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Body Composition Is Associated With Multisite Lower Body Musculoskeletal Pain in a Community-Based Study
Accepted Manuscript Body Composition Is Associated With Multisite Lower Body Musculoskeletal Pain In a Community-based Study Sharmayne R.E. Brady, BMedSc (Hons), MBBS (Hons), FRACP, Bambino B. Mamuaya, BMedSc(Hons), Flavia Cicuttini, MBBS, FRACP, PhD, Anita E. Wluka, MBBS, FRACP, PhD, Yuanyuan Wang, MD, PhD, Sultana Monira Hussain, MBBS, MPH, Donna M. Urquhart, BPhysio, PhD PII:
S1526-5900(15)00642-2
DOI:
10.1016/j.jpain.2015.04.006
Reference:
YJPAI 3080
To appear in:
Journal of Pain
Received Date: 11 November 2014 Revised Date:
19 March 2015
Accepted Date: 17 April 2015
Please cite this article as: Brady SRE, Mamuaya BB, Cicuttini F, Wluka AE, Wang Y, Hussain SM, Urquhart DM, Body Composition Is Associated With Multisite Lower Body Musculoskeletal Pain In a Community-based Study, Journal of Pain (2015), doi: 10.1016/j.jpain.2015.04.006. This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.
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Body Composition Is Associated With Multisite Lower Body Musculoskeletal Pain In a Community-based Study Sharmayne R.E. Brady1 (BMedSc (Hons), MBBS (Hons), FRACP), Bambino B. Mamuaya1
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(BMedSc(Hons)), Flavia Cicuttini1 (MBBS, FRACP, PhD), Anita E. Wluka1 (MBBS, FRACP, PhD), Yuanyuan Wang1 (MD, PhD), Sultana Monira Hussain1 (MBBS, MPH), Donna M. Urquhart1 (BPhysio, PhD)
Department of Epidemiology and Preventive Medicine, School of Public Health and
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Preventive Medicine, Monash University, Melbourne, Victoria 3004, Australia S.R.E.B. and B.B.M. are co-first authors
Disclosures
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S.R.E.B. was supported by a NHMRC Clinical Postgraduate Research scholarship (#1074979). A.E.W., Y. W., and D.M.U. are the recipients of NHMRC Career Development Fellowships (Clinical Level 2 #1063574, Clinical Level 1 #1065464, and Clinical Level 1 #1011975,
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respectively). All authors made significant contributions to the manuscript. There are no
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conflicts of interest to disclose.
Address correspondence to:
Dr Donna Urquhart, Department of Epidemiology and
Preventive Medicine, School of Public Health and Preventive Medicine, Monash University The Alfred Centre, 99 Commercial Rd Melbourne 3004, Victoria, AUSTRALIA Ph: 9903 0555 Fax: 9903 0556 Email: [email protected]
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ACCEPTED MANUSCRIPT Abstract
Population-based studies suggest that pain in the lower body is common, and that pain at multiple sites is more prevalent than single site pain. Obesity is a risk factor for multisite
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musculoskeletal pain, but there are limited data on the role of body composition. Therefore, we determined whether body composition is associated with multisite musculoskeletal pain, involving the lower back, knee and foot. 133 participants were recruited for a study
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examining the relationship between obesity and musculoskeletal disease. Participants completed validated questionnaires which examined levels of pain at the low back, knee
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and foot. Body composition was assessed using dual energy x-ray absorptiometry. Multisite pain was common, with 26.3% of participants reporting pain at two sites, 31.6% at three sites and only 20% were pain free. The lower back was the most common site of pain (63%). Increasing fat mass and fat mass index, but not fat free mass, was associated with pain at a
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greater number of sites, independent of age, gender and fat free mass (p<0.01). Longitudinal studies exploring the mechanism of action by which increased fat mass is
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associated with pain may provide important insight into therapeutic strategies for the
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prevention of multi-site pain.
Running title: Fat mass is associated with multisite pain
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Perspective: Greater fat mass and fat mass index were associated with a greater number of lower body pain sites, with no association observed for fat free mass. Understanding the mechanism by which increased fat mass is associated with pain may provide important
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Key words: Body composition, Fat mass Pain, Epidemiology
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insight into therapeutic strategies for the prevention of pain.
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ACCEPTED MANUSCRIPT Introduction Musculoskeletal pain is an important clinical and public health problem. Although most
studies focus on musculoskeletal pain at a single site, pain in more than one anatomical site
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is common. In a study of 12,410 employed adults across 18 different countries, multisite pain (or pain located at ≥2 sites) was more common than pain located at one site6. Similarly a population-based study of 3179 Norwegian adults found that 53% had multisite pain
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compared to 17% with single site pain19.
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Population-based studies have also suggested that localised musculoskeletal pain (e.g. back or knee pain), are more disabling when accompanied by pain at other sites than when a single site is affected24. Results from cross sectional studies show that there is an almost linear increase in functional problems with increasing number of pain sites19. Moreover, the
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absenteeism13.
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number of pain sites has been shown to be a strong independent predictor of work
Potential risk factors for multisite pain include older age6, 12, female gender6, 9, high physical
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workload6, 14, 29, as well as psychological factors such as somatising tendency6, 29. There is also growing evidence to indicate a role of obesity. For instance, a study of female kitchen workers found obesity (body mass index [BMI] ≥ 30 kg/m2) to be associated with an increased prevalence of multisite musculoskeletal pain14, and a population-based study reported a greater number of pain sites in individuals with higher BMI18. Moreover, in a study of 48 participants, musculoskeletal pain improved in obese subjects after undergoing bariatric surgery at 6 and 12 months post-procedure15. While 100% had lower extremity
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musculoskeletal pain before surgery, only 37% reported pain after weight loss. Similarly, 79% had upper extremity musculoskeletal conditions before surgery and 40% after weight loss15. Given this is a non-weight bearing region, it suggests that the effect of adipose tissue
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on musculoskeletal pain is unlikely to be simply due to physical loading on joints, but rather that fat (or adipose tissue) may also contribute to pain through systemic mechanisms20, 27.
