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Logo of nihpaAbout Author manuscriptsSubmit a manuscriptHHS Public Access; Author Manuscript; Accepted for publication in peer reviewed journal;
 
Pain Med. Author manuscript; available in PMC 2011 June 1.
Published in final edited form as:
PMCID: PMC3088098
NIHMSID: NIHMS287556

Sex differences in pain and misuse of prescription analgesics among persons with HIV

Abstract

Objective

Women represent the largest percentage of new HIV infections globally. Yet, no large-scale studies have examined the experience of pain and its treatment in women living with HIV.

Design

This study used structural equation modeling (SEM) to examine sex differences in pain and the use and misuse of prescription analgesics in a representative sample of HIV+ persons in the United Stated (US) within a prospective, longitudinal design.

Outcome Measures

Bodily Pain subscale of the Short-Form 36; Modified Short Form of the World Health Organization’s Composite International Diagnostic Interview (Opioid Misuse).

Results

Women reported more pain than men over a roughly 6 month period regardless of mode of HIV transmission or prior drug use history. Men acknowledged more misuse of prescription analgesics over an approximate 1 year period compared to women, after taking into account pain, use of analgesics specifically for pain and drug use history. Weaker associations between pain and use of analgesics specifically for pain that persisted over time were found among women compared to men. For both men and women, pain was stable over time. Problem drug use history exerted significant direct and indirect effects on pain, opioid misuse and pain-specific analgesic use across sex.

Conclusion

The current findings are consistent with prior evidence indicating female pain predominance as well as the under treatment of pain among women with HIV. Efforts should be made to improve the assessment and long-term management of pain in HIV+ persons.

Keywords: pain, substance abuse, opioid misuse, women, gender differences, AIDS

Introduction

Globally, women account for the largest percentage of newly infected HIV individuals (1, 2). Given the necessary focus on disease treatment, relatively little attention has centered on the management of pain and other distressing, yet treatable symptoms (3). Pain is a source of considerable disability among HIV+ persons (4) and may arise from various sources (5) including the direct effects of HIV on the central or peripheral nervous system, disorders associated with HIV, or treatment for HIV. Pain in HIV is conceptualized as an entity with its own significant sequelae including impaired functioning and reduced quality of life (68). Women are identified as the modal human sufferers of pain (9). Yet, there is a dearth of research on sex-based disparities in pain and its consequences among HIV+ persons.

The evidence for sex-based differences in pain in HIV is mixed. Three studies (4, 10, 11) found no sex differences in pain among HIV+ persons. Rotheram-Borus (12) found that sex was not associated with pain symptoms or pain distress in HIV+ persons, although women reported more frequent anticipation of pain compared to men. On the other hand, positive associations between female sex and the presence of pain in HIV have been reported (6, 13). These divergent findings may be due to variations in sample composition and/or pain assessment, including the use of unstandardized measures and small convenience samples.

In a nationally representative sample of HIV+ persons in the United States (US), it was previously found that women exposed to HIV via intravenous drug use (IDU) reported more pain then men who had sex with men (MSM) (14). Because sex and mode of HIV exposure were combined into mutually exclusive categories (e.g., female IDU, male IDU, heterosexual female, heterosexual male), the specific impact of sex on reporting of pain was not analyzed. Another study found that female intravenous drug users (IDUs) reported more pain sites compared to male IDUs, but no such differences among non-IDUs (15). No population-based research in HIV+ persons has examined whether sex exerts a specific impact on pain irrespective of mode of HIV transmission. Such work is needed in light of data indicating sex-based disparities in the management of pain among HIV+ persons. In one study, HIV+ women were more than twice as likely to receive inadequate treatment for pain compared to HIV+ men (16). Of particular concern is the possibility that inadequate analgesia from legitimate sources may lead to misuse of opioids (e.g., use of illicitly obtained medications). Previously, it was found that among HIV patients without a history of drug abuse, men reported more opioid misuse than women but there were no such differences among patients with a drug use history (17).

The present investigation used structural equation modeling (SEM) to examine sex differences in the experience of pain and the misuse of prescription analgesics in a nationally representative sample of HIV+ persons using a prospective, longitudinal design. Consistent with research in non-HIV populations, we hypothesized that in this HIV+ sample women would report more pain than men. We further hypothesized that men regardless of drug use history would report more misuse of prescription opioids relative to women. We also expected that women would demonstrate weaker associations between pain and the use of prescription pain medications specifically for pain (i.e., pain-specific analgesic use) than men. Evidence of a weak link between pain and pain-specific analgesic use may point to possible undertreatment of pain. For example, high levels of pain associated with low rates of pain-specific analgesic use or nonsignificant associations between pain and analgesic use may indicate insufficient treatment of pain. These analyses were conducted across three time points (i.e., baseline, Time 2 – 6 month follow-up, Time 3 – 12 month follow-up), controlling for key sociodemographic variables.

