Interconnections Between Chronic Lower Back Pain and Smoking: A Systematic Review

Chronic Lower Back Pain (CLBP) is a prevalent condition with complex causal interactions, with significant impact on public health and economic systems globally [1]. As one of the leading causes of disability, CLBP is a complex problem, with the intersection of biophysical, psychosocial and environmental factors being implicated in its etiology and long-term persistence. The chronic nature of lower back pain has been linked to a plethora of risk factors, among which smoking has been hypothesized as a causal factor [2]. While the association between smoking and many health outcomes is well known, the complete explanations of the mechanisms and magnitude of effect that smoking has on CLBP remain to be unraveled [3].

Literature proposes several hypotheses on how smoking can exacerbate or initiate the development of CLBP. These involve smoking-induced vascular changes, alteration in pain processing and nicotine effects on disc degeneration and connective tissue [4]. Moreover, smoking has also been associated with systemic inflammatory processes and oxidative stress, which may augment nociceptive pathways. Conversely, CLBP itself may influence smoking behavior, potentially creating a bidirectional relationship that complicates individual prognosis and treatment [5].

Extensive empirical literature has characterized the therapeutic efficacy of physical exercise in the relief of low back pain (LBP), taking into account the multifactorial determinants of its causative determinants [5-7]. The pathophysiology of LBP is established as a multifactorial interaction between genetic determinants, biomechanical and demographic factors (e.g., age, gender and history of prior lumbar trauma), psychological states (e.g., chronic stress, anxiety and fear of movement) and different lifestyle habits (especially, alcohol consumption and tobacco smoking) [8-9].

In the recent scientific literature, the relationship between nociception, nicotine use and smoking behavior has been widely discussed because of its prevalence, public health relevance and secondary health effects [10]. More recent evidence show that almost sixty percent of tobacco-dependent patients have symptoms typical of chronic pain syndromes [11]. Previous studies have proven correlation where current or former smokers have reported greater and more extensive pain compared to people who never smoked [12].

In spite of the credible mechanisms at the biological level, the epidemiologic evidence is heterogeneous. The studies have differed in design, population, exposure and outcome measurement and control for confounders [9-12]. The heterogeneity has presented a range of reported associations, from strong to minimal or no significant relationship between CLBP and smoking. The strengths of smoking as a modifiable lifestyle factor present a window of opportunity for intervention strategies that can reduce the burden of CLBP [5, 7]. An understanding of how large and what kind of its association with CLBP is necessary for the formulation of overall treatment strategies, which may incorporate smoking cessation interventions in addition to traditional pain treatment therapies.

Against this background, the current systematic review aims to critically evaluate and summarize the available evidence on the relationship between smoking and CLBP. In a critical examination of the cumulative evidence of prior studies, the review also aims to explore the contribution of smoking towards the aetiology and causes of CLBP. The review aims to establish trends, strength of association and presumable causation relationship as a means of improving knowledge in CLBP as well as supplying evidence-based information for practice and public health intervention.

Eligibility Criteria

This review utilised the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines [13], ensuring a structured and transparent approach to the review process. Initially, a comprehensive search strategy was formulated and applied across multiple databases to capture all relevant studies published from 2014 onwards.

For the PECO (Population, Exposure, Comparator, Outcome) protocol of this review, the following criteria were established:

• Population: Adults with chronic lower back pain, defined as pain persisting for more than 12 weeks
• Exposure: Smoking, including current and former smokers, with the consideration of smoking intensity and duration
• Comparator: Non-smokers or individuals with different levels of smoking exposure, to identify the gradient effect of smoking on CLBP
• Outcome: The primary outcome of interest was the presence and severity of chronic lower back pain. Secondary outcomes included the impact of smoking cessation on CLBP and the relationship between smoking and other clinical features of CLBP, such as disability and quality of life

Table 1 elucidates the inclusion and exclusion criterion that were devised for this investigation.

The decision to restrict the studies to those published after 2014 was a conscious one that directly responded to the goals of our review. By restricting the literature to recent years, the review aimed to capture the most up-to-date evidence and advances in the field, including methodological innovations and new knowledge of the link between smoking and CLBP. The limitation by timespan was aimed at ensuring that the review captured current knowledge and practice and offered a modern and relevant synthesis of evidence to inform clinical decision and the guidance of future research. The cut-off was chosen to cover a timespan broad enough to encompass recent studies but representative of the status of research at the time that this review was being conducted.

