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. Author manuscript; available in PMC: 2013 Jan 1.
Published in final edited form as: J Pain. 2012 Jan;13(1):64–72. doi: 10.1016/j.jpain.2011.10.007

Predictors of Change in Pain and Physical Functioning among Post-Menopausal Women with Recurrent Pain Conditions in the Women’s Health Initiative Observational Cohort

Jennifer Brennan Braden *, Alicia Young †, Mark D Sullivan *, Brian Walitt ±, Andrea Z LaCroix †,§, Lisa Martin ||
PMCID: PMC3249604  NIHMSID: NIHMS336318  PMID: 22208802

Abstract

Pain complaints are commonly reported symptoms among postmenopausal women and can have significant effects on health-related quality of life. We sought to identify medical and psychosocial factors that predict changes in pain and overall physical functioning over a three-year period among post-menopausal women with recurrent pain conditions. We examined data from postmenopausal women age 50–79 with recurrent pain conditions (low back pain, neck pain, headache or migraines, or joint pain or stiffness) over a three-year period using the Women’s Health Initiative Observational Study Cohort (N=67,963). Multinomial logistic regression models controlling for demographic and clinical characteristics were used to identify baseline predictors of change in the SF-36 subscales for pain and physical functioning between baseline and three year follow-up. BMI was associated with worsening of pain (OR [95% CI] 1.54 [1.45–1.63] for BMI ≥30) and physical functioning (1.83 [1.71–1.95] for BMI≥30). A higher reported number of non-pain symptoms, higher medical comorbidity and a positive screen for depression (1.13 [1.05–1.22] for worsened pain) were also associated with worsening of pain and physical functioning. Baseline prescription opioid use was also associated with lack of improvement in pain (OR 0.42, 95% CI 0.36–0.49) and with worsened physical functioning (1.25 [1.04–1.51]).

Keywords: pain, opioid, women, longitudinal cohort, obesity

Introduction

The prevalence of persistent pain complaints is higher among women than among men and increases with age7,47,53. Pain complaints are commonly reported symptoms among women in midlife and later9,20,24,25 and along with other complaints such as vasomotor symptoms, depression and sleep disturbance, can have significant effects on health-related quality of life3,18,52. For example, approximately half of perimenopausal or post-menopausal women age 45 to 50 in the Australian Longitudinal Study on Women’s Health endorsed back pain, headaches or joint pain9. In both the Penn Ovarian Aging Study and the Study of Women’s Health Across the Nation (SWAN), approximately three-fourths of women endorsed joint pain or stiffness20,24. In the SWAN study, approximately one quarter reported these symptoms as moderate to severe intensity. While headaches have been reported to decrease in the transition to menopause24, joint pain tends to increase20,25. This finding is consistent with surveys of older adults (men and women), where about half report experiencing joint pain compared to one-quarter to one-third of younger adults7,40.

Psychological symptoms have been associated with persistent pain. Depression has been shown to both precede and follow the development of pain19,42, and the co-occurrence of depression and pain is associated with worse physical and emotional functioning in cross-sectional studies2,7,8. Depression has been reported to be positively associated with higher subjective levels of pain interference both in the broader pain population2,8 and in menopausal women specifically49. Anger and hostility have been associated with poor pain treatment outcomes, and ambivalence over emotional expression (AEE), the tendency to be conflicted about expressing one’s emotions, may be linked to increased pain11,13,22,36. In a recent study of chronic low back pain patients, patients scoring high on AEE were much more likely to report higher pain on the affective and evaluative pain scales of the McGill Pain Questionnaire13. In a longitudinal study of 169 continuing care retirement community residents, the percent with any pain increased 6.5% over the 24-month period; the percent with pain without activity limitations remained relatively stable, but the percent with pain with activity limitations increased from 35.5 to 42.2%39. Psychiatric comorbidity, poor pain coping behaviors, high baseline functional impairment and low general health status have been shown to be predictive of persistent disabling back pain one year later among those with fewer than eight weeks of low back pain15. Little is known, however, about the longitudinal course and modifiers of pain in the general population or in postmenopausal women specifically.

In this study, we sought to identify psychosocial, demographic and clinical factors that predict changes in pain and overall physical functioning over a three-year period among post-menopausal women with recurrent pain conditions using data from the Women’s Health Initiative Observational Cohort. The subpopulation of patients with non-cancer pain receiving opioid therapy is of special interest, given the marked increase in use of these drugs for non-cancer pain over the past 30 years. Individuals with depression are more likely to be prescribed opioids for non-cancer pain than those without depression6,21,48, and post-menopausal women may be more likely to receive opioids than younger women for non-cancer pain given the health risks associated with COX-2 inhibitors and non-sterioidal anti-inflammatory drugs1,12. Hence, we included use of regular prescription opioids as one of the clinical factors examined in our study.

Materials and Methods

Population

Data are from the Women’s Health Initiative Observational Study Cohort. The Women’s Health Initiative is a national health study consisting of a set of randomized controlled trials and an observational study. The Observational Study Cohort followed 93,676 postmenopausal women age 50–79 for a period of eight to 12 years starting in 1998. Women were eligible if they were age 50–79, postmenopausal, had ability and willingness to provide written informed consent, and intention to reside in the area for at least three years. Women were excluded if they had a medical condition with predicted survival of less than three years, or mental disorders that might interfere with adherence or retention in the study (assessed by asking potential study participants, “Are there any reasons, like serious emotional problems, mental illness, or too much stress, that would make it hard for you to be in a research study?”). Women screened for participation in the clinical trials but unwilling or ineligible (i.e. because of the presence of a health condition that was a competing risk factor or safety concern for trial outcomes), were offered the opportunity to participate in the Observational Study Cohort. Participants completed questionnaires and provided blood specimens and physical measurements at the baseline screening visit and returned for a second visit three years later. Informed consent from each participant was obtained, and human subjects review committees at each participating institution approved the study. Analyses for this study were limited to the subset of women in the Observational Study Cohort with “recurrent pain,” defined as endorsing low back pain, neck pain, headache or migraines, or joint pain or stiffness in the prior four weeks at both the baseline and three-year follow-up visits (N=67,963). Details about the design of the WHI can be found elsewhere30,43.

