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Abstract

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. SUBJECTS AND METHODS
  5. RESULTS
  6. DISCUSSION
  7. AUTHOR CONTRIBUTIONS
  8. REFERENCES

Objective

To determine the population prevalence of joint hypermobility (JH) and to test the hypothesis that JH would be associated with reporting musculoskeletal pain.

Methods

We conducted a cross-sectional population survey in Aberdeen and Cheshire. A total of 45,949 questionnaires were mailed that assessed JH and the presence, distribution, duration, and severity of musculoskeletal pain. Based on their pain reports, participants were classified as having chronic widespread pain (CWP), some pain, or no pain. Multinominal logistic regression tested the relationship between JH and pain status. Associations were adjusted for age, sex, and other putative confounders. Participants with no pain were the referent category.

Results

A total of 12,853 participants (28.0%) returned a questionnaire with complete data; 2,354 participants (18.3%) were classified as hypermobile. A total of 2,094 participants (16.3%) had CWP, 5,801 participants (45.1%) had some pain, and 4,958 participants (38.6%) reported no pain. JH participants were significantly more likely to report CWP than non-JH participants (18.5% versus 15.8%; P < 0.001). After adjusting for age and sex, hypermobile participants were 40% more likely to report the most severe CWP (relative risk ratio [RRR] 1.4, 95% confidence interval [95% CI] 1.1–1.7; P < 0.00). After further adjustments for employment status, smoking, alcohol, and physical activity, JH remained significantly associated with the most severe CWP (RRR 1.6, 95% CI 1.3–2.1; P < 0.000) and some pain (RRR 1.3, 95% CI 1.02–1.6; P = 0.03).

Conclusion

JH was associated with severe pain; however, this relationship was not specific to CWP. The relationship was relatively modest and may be explained by unmeasured confounding factors such as psychological distress.


INTRODUCTION

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. SUBJECTS AND METHODS
  5. RESULTS
  6. DISCUSSION
  7. AUTHOR CONTRIBUTIONS
  8. REFERENCES

Joint hypermobility (JH) is an excessive range of movement in one or more joints and is a very common finding in the general population ([1]) and in the rheumatology clinic ([2]). In many cases, JH is often considered asymptomatic; however, among rheumatology patients, it is strongly associated with reporting musculoskeletal pain ([1-3]). JH is associated with arthralgia (joint pain) ([4-7]), back pain ([5, 8]), and chronic widespread pain (CWP) ([9]), the primary feature of fibromyalgia. Putative mechanisms of association include minor injury in the soft tissues in and around the joint and recurrent joint dislocation or subluxation (partial dislocation) in patients with JH ([10]).

Epidemiologic data indicate that JH is reported more frequently by younger people and by women, with prevalence estimates ranging between 2% and 35% for men and between 6% and 57% for women ([1]). Two recent studies of healthy volunteers reported prevalence rates of 17.6% ([11]) and 21.1% ([12]) using the Beighton criteria for JH ([13]), which assess joint mobility across 8 joints and the spine (a score of ≥4 of 9 indicates JH). Although the Beighton score has excellent validity and high interobserver reproducibility ([14, 15]), the necessity for a clinical examination precludes its use in large-scale population-based surveys. Consequently, the prevalence of JH and its relationship with pain and associated risk factors in an unselected population remain unclear. However, a simple 5-item self-report questionnaire to detect JH that does not require a physical examination has been developed and validated for use in questionnaire surveys ([16]).

It is believed that current published population prevalence rates of JH are underestimates ([1]) and as such, the extent of the problem may not be fully known. Moreover, living with musculoskeletal pain is known to have a negative impact on quality of life, morbidity, and mortality ([17]); therefore, identifying associated factors (such as JH, lifestyle factors, socioeconomic status, employment status, and levels of physical activity) may be useful in primary and secondary pain prevention.

