I’m Tired and It Hurts! Sleep quality and acute pain response in a chronic pain population

Abstract

Objective/Background:

There are bidirectional links between sleep quality and pain, with recent research suggesting that sleep impairment more strongly predicts future pain than vice versa. Relatively few studies have examined sleep quality in relationship to acute pain among chronic pain patients. The purpose of the current study is to investigate relationships among subjective sleep quality and behavioral and physiological responses to a cold pressor pain task (CPT) in chronic pain patients.

Patients/Methods:

Participants were 120 individuals with chronic pain. Participants completed a series of questionnaires followed by the CPT. Sleep quality was assessed using the Pittsburgh Sleep Quality Index (PSQI). Physiological baseline state and stress response were assessed before and during the CPT using heart rate (HR), electromyography frontalis (EMGF), galvanic skin response conductance (GSR), and skin temperature (oC). Multiple linear regressions adjusting for opioid usage were performed.

Results:

After adjusting for opioid use, PSQI global score explained significant variance in pain tolerance (B=−5.37, β=−.23, p=.01), baseline GSR (B=−.66, β=−.24, p=.01), and HR change from baseline to CPT (B=1.33, β=.25, p=.01).

Conclusions:

Worse perceived sleep quality was associated with lower pain tolerance, lower baseline GSR conductance, and greater HR change from baseline to CPT. These findings underscore the importance of accounting for opioid usage and psychological dimensions of pain in the relationship between sleep and acute pain response in chronic pain populations.

1.1. Introduction

Sleep difficulties are common among individuals with chronic pain, with some studies finding that up to 70–88% of chronic pain patients suffer from significant sleep disturbance (Smith & Haythornthwaite, 2004). There is likely a reciprocal relationship between pain and sleep impairment and there are many unanswered questions about this relationship. However, recent research suggests that sleep impairment more strongly predicts future pain than vice versa (Finan, Goodin, & Smith, 2013). For example, among burn victims with acute pain, it was found that subjective sleep quality for a single night was a significant predictor of pain intensity the next day but that pain intensity was not a significant predictor of the following night’s sleep quality (Raymond, Nielsen, Lavigne, Manzini, & Choiniere, 2001). Regarding pain-related neurotransmitters impacted by sleep, animal studies have provided evidence that sleep deprivation may dysregulate endogenous opioid systems, rendering the body’s ability to regulate pain less effective (Nascimento, Andersen, Hipólide, Nobrega, & Tufik, 2007; Ukponmwan, Rupreht, & Dzoljic, 1984). Systems regulating serotonin and dopamine activity are also involved in pain regulation and may be affected by sleep impairment (Lautenbacher, Kundermann, & Krieg, 2006).

The purpose of the current study is to investigate relationships among subjective sleep quality and behavioral and physiological responses to a cold pressor pain task (CPT) in chronic pain patients. Behavioral acute pain response variables included pain tolerance, pain sensitivity, and reported pain intensity due to the CPT. Previous findings have suggested that worse sleep quality is associated with higher pain sensitivity and lower pain tolerance. In a recent review of sleep deprivation and pain perception, the majority of experimental human studies showed that sleep deprivation had hyperalgesic effects (increased sensitivity to noxious stimuli). Importantly, all of the reviewed studies included healthy participants (i.e., no chronic pain) and relatively small samples (no sample size exceeding an N of 20) (Lautenbacher et al., 2006).

In a large study of 10,412 participants, self-reported higher insomnia frequency, higher insomnia severity, worse sleep efficiency, and longer sleep onset latency during the previous year were all associated with lower CPT pain tolerance. Sleep duration was not associated with a significant difference in pain tolerance except for participants sleeping 8 hours or more. A synergistic interaction effect of chronic pain and insomnia was found for pain tolerance, such that those with comorbid chronic pain and insomnia had significantly higher hazard ratios for reduced CPT pain tolerance (Sivertsen et al., 2015).