Variables

Participants were asked to indicate the presence and severity of 34 symptoms of distress (scale of 0=symptom did not occur to 3=severe) in the prior four weeks at baseline and follow-up visits. The list of symptoms was obtained from the Postmenopausal Estrogen/Progestin Intervention study and from other national health surveys. Those who responded ≥1 for low back pain, neck pain, headache/migraine, or joint pain/stiffness at both baseline and follow-up visits were defined as having recurrent pain. Responses to the other items were summed to create a measure of the number of non-pain symptoms. Pain severity and pain interference in the prior four weeks were assessed via a Likert scale (pain severity: 0=none to 5=severe; pain interference: 1=not at all to 5=extremely) using questions from the Short Form (SF)-3655, and averaged to create one pain score (i.e. the SF-36 pain subscale). Physical functioning was assessed using the physical functioning subscale of the SF-36. Scores were converted to a scale ranging from 0 and 100, with a higher score indicating a more favorable health state. Changes in pain and physical functioning were determined by subtracting the numerical score at baseline from that at year three for each respondent. For the sake of clarity, moving to a more favorable health state between baseline and year 3 (i.e., decrease in pain, increase in physical functioning) was defined as “improved” and moving to a less favorable health state between baseline and year 3 (i.e., increase in pain, decrease in physical functioning) was defined as “worsened.” Medical comorbidity was assessed with the Charlson comorbidity index14. Hours per day of sedentary activity was obtained by self report and defined as hours sleeping, sitting or lying down. Participants were asked about use of medications for two weeks or more, along with duration of use. Opioid use was defined as use of DEA Schedule II-V prescription opioids. Other analgesic use was defined as use of acetaminophen, ibuprofen and other non-steroidal anti-inflammatories, aspirin, salicylate analgesics, other aspirin like analgesics, lidocaine and capsaicin creams. Use of hormone replacement therapy (HT) was assessed by a series of questions about use of hormone medications for relief of menopausal symptoms, following hysterectomy with removal of the ovaries, or for prevention of disease such as bone loss. Body mass index (BMI) was calculated from height and weight measurements obtained at the baseline visit (weight in kilograms/height in meters2). For analysis purposes, BMI was divided into three categories to correspond with normal, overweight and obese: <25, 25–<30, ≥30. Demographic characteristics and disability status were obtained by self report.

Depression was assessed with the Burman scale10, a shortened form of the CES-D that has been validated in a large study of office-based practices. Respondents with scores ≥0.06 were considered to be depressed. Social support was assessed by nine questions from the Medical Outcomes Study45. Possible scores ranged from 9–45, with a higher score indicating greater support. The Ambivalence Over Emotional Expression Questionnaire was used to assess the relationship between negative emotion and health outcomes35. The questionnaire consists of three items (e.g. after I express anger at someone, it bothers me for a long time); possible scores range from 1–5, with higher scores indicating greater ambivalence in expressing negative emotions. Cynicism was measured using the 13-item cynicism subscale of the Cook-Medley Hostility Questionnaire (example items: no one cares much what happens to you; I think most people would lie to get ahead); possible scores ranged from 0–13, with higher scores indicating greater cynicism5.

Statistical Analyses

Demographic and clinical variables were analyzed descriptively using frequencies and percents for categorical variables and means with standard deviations for continuous variables, stratified by change in pain between baseline and year 3 (no change, worsened, improved pain). Chi-square tests were performed for categorical variables, and one-way ANOVA tests were performed for continuous variables to assess differences among groups. Multinomial logistic regression models were used to identify predictors of change in pain and physical functioning between baseline and three year follow-up, while controlling for demographic (age at screening, highest education level, family income, employment status-disabled, race/ethnicity) and clinical characteristics (BMI, Charlson index, number of non-pain symptoms, HT use, baseline pain or physical functioning) at baseline. Specifically, the models examined the association between the independent variables and 1) increase in pain (i.e. worsening) versus no change in pain 2) decrease in pain (i.e. improvement) versus no change in pain 3) increase in physical functioning (i.e. improvement) versus no change in physical functioning and 4) decrease in physical functioning (i.e. worsening) versus no change in physical functioning) between baseline and year 3. Independent variables in the regression models included opioid use, the presence of depression, ambivalence over emotional expressiveness, hostility, social support, and hours of sedentary activity per day. Data from participants with missing values for one or more covariates in the models was excluded from the regression analyses, leaving a total of 51839 participants for the model with outcome change in pain and 50849 for the model with outcome change in physical functioning.

Results

Of the 93,676 women enrolled in the WHI OS, 67963 met the criteria for recurrent pain and were included in the analyses for this study. An additional 9774 reported pain at baseline and were missing the pain measures at Year 3, and another 4584 reported pain at baseline and not at Year 3.

Sociodemographic and Clinical Characteristics

Table 1 presents the demographic and clinical characteristics of the cohort with recurrent pain, stratified by whether they experienced a worsening, improvement or no change in pain between baseline and year 3. In general, the women were primarily White, had at least a high school diploma, an annual family income >$35,000, a mean age of 63–64 years, and a mean BMI in the overweight range. The majority of the women reported at least mild joint pain or stiffness; the next most common pain condition reported was low back pain. Most women (56017 [82%]) reported more than one pain type. Mean baseline scores for pain and physical functioning were higher among those reporting no change or worsened pain between baseline and year 3. Nearly half of the women (43.9%, n=29,721) reported use of a non-opioid analgesic. 4.3% (2914) reported prescription opioid use: 2.3% (1582) at baseline, 2.0% (1332) at year 3 only and 0.9% (615) at baseline and year 3. Most women with baseline opioid use had use for >90 days (83%, n=1325). The median duration of those reporting opioid use at baseline was 2 years, and at year 3 was 1.5 years. Approximately 11% of women screened positive for depression on the Burman (shortened CES-D) scale (score≥0.06); average scores for ambivalence over emotional expressiveness and cynicism were low, and for social support were high.

Table 1.