Methods

Participants

This study used longitudinal data from the HIV Cost and Services Utilization Study (HCSUS) and included 2267 participants (664 females, 1603 males). Participants were assessed at baseline, and at approximately 6-month (Time 2) and 12-month (Time 3) follow-ups. Baseline interviews occurred between January 1996 and April 1997 (18). The first follow-up interviews (Time 2) were conducted with 2,466 respondents (86.1% of baseline) from December 1996 to July 1997. The mean time between baseline and Time 2 was 223 days (95% confidence interval [CI], 204–244). The second follow-up interviews (Time 3) were conducted from August 1997 to January 1998, with a mean time between baseline and Time 3 of 416 days (95% CI, 391–441). Time 3 included interviews with 2,267 persons (84.5% of baseline). The mean age of the females was 40 years, and the mean age of the males was 35 years. African Americans comprised 51% of the females and 23% of the males.

The HCSUS is a nationally representative probability sample of HIV+ persons at least 18 years of age receiving care in the continental US. The reference population was limited to known HIV+ persons who made at least one visit for regular or ongoing care to a non-military, non-prison medical provider other than an emergency department between January 5 and February 29, 1996. The data are weighted to account for differences in ethnic and racial composition. Further information on the design and weighting procedure is available elsewhere (1820). Interviews were completed by 2,864 (71%) of the 4,042 sampled eligible subjects. The HCSUS was reviewed and approved by the appropriate institutional review boards (IRBs), including local IRBs.

Measures

Background variables

Additional detail on the demographic characteristics of the sample is available elsewhere (14, 21). Age and socioeconomic status (SES) were included as baseline demographic correlates. Age was reported in years. Education and income were used to indicate a latent variable representing SES. Yearly income was assessed categorically: 1 = $0 to 5,000; 2 = $5,001 to $10,000; 3 = $10,001 to $25,000; 4 = >$25,000 (range: 25,000-$75,001 or more). Education was also assessed categorically: 1 = some high school; 2 = high school graduate; 3 = some college; 4 = college graduate or more. We considered including African-American race/ethnicity because the disparity in the proportion of African-Americans in the two samples could be influencing the results rather than sex differences (i.e., there were more African-American women than men). Preliminary analyses indicated that race/ethnicity was not driving the results and that the weights were accounting for any differences that arose. African-Americans in both samples tended to report less misuse of prescription analgesics. Other associations were not significant except for lower SES among the African-Americans in both samples.

Problem Drug Use History

Participants who answered “yes” to the following two questions were classified as having problem drug use history: 1) ever had to use much larger amounts of illicit drugs than usual to get the same effect or that the same amount had less effect on them than before; and/or 2) ever had any emotional or psychological problems from using drugs such as feeling uninterested in things, feeling depressed, suspicious of people, paranoid, or having strange ideas. All others were classified as non-problem drug use history patients. These items were based on the short form of the World Health Organization’s Composite International Diagnostic Interview (CIDI-SF) (22) and devised by the HCSUS consortium (2325). The sensitivity and specificity of the CIDI-SF for diagnosis of drug dependence is 0.77 and 0.99, respectively, in the general population (22). Separate data for diagnosis of drug dependence were not available, but the sensitivity and specificity of the CIDI-SF for any psychiatric disorder in the HCSUS sample was 0.80 and 0.76, respectively (23). The proportion of men and women classified as having a drug problem history was similar (38%).

Pain was assessed at all three time points using the bodily pain scale of the Short-Form 36 (SF-36) (26, 27). A latent variable for pain was indicated by the 2 scale items: 1) “During the past four weeks, how much did pain interfere with your normal work (including work outside the house and housework)?” Responses ranged from “Not at all” = 1, to “extremely” = 5; 2) How much bodily pain have you had during the past four weeks? Responses ranged from “none” = 1 to “very severe” = 6.

Misuse of prescription analgesics was measured at baseline and Time 2 with the yes/no item: “In the past 12 months have you used analgesics or other prescription painkillers without a doctor’s prescription, in larger amounts than prescribed, or for a longer period than prescribed. This does not include normal use of aspirin, Tylenol without codeine, etc., but does include use of Tylenol with Codeine and other prescription painkillers like Demerol, Darvon, Darvocet, Percodan, Percocet, Codeine, Morphine, Methadone, and Fentanyl.” The same question was asked at Time 3 but the time interval was shortened to the past 30 days rather than the past 12 months, thus avoiding any overlap in the period assessed at Time 2.

