Pack-Years of Tobacco Cigarette Smoking as a Predictor of Spontaneous Pain Reporting and Experimental Pain Reactivity

Abstract

The pack-years formula is a widely used estimate of lifetime tobacco smoking exposure, and greater pack-years have been associated with greater risk of chronic pain development and poorer pain-related outcomes among smokers with chronic pain. The pathophysiology underlying these associations is poorly understood. Regular tobacco smoking exposure may dysregulate homeostatic pain processes, producing an allostatic state of pain facilitation. Maladaptive pain mechanisms, such as central and peripheral sensitization, are chronic pain risk factors. Yet, no published research has examined the relation between lifetime-smoking exposure and dysregulated pain processing. The current study used hierarchical linear regression analyses to test pack-years of tobacco smoking as a predictor of (1) pain reporting (current pain severity, pain frequency in the last 180 days) among a sample of 228 daily smokers without chronic pain, and (2) experimental capsaicin-induced pain reactivity (pain intensity, area of flare, mechanical pain sensitivity, and area of mechanical hyperalgesia) among 101 daily smokers without chronic pain. As hypothesized, results indicated that pack-years smoking was positively and significantly associated with current pain severity, past 180-day pain frequency, experimental pain intensity, mechanical pain sensitivity ratings, and area of mechanical hyperalgesia. Pack-years smoking was not significantly associated with neurogenic flare. These findings implicate central sensitization as a factor that may underlie the association between chronic tobacco smoking and increased risk for persistent pain.

Pack-Years of Tobacco Cigarette Smoking as a Predictor of Pain Reporting and Reactivity

Tobacco dependence and pain are both highly prevalent and co-occurring conditions, with a combined annual economic burden in excess of $800 billion in the United States alone (CDC, 2014; Gaskin & Richard, 2012; IOM, 2011; Tsang et al., 2008). These conditions may interact reciprocally, resulting in greater pain and the maintenance of tobacco dependence (Ditre, Brandon, Zale, & Meagher, 2011; Zale, Maisto, & Ditre, 2016). Smoking prevalence among individuals with co-occurring pain (e.g., 42–68%; Michna et al., 2004; Zvolensky, McMillan, Gonzalez, & Asmundson, 2009) may be greater than twice the rate observed in the general population (e.g., 15%; Jamal et al., 2016). Although nicotine has been shown to reduce pain in the short-term (Ditre, Heckman, Zale, Kosiba, & Maisto, 2016), long-term smoking has been implicated in the onset and progression of several chronically painful conditions (Shiri & Falah-Hassani, 2016; Shiri, Karppinen, Leino-Arjas, Solovieva, & Viikari-Juntura, 2010; Sugiyama et al., 2010). Despite these associations, research has yet to specify how regular tobacco use engenders pathological pain states.

A recently proposed allostatic load model of addiction and pain may account for how chronic substance use can lead to pain development (Egli, Koob, & Edwards, 2012). This model posits that repeated opponent process cycles of substance-induced analgesia and withdrawal-induced hyperalgesia may dysregulate overlapping neural substrates to produce an imbalanced state of pain facilitation (Egli et al., 2012; Koob & Le Moal, 1997; Koob & Le Moal, 2001). From this perspective, it could be hypothesized that chronic smoking dysregulates homeostatic pain mechanisms (i.e., endogenous pain facilitation/inhibition) to engender an allostatic state that over-facilitates pain signaling. Yet, no published research has examined the relation between lifetime-smoking exposure and dysregulated pain processing.

Research has implicated pack-years smoking as a unique risk factor in the development of persistent pain (Shiri & Falah-Hassani, 2016; Shiri et al., 2010; Sugiyama et al., 2010). The pack-years formula is a widely used estimate of lifetime smoking exposure that is calculated by multiplying the number of cigarette packs smoked per day by the number of years smoking (Bernaards, Twisk, Snel, Van Mechelen, & Kemper, 2001). Greater pack-years have been associated with increased pain intensity, frequency, and duration among smokers seeking treatment for chronic pain (Scott, Goldberg, Mayo, Stock, & Poitras, 1999). The risk for developing persistent pain also tends to increase as a function of greater pack-years (Deyo & Bass, 1989; Dube et al., 2015; Mikkonen et al., 2008; Pisinger et al., 2011; Scott et al., 1999; Sugiyama et al., 2010). These data are consistent with the notion that lifetime smoking exposure may dysregulate pain processes, and promote the transition from acute to chronic pain (i.e., pain that extends beyond the expected period of healing; Turk & Okifuji, 2001).