Sociodemographic and Clinical Characteristics at Baseline of Post-Menopausal Women with Recurrent Pain Conditions 3-Years Later

Change in Pain Baseline to 3-Year Follow-Up
Characteristics Improved (N=20742) None (N=20163) Worsened (N=26647) P-value
Sociodemographic
Age at screening, mean (SD) 63 (7.3) 63 (7.2) 64 (7.3) < 0.001
Racial/ethnic group, N (%)
 White 17542 (84.6%) 17447 (86.5%) 22749 (85.4%) < 0.001
 Black 1524 (7.3%) 1276 (6.3%) 1909 (7.2%)
 Hispanic 759 (3.7%) 550 (2.7%) 838 (3.1%)
 American Indian 90 (0.4%) 59 (0.3%) 112 (0.4%)
 Asian/Pacific Islander 538 (2.6%) 578 (2.9%) 671 (2.5%)
 Unknown 289 (1.4%) 253 (1.3%) 368 (1.4%)
Highest education level
 0–8 years 314 (1.5%) 175 (0.9%) 380 (1.4%) < 0.001
 Some high school 704 (3.4%) 545 (2.7%) 923 (3.5%)
 High school diploma/GED 3279 (15.8%) 3183 (15.8%) 4532 (17.0%)
 School after high school 7708 (37.2%) 7213 (35.8%) 9972 (37.4%)
 College degree or higher 8569 (41.3%) 8907 (44.2%) 10635 (39.9%)
Total family income*
 < $10,000 781 (3.8%) 617 (3.1%) 1053 (4.0%) < 0.001
 $10,000 – $19,999 2229 (10.7%) 1907 (9.5%) 2997 (11.2%)
 $20,000 – $34,999 4583 (22.1%) 4143 (20.5%) 6113 (22.9%)
 $35,000 – $49,999 3863 (18.6%) 3866 (19.2%) 5085 (19.1%)
 $50,000 – $74,999 3962 (19.1%) 4045 (20.1%) 4981 (18.7%)
 $75,000 + 3898 (18.8%) 4266 (21.2%) 4645 (17.4%)
Disabled 564 (2.7%) 374 (1.9%) 516 (1.9%) < 0.001
Recurrent pain and other medical conditions
Joint pain or stiffness
 Severe 2221 (10.7%) 992 (4.9%) 1286 (4.8%) < 0.001
 Moderate 6031 (29.1%) 3592 (17.8%) 5773 (21.7%)
 Mild 9386 (45.3%) 11345 (56.3%) 14522 (54.5%)
Low back pain
 Severe 1880 (9.1%) 891 (4.4%) 1094 (4.1%) < 0.001
 Moderate 4663 (22.5%) 2761 (13.7%) 4566 (17.1%)
 Mild 7286 (35.1%) 8293 (41.1%) 10831 (40.6%)
Neck pain
 Severe 1091 (5.3%) 520 (2.6%) 753 (2.8%) < 0.001
 Moderate 3380 (16.3%) 2242 (11.1%) 3252 (12.2%)
 Mild 6454 (31.1%) 6757 (33.5%) 9118 (34.2%)
Migraines or headaches
 Severe 773 (3.7%) 435 (2.2%) 565 (2.1%) < 0.001
 Moderate 2448 (11.8%) 1726 (8.6%) 2576 (9.7%)
 Mild 7495 (36.1%) 8062 (40.0%) 10460 (39.3%)
Charlson index (mean [SD]) 0.8 (1.1) 0.7 (1.0) 0.8 (1.1) < 0.001
Number of non-pain medical conditions (mean [SD]) 9.2 (4.7) 8.4 (4.5) 9.1 (4.6) < 0.001
BMI (mean[SD]) 27.5 (5.9) 26.8 (5.6) 27.7 (6) <0.001
Sedentary activity, hours per day (mean [SD])‡ 15.2 (4.2) 15.2 (4) 15.1 (4.1) 0.153
Pain, mean (SD)§ 56 (22.7) 77 (21.3) 79 (19.1) < 0.001
Physical functioning, mean (SD) § 76.7 (21.7) 83.2 (19.3) 80.3 (19.4) < 0.001
BASELINE medication use
Opioid use 634 (3.1%) 405 (2.0%) 542 (2.0%) < 0.001
Other analgesic use|| 9675 (46.6%) 8418 (41.7%) 11603 (43.5%) < 0.001
HRT use 9730 (46.9%) 9548 (47.4%) 12504 (46.9%) 0.789
Psychosocial
Depressed† (≥ 0.06 on shortened CES-D scale) 2677 (12.9%) 1887 (9.4%) 3097 (11.6%) < 0.001
Ambivalence over emotional expressiveness, mean (SD) 3.0 (0.7) 3.0 (0.7) 3.0 (0.7) < 0.001
Cynicism**, mean (SD) 3.8 (2.8) 3.5 (2.7) 3.8 (2.8) < 0.001
Social support††, mean (SD) 35.8 (7.8) 36.5 (7.5) 35.6 (7.8) < 0.001
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*

6–7% missing

†

1–3% missing

‡

Hours sleeping, sitting or lying down

§

From the SF-36, possible scores range from 0–100, higher scores indicate better health/functioning

||

Use of acetaminophen, ibuprofen and other non-steroidal anti-inflammatories, aspirin, salicylate analgesics, other aspirin like analgesics, lidocaine and capsaicin creams

Possible scores range from 1–5, higher scores indicating greater ambivalence in expressing negative emotions

**

Possible scores range from 0–13, higher scores indicating greater cynicism

††

Possible scores range from 9–45, higher scores indicating greater support

Women with any prescription opioid use at baseline differed from women with no opioid use at baseline on all variables examined. They tended to have worse pain scores (mean [SD] 41 [25.2] vs. 72.6 [22.6].), a higher number of non-pain medical conditions (11 [5.2] vs. 8.9 [4.6]), a higher Charlson score (1.3 [1.4] vs. 0.8 [1.1]), lower physical functioning (56.8 [26.7] vs. 80.6 [19.7]), slightly higher BMI (29.5 [6.9] vs. 27.3 [5.8]), were more likely to be disabled (13.5% vs. 1.9%) and were more likely to screen positive for depression (20.5% vs. 11.1%) (p<0.001 for all differences noted). Women with baseline opioid use also were more likely to report having each of the four pain symptoms examined in our study than those without baseline opioid use. The most common pain type reported by those with baseline opioid use was low back pain (80.6%, n=1272).

Logistic Regression Models

Tables 2 and 3 present results from multinomial logistic regression models examining variables associated with change in pain and physical functioning between baseline and year 3 among women with recurrent pain conditions. The effect size of many of the covariates tended to be small, particularly for the psychosocial variables other than depression.

Table 2.