The aim of this study was to determine the population prevalence of JH and to investigate the association between JH and musculoskeletal pain. The specific objectives were: 1) to determine the population prevalence of JH in a large unselected sample of adults; 2) to determine whether JH would be associated with musculoskeletal pain and that the strength of the association would be strongest among participants reporting the most severe pain; 3) to determine whether putative risk factors (such as employment status, current health, smoking and alcohol consumption, and levels of physical activity) known to be associated with musculoskeletal pain explain in part the relationship with JH; and 4) to determine the proportion of variance of pain data explained by JH.

Box 1. Significance & Innovations

  • This is the first report of the prevalence of joint hypermobility in a large unselected population-based sample.
  • In our sample, 18% were classified as being hypermobile.
  • Compared to those who were not hypermobile, having joint hypermobility was associated with a 40% increased risk of reporting the most severe pain.

SUBJECTS AND METHODS

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. SUBJECTS AND METHODS
  5. RESULTS
  6. DISCUSSION
  7. AUTHOR CONTRIBUTIONS
  8. REFERENCES

Study design.

The Managing Unexplained Symptoms (CWP) in Primary Care: Involving Traditional and Accessible New Approaches (MUSICIAN) study was a 2 × 2 factorial randomized controlled trial that aimed to determine the clinical effectiveness of cognitive–behavioral therapy and/or exercise for the management of CWP ([18]). Since identification of eligible patients was difficult from primary care records, a large-scale population screening survey was undertaken in Aberdeen and North Cheshire, UK. Persons reporting CWP for which they had consulted their general practitioner in the past 12 months were eligible to be invited to take part in the trial. To identify those persons, a random sample of individuals ages ≥25 years from the lists of 8 general practices (4 in Aberdeen and 4 in Cheshire) were mailed a questionnaire. General practice lists provide convenient population sampling frames, since >95% of persons residing in the UK are registered with a general practitioner. Nonresponders were sent a further questionnaire 2 weeks after the initial mailing. Data from this large-scale population survey are shown here.

Demographics.

Participants were asked to report their date of birth, sex, employment status, and current health status, and whether they regularly smoked and regularly drank alcohol.

JH.

Participants completed the 5-item JH scale developed by Hakim and Grahame ([16]). Example scale items are: “Can you now (or could you ever) place your hands flat on the floor without bending your knees?” (yes = 1/no = 0) and “Can you now (or could you ever) bend your thumb to touch your forearm?” (yes = 1/no = 0). The scale was developed in adult women between ages 16 and 80 years presenting to rheumatology outpatient clinics (n = 212), and hospital clinic staff were recruited as healthy controls (n = 59). Responses to the scale items are summed and participants scoring ≥2 of 5 are classified as hypermobile. Hakim and Grahame reported that a positive answer to ≥2 of the 5 items gave the highest combined sensitivity (84%) and specificity (89%) and correctly identified 84% of cases ([16]). As part of the current study, a sensitivity analysis was conducted to explore the influence of including men and older adults (ages >80 years) on JH prevalence and any associations with musculoskeletal pain.

Presence, distribution, and duration of musculoskeletal pain.

The questionnaire included a detailed assessment of the presence of musculoskeletal pain. All participants were asked, “During the past month have you experienced any pain which has lasted at least one day or longer?” Respondents answering positively were invited to shade the location(s) of their pain on a 4-view body manikin. Participants were then asked whether they had been aware of their pain for 3 months or longer (yes/no). Using their response to these questions, participants were classified as having CWP (using the definition from the American College of Rheumatology [ACR] 1990 classification criteria for fibromyalgia [19], which require pain in contralateral body quadrants above and below the waist that has lasted for at least 3 months), some pain (those participants reporting pain that did not satisfy the criteria for CWP), or no pain.

Pain severity.

Participants reporting musculoskeletal pain also completed the Chronic Pain Grade (CPG) scale, which measures the global impact of chronic pain ([20]). The CPG scale, which has been validated for use in questionnaire surveys ([20]), classifies chronic pain as grade I (low intensity/low disability), grade II (high intensity/low disability), grade III (high disability/moderately limiting), or grade IV (high disability/severely limiting). Therefore, those participants classified as having some pain or CWP were further categorized based on their level of pain severity.

Physical activity.