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The emerging evidence suggests that fat and muscle mass have different roles in the
pathogenesis of musculoskeletal disease28. The detrimental effects of adipose tissue on
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musculoskeletal health have previously been reviewed20. In a study of synovial leptin (an adipose tissue-derived hormone), Dumond et al found that leptin was overexpressed in human osteoarthritic knee joints and the level of leptin expression related to the degree of cartilage destruction, suggesting its role in the pathogenesis of OA8. Moreover high synovial
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leptin levels have been associated with high levels of lower limb joint pain21. The role of body composition has only recently been addressed as previous studies have used weight
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and BMI as measures of obesity and these do not allow examination of body composition (muscle and fat mass). However, recent studies have examined body composition and their
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association with pain at single anatomical sites. These studies have found that greater fat mass, but not lean tissue mass, is associated with greater levels of low back pain and disability31, incident foot pain3, and early structural changes at the knee, which are predictors of knee osteoarthritis (cartilage defects, bone marrow lesions and decreased cartilage volume)2, 34. However, few studies to date have assessed the relationship between body composition and pain at multiple sites.
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The aim of this study was to examine the associations between body composition and lower body pain at three sites (lower back, knee and foot). These lower body sites were our focus in the study because of the high prevalence of lower body pain in the general population19, 25
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, and because lower body musculoskeletal pain causes significant disability and burden in
society10, 17. Our hypothesis was that fat mass would be associated with a greater number of
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pain sites in the lower body.
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ACCEPTED MANUSCRIPT Materials and Methods
Participants
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A total of 133 participants, who ranged from normal weight to obese, were recruited through local media and community weight loss clinics to take part in a study of obesity and musculoskeletal health. These participants were not recruited on the basis of having pain.
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All provided informed consent. Exclusion criteria included malignancy or inability to complete the study. The study was approved by the Alfred Human Research Ethics
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Committee (HREC), Monash University HREC, Austin Health HREC, and the University of Melbourne Central HREC.
Data Collection
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Demographic and anthropometric data
Age, gender, weight, and height were recorded. Height was measured using a stadiometer
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and weight measured using a single pair of electronic scales, to the nearest 0.1 kg with
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shoes and bulky clothing removed. BMI (weight ÷ [height2]; kg/m2) was calculated.
Body composition measurement Body composition was measured using dual energy x-ray absorptiometry (DEXA, GE Lunar Prodigy, using operating system version 9; GE Healthcare, United Kingdom), which had a weight limit of approximately 130kg. Standard regional analyses were used to measure total body fat mass as well as total body lean tissue mass. Lean tissue mass was used as a measurement of skeletal muscle mass. Fat mass index (FMI) and fat free mass index (FFMI)
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were calculated as follows: FMI = fat mass/height2 and FFMI = fat free mass / height2, where fat free mass = lean tissue mass + bone mineral content.
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Pain prevalence Data on pain prevalence at the low back, knee and foot was performed using region-specific questionnaires. To examine the prevalence of low back pain, the question “Have you had
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low back pain in the past month?” was used, along with a figure of a mannequin that marked the low back as a squared area between the lower border of the rib cage and the
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gluteal folds. The Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) and Visual Analogue Scale (VAS), validated tools for use in populations with knee pain1, were used for the identification of knee pain. The WOMAC is composed of 24 items divided into 3 subscales, pain, stiffness, and physical function. In this study, only the pain subscale
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knee pain.
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was used. A cut-off of ≥20 on a 0–100-mm VAS was used to determine clinically significant
To establish foot pain prevalence in our study, the Foot pain and Manchester Foot Pain and
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Disability Index (MFPDI) was utilised11, which has been validated in rheumatology patients, patients of general health practitioners who have reported foot-related problems, and people from the general community23. The MFPDI consists of 19 items that are preceded with the phrase, ‘because of pain in my feet,’’ formalized under four categories: functional limitation (10 items), pain intensity (5 items), personal appearance (2 items), and difficulties with work or leisure activities (2 items). Each item is scored according to frequency (e.g. ‘‘none of the time" [0 points], ‘‘on some days" [1 point], or ‘‘on most/everyday" [2 points]);
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subsequently, scores on the MFPDI range between 0 and 38, with higher scores denoting more disabling pain. Using the original definition of foot pain as described by Garrow et al11,
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participants with a score of ≥1 from 19 items were defined as having disabling foot pain.
Multisite lower body pain was defined as musculoskeletal pain arising from two or more anatomical sites involving the low back, knees and feet. This definition was used because
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number of pain sites has been shown to be a useful method of classifying multisite pain and studies have shown that pain in multiple sites differs in its risk factors to localised pain at
site, two sites and pain at three sites).
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one site6. The number of pain sites was classified into four categories (no pain, pain at one
The Short Form 36 (SF-36) questionnaire (mental and physical health component) was used
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Statistical Analysis
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to estimate the overall mental and physical health of the participants22.
Chi squared tests were used for comparison of categorical data for participants with
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different numbers of pain sites. The F test was used to determine the pairwise comparison among the estimated marginal means for continuous data. To examine the relationship between fat mass and number of pain sites, independent of lean tissue mass, the respective fat free mass parameter was included in the multivariate model. Similarly, to examine the relationship between fat free mass and number of pain sites, independent of fat mass, the respective fat mass parameter was included in the multivariate model. Adjustment was also made for potential confounders including age, gender and the mental health component
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score from the SF-36. The statistical analyses were conducted using SPSS Statistics 21.0
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(SPSS Institute, Cary, NC). A p value of less than 0.05 was considered statistically significant.
Results
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The 133 participants recruited for this study were aged between 25 to 62 years with a range of body mass indices (18–55 kg/m2). Three participants were excluded from body
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composition measurements due to the 130kg weight limit of the dual energy x-ray absorptiometry machine. The characteristics of the participants based on the number of pain sites are presented in Table 1. While the mean age (p=0.81) and gender distribution (p=0.89) did not differ according to the number of pain sites, physical health scores, but not
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mental health scores, were significantly lower in those with pain compared to those without pain (p<0.01). In terms of obesity measures, elevated weight and BMI were associated with
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a greater number of pain sites (p<0.01).