Multinomial Logistic Regression Models*: Change in Pain† Among Post-Menopausal Women with Recurrent Pain Conditions

Independent Variables‡ Change Between Baseline and Year 3
Improved vs No Change Worsened vs No Change
Odds Ratio (95% CI) P-value Odds Ratio (95% CI) P-value
Depressed: ≥ 0.06 vs < 0.06 on shortened CES-D 0.91 (0.84, 0.99) 0.031 1.13 (1.05, 1.22) 0.001
Physical activity: +1 hour/day sitting or lying down 1.00 (0.99, 1.01) 0.880 1.00 (1.00, 1.01) 0.603
Ambivalence over emotional expressiveness construct (+1 unit) 1.00 (0.97, 1.04) 0.807 1.01 (0.98, 1.04) 0.716
Cynicism construct (+ 1 unit) 1.01 (1.00, 1.02) 0.108 1.01 (1.00, 1.02) 0.146
Social support construct (+1 unit) 1.00 (1.00, 1.01) 0.214 0.99 (0.99, 0.99) <.001
Disabled 0.37 (0.31, 0.44) <.001 1.03 (0.87, 1.23) 0.705
Charlson index (+1 unit) 0.97 (0.94, 0.99) 0.004 1.06 (1.04, 1.08) <.001
Baseline hormone replacement therapy use 0.92 (0.87, 0.96) <.001 1.15 (1.10, 1.20) <.001
BMI: 25 – < 30 vs < 25 0.99 (0.94, 1.05) 0.786 1.20 (1.14, 1.26) <.001
BMI: ≥30 vs <25 0.80 (0.75, 0.85) <.001 1.54 (1.45, 1.63) <.001
Number of non-pain symptoms (+1 unit) 0.97 (0.96, 0.97) <.001 1.04 (1.03, 1.04) <.001
Baseline opioid use vs no baseline opioid use 0.42 (0.36, 0.49) <.001 1.13 (0.97, 1.32) 0.127
Baseline pain severity (+1 unit) 0.95 (0.95, 0.95) <.001 1.01 (1.01, 1.02) <.001
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*

Adjusted for age at screening, highest education level, family income, employment status-disabled, race/ethnicity

†

Based on scores from SF-36 pain subscale

‡

All variables from baseline interview

Table 3.

Multinomial Logistic Regression Models*: Change in Physical Functioning† Among Post-Menopausal Women with Recurrent Pain Conditions

Independent Variables‡ Change Between Baseline and Year 3
Improved vs No Change Worsened vs No Change
Odds Ratio (95% CI) P-value Odds Ratio (95% CI) P-value
Depressed: ≥ 0.06 vs < 0.06 on shortened CES-D 0.99 (0.90, 1.08) 0.781 1.10 (1.01, 1.19) 0.028
Physical activity: +1 hour/day sitting or lying down 0.99 (0.99, 1.00) 0.082 1.01 (1.00, 1.02) 0.002
Ambivalence over emotional expressiveness construct (+1 unit) 1.06 (1.02, 1.10) 0.004 1.05 (1.02, 1.08) 0.004
Cynicism construct (+ 1 unit) 1.00 (0.99, 1.01) 0.961 1.00 (0.99, 1.01) 0.961
Social support construct (+1 unit) 1.00 (1.00, 1.00) 0.513 0.99 (0.99, 0.99) <.001
Disabled 0.39 (0.31, 0.49) <.001 0.71 (0.57, 0.87) 0.001
Charlson index (+1 unit) 0.94 (0.92, 0.97) <.001 1.05 (1.03, 1.08) <.001
Baseline hormone replacement therapy use 1.02 (0.97, 1.08) 0.393 1.10 (1.05, 1.15) <.001
BMI: 25 – <30 vs <25 1.07 (1.01, 1.14) 0.018 1.32 (1.25, 1.39) <.001
BMI: ≥30 vs <25 0.99 (0.92, 1.06) 0.747 1.83 (1.71, 1.95) <.001
Number of non-pain symptoms (+1) 1.00 (1.00, 1.01) 0.351 1.03 (1.03, 1.04) <.001
Baseline opioid use only vs no baseline opioid use 0.88 (0.72, 1.08) 0.236 1.25 (1.04, 1.51) 0.020
Baseline physical functioning (+1 unit) 0.99 (0.98, 0.99) <.001 0.95 (0.95, 0.95) <.001
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*

Adjusted for age at screening, highest education level, family income, employment status-disabled, race/ethnicity

†

Based on scores from SF-36 physical functioning subscale

‡

All variables from baseline interview

Table 2: Change in Pain

Baseline opioid use (OR [95% CI] 0.42 (0.36, 0.49), p<.001; and being disabled at baseline (0.37 (0.31, 0.44) were strongly associated with a lack of improvement (i.e. decreased odds of improvement vs. no change) in pain. BMI ≥30 vs. <25 (1.54 (1.45,1.63) was strongly associated with a worsening in pain.

A positive screen for depression, baseline hormone therapy use, higher Charlson index score, and higher number of non-pain symptoms were all associated with lack of improvement and worsening of pain between baseline and year 3. More social support was associated with decreased likelihood of worsening of pain. We also ran the regression model including the different pain types (i.e. joint pain or stiffness, low back pain, neck pain, migraine or headaches) as additional covariates. We did this as a sensitivity analysis to rule out potential confounding of the results for baseline opioid use by responsiveness of pain type to prescription opioid treatment. Results for the model were not significantly changed by this addition. All of the pain types were associated with worse pain and lack of improvement between baseline and year 3, with the exception that migraines or headaches were not significantly associated with worsening of pain.

Table 3: Change in Physical Functioning

BMI ≥30 vs. <25 (OR [95% CI] 1.83 [1.71–1.95]) was strongly associated with worsened physical functioning between baseline and year 3. Being disabled at baseline was strongly associated with lack of improvement in physical functioning (0.39 [0.31, 0.49]). A positive screen for depression, increased hours of sedentary activity per day, higher ambivalence over emotional expressiveness score, baseline hormone therapy use, higher Charlson index score, higher number of non-pain symptoms, and baseline opioid use were associated with a worsening of physical functioning between baseline and year 3. More social support was associated with decreased likelihood of worsened physical functioning.

