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. 2017 Jul 25;2017:6751856. doi: 10.1155/2017/6751856

Nonvitamin, Nonmineral Dietary Supplement Use among Adults with Fibromyalgia: United States, 2007–2012

Termeh Feinberg 1,2,*, Christa Lilly 3, Kim Innes 2,4
PMCID: PMC5547703  PMID: 28811828

Abstract

Background

Fibromyalgia (FMS) is a pain condition affecting 2–6% of US adults; effective treatment remains limited. Determinants of nonvitamin, nonmineral dietary supplement (NVNM) use among adults with FMS are not well-studied. We investigated the relation of NVNM use to FMS, and trends, in two nationally representative samples of US adults ≥18 years.

Methods

Data were drawn from 2007 and 2012 National Health Interview Surveys (N's = 20127 and 30672, resp.). Logistic regression was used to examine associations of FMS to NVNM use (past 12 months) and evaluate potential modifying influences of gender and comorbidities. Multivariate models adjusted for sampling design, demographic, lifestyle, and health-related factors.

Results

FMS was significantly higher in 2012 than in 2007 (1.7% versus 1.3%), whereas NVNM use decreased (57% versus 41%; p < 0.0001). Adults reporting diagnosis were more likely to use NVNMs within 12 months, 30 days, or ever relative to adults without; positive associations remained significant after controlling for demographics, lifestyle characteristics, medical history, and other confounders (ranges: 2007 and 2012 AORs = 2.3–2.7; 1.5–1.6, resp.; p's < 0.0001).

Conclusion

In this cross-sectional study of two national samples, NVNM use was strongly and positively associated with FMS, highlighting the need for further study.

1. Introduction

Fibromyalgia syndrome (FMS) is a rheumatologic neuropathic chronic pain syndrome affecting approximately 2.7% of populations of all ages across the world [1], including an estimated 1.8–6.4% of those in the US [2, 3]. FMS is characterized by a constellation of somatic symptoms (e.g., fatigue, sleep, mood disturbances, and cognitive impairment) that are typically present in addition to widespread pain [4]; the etiology of FMS is largely unknown [4]. Additionally, those with FMS may also experience high rates of comorbidity, such as osteoarthritis [5], autoimmune [6], kidney [7], respiratory [7], and cardiovascular [7, 8] disease, gastrointestinal conditions [7, 9], and headache [1, 7, 10]. Although FMS affects both sexes and people of all ages, the majority of US cases occur in Caucasian, middle-aged women [11, 12].

The chronic widespread pain characterizing FMS is difficult to manage, and many physicians remain unfamiliar with FMS diagnostic criteria and treatment [13] often making it difficult for patients to obtain an accurate FMS diagnosis and appropriate care. Although a lack of efficacy evidence for opioids as FMS treatment exists [14, 15] and opioid overdose deaths have more than tripled since 1999 [16, 17], FMS patients may receive opioid therapy [18]. Common treatments for FMS include antidepressants, anticonvulsants, muscle relaxants, and other pain medications [19]. Nonsteroidal anti-inflammatory drugs, which may carry side effects for as many as 25% of long-term users [20], are not currently recommended for FMS by any guidelines [19]. Although three drugs are FDA-approved for FMS treatment [21], these medications may carry significant side effects for some [22] and are not always effective for all [19]. Thus, patients may turn to complementary health approaches (CHAs, defined as medical/healthcare systems or practices used outside of mainstream medicine [23]) to manage symptoms [24]; back, neck, and joint pain are among the most commonly reported conditions for which patients use CHAs in the US [25, 26].

Nonvitamin, nonmineral dietary supplements (NVNMs) are a type of CHA used by nearly twenty-five percent of US adults with a musculoskeletal disorder [25] and include animal- and plant-derived products (i.e., fish oil, herbal dietary supplements). The extent and efficacy of NVNMs, particularly herbal dietary supplements, are largely unknown [27, 28]. Although a handful of large surveys have documented high rates of herbal and other NVNM use for chronic pain syndromes [24, 25, 29, 30], and anecdotal accounts indicate that a wide range of herbs have been used for the treatment of FMS [31], rigorous investigations regarding the prevalence and correlates of NVNM use in FMS remain limited. To address these gaps, we assessed the relation of FMS to NVNM use in two large, representative samples of US adults and examined potential changes in prevalence rates for NVNM use among those with FMS over a 5-year time period.

2. Materials and Methods

2.1. Data Sources

Participants for this study were drawn from two nationally representative samples of 23,501 and 34,525 US adults (National Health Interview Surveys (NHIS), 2007 and 2012, resp.). The NHIS is an annual national, cross-sectional household survey of the noninstitutionalized US population and is administered by the Centers for Disease Control and Prevention's National Center for Health Statistics. A supplement (adult alternative medicine) to the core individual, family, and household surveys asked participants about use of a broad range of CHAs, including herbs and other NVNMs, for both years. All questions were administered in a personal interview format. Adult response rates to the NHIS were 78.3% in 2007 and 79.7% in 2012, respectively [32].

The NHIS is the only national, public-use survey that includes comprehensive sets of questions regarding NVNM and other CHA use. Both 2007 and 2012 surveys used a stratified multistage probability design weighted on age, sex, and race/ethnicity, using 2000 and 2010 Census data for each, respectively. Both surveys oversampled Asian, Black, Hispanic, and minority elderly populations. Thus, each person in the covered population had a known nonzero probability of selection. Additional project details have been described elsewhere [32].

2.2. Study Population

Our analysis excluded participants who were <18 years of age, were pregnant, had functional limitation(s) due to senility, had a stroke and used a proxy to complete the interview, or had current cancer; those missing data on key covariates were also excluded, as were participants with extreme values for exercise (>6,000 minutes per week) in order to eliminate potential information bias. Further exclusion of persons with missing data on FMS and NVNM use (at 30 days, at 12 months, or ever using NVNMs) yielded final study samples of 20,127 and 30,672 adults for 2007 and 2012, respectively (Figure 1).

Figure 1.

Figure 1

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Study flow diagram for nonvitamin, nonmineral dietary supplement (NVNM) use in two national datasets.