Physical activity levels were assessed using the Brief Physical Activity Assessment scale ([21]). The scale was developed in adults ages 20–60 years and classifies participants as either sufficiently active or insufficiently active. In the original study, validity was established against a physical activity monitor worn by participants. The scale correctly identified 76% of cases (sufficiently/insufficiently active) with a sensitivity of 71%. Participants were asked, “How many times a week do you usually do 30 minutes of moderate physical activity?” (response options were: none [score 0], 1–2 times/week [score 2], and ≥3 times/week [score 4]) and “How many times a week do you usually do 20 minutes of vigorous physical activity that makes you sweat, puff or pant?” (response options were: none [score 0], 1–2 times/week [score 1], 3–4 times/week [score 2], and ≥5 times/week [score 4]). Responses were summed and participants were dichotomized into those who were “sufficiently active” (scale score ≥4) or “insufficiently active” (scale score 0–3).

Statistical analysis.

All analyses were conducted using Stata, version 11 (StataCorp). The results are shown as numbers and percentages for categorical variables and medians with 95% confidence intervals (95% CIs) for continuous variables. To adjust for multiple testing, Bonferroni adjustments were made to the alpha level and P values less than 0.006 were considered statistically significant. For the purpose of descriptive statistics, age (in years) was categorized into 10 equal age bands across the cohort, but was used as a continuous variable in all regression analyses. Due to low numbers of participants reporting grade IV of the CPG scale, grades III and IV were combined. Multinomial logistic regression tested the relationship between JH and pain status. Associations were adjusted for age, sex, and other putative confounders. Participants with no pain were the referent category. In each model, the proportion of variance explained is shown as the pseudo R2. The JH scale ([16]) was validated in women ages 16–80 years. Sensitivity analysis was conducted by running a series of univariate and multivariate logistic regression models with and without male participants and with and without participants ages >80 years. Results are shown as relative risk ratios (RRRs) with 95% CIs.

RESULTS

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. SUBJECTS AND METHODS
  5. RESULTS
  6. DISCUSSION
  7. AUTHOR CONTRIBUTIONS
  8. REFERENCES

Response rates.

A total of 45,949 questionnaires were mailed; 18,892 individuals returned a questionnaire, of which 3,586 declined to take part (i.e., returned a blank questionnaire) and 15,306 agreed to take part and completed the questionnaire. Of those who completed the questionnaire, in 120 cases the questionnaire had been completed by the wrong individual in the household, and a further 2,333 cases had not provided complete answers to the demographic, pain, and/or JH questions. Therefore, 12,853 individuals provided complete data and were available for the current analysis, and are henceforth referred to as participants (unadjusted participation rate 28.0%) (Figure 1). The participants' median age was 55 years (range 25–107 years) and 56.6% (n = 7,268) were women (Table 1).

image

Figure 1. Flow diagram of participation in the Managing Unexplained Symptoms (Chronic Widespread Pain) in Primary Care: Involving Traditional and Accessible New Approaches (MUSICIAN) study. * = proportion of the initial mailing; † = proportion of those who responded and consented to take part; ‡ = proportion of those with complete data; CWP = chronic widespread pain; CPG = Chronic Pain Grade.

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Table 1. Summary of data stratified by pain status and CPG Questionnaire*
 All (n = 12,853)No pain (n = 4,958 [38.6%])Some pain (n = 5,801 [45.1%])CWP (n = 2,094 [16.3%])Pa
Grade I (n = 3,501 [60.4%])Grade II (n = 1,566 [27.0%])Grade III/IV (n = 734 [12.7%])Grade I (n = 731 [34.9%])Grade II (n = 773 [36.9%])Grade III/IV (n = 590 [28.2%])
  1. Values are the number (percentage) unless otherwise indicated. The some pain and chronic widespread pain (CWP) groups are categorized by pain severity grade (Chronic Pain Grade [CPG] questionnaire grades I–IV). 95% CI = 95% confidence interval.

  2. a

    P values calculated across the 7 pain groups.

  3. b

    By the Kruskal-Wallis test.