Discussion

In this longitudinal study of 67,963 postmenopausal women with recurrent pain, we examined demographic, medical, and psychosocial variables associated with change in pain and physical functioning over three years of follow up. To the best of our knowledge this is the largest prospective observational study to look at factors associated with change in pain. Previous prospective studies have focused primarily on recovery after acute trauma or injury17,44,46. In our study, recurrent pain was very common among study participants, endorsed by nearly three-fourths. This is consistent with prior studies reporting the prevalence of pain complaints among postmenopausal women9,20,24, and extends these findings by demonstrating the recurrence of pain over a several year period in this population. Almost 40% of the women in our study reported worse pain at year 3 compared to baseline. BMI in the overweight or obese range (≥25) was associated with worsened pain and physical functioning at year 3 and the associations were greatest in those with BMI ≥30. Prior cross-sectional studies have demonstrated an association between chronic pain and obesity32,37,50,56 and prospective studies suggest that overweight/obesity early in life is a risk factor for development of pain33. In the Longitudinal Aging Amsterdam Study, adults age 55–85 years in the highest quartile of BMI had a twofold increased odds for incident pain after 3 years of follow-up31. Our study results are consistent with these findings and add to them by suggesting that elevated BMI also is associated with worsening of pre-existing pain conditions over time.

Even after controlling for baseline pain, pain type and depression, women reporting prescription opioid use at baseline were more likely to report lack of improvement in pain and worsened physical functioning three years later. It is possible that the women reporting prescription opioid use had pain that was both more severe and more difficult to treat. Nearly all the women in our study with baseline opioid use reported use for 90 days or longer, suggesting they were receiving chronic opioid therapy for a chronic pain condition. Meta-analyses have shown opioids to be more effective that placebo for treatment of chronic pain over 12 weeks of therapy26, but there are no controlled trials that examine efficacy over years of therapy. A large cross-sectional observational study in Denmark showed higher pain intensity, pain interference, and worse quality of life for patients treated with opioids than those not treated with opioids, but it was not possible to rule out selection bias in this study23. There also is some evidence that longer term use of opioids could be associated with the development of hyperalgesia, increased sensitivity to pain16,51. Individuals receiving prescription opioids had higher baseline pain which could result in decreased physical activity levels and subsequent weight gain, further worsening pain and overall physical functioning. Consistent with this assessment, more hours per day of sedentary activity at baseline was associated with a worsening of physical functioning at year 3. Being disabled at baseline was also associated with lack of improvement in pain over the three-year period, and may similarly reflect a subpopulation more refractory to treatment. Results from our study highlight the need for clinical effectiveness studies to evaluate the long-term use and tolerability of prescription opioids, and to evaluate functional outcomes, in the treatment of recurrent pain among postmenopausal women.

The non-pain symptom count captured information on symptoms of distress that might be obtained in a review of symptoms, e.g. nausea, hot flashes, dizziness, fatigue, and was associated with worse pain outcomes over the three year period. This variable reflects overall symptom burden and is associated with both medical and psychiatric comorbidity34. Results from our study are consistent with prior studies, which have found a positive association between elevated levels of non-specific physical symptoms and pain severity, negative affect and disability among individuals with chronic pain38,41,54. The association between baseline hormone therapy use and worse pain outcomes may reflect use of HRT to treat postmenopausal symptoms, which include pain (e.g. joint and back pain), as well as non-pain symptoms (e.g. fatigue, mood lability, sleep disturbance, memory changes, night sweats).

One of the primary objectives of our study was to examine psychosocial predictors of a change in pain interference, pain severity and physical functioning. Prior cross-sectional studies have shown an association between depression and higher pain interference and severity2,4,8 and prospective studies have found that depression and persistent pain equally predict the subsequent onset of the other27. Consistent with this, a positive screen for depression at baseline was associated with worsening of pain at year 3 among women in our study. The association was modest, possibly reflecting the healthier baseline mental health status of the study population in comparison with clinical populations. In addition, the shortened CES-D screening instrument used in this study is less specific than the full CES-D or a diagnostic interview, and thus women screening positive likely included some with more minor depressive symptoms that would not necessarily prompt help-seeking or clinical intervention. Ambivalence over emotional expression and cynicism were not consistent or strong predictors of pain outcomes. This may be because the women in this study had relatively low baseline scores on these construct measures.

Strengths of our study include the large population-based sample with longitudinal follow-up and availability of data on a variety of psychosocial, medication use and medical variables. There are several limitations to our study that should be mentioned. The data available on prescription opioid use from this study was limited to self report of duration of use at the baseline and year 3 interviews. Hence, we are unable to determine whether use continued between the two interviews, and we lack data on prescribed dose. In addition, because this is an observational study and opioid use was obtained by self report, we cannot verify what pain condition the opioids were prescribed to treat. We also are unable to rule out the possibility that patients selected for opioid therapy had more progressive pain problems. Information on pain conditions and depressive symptoms were based on self report, not diagnoses from a health care provider or via a structured diagnostic interview. In addition, we lacked information on anxiety, which has previously been shown to be associated with persistent pain47,53, and illicit drug or alcohol use, as well as information on the presence and severity of pain complaints at time points between the baseline and year 3 interviews. Pain complaints included in the definition of recurrent pain were limited to four of the more common conditions seen in primary care28, but did not include others of clinical importance, such as fibromyalgia. The study population consisted of primarily White, middle-class postmenopausal women and results therefore may not be generalizable to all individuals with recurrent pain conditions.

In summary, elevated BMI in the overweight/obese range, a positive screen for depression, higher medical comorbidity and number of non-pain symptoms were all associated with worsening pain and physical functioning over a three-year period in this cohort of postmenopausal women with recurrent pain conditions. Baseline prescription opioid use was not associated with worsening pain but was associated with lack of improvement in pain and with worsened physical functioning at year 3. This is consistent with concerns of some experts that long-term opioid use may decrease physical function by promoting rest or inactivity29.

While it is impossible to rule out selection bias in opioid prescription in this observational study, results suggest further inquiry into the efficacy and tolerability of opioid treatment in this population is warranted. Results support prior recommendations to screen for and treat depression among those with recurrent pain conditions51 and highlight the role of obesity and weight management in long-term pain outcomes. In addition, results suggest that individuals reporting multiple physical symptoms in addition to pain are at risk for worsening pain over time. Additional prospective and comparative effectiveness studies are needed to further examine the effects of obesity, depression and opioid therapy on the course of recurrent pain conditions.

Perspective.

This study presents prospective data on change in pain and physical functioning in postmenopausal women over a three-year period. Our results suggest depression, non-pain physical symptoms, obesity and possibly opioid treatment are associated with worse long-term pain outcomes in this population.

