reorganization of functional between-region connectivity (e.g., S1, insula, dlPFC, among others) (Barroso et al., 2021; Cottam et al., 2018; Hiramatsu et al., 2014; Parksl et al., 2011). Furthermore, arthritic clinical pain was associated with increased activity in brain regions involved in processing emotions (Kulkarni et al., 2007). In addition, arterial spin labeling showed alterations in resting-state regional cerebral blood flow in several brain regions (primary and secondary somatosensory, insula, and cingulate cortices; thalamus; amygdala; hippocampus; periaqueductal gray) that was associated with ongoing clinical pain in patients with hand osteoarthritis. While the evidence is clear that pain-related connectivity becomes altered in persons with chronic osteoarthritis pain, the degree of connectivity may vary due to the influence of other factors (e.g., psychological states, cognitive demands) (Kucyi & Davis, 2015, 2017; Necka et al., 2019). Our findings demonstrate that multiple psychological and social factors may interactively contribute to altered brain function in knee osteoarthritis.

Pain catastrophizing has been shown to influence pain perception through altering attention and anticipation of pain, heightening emotional responses to pain, as well as disrupting descending pain modulatory circuits (Ellingson et al., 2018; Galambos et al., 2019; Gracely et al., 2004; Loggia et al., 2015; Malfliet et al., 2017). Increased attention to thoughts about pain and its perceived negative consequences and difficulty shifting one’s attention away from pain are characteristics of individuals who catastrophize (Crombez et al., 1998, 2002; Van Damme et al., 2004b). In addition, pain is biologically designed to capture one’s attention and serves as a signal to escape bodily harm, particularly when the pain is appraised as threatening, even in instances of false alarm (Eccleston & Crombez, 1999). Indeed, anticipation of pain has been shown to strongly modulate attention when the stimulus was appraised as threatening (i.e., painful stimuli) in participants high in catastrophic thinking about pain (Van Damme et al., 2004a). Furthermore, while pain elicits an unpleasant sensory and emotional experience (IASP Task Force on Taxonomy et al., 1994), the negative emotional state is amplified in those who catastrophize about their pain (Jones et al., 2003; Sturgeon & Zautra, 2013), which contributes to emotional distress (Sullivan & Neish, 1999).

Importantly, networks involving cortical and subcortical regions that govern emotional, motivational, and cognitive processes communicate directly with descending pain modulatory circuits, providing a framework whereby cognitive and emotional factors (e.g., pain catastrophizing) can modulate and/or be modulated by pain (Bingel & Tracey, 2008; Ossipov et al., 2014). Indeed, brain imaging studies have found that pain catastrophizing is significantly associated with cortical activity in brain regions that underlie increased attention to pain (i.e., dorsal ACC, and dlPFC) (Gracely et al., 2004; Hubbard et al., 2015), anticipation of pain (i.e., lateral PFC, PFC, and parietal cortex) (Lloyd et al., 2016; Loggia et al., 2015), negative emotional state in response to pain (i.e., insula) (Galambos et al., 2019; Phillips et al., 2003), disrupted perception of sensory features of pain (i.e., S1) (Engel-sYeger & Dunn, 2011; Kim et al., 2015), as well as deficient descending modulation of pain (dlPFC, periaqueductal gray) (Coulombe et al., 2017; Ellingson et al., 2018; Seminowicz & Davis, 2006). Notably, these brain regions are not exclusively activated during nociception and pain perception, but rather cognitive, emotional, motivational, and sensory processes are “functionally connected in the context of nociception and give rise to the experience of pain” (Ossipov et al., 2014). Interestingly, our findings showed that the associations between clinical pain and resting-state functional connectivity in all the nodes, except the ACC, were mediated through pain catastrophizing in NHB participants, but not in NHW participants. With the ACC connectivity, different patterns emerged for the NHB and NHW participants, but the mediation was not significant within either group. These findings are consistent with our prior study showing that pain catastrophizing was differentially associated with brain structure in similar brain regions (e.g., S1 and insula) in NHBs and NHWs (Terry, Tanner, et al., 2020). We also found ethnicity/race moderated the associations between clinical pain and connectivity of the dlPFC with the other included brain resgions but only when accounting for pain catastrophizing. Our results therefore suggest the importance of both the appraisal of pain and sociodemographic factors.