  4. c

    By the chi-square test.

  5. d

    N = 17 missing.

  6. e

    N = 1 missing.

Age, median (95% CI) years55 (43–66)54 (54–55)54 (54–55)57 (56–58)60 (58–61)54 (53–56)58 (56–59)59 (57–61)< 0.000b
Sex         
Female7,268 (56.6)2,734 (55.2)1,811 (51.7)949 (60.6)442 (60.2)414 (56.6)516 (66.8)402 (68.1)< 0.000c
Male5,585 (43.4)2,224 (44.8)1,690 (48.3)617 (39.4)292 (39.8)317 (43.4)257 (33.2)188 (31.9) 
Hypermobile         
Yes2,354 (18.3)852 (17.2)613 (17.5)319 (20.4)134 (18.3)150 (20.5)156 (20.2)130 (22.0)0.003c
No10,499 (81.7)4,106 (82.2)2,888 (82.5)1,247 (79.6)600 (81.7)581 (79.5)617 (79.2)460 (78.0) 
Employment status         
Full time5,513 (42.9)2,280 (46.0)1,658 (47.4)652 (41.6)201 (27.4)331 (45.3)291 (37.7)101 (17.1)< 0.000c
Part time1,885 (14.7)742 (15.0)544 (15.5)246 (15.7)74 (10.1)114 (15.6)125 (16.2)39 (6.6) 
Retired3,872 (30.1)1,475 (29.8)977 (27.9)483 (30.8)286 (39.0)193 (26.4)245 (31.7)213 (36.1) 
Unemployed (ill health)486 (3.8)55 (1.1)34 (1.0)45 (2.9)116 (15.8)19 (2.6)32 (4.1)185 (31.4) 
Unemployed (job seeking)771 (6.0)276 (5.6)212 (5.1)97 (6.2)43 (5.9)55 (7.5)57 (7.4)31 (5.2) 
Other326 (2.5)130 (2.6)76 (2.2)43 (2.8)14 (1.9)19 (2.6)23 (3.0)21 (3.6) 
Current health         
Excellent/very good6,460 (50.3)3,320 (67.0)1,936 (55.3)565 (36.1)150 (20.4)299 (40.9)156 (20.2)34 (5.8)< 0.000c
Good4,432 (34.5)1,370 (27.6)1,284 (36.7)716 (45.7)241 (32.8)324 (44.3)369 (47.7)128 (21.7) 
Fair/poor1,961 (15.2)268 (5.4)281 (8.0)285 (18.2)343 (46.7)108 (14.8)248 (32.1)428 (72.5) 
Regularly smoke         
Yes5,395 (42.0)1,798 (36.5)1,402 (40.0)740 (47.3)393 (53.5)326 (44.6)391 (50.6)345 (58.5)< 0.000c
No7,458 (58.0)3,160 (63.5)2,099 (60.0)826 (52.7)341 (46.6)405 (55.4)382 (49.4)245 (41.5) 
Drink alcohol         
Yes9,425 (73.3)3,679 (74.2)2,777 (79.3)1,087 (69.4)461 (62.8)569 (80.2)d519 (67.1)316 (53.6)< 0.000c
No3,428 (26.7)1,279 (25.8)724 (20.7)479 (30.6)273 (37.2)145 (19.9)d254 (32.9)274 (46.4) 
Physical activity         
Sufficiently active5,237 (40.8)2,186 (44.1)1,502 (42.9)569 (36.3)225 (30.7)321 (43.9)290 (37.5)144 (24.4)e< 0.000c
Insufficiently active7,616 (59.2)2,772 (55.9)1,999 (57.1)997 (63.7)509 (69.3)410 (56.1)483 (62.5)445 (75.6)e 

JH data.