Acknowledgments

Short list of WHI investigators:

Program Office: (National Heart, Lung, and Blood Institute, Bethesda, Maryland) Jacques Rossouw, Shari Ludlam, Joan McGowan, Leslie Ford, and Nancy Geller

Clinical Coordinating Center: Clinical Coordinating Center: (Fred Hutchinson Cancer Research Center, Seattle, WA) Garnet Anderson, Ross Prentice, Andrea LaCroix, and Charles Kooperberg

Investigators and Academic Centers: (Brigham and Women’s Hospital, Harvard Medical School, Boston, MA) JoAnn E. Manson; (MedStar Health Research Institute/Howard University, Washington, DC) Barbara V. Howard; (Stanford Prevention Research Center, Stanford, CA) Marcia L. Stefanick; (The Ohio State University, Columbus, OH) Rebecca Jackson; (University of Arizona, Tucson/Phoenix, AZ) Cynthia A. Thomson; (University at Buffalo, Buffalo, NY) Jean Wactawski-Wende; (University of Florida, Gainesville/Jacksonville, FL) Marian Limacher; (University of Iowa, Iowa City/Davenport, IA) Robert Wallace; (University of Pittsburgh, Pittsburgh, PA) Lewis Kuller; (Wake Forest University School of Medicine, Winston-Salem, NC) Sally Shumaker

Women’s Health Initiative Memory Study: (Wake Forest University School of Medicine, Winston-Salem, NC) Sally Shumaker

Footnotes

All of the authors report no conflicts of interest.

Disclosures

The WHI program is funded by the National Heart, Lung, and Blood Institute, National Institutes of Health, U.S. Department of Health and Human Services through contracts N01WH22110, 24152, 32100-2, 32105-6, 32108-9, 32111-13, 32115, 32118-32119, 32122, 42107-26, 42129-32, and 44221. Dr. Braden was supported by a Ruth L. Kirschstein National Research Service Award (NRSA) Institutional Research Training Grant [T32 MH20021 (Katon)].