2.3. Variables

2.3.1. Outcome Variables

The main outcome variable for this study was the reported use of NVNMs within the past 12 months (Y/N). We additionally assessed use of NVNMs within the previous 30 days (Y/N) and ever (Y/N). Briefly, survey participants were shown a card with a list of NVNMs (for which the majority were comprised of herbs or their compounds; 2007 list: 44 NVNM items with additional queries for up to two combination supplements, and 2012 list: 21 NVNM items with additional queries for up to two combination supplements) and queried for a dichotomous response regarding consumption of any “herbal or other nonvitamin supplements.” NVNMs included those labelled “dietary supplement” and in the form of pills, capsules, tablets, or (2012) liquids (including tinctures) and did not include homeopathic or cannabis products.

2.3.2. Exposure Variable

Our main exposure was fibromyalgia syndrome (FMS) (Y/N), ascertained as an affirmative response to fibromyalgia after being asked “Have you EVER been told by a doctor or other health professional that you had some form of arthritis, rheumatoid arthritis, gout, lupus, or fibromyalgia? Which of these were you told you had?”

2.3.3. Covariates

Demographics, lifestyle factors, health conditions, and medical care-related factors known or suspected to be associated with CHAs, NVNM use, and/or FMS were considered a priori as potential covariates in multivariate models. Demographic factors assessed included age, gender, race/ethnicity, education, employment, income, marital status, geographic region, and place of birth. Additional related factors included insurance status, annual family out-of-pocket medical costs, and delay of care due to concerns over cost. Lifestyle factors included smoking status, alcohol use, exercise, BMI (using the National Institutes of Health clinical classifications scores) [33], health status, and substance abuse. Health conditions included self-reported history of physician-diagnosed diabetes, kidney disease, gastrointestinal disorder, respiratory conditions, dyslipidemia, liver condition, rheumatoid arthritis, cardiovascular disease, hypertension, nonspecific arthritis, gout, migraines, mental health condition, insomnia, and previous cancer diagnosis. These variables are described in greater detail below.

2.4. Statistical Analysis

We conducted complete-case analyses using SAS 9.4 (Cary, NC, USA) and used sampling weights to account for complex survey procedures; these were adjusted for the probabilities of selection, nonresponse, and poststratification [34]. We merged NHIS family, person, household, sample adult, and adult alternative health files for each year and measured sample characteristics, including frequencies/prevalence rates of NVNM use (previous or current use, past 12 months, and past 30 days) for 2007 and 2012, respectively; we extrapolated estimates to generate population frequencies using NHIS sampling weights. Weighted t-tests and Rao-Scott Chi-square tests were used to determine significant differences by NVNM use status for three outcome time points in both survey years; significant factors were included in models as covariates. We also used a DOMAIN statement to keep our exclusions separate while maintaining the integrity of sampling weights and used Chi-square and t-tests to determine significant changes between 2007 and 2012 on weighted frequencies and means of all items, in addition to number of different NVNMs used, physician disclosure of NVNM use, and use of other CHAs. We considered trends between time points significant if there was no overlap in weighted percentage confidence intervals. Differences between participants with versus without missing data were assessed. All p values shown are two-sided at p ≤ 0.05.

Weighted logistic regressions were used to evaluate the independent associations of FMS diagnosis to NVNM use in the last 30 days or 12 months or ever. All multivariate models were adjusted for demographics and medical care-related factors; additional models also included lifestyle characteristics and health conditions.

Demographic characteristics included age (evaluated as both a continuous and categorical variable (18–24, 25–44, 45–64, 65–74, and 75+ years)), sex (male/female), race (“non-Hispanic White,” “non-Hispanic Black,” “Hispanic,” “Asian,” and “other”), marital status (“married/cohabitating,” “divorced/separated/widowed,” and “single”), education (“≤some HS,” “HS/GED,” “some college/AA/tech,” and “bachelor's degree+”), employment (“employed for pay,” “employed but not for pay,” and “unemployed”), income ($1–$24,999; $25,000–$44,999; $45,000–$74,999; $75,000+; “do not know;” and “missing”), geographic region (“northeast,” “midwest,” “south,” and “west”), and place of birth (US-born/other). Medical care-related factors included insurance status (“uninsured,” “Medicaid,” “Medicare,” “disability,” and “private”), annual out-of-pocket medical costs (“none”; <$500; $500–$1999; $2000–$2999; $3000–$4999; $5000 and over; and “do not know”), and delayed access to care because they “could not afford” or “worried about cost” (yes/no). Additional analyses also controlled for lifestyle-related factors, including BMI (evaluated as continuous and categorical (<18.5 = “underweight,” 18.5–25 = “underweight or normal weight,” 25–29.9 = “overweight,” 30–34.9 = “obese class 1,” and 35+ = “obese classes 2/3”)) [35]; tobacco use (“current smoker,” “former smoker,” and “never smoked”); alcohol use (“none,” “light,” and “moderate to heavy”); substance abuse other than tobacco or alcohol in past year (yes/no); and physical activity (continuous, in minutes/week).

In our fully adjusted models, we also evaluated the potentially confounding influence of self-reported health status (“excellent/very good/good,” “fair,” and “poor”), specific health conditions, and total number of health conditions; this comorbidity index was created from 0–13 participant-reported conditions, including a history of (1) diabetes; (2) kidney disease; (3) gastrointestinal disorder (including history of ulcers, inflammatory/irritable bowel disease, or constipation severe enough to require medication in the past year and/or (2012) abdominal pain, digestive allergy, and/or heartburn in the past year); (4) respiratory conditions (history of asthma or emphysema and/or chronic bronchitis); (5) dyslipidemia; (6) liver condition; (7) rheumatoid arthritis; (8) cardiovascular disease (coronary heart disease, angina, and/or heart attack); (9) hypertension; (10) nonspecific arthritis; (11) gout; (12) migraines; and (13) mental health condition (depression, phobias, and/or being often anxious in past year and/or ever having bipolar disorder). Health conditions were evaluated both collectively and individually; insomnia in the past year and previous cancer diagnosis were evaluated individually.

We also assessed the potential modifying influence of gender and presence of comorbid health conditions (0-1 versus 2+) on the association between FMS and NVNM use at each outcome time point and for each survey year by including the corresponding multiplicative-interaction term in age-adjusted models.