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ACCEPTED MANUSCRIPT Table 1: Participant characteristics according to the number of pain sites (n=133)
Physical health component
score (SF-36) Mental health component
score (SF-36)
Pain at 2
Pain at 3
P
(n=27)
site (n=29)
sites (n=35)
sites (n=42)
value
46.3
48.8
47.7
47.9
0.81
(42.8 - 50.0)
(45.3 - 52.2)
(44.6 - 50.8)
(45.0 - 50.7)
20 (74.1)
24 (82.8)
27 (77.1)
33 (78.6)
0.89
54.7
52.8
47.8
41.9
<0.01
(51.3 - 58.0)
(49.6 - 55.9)
48.3
50.7
(43.1 - 53.5)
Foot pain, n (%) a
0.31
95.3
98.4
(73.3 - 89.9)
(87.8 - 102.8)
(91.5 - 105.3)
28.4
29.8
34.6
36.6
(25.2 - 31.6)
(26.8 - 32.9)
(31.8 - 37.4)
(34.1 - 39.2)
0
16 (55.2)
26 (74.3)
42 (100)
N/A
0
7 (24.1)
16 (45.7)
42 (100)
N/A
0
6 (20.7)
28 (80)
42 (100)
N/A
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Knee pain, n (%)
44.9
81.6
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Back pain, n (%)
46.1
(40.8 - 48.9)
(68.3 - 85.5)
Pain characteristics
(39.2 – 44.5)
(41.7 - 50.6)
76.9
BMI (kg/m2)
(45.0 - 50.7)
(45.8–55.6)
Measures of obesity Weight (kg)
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Female, n (%)
Pain at 1
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Age (years)
No pain
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Characteristics a
All continuous variables are expressed as mean (95% confidence interval).
Abbreviations: BMI, Body mass index
<0.01
<0.01
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Total n=133 No pain n=27 (20.3%)
Knee pain (n=7)
Total at three sites n= 42 (31.6%)
n=42 Back pain (n=16)
Foot pain (n=6)
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Total at two sites n = 35 (26.3%)
n=9
n=7
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Total at one site n = 29 (21.8%)
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(Total = 65, 49%)
n=19
(Total = 76, 57%)
(Total = 84, 63%)
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Figure 1: Pain experienced by study population
The location of pain experienced by the participants is presented in Figure 1 and Table 1. In
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the study population, 27 (20.3%) people were pain free and of the 29 (21.8%) people who
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had pain at one site alone, back pain contributed 55.2%, followed by knee pain in 24.1%. In the 35 (26.3%) people who had pain in two areas, the back and feet were most commonly reported (54.3%). There were 42 participants who had pain at all three sites, comprising 31.6% of the study population. The lower back was the most common site of pain overall, with 63% of the participants having back pain, followed by foot pain (57%) and knee pain (49%). Multi-site pain was common, with 57.9% of participants suffering from pain in two or three anatomical sites. 106 (79.7%) had pain in at least one site (comprising back, knee or foot).
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The relationship between both BMI and body composition measures and the number of pain sites is presented in Table 2. In both the crude and adjusted analysis, there was an
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increase in fat mass and fat mass index as the number of pain sites increased (p<0.01). Fat free mass index was also increased in both crude analyses and when adjusted for age and gender (p=0.04). However, when fat mass index was added to the model, the association
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did not remain significant (p=0.56). When analyses were repeated with mental health component score from the SF-36 questionnaire added to the model, both the fat mass index
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and fat mass association were still significant (p< 0.01, data not shown).
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ACCEPTED MANUSCRIPT Table 2: Association between the number of pain sites and body mass index (BMI) and body composition
Measures of obesity No pain and body composition a (n=27)
Pain at one Pain at 2 Pain at 3 P site (n=29) sites (n=35) sites (n=42) value
Unadjusted analysis Body mass index (kg/m2)
<0.01
28.4 29.9 34.5 36.6 (25.2 – 31.5) (26.8 – 32.9) (31.8 – 37.3) (34.1 – 39.2) Fat mass (kg) 26.9 32.0 41.2 43.9 (20.9 - 33.0) (26.3 - 37.7) (36.0 - 46.4) (39.0 - 48.7) Fat mass index 10.0 11.7 15.1 16.6 (7.7 – 12.4) (9.5 – 13.9) (13.1 – 17.1) (14.7 – 18.5) Fat free mass (kg) 47.2 48.8 53.5 50.8 (43.2 – 51.2) (45.1 – 52.6) (50.1 – 56.9) (47.6 – 54.0) Fat free mass index 17.4 17.8 19.2 18.8 (16.4 – 18.5) (16.8 – 18.8) (18.3 – 20.1) (17.9 – 19.6) Adjusted for age, gender and respective body composition measure (fat or fat free mass)
<0.01
Fat mass (kg)
<0.01b
Fat free mass (kg) Fat free mass index Adjusted for age and gender
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Body mass index (kg/m2)
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Fat mass index
34.6 (31.8 - 37.4) 41.2 (36.0 - 46.4) 15.1 (13.1 - 17.1) 53.5 (50.1 - 56.9) 19.2 (18.2 - 20.1)
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36.6 (34.1 - 39.2) 43.9 (39.0 - 48.7) 16.6 (14.7 - 18.5) 50.8 (47.6 - 54.0) 18.8 (17.9 - 19. 6)
Fat mass (kg)
29.8 (26.8 - 32.9) 32.1 (26.4 - 37.8) 11.8 (9.5 - 14.0) 48.8 (45.1 - 52.5) 17.8 (16.8 - 18.8)
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28.4 (25.2 - 31.6) 26.9 (20.9 - 32.9) 10.0 (7.6 - 12.3) 47.2 (43.3 - 51.2) 17.4 (16.3 - 18.4)
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28.2 32.6 40.0 (22.2 - 34.1) (27.0 - 38.2) (34.9 – 45.2) Fat mass index 11.0 12.3 14.4 (8.8 – 13.1) (10.2 – 14.3) (12.5 – 16.2) Fat free mass (kg) 48.9 49.7 52.8 (44.9 – 52.9) (46.0 – 53.4) (49.5 – 56.2) Fat free mass index 18.1 18.2 18.9 (17.1 – 19.2) (17.3 – 19.1) (18.1 – 19.7) a All continuous variables are expressed as mean (95% confidence interval). b Fat free mass/index added to the model c Fat mass/index added to the model
43.7 (39.0 – 48.4) 16.2 (14.5 – 17.9) 49.7 (46.5 – 52.9) 18.2 (17.4 – 19.0)
<0.01 <0.01 0.09 0.04
<0.01 <0.01 0.09 0.04
<0.01b 0.40c 0.56c
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ACCEPTED MANUSCRIPT Discussion
In our study of community-based adults, multisite lower body pain was common with 58%
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of participants having pain in two or three anatomical sites. The lower back was the most common site of lower body pain, followed by the feet and knees. Greater weight, BMI, fat mass and fat mass index were all associated with an increased number of lower body pain
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sites, with no association observed for fat free mass or fat free mass index. The findings suggest that one possible mechanism for the relationship between fat mass and multisite
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lower body pain may be via systemic metabolic factors associated with having excess adipose tissue. If lower body pain was simply related to physical loading on anatomical structures, then we would have expected to see the same relationship with fat free mass.
