Racial Disparities in Pain Among Women with Fibromyalgia: Secondary Data Analysis of Severity,Interference with Function,and Response to Guided Imagery

Abstract

Background:

Fibromyalgia syndrome (FMS) is characterized by widespread persistent musculoskeletal pain. Mostly prevalent among White women, little is known about FMS in other population cohorts. This study examined secondary data of a racially diverse sample of women with FMS that were collected as part of a randomized controlled clinical trial that examined the effect of a complementary therapy intervention over the course of a 10-week guided imagery intervention to identify demographic, social, or economic differences in self-reported pain.

Materials and Methods:

The Brief Pain Inventory (BPI), which measures pain severity and interference, was administered to 72 women (21 Black and 51 Whites) at baseline, 6 and 10 weeks. Student's t tests and time series regression models examined racial difference in pain dimensions and treatment response. Regression models accounted for age, race, income, duration of symptoms, treatment group, pain at baseline, smoking, alcohol use, comorbid conditions, and time.

Results:

Black women experienced significantly higher pain severity (β = 5.52, standard deviation [SD] = 2.13) and interference (β = 5.54, SD = 2.74) than Whites (severity β = 4.56, SD = 2.08; interference β = 4.72, SD = 2.76) (interference: t = 1.92, p = 0.05; severity: t = 2.95, p = 0.00). Disparities persisted over time. Controlling for differences in age, income, and previous pain levels, Black women had 0.26 (standard error [SE] = 0.065) higher pain severity and 0.36 (SE = 0.078) higher interference than Whites. Low-income earners also experienced 2.02 (SE = 0.38) and 2.19 (SE = 0.46) higher pain severity and interference, respectively, than other earners. Results were robust to inclusion of comorbidities.

Conclusions:

Black women and low-income earners experienced significantly higher levels of pain severity and interference and a lower dose response to the intervention. Differentials were robust to inclusion of demographic, health, and behavioral characteristics. Findings suggest that external factors may contribute to pain perception among women with FMS.

Introduction

Fibromyalgia syndrome (FMS) is poorly understood, difficult to diagnose, leads to considerable variation in symptom management, diminished quality of life (QOL), and burden of pain.¹ FMS is characterized by chronic musculoskeletal pain accompanied by fatigue, sleep, memory, and mood issues.² Researchers believe that fibromyalgia amplifies painful sensations by affecting the way the brain and spinal cord process painful and nonpainful signals.³ Lacking a reliable diagnostic biomarker, FMS is primarily diagnosed by elimination based on patient reports of symptoms.⁴ FMS is most frequently diagnosed among middle-aged White women who experience an array of mental and physical FMS comorbidities ranging from slight to severe.⁵ However, diagnostic homogeneity has limited understanding of how social, environmental, and structural influences (social determinants of health [SDOH]; e.g., race, education, socioeconomic status [SES], and rurality) influence FMS presentation and severity.⁶

The diversity and severity of FMS symptoms have led to considerable disparities in FMS pain burden and pain management.⁷ Studies have shown significant variation in both intra- and interindividual levels of pain and identified a variety of personal, physical, and psychosocial characteristics associated with FMS pain.^8,9 Higher levels of pain frequency and severity are associated with greater fatigue, lower social functioning, reduced self-reported QOL, and a higher prevalence of depression and anxiety.¹⁰ High levels of pain have been shown to significantly impact daily life leading to functional difficulty and frequent work absenteeism.¹¹ However, significant heterogeneity in FMS pain has also been met with skepticism and associated with weakness, emotionality, and objectification.¹²

Pain, FMS, and health disparities

Pain among individuals with FMS has been shown to vary by age, neighborhood, SES, and race.^13
–15 Compared with Whites, non-Hispanic Blacks experience a higher prevalence of chronic pain, greater levels of pain severity, and greater rates of pain-related disability. In addition to an increased prevalence of chronic pain, it has been reported that Blacks also have poorer treatment of chronic pain and subsequently worse chronic pain outcomes.^16,17 While women, in general, Blacks, those with a high school education or less, low-income earners, and individuals older than age 65 are more likely to report chronic pain than their respective counterparts (males, Whites, those with higher education, higher income earners, and individuals under age 65).¹⁸

These differences may arise from differential exposure to psychosocial and environmental factors such as adverse childhood experiences, racial discrimination, low SES, and depression, all of which have been associated with chronic stress and chronic pain.¹⁹ Frequently cited explanations for disparities in chronic health conditions include differences in SES,^15,18,20 education,²¹ childhood trauma,²² accumulated stress,²³ racial discrimination,^24,25 and neighborhood crime¹⁵ as well as mental disorders such as anxiety and depression.^26,27

Despite differences in the incidence, severity, and exposure to risk factors for chronic pain, FMS is more prevalent among White individuals than among racial and ethnic minorities^5,28—a differential that is believed to be circumstantial.²⁹ Marr⁵ hypothesized that Black women might be less likely to be diagnosed with FMS because of racial/ethnic health disparities and/or different cultural dispositions toward stress and suffering.

Furthermore, Pryma¹² suggested that women of color experienced racialized stigma when reporting their FMS symptoms. Others have suggested that the lower rates of diagnoses can be attributed to health care professionals distrusting racial/ethnic minority patients' claims of pain.¹² The diagnosis of FMS is exclusionary, often requiring that other possible causes for patients' symptoms be ruled out before a diagnosis is made.¹² For this reason, factors that limit or affect health-seeking behaviors such as education level, SES, and race play a role in whether the condition is recognized and correctly diagnosed by a health care provider.^30,31

Because racial/ethnic minorities are less likely to participate in research studies,^32
–34 few researchers have examined how the symptoms of FMS vary as a function of racial/ethnic minority status.¹² Some have suggested that FMS prevalence may be higher among racial/ethnic minority women than among White women.^29,35 Given the limitations in knowledge regarding the sources of differential diagnostic rates between Whites and other racial groups, it is important to know whether there are differences in FMS experience and symptomology between population cohorts.³⁶ This secondary data analysis examined racial differences in pain severity, pain interference with function, and treatment response.