Relatively few studies have examined sleep quality in relationship to acute pain among chronic pain patients. In a correlational study of 16 fibromyalgia patients, Agargun et al. (1999) found that worse self-reported sleep quality as measured by the Pittsburgh Sleep Quality Index (PSQI) was associated with higher sensitivity to pressure pain. Another study found insomnia diagnosed by polysomnography to be associated with higher pain sensitivity to mechanical pressure and heat in individuals with temporomandibular joint disorder (Smith et al., 2009).

Regarding links between sleep quality and physiological stress response, findings have been mixed. Previous research suggests that in the short term, sleep loss causes temporary increases in baseline activity of the sympathetic nervous system (SNS) and hypothalamic pituitary adrenal (HPA) axis (Meerlo, Sgoifo, & Suchecki, 2008). One night of sleep loss has been shown to cause higher blood pressure and increased urinary excretion of norepinephrine on the following day, both of which are markers of higher baseline sympathetic activity (Tochikubo, Ikeda, Miyajima, & Ishii, 1996). Despite these findings, not all studies have found significant autonomic changes among individuals with sleep challenges. In a recent systematic review by Nano et al. (2017), only one of four studies examining baseline cardiovascular activity during daytime found significant differences between healthy sleepers and individuals with insomnia.

In addition to the effects of sleep impairment on baseline autonomic activity, research has also demonstrated a relationship between habitual poor sleep and higher stress reactivity. In the review by Nano et al. (2017), out of five studies examining cardiovascular activity during daytime tasks, four found differences between those with and without insomnia. Findings varied but generally revealed increased sympathetic activity and decreased parasympathetic activity for insomniacs in response to activity or stressors (Nano, Fonseca, Vullings, & Aarts, 2017). In a study of 59 adult males, participants showing poor sleep efficiency, measured by actigraphy during the previous week, responded to induced psychosocial stress with greater increases in cortisol and blood pressure (Massar, Liu, Mohammad, & Chee, 2017). Another study of 40 healthy adults found that worse perceived sleep quality over the previous month was associated with higher baseline cortisol levels, greater cortisol reactivity to a CPT, and reports of higher severity of pain induced by the CPT. The authors additionally found evidence suggesting that cortisol activity mediated the relationship between pain severity and sleep quality (Goodin, Smith, Quinn, King, & McGuire, 2012).

Based on the current evidence, it is apparent that chronic sleep loss changes the physiological reactivity of the body’s stress systems including the HPA axis and SNS. Animal studies have demonstrated that sleep deprivation or the physiological or psychological stress associated with sleep deprivation produces changes in brain systems that regulate stress responses. Researchers using a rat model of insomnia found that cortisol levels increased after chronic sleep loss. Interestingly, adrenocorticotropic hormone, which stimulates cortisol release, did not appear to change in response to chronic sleep loss (Meerlo, Koehl, van der Borght, & Turek, 2002). Overall, much of the existing research suggests that sleep loss can contribute to higher baseline SNS and HPA activity, as well as higher reactivity of these systems to stressors, including acute pain.

Despite these connections between sleep quality and physiology, some investigations have suggested that perceived sleep quality impacts psychological responses to stressors such as pain without apparent physiological ANS correlates. For instance, some studies have reported significant effects on emotional and cognitive responses to exercise and work related challenges despite normal physiological stress response markers (Meerlo et al., 2008). In one study of ANS functioning and sleep in a fibromyalgia population, reported sleep quality was significantly worse than that of healthy controls; however, there was no difference in baseline blood pressure, heart rate, or heart rate variability between healthy participants and those with fibromyalgia. Sleep quality measures were significantly correlated with severity of fibromyalgia, but there were no autonomic differences between participants reporting low life impact from fibromyalgia and those reporting moderate fibromyalgia life impact (Singh, Rai, Rastogi, & Endukuru, 2018). Thus, there is at least some evidence suggesting that the lower pain tolerance and higher pain sensitivity often found among poorer sleepers are not always reflected in physiological stress system measures.