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The high prevalence of multisite lower body pain seen in our study is consistent with previous studies that have examined sites over the whole body. In a study of 12,410 working
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adults aged 20–59 years across 18 countries, 41% of people reported pain located in at least two sites out of the six anatomical regions assessed (low back, neck, shoulder, elbow,
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wrist/hand and knee)6. Pain was most frequently seen in the low back (36%), which is consistent with our findings. Our results are also consistent with a population based UK study of 2445 adults, which showed that more people had chronic pain in two or more sites (73%) than at a single site (27%)4. Similarly a population-based Norwegian study of 3179 patients (aged 24 to 76 years) found that 53% of patients had multisite pain in comparison to 17% who had single site pain. In this study there were 10 regions assessed including head,
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neck, shoulder, elbow, hand/wrist, upper back, lower back, hip, knee, and ankle/foot with the neck (36%) and low back (34%) being the most common sites19.
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Our study found that having a BMI greater than 30 kg/m2 was associated with having pain at multiple sites in the lower body. This is consistent with Yoo et al who demonstrated that widespread pain was associated with high fat:muscle mass ratios, particularly in women35.
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Similarly, Haukka et al found that obesity (BMI ≥30 kg/m2) in Finnish female kitchen workers was associated with an increased prevalence of multisite musculoskeletal pain14 and
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Kamaleri et al also found that a greater number of pain sites were reported in individuals with higher BMI18. While the relationship between measurements of body composition, specifically fat mass and fat mass index, with number of lower body pain sites has not been examined before, previous studies have recognized the association of fat mass with pain at
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single sites only3, 31. Recently our group has reported that greater fat mass, but not lean tissue mass, is associated with greater levels of low back pain and disability31, prevalent and
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incident foot pain3, 30, and cartilage defects, bone marrow lesions and decreased cartilage
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volume in the knee2, 34.
Although it is recognized that obesity is a risk factor for musculoskeletal disease, the evidence is accumulating to support that this is not simply through physical loading but rather via systemic mechanisms. This was recognized in studies that showed obesity is a risk factor for hand osteoarthritis which is a non-weight bearing joint5. The current study provides further support for a systemic effect of obesity on the risk of lower limb multisite pain as we found that fat mass, rather than fat free mass, was associated with multisite pain.
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If the mechanism was simply physical loading, then we would have expected to see the same relationship with fat mass and fat free mass. Adipose tissue is metabolically active and has even been labelled an endocrine organ because it releases such a large number of
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substances including cytokines, such as interleukin 1 and tumour necrosis factor alpha, as well as adipokines, such as leptin, adiponectin and resistin26,
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. These inflammatory
mediators have been shown to affect both joint structures contributing to structural
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abnormalities8, but also to have a role in nociceptive pathways21 and in the development
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and progression of chronic pain7, 32.
A limitation of this study is that it is cross-sectional so the results will need to be confirmed with a longitudinal study. Although we had a modest sample size, all participants had body composition measured using DEXA, which is costly and difficult to perform on large samples.
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Moreover, this sample size provided adequate power to detect significant relationships using independent measures of fat mass. Although the quality of the data on pain depends
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on the willingness of the participants to answer questionnaires, these measures were completed using either validated tools or questions that have been used in numerous
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population-based studies in the field16. While this study focuses on the presence of pain at multiple sites, exploring the severity and chronicity of pain and its functional impact across multiple sites is a potential area for future investigation. While we investigated lower back, foot and knee pain in this study, hip pain was not included. Further investigation is needed to determine whether including other regions of the lower limb such as the hip alters our findings. Given hip pain is not as common as the other three sites we examined, and obesity, including fat mass, is also a risk factor for hip OA33, we hypothesise that our results will
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ACCEPTED MANUSCRIPT remain unchanged. Further work will be needed to determine whether the relationship is
similar if the upper body is examined. Potential strengths of our study was that we adjusted for confounders such as age, sex as well as fat and fat free mass, which are known to have a
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collinear relationship. We also used unique measures of body composition and identified significant associations with number of pain sites. Additionally, we used a community based sample of participants who were not recruited on the basis of having pain and the region we
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assessed was the lower body, which allowed us to specifically address sites that work as one
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functional unit of mobility.
In community-based adults, increased fat mass, but not fat free mass, was associated with a greater number of sites of pain in the lower body. Understanding the mechanism of action by which increased fat mass is associated with pain may provide important insight into
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therapeutic strategies for the prevention of pain. Longitudinal studies assessing a wide range of pain sites in the body may help confirm these associations and determine whether
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fat mass is predictive of pain at other non-weight bearing sites. This may have important implications for future prevention strategies which could be focussed towards reducing fat
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mass and may assist in reducing the significant burden of multisite pain in the community.