Database Search Protocol

Databases that were searched for this review included MEDLINE on PubMed, EMBASE, PsycINFO, Scopus, Web of Science, CINAHL, the Cochrane Library and Google Scholar and all were searched with relevance to studies for the purpose of our review. The search strategy was optimized to take advantage of the best features of each database's index systems, using a combination of Boolean operators and Medical Subject Headings (MeSH) terms and database-specific keywords. The search string was constructed such that Boolean operators were employed, i.e., "AND" between dissimilar ideas and "OR" to cover variations and synonyms related to the same idea. Keywords and MeSH terms were selected wisely to cover the regions of "chronic lower back pain" and "smoking." Search strings were constructed to be compatible with the various syntax and subject headings of different databases while the conceptual similarity of all the searches was maintained (Table 2).

Data Extraction Protocol and Items Selected

The protocol was executed by a pair of independent reviewers who extracted the data using a standardized data extraction form. Discrepancies between reviewers were resolved through discussion or consultation with a third reviewer. The data extraction form was pretested on a subset of included studies to confirm its comprehensiveness and functionality.

Table 1: Selection criterion utilised for the inclusion of relevant studies

Table 2: Databases assessed for selection of articles in this review

The form was refined accordingly before its application to the full set of included studies. The extracted data items encompassed:

• General information: Bibliographic details such as the title, authors, year of publication, country of origin and journal were recorded to provide the reference for each study
• Study characteristics: Methodological aspects, including study design (e.g., cross-sectional, cohort, case-control, or clinical trial), setting, duration of follow-up (if applicable) and sample size were captured
• Population details: Characteristics of the study population such as age, sex and baseline health status, including specific inclusion and exclusion criteria for participants, were documented
• Exposure assessment: Information on how smoking status was measured, including definitions of smoking categories (e.g., current, former, never-smoker) and quantification of smoking exposure (e.g., pack-years, smoking duration) were extracted
• Outcome measures: The primary and secondary outcomes related to chronic lower back pain, including pain severity, functional disability, quality of life and any other reported outcomes, were detailed along with the methods of measurement and time points recorded
• Key conclusions: The main findings of the study as concluded by the authors were summarized

Bias Assessment Protocol

For cross-sectional studies, the Appraisal Tool for Cross-Sectional Studies (AXIS) was used [14]. AXIS contains several components that assess several facets of a study, from its objectives to its design, sampling, methods of data collection, analysis and reporting. Each component is constructed to identify possible sources of bias, such as selection bias, information bias and confounding. For non-randomized studies by exposures, the Risk Of Bias In Non-randomized Studies - of Exposures (ROBINS-E) tool [15] was used. This tool is specifically constructed to evaluate the risk of bias in studies that investigate the effect of exposures on health outcomes.

Measurement Of Certainty Bias

Once the bias assessment for each individual study was completed, the reviewers applied the GRADE approach [16] to evaluate the overall body of evidence in relation to each primary outcome of interest. The GRADE approach considers a range of factors, including risk of bias, inconsistency, indirectness, imprecision and publication bias. Each of these factors has the potential to necessitate downgrading the quality of evidence. The reviewers started grading the quality of evidence for each outcome as 'high' by default, according to standard procedures in the GRADE system. They then reviewed the outcomes of the AXIS [14] and ROBINS-E assessments [15] to identify any issues with the risk of bias of the studies. Studies with high or critical risk of bias were reasons for downgrading the quality of evidence based on the GRADE system.

Study Selection Schematics

The systematic review article selection process, in accordance with the PRISMA reporting, was carried out in phases. A broad search in various databases initially yielded the collection of 368 records and no other records were accessed from registers. Before proceeding with the screening step, duplicates were eliminated carefully and 42 records were excluded. After duplicate removal, 326 records proceeded to the screening step. In the screening step, a large number of records, i.e., 55, were excluded as there was no full text mentioned. This led to the retrieval of 271 reports. All the same, challenges were encountered as 38 of these reports could not be retrieved due to various reasons. Consequently, the number of reports under consideration for eligibility dropped to 233.

The process of determining eligibility included an exhaustive review phase, with a large number of reports excluded according to the predetermined criteria: 43 reports did not include the predetermined PECO criteria; 38 reports were not relevant to the subject area; 42 were individual case reports and not suitable to be included in the systematic review; 22 were scoping reviews and 19 literature reviews, both being excluded in order to include only primary research studies and 61 studies were published before 2014, a year presumably selected as a cut-off point for relevance or methodological consistency. After this rigorous process of exclusion, 8 studies [17-24] met all the criteria and were thus included in the systematic review (Figure 1).