For the current study, we hypothesized, first, that poor subjective sleep as indicated by higher PSQI global score would be associated with higher pain sensitivity and lower pain tolerance. Second, we hypothesized that poor sleep would be associated with higher baseline ANS activity, as indicated by higher baseline heart rate (HR), electromyography frontalis (EMGF), galvanic skin response conductance (GSR), and skin temperature (°C). Third, we expected poor sleep quality to be associated with stronger ANS response to the CPT as indicated by larger changes in HR, EMGF, GSR, and skin temperature.

1.2. Material and Methods

1.2.1. Participants and Procedures

All participants (N=120) had non-malignant chronic pain and an average SF-36 pain score of 54.3 ± 10.0. Participants were recruited from buprenorphine and methadone treatment centers, Narcotic Anonymous groups, radio advertising, public access TV advertising, and flyers in public areas. Of the 120 participants, 60 were currently taking methadone or buprenorphine for opioid addiction, 30 had a history of opioid maintenance for opioid addiction but were currently opioid abstinent, and 30 were opioid naïve. After signing an informed consent, participants completed a urine drug screen, reported current pain severity, and completed several questionnaires regarding pain and sleep quality. If urine toxicology results met inclusion criteria, participants completed the CPT. All procedures were approved by the University of Massachusetts Medical School Institutional Review Board.

1.2.2. CPT

The cold pressor task is a method of pain and stress induction that permits slowly increasing pain via placing an appendage (typically hand or foot) in a container of painfully cold water. In the current study, participants placed their dominant hand up to the wrist in cold water (2° C). They were instructed to let the assessor know when they first experienced pain (pain sensitivity) and to keep their hand in the water “until it is too painful,” (pain tolerance) at which time they were instructed to remove their hand.

1.2.3. Operational Definitions of Pain Tolerance, Sensitivity, and CPT Pain Rating

For this study, we define pain sensitivity as time of contact with cold water until the participant reported first feeling pain. We define pain tolerance as time until patient removed his/her hand from the cold water, with a maximum duration of 300 seconds. Participants reported after the CPT the level of pain they experienced as a result of the task on a scale from 0–100, which we refer to as CPT pain rating.

1.2.4. Opioid Use

Participants also reported opioid dosage and frequency. A urine drug screen was used to verify absence of drug abuse within the past 72 hours.

1.2.5. PSQI

The Pittsburgh Sleep Quality Index (PSQI) was used to assess perceived sleep quality. The PSQI is a validated measure of seven sleep quality domains over a 1-month period. Domains include: subjective sleep quality, sleep latency, sleep duration, habitual sleep efficiency, sleep disturbances, use of sleep medications, and daytime dysfunction. A global PSQI score greater than 5 is the clinical cutoff score indicative of poor sleep (Buysse, Reynolds, Monk, Berman, & Kupfer, 1989).

1.2.6. SF-36

The SF-36 was used to assess general pain levels over the past four weeks. The SF-36 is a validated measure of eight health related domains: vitality, physical functioning, bodily pain, general health perceptions, physical role functioning, emotional role functioning, social role functioning, and mental health (McHorney, Ware, Lu, & Sherbourne, 1994).

1.2.7. Physiological Measures

To analyze markers of ANS functioning, we measured heart rate (HR), electromyography frontalis (EMGF), galvanic skin response (GSR), and skin temperature. Higher EMGF values represented more tension in the forehead frontalis muscle and higher GSR values indicated higher level of finger skin conductance due to sweat gland activation.