A recent content analysis of pain catastrophizing measures suggested that pain catastrophizing instruments were more related to pain-related worry and pain-related distress (Crombez et al., 2020). Several theoretical models have been proposed [for review, see Sullivan et al. (2001)], including models that conceptualized pain catastrophizing as a form of negative repetitive thinking and worry (Eccleston & Crombez, 2007; Flink et al., 2013) and Severeijns et al. (2004) proposed an appraisal model of pain catastrophizing, conceptualized based on the transactional model of stress and coping (Lazarus & Folkman, 1984). Together, experiences that are appraised as a threat and are perceived as unmanageable (e.g., chronic painful experiences) become a source of stress and may result in the use of coping strategies such as pain catastrophizing (e.g., negative repetitive thinking [rumination], worry) about pain and its negative consequences and fear of future pain via anticipation of pain. Indeed, the use of these coping strategies are known to contribute to pain facilitation and altered cerebral functional connectivity (Meints & Edwards, 2018; Meints et al., 2020).

The current study results have important scientific and clinical implications. Specifically, underrepresented ethnic/race groups may be at higher risk of being stigmatized as high “pain catastrophizers” and risk further marginalization in health-care settings and during pain management, when contextual factors such as experiences of discrimination are not considered. Crombez et al. (2020) proposed that their definition of pain catastrophizing “to view or present pain or pain-related problems as considerably worse than they actually are” is not measured in current pain catastrophizing instruments and that the construct “pain catastrophizing” requires contextual information about an individual’s pain or pain-related problems, a population normative standard, and an expert judgment that the person’s perception is extreme. Therefore, research should address the need for a more respectful and patient-centered approach to understanding the processes reflected by what we currently refer to as “pain catastrophizing,” as is currently being investigated (https://renamepc.stanford.edu/). Importantly, such efforts must consider contextual factors, including those that disproportionately impact underserved communities, in order to reduce the stigma and further marginalization of ethnic/racial minority groups in research and clinical settings.

Interventions that target pain catastrophizing using cognitive and behavioral approaches have been shown to be effective in reducing pain catastrophizing, but improvement in pain and pain-related outcomes have been mixed (Buhrman et al., 2011; Burns et al., 2003; Smeets et al., 2006; Thorn et al., 2007; Turner et al., 2006). The authors of a recent meta-analysis found that multimodal treatment approaches (e.g., combined cognitive-behavioral therapy and exercise) were more effective at improving outcomes (Schütze et al., 2018), possibly due to the bidirectional relationship between pain intensity and pain catastrophizing (Racine et al., 2016). More work needs to be done to develop culturally tailored interventions to reduce pain catastrophizing and improve pain and pain-related outcomes in African American individuals, a group who have historically been poorly represented in health-related research and who stand to benefit substantially from evidence-based efficacious interventions that are culturally sensitive (Allen et al., 2019).

Therefore, vulnerable and underserved populations (e.g., ethnic/racial minorities) could benefit from tailored pain catastrophizing interventions in clinical and community settings within a multimodal pain management plan. An additional benefit of psychosocial interventions is evidence showing that reducing pain catastrophizing and pain appear to produce adaptive changes in pain-related brain structure and function in persons with chronic pain (Lazaridou et al., 2017; Seminowicz et al., 2013; Shpaner et al., 2014; Yoshino et al., 2018). Furthermore, the reduction of factors that contribute to disparities in pain (e.g., structural/systemic barriers, racial discrimination) through the advancement of health policy, education, practice, and research are needed to achieve equity in pain management and treatment (Meghani et al., 2012) and to improve pain-related outcomes, including reducing pain catastrophizing, among ethnic/racial minority groups.