Materials and Methods

Study design

This study used data previously collected as part of a randomized controlled clinical trial that examined the effect of a complementary therapy intervention (guided imagery) on biological and nonbiological indicators over the course of 10 weeks.³⁷ While the parent study examined symptoms of pain, fatigue, depression, and perceived stress in women with FMS, the authors report only on the symptom of pain for purposes of this secondary analysis. Study participants completed self-report forms to provide data regarding age, race/ethnicity, length of time since the diagnosis of FMS, marital status, employment status, SES, and medical and medication history.

Medical history included self-reported data on comorbid conditions of anxiety, asthma, depression, diabetes, heart disease, high blood pressure, irritable bowel syndrome (IBS), overweight, stiffness, self-reported weight, and height to determine body mass index, hours of sleep per night, exercise, smoking, and alcohol use. The purpose of the parent study was to examine a nonpharmacologic symptom management strategy in women diagnosed with FMS. The purpose of this secondary analysis was to use existing data to highlight disparate outcomes among women with persistent pain to elucidate a growing concern regarding pain and pain management in minoritized individuals.

Participants

In the parent study, a total of 72 women were recruited who met inclusion criteria: age >18 years, female, diagnosis of FMS as defined by the 1990 College of Rheumatology (ACR) criteria for FMS,³⁸ no known major psychiatric or neurological conditions that would interfere with study participations, and an ability to understand and sign the consent form. The parent study for this analysis was completed before the publications of the 2010 and 2016 revised FMS diagnostic criteria, respectively.^39,40 Exclusion criteria included presence of other systemic rheumatologic conditions, being treated for cancer/HIV, and/or being pregnant. Self-reported diagnosis was confirmed by the participant's primary physician or rheumatologist. The study was approved by the Institutional Review Board (IRB) of Virginia Commonwealth University. This secondary analysis was approved by the University of Florida IRB (IRB#202201113).

Outcome measure

Pain was measured using The Brief Pain Inventory (BPI) Short form.³⁹ The BPI assesses pain severity (BPI-S) and pain interference (BPI-I) and uses 0–10 numeric scales for item rating; higher scores indicate increased pain/interference. Participants were asked to rate pain within the past 24 h. In widespread testing, the Cronbach's alpha reliability ranges from 0.71 to 0.91.⁴¹ Comparatively, Cronbach's alpha calculated from these data were 0.81 for BPI-S and 0.76 for BPI-I. Numerous studies have shown that the BPI and both subscales are reliable and valid instruments for assessing pain among women with FMS.^42
–44

Procedure

Data consisted of up to three observations for each participant collected over 10 weeks. To evaluate differences between Black and White participants, the authors first calculated descriptive mean and frequency values for those characteristics of interest. Student's t tests and chi-square tests were used to compare mean and frequency differences between the two groups. To account for differences in age, diagnoses, and duration of FMS symptoms, time series Poisson regression models were estimated. The Poisson distribution was selected given the limited range and highly skewed nature of the outcomes.⁴⁵

Regression models were specified separately using BPI severity and BPI interference. Models were first specified using only control variables and demographic characteristics. Second, indicators of comorbid conditions were added to account for diagnostic heterogeneity in the sample. Age and duration of FMS symptoms (in logarithmic form) were included as continuous variables. Binary indicators for Black race, income below $29,999 (aka, “low-income”), and membership in the control group were added. Controls for each visit after baseline accounted for variation in time. Since individual pain level is likely heavily dependent on previous levels of pain, a lagged dependent variable was used to ensure robust estimates. To account for differential representation among groups, an interaction term between control group membership and race was included.

Finally, binary indicators for behavioral characteristics and potentially confounding conditions were added. Conditions included IBS, anxiety, asthma, heart disease, diabetes, high blood pressure, and stiffness. Behavioral indicators included smoking and alcohol consumption.

Results

Descriptive statistics

Table 1 lists mean and frequency values for sample demographic characteristics by race. The sample consisted of 51 White and 21 Black women with average ages of 45.02 (standard deviation [SD] = 14.85) and 51.43 (SD = 7.51), respectively (t = 1.88, p = 0.0648). On average, White women had experienced FMS symptoms for 10.48 (SD = 8.80) years, while Black women had experienced symptoms for 9.51 (SD = 7.81) years, but the difference was not statistically significant (t = 0.44, p = 0.661). About 20% of White women were regular smokers (n = 9) compared with 33% of Black women (n = 7), but the difference was insignificant (χ ² = 0.2491, p = 0.6177). Over half of both groups experienced anxiety (White 74.42% and Black 66.67%) and joint stiffness (White 79.07% and Black 66.67%); however, racial groups did not show any statistically significant differences in their comorbidity profiles.

Table 1.

Sample Characteristics and Between-Group Differences by Race for Women Diagnosed with Fibromyalgia

	N	Mean	Non-Black (N = 51)			N	Mean	Black (N = 21)			t	Probability
	N	Mean	SD	Min	Max	N	Mean	SD	Min	Max	t	Probability
Age	51	45.02	14.85	18	71	21	51.43	7.51	40	64	−1.88	0.0648
BPI severity (Visit 1)	51	4.61	2.06	0.25	9.5	21	5.83	2.08	2.25	9.0	−2.28	0.0258
BPI severity (Visit 2)	44	4.44	1.98	0.25	8.5	19	5.55	2.48	0.5	9.25	−1.93	0.0585
BPI severity (Visit 3)	43	4.64	2.26	0.5	9.25	19	5.14	1.83	2	8	−0.86	0.3951
BPI interference (Visit 1)	51	5.17	2.68	0	10.0	21	6.10	2.63	0.57	9.86	−1.36	0.1793
BPI interference (Visit 2)	44	4.47	2.80	0	9.57	19	5.59	3.05	0	9.57	−1.41	0.1638
BPI interference (Visit 3)	43	4.43	2.82	0	9.43	19	4.87	2.51	1.14	9.57	−0.59	0.5604
Duration of symptoms	51	10.48	8.80	0.25	43	21	9.51	7.81	0.58	30	−0.44	0.661
											Chi-square	Probability
Control	16	37.21				15	71.43				5.4454	0.0196
Smoking	9	20.93				7	33.33				0.2491	0.6177
Alcohol	20	46.51				7	33.33				1.143	0.285
Irritable bowel syndrome	17	39.53				5	23.81				1.9446	0.1632
Anxiety	32	74.42				14	66.67				0.736	0.3909
Asthma	6	13.95				6	28.57				2.2159	0.1366
Heart disease	1	2.33				1	4.76				0.0263	0.8712
Diabetes	2	4.65				6	28.57				9.1513	0.0025
Low income	14	32.56				8	38.10				0.0045	0.9466
High blood pressure	12	27.91				10	47.62				3.3505	0.0672
Stiffness	34	79.07				14	66.67				1.098	0.2947

Age Min = minimum participant age; Age Max = maximum participant age; BPI Min = lowest score; BPI Max = highest score control = no intervention received.