1.2.8. Data Analysis

SPSS v25.0 was used for data analysis. Four participants had missing baseline physiology measures and three participants had missing physiology measures during the CPT. For each analysis, missing data was excluded listwise. We performed hierarchical linear regressions for each outcome variable, with morphine equivalent dosage (MEQ) as the predictor for the first model and both PSQI global score and MEQ as predictor variables in the second model. Previous research suggests that opioid use can disrupt sleep architecture (Benyamin et al., 2008; Dimsdale, Norman, DeJardin, & Wallace, 2007; Gauthier, Guzick, Brummett, Baghdoyan, & Lydic, 2011) and that chronic opioid use can cause hyperalgesia (Wachholtz & Gonzalez, 2014). In light of the evidence that opioid use disrupts sleep architecure and because the study population included individuals who were opioid naïve, individuals with a history of opioid use but no current use, and indivduals currently taking buprenorphine or methadone, it was important to statistically account for opioid use in order to identify direct relationships between PSQI scores and outcome variables. The hierarchical regression allowed us to adjust for MEQ and determine whether PSQI explained significant variance in outcome variables above and beyond that explained by MEQ.

Outcome variables included pain tolerance, pain sensitivity, CPT pain rating, physiology baseline values, and change in physiology variables. For regressions with nonsignificant overall effects and non-normally distributed outcome variables, we transformed variables for normality and repeated the regression analyses. In no case did this change the outcome of the regression analyses with a significance level of p<.05. Thus, results of analyses with untransformed variables are reported below.

1.3. Results

1.3.1. Participant Characteristics

Mean participant age was 41.98 (SD=11.44). A majority of participants were female (60.8%) and individuals in the study sample were predominantly Caucasian (84.2%). All 120 PSQI global scores were greater than the poor sleep clinical cutoff score of 5, with the minimum PSQI global score being 8 (M=13.69, SD=3.24). Further sample characteristics can be found in Table 1. For average physiology values, see Table 2.

Table 1.

Sample Characteristics

Gender (%)
Female	73 (61%)
Male	47 (39%)
Ethnicity (%)
Caucasian	101 (84%)
African	5 (4%)
Native American	7 (6%)
Multiracial	7 (6%)
Latino	17 (14.2%)
Age (yrs)	41.98 ± 11.44
PSQI Global Score	13.69 ± 3.24
SF-36 Score	54.29 ± 10.00
Pain Sensitivity1	31.26 ± 37.35
Pain Tolerance2	76.69 ± 76.08
CPT Pain Rating	63.84 ± 25.09

¹Time to first pain (sec)

²Duration until hand removed from cold water (sec)

Mean ± SD

Table 2.

Physiology Values

	Mean ± SD
Baseline Physiology Values
HR	84.09 ± 31.99
EMGF	57.21 ± 68.23
GSR	7.27 ± 8.97
Skin Temperature (°C)	32.65 ± 3.61
CPT Physiology Values
HR	87.31 ± 31.19
EMGF	66.20 ± 77.98
GSR	9.06 ± 11.61
Skin Temperature (°C)	32.47 ± 3.34
Δ Physiology Values (BL to CPT)
HR	2.78 ± 17.20
EMGF	9.41 ± 56.76
GSR	1.79 ± 3.90
Skin Temperature (°C)	−0.20 ± 0.86

1.3.2. Sleep and Pain Variables

PSQI global score and MEQ together were significant predictors of pain tolerance (R²=.11, F_2,117=7.37, p=.001), with PSQI explaining significant variance in pain tolerance above and beyond that accounted for by MEQ (See Appendix). Worse sleep was associated with lower pain tolerance. While the overall regression model explained significant variability in pain sensitivity (R²=.06, F_2,117=4.03, p=.02), PSQI was not a significant predictor of pain sensitivity when controlling for MEQ and thus did not add significant predictive power to the model (See Appendix). The regression model did not explain significant variability in CPT pain rating.

1.3.3. Sleep and Baseline Physiology Measures

After controlling for MEQ, PSQI global score explained significant variability in baseline GSR, with higher PSQI score associated with lower baseline skin conductance (See Appendix). Together, MEQ and PSQI were significantly predictive of baseline HR (R²=.07, F_2,113=4.30, p=.02), but the relationship between PSQI and baseline HR was not significant after controlling for MEQ (See Appendix). The regression model did not explain significant variability in baseline skin temperature nor baseline EMGF.