A total of 2,354 participants (18.3%) were classified as having self-reported JH. The prevalence of JH was highest in the youngest age category (18–29 years) at 31.3% and consistently decreased with increasing age, with 14.5% of persons ages ≥78 years having self-reported JH (χ2 = 271, P < 0.001 for trend) (Figure 2). Compared to non-JH participants, those participants classified with JH were more likely to be women (71.7% versus 52.5%, female to male ratio 2.5:1; P < 0.001), younger (median age 48 years, interquartile range [IRQ] 48–49 years versus median age 57 years, IRQ 56–57 years; P < 0.001), sufficiently active (45.8% versus 39.6%; P < 0.0001), and smokers (44.7% versus 41.4%; P < 0.00), but were equally likely to drink alcohol regularly (73.6% versus 73.3%; P = 0.8).

image

Figure 2. Age-specific prevalence rates of pain groups (no pain, some pain, and chronic widespread pain [CWP]) and hypermobility.

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Musculoskeletal pain.

Of the 12,853 participants, 2,094 (16.3%) were classified as having CWP, 5,801 (45.1%) had some pain, and 4,958 (38.6%) reported no pain (Table 1). The prevalence of CWP peaked in the sixth decade at 19.2% and thereafter decreased with increasing age to 17.4% in persons ages ≥80 years (χ2 = 74.2, P < 0.001 for trend) (Figure 2). When compared to those with no pain, participants with CWP were more likely to be older, be women, have self-reported JH, rate their health poorly, be insufficiently active, and smoke, but were less likely to drink alcohol regularly (Table 1).

The some pain and CWP groups were stratified based on the severity of pain using the CPG questionnaire (Table 1). Of those reporting some pain, 60.4% graded their pain as low intensity/low disability (grade I), 27.0% as high intensity/low disability (grade II), and 12.7% as high disability/severely limiting (grade III/IV). Of those reporting CWP, 34.9% graded their pain as low intensity/low disability (grade I), 36.9% as high intensity/low disability (grade II), and 28.2% as high disability/severely limiting (grade III/IV) (Table 1).

Quantifying the relationship between JH and musculoskeletal pain.

Compared to non-JH participants, those participants classified with JH were more likely to report CWP (18.5% versus 15.8%; χ2 = 13, P < 0.001 for trend), equally likely to report some pain (45.3% versus 45.1%), and less likely to report no pain (36.2% versus 39.1%). Participants with JH were more likely to report CWP grade III/IV than non-JH participants (5.5% versus 4.4%; χ2 = 19.8, P < 0.003 for trend), although the significant differences were slight. Among those classified with JH, the proportion of participants reporting CWP increased from 17.1% to 20.3% to 27.2% to 29.2% for those scoring 2, 3, 4, and 5, respectively, on the JH scale (χ2 = 39.7, P < 0.000 for trend).

After adjusting for age and sex in a univariate multinomial logistic regression model, there was a modest association between JH and CWP grades I (RRR 1.2, 95% CI 1.0–1.5; P = 0.03) and II (RRR 1.2, 95% CI 0.5–1.4; P = 0.1), although the latter was not statistically significant. Participants with JH were 40% more likely to report CWP grade III/IV (RRR 1.4, 95% CI 1.1–1.7; P < 0.00). In the some pain group, JH was moderately associated with grade II (RRR 1.3, 95% CI 1.1–1.5; P < 0.00) and grade III/IV (RRR 1.2, 95% CI 0.9–1.4; P = 0.1). The proportion of variance (R2) of the outcome (pain) explained by JH in this first univariate model was 0.65% (pseudo R2 = 0.0065). After further adjustment in a multivariate model for employment status, smoking, alcohol consumption, and physical activity, JH remained significantly associated with grade III/IV (the most disabling and limiting grade) for some pain (RRR 1.3, 95% CI 1.02–1.6; P = 0.03) and CWP (RRR 1.6, 95% CI 1.3–2.1; P < 0.00) (Table 2), although the proportion of variance in pain explained by all factors in the model remained low (pseudo R2 = 0.088).