BPI, Brief Pain Inventory; SD, standard deviation.

At baseline (visit 1), White women had lower BPI severity 4.61 (SD = 2.06) and BPI interference (5.17, SD = 2.68) than Black women (BPI severity 5.83, SD = 2.08; BPI interference 6.10, SD = 2.63)—a statistically significant disparity (t = 2.28, p = 0.0258). As seen in Figure 1, Black women had higher average BPI interference and BPI severity scores at visits 2 and 3 as well, but mean values did not reach statistical significance. Each group demonstrated decline in both BPI metrics over time. To further evaluate these differences, regression analysis was conducted.

FIG. 1.

Brief pain interference with function and brief pain severity scores by race.

Initial regression

Tables 2 and 3 list results from regression models for BPI severity and interference, respectively. Initially, a “base” model was specified with covariates for age, race, income, duration of symptoms, treatment/control group, pain reported at baseline, visit number, and a binary indicator for participation in the control group. An interaction term between Black race and membership in the control group was also added to assess any racial differences in the treatment effect. Next, covariates were added for behavior and comorbid characteristics, including smoking, alcohol use, IBS, anxiety, asthma, heart disease, diabetes, high blood pressure, and stiffness.

Table 2.

Determinants of Brief Pain Inventory Severity Among Women with Fibromyalgia Syndrome

	Model fit statistics
	Regression 1 (demographic and individual variables)	Regression 2 (demographic and individual variables plus comorbidities)
-2 Res Log Likelihood	732.6	723.6
AIC (smaller is better)	736.6	727.6
AIC (smaller is better)	736.7	727.6
BIC (smaller is better)	741.2	732.1
Chi-square	15.8	20.36

	Estimate	SE	t	Pr>[t]	CI lower	CI upper	Estimate	SE	t	Pr>[t]	CI lower	CI upper
Intercept	3.9843	0.8155	4.89	<0.0001	2.3433	5.6253	3.6619	1.0299	3.56	0.0009	1.5841	5.7397
Age	0.005331	0.01478	0.36	0.72	−0.02443	0.0351	0.008382	0.01805	0.46	0.6448	−0.02806	0.04483
Visit 2	−0.5741	0.443	−1.3	0.1972	−1.4498	0.3017	−2.0368	0.4678	−4.35	<0.0001	1.0948	2.9788
Visit 3	−0.5346	0.4055	−1.32	0.1898	−1.3371	0.268	0.06486	0.7447	0.09	0.931	−1.4409	1.5706
Low income	2.0185	0.3834	5.26	<0.0001	1.2488	2.7882	1.868	0.4962	3.78	0.03085	1.189	1.8955
Black	0.2631	0.06526	2.33	0.02456	0.1041	0.5304	0.3573	0.4446	2.08	0.04229	0.5216	1.2363
Control	−0.03697	0.4463	−0.08	0.9344	−0.936	0.8621	−0.3333	0.4052	−0.82	0.4124	−1.1353	0.4687
Black^* control	1.0518	0.8324	1.26	0.2132	−0.6267	2.7302	1.2102	1.0402	1.16	0.2516	−0.8924	3.3128
BPI severity₀	0.08355	0.073	1.14	0.2544	−0.0608	0.2279	0.04473	0.07303	0.61	0.5413	−0.09973	0.1892
Duration	−0.1552	0.1723	−0.9	0.3729	−0.5028	0.1925	−0.07786	0.2061	−0.38	0.7077	−0.4946	0.3389
Smoking							0.2515	0.4799	0.52	0.603	−0.7167	1.2196
Alcohol							−0.1275	0.4118	−0.31	0.7585	−0.959	0.7041
IBS							−0.1174	0.4412	−0.27	0.7915	−1.0086	0.7738
Anxiety							0.4355	0.4562	0.95	0.3454	−0.4861	1.3571
Asthma							0.05158	0.557	0.09	0.9267	−1.072	1.1751
Heart disease							1.5621	1.0371	1.51	0.139	−0.5266	3.6508
Diabetes							0.1451	0.6795	0.21	0.832	−1.2269	1.517
HBP							−0.00818	0.4569	−0.02	0.9858	−0.9306	0.9142
Stiffness							0.3744	0.5376	−0.7	0.4902	−1.4608	0.7121

Bold font: Denotes significance at 95% level.

Control = No intervention received; BPI Severity₀ = Brief Pain Inventory-pain severity at baseline (time 1); Duration- = duration of symptoms.

CI, confidence interval; HBP, high blood pressure; IBS, irritable bowel syndrome; SE, standard error.

Table 3.