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ACCEPTED MANUSCRIPT Highlights Pain at multiple sites is common; the impact of body composition is unclear.
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We examined the association between body composition and pain at three sites.
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Dual energy x-ray absorptiometry was used to assess body composition.
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Multisite pain was common, with the most frequent site being the lower back.
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Greater fat mass was associated with an increased number of lower body pain sites.
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S1526-5900(15)00642-2
DOI:
10.1016/j.jpain.2015.04.006
Reference:
YJPAI 3080
To appear in:
Journal of Pain
Received Date: 11 November 2014 Revised Date:
19 March 2015
Accepted Date: 17 April 2015
Please cite this article as: Brady SRE, Mamuaya BB, Cicuttini F, Wluka AE, Wang Y, Hussain SM, Urquhart DM, Body Composition Is Associated With Multisite Lower Body Musculoskeletal Pain In a Community-based Study, Journal of Pain (2015), doi: 10.1016/j.jpain.2015.04.006. This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.
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Body Composition Is Associated With Multisite Lower Body Musculoskeletal Pain In a Community-based Study Sharmayne R.E. Brady1 (BMedSc (Hons), MBBS (Hons), FRACP), Bambino B. Mamuaya1
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(BMedSc(Hons)), Flavia Cicuttini1 (MBBS, FRACP, PhD), Anita E. Wluka1 (MBBS, FRACP, PhD), Yuanyuan Wang1 (MD, PhD), Sultana Monira Hussain1 (MBBS, MPH), Donna M. Urquhart1 (BPhysio, PhD)
Department of Epidemiology and Preventive Medicine, School of Public Health and
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Preventive Medicine, Monash University, Melbourne, Victoria 3004, Australia S.R.E.B. and B.B.M. are co-first authors
Disclosures
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S.R.E.B. was supported by a NHMRC Clinical Postgraduate Research scholarship (#1074979). A.E.W., Y. W., and D.M.U. are the recipients of NHMRC Career Development Fellowships (Clinical Level 2 #1063574, Clinical Level 1 #1065464, and Clinical Level 1 #1011975,
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respectively). All authors made significant contributions to the manuscript. There are no
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conflicts of interest to disclose.
Address correspondence to:
Dr Donna Urquhart, Department of Epidemiology and
Preventive Medicine, School of Public Health and Preventive Medicine, Monash University The Alfred Centre, 99 Commercial Rd Melbourne 3004, Victoria, AUSTRALIA Ph: 9903 0555 Fax: 9903 0556 Email: [email protected]
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ACCEPTED MANUSCRIPT Abstract
Population-based studies suggest that pain in the lower body is common, and that pain at multiple sites is more prevalent than single site pain. Obesity is a risk factor for multisite
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musculoskeletal pain, but there are limited data on the role of body composition. Therefore, we determined whether body composition is associated with multisite musculoskeletal pain, involving the lower back, knee and foot. 133 participants were recruited for a study
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examining the relationship between obesity and musculoskeletal disease. Participants completed validated questionnaires which examined levels of pain at the low back, knee
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and foot. Body composition was assessed using dual energy x-ray absorptiometry. Multisite pain was common, with 26.3% of participants reporting pain at two sites, 31.6% at three sites and only 20% were pain free. The lower back was the most common site of pain (63%). Increasing fat mass and fat mass index, but not fat free mass, was associated with pain at a
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greater number of sites, independent of age, gender and fat free mass (p<0.01). Longitudinal studies exploring the mechanism of action by which increased fat mass is
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associated with pain may provide important insight into therapeutic strategies for the
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prevention of multi-site pain.
Running title: Fat mass is associated with multisite pain
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Perspective: Greater fat mass and fat mass index were associated with a greater number of lower body pain sites, with no association observed for fat free mass. Understanding the mechanism by which increased fat mass is associated with pain may provide important
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Key words: Body composition, Fat mass Pain, Epidemiology
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insight into therapeutic strategies for the prevention of pain.
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ACCEPTED MANUSCRIPT Introduction Musculoskeletal pain is an important clinical and public health problem. Although most
studies focus on musculoskeletal pain at a single site, pain in more than one anatomical site
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is common. In a study of 12,410 employed adults across 18 different countries, multisite pain (or pain located at ≥2 sites) was more common than pain located at one site6. Similarly a population-based study of 3179 Norwegian adults found that 53% had multisite pain
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compared to 17% with single site pain19.
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Population-based studies have also suggested that localised musculoskeletal pain (e.g. back or knee pain), are more disabling when accompanied by pain at other sites than when a single site is affected24. Results from cross sectional studies show that there is an almost linear increase in functional problems with increasing number of pain sites19. Moreover, the
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absenteeism13.
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number of pain sites has been shown to be a strong independent predictor of work
Potential risk factors for multisite pain include older age6, 12, female gender6, 9, high physical
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workload6, 14, 29, as well as psychological factors such as somatising tendency6, 29. There is also growing evidence to indicate a role of obesity. For instance, a study of female kitchen workers found obesity (body mass index [BMI] ≥ 30 kg/m2) to be associated with an increased prevalence of multisite musculoskeletal pain14, and a population-based study reported a greater number of pain sites in individuals with higher BMI18. Moreover, in a study of 48 participants, musculoskeletal pain improved in obese subjects after undergoing bariatric surgery at 6 and 12 months post-procedure15. While 100% had lower extremity
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musculoskeletal pain before surgery, only 37% reported pain after weight loss. Similarly, 79% had upper extremity musculoskeletal conditions before surgery and 40% after weight loss15. Given this is a non-weight bearing region, it suggests that the effect of adipose tissue
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on musculoskeletal pain is unlikely to be simply due to physical loading on joints, but rather that fat (or adipose tissue) may also contribute to pain through systemic mechanisms20, 27.