Table 2. Multivariate logistic regression analysis quantifying the relationship between joint hypermobility and pain, controlled for known putative confounding factors (n = 12,853)*
 Some pain (n = 5,801)CWP (n = 2,094)
Grade I (n = 3,501 [60.4%])Grade II (n = 1,566 [27.0%])Grade III/IV (n = 734 [12.7%])Grade I (n = 731 [34.9%])Grade II (n = 773 [36.9%])Grade III/IV (n = 590 [28.2%])
  1. Values are the relative risk ratio (95% confidence interval). The no pain group is the referent category. Model adjusted for age, sex, employment status, smoking, alcohol consumption, and physical activity. Pseudo R2multivariate model = 0.088. CWP = chronic widespread pain.

Hypermobile      
NoReferentReferentReferentReferentReferentReferent
Yes1.1 (0.9–1.2)1.3 (1.1–1.5)1.3 (1.02–1.6)1.3 (1.02–1.5)1.2 (0.99–1.5)1.6 (1.3–2.1)
Employment status      
Full timeReferentReferentReferentReferentReferentReferent
Part time1.1 (0.9–1.2)0.9 (0.8–1.1)0.9 (0.7–1.2)0.9 (0.8–1.3)0.9 (0.8–1.3)0.8 (0.5–1.2)
Retired0.9 (0.8–1.1)0.7 (0.5–0.8)1.1 (0.8–1.5)0.7 (0.6–0.98)0.8 (0.6–0.98)1.4 (1.1–2.0)
Unemployed (ill health)0.6 (0.4–0.9)1.0 (0.7–1.6)4.3 (2.8–6.2)1.1 (0.7–1.9)0.9 (0.7–2.2)7.8 (5.1–11.7)
Unemployed (job seeking)1.1 (0.9–1.3)0.9 (0.7–1.1)1.0 (0.7–1.5)1.1 (0.8–1.5)0.9 (0.8–1.5)1.1 (0.7–1.8)
Other0.8 (0.6–1.1)0.9 (0.6–1.3)0.8 (0.5–1.5)0.9 (0.5–1.5)0.9 (0.5–1.5)1.8 (1.0–3.0)
Current health      
Excellent/very goodReferentReferentReferentReferentReferentReferent
Good1.7 (1.5–1.9)3.0 (2.6–3.4)3.5 (2.8–4.4)2.9 (2.4–3.4)6.1 (5.0–7.4)7.9 (5.3–11.7)
Fair/poor2.0 (1.7–2.4)6.1 (5.0–7.5)19.7 (15.3–25.4)5.2 (17.2–28.5)22.1 (8.0–17.2)93.3 (63.0–138.2)
Regularly smoke      
NoReferentReferentReferentReferentReferentReferent
Yes1.1 (0.9–1.2)1.4 (1.2–1.6)1.5 (1.3–1.8)1.2 (1.0–1.4)1.5 (1.3–1.8)1.7 (1.4–2.1)
Drink alcohol      
NoReferentReferentReferentReferentReferentReferent
Yes1.3 (1.2–1.5)1.1 (0.9–1.2)0.8 (0.7–0.95)1.5 (1.2–1.8)0.9 (0.7–1.1)0.6 (0.5–0.7)
Physical activity      
Sufficiently activeReferentReferentReferentReferentReferentReferent
Insufficiently active1.0 (0.9–1.1)1.0 (1.0–1.0)1.0 (0.9–1.2)0.8 (0.7–0.99)0.8 (0.1–1.0)1.1 (0.9–1.3)

Sensitivity analysis.

Series of multivariate multinomial regression models were conducted to examine the influence of excluding adults ages >80 years or men on the strength of association between JH and pain status, since the 5-point JH scale ([16]) previously has not been validated for use with these populations. These analyses show that the observed associations (Table 2) were not affected by the exclusion of older participants. However, when the analyses included only women, the association with some pain grade III/IV was no longer statistically significant (RRR 1.2, 95% CI 0.95–1.6; P > 0.05); however, the association with CWP grade III/IV persisted (RRR 1.6, 95% CI 1.2–2.1; P < 0.05).