Determinants of Brief Pain Inventory Interference with Function Among Women with Fibromyalgia Syndrome

	Model fit statistics
	Regression 1 (demographic and individual variables)	Regression 2 (demographic and individual variables plus comorbidities)
-2 Res Log Likelihood	839.9	819.3
AIC (smaller is better)	843.9	823.3
AIC (smaller is better)	843.9	823.4
BIC (smaller is better)	848.4	827.9
Chi-square	10.96	16.56

	Estimate	SE	t	Pr>[t]	CI lower	CI upper	Estimate	SE	t	Pr>[t]	CI lower	CI upper
Intercept	4.912	0.9832	5	<0.0001	2.9322	6.8919	4.1132	1.1854	3.47	0.0012	1.7257	6.5007
Age	0.01057	0.01769	0.6	0.5532	−0.02507	0.04621	0.002842	0.02064	0.14	0.8911	−0.03877	0.04445
Visit 2	−1.5657	0.5197	−3.01	0.003	−2.5924	−0.539	1.7244	0.5335	3.23	0.0023	0.6505	2.7982
Visit 3	−1.6823	0.451	−3.73	0.0003	−2.5752	−0.7894	−0.3781	0.851	−0.44	0.6591	−2.0962	1.34
Low income	2.1927	0.4596	4.77	<0.0001	1.2696	3.1159	0.9288	0.5698	2.63	0.011	0.2202	1.1804
Black	0.3575	0.07797	−2.2	0.0481	0.4184	0.7334	0.2557	0.5161	2.43	0.0161	0.2031	0.2661
Control	−0.5896	0.5358	−1.1	0.2772	−1.6697	0.4906	−1.4079	0.4463	−3.15	0.002	−2.2912	−0.5245
Black^* control	1.5244	0.9993	1.53	0.1347	−0.4928	3.5415	1.8115	1.1925	1.52	0.1363	−0.5954	4.2184
BPI-IWF.₀	0.1781	0.07314	2.44	0.0161	0.03358	0.3227	0.1276	0.07256	1.76	0.0808	0.01584	0.271
Duration	−0.4048	0.2063	−1.96	0.0566	−0.8214	0.01184	−0.3527	0.2362	−1.49	0.1429	−0.8294	0.124
Smoking							0.9273	0.5532	1.68	0.1005	−0.1863	2.0409
Alcohol							−0.2365	0.4714	−0.5	0.6184	−1.1867	0.7136
IBS							−0.4129	0.5065	−0.82	0.4194	−1.4344	0.6086
Anxiety							0.9152	0.5168	1.77	0.0836	−0.1266	1.957
Asthma							0.5601	0.6423	0.87	0.3878	−0.7333	1.8536
Heart disease							2.2954	1.2051	1.9	0.0627	−0.1268	4.7175
Diabetes							0.5647	0.7825	0.72	0.4743	−1.0126	2.142
HBP							0.05556	0.5238	−0.11	0.916	−1.1113	1.0002
Stiffness							0.6362	0.616	1.03	0.3076	−0.6071	1.8794

Bold font: Denotes significance at 95% level.

Control = no intervention received; BPI-IWF.₀ = Brief Pain Inventory-interference with function at baseline (time 1); Duration- = duration of symptoms.

An interaction term between Black race and membership in the control group indicated that, compared with White women in the control group, Black women experienced significantly differential BPI severity (1.0518, confidence interval [CI] = 0.6267 to 2.7302) and BPI interference (1.5244, CI = 0.0493 to 3.5415) effects from treatment.

Fully adjusted regression

After controlling for demographic differences, previous BPI severity, and participation in the treatment/control groups, Black women experienced significantly higher BPI severity (0.2631, CI = −1.01 to 1.53) even after controlling for behavioral and comorbidity differences (0.2164, CI = −1.46 to 1.60). Low-income women also show significantly higher BPI severity (2.0185, CI = 1.25 to 2.79) despite the addition of supplement covariates (2.0379, CI = 1.03 to 3.04). Neither behavioral nor comorbidity characteristics reached statistical significance.

Black (0.3575, CI = −0.03 to 0.42) and low-income (2.1927, CI = 1.27 to 3.12) women showed significantly higher BPI interference in both model specifications (Black 0.3942, CI = 0.13 to 0.45; low income 1.7784, CI = 0.63 to 2.92). Previous BPI severity level was positively related to current BPI severity (0.1781, CI = 0.03, 0.32), but significance was not retained after the addition of supplemental controls. BPI severity significantly decreased through the panel (visit 2: −1.5657, CI = −2.59 to −0.54; visit 3: −1.6823, CI = −2.58 to −0.79) even after controlling for initial pain and comorbid conditions. Lack of significance in the racial interaction term (1.5244, CI = −0.49 to 3.54) suggests similar treatment effects between racial groups.

Discussion

After accounting for differences in age, duration of diagnosis, and prior pain levels, results showed that, on average, Black women and low-income earners with FMS had significantly higher pain severity/pain interference than White women. These groups also showed a lower average dose response to guided imagery with disparities shown to persist throughout the study. While exploration of causality is outside the scope of this analysis, findings show significant racial and socioeconomic differences in pain severity and interference. These findings concur with earlier studies that have similarly focused on chronic pain.^17,46
–48

For example, Green⁴⁸ showed greater pain severity among Blacks compared with non-Hispanic, Whites at a tertiary care pain center. Furthermore, a systematic review of chronic pain literature showed that greater levels of clinical pain could be attributed to disparities in culture, environment, and chronic morbidities.¹⁷ However, other researchers have posited that disparities in pain between Black and White women could result from differences in exposure to physical, psychological, and social impairment,⁴⁷ or result from a stronger link between emotions and pain behaviors among Blacks.^47,49,50

While there is no consensus on the cause of racial and ethnic differences in pain, numerous studies have documented inconsistent pain mitigation treatment between Blacks, Hispanics, and Whites observed in a variety of settings, including pain clinics,⁴⁷ hospice care, hospital emergency departments, and nursing homes.^{51

–58} Compared with Whites, minority patients are less likely to receive pain medication,^52,55,59 less likely to receive opiates for pain,^51,52,54,55 and less likely to receive treatment consistent with the World Health Organization recommendations.⁶⁰ However, compared with White, racial and ethnic minorities are more likely to receive lower doses of pain medications⁵² and more likely to experience longer wait times to receipt of pain medication.^53,61 In general, extensive research indicates that the pain management needs of Black individuals are adequately met less frequently than Whites^62
–64 thereby resulting in increased morbidity and mortality.⁴⁷

In addition to differential experiences in the health system, research suggests that racial/ethnic groups have different emotional, behavioral, and physical response to pain,^65,66 which may stem from variations in cultural perceptions, expectations, and past experiences. These cultural factors include pain expression, pain language, lay remedies for pain, social roles, expectations, and perceptions of the medical care system.⁶⁷ Racial/ethnic variation in pain coping strategies depend not only on their view of pain, but also their perceived ability to cope with pain.⁶⁸ Therefore, differences in pain perception, pain response, pain coping, and pain mitigation effectiveness likely contribute to disparities in their pain experience.