Despite empirical evidence suggesting that smoking causes pain (e.g., Shiri et al., 2010), the pathophysiological mechanisms underlying this relation are poorly understood. To inform intervention design, researchers have emphasized the importance of identifying dysregulated pain processes that increase the risk for persistent pain development (McGreevy, Bottros, & Raja, 2011). Current spontaneous pain reporting and experimental pain reactivity represent two complementary pain assessment methods that could inform our understanding of how chronic tobacco exposure may influence pain development. Current spontaneous pain reporting is readily assessed by asking smokers to rate the severity of pain they are experiencing right now (e.g., using numerical rating scales of current pain intensity), and to indicate the frequency with which they experience pain (e.g., number of days with pain). On the other hand, measuring psychophysiological reactivity to experimental pain induction yields insights into underlying mechanisms using laboratory methods (Arendt-Nielsen & Yarnitsky, 2009), including the current gold-standard approach of quantitative sensory testing (QST). Unlike self-reported pain ratings, QST employs highly standardized psychophysiological protocols to assess nervous system processes that underlie the experience of pain. QST evaluates both central and peripheral nervous system mechanisms using laboratory models that mimic painful conditions without causing lasting tissue damage (Edens & Gil, 1995). Given that peripheral and central sensitization are considered maladaptive neuroplastic mechanisms in the transition from acute to persistent pain (McGreevy et al., 2011), it is important to examine these processes among smokers who have not yet developed chronic pain

The current study examined pack-years of tobacco cigarette smoking as a predictor of current spontaneous pain reporting (Aim 1) and experimental pain reactivity (Aim 2) among daily cigarette smokers who do not have chronic pain. For Aim 1, we hypothesized that higher numbers of pack-years would predict greater current pain severity and greater frequency of pain during the last 180 days. In Aim 2, we hypothesized that greater pack-years would predict greater experimental pain intensity ratings, larger areas of neurogenic flare, greater mechanical pain sensitivity, and larger area of mechanical hyperalgesia. As an exploratory aim, alcohol consumption was tested as a moderator of the relations hypothesized in Aims 1 and 2. The allostatic load generated from co-occurring alcohol and tobacco use may be greater than the dysregulation caused by either drug alone. Accordingly, the effects hypothesized in Aims 1 and 2 may be more evident among smokers who reported greater alcohol consumption.

Method

Participants

Community participants were recruited to participate in a larger, two-session study that tested the effects of nicotine deprivation on experimental pain reactivity (Ditre et al., 2018). Respondents were screened by phone for the following inclusion criteria: (a) between 18–65 years of age; (b) currently smoking ≥ 15 cigarettes per day; and (c) ability to speak and read English. Respondents were excluded if they endorsed: (a) a current attempt to reduce or quit smoking; (b) current chronic pain; (c) current use of prescription pain medications; or (d) pepper allergy (contraindicated for capsaicin pain induction). Participants attended a baseline assessment and were subsequently randomized to one of three experimental conditions: continued smoking (N = 66), minimal 2-hour deprivation (N = 35), or extended 12–24 hour deprivation (N = 127).

The parent study included a minimal deprivation group to ensure that continued smokers were not experiencing acute nicotine analgesia. As expected, the primary study revealed no differences between the continued smoking and minimal deprivation groups on withdrawal or pain-related outcomes (Ditre et al., 2018). Findings from the parent study indicated that extended nicotine-deprivation significantly increased all measures of pain reactivity (Ditre et al., 2018). These observed effects would likely confound analyses aiming to examine associations between pack-years smoking and pain reactivity among daily smokers. Given that current spontaneous pain reporting was assessed at the baseline session of the larger study (i.e., prior to randomization to deprivation condition), Aim 1 analyses included the entire sample (N = 228). To examine pain reactivity as a function of lifetime smoking exposure, Aim 2 analyses excluded participants who were randomly assigned to the extended nicotine deprivation condition to avoid the aforementioned confounds. Thus, Aim 2 analyses included N = 101 participants who were randomized to either continued smoking (n = 66) or minimal deprivation conditions (n = 35).

Measures

Baseline assessment.

Demographic questionnaire.

Participants reported demographic information, including age, gender, race, ethnicity, education, employment status, and annual income.

Smoking questionnaire.