3. Results and Discussion

Relative to participants with complete data in both survey years, those with missing data on key covariates were less likely to be employed and report high educational attainment and more likely to be underweight, be older, and indicate poor reported health status (p's ≤ 0.0001). Participant age ranged from 18 to 85 years, averaging 47.5 ± 0.25 and 48.5 ± 0.18 years for 2007 and 2012, respectively. In both years, study participants were predominantly white (72.2% and 69.5%, resp.), female (53.1% and 53.5%), and insured (84.3% and 84.2%); most (56.4% and 57.9%) reported they never smoked cigarettes. Excluding prayer, most participants had used at least one CHA before (69.8% and 68.8%), and a majority had also used natural products other than NVNMs (60.4% and 62.4%) (not shown). In both years, 35% were overweight (mean BMI = 27.4 ± 0.05 and 27.7 ± 0.04, for 2007 and 2012, resp.), and most (63% and 72%) reported at least one chronic health condition, with the number of chronic health conditions increasing from a mean of 1.5 ± 0.02 in 2007 to 1.9 ± 0.01 in 2012.

Table 1 illustrates the distribution of demographic and lifestyle characteristics, stratified by year and NVNM use in the past 12 months; medical-related/health characteristics are displayed in Table 2. The percentage of adults reporting NVNM use (ever) declined significantly between time points (p < 0.0001) from 27.1% of the sample population in 2007 (n = 5057) to 24.2% in 2012 (n = 7238; not shown). In contrast, the percentage of adults reporting use of NVNMs within the last 12 months (19.1% to 18.5%, resp.) and 30 days (13.9% in both years; not shown) remained approximately the same. Prevalence of diagnosed FMS also increased from 1.3% to 1.7% (p < 0.0001) (Table 3). Consistent with a slight decrease in overall NVNM use among the general population, overall NVNM use among adults diagnosed with FMS declined from 57% in 2007 to 41% in 2012 (p < 0.0001). There were no apparent changes in the number of different combination NVNM supplements taken among those with FMS (mean (SE) for past 30 days = 0.99 (0.20) in 2007, 1.1 (0.38) in 2012, p = 0.89).

Table 1.

Demographic and lifestyle characteristics of 2007 and 2012 national US samples, stratified by NVNM use in the past 12 months, National Health Interview Survey.

Characteristic 2007 (N = 20,127) p 2012 (N = 30,672) p Overall pW
NVNM Use NVNM Use
Yes 95% CI Weighted population estimate∗ No Yes 95% CI Weighted population estimate∗∗ No
N (%) N (%) N (%) N (%)
Total 3582 (19.1) (18.4, 19.8) 16270972 16545 (80.9)   5490 (18.5) (17.8, 19.2) 16713004 25182 (72.4)   <0.0001
Age in years         <0.0001         <0.0001 <0.0001
 18–24 269 (8.2) (6.8, 9.6) 1332833 1884 (11.7)   391 (7.4) (6.3, 8.4) 1231081 2637 (11.1)    
 25–44 1169 (31.9) (30.1, 33.7) 5193487 6195 (36.3)   1775 (32.1) (30.4, 33.7) 5358304 8879 (34.1)    
 45–64 1414 (39.8) (37.9, 41.7) 6476821 5314 (32.3)   2162 (39.1) (37.5, 40.8) 6542615 8379 (33.1)    
 65–75 462 (12.6) (11.4, 13.7) 2044193 1599 (9.5)   741 (14.0) (12.8, 15.1) 2332396 2777 (11.4)    
 75+ 268 (7.5) (6.5, 8.5) 1223638 1553 (10.2)   421 (7.5) (6.6, 8.4) 1248608 2510 (10.3)    
 Mean (SE) 49.06 (0.35) (48.38, 49.75)   47.09 (0.27) <0.0001 49.58 (0.33) (48.93, 50.23)   48.24 (0.19) <0.0001 0.2794
Sex         0.0001         <0.0001 <0.0001
 Male 1535 (43.2) (41.3, 45.1) 7028291 7644 (47.8)   2341 (42.8) (41.1, 44.5) 7153927 11565 (47.3)    
 Female 2047 (56.8) (54.9, 58.7) 9242681 8901 (52.2)   3149 (57.2) (55.5, 58.9) 9559077 13617 (52.7)    
Race/ethnicity         <0.0001         <0.0001 <0.0001