Pain-specific use of prescription analgesics was assessed at baseline using the following question: “Over the last 6 months, have you taken any prescription drugs for pain.” At Time 2 and Time 3 participants were asked “since we last interviewed you, have you taken any prescription drugs for pain?”

Statistical analysis

Confirmatory structural equation models

Latent variable structural equation modeling (SEM) was performed using EQS (28). The robust comparative fit index (RCFI), Satorra-Bentler robust chi-square values (ML χ2), and the Root Mean Square Error of Approximation (RMSEA) were used as indicators of fit (28, 29) due to high multivariate kurtosis in both data sets. The RCFI compares the improvement of fit of a hypothesized model to a model of complete independence among the measured variables. The RCFI ranges between 0 and 1; values greater than or equal to .95 indicate a good fit (28). The RMSEA is a measure of fit per degrees of freedom, controlling for sample size; values less than .06 indicate a relatively good fit between the hypothesized model and the observed data (29). An initial confirmatory factor analysis (CFA) was performed for men and for women separately with each hypothesized latent construct predicting its measured indicators. All latent constructs, and the single-item variables were correlated with no imputation of causality or temporal ordering. This analysis assessed the adequacy of the proposed factor structure and the relationships among the latent and measured variables. This analysis was used in the next stage which compared the men and women with multi-sample models.

Multisample models

In the multisample models in this study, we contrasted the two groups on their factor structures, covariances among the constructs, and also on their latent means (28, 30, 31, 32). We began by specifying an initial baseline model with no constraints that is used for comparison purposes. We then tested a model in which their factor structures were constrained to equality. We then constrained the covariances among the latent variables to equality and tested whether they were significantly different in the two groups. In addition, following the test that constrained the measurement model (factor structure) to equality, we assessed differences in latent construct means. The tenability of the successively more stringent set of constraints was assessed with the goodness-of-fit indexes described above, χ2 difference tests, and results from the Lagrange Multiplier test (30), which in this context identifies constraints that are untenable.

Predictive longitudinal path models

A predictive cross-lagged longitudinal path model was tested in each group in which background characteristics of socioeconomic status, age, and a drug problem history predicted baseline pain, opioid misuse and pain-specific prescription analgesic use. In turn, all variables predicted pain, opioid misuse, and pain-specific analgesic use at times 2 and 3. Non-significant paths were dropped until only significant paths remained.

Results

Confirmatory factor analysis

All measured variables loaded significantly (p < 0.001) on their hypothesized latent factors. Fit indexes were excellent in both groups: Men: S-B χ2 (46, N = 1603) = 82.05, RCFI = 0.99, RMSEA = 0.022. Women: S-Bχ2 (46, N = 664) = 39.31, RCFI = 0.99, RMSEA = 0.000. Table 1 reports summary statistics for the measured variables and factor loadings of the latent variables. Table 2 reports correlations among all variables in the model for men and women separately

Table 1
Summary statistics and factor loadings of variables in CFA.
Table 2
Correlations among model variables. Correlations for males below diagonal. Correlations in boldface are significantly larger than the corresponding correlation for the other sex.

Multiple group analyses

Constrained factor structure

An unconstrained multisample model served as the baseline (χ2 (92) =119.41, RCFI = 0.99). When the factor structures were constrained to equality, there was a significant decrement in fit in terms of the chi-square difference between the two models (χ2 (100) = 137.10, CFI = 0.99, adjusted chi-square difference = 17.89/8 df,). After dropping the constraint of income equality as recommended by the LM test there was no significant decrement in fit between the constrained and unconstrained models (χ2 (99) = 123.13, CFI = 0.99; adjusted chi-square difference = 2.81/7df, non-significant). Thus, we were able to assume equal factor structures for the two groups and to proceed to the next level of stringency by constraining the covariances (correlations) between the constructs to equality.

Constrained covariances

The more constrained model in which the covariances among the latent variables and single item variables were constrained to equality across the groups did not have a significant increase in its chi-square value (χ2 (165) = 192.14, RCFI = 0.99). The adjusted χ2-difference was 73.94/73 df. However, some individual covariances differed significantly in the two groups (p < .05). Compared to women, men reported a significantly higher correlation between pain-specific analgesic use and pain at Time 1 (.49 vs. .31), as well as a higher correlation between pain-specific analgesic use and pain at Time 2 (.51 vs. .33). Relative to women, men also reported a higher correlation between pain-specific analgesic use at Time 1 and pain at Time 2 (.37 vs. .22). Compared to men, women reported a significantly higher correlation between pain-specific analgesic use at Time 2 and opioid misuse at Time 3 (.15 vs. .07). Younger men were more likely than younger women to report opioid misuse at Time 2 (−.14 vs. −.02).