A smoking questionnaire assessed smoking history and current smoking status. Pack-years smoking was determined using two items where participants were asked, “For how many years, altogether, have you been a regular/daily smoker?” and “Since you started regular/daily smoking, what is the average number of cigarettes you smoke per day?” Consistent with previous research, pack-years was computed as: $\left(\frac{\text{cigarettes}\text{per}\text{day}}{\text{20}}\right)\text{×}$ years smoking (Deyo & Bass, 1989; Dubé et al., 2015; Mikkonen et al., 2008; Pisinger et al., 2011; Scott et al., 1999; Sugiyama et al., 2010). In past research, the pack-years calculation has demonstrated high test-retest reliability (ICC = .76; Brigham et al., 2009), and moderate to good relative validity when compared to prospective tobacco use estimates (κ = 0.79; Bernaards et al., 2001)

Alcohol Consumption.

The Alcohol Use Disorder Identification Test (AUDIT; Babor, Higgins-Biddle, Saunders, & Monteiro, 2001; Saunders, Aasland, Babor, De la Fuente, & Grant, 1993) is a 10-item instrument that assesses current (defined in this study as the last 12 months) risk for alcohol use disorder. Due to the aforementioned associations between alcohol-related factors, allostatic load, and dysregulated pain processing reported in the literature (Egli et al., 2012), we were primarily interested in testing the sub-domain of alcohol consumption (items 1–3) as a potential moderator of the effects hypothesized in Aims 1 and 2.

Aim 1 pain reporting outcomes.

Current spontaneous pain severity and frequency ofpain.

A single item from the Graded Chronic Pain Scale (GCPS; Von Korff, 2011) assessed current pain severity. Participants responded to the question “How would you rate your pain RIGHT NOW?” using a numerical rating scale that ranged from 0 (no pain) to 10 (pain as bad as it could be). Pain frequency in the last 180 days was assessed with another item that asked, “On how many days in the last 180 days (6 months) have you had pain?” (Von Korff, 2011).

Aim 2 experimental pain reactivity outcomes.

Experimental pain intensity.

Capsaicin-induced pain intensity was assessed using a visual analogue scale (VAS) that ranged from 0 (no pain) to 10 (pain as bad as you can imagine). Participants provided ratings at five-minute intervals, and area under the VAS curves (AUC) were calculated for each participant using the trapezoidal method (Matthews, Altman, Campbell, & Royston, 1990). Experimental pain intensity ratings provide a general measure of pain reactivity that involves peripheral conduction via afferent pain neurons (Schaible, 2006), and nociceptive processing in the central nervous system (Coghill, Sang, Maisog, & Iadarola, 1999).

Neurogenic flare.

Neurogenic flare was quantified as the area of visible skin inflammation (i.e., redness extending beyond the capsaicin application site; Helme & McKernan, 1985). Flare boundaries were traced and scanned to generate an area value in cm² (Helme & McKernan, 1985). Neurogenic flare is considered a measure of peripheral sensitization (Klede, Handwerker, & Schmelz, 2003), in that it reflects visible neuropeptide-induced vasodilation caused by peripheral C-fiber activation (Brain & Grant, 2004; Geber et al., 2007; Holzer, 1998; Schmelz, 2009).

Mechanical hyperalgesia.

Mechanical hyperalgesia (i.e., increased sensitivity to mechanical stimulation) was assessed using a 6.65 von Frey hair applied at points separated by 1 centimeter (cm) along 8 linear paths radiating from the application site to form 8 concentric von Frey rings (Modir & Wallace, 2010). Participants rated pain intensity at each point using a numerical rating scale ranging from 0 (no pain) to 10 (pain as bad as you can imagine). Two distinct measures of mechanical hyperalgesia were quantified. First, mechanical pain sensitivity was calculated as the AUC for each von Frey ring. Second, the area of mechanical hyperalgesia was computed by entering the boundaries of hyperalgesia (defined as the last 50% reduction in pain ratings along each von Frey path) into an established vector algorithm (Gottrup et al., 2004; Werner, Petersen, Rowbotham, & Dahl, 2013). Mechanical hyperalgesia is considered a measure of central sensitization (Klede et al., 2003) in that it reflects enhanced excitability of spinal dorsal horn neurons (Treede, Handwerker, Baumgärtner, Meyer, & Magerl, 2004), and the release of several pain-related neurotransmitters (i.e., glutamate, substance P, CGRP, somatostatin, and nitric oxide) at the central level (Sandkühler, 2009; Serra, Campero, & Ochoa, 1998; Ziegler, Magerl, Meyer, & Treede, 1999).