 Non-Hispanic White 2716 (82.9) (81.7, 84.1) 13487880 9419 (69.6)   3979 (78.8) (77.5, 80.1) 13163299 14637 (67.4)   ∗ ∗ ∗
 Non-Hispanic Black 329 (6.9) (6.0, 7.8) 1121133 2812 (13.5)   513 (7.6) (6.7, 8.4) 1266927 4058 (13.3)    
 Hispanic 360 (6.7) (5.9, 7.5) 1091895 3358 (12.8)   622 (9.0) (8.1, 9.8) 1496127 4796 (14.4)   ∗ ∗ ∗
 Asian 99 (1.8) (1.4, 2.2) 297318 547 (2.3)   196 (2.6) (2.2, 3.0) 438850 975 (2.9)    
 Other Race/ethnicity 78 (1.7) (1.3, 2.0) 272746 409 (1.8)   180 (2.1) (1.7, 2.4) 347801 716 (2.1)    
Marital status         0.088         0.009 <0.0001
 Married/
Cohabitating		 1903 (52.0) (50.0, 53.9) 8453944 8507 (51.4)   2865 (52.1) (50.2, 53.9) 8703339 12354 (49.4)    
 Never married 710 (21.0) (19.2, 22.7) 3411156 3800 (23.1)   1206 (22.8) (21.2, 24.4) 3813588 6184 (24.7)    
 Divorced/sep/
widow		 969 (27.1) (25.5, 28.7) 4405872 4238 (25.6)   1419 (25.1) (23.7, 26.5) 4196077 6644 (25.9)    
Education         <0.0001         <0.0001 <0.0001
 <12th grade 272 (7.0) (6.1, 7.8) 1131795 3307 (16.5)   417 (6.4) (5.7, 7.2) 1076502 4420 (15.1)    
 HS/GED 808 (22.3) (20.7, 23.8) 3624376 4830 (29.6)   1043 (18.4) (17.2, 19.6) 3078409 6860 (26.8)   ∗ ∗ ∗
 Tech training/
some college		 1185 (33.4) (31.6, 35.2) 5436406 4527 (28.5)   1924 (35.3) (33.6, 36.9) 5896361 7548 (30.7)    
 ≥Bachelor's degree 1317 (37.4) (35.4, 39.3) 6078395 3881 (25.4)   2106 (39.9) (38.1, 41.6) 6661732 6354 (27.4)    
Employment         <0.0001         <0.0001 <0.0001
 Employed for pay 2189 (61.6) (59.8, 63.3) 10016152 9818 (59.5)   3301 (60.2) (58.5, 61.9) 10065089 13857 (55.4)    
 Employed but not for pay 162 (4.8) (4.0, 5.6) 784425 465 (3.1)   227 (4.3) (3.7, 5.0) 725979 703 (3.0)    
 Unemployed 1231 (33.6) (31.9, 35.3) 5470395 6262 (37.4)   1962 (35.4) (33.7, 37.1) 5921936 10622 (41.7)  
Income         <0.0001         <0.0001 <0.0001
 $1–$24,999 820 (23.4) (21.8, 25.1) 3809168 3710 (22.2)   1186 (21.0) (19.8, 22.3) 3512363 5670 (21.6)    
 $25,000–$44,999 576 (15.7) (14.3, 17.1) 2553714 2545 (15.9)   894 (16.3) (15.1, 17.5) 2727946 3675 (14.5)    
 $45,000–$74,999 478 (13.5) (12.2, 14.9) 2203952 1643 (10.6)   803 (14.9) (13.7, 16.0) 2490180 2727 (11.5)    
 $75,000 and over 341 (10.0) (8.8, 11.1) 1622926 858 (5.6)   583 (11.4) (10.4, 12.5) 1912903 1683 (7.5)    
 Do not know 129 (3.6) (3.0, 4.2) 578665 944 (5.3)   189 (3.2) (2.6, 3.8) 538020 1103 (4.3)    
 Missing 1238 (33.8) (31.9, 35.7) 5502547 6845 (40.4)   1835 (33.1) (31.6, 34.6) 5531592 10324 (40.5)    
Geographic location         <0.0001         <0.0001 <0.0001
 Northeast 541 (15.5) (13.8, 17.2) 2526830 2783 (17.4)   762 (13.9) (12.5, 15.3) 2324064 4325 (18.3)    
 Midwest 850 (25.6) (23.1, 28.1) 4161206 3642 (25.0)   1230 (26.2) (24.2, 28.1) 4374539 5173 (23.3)    
 South 1190 (32.2) (29.7, 34.7) 5232720 6337 (37.8)   1506 (29.2) (26.8, 31.7) 4886374 9683 (38.9)    
 West 1001 (26.7) (24.6, 28.9) 4350216 3783 (19.8)   1992 (30.7) (28.6, 32.7) 5128027 6001 (19.6)    
Place of birth                     <0.0001
 US born 3164 (91.0) (90.1, 91.9) 14807161 13116 (85.4) <0.0001 4791 (89.8) (88.9, 90.7) 15010846 20112 (83.5) <0.0001  
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Note. Column percentages shown; ∗adjusted for age, sex, and race/ethnicity based on 2000 Census data; ∗∗adjusted for age, sex, and race/ethnicity based on 2010 Census data; ∗∗∗significant changes between 2007 and 2012 indicated by nonoverlapping weighted population confidence intervals; Wp values obtained by comparing weighted estimates; note: significant changes between datasets with differing weighting schemes indicated by nonoverlapping weighted population confidence intervals as ∗∗∗.