DISCUSSION

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. SUBJECTS AND METHODS
  5. RESULTS
  6. DISCUSSION
  7. AUTHOR CONTRIBUTIONS
  8. REFERENCES

Of the surveyed participants, 18.3% satisfied the criteria for JH ([16]). To the best of our knowledge, this is the first report of the prevalence of JH in a large unselected population-based sample using the 5-point questionnaire to detect hypermobility ([16]). Previous observational and experimental studies using the Beighton criteria have reported similar prevalence rates between 17.6% ([11]) and 64.2% ([22]). The population prevalence of JH reported here (18.3%) is considerably lower than has been previously observed in clinical populations ([22, 23]). In a case–control study of women with fibromyalgia, Ofluoglu et al observed a JH point prevalence rate of 64.2% versus 22% in healthy controls ([22]). It is unclear why prevalence rates from clinical populations are so much greater than population-derived rates, although other studies have identified a bias toward reporting of somatic symptoms (such as JH) in those with CWP ([24, 25]) that may account for some of the variance.

Our results support the hypotheses that in an unselected population, JH would be associated with reporting musculoskeletal pain and the strength of association would be strongest for those reporting the most severe pain. Our data also suggest that these associations were independent of putative confounders, including physical activity levels, smoking, and alcohol use. These findings should be interpreted carefully. Although the differences in CWP between those with and without JH were statistically significant, the degree of difference was modest (18.5% versus 15.8%). Moreover, the differences in the proportion of participants reporting the most severe CWP (grade III/IV) between those with and without JH were even more modest (5.5% versus 4.4%), yet remained statistically significant. The fact that modest differences reached significance may be explained by the large sample size ([26]).

The reason for the relationship between JH and age observed in the present data is unclear. Beighton et al also demonstrated an age-related decline in JH prevalence more than 3 decades ago ([13]). Pailhez et al found JH in 27.3% of 15–18-year-olds ([27]). In the present study, the prevalence of JH was highest in the youngest age group (18–29 years) at 31.3% and steadily decreased as age increased (Figure 2). Why this bias toward an age-related decline in JH is the case is unclear. It is possible that this is a real age-related effect underpinned by biologic processes that decrease joint laxity. The finding here that hypermobile participants were both younger and more likely to be sufficiently active (Table 1) suggests that the reduction in the prevalence of JH with age may be explained by an overall decrease in physical activity with increasing age, although this is speculative and requires confirmation by a formal prospective study. Alternatively, it is possible that participants do not recall the signs of hypermobility as they age, or the decline in prevalence may be the result of a cohort effect. The sex-related prevalence of JH has been well documented, with women consistently reporting a higher prevalence of hypermobility than men ([1, 12, 27, 28]). In our sample, the female to male ratio of JH prevalence was 2.5:1, although the underpinning explanation for sex-related differences in JH remains unclear.

The prevalence of pain among individuals with hypermobility is not clear. Although many authors state that the main symptom of people with JH is pain ([2, 16, 29, 30]), there are few reports to support this assertion. In the present study, of those participants classified as hypermobile, 36.2% reported no pain, 45.3% reported some pain, and 18.5% reported CWP compared with 39.1%, 45.1%, and 15.8% of those participants who were not hypermobile, respectively. Moreover, the strength of association between JH and pain was strongest in those reporting the most disabling and limiting CWP (Table 2). In a study of 273 patients with Ehlers-Danlos syndrome, 84% self-reported past or current JH and 90% reported the presence of pain (it is unclear from the report if standardized measures of pain and JH were used) ([7]). In a recent review, Grahame reported unpublished data indicating that of 700 hypermobile patients attending the author's clinic, 26% reported that their pain was life dominating ([2]). In another review by Remvig et al, hypermobility was correlated with “general back pain” as well as with “work-related back pain” in adults, although this relationship was not found in young adults or children ([1]).

In considering these results, the following study limitations are important. First, the proportion of variance in pain explained by JH was relatively minor. Although a significant association was demonstrated, the proportion of variance in pain reporting explained by JH was 0.65% (univariate model). After additional putative risk factors were included in the model, the proportion of variance explained was 8.8% (multivariate model). Therefore, we must consider what potential unmeasured factors may explain the remaining 91% of the variance in pain reporting. There are a number of factors that were not measured in this study that may account for some of the remaining unexplained variance in the model. Psychological factors such as anxiety and depression are known to be strongly associated with the reporting of JH and pain ([31, 32]). In a 15-year followup study, Bulbena et al found that compared to those without JH, those with JH had a 22-fold increased risk of being diagnosed with a trait anxiety disorder at followup ([12]). The absence of measures of psychological distress in our study therefore limits the extent to which we are able to explain the relationship between JH and musculoskeletal pain.