Procedure

The study was approved by the Institutional Review Board at Syracuse University (Protocol: Smoking and Mood Study - IRB#12–228). Individuals were recruited to participate in the parent study using internet and newspaper advertisements (Ditre et al., 2018). Eligible daily tobacco smokers attended a baseline session, where they provided informed consent, verified smoking status via exhaled carbon monoxide (CO ≥ 8ppm), completed measures of smoking history, spontaneous current pain reporting (Aim 1 outcomes), and other relevant variables (e.g., sociodemographic info). Participants were then randomized to 1 of the 3 experimental conditions, scheduled for an experimental session, and compensated $20. At the experimental session, participants completed pre-application measures, underwent a capsaicin QST pain reactivity assessment (Aim 2 outcomes), and completed post-application measures. Participants were then debriefed and compensated $80.

Experimental pain induction.

Experimental pain was induced using capsaicin, a vanilloid receptor agonist derived from chili peppers (Arendt-Nielsen & Andersen, 2005). The capsaicin QST model induces prolonged nociception that approximates clinical pain states (Arendt-Nielsen & Andersen, 2005; Benarroch & Low, 1991; Hsieh & Lin, 1999; Parkhouse & Le Quesne, 1988). A 10% capsaicin solution was applied to the non-dominant volar forearm via a 1.5cm x 1.5cm gauze pad (Baron et al., 1999). Capsaicin pain peaks in approximately 15–20 minutes (Geber et al., 2007; Petersen, Jones, Segredo, Dahl, & Rowbotham, 2001), and the substance was removed after 30 minutes.

Data Analytic Strategy

All statistical analyses were conducted using SPSS, version 24 (IBM, Armonk, New York). Bivariate correlations were performed to test zero-order associations among pack-years smoking, pain outcomes, sociodemographic factors, and AUDIT scores. Variables that were significantly associated with either the independent or dependent variables were considered for inclusion in subsequent analyses, as either covariates or potential moderators (Pocock, Assmann, Enos, & Kasten, 2002). Distributional assumptions were considered, and transformations (e.g., logarithmic, square root) were applied when indicated to improve data normality (Howell, 2012).

For Aim 1, separate hierarchical regression models were constructed to test each pain reporting outcome (current spontaneous pain severity, pain frequency in the last 180 days) among the entire sample (N = 228). Sociodemographic covariates were entered in the first step, and pack-years smoking was entered in the last step. For Aim 2 analyses, separate models tested each pain reactivity outcome (experimental pain intensity, area of flare, area of mechanical pain sensitivity ratings, and area of secondary hyperalgesia) among the non-deprived participants (N = 101). Sociodemographic covariates were entered in the first step, and the second step included procedural factors that may have influenced pain reactivity outcomes (i.e., time since last cigarette, room temperature). Pack-years smoking was entered into the final step of the models. The t test was used to determine the significance of each predictor, whereas change in R squared (ΔR²) and squared semi-partial correlations (sr²) were used to assess the relative contribution of pack-years smoking to the observed variance in pain outcomes. Cohen’s f² was used to characterize effect size, with .02, .15, .35 corresponding to small, medium, and large effects, respectively (Cohen, 1988). The AUDIT consumption subscale was explored as a moderator using the PROCESS Macro for SPSS (Hayes, 2013).

Results

Aim 1: Pack-Years Smoking and Spontaneous Pain Reporting

Participant characteristics.

In Aim 1, participants included 228 current daily tobacco smokers (42.1% female; M_age = 41.5, SD = 12.4), who reported smoking approximately 21 cigarettes per day (SD = 11) for an average of 24.4 years (SD = 12.3). The number of pack-years smoking for the sample ranged from 1.4 to 165, and had an average of 27.0 (SD = 23.2). The sample was predominately Caucasian (57.5%), and most participants had at least a high school education (76.8%). On average, participants reported experiencing pain on 44.2 days in the past 6 months. The sample yielded an average AUDIT score of 6.5 (SD = 7.7). Additional sociodemographic, pain, smoking, and drinking data are presented in Table 1.

Table 1.