Different cultural beliefs about the origin and the purpose of pain may be grounded in religion and spirituality⁶⁹ and precipitate in variations in the acknowledgment, acceptance, and response to pain and the use of pain-relieving medications.^70,71 While religiosity and spirituality have both positive and negative impacts on pain experiences, these effects are larger for racial/ethnic minority patients compared with Whites.^72
–74 Among Blacks, religious participation is associated with improved health status, higher QOL, more positive pain and symptom attitudes, more social support, positive mental health outcomes,⁷⁵ and a greater likelihood of taking pain medication. Compared with individuals who do not participate in religious observances, those with religious beliefs have lower psychological distress, lower pain scores, and less depression.^8,76

However, spirituality can negatively affect the pain experience through acceptability of health care interventions^75,77; the stigmatization of certain diseases/conditions that may reduce the likelihood of receiving health services⁷⁸; and the belief that religious transgressions, lack of faith, or the individual's behavior are responsible for the pain.^79,80

Limitations

Some limitations to our study must be acknowledged. First, this was a single-center design and data only included Black and White women residing in a localized geographic area of the United States. Therefore, findings are not generalizable outside the scope of these parameters, and the authors are unable to comment on any possible differences that may exist between these women and the national U.S. population. In addition, 72 women (51 White and 21 Black) were recruited into the initial study sample, but only 62 (44 White and 19 Black) completed the study protocol. Unequal rates of sample attrition (13% White and 10% Black) could have potentially influenced findings. Also, individuals with FMS may experience varying levels of pain at different points in time.

Persistent levels of severe pain may represent different levels of disease severity. Those with more severe symptoms could be those who are most likely to participate in research. Furthermore, additional comorbidities may have been present outside of those included on the initial patient questionnaire. Since FMS is a polysymptomatic condition with a high degree of variability among individuals,⁸¹ the study of individuals with FMS is inevitably influenced by the characteristics of the patient cohort. While evidence suggests that FMS is likely underdiagnosed among minority racial or ethnic groups, this study only included individuals with a confirmed diagnosis of FMS. Individuals with symptomology profiles resembling FMS who had not received a formal diagnosis were not included in the study.

A final limitation to the parent study was that while self-reported medication usage was collected at baseline, it was not tracked at 6 and 10 weeks and, therefore, was not accounted for in comparison with intervention outcomes.³⁷ The authors acknowledge that future studies should include data that report medication use across time so as to demonstrate the potential impact of the nonpharmacologic intervention on both pain and medication usage. This is particularly relevant given the paucity of studies that have examined the effect of guided imagery on perceived pain and opioid or other analgesic dosage outcomes.⁸²

Conclusion

In this study, Black women, and those with earnings below $29,999, had higher pain severity and pain interference as measured by the BPI than other racial and income groups despite reporting a shorter duration of symptom persistence. Even after controlling for age, income, and the duration of FMS symptoms, Black women showed significantly higher pain than their White counterparts.

While the data cannot directly attribute these disparities to any single factor, when coupled with other research showing that social, environmental, and psychological factors play a large role in pain perception,^46,49 they suggest that SDOH may amplify FMS severity and presentation as they do with other conditions such as stroke, heart attack, and cancer.^49,83 Psychological trauma suffered from years of discrimination and racial bias coupled with limited financial resources, lower availability of health care, and poorer physical conditions manifests as higher pain severity and greater interference with function among Black women with FMS.^84,85 However, the intersectional nature of these influences makes attribution difficult and correction improbable. Therefore, greater awareness among clinicians and diagnosticians of these influences and dedication to the management of FMS symptoms for a diversity of women is imperative.

Footnotes

Authors' Contributions

M.J. conducted the data curation and formal analysis. She also formulated the methodology and initial conceptualization of this article. E.C. aided with the data curation in addition to the writing and editing of the submitted article. V.M. contributed to the conceptualization of the topic as well as the writing, review, and editing of the article.

Author Disclosure Statement

No competing financial interests exist.

Funding Information

This research received no specific grant from any funding agency in the public, commercial, or not-for-profit sectors.

References

Kashikar-Zuck

, Ting

. Juvenile fibromyalgia: Current status of research and future developments. Nat Rev Rheumatol, 2014; 10(2):89–96; 10.1038/nrrheum.2013.177

Heidari

, Afshari

, Moosazadeh

. Prevalence of fibromyalgia in general population and patients, a systematic review and meta-analysis. Rheumatol Int, 2017; 37(9):1527–1539; 10.1007/s00296-017-3725-2

Lee

, Nassikas

, Clauw

. The role of the central nervous system in the generation and maintenance of chronic pain in rheumatoid arthritis, osteoarthritis and fibromyalgia. Arthritis Res Ther, 2011; 13(2):211; 10.1186/ar3306

Wang

, Han

, Lee

, et al. Fibromyalgia diagnosis: A review of the past, present and future. Expert Rev Neurother, 2015; 15(6):667–679; 10.1586/14737175.2015.1046841

Marr

, Van Liew

, Carovich

, et al. The effects of racial/ethnic minority status on sleep, mood disturbance, and depression in people with fibromyalgia. Psychol Res Behav Manag, 2020; 13:343–353; 10.2147/PRBM.S242699

Rodrigues-de-Souza

, Palacios-Ceña

, Moro-Gutiérrez

, et al. Socio-cultural factors and experience of chronic low back pain: A Spanish and Brazilian Patients' Perspective. A qualitative study. PLoS One, 2016; 11(7):e0159554; 10.1371/journal.pone.0159554

Luo

, Cappelleri

, Chandran

. The burden of fibromyalgia: Assessment of Health Status Using the EuroQol (EQ-5D) in patients with fibromyalgia relative to other chronic conditions. Health Outcomes Res Med, 2011; 2(4):e203–e214.

