Prevalence of fibromyalgia in a low socioeconomic status population

Fibromyalgia (FM) is a frequent rheumatologic disorder worldwide [1–5]. It responds by up of 7% of all primary care consultations, imposing substantial costs to the system [6].

The prevalence of FM ranges from 0.66% to 10.5% [7], with most studies pointing into a prevalence around 2% in the adult population. Prevalence is higher in women (around 3.4%) [8] and in middle-age (5%) [1, 4]. Most studies were conducted in developed countries; studies in emerging countries or in under-assisted populations are scarce.

Although the impact of FM in productivity [9, 10], disability [11, 12] and quality of life [13, 14] of sufferers is well documented in the Brazilian population [14, 15], only one study assessed its prevalence. This study was conducted in a single city and reported a prevalence of 2.5% [4]. Because Brazil is a continental country, other studies are necessary. A better understanding of the epidemiology of FM is an important step for planning the health care system to properly assist this population, assuring improvements in the quality of care and rational cost-implementation.

The aim of this study was to estimate the prevalence of FM and its symptoms in a middle-aged adult population (35–60 years) registered in the primary health care system of a city in Brazil (Embu City, São Paulo State). The population assisted by this system is of low income. We hypothesized that the prevalence of FM is increased in this low income population, may be because they are exposed to several pain risk factors.

Using the Bayesian approach, the prevalence of widespread chronic pain was 24%, with a 95% credibility interval (CI) [21%; 27%]. Among individuals with WP the prevalence of FM was 18% (95% CI = 11% – 25%). For this calculation, the Beta distribution parameters were 0.1 to 0.4 (a priori) and 19.1 to 87.4 (a posteriori). The beta distribution assumes continuous.. probability distributions defined on the interval [0, 1]. The a priori parameters was defined based on known proportions of WP and FM and the a posteriori parameters was calculated based on the number of FM and WP subjects. Accordingly, the prevalence of FM was defined as a function of WP probability and proportion of individuals with WP who also endorsed FM. It was 4.4% (95% CI = 2.7%–6.3%).

In our study, the prevalence of FM in a middle-aged adult population of a low socioeconomic population was 4.4% and all cases were women. The prevalence was higher than what has been reported elsewhere. In most studies the prevalence ranges from 2% to 4% [8, 13], but important discrepancies exist [26–28].

Although the prevalence of FM in our casuistic was very similar to what had been found in other studies, we found a higher prevalence of widespread chronic pain (24%, 95% CI = 21–27%). Croft et al. [30] reported prevalence of 11.2%, later confirmed by Storozhenko et al. [31]. This discrepancy may be due to the fact we enrolled a high-risk population for chronic pain. Both middle age [32] and female gender are known risk factors for chronic pain [33–35], determined by biological [36] and social factors [32, 37, 38]. Increased weight is also a risk factor for pain, especially in women [32]. Furthermore, low-income individuals are more likely to work in manual functions, which may also facilitate injuries and pain. Wijnhoven et al. [39] related that non-paid work (e.g. household work) is per se a risk factor for pain [33, 36]. Other studies report an inverse association between education and chronic pain [33, 36]. Accordingly, our sample should be considered of high risk for widespread chronic pain (as shown in Table 1).

The last assumption is supported by the fact that several studies showed an inverse relation between presence of musculoskeletal symptoms and socioeconomic status [40]. However, of interest is that these factors did not determine a higher prevalence of FM in our study. Another factor explaining the high prevalence of widespread chronic pain was the screening interview being conducted over the telephone, forcing reliance on self-report.

We also assessed the main symptoms of FM in the population. Although not considered in the ACR criteria, they define the essence of the syndrome [41, 42] and add to its disability [13] and negative impact on quality of life [14]. We used the FIQ to assess the impact of FM symptoms in individuals not fulfilling de ACR criteria. Some symptoms were common in the other groups as well. As compared to individuals with NP, there were significant differences for all FIQ items, except for "physical function" and "work missed. However, the multiple variances analysis showed that, for the majority of FIQ items, NP and RP were similar and statistically different than the groups WP and FM (which, in turn, where not different).

Accordingly, we notice that although WP and FM have different criteria and definitions, the intensity of the symptoms is similar. It may be that individuals with WP, due to the physical and emotional aspects of pain [43], decrease physical and social activities and become more sedentary [44]. Eventually this may predispose to anxiety, depression and tiredness which, according to Croft et al. [30], may then predispose to FM.

Alternative, it may be that many individuals with WP have unclassified FM. As with FM, individuals with WP have chronic pain in different regions of the body. However, they have less than 11 tender points. It has been suggested that experienced rheumatologists often diagnose WP as FM, even in the absence of tender points [45]. Indeed, recent discussions question whether the ACR Criteria adequately capture the essence of FM. Symptoms perhaps could be included in the diagnosis again [41, 42] as had been used by Smythe & Modollfsky [46].

Being so prevalent in the population assisted by the primary care public system, WP and FM are certainly of economic importance, suggesting that the health professionals should be careful in assessing these disorders. Future studies should be developed to assess the adequacy of the ACR criteria in the primary care.

Our study has limitations. Our sample was formed among people registered in the Public Health Care System of Embu, and the data may not be extrapolated. Several biases may exist in the screening interview including lack of telephone or inability to be contacted. The screening survey was established based on methodological and economical feasibility. Some of these biases were at least partially addressed by the Bayesian Analyses. Nonetheless, we suggest that future studies addressing the low-income population account for inherent problems of dealing with this stratum, including education limitations (difficulties in understanding certain questions or demands, need for cross-cultural adaptation of the instruments, etc). Finally, it may be that the personal assessments should be done in the household of the participants, to mitigate economic barriers (e.g. lack of money for transportation, need to work on weekends). Nonetheless, our findings should not be discrepant to what happens in similar cities.

Our findings point for the importance of FM to the public health system, and highlight the need of preparing public policies to prepare the system to the demand posed by FM, and also to provide adequate care aiming to improve the daily life activities and the quality of life, as recently suggested by Blyth [47]. These policies are especially important for people of low income, who depend on the government health care system. Because classification of FM was done using the ACR Criteria proposed in 1990, future studies are necessary to discuss the better criteria to account for the syndrome complexity.