Table 2.

Medical care/health characteristics of 2007 and 2012 national US samples, stratified by NVNM use in the past 12 months, National Health Interview Survey.

Characteristic 2007 (N = 20,127) p 2012 (N = 30,672) p Overall pW
NVNM use NVNM Use
Yes 95% CI Weighted population estimate∗  No Yes 95% CI Weighted population estimate∗∗  No
N (%) N (%) N (%) N (%)
Insurance status                      
 Uninsured 505 (13.4) (12.4, 14.5) 2185136 2999 (16.2) <0.0001 790 (13.0) (12.0, 13.9) 2168607 4705 (16.5) <0.0001 <0.0001
 Medicaid 155 (4.0) (3.3, 4.6) 645744 1510 (7.6) <0.0001 287 (4.4) (5.2, 10.5) 735478 2736 (9.3) <0.0001 <0.0001 ∗∗∗
 Medicare 786 (21.6) (20.0, 23.2) 3519561 3466 (21.7) 0.623 1277 (23.3) (21.8, 24.8) 3892141 5922 (23.9) 0.451 <0.0001
 Disability 63 (2.0) (1.3, 2.7) 321398 165 (0.96) <0.0001 111 (2.1) (1.7, 2.5) 346117 258 (1.1) <0.0001 <0.0001
 Private insurance 2537 (72.6) (70.9, 74.3) 11813273 10211 (65.3) <0.0001 3736 (70.2) (68.7, 71.8) 11739270 14238 (60.2) <0.0001 <0.0001
Out of pocket costs, annual$         <0.0001         <0.0001 <0.0001
 None 286 (7.8) (6.8, 8.8) 1272433 2155 (11.7)   483 (8.1) (7.3, 9.0) 1358939 3811 (13.9)    
 <$500 1249 (35.0) (33.3, 36.8) 5700791 6719 (39.6)   1780 (31.3) (29.7, 32.9) 5230362 9593 (37.3)   ∗ ∗ ∗
 $500–$1999 1236 (34.1) (32.4, 35.8) 5549126 4755 (29.5)   1809 (33.8) (32.4, 35.1) 5641914 6938 (28.3)    
 $2000–$2999 333 (9.3) (8.3, 10.3) 1512573 1151 (7.7)   554 (10.3) (9.3, 11.3) 1717635 2025 (8.7)    
 $3000–$4999 217 (6.2) (5.3, 7.1) 1008834 691 (4.5)   420 (8.3) (7.5, 9.1) 1391128 1237 (5.1)   ∗ ∗ ∗
 $5000+ 222 (6.4) (5.6, 7.2) 1039327 635 (4.1)   396 (7.3) (6.5, 8.1) 1219938 1180 (5.1)    
 Do not know 39 (1.2) (0.74, 1.6) 187888 439 (2.9)   48 (0.9) (0.63, 1.2) 153088 398 (1.6)    
Delayed care because they could not afford/worried about cost 621 (17.6) (16.2, 19.0) 2867318 1947 (12.0) <0.0001 964 (16.7) (15.6, 17.9) 2794500 3478 (13.2) <0.0001 <0.0001
Perceived health status         0.001         0.001 <0.0001
 Excellent/very good/good 3133 (87.7) (86.6, 88.9) 14272846 14162 (86.3)   4849 (89.7) (88.8, 90.6) 14987051 21383 (86.2)    
 Fair 363 (10.0) (9.0, 11.1) 1632026 1781 (10.1)   505 (8.1) (7.3, 8.9) 1347889 2942 (10.7)   ∗ ∗ ∗
 Poor 86 (2.3) (1.7, 2.8) 366100 602 (3.6)   136 (14.0) (1.8, 2.7) 378064 857 (86.0)    
Physical activityR                      
 None 915 (24.6) (22.9, 26.3) 4001744 7428 (42.2) <0.0001 1078 (18.9) (17.7, 20.1) 3158655 9136 (34.8) <0.0001 <0.0001 ∗∗∗
 Low/moderate 2298 (65.3) (63.3, 67.3) 10629710 7504 (47.5) <0.0001 3837 (70.8) (69.5, 72.2) 11841154 13429 (54.8) <0.0001 <0.0001 ∗∗∗
 High 1613 (46.5) (44.5, 48.5) 7571196 5164 (33.8) <0.0001 2924 (54.7) (53.0, 56.3) 9136857 9817 (40.6) <0.0001 <0.0001 ∗∗∗
 Mean (SE) (weekly) (min) 283.09 (10.23) (262.96, 303.22)   198.45 (6.00) <0.0001 325.00 (9.77) (305.77, 344.24)   239.65 (4.63) <0.0001 0.003 ∗∗∗
Body mass index (BMI)         0.016         0.031 <0.0001
 <24.9 1384 (39.0) (37.3, 40.8) 6348273 6243 (38.7)   2057 (38.6) (37.0, 40.1) 6448785 9039 (36.3)    
 25–29.9 1246 (34.5) (32.7, 36.2) 5605830 5875 (35.4)   1916 (34.4) (32.9, 36.0) 5757553 8717 (34.8)    
 30–35 614 (17.2) (15.8, 18.6) 2793014 2731 (16.1)   903 (16.3) (15.1, 17.4) 2718245 4425 (17.3)    
 35+ 338 (9.4) (8.3, 10.5) 1523855 1696 (9.9)   614 (10.7) (9.8, 11.6) 1788421 3001 (11.6)    
 Mean (SE) 27.37 (0.11) (27.15, 27.60)   27.35 (0.56) 0.887 27.54 (0.09) (27.36, 27.72)   27.77 (0.05) 0.024 0.2305
Tobacco use         <0.0001         <0.0001 <0.0001
 Never 1894 (51.2) (49.2, 53.2) 8330263 9977 (57.6)   3114 (56.3) (54.8, 57.9) 9413789 14939 (58.3)   ∗ ∗ ∗
 Former 1067 (30.3) (28.7, 31.9) 4930987 3292 (21.2)   1539 (28.6) (27.3, 30.0) 4788193 5281 (22.0)    
 Current 621 (18.5) (16.7, 20.3) 3009722 3276 (21.2)   837 (15.0) (13.8, 16.2) 2511022 4962 (19.6)   ∗ ∗ ∗
Alcohol use         <0.0001         <0.0001 <0.0001
 None 1006 (26.7) (25.1, 28.4) 4349888 6958 (39.0)   1454 (24.0) (22.5, 25.5) 4012831 9897 (36.6)    
 Light 1740 (47.9) (46.1, 49.7) 7794610 6609 (41.0)   2662 (49.6) (48.0, 51.3) 8292892 10426 (42.7)    
 Moderate to heavy 836 (25.4) (23.6, 27.1) 4126474 2978 (19.9)   1374 (26.4) (24.9, 27.9) 15263475 4859 (20.7)    
Substance abuse 30 (0.81) (0.52, 1.1) 132414 96 (0.62) 0.157 62 (1.3) (0.89, 1.6) 210988 164 (0.66) 0.0003 <0.0001
Comorbidity indexa                      
 None 918 (25.6) (23.9, 27.3) 4164042 6532 (38.4) <0.0001 1035 (18.7) (17.5, 19.8) 3117059 7588 (29.8) <0.0001 0.0001 ∗∗∗
 One 912 (26.0) (24.4, 27.5) 4225414 3846 (23.7)   1218 (22.3) (20.9, 23.6) 3721577 5717 (22.9)   ∗ ∗ ∗
 Two 662 (18.4) (16.9, 19.8) 2987313 2488 (15.5)   1083 (19.6) (18.4, 20.8) 3272605 4243 (17.2)    
 ≥Three 1090 (30.1) (28.4, 31.7) 4894203 3679 (22.4)   2154 (39.5) (37.8, 41.2) 6601763 7634 (30.2)   ∗ ∗ ∗