Sociodemographic and Smoking Characteristics for Aim 1 and Aim 2 Samples

Participant Characteristics	Aim 1 Sample N (%)	Aim 2 Sample N (%)
Total Sample Size	228	101
Gender
Female	96 (42.1)	41 (40.6)
Income
<30K	169 (74.1)	81 (80.2)
30–50K	27 (11.9)	10 (9.8)
>50K	32 (14.0)	10 (10.0)
Education
Did not graduate high school	53 (23.2)	26 (25.7)
High school or part college	134 (58.7)	59 (58.4)
Technical school/Associates	27 (12.0)	9 (8.9)
Four-year college or more	14 (6.1)	7 (7.0)
Marital Status
Single	138 (60.5)	65 (64.4)
Married	36 (15.8)	13 (12.9)
Divorced/Other	54 (23.7)	23 (22.7)
Ethnicity
Hispanic/Latino	9 (3.9)	5 (5)
Not Hispanic/Latino	219 (96.1)	96 (95)
Race
Caucasian	131 (57.5)	51 (50.5)
Black/African American	89 (39.0)	47 (46.5)
Other	8 (3.5)	3 (3.0)
	M (SD)	M (SD)
Age	41.5 (12.4)	42.5 (12.9)
Pack-Years Smoking 1	27.0 (23.2)	26.9 (21.1)
Average Cigarettes Per Day	21.1 (11.0)	20.5 (10.3)
Years of Regular Smoking	24.4 (12.3)	24.8 (12.4)
AUDIT Total 2	6.5 (7.7)	6.0 (6.7)
Consumption	3.2 (3.2)	3.0 (2.9)
Dependence	1.3 (2.8)	1.2 (2.4)
Problematic Use	2.0 (3.3)	1.9 (2.8)

Note.

¹Pack-Years = $\frac{cigarettesperday}{20}\times yearssmoking$;

²Alcohol Use Disorders Identification Test.

Bivariate correlations.

The pack-years variable was log transformed before correlations and regressions were calculated. Pack-years smoking was positively correlated with current spontaneous pain severity (r = .22, p < .01), pain frequency in the last 180 days (r = .18, p < .01), and age (r = .69, p < .001). Pain frequency was correlated with alcohol consumption (r = .23, p < .01). Given known associations between age, smoking exposure, and pain (e.g., Scott, 1999), all Aim 1 analyses were designed to control for age.

Pack-years smoking and current spontaneous pain severity.

Results of the hierarchical regression analysis revealed that age did not account for a significant portion of the variance in current spontaneous pain severity ratings (Step 1: p = .62). As hypothesized, a positive and significant association between pack-years smoking and current pain severity was observed (Step 2: β= .30, p < .01, sr² = .05). Examining the ΔR² statistic at Step 2 revealed that pack-years accounted for approximately 5% of the unique variance in pain severity ratings, indicating an effect size (f² = .05) in the small to medium range.

Pack-years smoking and frequency of pain in the last 180 days.

Similar to the finding observed for current spontaneous pain severity, the results of separate hierarchical regression analyses indicated that pack-years smoking was positively and significantly associated with the frequency of pain in the last 180 days (Step 2: β= .30, p < .01, sr² = .02, f²= 02), even after controlling for age. The ΔR² value at Step 2 revealed that pack-years accounted for approximately 2% of the unique variance in reported pain frequency, indicating a small effect size (f² = .02).

Aim 2: Pack-Years Smoking and Experimental Pain Reactivity

Participant characteristics.

In the Aim 2 sample, participants included 101 daily tobacco smokers, who reported smoking an average of 20.5 cigarettes per day (SD = 12.9) for approximately 24.8 years (SD = 12.4). The number of pack-years smoking for the sample in Aim 2 ranged from 1.4 to 112.5, and averaged 26.9 (SD = 21.1). The sample was predominately male (59.4%) and Caucasian (50.5%). The sample yielded an average AUDIT score of 6.0 (SD = 6.7). Additional sociodemographic, smoking, and drinking data are presented in Table 1.

Bivariate correlations.