1.3.4. Sleep and Physiological Response to CPT

PSQI Global Score and MEQ together predicted HR change from baseline to CPT (R²=.06, F_{2, 113}=3.71, p=.03). PSQI score explained variability in HR change above and beyond MEQ, with worse sleep associated with a larger change in HR in response to the CPT (See Appendix). PSQI score and MEQ did not explain significant variability in GSR change, EMGF change, or skin temperature change.

1.4. Discussion

1.4.1. Conclusions

Consistent with previous research, we found worse perceived sleep quality to be associated with lower pain tolerance (Lautenbacher et al., 2006; Sivertsen et al., 2015). However, this study did not find evidence to support a direct link between sleep quality and pain sensitivity. This finding may be due to relationships among sleep quality and psychological dimensions such as self-efficacy. Those with worse sleep may have experienced similar levels of pain intensity but lower pain tolerance due to a lack of self-efficacy and a sense of control over pain. As noted in a review by Finan, Goodin, & Smith (2013), relationships between sleep, affect, and pain have been repeatedly demonstrated over the past decade. A common theory is that sleep quality impacts cognition and affect, which in turn impact our perception of pain and our sense of control over pain. Schlarb, Kulessa, and Gulewitsch (2012) found that students suffering from insomnia had significantly lower scores in self-efficacy. Pain tolerance may be more related to psychological dimensions such as self-efficacy than pain sensitivity. This may be reflected by the current study’s finding that sleep quality and pain tolerance were directly related while sleep quality and pain sensitivity were not.

While previous research has found evidence of a relationship between poor sleep and higher pain sensitivity (Agargun et al., 1999; Smith et al., 2009), a unique aspect of the current study that may account for our difference in findings is the adjustment for opioid use. Specifically, a simultaneous regression of MEQ and PSQI scores significantly predicted pain sensitivity; however, when controlling for MEQ, PSQI was not a significant predictor of pain sensitivity. In previous studies that found a direct link between poor sleep and higher pain sensitivity, opioid use may have been an unidentified confounding variable. The consideration of opioid use in the current study is particularly important in light of previous research suggesting that opioid use can disrupt sleep architecture (Dimsdale et al., 2007). Given the detrimental relationship between opioid use, sleep, and pain, it is apparent that opioid use is a likely risk factor for those with chronic pain. This is particularly relevant given the current lack of support for long-term analgesic efficacy of opioids in chronic pain populations (Chou et al., 2015) and evidence for opioid-related hyperalgesia (Wachholtz & Gonzalez, 2014, Wachholtz, Gonzalez, & Ziedonis, 2019). Specifically, those with long-term opioid use may be exacerbating their chronic pain via a double-edged sword of opioid-related sleep impairment and diminishing efficacy of opioid-related analgesia or increased hyperalgesia.

Our finding that worse perceived sleep quality was associated with a greater HR change from baseline to the CPT is consistent with previous research indicating that habitual poor sleep is linked with higher ANS stress reactivity (Meerlo et al., 2008, Nano et al., 2017). Chronic sleep disruption may lead to gradual changes in the brain and, in turn, stress reactivity systems (Meerlo et al., 2008). Unlike in previous research, accounting for opioid use in this study removed opioid dosage as a potential confounding variable in the link between poor sleep and higher HR reactivity to the CPT.