 Mean (SE) 1.83 (0.03) (1.77, 1.90)   1.45 (0.02) <0.0001 2.23 (0.03) (2.17, 2.29)   1.84 (0.02) <0.0001 <0.0001 ∗∗∗
Chronic health conditions                      
 Diabetes 314 (8.2) (7.2, 9.1) 1331587 1633 (9.4) 0.021 596 (10.2) (9.3, 11.2) 1709992 2965 (11.2) 0.106 <0.0001 ∗∗∗
 Kidney disease 57 (1.6) (1.2, 2.1) 263373 289 (1.6) 0.713 91 (1.5) (1.2, 1.8) 250872 506 (1.9) 0.047 <0.0001
 GI diseaseaa 590 (16.9) (15.5, 18.3) 2752405 1696 (10.8) <0.0001 2186 (40.4) (38.9, 41.9) 6744109 7468 (29.9) <0.0001 <0.0001 ∗∗∗
 Chronic resp. conditionsb 615 (16.9) (15.6, 18.2) 2745606 2144 (13.4) <0.0001 985 (18.0) (16.8, 19.3) 3015703 3762 (15.1) <0.0001 <0.0001
 CVDc 257 (7.0) (6.1, 7.9) 1142025 1078 (6.8) 0.607 393 (7.1) (6.3, 7.9) 1186819 1829 (7.3) 0.621 <0.0001
 Hypertension 1136 (31.1) (29.4, 32.9) 5064154 4764 (28.7) 0.017 1856 (33.4) (31.8, 35.0) 5582424 8168 (32.2) 0.165 <0.0001
 Dyslipidemia 1159 (32.2) (30.5, 34.0) 5246236 3977 (24.6) <0.0001 1881 (33.9) (32.2, 35.6) 5659527 6628 (26.8) <0.0001 <0.0001
 Liver disease 54 (1.5) (1.1, 1.9) 244387 198 (1.2) 0.138 91 (1.6) (1.2, 2.0) 271510 348 (1.3) 0.146 <0.0001
 Chronic pain conditionsd 1836 (51.6) (49.8, 53.3) 8390744 5940 (36.9) <0.0001 3018 (55.2) (53.9, 56.9) 9263106 9943 (39.9) <0.0001 <0.0001 ∗∗∗
 Mental health conditionse 832 (23.8) (22.1, 25.6) 3874783 2623 (16.0) <0.0001 1674 (30.4) (28.9, 31.9) 5084683 5854 (22.9) <0.0001 <0.0001
 Insomnia 948 (26.9) (25.2, 28.7) 4383811 2885 (17.8) <0.0001 1488 (26.8) (25.4, 28.2) 4472612 4728 (18.8) <0.0001 <0.0001
 History of cancer 355 (10.1) (9.0, 11.2) 1638188 1101 (7.4) <0.0001 569 (10.7) (9.7, 11.7) 1792043 2039 (8.6) <0.0001 <0.0001
Use of other complementary health approaches 3539 (98.9) (98.6, 99.3) 16094998 14150 (86.2) <0.0001 5357 (97.9) (97.5, 98.4) 16369136 17689 (72.1) <0.0001 <0.0001 ∗∗∗
 Other natural productsf 3331 (93.4) (92.4, 94.4) 15192940 10243 (64.4) <0.0001 5215 (95.5) (94.9, 96.2) 15965914 15806 (64.5) <0.0001 <0.0001 ∗∗∗
 Mind-bodyg 1870 (53.2) (51.5, 55.0) 8659604 3621 (23.6) <0.0001 2094 (39.7) (38.0, 41.4) 6633294 3290 (13.9) <0.0001 <0.0001 ∗∗∗
 Manipulative/
bodyworkh 		2034 (58.4) (56.5, 60.3) 9496114 4144 (27.1) <0.0001 2783 (51.7) (50.0, 53.4) 8634942 6075 (25.3) <0.0001 <0.0001 ∗∗∗
 Energy healing/Reiki 218 (6.1) (5.2, 7.0) 997157 137 (0.89) <0.0001 240 (4.5) (3.8, 5.1) 747014 123 (0.47) <0.0001 <0.0001 ∗∗∗
 spiritual practicesi 2334 (64.6) (62.7, 66.5) 10512222 9637 (56.5) <0.0001 643 (12.5) (11.4, 13.5) 2081886 718 (2.9) <0.0001 <0.0001 ∗∗∗
 Alternative systemsk 858 (23.8) (22.1, 25.5) 3867268 1136 (6.9) <0.0001 1037 (19.0) (17.8, 20.2) 3180077 1231 (4.9) <0.0001 <0.0001 ∗∗∗
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Note. Column percentages shown; ∗adjusted for age, sex, and race/ethnicity based on 2000 Census data; ∗∗adjusted for age, sex, and race/ethnicity based on 2010 Census data; ∗∗∗significant changes between 2007 and 2012 indicated by nonoverlapping weighted population confidence intervals; Wp values obtained by comparing weighted estimates; note: significant changes between datasets with differing weighting schemes indicated by nonoverlapping weighted population confidence intervals as ∗∗∗; $family costs aside from deductibles, premiums, copays; Rdefined as ≥10 min. increments; aincluding diabetes, kidney disease, gastrointestinal disorder (including ulcer and/or abdominal pain, digestive allergy, and heartburn), respiratory conditions (asthma, emphysema, and/or chronic bronchitis), dyslipidemia, liver condition, rheumatoid arthritis, CVD, hypertension, nonspecific arthritis, gout, migraines, mental health condition; aaincluding bowel conditions and ulcers (2007); past 12 months: abdominal pain, digestive allergy, heartburn, and ever having ulcer (2012); basthma, emphysema, and/or chronic bronchitis; cmyocardial infarction, heart disease, angina pectoris; dmigraines (past 3 months), nonspecific arthritis, gout, nonspecific joint pain for 3+ months, rheumatoid arthritis; edepression, bipolar disorder, phobias, often anxious (past year); fsupplements other than NVNMs, including vitamins/minerals, probiotics (past 30 days), fish oil (past 30 days), chelation therapies; gTai Chi/Qi Gong, yoga, guided imagery, progressive relaxation, deep breathing exercises, meditation (singular term “meditation” used in 2007; expanded in 2012 to include mantra and mindfulness meditation), mindfulness-based stress reduction and cognitive therapy (2012), stress-management class (2007), biofeedback, hypnosis; hpractitioner-based massage (ever), chiropractic/osteopathic manipulation, Sobador visit; iprayed for one's own health (2007) or centering prayer/contemplative meditation (2012); and/or visit with Espiritista (2007 only), Curandero, Shaman, and/or native American healer; kacupuncture, Ayurveda, homeopathy, and naturopathy.