Before calculating correlations and regressions, square root transformations were applied to positively skewed area measurements of flare and mechanical hyperalgesia to improve normality. Log transformations were used to improve normality of mechanical pain sensitivity ratings for each of the von Frey rings. Pack-years of tobacco cigarette smoking was positively correlated with age (r = .75, p < .001) and mechanical pain ratings at the outermost (8^th) von Frey ring (r = .20, p < .05). Age was also negatively associated with area of flare (r = − .30, p < .01) and mechanical pain ratings at the innermost (1^st) von Frey ring (r = −.21, P < .05). Race was positively associated with area of flare (r = .48, p < .001), and negatively associated with mechanical pain ratings at the outermost von Frey ring (r = −.31 , p < .01) and time since last cigarette (r = −.20, p < .05). AUDIT consumption scores were negatively correlated with area of mechanical hyperalgesia (r = −.27, p < .01). Again, based on these observations, and known associations between age, smoking exposure, and pain (e.g., Scott, 1999), all Aim 2 analyses were designed to control for the influence of age. African Americans tend to show less hyperalgesia and neurogenic flare in response to the application of topical capsaicin, especially in comparison to Caucasian participants (Wang et al., 2010). Given that the current sample has a similar proportion of White and Non-White participants (47.5% African American), as well as the observed associations between race and pain outcomes, race was entered as a covariate in all Aim 2 analyses.

Experimental pain intensity ratings.

As seen in Table 2, results of hierarchical regression analysis revealed that neither age nor race accounted for a significant portion of the variance in experimental pain intensity ratings at Step 1 (p = .52). Experimental factors added in Step 2 (i.e., time since last cigarette and room temperature) did not account for a significant portion of the variance in pain intensity ratings either (p = .57). At Step 3 however, as hypothesized, the analyses revealed a positive and significant association between pack-years smoking and experimental pain intensity ratings (β = .51, p < .01, sr² = .11). Examination of the ΔR² statistic at Step 3 showed that pack-years smoking accounted for approximately 11% of the unique variance in pain intensity ratings, indicating an effect size (f² = .12) in the small to medium range.

Table 2.

Hierarchical Regression Model with Experimental Pain Intensity Entered as the Criterion Variable

	ΔR2	ϐ	t	sr2	p
Step 1	.01				.52
Age		−.11	−1.10	.01	.28
Race		−.04	−0.38	.00	.71
Step 2	.01				.57
Age		−.13	−1.28	.01	.21
Race		−.01	−0.10	.00	.93
Time Since Last Cig.		.07	0.63	.00	.53
Room Temp (°F)		−.09	−0.86	.00	.39
Step 3	.11				.00**
Age		−.52	−3.49	.11	.00**
Race		−.08	0.80	.00	.42
Time Since Last Cig.		.08	0.79	.00	.43
Room Temp (°F)		−.06	−0.06	.00	.57
Pack-Years		.51	3.47	.11	.00**

Note. N = 101. ΔR²= change in R²; ϐ = standardized beta weights; sr² = squared semi-partial correlations.

^*p < .05,

^**p < .01,

^***p < .001

Neurogenic flare.

Hierarchical regression analyses revealed that both age and race accounted for a significant portion of variance in area of flare measurements at Step 1 (p = .00). Whereas age (p = .00), race (p = .00), and room temperature (p = .02) accounted for a significant portion of variance in flare measurements at Step 2, time since last cigarette did not (p = .88). At Step 3 however, no association was observed between pack-years smoking and area of flare (β = .11, p = .38, sr² = .01).

Mechanical pain sensitivity.

As seen in Table 3, Step 1 of the hierarchical regression model revealed that neither age nor race accounted for a significant portion of variance in the mechanical hyperalgesia area measurements (p = .32). Whereas age (p = .57), race (p = .12), and time since last cigarette (p = .39) were not significant at Step 2, room temperature accounted for a significant portion of variance in mechanical hyperalgesia area measurements (p = .04). As hypothesized, Step 3 analyses revealed a positive and significant association between pack-years smoking and area of mechanical hyperalgesia, even after controlling for these relevant factors (Step 3: β = .30, p < .05, sr² = .04). Examining the ΔR² statistic at Step 3 revealed that pack-years of tobacco smoking accounted for approximately 4% of the unique variance in mechanical hyperalgesia area measurements, indicating an effect size (f² = .04) in the small to medium range. Separate hierarchical models revealed that pack-years smoking was positively and significantly associated with ratings of mechanical pain sensitivity at seven of the von Frey rings (p’s < .05), even after controlling for age, race, time since last cigarette, and room temperature. For these associations, the proportion of variance accounted for by pack-years smoking ranged from 4 – 8%.

Table 3.