Latent means model

Table 3 reports the results of the latent means comparison. There were significant differences between the latent means of the two groups in several of the variables. Men reported a substantially higher SES. Women reported more pain at Times 1 and 2, whereas the men reported greater opioid misuse at all time periods. Women reported more pain-specific analgesic use at Time 2 and the males reported somewhat more pain-specific analgesic use at Time 3 (.05, 1-tailed test).

Table 3
Latent Mean Differences between HIV+ men and women

Path models

Figures 1 and and22 depict the significant paths in the longitudinal path analyses for men and women: . Men: S-B χ2 (75, N = 1603) = 114.56, RCFI = 0.99, RMSEA = 0.018. Women: S-Bχ2 (85, N = 664) = 73.45, CFI = 0.99, RMSEA = 0.000. Because of the substantially greater sample size for men, some of the regression coefficients that are only present in the path model for men were not necessarily significantly different from those of women even if they were nonsignificant for women. Thus, some apparent differences should be interpreted with caution.

Figure 1
Longitudinal path model for female HCSUS participants (N = 664). Latent constructs are in circles, single items are in rectangles; 1-headed arrows depict standardized regression paths, 2-headed arrows represent correlations (standardized covariances). ...
Figure 2
Longitudinal path model for male HCSUS participants (N = 1603). Latent constructs are in circles, single items are in rectangles; 1-headed arrows depict standardized regression paths, 2-headed arrows represent correlations (standardized covariances). ...

The following similarities were found in both groups. There was stability among the same variables across time, e.g., Pain at baseline, Time 2, and Time 3. A problem drug use history predicted Pain, opioid misuse, and pain-specific analgesic use at baseline as well as continued opioid misuse at Time 2. Older participants reported more pain at baseline. Higher SES participants reported less Pain at baseline. More Pain at Time 2 predicted more pain-specific analgesic use at Time 3. There were also several significant indirect effects. Space precludes mentioning them all but, of most interest, for both men and women greater age and a problem drug use history had significant indirect effects on Pain at Times 2 and 3. A problem drug history had substantially significant indirect effects on opioid misuse and pain-specific use at Times 2 and 3 in both groups. Pain at baseline had an indirect effect on Pain and Pain-specific use at Time 3. Greater age had significant indirect effects on less opioid misuse at Times 2 and 3 for men. Higher SES among men had a significant indirect effect on less Pain among men at Times 2 and 3. The effect was nonsignificant for women.

Discussion

The present analyses indicated significant sex differences in the experience of pain and the misuse of opioid analgesics in a nationally representative sample of persons living with HIV. Consistent with our hypothesis, we found that after controlling for key sociodemographic variables as well as prior history of problem drug use, women reported more pain than men regardless of the mode of HIV transmission. Moreover, this sex-specific difference in pain persisted over a roughly six month period. Also consistent with our hypothesis, the current analyses indicated that men acknowledged more misuse of opioid medications compared to women, after taking into account pain, use of analgesics specifically for pain and history of problem drug use. In addition, the observed sex difference in opioid misuse held over an approximate one year period. It should be noted that the proportion of respondents in the current sample with a problem drug use history (roughly 38%) did not differ based on sex. These findings suggest that despite increased pain that persisted over time and irrespective of prior drug use history, women were less likely than men to engage in misuse of opioids. Also consistent with hypothesis, weaker associations between pain and pain-specific analgesic use were found among women compared to men.

The current findings advance the literature on sex differences in pain in HIV. Not only were the data derived from the first US national sample of HIV+ persons, pain was also assessed using a well-established, validated instrument. The present findings agree with the considerable literature in non-HIV populations indicating substantial sex differences in the experience of pain (9). Our results also agree with prior work demonstrating that among HIV+ persons, women are more likely to experience pain (13), and to report increased pain intensity (6) compared to men. By confirming that sex has a specific association with pain irrespective of HIV transmission factor or history of problem drug use, the present findings also extend prior work indicating that female IDUs reported more pain than MSM (14). However, the current results are at odds with null findings for sex-based differences in pain in HIV+ convenience samples (4, 10, 11). This divergence may be due to variations in sample composition and/or pain assessment measures.