Figure 1: Article selection process representation of the review

Assessed Bias Observations

For the cross-sectional studies (Figure 2), Beyera et al. [17] demonstrated a low risk of bias in most categories including selection, detection, attrition, reporting and other biases, while performance and attrition biases were assessed as moderate. Choi et al. [18] had a moderate risk of bias in the selection and detection categories, a low risk in performance, attrition and other biases and a moderate risk in reporting. Depintor et al. [19] showed a low risk across selection, performance, detection, attrition and other biases but had a moderate risk in reporting, resulting in an overall moderate bias rating.

Figure 2: Bias observations as per the AXIS tool

Green et al. [20] exhibited a moderate risk of bias in selection and performance, but a low risk in the other areas, culminating in an overall low risk of bias. Schembri et al. [21] maintained a low risk in most categories, with the exceptions of moderate risks in performance and reporting. Schembri et al. [22] had a similar profile to Green et al. [20], with moderate risks in selection and other biases, but otherwise low risks, leading to an overall moderate risk of bias assessment. Yang et al. [24] showed a low risk in most areas but moderate risks in performance and detection. For the cohort-based study by Xu et al. [23] assessed with the ROBINS-E tool (Figure 3), the study was found to have a low risk of bias in most domains, except for moderate risk in domains D3 and D7, which did not significantly affect the overall low risk of bias rating for the study.

Figure 3: Bias observations as per the ROBINS-E tool

Baseline Characteristics Assessed

In the synthesis of demographic data of studies incorporated herein [17-24] as described through Table 3, cross-sectional method was the prevalent approach [17-22, 24], with one cohort-based protocol [23]. Sample sizes were relatively varied, ranging from a minimum of 54 participants in a study that sought to investigate the implication of smoking status on CLBP to a maximum of 438, 510 participants in a cohort study most likely to provide a broad overview of the studied condition, conducted in 2023 [23-24]. The year of implementation of studies varied from 2016 to 2023, representing a recent and perhaps evolving understanding of the study conditions [19-20, 23]. Regional heterogeneity was noted and reported, with studies having been conducted in Ethiopia, China, Brazil, the United States and Malta, which may represent different environmental, genetic and sociocultural factors influencing the study findings [17-22].

The mean ages of the participants also varied, with one study reporting a mean age higher than 18 years and another reporting mean ages in smokers and non-smokers separately, suggesting the impact of smoking on onset or severity of CLBP [20-21]. The male to female ratios were also reported in all except two Maltese studies, where demographic information was not specified [21-22]. Interestingly, in the largest cohort study, the mean ages of males and females were reported separately, suggesting a detailed consideration of effects due to age in the results reported [23]. The gender ratio was also imbalanced with higher representation of females in some studies, perhaps suggesting the reported or actual higher prevalence of CLBP in females or may be simply an artefact of sampling biases [18-20]. The smallest sample study addressed the smoking group and reported mean ages of smokers and non-smokers separately, which may suggest information on the effect of lifestyle factors on CLBP [24].

Table 3: Demographic characteristics observed in the included studies

Groups and Parameters Assessed

Table 4 outlines the varied variables in accordance with the association of LBP with cigarette smoking. In the work of Beyera et al. [17], 18+ adults with LBP were interviewed on a very extensive range of factors, encompassing socio-demographic data, health behavior and lifestyle, ideas about pain and other general and pain-specific health factors. The wide nature of the information gathered enabled multifaceted LBP research to be conducted with this population. Choi et al. [18] sampled patients in the Korea National Health and Nutrition Examination Survey and studied health and nutrition status. Notably, the study factored in the levels of stress and environmental components such as smoking, which were identified to affect health outcomes severely.

Depintor et al. [19] conducted an evaluation on a population of 826 patients using various well-documented tools. The assessment included the Hospital Anxiety and Depression Scale (HADS), EuroQol-5D, Alcohol Use Disorders Identification Test (AUDIT) and the Fagerström test for nicotine dependence, supplemented by a Brazilian economic classification tool. Collectively, these evaluations offered valuable information regarding the mental health, quality of life, substance use and socioeconomic status of low back pain (LBP) patients. In another study, Green et al. [20] conducted a comprehensive evaluation on 34,525 American adults. The study centered on the investigation of the prevalence of back pain across different alternative smoking statuses and quantified the level of cigarette smoking, which may indicate the association between smoking behavior and LBP prevalence.