Strengths of this current study include the recruitment of a large community sample with equal representation of NHB participants in a brain imaging investigation. Also, we included several covariates in the analyses in an effort to reduce confounding due to significant differences in socioeconomic status (SES) and other social and demographic factors between the groups. However, several limitations in the current study are noteworthy. First, the study analyses were based on cross-sectional data which limit conclusions about causation and given that the parent study was not designed to test these mediational models, conclusions are limited regarding the direction of the observed relationships. Second, a limitation of using PROCESS which is a linear regression-based approach is that the relationships are assumed to be linear; however, sometimes these relationships are best represented as a curved relationship. Third, it is unclear whether results from the current study are generalizable to younger patient groups or to individuals with other types of chronic pain. Fourth, significant differences in SES between the groups were reported and this could affect pain catastrophizing and pain-related brain outcomes. Fifth, sociodemographic factors (e.g., wealth, social support) or sociocultural factors (e.g., perceived racial discrimination) not considered in these models could have confounded the results given the comparisons between NHB and NHW participants. Sixth, the current study used the pain catastrophizing scale of the Coping Strategies Questionnaire-Revised, which assesses the helplessness domain of pain catastrophizing, rather than a more comprehensive measure of pain catastrophizing such as the Pain Catastrophizing Scale which captures three domains of pain catastrophizing (i.e., magnification, rumination, and helplessness). Seventh, clinical pain and catastrophizing were statistically significantly higher in the NHB compared with NHW participants; therefore, restriction of range in the NHW group could have impacted results. Lastly, we did not investigate discrimination in the current study. Future studies should investigate the effects of racial discrimination within the context of the health-care system and its effects on pain catastrophizing as well as in consideration of the development of a more culturally sensitive measure of pain catastrophizing. In addition, future studies could examine pain catastrophizing dimensions with the use of a measure that comprise multiple components of pain catastrophizing (e.g., Pain Catastrophizing Scale). Lastly, future studies could include the use of well-recognized intrinsic resting-state networks, such as default mode and salience networks to determine their relationship, if any, with pain catastrophizing.

In summary, we found ethnicity/race influenced the relationships between clinical pain, catastrophizing, and the magnitude of resting-state functional connectivity between the ACC, dlPFC, insula, and S1. Specifically, in NHB participants, higher pain was associated with higher catastrophizing and that in turn was associated with lower connectivity. The patterns for the NHW participants suggested different relationships including the possibility that higher pain catastrophizing was associated with increased connectivity between those regions. These findings provide evidence for further investigations specific to the complex interaction of sociodemographic factors in the interrelationships among pain, pain catastrophizing, and resting-state functional connectivity. We thus encourage pain and neurobiological research to incorporate more sociodemographically diverse samples.

Significance.

The evidence suggests ethnicity/race differentially influenced the relationships between clinical pain, pain catastrophizing, and the magnitude of resting-state functional connectivity between the anterior cingulate cortex (ACC), dorsolateral prefrontal cortex (dlPFC), insula, and primary somatosensory cortex (S1). These findings provide evidence for further investigations specific to the complex interaction of sociodemographic factors in the interrelationships among pain, pain catastrophizing, and resting-state functional connectivity.

ACKNOWLEDGEMENTS

The authors thank Laurence A. Bradley, Ph.D. for his contributions.

Funding information

This study was funded and supported by NIH Grants R37AG033906 (R.B.F.), R01AG054370 (K.T.S.), CTSA Grants UL1TR001427 (UF) and UL1TR001417 (UAB) from the NIH Center for Advancing Translational Sciences, and K22NS102334 (E.L.T.). Support was also provided by UF McKnight Brain Institute Career Enhancement Award (E.L.T.)

Footnotes

DECLARATION OF TRANSPARENCY

The authors, reviewers and editors affirm that in accordance to the policies set by the Journal of Neuroscience Research, this manuscript presents an accurate and transparent account of the study being reported and that all critical details describing the methods and results are present.

CONFLICT OF INTEREST

All authors declare that there is no conflict of interest with this study.

ETHICAL APPROVAL

All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional research committee at the University of Florida and University of Alabama at Birmingham and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards.

INFORMED CONSENT

Informed consent was obtained from all individual participants included in the study.

SUPPORTING INFORMATION

Additional supporting information may be found in the online version of the article at the publisher’s website.

Transparent Science Questionnaire for Authors

DATA AVAILABILITY STATEMENT

The data that support the findings of this study are available from the corresponding author upon reasonable request.

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Data Availability Statement

The data that support the findings of this study are available from the corresponding author upon reasonable request.

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