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The emerging evidence suggests that fat and muscle mass have different roles in the
pathogenesis of musculoskeletal disease28. The detrimental effects of adipose tissue on
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musculoskeletal health have previously been reviewed20. In a study of synovial leptin (an adipose tissue-derived hormone), Dumond et al found that leptin was overexpressed in human osteoarthritic knee joints and the level of leptin expression related to the degree of cartilage destruction, suggesting its role in the pathogenesis of OA8. Moreover high synovial
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leptin levels have been associated with high levels of lower limb joint pain21. The role of body composition has only recently been addressed as previous studies have used weight
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and BMI as measures of obesity and these do not allow examination of body composition (muscle and fat mass). However, recent studies have examined body composition and their
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association with pain at single anatomical sites. These studies have found that greater fat mass, but not lean tissue mass, is associated with greater levels of low back pain and disability31, incident foot pain3, and early structural changes at the knee, which are predictors of knee osteoarthritis (cartilage defects, bone marrow lesions and decreased cartilage volume)2, 34. However, few studies to date have assessed the relationship between body composition and pain at multiple sites.
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The aim of this study was to examine the associations between body composition and lower body pain at three sites (lower back, knee and foot). These lower body sites were our focus in the study because of the high prevalence of lower body pain in the general population19, 25
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, and because lower body musculoskeletal pain causes significant disability and burden in
society10, 17. Our hypothesis was that fat mass would be associated with a greater number of
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pain sites in the lower body.
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ACCEPTED MANUSCRIPT Materials and Methods
Participants
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A total of 133 participants, who ranged from normal weight to obese, were recruited through local media and community weight loss clinics to take part in a study of obesity and musculoskeletal health. These participants were not recruited on the basis of having pain.
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All provided informed consent. Exclusion criteria included malignancy or inability to complete the study. The study was approved by the Alfred Human Research Ethics
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Committee (HREC), Monash University HREC, Austin Health HREC, and the University of Melbourne Central HREC.
Data Collection
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Demographic and anthropometric data
Age, gender, weight, and height were recorded. Height was measured using a stadiometer
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and weight measured using a single pair of electronic scales, to the nearest 0.1 kg with
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shoes and bulky clothing removed. BMI (weight ÷ [height2]; kg/m2) was calculated.
Body composition measurement Body composition was measured using dual energy x-ray absorptiometry (DEXA, GE Lunar Prodigy, using operating system version 9; GE Healthcare, United Kingdom), which had a weight limit of approximately 130kg. Standard regional analyses were used to measure total body fat mass as well as total body lean tissue mass. Lean tissue mass was used as a measurement of skeletal muscle mass. Fat mass index (FMI) and fat free mass index (FFMI)
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were calculated as follows: FMI = fat mass/height2 and FFMI = fat free mass / height2, where fat free mass = lean tissue mass + bone mineral content.
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Pain prevalence Data on pain prevalence at the low back, knee and foot was performed using region-specific questionnaires. To examine the prevalence of low back pain, the question “Have you had
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low back pain in the past month?” was used, along with a figure of a mannequin that marked the low back as a squared area between the lower border of the rib cage and the
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gluteal folds. The Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) and Visual Analogue Scale (VAS), validated tools for use in populations with knee pain1, were used for the identification of knee pain. The WOMAC is composed of 24 items divided into 3 subscales, pain, stiffness, and physical function. In this study, only the pain subscale
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knee pain.
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was used. A cut-off of ≥20 on a 0–100-mm VAS was used to determine clinically significant
To establish foot pain prevalence in our study, the Foot pain and Manchester Foot Pain and
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Disability Index (MFPDI) was utilised11, which has been validated in rheumatology patients, patients of general health practitioners who have reported foot-related problems, and people from the general community23. The MFPDI consists of 19 items that are preceded with the phrase, ‘because of pain in my feet,’’ formalized under four categories: functional limitation (10 items), pain intensity (5 items), personal appearance (2 items), and difficulties with work or leisure activities (2 items). Each item is scored according to frequency (e.g. ‘‘none of the time" [0 points], ‘‘on some days" [1 point], or ‘‘on most/everyday" [2 points]);
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subsequently, scores on the MFPDI range between 0 and 38, with higher scores denoting more disabling pain. Using the original definition of foot pain as described by Garrow et al11,
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participants with a score of ≥1 from 19 items were defined as having disabling foot pain.
Multisite lower body pain was defined as musculoskeletal pain arising from two or more anatomical sites involving the low back, knees and feet. This definition was used because
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number of pain sites has been shown to be a useful method of classifying multisite pain and studies have shown that pain in multiple sites differs in its risk factors to localised pain at
site, two sites and pain at three sites).
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one site6. The number of pain sites was classified into four categories (no pain, pain at one
The Short Form 36 (SF-36) questionnaire (mental and physical health component) was used
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Statistical Analysis
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to estimate the overall mental and physical health of the participants22.
Chi squared tests were used for comparison of categorical data for participants with
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different numbers of pain sites. The F test was used to determine the pairwise comparison among the estimated marginal means for continuous data. To examine the relationship between fat mass and number of pain sites, independent of lean tissue mass, the respective fat free mass parameter was included in the multivariate model. Similarly, to examine the relationship between fat free mass and number of pain sites, independent of fat mass, the respective fat mass parameter was included in the multivariate model. Adjustment was also made for potential confounders including age, gender and the mental health component
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score from the SF-36. The statistical analyses were conducted using SPSS Statistics 21.0
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(SPSS Institute, Cary, NC). A p value of less than 0.05 was considered statistically significant.
Results
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The 133 participants recruited for this study were aged between 25 to 62 years with a range of body mass indices (18–55 kg/m2). Three participants were excluded from body
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composition measurements due to the 130kg weight limit of the dual energy x-ray absorptiometry machine. The characteristics of the participants based on the number of pain sites are presented in Table 1. While the mean age (p=0.81) and gender distribution (p=0.89) did not differ according to the number of pain sites, physical health scores, but not
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mental health scores, were significantly lower in those with pain compared to those without pain (p<0.01). In terms of obesity measures, elevated weight and BMI were associated with
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a greater number of pain sites (p<0.01).