A particularly interesting finding in our study was the association between poor sleep quality and lower baseline GSR. Liu, Zhou, Liu, & Zhao (2015) found similar results in a study of 12 healthy males with good sleep habits and sleep quality, in which participants underwent counterbalanced sleep deprivation and social isolation conditions. Specifically, the authors found that 72 hours of sleep deprivation resulted in significantly increased HR, decreased HR variability, and depressed GSR compared to baseline measures taken prior to sleep deprivation. Similarly, Johnson, Slye, & Dement (1965) found decreased GSR with 24 hours of sleep deprivation, an effect that held with 264 hours of sleep deprivation in a case study of a previously healthy sleeper. It is important to acknowledge a population difference in previous sleep quality between these studies and the current study; specifically that the previous study populations consitsted of healthy/good sleepers and the current study population consisted of individuals with chronic low-grade sleep difficulites. Possible explanations for increased autonomic reactivity (e.g., HR) accompanied by depressed baseline GSR may involve overall physiologic exhaustion of the body. For example, chronic sleep disruption may lead to chronic elevations of sympathetic stress responses, which may lead to sympathetic fatigue or burnout, resulting in dysfunctional autonomic activity (Meerlo et al., 2008). Importantly, more studies need to be run on potential sympathetic burnout related to chronic sleep disruption and stress. Future studies should focus on different responses among specific physiologic measures (e.g., HR, HR variability, blood pressure, cortisol measures, and GSR).

While worse sleep was associated with lower baseline GSR and greater change in HR, there were no other significant relationships between PSQI scores and physiological ANS measures after adjusting for MEQ. Combined with the association between PSQI score and pain tolerance, the lack of significant relationships between PSQI score and these physiological measurements may underscore the psychological dimension of pain tolerance. These findings together suggest that the link between PSQI score and pain tolerance involves psychological factors not detected by physiological measures. For instance, perceived sleep quality may affect or be affected by factors such as depression, anxiety, and/or self-efficacy, all of which may impact CPT pain tolerance. Such an explanation is consistent with other research suggesting that pain tolerance is related to both psychological and somatosensory experiences (Keefe, Abernethy, & Campbell, 2004; Wachholtz & Gonzalez, 2014).

1.4.2. Limitations and Future Directions

One limitation of the current study is that the PSQI uses retrospective self-report to measure sleep quality. PSQI scores could additionally be impacted by pain- and sleep-related factors, such as depression or anxiety. To more objectively assess sleep, future research should comprehensively assess sleep with objective measures such as polysomnography and actigraphy. In addition, the range of PSQI scores in the current study was limited, with no participants scoring below the clinical cut-off score of 5. Since chronic pain and opioid use can both negatively impact sleep, poor PSQI scores among this study’s participants are unsurprising. However, it is possible that a certain minimum quality of sleep is necessary for beneficial impacts on pain sensitivity to be detectable.

In addition, the correlational nature of this analysis prevents us from making any conclusions about causality. There are likely bidirectional relationships between all the variables studied, namely ANS functioning, sleep quality, pain response, as well as other variables not accounted for in this study. One particular area ripe for future research is differential autonomic responses in relation to sympathetic nervous system fatigue. Finally, future work will be needed to better understand the mechanisms underlying relationships among these variables and possible interventions to improve sleep and pain outcomes in chronic pain populations.

In summary, the current study sheds unique light on the relationship between sleep and experimentally induced pain in a general chronic pain population. We found that after adjusting for opioid use, worse perceived sleep quality was associated with lower pain tolerance but not associated with pain sensitivity or CPT pain rating. Worse perceived sleep was also associated with lower baseline GSR conductance and greater change in HR in response to the CPT, but not other physiological variables. Taken together, these findings may point to the importance of psychological dimensions of the pain experience and the complex psychological and physiological interactions among sleep quality, pain, and opioid usage.

Highlights.

• Worse perceived sleep quality was associated with lower acute pain tolerance in chronic pain patients after adjusting for opioid dosage.

• Worse perceived sleep quality was not related to higher pain sensitivity or acute pain ratings.

• After adjusting for opioid usage, worse perceived sleep in chronic pain patients was linked with lower baseline Galvanic Skin Response conductance and greater heart rate change between baseline and an acute pain task.