Harris

, Williams

, McLean

, et al. Characterization and consequences of pain variability in individuals with fibromyalgia. Arthritis Rheum, 2005; 52(11):3670–3674; 10.1002/art.21407

Offenbaecher

, Kohls

, Ewert

, et al. Pain is not the major determinant of quality of life in fibromyalgia: Results from a retrospective “real world” data analysis of fibromyalgia patients. Rheumatol Int, 2021; 41(11):1995–2006; 10.1007/s00296-020-04702-5

10.

Bartley

, Robinson

, Staud

. Pain and fatigue variability patterns distinguish subgroups of fibromyalgia patients. J Pain, 2018; 19(4):372–381; 10.1016/j.jpain.2017.11.014

11.

Bourgaize

, Newton

, Kumbhare

, et al. A comparison of the clinical manifestation and pathophysiology of myofascial pain syndrome and fibromyalgia: Implications for differential diagnosis and management. J Can Chiropr Assoc, 2018; 62(1):26–41.

12.

Pryma

. “Even my sister says I'm acting like a crazy to get a check”: Race, gender, and moral boundary-work in women's claims of disabling chronic pain. Soc Sci Med, 2017; 181:66–73; 10.1016/j.socscimed.2017.03.048

13.

Theoharides

, Tsilioni

, Arbetman

, et al. Fibromyalgia syndrome in need of effective treatments. J Pharmacol Exp Ther, 2015; 355(2):255–263; 10.1124/jpet.115.227298

14.

Lourenço

, Costa

, Rodrigues

, et al. Gender and psychosocial context as determinants of fibromyalgia symptoms (fibromyalgia research criteria) in young adults from the general population. Rheumatology, 2015; 54(10):1806–1815; 10.1093/rheumatology/kev110

15.

Maly

, Vallerand

. Neighborhood, socioeconomic, and racial influence on chronic pain. Pain Manag Nurs Off J Am Soc Pain Manag Nurses, 2018; 19(1):14–22; 10.1016/j.pmn.2017.11.004

16.

Reyes-Gibby

, Aday

, Todd

, et al. Pain in aging community-dwelling adults in the United States: Non-Hispanic Whites, Non-Hispanic Blacks, and Hispanics. J Pain Off J Am Pain Soc, 2007; 8(1):75–84.

17.

Shavers

, Bakos

, Sheppard

. Race, ethnicity, and pain among the U.S. adult population. J Health Care Poor Underserved, 2010; 21(1):177–220; 10.1353/hpu.0.0255

18.

Janevic

, McLaughlin

, Heapy

, et al. Racial and socioeconomic disparities in disabling chronic pain: Findings from the health and retirement study. J Pain, 2017; 18(12):1459–1467; 10.1016/j.jpain.2017.07.005

19.

Aroke

, Joseph

, Roy

, et al. Could epigenetics help explain racial disparities in chronic pain?. J Pain Res, 2019; 12:701–710.

20.

Green

, Hart-Johnson

. The association between race and neighborhood socioeconomic status in Younger Black and White adults with chronic Pain. J Pain, 2012; 13(2):176–186; 10.1016/j.jpain.2011.10.008

21.

Anderson

, Green

, Payne

. Racial and ethnic disparities in pain: Causes and consequences of unequal care. J Pain, 2009; 10(12):1187–1204; 10.1016/j.jpain.2009.10.002

22.

Alvarez

, Green

, Levine

. Stress in the adult rat exacerbates muscle pain induced by early-life stress. Biol Psychiatry, 2013; 74(9):688–695; 10.1016/j.biopsych.2013.04.006

23.

Pervanidou

, Agorastos

, Kolaitis

, et al. Neuroendocrine responses to early life stress and trauma and susceptibility to disease. Eur J Psychotraumatology, 2017; 8(sup4):1351218; 10.1080/20008198.2017.1351218

24.

Hoffman

, Trawalter

, Axt

, et al. Racial bias in pain assessment and treatment recommendations, and false beliefs about biological differences between blacks and whites. Proc Natl Acad Sci U S A, 2016; 113(16):4296–4301.

25.

Burgess

, Grill

, Noorbaloochi

, et al. The effect of perceived racial discrimination on bodily pain among older African American men. Pain Med, 2009; 10(8):1341–1352; 10.1111/j.1526-4637.2009.00742.x

26.

Cruz-Almeida

, King

, Goodin

, et al. Psychological profiles and pain characteristics of older adults with knee osteoarthritis. Arthritis Care Res, 2013; 65(11):1786–1794; 10.1002/acr.22070

27.

Moix

, Kovacs

, Martín

, et al. The Spanish Back pain research network. catastrophizing, state anxiety, anger, and depressive symptoms do not correlate with disability when variations of trait anxiety are taken into account. A study of chronic low back pain patients treated in Spanish pain units [NCT00360802]. Pain Med, 2011; 12(7):1008–1017; 10.1111/j.1526-4637.2011.01155.x

28.

Haviland

, Morton

, Oda

, et al. Traumatic experiences, major life stressors, and self-reporting a physician-given fibromyalgia diagnosis. Psychiatry Res, 2010; 177(3):335–341; 10.1016/j.psychres.2009.08.017

29.

Raphael

, Janal

, Nayak

, et al. Psychiatric comorbidities in a community sample of women with fibromyalgia. Pain, 2006; 124(1–2):117–125. 10.1016/j.pain.2006.04.004

30.

Begley

, Basu

, Lairson

, et al. Socioeconomic status, health care use, and outcomes: Persistence of disparities over time. Epilepsia, 2011; 52(5):957–964; 10.1111/j.1528-1167.2010.02968.x

31.

Vickrey

, Shapiro

. Disparities research in neurology: An urgent need. Nat Rev Neurol, 2009; 5(4):184–185; 10.1038/nrneurol.2009.30

32.

Fisher

, Kalbaugh

. Challenging assumptions about minority participation in US clinical research. Am J Public Health, 2011; 101(12):2217–2222; 10.2105/AJPH.2011.300279

33.

