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 (χ² = 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
			SD	Min	Max			SD	Min	Max
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.

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.