Hierarchical Regression Model with Area of Mechanical Hyperalgesia Entered as the Criterion Variable

	ΔR2	β	t	sr2	p
Step 1	.02				.32
Age		−.07	−0.67	.00	.50
Race		−.14	−1.40	.02	.16
Step 2	.05				.09
Age		−.06	−0.58	.00	.57
Race		−.16	−1.56	.02	.12
Time Since Last Cig.		.09	0.86	.01	.39
Room Temp (°F)		.21	2.07	.04	.04*
Step 3	.04				.04*
Age		−.29	−1.85	.03	.06
Race		−.20	−1.91	.04	.05
Time Since Last Cig.		.10	0.94	.01	.35
Room Temp (°F)		.23	2.28	.05	.03*
Pack-Years		.30	2.03	.04	.04*

Note. N = 101. ΔR²= change in R²; β = standardized beta weights; sr² = squared semi-partial correlations.

^*p < .05,

^**p < .01,

^***p < .001

Moderator Analysis

The AUDIT alcohol consumption subscale was explored as a moderator of the associations between pack-years smoking and pain outcomes in Aims 1 and 2. Analyses revealed no moderation effects of alcohol consumption on any of the associations tested in either sample (p’s > .05).

Discussion

The current study investigated pack-years, an index of lifetime tobacco smoking exposure, as a predictor of pain reporting (i.e., current pain severity and frequency) and experimental pain reactivity (i.e., pain intensity, neurogenic flare, and mechanical hyperalgesia) among smokers without chronic pain. Pack-years smoking was positively and significantly associated with greater current spontaneous pain severity and frequency of pain in the past 180 days. Pack-years accounted for 2 – 5% of the variance in these outcomes, indicating effect sizes in the small to medium range. These findings highlight the relevance of smoking and pain relations, even among those without chronic pain. A higher number of pack-years smoking was also associated with greater capsaicin-induced pain intensity, heightened mechanical pain sensitivity, and larger areas of mechanical hyperalgesia. For these associations, pack-years accounted for proportions of variance that ranged from 4 – 11%, indicating small- to medium-sized effects. As such, this study provides initial evidence for an exposure-response relation between lifetime tobacco smoking exposure and dysregulated pain processes, primarily at the central level. Pack-years was not significantly associated with neurogenic flare, an index of peripheral sensitization. Taken together, these data implicate central sensitization as a relevant factor to consider in the relation between chronic tobacco smoking and increased risk for persistent pain development.

Nicotinic acetylcholine receptors (nAChRs) are widespread throughout central regions associated with pain transmission (e.g., spinal dorsal horn, locus coeruleus, thalamus; Shi et al., 2010). Nicotine-induced nAChR activation results in the release of endogenous opioids and norepinephrine, which alter central pain facilitation and/or inhibition (Shi et al., 2010). An allostatic load model of substance use and pain (e.g., Egli, Koob, & Edwards, 2012) would posit that chronic tobacco use may dysregulate these central mechanisms to engender a persistent imbalance towards pain facilitation. Consistently, the current results provide evidence for enhanced facilitation of pain transmission at the central level as a function of smoking chronicity.

The results implicating central sensitization may be clinically relevant. Central sensitization, a chronic pain-risk factor, may be potentially modified using pharmacological and behavioral strategies. Pharmacological research has shown that NMDA antagonists (e.g., Ketamine) inhibit central sensitization (McGreevy et al., 2011). Additionally, a brief Cognitive Behavioral intervention for pain has been shown to significantly reduce secondary hyperalgesia (i.e., central sensitization) in healthy human subjects undergoing an experimental pain task (Salomons, Moayedi, Erpelding, & Davis, 2014). Reducing central sensitization in chronic tobacco smokers may mitigate the risk of persistent pain development following an acute injury.

Recovery from the effects of chronic nicotine exposure may improve pain pathophysiology in the long-term (Shi et al., 2010). If chronic smoking engenders an allostatic state of pain facilitation, then removing this potential cause may improve efforts to reduce maladaptive sensitization. Nonetheless, tobacco cessation alone may not be enough to mitigate the effects of chronic smoking, which have been shown to produce persistent alterations in nervous system functioning that can endure long after cessation (Perkins et al., 2001). Combining smoking cessation interventions with targeted pain treatments may improve outcomes for both (Ditre et al., 2011; Zale et al., 2016). Integrated treatments, such as Cognitive Behavioral Therapy for pain and smoking cessation (Zale et al., 2016), and tailored nicotine replacement therapies that confer analgesic effects in smokers with pain (Ditre et al., 2016), have been proposed. Although smokers with co-occurring pain may benefit from these types of tailored interventions (Ditre et al., 2011; Zale et al., 2014), the current study also has implications for smokers who have not yet developed pain. Providers may deliver brief psychoeducational interventions that inform patients about the interrelations between smoking and pain, including how smoking exposure is associated with increased pain sensitivity, dysregulated pain processing, and greater risk for chronic pain development. Further study of the pathophysiological mechanisms underlying the association between tobacco smoking and pain development could ultimately inform clinical interventions that aim to break the causal chain.