Table 3.

NVNM use in two nationally representative samples of adults with diagnosed fibromyalgia, National Health Interview Survey (NHIS 2007 N = 221 (1.3%∗C1) versus NHIS 2012 N = 524 (1.7%∗∗C2)).

Characteristic 2007 2012 Overall pW
N (%) 95% CI Weighted population estimate∗ N (%) 95% CI Weighted population estimate∗∗
NVNM use ever             <0.0001 ∗∗∗
 Yes 114 (57.1) (49.3, 64.9) 624881 204 (40.6) (35.3, 45.8) 633029  
 No 107 (42.9) (35.1, 50.7) 469162 320 (59.4) (54.2, 64.7) 927192  
NVNM use in past 12 months             <0.0001
 Yes 82 (41.7) (33.3, 50.2) 456477 157 (31.2) (26.1, 36.4) 487362  
 No 139 (58.3) (49.8, 66.7) 637566 367 (68.8) (63.6, 73.9) 1072859  
NVNM use in past 30 days             <0.0001
 Yes 62 (32.7) (24.6, 40.9) 358265 126 (24.5) (19.9, 29.1) 382285  
 No 159 (67.3) (59.1, 75.4) 735778 398 (75.5) (70.9, 80.1) 1177936  
Number of different NVNM supps in past 30 daystt              
 (Mean (SE)) 0.99 (0.20) (0.60, 1.4)   1.07 (0.38) (0.32, 1.8)   0.894
Physician disclosure of NVNMd             <0.0001
 Yes 50 (64.6) (53.1, 76.1) 294988 51 (71.4) (59.0, 83.9) 140681  
 No 32 (35.4) (23.9, 46.9) 161489 15 (28.6) (16.1, 41.0) 56221  
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Note. Total sample with fibromyalgia is percentage denominator; ∗adjusted for age, sex, and race/ethnicity based on 2000 Census data; ∗∗adjusted for age, sex, and race/ethnicity based on 2010 Census data; ∗ ∗∗significant changes between 2007 and 2012 indicated by nonoverlapping weighted population confidence intervals; Wp values obtained by comparing weighted estimates; note: significant changes between datasets with differing weighting schemes indicated by nonoverlapping weighted population confidence intervals as ∗∗∗; ttamong NVNM users with fibromyalgia; including combination NVNM supplement; dwithin past 30 days (N = 66; 2007); only disclosure of top therapy assessed within past 12 months (2012); C1(95% CI: 1.1, 1.5); C2(95% CI: 1.6, 1.9).

Between 2007 and 2012, rates of NVNM consumption (past 12 months; Table 1) declined among non-Hispanic White adults (83% to 79%) but increased among those identified as Hispanic (7% to 9%; p's < 0.0001). Overall, the likelihood of NVNM use significantly increased by number of health conditions in both years (Table 2; p's for trend ≤ 0.0001, not shown). In addition, NVNM users (past 12 months) spending under $500 in out-of-pocket medical costs decreased (2007 and 2012: 35.0% and 31.3%, resp.) while NVNM users spending over $3,000 increased (6.2% and 8.3%). This was also noted by an increase in likelihood of NVNM use by out-of-pocket costs for both years (p's for trend = 0.0001; not shown). Lastly, consumption of other natural products (i.e., vitamins/minerals) increased (93% to 96%) among all herbal users between time points.

3.1. Relation of FMS to Herbal Use

Nearly 60% of those with FMS reported previous or current NVNM use; 42% indicated using NVNMs in the past 12 months, and 33% in the past 30 days (Table 3). Approximately 3% of all NVNM users had FMS; this rate did not differ between years (Table 4). In 2007, participants with FMS were 3.7 times as likely as those without FMS to use NVNMs for any length of time (OR = 3.7, 95% confidence interval (CI): 2.7, 5.0). After adjustment for demographic, lifestyle, and medical/health factors, those with FMS were 2.7 times as likely to report ever using NVNMs than those without FMS (adjusted odds ratio (AOR) = 2.7, (CI: 1.9, 3.8)). FMS showed a similarly strong positive association to recent NVNM use (12-month and 30-day AORs = 2.3 (CI: 1.5, 3.4) and 2.3 (CI: 1.6, 3.5), resp.). Likewise, FMS was significantly and positively associated with all NVNM use outcomes in 2012, although the magnitude of the associations was lower (2012 AORs: herbal use (ever) = 1.6 (CI: 1.3, 2.0); 12 months = 1.6 (CI: 1.2, 2.0); 30 days = 1.5 (CI: 1.2, 2.0)).

Table 4.

Association of NVNM use to self-reported fibromyalgia diagnosis in two nationally representative samples of adults, National Health Interview Survey (NHIS 2007, N = 20,127; and 2012, N = 30,672).

  N (%) 95% CI Unadjusted odds ratio (95% CI) p Odds ratio adjusted for demographics and related factors∗ (95% CI) p Odds ratio adjusted for demographics, lifestyle, and related factors¥ (95% CI) p Odds ratio adjusted for demographics, lifestyle, and related factors + comorbidityt (95% CI) p
NHIS 2007                    
NVNM use in the last 30 days                    
 Fibromyalgia                    
  Yes 62 (3.0) (2.1, 3.9) 3.07 (2.12, 4.45) <0.0001 2.36 (1.59, 3.51) <0.0001 2.54 (1.69, 3.83) <0.0001 2.34 (1.55, 3.52) <0.0001
  No 2561 (97.0) (96.1, 97.9) 1.00 (reference)   1.00 (reference)   1.00 (reference)   1.00 (reference)  
NVNM use in the last 12 months                    
 Fibromyalgia                    
  Yes 82 (2.8) (2.0, 3.6) 3.09 (2.19, 4.37) <0.0001 2.34 (1.58, 3.47) <0.0001 2.48 (1.67, 3.71) <0.0001 2.25 (1.51, 3.35) <0.0001
  No 3500 (97.2) (96.4, 98.0) 1.00 (reference)   1.00 (reference)   1.00 (reference)   1.00 (reference)  
NVNM use ever                    
 Fibromyalgia                    
  Yes 114 (2.7) (2.1, 3.3) 3.66 (2.66, 5.03) <0.0001 2.85 (2.02, 4.02) <0.0001 3.01 (2.13, 4.25) <0.0001 2.66 (1.85, 3.82) <0.0001
  No 4943 (97.3) (96.7, 97.9) 1.00 (reference)   1.00 (reference)   1.00 (reference)   1.00 (reference)  
NHIS 2012                    
NVNM use in the last 30 days                    
 Fibromyalgia                    
  Yes 126 (3.0) (2.4, 3.6) 2.04 (1.59, 2.61) <0.0001 1.65 (1.27, 2.14) 0.0002 1.72 (1.33, 2.24) <0.0001 1.51 (1.15, 2.00) 0.003
  No 3994 (97.0) (96.4, 97.6) 1.00 (reference)   1.00 (reference)   1.00 (reference)   1.00 (reference)  
NVNM use in the last 12 months                    
 Fibromyalgia                    
  Yes 157 (2.9) (2.4, 3.4) 2.03 (1.62, 2.56) <0.0001 1.72 (1.34, 2.20) <0.0001 1.82 (1.42, 2.33) <0.0001 1.57 (1.21, 2.04) 0.0007
  No 5333 (97.1) (96.6, 97.6) 1.00 (reference)   1.00 (reference)   1.00 (reference)   1.00 (reference)  
NVNM use ever                    
 Fibromyalgia                    
  Yes 204 (2.9) (2.4, 3.3) 2.17 (1.75, 2.69) <0.0001 1.84 (1.47, 2.32) <0.0001 1.92 (1.52, 2.42) <0.0001 1.59 (1.25, 2.03) 0.0002
  No 7034 (97.1) (96.7, 97.6) 1.00 (reference)   1.00 (reference)   1.00 (reference)   1.00 (reference)  
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Boldface indicates statistical significance at p ≤ 0.05; ∗adjusted for age, sex, race, education, employment, income, geographic location of birth, insurance status (Medicaid, disability, and private), out-of-pocket medical expenses, delayed access to care due to cost, and region (2007); additionally, marital status (2012); ¥additionally adjusted for smoking status, alcohol use, exercise, and BMI (2007); and substance abuse (2012); thealth conditions include diabetes, kidney disease, gastrointestinal disorder (including ulcer), respiratory conditions, dyslipidemia, liver condition, rheumatoid arthritis, CVD, hypertension, arthritis, gout, migraines, and mental health condition; and self-reported health status.