Liu

, Elliott

, Strelnick

, et al. Asian Americans are less willing than other racial groups to participate in health research. J Clin Transl Sci, 2019; 3(2–3):90–96; 10.1017/cts.2019.372

34.

Patel

, Staples

, Garcia

, et al. Are ethnic and racial minority women less likely to participate in clinical trials?. Gynecol Oncol, 2020; 157(2):323–328; 10.1016/j.ygyno.2020.01.040

35.

Menzies

, Kim

. Relaxation and guided imagery in Hispanic persons diagnosed with fibromyalgia: A pilot study. Fam Community Health, 2008; 31(3):204–212; 10.1097/01.FCH.0000324477.48083.08

36.

Wolfe

, Clauw

, Fitzcharles

, et al. The American College of Rheumatology preliminary diagnostic criteria for fibromyalgia and measurement of symptom severity. Arthritis Care Res, 2010; 62(5):600–610; 10.1002/acr.20140

37.

Menzies

, Lyon

, Elswick

, et al. Effects of guided imagery on biobehavioral factors in women with fibromyalgia. J Behav Med, 2014; 37(1):70–80; 10.1007/s10865-012-9464-7

38.

Wolfe

, Smythe

, Yunus

, et al. The American College of Rheumatology 1990 Criteria for the Classification of Fibromyalgia. Report of the Multicenter Criteria Committee. Arthritis Rheum, 1990; 33(2):160–172; 10.1002/art.1780330203

39.

Wolfe

, Clauw

, Fitzcharles

, et al. Fibromyalgia criteria and severity scales for clinical and epidemiological studies: A modification of the ACR Preliminary Diagnostic Criteria for Fibromyalgia. J Rheumatol, 2011; 38(6):1113–1122; 10.3899/jrheum.100594

40.

Wolfe

, Clauw

, Fitzcharles

, et al. 2016 Revisions to the 2010/2011 fibromyalgia diagnostic criteria. Semin Arthritis Rheum, 2016; 46(3):319–329; 10.1016/j.semarthrit.2016.08.012

41.

Cleeland

, Ryan

. Pain assessment: Global use of the Brief Pain Inventory. Ann Acad Med Singapore, 1994; 23(2):129–138.

42.

D'Onghia

, Ciaffi

, Lisi

, et al. Fibromyalgia and obesity: A comprehensive systematic review and meta-analysis. Semin Arthritis Rheum, 2021; 51(2):409–424; 10.1016/j.semarthrit.2021.02.007

43.

Mortensen

, Kristensen

, Brooks

, et al. Women with fibromyalgia's experience with three motion-controlled video game consoles and indicators of symptom severity and performance of activities of daily living. Disabil Rehabil Assist Technol, 2015; 10(1):61–66; 10.3109/17483107.2013.836687

44.

, Chen

, Zheng

, et al. Benefits of exergame training for female patients with fibromyalgia: A systematic review and meta-analysis of randomized controlled trials. Arch Phys Med Rehabil, 2022; 103(6):1192–1200.e2; 10.1016/j.apmr.2021.10.022

45.

Goulet

, Buta

, Bathulapalli

, et al. Statistical models for the analysis of zero-inflated pain intensity numeric rating scale data. J Pain, 2017; 18(3):340–348; 10.1016/j.jpain.2016.11.008

46.

Meints

, Wang

, Edwards

. Sex and race differences in pain sensitization among patients with chronic low back pain. J Pain, 2018; 19(12):1461–1470; 10.1016/j.jpain.2018.07.001

47.

Ndao-Brumblay

, Green

. Racial differences in the physical and psychosocial health among black and white women with chronic pain. J Natl Med Assoc, 2005; 97(10):1369–1377.

48.

Green

, Anderson

, Baker

, et al. The unequal burden of pain: Confronting racial and ethnic disparities in pain. Pain Med, 2003; 4(3):277–294; 10.1046/j.1526-4637.2003.03034.x

49.

Edwards

, Fillingim

, Keefe

. Race, ethnicity and pain. Pain, 2001; 94(2):133–137; 10.1016/S0304-3959(01)00408-0

50.

Riley

, Wade

, Myers

, et al. Racial/ethnic differences in the experience of chronic pain. Pain, 2002; 100(3):291–298; 10.1016/S0304-3959(02)00306-8

51.

Pletcher

, Kertesz

, Kohn

, et al. Trends in opioid prescribing by race/ethnicity for patients seeking care in US emergency departments. JAMA, 2008; 299(1):70–78; 10.1001/jama.2007.64

52.

Chen

, Shofer

, Dean

, et al. Gender disparity in analgesic treatment of emergency department patients with acute abdominal pain. Acad Emerg Med Off J Soc Acad Emerg Med, 2008; 15(5):414–418; 10.1111/j.1553-2712.2008.00100.x

53.

Epps

, Ware

, Packard

. Ethnic wait time differences in analgesic administration in the emergency department. Pain Manag Nurs Off J Am Soc Pain Manag Nurses, 2008; 9(1):26–32; 10.1016/j.pmn.2007.07.005

54.

Chen

, Kurz

, Pasanen

, et al. Racial differences in opioid use for chronic nonmalignant pain. J Gen Intern Med, 2005; 20(7):593–598; 10.1111/j.1525-1497.2005.0106.x

55.

Heins

, Grammas

, Heins

, et al. Determinants of variation in analgesic and opioid prescribing practice in an emergency department. J Opioid Manag, 2006; 2(6):335–340; 10.5055/jom.2006.0049

56.

Heins

, Heins

, Grammas

, et al. Disparities in analgesia and opioid prescribing practices for patients with musculoskeletal pain in the emergency department. J Emerg Nurs, 2006; 32(3):219–224; 10.1016/j.jen.2006.01.010

57.

Todd

, Deaton

, D'Adamo

, et al. Ethnicity and analgesic practice. Ann Emerg Med, 2000; 35(1):11–16; 10.1016/s0196-0644(00)70099-0

58.

Tamayo-Sarver

, Hinze

, Cydulka

, et al. Racial and ethnic disparities in emergency department analgesic prescription. Am J Public Health, 2003; 93(12):2067–2073; 10.2105/ajph.93.12.2067

59.