The current study had notable strengths. The recruitment of a relatively large community sample of daily tobacco smokers was beneficial, for both external validity and statistical power in the primary aims. By examining these associations in a sample without chronic pain, hypotheses about the transition to persistent pain in smokers may be advanced. Employing sophisticated QST methods permitted various mechanistic insights that likely have implications for the study, prevention, diagnosis, and treatment of pain in tobacco smokers.

Despite its strengths, several limitations should be considered. The retrospective pack-years calculation may be susceptible to recall errors (Bernaards et al., 2001; Brigham et al.,2009). The equation can generate similar values for individuals with disparate smoking histories. It also has limited precision, and does not account for quit attempts, periods of abstinence, or other forms of tobacco use (e.g., cigar smoking). Yet, the pack-years calculation remains a commonly used estimate of lifetime smoking exposure, which cannot be quantified by singular tobacco use variables (e.g., cigarettes per day; Bernaards et al., 2001; Brigham et al., 2009). The pack-years index has demonstrated good reliability and validity in previous research (Brigham et al., 2009; Bernaards et al., 2001). Although this was a preliminary investigation, pack-years demonstrated utility for predicting numerous pain outcomes. More precise measures of lifetime tobacco use may enhance predictive validity and improve the accuracy of estimates in future research. Our sample consisted of daily tobacco users who reported smoking at least 15 cigarettes per day. Future research should examine these processes among lighter and intermittent smokers to enhance external validity. Former smokers should also be examined to determine the extent to which indicators of allostatic load have persisted or alleviated post-cessation. This was a cross-sectional, observational study, and therefore it is not possible to make inferences about the dynamics of relations among variables. Future research may benefit from the application of prospective designs that assess pain reactivity closer to the onset of smoking to examine pathophysiological changes over time. Standardized pain induced in a laboratory differs from pain occurring in other contexts (e.g., clinical setting), which may limit the generalizability of outcomes associated with these models (Edens and Gil, 1995). Nonetheless, clinical pain often covaries with numerous confounding factors (e.g., depression), whereas experimental pain induction reduces threats to internal validity while providing useful measures of pain nervous system functioning (Olesen et al., 2012; Reddy et al. 2012). Finally, many relevant factors were precluded from analyses because they were not measured in the parent study. For example, although past-year alcohol consumption was assessed using the AUDIT, use of additional substances was not measured. Thus, a remaining question is whether other substance use behaviors influence the relations observed in this study. After all, tobacco smoking and other drug use often covary. However, several factors increase our confidence that the associations identified in this study were specific to tobacco use. People with a history of illicit or recreational drug use were excluded during screening to enhance internal validity. Additionally, alcohol consumption was not significantly correlated with pack-years in either of our samples, and was not a moderating factor for any of the tested associations. Nevertheless, interactions between lifetime use of tobacco and other substances may be more evident in larger samples with greater polydrug use, and should be investigated in future studies. Furthermore, it would be beneficial to use comprehensive substance use assessments, including lifetime use measures (e.g., Concordia Lifetime Drinking Questionnaire; Chaikelson, Arbuckle, Lapidus, & Gold, 1994) and bioverification tests (e.g., urine toxicology). The current study was also limited in its ability to account for independent relations among comorbid conditions and pain outcomes, given that the parent study did not collect detailed histories of psychological and medical conditions from participants. Future research should assess these factors to reduce threats to internal validity.

This study provides preliminary evidence of dysregulated pain processing as a function of lifetime smoking exposure among a non-pain sample. Although smoking contributes to chronic pain development, poor pathophysiological understanding of this association remains a critical barrier to pain prevention and treatment (Shi et al. 2010). Identifying dysregulated pain processes in smokers would allow researchers to examine how these neuroplastic mechanisms can be modified using interventions.

Public Health Significance:

This study showed that pack-years of tobacco smoking was positively and significantly associated with current pain severity, past 180-day pain frequency, experimental pain intensity, and mechanical hyperalgesia. The current study provides preliminary evidence of dysregulated pain processing as a function of smoking exposure among a non-pain sample. Prevention and intervention approaches that target maladaptive pain processes in smokers may reduce the risk for chronic pain development.