Second, of the 45,949 individuals who received the questionnaire, only 12,853 (28%) returned a questionnaire with complete data (Figure 1). Low response rates are of concern in population surveys because they may lead to uncertainty about sample representativeness. However, Groves et al provide evidence that the relationship between response rates and bias is complex and not simply a direct one-to-one association ([33]). The authors suggest that a low response rate alone may not necessarily alter survey estimates ([33]). Indeed, the age and sex distributions of the responders in this survey were similar to those found in the 2001 National Census in the North of England and Scotland. Furthermore, Macfarlane et al reported remarkably similar survey estimates to those reported here (female sex 58.9% versus 56.6%, median age 54 years versus 55 years, prevalence of CWP 15.3% versus 16.3%) in an unselected general population–based survey in a similar geographic region of the UK (Cheshire) to the present study and achieved a much higher response rate (80%) ([34]). Nevertheless, the participation rate (in absolute numbers rather than as a proportion of individuals mailed) was high compared with other chronic pain epidemiology studies ([34]). The inclusion of large sample sizes can lead to small differences between groups reaching the threshold of statistical significance (even after adjusting for multiple testing), which may not in fact reflect a clinically meaningful difference. This should be considered carefully when interpreting the statistically significant difference in pain between the JH groups, given that the association between pain and JH was modest and only 8.8% of the variance in pain was explained in the fully adjusted model (Table 2).

Finally, the cross-sectional nature of the present study prevents the investigation of the temporal associations between JH and musculoskeletal pain, and whether JH precedes the onset of pain is unclear.

It is particularly interesting that across both univariate and multivariate models (Table 2), there was a consistent relationship between self-reported JH and lifestyle factors, such as smoking, alcohol use, and physical activity. The data in Table 1 show that irrespective of ACR pain classification status, participants reporting the most limiting and disabling pain (grade III/IV) were more likely to smoke, rate their health poorly, be unemployed due to ill health, and be insufficiently active. Taken together, these data suggest that related lifestyle factors, known to be associated with socioeconomic status, may further explain the relationship between JH and musculoskeletal pain. Nevertheless, based on these data, it is difficult to suggest direct implications for clinical practice given the weak association observed between JH and musculoskeletal pain. A strong association would have lent support for further exploratory investigations into putative mechanisms of association and potential avenues to decrease pain; however, these data do not support such a statement.

In summary, these results provide the first report of the prevalence of self-reported JH in a large unselected general population sample using the 5-point JH questionnaire. JH was moderately associated with pain that was severely disabling and limiting, although the total proportion of variance in pain explained by JH was relatively small. Unmeasured confounding factors such as psychological distress may explain the relationship. Future studies should prospectively investigate the associations between JH and the onset and persistence of chronic musculoskeletal pain, accounting for putative biologic, behavioral, and psychological risk factors.

AUTHOR CONTRIBUTIONS

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. SUBJECTS AND METHODS
  5. RESULTS
  6. DISCUSSION
  7. AUTHOR CONTRIBUTIONS
  8. REFERENCES

All authors were involved in drafting the article or revising it critically for important intellectual content, and all authors approved the final version to be published. Dr. McBeth had full access to all of the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis.

Study conception and design. Mulvey, Macfarlane, Symmons, Lovell, Keeley, Woby, McBeth.

Acquisition of data. Macfarlane, Beasley, Lovell, Keeley, Woby, McBeth.

Analysis and interpretation of data. Mulvey, Symmons, Woby, McBeth.

REFERENCES

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. SUBJECTS AND METHODS
  5. RESULTS
  6. DISCUSSION
  7. AUTHOR CONTRIBUTIONS
  8. REFERENCES