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References

  • 1.Antman EM, Bennett JS, Daugherty A, Furberg C, Roberts H, Taubert KA, Association AH. Use of nonsteroidal antiinflammatory drugs: an update for clinicians: a scientific statement from the American Heart Association. Circulation. 2007;115:1634–1642. doi: 10.1161/CIRCULATIONAHA.106.181424. [DOI] [PubMed] [Google Scholar]
  • 2.Arnow BA, Hunkeler EM, Blasey CM, Lee J, Constantino MJ, Fireman B, Kraemer HC, Dea R, Robinson R, Hayward C. Comorbid depression, chronic pain, and disability in primary care. Psychosom Med. 2006;68:262–268. doi: 10.1097/01.psy.0000204851.15499.fc. [DOI] [PubMed] [Google Scholar]
  • 3.Avis NE, Colvin A, Bromberger JT, Hess R, Matthews KA, Ory M, Schocken M. Change in health-related quality of life over the menopausal transition in a multiethnic cohort of middle-aged women: Study of Women’s Health Across the Nation. Menopause. 2009 doi: 10.1097/gme.0b013e3181a3cdaf. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 4.Bair MJ, Robinson RL, Katon W, Kroenke K. Depression and pain comorbidity: a literature review. Arch Intern Med. 2003;163:2433–2445. doi: 10.1001/archinte.163.20.2433. [DOI] [PubMed] [Google Scholar]
  • 5.Barefoot JC, Dodge KA, Peterson BL, Dahlstrom WG, Williams RB., Jr The Cook-Medley hostility scale: item content and ability to predict survival. Psychosom Med. 1989;51:46–57. doi: 10.1097/00006842-198901000-00005. [DOI] [PubMed] [Google Scholar]
  • 6.Braden JB, Sullivan MD, Ray GT, Saunders K, Merrill J, Silverberg MJ, Rutter CM, Weisner C, Banta-Green C, Campbell C, Von Korff M. Trends in long-term opioid therapy for noncancer pain among persons with a history of depression. Gen Hosp Psychiatry. 2009;31:564–570. doi: 10.1016/j.genhosppsych.2009.07.003. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 7.Braden JB, Zhang L, Fan MY, Unutzer J, Edlund MJ, Sullivan MD. Mental health service use by older adults: the role of chronic pain. Am J Geriatr Psychiatry. 2008;16:156–167. doi: 10.1097/JGP.0b013e31815a3ea9. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 8.Braden JB, Zhang L, Zimmerman FJ, Sullivan MD. Employment outcomes of persons with a mental disorder and comorbid chronic pain. Psychiatr Serv. 2008;59:878–885. doi: 10.1176/appi.ps.59.8.878. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 9.Brown WJ, Mishra GD, Dobson A. Changes in physical symptoms during the menopause transition. Int J Behav Med. 2002;9:53–67. doi: 10.1207/s15327558ijbm0901_04. [DOI] [PubMed] [Google Scholar]
  • 10.Burman MA, Wells KB, Leake B, Landsverk J. Development of a brief screening instrument for detecting depressive disorders. Medical Care. 1988;26:8. doi: 10.1097/00005650-198808000-00004. [DOI] [PubMed] [Google Scholar]
  • 11.Burns JW, Johnson BJ, Devine J, Mahoney N, Pawl R. Anger management style and the prediction of treatment outcome among male and female chronic pain patients. Behav Res Ther. 1998;36:1051–1062. doi: 10.1016/s0005-7967(98)00080-1. [DOI] [PubMed] [Google Scholar]
  • 12.Campbell CI, Weisner C, Leresche L, Ray GT, Saunders K, Sullivan MD, Banta-Green CJ, Merrill JO, Silverberg MJ, Boudreau D, Satre DD, Von Korff M. Age and gender trends in long-term opioid analgesic use for noncancer pain. Am J Public Health. 2010;100:2541–2547. doi: 10.2105/AJPH.2009.180646. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 13.Carson JW, Keefe FJ, Lowry KP, Porter LS, Goli V, Fras AM. Conflict about expressing emotions and chronic low back pain: associations with pain and anger. J Pain. 2007;8:405–411. doi: 10.1016/j.jpain.2006.11.004. [DOI] [PubMed] [Google Scholar]
  • 14.Charlson ME, Pompei P, Ales KL, MacKenzie CR. A new method of classifying prognostic comorbidity in longitudinal studies: development and validation. J Chronic Dis. 1987;40:373–383. doi: 10.1016/0021-9681(87)90171-8. [DOI] [PubMed] [Google Scholar]
  • 15.Chou R, Shekelle P. Will this patient develop persistent disabling low back pain? JAMA. 2010;303:1295–1302. doi: 10.1001/jama.2010.344. [DOI] [PubMed] [Google Scholar]
  • 16.Chu LF, Clark DJ, Angst MS. Opioid tolerance and hyperalgesia in chronic pain patients after one month of oral morphine therapy: a preliminary prospective study. J Pain. 2006;7:43–48. doi: 10.1016/j.jpain.2005.08.001. [DOI] [PubMed] [Google Scholar]
  • 17.Clay FJ, Newstead SV, Watson WL, Ozanne-Smith J, Guy J, McClure RJ. Bio-psychosocial determinants of persistent pain 6 months after non-life-threatening acute orthopaedic trauma. J Pain. 2010;11:420–430. doi: 10.1016/j.jpain.2009.12.002. [DOI] [PubMed] [Google Scholar]
  • 18.Dennerstein L, Lehert P, Guthrie JR, Burger HG. Modeling women’s health during the menopausal transition: a longitudinal analysis. Menopause. 2007;14:53–62. doi: 10.1097/01.gme.0000229574.67376.ba. [DOI] [PubMed] [Google Scholar]
  • 19.Dersh J, Mayer T, Theodore BR, Polatin P, Gatchel RJ. Do psychiatric disorders first appear preinjury or postinjury in chronic disabling occupational spinal disorders? Spine. 2007;32:1045–1051. doi: 10.1097/01.brs.0000261027.28779.52. [DOI] [PubMed] [Google Scholar]
  • 20.Dugan SA, Powell LH, Kravitz HM, Everson Rose SA, Karavolos K, Luborsky J. Musculoskeletal pain and menopausal status. Clin J Pain. 2006;22:325–331. doi: 10.1097/01.ajp.0000208249.07949.d5. [DOI] [PubMed] [Google Scholar]
  • 21.Edlund MJ, Martin BC, Devries A, Fan MY, Braden JB, Sullivan MD. Trends in use of opioids for chronic noncancer pain among individuals with mental health and substance use disorders: the TROUP study. Clin J Pain. 2010;26:1–8. doi: 10.1097/AJP.0b013e3181b99f35. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 22.Epker J, Block AR. Presurgical psychological screening in back pain patients: a review. Clin J Pain. 2001;17:200–205. doi: 10.1097/00002508-200109000-00003. [DOI] [PubMed] [Google Scholar]
  • 23.Eriksen J, Sjøgren P, Bruera E, Ekholm O, Rasmussen NK. Critical issues on opioids in chronic non-cancer pain: an epidemiological study. Pain. 2006;125:172–179. doi: 10.1016/j.pain.2006.06.009. [DOI] [PubMed] [Google Scholar]
  • 24.Freeman EW, Sammel MD, Lin H, Gracia CR, Kapoor S. Symptoms in the menopausal transition: hormone and behavioral correlates. Obstet Gynecol. 2008;111:127–136. doi: 10.1097/01.AOG.0000295867.06184.b1. [DOI] [PubMed] [Google Scholar]
  • 25.Freeman EW, Sammel MD, Lin H, Gracia CR, Pien GW, Nelson DB, Sheng L. Symptoms associated with menopausal transition and reproductive hormones in midlife women. Obstet Gynecol. 2007;110:230–240. doi: 10.1097/01.AOG.0000270153.59102.40. [DOI] [PubMed] [Google Scholar]
  • 26.Furlan AD, Sandoval JA, Mailis-Gagnon A, Tunks E. Opioids for chronic noncancer pain: a meta-analysis of effectiveness and side effects. Cmaj. 2006;174:1589–1594. doi: 10.1503/cmaj.051528. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 27.Gureje O, Simon GE, Von Korff M. A cross-national study of the course of persistent pain in primary care. Pain. 2001;92:195–200. doi: 10.1016/s0304-3959(00)00483-8. [DOI] [PubMed] [Google Scholar]