The magnitude of the association of NVNM use to FMS was significantly greater in those with 0-1 comorbid health conditions than in those with 2 or more health conditions (age-adjusted ORs, resp., = 4.7 (CI: 2.2, 9.8) versus 2.8 (CI: 2.0, 3.9; p for interaction = 0.008) in 2007; not shown). However, we found no evidence of a modifying effect of multiple comorbidities in 2012 or for gender in either year.

To our knowledge, this is the first large, population-based study to examine the relation of NVNM use to FMS; it is also among the first rigorous studies to investigate the relation of NVNM use to any chronic pain condition in a large sample [25, 29, 30, 36]. Relative to adults without FMS, those with FMS were significantly more likely to report using NVNMs at any time point (within the past 30 days or 12 months or ever) in both 2007 and 2012 survey years; the positive association of FMS to NVNM use remained highly significant even after controlling for a broad array of demographic, lifestyle, and health-related factors.

In our study, the majority of those with FMS indicated using NVNMs at some time point; one-third had used NVNMs in the past 30 days. Previous studies assessing herbal use in FMS reported widely varying rates among FMS patients, ranging from 43% (FMS = 434) to 78% (FMS = 90) [36, 37]. Reported rates among other chronic pain populations have been considerably lower, ranging from 6.8% in a sample of primary care patients using opioids [29] to 15% in a primary care patient population with chronic pain [30]. However, percentages given in prior studies were unweighted and may in part reflect differences in study populations and outcome definitions, rendering comparison with our findings challenging.

Prevalence of diagnosed FMS increased between 2007 and 2012 (1.3% to 1.7%). Despite lower rates than those appearing globally and in some US studies [1–3], this apparent rise in diagnosed FMS may be due in part to increased recognition of FMS by physicians following publication of the 2010 Preliminary ACR updated criteria for fibromyalgia.

In contrast, we found reported NVNM use among adults with FMS declined significantly from 2007 to 2012, paralleling the modest but significant reduction in overall NVNM use observed between these periods. However, the mean number of different combination NVNM supplements used by those with FMS did not differ between time points and averaged lower than that reported in a case-control study of North American women (N = 434 with FMS) [36]. In addition, both the observed decline in NVNM use among those with FMS and the positive but more modest association between NVNM use and FMS in 2012 compared to 2007 may also reflect increased availability of FDA-approved FMS medications following the 2007 NHIS survey administration. It also remains possible that both the increase in FMS diagnoses and decrease in odds of NVNM use for FMS over time are also in part the result of promotion for FMS drugs by pharmaceutical companies [38] and increased off-label prescription of other drugs for FMS, potentially including opioids [39, 40].

Strengths and Limitations. This investigation was the first study to assess the relation between NVNM use and FMS in a large US population. Strengths of our study include large, nationally representative samples, use of data from two time periods, and the availability of comprehensive information on NVNM use, as well as a broad array of demographic, lifestyle, health-related, and other potentially confounding factors. However, there were some limitations. Perhaps most important, the cross-sectional study design precluded determination of causal relationships. Ascertainment of NVNM use and medical history, including diagnosis of FMS, was reliant on self-report, raising the possibility of recall bias; however, potential underascertainment would likely bias our results toward the null, indicating more conservative estimates.

Although the NVNM use outcome mainly comprised of herbal dietary supplements and was assessed separately from many other nonherbal supplements in both NHIS data collection periods, the nonherbal products coenzyme Q-10, SAM-e, fish oil, and prebiotics/probiotics were included in our main NVNM outcome. Thus, our consideration of a broader NVNM outcome may be more appropriate than a specific herbal supplement use outcome, since reports of individual ingredients were not consistently available between years. There was inadequate capture of certain herbal products within the NVNM outcome. No data were available on consumption of herbal and green teas used for health purposes or on products not labelled (per NHIS requirements for inclusion) “dietary supplement,” including home grown herbs, traditionally prepared herbal products, and bulk herbs/powders sometimes recommended (i.e., by nutritionists, natural foods purveyors) over widely available supplements due to quality and processing concerns. We did not have information on FMS severity or duration, and although the 2012 questionnaire differed from 2007, there were no differences with respect to assessment of fibromyalgia. Based on cognitive testing and input from expert panels, the definitions of certain modalities were modified in 2012 to reduce false-positive responses [34] which may have affected findings. However, these changes were relatively minor and were unlikely to affect our estimates, as these potential false-positives did not vary by disease status.

Given the high prevalence rates of those with FMS using NVNMs, and the strong, positive relationship of FMS to NVNM use which persisted in 2012 despite the availability of approved treatments, additional prospective research is warranted to confirm these findings, to further investigate the prevalence, patterns, and determinants of specific NVNM use in FMS, and to explore the safety and potential efficacy of NVNM products for this still poorly managed condition.

4. Conclusions

In the first large cross-sectional study of two nationally representative samples of US adults, reported diagnosis of FMS was strongly and positively associated with NVNM use in both 2007 and 2012 after adjustment for demographic, lifestyle, and health factors. Rigorous prospective studies are needed to confirm these findings and to further explore the patterns, determinants, and potential efficacy of NVNM use in those with FMS.

Acknowledgments

This research was partially funded by NIH NIGMS Grant T32 GM081741. The authors would like to acknowledge Dr. Dina Jones for feedback on earlier iterations of this manuscript.

Conflicts of Interest

The authors declare that there are no conflicts of interest regarding the publication of this paper.

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