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ACCEPTED MANUSCRIPT Table 1: Participant characteristics according to the number of pain sites (n=133)
Physical health component
score (SF-36) Mental health component
score (SF-36)
Pain at 2
Pain at 3
P
(n=27)
site (n=29)
sites (n=35)
sites (n=42)
value
46.3
48.8
47.7
47.9
0.81
(42.8 - 50.0)
(45.3 - 52.2)
(44.6 - 50.8)
(45.0 - 50.7)
20 (74.1)
24 (82.8)
27 (77.1)
33 (78.6)
0.89
54.7
52.8
47.8
41.9
<0.01
(51.3 - 58.0)
(49.6 - 55.9)
48.3
50.7
(43.1 - 53.5)
Foot pain, n (%) a
0.31
95.3
98.4
(73.3 - 89.9)
(87.8 - 102.8)
(91.5 - 105.3)
28.4
29.8
34.6
36.6
(25.2 - 31.6)
(26.8 - 32.9)
(31.8 - 37.4)
(34.1 - 39.2)
0
16 (55.2)
26 (74.3)
42 (100)
N/A
0
7 (24.1)
16 (45.7)
42 (100)
N/A
0
6 (20.7)
28 (80)
42 (100)
N/A
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Knee pain, n (%)
44.9
81.6
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Back pain, n (%)
46.1
(40.8 - 48.9)
(68.3 - 85.5)
Pain characteristics
(39.2 – 44.5)
(41.7 - 50.6)
76.9
BMI (kg/m2)
(45.0 - 50.7)
(45.8–55.6)
Measures of obesity Weight (kg)
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Female, n (%)
Pain at 1
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Age (years)
No pain
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Characteristics a
All continuous variables are expressed as mean (95% confidence interval).
Abbreviations: BMI, Body mass index
<0.01
<0.01
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Total n=133 No pain n=27 (20.3%)
Knee pain (n=7)
Total at three sites n= 42 (31.6%)
n=42 Back pain (n=16)
Foot pain (n=6)
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Total at two sites n = 35 (26.3%)
n=9
n=7
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Total at one site n = 29 (21.8%)
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(Total = 65, 49%)
n=19
(Total = 76, 57%)
(Total = 84, 63%)
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Figure 1: Pain experienced by study population
The location of pain experienced by the participants is presented in Figure 1 and Table 1. In
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the study population, 27 (20.3%) people were pain free and of the 29 (21.8%) people who
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had pain at one site alone, back pain contributed 55.2%, followed by knee pain in 24.1%. In the 35 (26.3%) people who had pain in two areas, the back and feet were most commonly reported (54.3%). There were 42 participants who had pain at all three sites, comprising 31.6% of the study population. The lower back was the most common site of pain overall, with 63% of the participants having back pain, followed by foot pain (57%) and knee pain (49%). Multi-site pain was common, with 57.9% of participants suffering from pain in two or three anatomical sites. 106 (79.7%) had pain in at least one site (comprising back, knee or foot).
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The relationship between both BMI and body composition measures and the number of pain sites is presented in Table 2. In both the crude and adjusted analysis, there was an
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increase in fat mass and fat mass index as the number of pain sites increased (p<0.01). Fat free mass index was also increased in both crude analyses and when adjusted for age and gender (p=0.04). However, when fat mass index was added to the model, the association
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did not remain significant (p=0.56). When analyses were repeated with mental health component score from the SF-36 questionnaire added to the model, both the fat mass index
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and fat mass association were still significant (p< 0.01, data not shown).
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ACCEPTED MANUSCRIPT Table 2: Association between the number of pain sites and body mass index (BMI) and body composition
Measures of obesity No pain and body composition a (n=27)
Pain at one Pain at 2 Pain at 3 P site (n=29) sites (n=35) sites (n=42) value
Unadjusted analysis Body mass index (kg/m2)
<0.01
28.4 29.9 34.5 36.6 (25.2 – 31.5) (26.8 – 32.9) (31.8 – 37.3) (34.1 – 39.2) Fat mass (kg) 26.9 32.0 41.2 43.9 (20.9 - 33.0) (26.3 - 37.7) (36.0 - 46.4) (39.0 - 48.7) Fat mass index 10.0 11.7 15.1 16.6 (7.7 – 12.4) (9.5 – 13.9) (13.1 – 17.1) (14.7 – 18.5) Fat free mass (kg) 47.2 48.8 53.5 50.8 (43.2 – 51.2) (45.1 – 52.6) (50.1 – 56.9) (47.6 – 54.0) Fat free mass index 17.4 17.8 19.2 18.8 (16.4 – 18.5) (16.8 – 18.8) (18.3 – 20.1) (17.9 – 19.6) Adjusted for age, gender and respective body composition measure (fat or fat free mass)
<0.01
Fat mass (kg)
<0.01b
Fat free mass (kg) Fat free mass index Adjusted for age and gender
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Body mass index (kg/m2)
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Fat mass index
34.6 (31.8 - 37.4) 41.2 (36.0 - 46.4) 15.1 (13.1 - 17.1) 53.5 (50.1 - 56.9) 19.2 (18.2 - 20.1)
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36.6 (34.1 - 39.2) 43.9 (39.0 - 48.7) 16.6 (14.7 - 18.5) 50.8 (47.6 - 54.0) 18.8 (17.9 - 19. 6)
Fat mass (kg)
29.8 (26.8 - 32.9) 32.1 (26.4 - 37.8) 11.8 (9.5 - 14.0) 48.8 (45.1 - 52.5) 17.8 (16.8 - 18.8)
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28.4 (25.2 - 31.6) 26.9 (20.9 - 32.9) 10.0 (7.6 - 12.3) 47.2 (43.3 - 51.2) 17.4 (16.3 - 18.4)
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28.2 32.6 40.0 (22.2 - 34.1) (27.0 - 38.2) (34.9 – 45.2) Fat mass index 11.0 12.3 14.4 (8.8 – 13.1) (10.2 – 14.3) (12.5 – 16.2) Fat free mass (kg) 48.9 49.7 52.8 (44.9 – 52.9) (46.0 – 53.4) (49.5 – 56.2) Fat free mass index 18.1 18.2 18.9 (17.1 – 19.2) (17.3 – 19.1) (18.1 – 19.7) a All continuous variables are expressed as mean (95% confidence interval). b Fat free mass/index added to the model c Fat mass/index added to the model
43.7 (39.0 – 48.4) 16.2 (14.5 – 17.9) 49.7 (46.5 – 52.9) 18.2 (17.4 – 19.0)
<0.01 <0.01 0.09 0.04
<0.01 <0.01 0.09 0.04
<0.01b 0.40c 0.56c
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ACCEPTED MANUSCRIPT Discussion
In our study of community-based adults, multisite lower body pain was common with 58%
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of participants having pain in two or three anatomical sites. The lower back was the most common site of lower body pain, followed by the feet and knees. Greater weight, BMI, fat mass and fat mass index were all associated with an increased number of lower body pain
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sites, with no association observed for fat free mass or fat free mass index. The findings suggest that one possible mechanism for the relationship between fat mass and multisite
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lower body pain may be via systemic metabolic factors associated with having excess adipose tissue. If lower body pain was simply related to physical loading on anatomical structures, then we would have expected to see the same relationship with fat free mass.