As noted above, we found increased opioid misuse among men compared to women in this representative HIV+ sample. Prior evidence of sex differences in opioid misuse is mixed. In the US general population, men report more overall illicit drug use than women, but rates of nonmedical use of prescription drugs, including opioids are similar across sex (31). However, an earlier national study indicated that women were more likely to report problem use of opioids than men (32). The current finding that men were more likely than women to misuse opioids in this HIV+ sample may be due to the overall higher SES of men. It may be that the increased resources available to men in the HCSUS sample allowed greater access to opioids and consequently, more opportunities for misuse.

Compared to women, men evidenced stronger concurrent relationships between pain and pain-specific opioid use at baseline and at Time 2 (6 month follow-up), as well as a more robust predictive relationship between pain-specific analgesic use at baseline and pain at Time 2. The weaker association between pain and pain-specific analgesic use among women is consistent with prior work indicating greater undertreatment of pain in women than men (16). Even though women in the current sample reported more pain than men at baseline, women did not report greater use of pain medications specifically to manage pain. Thus, women may have either received inadequate treatment for pain and/or may have chosen not to take sufficient analgesics for their pain. Because the HCSUS did not include prescription records, it is unclear whether women were less likely than men to be prescribed opioids or, whether women were prescribed opioids at the same rates as men but chose not to take them.

It should also be noted that certain similarities between men and women were found. As indicated in the path models (Figures 1 and and2),2), pain remained fairly stable over time for both men and women. In addition, a problem drug use history exerted significant direct and indirect effects on pain, opioid misuse and pain-specific analgesic use over time for both men and women. Finally, older age was linked with more pain whereas higher SES was associated with less pain across sex.

Limitations to our findings should be mentioned. The current investigation was not able to identify the mechanisms underlying the observed sex differences in pain and opioid misuse. Our conceptual model did not examine the possible role of psychological symptoms in pain and inappropriate use of opioids. It is recognized that women in general are at increased risk for mood and anxiety disorders relative to men, and both of these disorders have shown strong relationships with pain among HIV+ persons (33). Further research employing more complex modeling may examine sex-based differences in the associations among pain, psychological disorders, drug use, and health outcomes.

The present analyses also indicated sex-based differences in patterns of pain-specific prescription analgesic use among HIV-positive persons. Compared to women, men evidenced stronger concurrent relationships between pain and pain-specific opioid use at baseline and at Time 2 (6 month follow-up), as well as a more robust predictive relationship between pain-specific analgesic use at baseline and pain at Time 2. Although the weaker association between pain and pain-specific analgesic use among women is consistent with prior work indicating greater undertreatment of pain in women than men (16), an alternative explanation is that factors other than pain may drive analgesic use in women whereas in men, analgesic use is more strongly tied to their level of pain.

In sum, the current findings suggest that care should be taken to assess and treat pain adequately, particularly among women with HIV. Several investigations have noted the inadequate provision of opioid analgesics for pain in HIV (4, 16, 34) even though clinical guidelines recommend such medications for the treatment of severe pain (35). The present study suggests a need for educational interventions aimed at improving healthcare provider awareness of pain and its treatment among women with HIV. Such efforts should address sex-based stereotypes including the belief that pain in women may be psychogenic (36), as well as provider concerns regarding the risk of addiction. Similarly, there may be a need for additional education of persons of both sexes living with HIV regarding availability and appropriateness of pain management. For example, it has been suggested that women’s coping mechanisms may create the perception that they have a greater tolerance to pain whereas cultural factors may influence men to be more stoic regarding their pain and delay care-seeking behaviors (36). Assessment of possible misuse of prescription analgesics is also indicated, especially among HIV+ men irrespective of prior history of substance abuse. In light of the present findings indicating that pain is highly stable over time, continued efforts should be directed at improving the long-term management of pain in HIV+ persons.

Acknowledgments

Support for this research was provided by DA017026 awarded to the first author and by DA01070-35 awarded to the second author by the National Institute on Drug Abuse. The HIV Cost and Services Utilization Study (HCSUS) was supported by a cooperative agreement (U01HS08578) between RAND and the Agency for Healthcare Research and Quality. Substantial additional support for this agreement was provided by the Health Resources and Services Administration, the National Institute of Mental Health, the National Institute on Drug Abuse, and the Office of Research on Minority Health through the National Institute for Dental Research. Additional support was provided by the Robert Wood Johnson Foundation, Merck and Company, Glaxo-Wellcome, and the National Institute on Aging. The authors thank Gisele Pham for her secretarial and administrative contributions to this research project, and the participants in this study.

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