In the work of Schembri et al. [21], the two groups were compared in 120 chronic low back pain (LBP) patients and 50 control subjects. Pain intensity, Douleur Neuropathique 4 (DN4) questionnaire scores, STarT Back screening tool and Fagerström test for nicotine dependence were assessed to determine pain experience and related factors in the two groups. Schembri et al. [22] also researched an exact population with 150 chronic LBP patients (mean age: 60.1) and a control group of 50 subjects. Demographic information was gathered, the International Association for the Study of Pain (IASP) neuropathic pain grading system was used, the STarT Back screening tool was used, the Fagerström test for nicotine dependence was used and the aim was to determine neuropathic pain differences and other related attributes in chronic LBP subjects.

Xu et al. [23] performed a longitudinal study with the UK Biobank, tracking a large cohort of 438,510 individuals who were initially pain-free back between 2006 and 2010. The study quantified a number of factors, including Smoking Status (SS), Cigarettes per Day (CPD), Pack-Years (PY) and the incidence of back pain, thereby offering useful insights into the prospective longitudinal effect of smoking on the incidence of Low Back Pain (LBP). In another study, Yang et al. [24] targeted a smaller group of 54 Chronic Low Back Pain (CLBP) patients, classified according to their smoking status. This study quantified pain severity, functional capacity, psychological status and smoking behavior, offering a detailed analysis of the correlation of these factors specifically in the CLBP group and highlighting the contribution of smoking to these correlations.

Correlation Between LBP And Smoking Observed

Beyera et al. [17] did find smoking relatively rare in people with LBP and occurring in only 3.2% of instances. There was no apparent focus in the results on a correlation between LBP and smoking that would indicate other factors were perhaps more significant in developing LBP in this population. Choi et al. [18] listed smoking in a series of environmental variables in a multivariate regression analysis when they were examining the health and nutritional status of subjects. Smoking was not specifically referred to in the context of LBP, however, which would indicate that the correlation with stress factors was perhaps more significant in their research.

The study by Depintor et al. [19] found a statistically significant association between chronic back pain and smoking. Smoking subjects had a 41% higher likelihood of developing chronic back pain than non-smokers. This evidence supported by a 1.41 prevalence ratio and a 95% confidence interval of 1.06 to 1.88 and a p-value of 0.031, indicates the possible contributory role of smoking to the onset of chronic Low Back Pain (LBP). Green et al. [20], in another study, identified active smokers with the highest prevalence of back pain at 36.9%, followed by 33.1% for former smokers and 23.5% for never smokers. This nested pattern of observation demonstrates a dose-response effect of smoking to back pain incidence and positions current smoking as a stronger risk factor.

Table 4: Correlation between LBP and cigarette smoking as observed in the included papers

In the study by Schembri et al. [21], smokers experienced higher pain intensity and Douleur Neuropathique 4 (DN4) score, a neuropathic pain measure. This suggests the correlation between smoking intensity and increased risk for chronic Low Back Pain (LBP) and neuropathic leg pain and that higher smoking intensity has the potential to worsen pain symptoms. Schembri et al. [22] also found a difference between active smokers and non-smokers in the chronic LBP population. Smokers were more likely to experience chronic LBP and sciatica, with higher Fagerström scores being correlated with having a higher chance of chronic LBP and neuropathic pain. This highlights the deleterious effects of smoking on the prevalence and severity of chronic LBP and related neuropathic disorders.

Xu et al. [23] showed that ex- and current smokers had a higher prevalence of back pain compared to never-smokers. Hazard ratios (HRs) for back pain rose with Cigarettes per Day (CPD) and Pack-Years (PY) intake, more so in female smokers, who were at higher risk than male smokers. This again supports the evidence that smoking is a modifiable risk factor for causation of LBP. Yang et al. [24] found that higher daily cigarette intake was linked with higher pain, depression and work impairment in CLBP patients. This indicates that not only is smoking linked with the severity of pain endured but that it also has far-reaching effects on mental health and daily function.