Kposowa

, Tsunokai

. Searching for relief: Racial differences in treatment of patients with back pain. Race Soc, 2002; 5(2):193–223; 10.1016/j.racsoc.2004.01.004

60.

Pergolizzi

, Böger

, Budd

, et al. Opioids and the management of chronic severe pain in the elderly: Consensus statement of an International Expert Panel with focus on the six clinically most often used World Health Organization Step III opioids (buprenorphine, fentanyl, hydromorphone, methadone, morphine, oxycodone). Pain Pract Off J World Inst Pain, 2008; 8(4):287–313; 10.1111/j.1533-2500.2008.00204.x

61.

Lee

, Burelbach

, Fosnocht

. Hispanic and non-Hispanic white patient pain management expectations. Am J Emerg Med, 2001; 19(7):549–550; 10.1053/ajem.2001.28038

62.

Portenoy

, Ugarte

, Fuller

, et al. Population-based survey of pain in the United States: Differences among white, African American, and Hispanic subjects. J Pain, 2004; 5(6):317–328; 10.1016/j.jpain.2004.05.005

63.

OMara

, Arenella

. Minority representation, prevalence of symptoms, and utilization of services in a large metropolitan hospice. J Pain Symptom Manage, 2001; 21(4):290–297; 10.1016/s0885-3924(01)00256-1

64.

Rhodes

, Xuan

, Halm

. African American Bereaved Family Members' Perceptions of Hospice Quality: Do Hospices with High Proportions of African Americans Do Better?. J Palliat Med, 2012; 15(10):1137–1141.

65.

Tan

, Jensen

, Thornby

, et al. Ethnicity, control appraisal, coping, and adjustment to chronic pain among Black and White Americans. Pain Med Malden Mass, 2005; 6(1):18–28; 10.1111/j.1526-4637.2005.05008.x

66.

Weissman

, Gordon

, Bidar-Sielaff

. Cultural aspects of pain management. J Palliat Med, 2004; 7(5):715–716; 10.1089/jpm.2004.7.715

67.

Lasch

. Culture, pain, and culturally sensitive pain care. Pain Manag Nurs Off J Am Soc Pain Manag Nurses, 2000; 1(3 Suppl 1):16–22; 10.1053/jpmn.2000.9761

68.

Cano

, Mayo

, Ventimiglia

. Coping, pain severity, interference, and disability: The potential mediating and moderating roles of race and education. J Pain, 2006; 7(7):459–468; 10.1016/j.jpain.2006.01.445

69.

Lovering

. Cultural attitudes and beliefs about pain. J Transcult Nurs Off J Transcult Nurs Soc, 2006; 17(4):389–395; 10.1177/1043659606291546

70.

, Lim

, Clark

, et al. African American cancer patients' pain experience. Cancer Nurs, 2008; 31(1):38–46; quiz 47–48; 10.1097/01.NCC.0000305685.59507.9e

71.

Francoeur

, Payne

, Raveis

, et al. Palliative care in the inner city. Patient religious affiliation, underinsurance, and symptom attitude. Cancer, 2007; 109(2 Suppl):425–434; 10.1002/cncr.22363

72.

Edwards

, Moric

, Husfeldt

, et al. Ethnic similarities and differences in the chronic pain experience: A comparison of African American, Hispanic, and white patients. Pain Med Malden Mass, 2005; 6(1):88–98; 10.1111/j.1526-4637.2005.05007.x

73.

Anderson

, Richman

, Hurley

, et al. Cancer pain management among underserved minority outpatients: Perceived needs and barriers to optimal control. Cancer, 2002; 94(8):2295–2304; 10.1002/cncr.10414

74.

Cotton

, Puchalski

, Sherman

, et al. Spirituality and religion in patients with HIV/AIDS. J Gen Intern Med, 2006; 21 Suppl 5:S5–S13; 10.1111/j.1525-1497.2006.00642.x

75.

Ang

, Ibrahim

, Burant

, et al. Ethnic differences in the perception of prayer and consideration of joint arthroplasty. Med Care, 2002; 40(6):471–476; 10.1097/00005650-200206000-00004

76.

Levin

, Chatters

, Taylor

. Religion, health and medicine in African Americans: Implications for physicians. J Natl Med Assoc, 2005; 97(2):237–249.

77.

Mitchell

, Lannin

, Mathews

, et al. Religious beliefs and breast cancer screening. J Womens Health 2002, 2002; 11(10):907–915; 10.1089/154099902762203740

78.

Lichtenstein

. Stigma as a barrier to treatment of sexually transmitted infection in the American deep south: Issues of race, gender and poverty. Soc Sci Med 1982, 2003; 57(12):2435–2445; 10.1016/j.socscimed.2003.08.002

79.

Satterly

. Guilt, shame, and religious and spiritual pain. Holist Nurs Pract, 2001; 15(2):30–39; 10.1097/00004650-200101000-00006

80.

Henderson

. The unnatural nature of pain. JAMA, 2000; 283(1):117; 10.1001/jama.283.1.117

81.

Wolfe

, Walitt

, Rasker

, et al. Primary and secondary fibromyalgia are the same: The universality of polysymptomatic distress. J Rheumatol, 2019; 46(2):204–212; 10.3899/jrheum.180083

82.

Garland

, Brintz

, Hanley

, et al. Mind-body therapies for opioid-treated pain: A systematic review and meta-analysis. JAMA Intern Med, 2020; 180(1):91–105; 10.1001/jamainternmed.2019.4917

83.

Link

. Epidemiological sociology and the social shaping of population health. J Health Soc Behav, 2008; 49(4):367–384; 10.1177/002214650804900401

84.

Spelman

, Hunt

, Seal

, et al. Post deployment care for returning combat veterans. J Gen Intern Med, 2012; 27(9):1200–1209; 10.1007/s11606-012-2061-1

85.

Carter

, Mazzula

, Victoria

, et al. initial development of the race-based traumatic stress symptom scale: Assessing the emotional impact of racism. Psychol Trauma Theory Res Pract Policy, 2013; 5:1–9; 10.1037/a0025911