  • 28.Gureje O, Von Korff M, Simon GE, Gater R. Persistent pain and well-being: a World Health Organization Study in Primary Care. JAMA. 1998;280:147–151. doi: 10.1001/jama.280.2.147. [DOI] [PubMed] [Google Scholar]
  • 29.Harden RN. Chronic pain and opiates: a call for moderation. Arch Phys Med Rehabil. 2008;89:S72–76. doi: 10.1016/j.apmr.2007.12.013. [DOI] [PubMed] [Google Scholar]
  • 30.Hays J, Hunt JR, Hubbell FA, Anderson GL, Limacher M, Allen C, Rossouw JE. The Women’s Health Initiative recruitment methods and results. Ann Epidemiol. 2003;13:S18–77. doi: 10.1016/s1047-2797(03)00042-5. [DOI] [PubMed] [Google Scholar]
  • 31.Heim N, Snijder MB, Deeg DJ, Seidell JC, Visser M. Obesity in older adults is associated with an increased prevalence and incidence of pain. Obesity (Silver Spring) 2008;16:2510–2517. doi: 10.1038/oby.2008.407. [DOI] [PubMed] [Google Scholar]
  • 32.Hitt HC, McMillen RC, Thornton-Neaves T, Koch K, Cosby AG. Comorbidity of obesity and pain in a general population: results from the Southern Pain Prevalence Study. J Pain. 2007;8:430–436. doi: 10.1016/j.jpain.2006.12.003. [DOI] [PubMed] [Google Scholar]
  • 33.Janke EA, Collins A, Kozak AT. Overview of the relationship between pain and obesity: What do we know? Where do we go next? J Rehabil Res Dev. 2007;44:245–262. doi: 10.1682/jrrd.2006.06.0060. [DOI] [PubMed] [Google Scholar]
  • 34.Katon WJ. Clinical and health services relationships between major depression, depressive symptoms, and general medical illness. Biol Psychiatry. 2003;54:216–226. doi: 10.1016/s0006-3223(03)00273-7. [DOI] [PubMed] [Google Scholar]
  • 35.King LA, Emmons RA. Conflict over emotional expression: psychological and physical correlates. J Pers Soc Psychol. 1990;58:864–877. doi: 10.1037//0022-3514.58.5.864. [DOI] [PubMed] [Google Scholar]
  • 36.Lombardo ER, Tan G, Jensen MP, Anderson KO. Anger management style and associations with self-efficacy and pain in male veterans. J Pain. 2005;6:765–770. doi: 10.1016/j.jpain.2005.07.003. [DOI] [PubMed] [Google Scholar]
  • 37.McCarthy LH, Bigal ME, Katz M, Derby C, Lipton RB. Chronic pain and obesity in elderly people: results from the Einstein aging study. J Am Geriatr Soc. 2009;57:115–119. doi: 10.1111/j.1532-5415.2008.02089.x. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 38.McCracken LM, Faber SD, Janeck AS. Pain-related anxiety predicts non-specific physical complaints in persons with chronic pain. Behav Res Ther. 1998;36:621–630. doi: 10.1016/s0005-7967(97)10039-0. [DOI] [PubMed] [Google Scholar]
  • 39.Mossey JM, Gallagher RM. The longitudinal occurrence and impact of comorbid chronic pain and chronic depression over two years in continuing care retirement community residents. Pain Med. 2004;5:335–348. doi: 10.1111/j.1526-4637.2004.04041.x. [DOI] [PubMed] [Google Scholar]
  • 40.National Center for Health Statistics. Health, United States. With Chartbook on Trends in the Health of Americans. Hyattsville, MD: 2006. [PubMed] [Google Scholar]
  • 41.O’Brien EM, Atchison JW, Gremillion HA, Waxenberg LB, Robinson ME. Somatic focus/awareness: Relationship to negative affect and pain in chronic pain patients. Eur J Pain. 2008;12:104–115. doi: 10.1016/j.ejpain.2007.04.001. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 42.Polatin PB, Kinney RK, Gatchel RJ, Lillo E, Mayer TG. Psychiatric illness and chronic low-back pain. The mind and the spine--which goes first? Spine. 1993;18:66–71. doi: 10.1097/00007632-199301000-00011. [DOI] [PubMed] [Google Scholar]
  • 43.Prentice R, Rossouw J, Furberg C, Johnson S, Henderson M, Cummings S, Manson J, Freedman L, Oberman A, Kuller L, Anderson G. Design of the WHI Clinical Trial and Observational Study. Control Clin Trials. 1998;19:61–109. doi: 10.1016/s0197-2456(97)00078-0. [DOI] [PubMed] [Google Scholar]
  • 44.Rivara FP, Mackenzie EJ, Jurkovich GJ, Nathens AB, Wang J, Scharfstein DO. Prevalence of pain in patients 1 year after major trauma. Arch Surg. 2008;143:282–287. doi: 10.1001/archsurg.2007.61. discussion 288. [DOI] [PubMed] [Google Scholar]
  • 45.Sherbourne CD, Stewart AL. The MOS social support survey. Soc Sci Med. 1991;32:705–714. doi: 10.1016/0277-9536(91)90150-b. [DOI] [PubMed] [Google Scholar]
  • 46.Stålnacke BM. Relationship between symptoms and psychological factors five years after whiplash injury. J Rehabil Med. 2009;41:353–359. doi: 10.2340/16501977-0349. [DOI] [PubMed] [Google Scholar]
  • 47.Stang PE, Brandenburg NA, Lane MC, Merikangas KR, Von Korff MR, Kessler RC. Mental and physical comorbid conditions and days in role among persons with arthritis. Psychosom Med. 2006;68:152–158. doi: 10.1097/01.psy.0000195821.25811.b4. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 48.Sullivan MD, Edlund MJ, Steffick D, Unutzer J. Regular use of prescribed opioids: association with common psychiatric disorders. Pain. 2005;119:95–103. doi: 10.1016/j.pain.2005.09.020. [DOI] [PubMed] [Google Scholar]
  • 49.Szoeke CE, Cicuttini FM, Guthrie JR, Dennerstein L. The relationship of reports of aches and joint pains to the menopausal transition: a longitudinal study. Climacteric. 2008;11:55–62. doi: 10.1080/13697130701746006. [DOI] [PubMed] [Google Scholar]
  • 50.Toblin RL, Mack KA, Perveen G, Paulozzi LJ. A population-based survey of chronic pain and its treatment with prescription drugs. Pain. 2011 doi: 10.1016/j.pain.2010.12.036. [DOI] [PubMed] [Google Scholar]
  • 51.Trescot AM, Boswell MV, Atluri SL, Hansen HC, Deer TR, Abdi S, Jasper JF, Singh V, Jordan AE, Johnson BW, Cicala RS, Dunbar EE, Helm S, 2nd, Varley KG, Suchdev PK, Swicegood JR, Calodney AK, Ogoke BA, Minore WS, Manchikanti L. Opioid guidelines in the management of chronic non-cancer pain. Pain Physician. 2006;9:1–39. [PubMed] [Google Scholar]
  • 52.Vogt MT, Lauerman WC, Chirumbole M, Kuller LH. A community-based study of postmenopausal white women with back and leg pain: health status and limitations in physical activity. J Gerontol A Biol Sci Med Sci. 2002;57:M544–550. doi: 10.1093/gerona/57.8.m544. [DOI] [PubMed] [Google Scholar]
  • 53.Von Korff M, Crane P, Lane M, Miglioretti DL, Simon G, Saunders K, Stang P, Brandenburg N, Kessler R. Chronic spinal pain and physical-mental comorbidity in the United States: results from the national comorbidity survey replication. Pain. 2005;113:331–339. doi: 10.1016/j.pain.2004.11.010. [DOI] [PubMed] [Google Scholar]
  • 54.Von Korff M, Dworkin SF, Le Resche L, Kruger A. An epidemiologic comparison of pain complaints. Pain. 1988;32:173–183. doi: 10.1016/0304-3959(88)90066-8. [DOI] [PubMed] [Google Scholar]
  • 55.Ware JE, Jr, Sherbourne CD. The MOS 36-item short-form health survey (SF-36). I. Conceptual framework and item selection. Med Care. 1992;30:473–483. [PubMed] [Google Scholar]
  • 56.Wright LJ, Schur E, Noonan C, Ahumada S, Buchwald D, Afari N. Chronic pain, overweight, and obesity: findings from a community-based twin registry. J Pain. 2011;11:628–635. doi: 10.1016/j.jpain.2009.10.004. [DOI] [PMC free article] [PubMed] [Google Scholar]

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