Table 5: GRADE assessment observations

GRADE Assessment Observations

Table 5 summarizes the GRADE certainty assessment for the studies included in the review. The body of evidence comprises seven cross-sectional studies and one cohort-based study, with the overarching inference being that a multitude of factors influence CLBP, with the role of smoking being variably significant. The risk of bias across most studies was considered 'low to moderate,' reflecting a generally robust methodological approach, although some concerns may still potentially affect the validity of the findings. The inconsistency was rated as 'low,' indicating that findings across the studies were sufficiently similar to suggest a degree of reliability.

The directness of the evidence was considered high, as the studies directly addressed the research question regarding factors associated with chronic LBP. The precision of the evidence was rated as 'moderate' for the cross-sectional studies, suggesting some uncertainty in the effect estimates, possibly due to variability in study sample sizes or measurement approaches. There were no additional considerations that affected the certainty of the evidence, such as publication bias, which was not reported. Therefore, the certainty of the evidence from the cross-sectional studies was rated as 'moderate,' while the evidence from the cohort study was rated as 'high,' given the longitudinal design's strength in establishing temporal associations.

The work of Depintor et al. [19], Green et al. [20], Schembri et al. [21], Schembri et al. [22], Xu et al. [23] and Yang et al. [24] all classify smoking as a causative risk factor in LBP causation and exacerbation, with the risk graded along intensity and longevity of smoking. These articles, to varying degrees, agree with one another on the conclusion that smoking is a modifiable LBP risk factor. Beyera et al. [17] and Choi et al. [18], however, deviate more from this group of articles in their attribution of lower importance to smoking and higher to other stress-associated and psychosocial determinants. Beyera et al. [17] defied the norm in that the article did not mention smoking as a common cause linked to the chronicity of LBP. Rather, psychosocial aspects like negative ideas about pain, general health state and depressive mood were singled out. Contrary to the majority of articles in the list, all which mentioned smoking as a major contribution to LBP, this differed.

Choi et al. [18], however, did find smoking in their multivariate analysis but eventually emphasized stress as the more significant factor in the context of chronic LBP. The emphasis of the study on stress is aligned with Beyera et al. [17] in the emphasis on non-smoking-related variables, which places both studies in opposition to the others that isolated smoking as a significant variable. Depintor et al. [19] and Green et al. [20] were in close agreement with their findings, with both studies finding smoking as a significant factor that was linked with chronic spinal pain and back pain, respectively. Green et al. [20] further quantified this, with a dose-response relationship between higher smoking exposure and higher back pain. These studies concur with the findings of Xu et al. [23], which also arrived at an association between smoking intensity, duration and risk of developing back pain.

Schembri et al. [21] and Schembri et al. [22] reported results with high levels of concordance, both showing the high correlation between smoking and severity of chronic LBP. Schembri et al. [22] also widened the scope by correlating the Fagerström score with greater severity of chronic pain, thereby proposing a causal relationship between nicotine dependence and severity of pain. Xu et al. [23] shared the universality of the studies by Green et al. [20], Schembri et al. [21] and Schembri et al. [22] in the identification of the causative role of smoking in back pain. Xu et al. [23] added the longitudinal aspect to the studies with a focus on the possible benefits of smoking cessation or reduction in the prevention of back pain. Yang et al. [24] offered a viewpoint that not only shares universality with the evidence of the relationship between smoking and severity of pain but also widens the scope by correlating heavier smoking with wider implications such as psychological distress and compromise of quality of life among chronic LBP patients.

Dai et al. [25] in their review had also reported that current smoking was linked with a higher risk of CMP, but interestingly, the strength of association was weaker for past smoking and ever-smoking. This indicates an active and continuous role of smoking in aggravating pain conditions, consistent with the findings of Green et al. [20], Schembri et al. [21] and Yang et al. [24] in our review that identified a gradient effect with increasing back pain corresponding to increased exposure to smoking and more smoking resulting in poorer outcomes in patients with chronic LBP. But Dai et al. [25] also observed that in certain strata, current smoking was not significant and there was even a negative association between cigarette smoking and the risk of knee pain. This is a more subtle finding that is opposite to the overall trend in our review where smoking was largely linked with poor pain outcomes.