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The high prevalence of multisite lower body pain seen in our study is consistent with previous studies that have examined sites over the whole body. In a study of 12,410 working
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adults aged 20–59 years across 18 countries, 41% of people reported pain located in at least two sites out of the six anatomical regions assessed (low back, neck, shoulder, elbow,
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wrist/hand and knee)6. Pain was most frequently seen in the low back (36%), which is consistent with our findings. Our results are also consistent with a population based UK study of 2445 adults, which showed that more people had chronic pain in two or more sites (73%) than at a single site (27%)4. Similarly a population-based Norwegian study of 3179 patients (aged 24 to 76 years) found that 53% of patients had multisite pain in comparison to 17% who had single site pain. In this study there were 10 regions assessed including head,
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neck, shoulder, elbow, hand/wrist, upper back, lower back, hip, knee, and ankle/foot with the neck (36%) and low back (34%) being the most common sites19.
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Our study found that having a BMI greater than 30 kg/m2 was associated with having pain at multiple sites in the lower body. This is consistent with Yoo et al who demonstrated that widespread pain was associated with high fat:muscle mass ratios, particularly in women35.
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Similarly, Haukka et al found that obesity (BMI ≥30 kg/m2) in Finnish female kitchen workers was associated with an increased prevalence of multisite musculoskeletal pain14 and
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Kamaleri et al also found that a greater number of pain sites were reported in individuals with higher BMI18. While the relationship between measurements of body composition, specifically fat mass and fat mass index, with number of lower body pain sites has not been examined before, previous studies have recognized the association of fat mass with pain at
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single sites only3, 31. Recently our group has reported that greater fat mass, but not lean tissue mass, is associated with greater levels of low back pain and disability31, prevalent and
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incident foot pain3, 30, and cartilage defects, bone marrow lesions and decreased cartilage
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volume in the knee2, 34.
Although it is recognized that obesity is a risk factor for musculoskeletal disease, the evidence is accumulating to support that this is not simply through physical loading but rather via systemic mechanisms. This was recognized in studies that showed obesity is a risk factor for hand osteoarthritis which is a non-weight bearing joint5. The current study provides further support for a systemic effect of obesity on the risk of lower limb multisite pain as we found that fat mass, rather than fat free mass, was associated with multisite pain.
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If the mechanism was simply physical loading, then we would have expected to see the same relationship with fat mass and fat free mass. Adipose tissue is metabolically active and has even been labelled an endocrine organ because it releases such a large number of
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substances including cytokines, such as interleukin 1 and tumour necrosis factor alpha, as well as adipokines, such as leptin, adiponectin and resistin26,
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. These inflammatory
mediators have been shown to affect both joint structures contributing to structural
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abnormalities8, but also to have a role in nociceptive pathways21 and in the development
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and progression of chronic pain7, 32.
A limitation of this study is that it is cross-sectional so the results will need to be confirmed with a longitudinal study. Although we had a modest sample size, all participants had body composition measured using DEXA, which is costly and difficult to perform on large samples.
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Moreover, this sample size provided adequate power to detect significant relationships using independent measures of fat mass. Although the quality of the data on pain depends
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on the willingness of the participants to answer questionnaires, these measures were completed using either validated tools or questions that have been used in numerous
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population-based studies in the field16. While this study focuses on the presence of pain at multiple sites, exploring the severity and chronicity of pain and its functional impact across multiple sites is a potential area for future investigation. While we investigated lower back, foot and knee pain in this study, hip pain was not included. Further investigation is needed to determine whether including other regions of the lower limb such as the hip alters our findings. Given hip pain is not as common as the other three sites we examined, and obesity, including fat mass, is also a risk factor for hip OA33, we hypothesise that our results will
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similar if the upper body is examined. Potential strengths of our study was that we adjusted for confounders such as age, sex as well as fat and fat free mass, which are known to have a
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collinear relationship. We also used unique measures of body composition and identified significant associations with number of pain sites. Additionally, we used a community based sample of participants who were not recruited on the basis of having pain and the region we
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assessed was the lower body, which allowed us to specifically address sites that work as one
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functional unit of mobility.
In community-based adults, increased fat mass, but not fat free mass, was associated with a greater number of sites of pain in the lower body. Understanding the mechanism of action by which increased fat mass is associated with pain may provide important insight into
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therapeutic strategies for the prevention of pain. Longitudinal studies assessing a wide range of pain sites in the body may help confirm these associations and determine whether
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fat mass is predictive of pain at other non-weight bearing sites. This may have important implications for future prevention strategies which could be focussed towards reducing fat
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mass and may assist in reducing the significant burden of multisite pain in the community.
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ACCEPTED MANUSCRIPT Highlights Pain at multiple sites is common; the impact of body composition is unclear.
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We examined the association between body composition and pain at three sites.
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Dual energy x-ray absorptiometry was used to assess body composition.
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Multisite pain was common, with the most frequent site being the lower back.
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Greater fat mass was associated with an increased number of lower body pain sites.
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