Shiri et al. [26] noted the increased incidence and prevalence of LBP attributable to current smoking over different periods of time, from the previous month to consultation for chronic and disabling LBP. They noted that the prevalence of LBP was increased among former smokers compared with never smokers but was less than among current smokers, suggesting a dose-response association. This concurs with the findings of Green et al. [20], Schembri et al. [21] and Yang et al. [24], who all found a dose-response association and emphasized the deleterious effect of smoking on LBP. Furthermore, Shiri et al. [26] emphasized that the association between current smoking and LBP incidence was stronger among young people compared with adults. This specific age-related finding was not specifically noted in our review findings. However, the longitudinal method used by Xu et al. [23] in our review does echo the concept that smoking is associated with an increased risk of the development of back pain over a period of time, which could suggest an accumulating effect that could be more clearly observed when the onset of smoking is at a younger age.

Literature review shows that comparison with the study of Çelik et al. [27] is most appropriate. Their results showed that those with an indication of positive DN4 score, suggesting neuropathic pain, had greater cigarette use compared with those with a negative DN4 score. This is consistent with our results, which showed an increase in the mean overall DN4 score with increased daily cigarette use (p = 0.002). Differences between study design, including presentation of findings and comparison groups used, may account for the slightly different findings. Shemory et al. [28] showed a high relative risk for Low Back Pain (LBP) with nicotine dependence, but did not separate acute and chronic LBP and did not derive their diagnostic criteria for nicotine dependence, so direct comparison with our findings is not easy.

Shaw et al. [29] investigated men with acute LBP and identified increased risk of chronicity with nicotine dependence. Their employment of the Diagnostic Interview Schedule-III-R to determine nicotine dependence and investigation of primary LBP symptoms, however, differ from the methodology and goal of our investigation of chronic LBP and direct comparison is not possible. Zvolensky et al. [30] similarly identified increased risk of chronic neck or back pain in individuals with nicotine dependence, but employed the Composite International Diagnostic Interview to measure dependence and direct comparison is not possible.

In adjusting for smoking status, reviews from various authors [31-36] examined the interaction between LBP, sciatic pain and smoking but the lack of standardization of the definition of sciatica and the failure to examine a neuropathic pain component in the studies makes it hard to make direct comparison. This was actually noted by Cook et al. [34], who found that inconsistent definitions of sciatica might have a huge impact on the result of such studies. Parreira et al. [31] highlighted in their systematic review chronic LBP in twins, which found a significant association between smoking and LBP, similar to our study. The specificity of these findings to chronic LBP was, however, not stated explicitly and the definition of the most chronic symptom of LBP may influence the interpretation.

Clinical recommendations and future implications

The overall assessments obtained from this study underscored and emphasized the need to heed and attend to smoking as another crucial modifiable risk factor while treating and preventing CLBP. Evidence shows that this element not only predisposes but also worsens the suffering and impairments in all connected psychological and functional well-being components involved in CLBP. A well-coordinated intervention to reduce this prevalence of smoking among such at-risk individuals for and with CLBP is urged. Strategies for smoking cessation should be an element of holistic programs of pain management in populations with higher smoking intensity and longer durations, which are also elements of public health campaigns and clinical guidelines. This heterogeneity in regional, demographic and methodological factors across studies suggests the need for contextualized approaches in designing interventions. Further research to strengthen the causal inferences may involve further study on the dose-response relation between smoking and CLBP, specifically using longitudinal data. Other possible approaches might relate to understanding the interaction between smoking with other lifestyle or psychosocial factors so that their joint effect can more adequately elucidate its involvement in the pathophysiology of CLBP.

Clinicians should include assessments of smoking in routine evaluations of patients with CLBP and consider using validated measures to quantify intensity and dependence. Perhaps optimal patient outcomes will be attained through the collaborative work of the healthcare providers, pain specialists and smoking cessation programs attacking both the behavioral and the physical aspects of CLBP. Future studies should work towards bridging gaps in accuracy and explain mechanistic pathways through which smoking contributes to the induction and maintenance of pain, which may result in targeted pharmacologic or behavioral therapies.

The aggregate evidence from the reviewed papers suggests a significant correlation between smoking and the prevalence, severity and persistence of CLBP. Notably, the data pointed toward a dose-response relationship, where increased smoking intensity and duration were linked to heightened risk and exacerbation of CLBP symptoms. The findings indicated that smoking might not only be a contributing factor in the development of CLBP but also in the worsening of pain over time. The review revealed a consistent trend across diverse populations and methodologies, reinforcing the potential role of smoking as a risk factor for CLBP. The analyses also highlighted the multifactorial nature of CLBP, with psychosocial elements such as stress and depressive symptoms demonstrating a considerable influence on the chronicity of back pain. The potential for reverse causation, where the experience of CLBP could lead to increased smoking due to stress or coping mechanisms, was acknowledged, although not definitively resolved within the scope of the reviewed literature. Furthermore, while smoking emerged as a significant factor in the context of CLBP, the review's findings underscored the importance of considering a holistic approach that addresses both smoking cessation and the psychological aspects of chronic pain management.

Limitations

The limitations of this systematic review are primarily influenced the interpretation of the findings. One of the principal limitations was the decision to include studies published from 2014 onwards. This temporal restriction potentially excluded relevant earlier research that might have provided additional insights into the long-term trends and evolution of understanding regarding the association between smoking and CLBP. By focusing on more recent studies, the review may have overlooked foundational work or shifts in research paradigms that could inform current hypotheses and analytical frameworks. Furthermore, the heterogeneity in study designs, populations and methodological approaches made it challenging to compare results across studies directly. While the review attempted to synthesize available data, the variations in measurement tools for smoking and pain, as well as differences in controlling for confounding factors, may have contributed to inconsistent findings. For instance, the extent to which psychosocial factors were considered and adjusted for varied among the studies, as evidenced by the emphasis on such factors in the studies by Beyera et al. [17] and Choi et al. [18] as opposed to those where smoking emerged as a significant factor. This heterogeneity underscores the complexity of CLBP and suggests that its relationship with smoking may be influenced by an intricate interplay of biological, psychological and social elements. Additionally, the reliance on self-reported measures for smoking status and pain intensity in some studies could have introduced bias due to recall or reporting inaccuracies. Objective measures of smoking exposure and clinical assessments of pain would have strengthened the review's findings.

1. Maher, Chris et al. “Martin Underwood, and Rachelle Buchbinder. "Non-specific low back pain.” The Lancet, vol. 389, no. 10070, February 2017, pp. 736-747. https://www.thelancet.com/article/S0140-6736(16)30970-9/abstract.

2. Lawrence, Reva C. et al. “Estimates of the prevalence of arthritis and other rheumatic conditions in the United States: Part II.” Arthritis & Rheumatism, vol. 58, no. 1, January 2008, pp. 26-35. https://acrjournals. onlinelibrary.wiley.com/doi/abs/10.1002/art.23176.

3. Anders, Thelin et al. “Functioning in neck and low back pain from a 12-year perspective: a prospective population-based study.” Journal of Rehabilitation Medicine, vol. 40, no. 7, July 2008, pp. 555-561. https:// europepmc.org/article/med/18758673.

4. Vlaeyen, Johan W.S. et al. “Low back pain.” Nature Reviews, vol. 4, no. 1, December 2018. https://pubmed.ncbi.nlm.nih.gov/30546064/.

5. Peng, Meng-Si et al. “Efficacy of therapeutic aquatic exercise vs physical therapy modalities for patients with chronic low back pain: a randomized clinical trial.” JAMA Network Open, vol. 5, no. 1, January 2022, pp. e2142069-e2142069. https://jamanetwork.com/ journals/jamanetworkopen/article-abstract/2787713.

6. Wang, Rui et al. “Exercise for low back pain: A bibliometric analysis of global research from 1980 to 2018.” Journal of Rehabilitation Medicine, vol. 52, no. 4, April 2020, pp. 52-52. https://europepmc.org/ article/med/32296852.

7. Wang, Xue-Qiang et al. “Effects of whole-body vibration exercise for non-specific chronic low back pain: an assessor-blind, randomized controlled trial.” Clinical Rehabilitation, vol. 33, no. 9, May 2019, pp. 1445-1457. https://journals.sagepub.com/doi/abs/10.1177/ 0269215519848076.

8. Wang, Xue-Qiang et al. “A bioinformatic analysis of MicroRNAs’ role in human intervertebral disc degeneration.” Pain Medicine, vol. 20, no. 12, December 2019, pp. 2459-2471. https://academic.oup.com/pain medicine/article-abstract/20/12/2459/5430237.

9. Taylor, Jeffrey B. et al. “Incidence and risk factors for first-time incident low back pain: a systematic review and meta-analysis.” The Spine Journal, vol. 14, no. 10, October 2014, pp. 2299-2319. https:// www.sciencedirect.com/science/article/abs/pii/S152994301400103X.

10. LaRowe, Lisa R., and Joseph W. Ditre. “Pain, nicotine, and tobacco smoking: current state of the science.” Pain, vol. 161, no. 8, August 2020, pp. 1688-1693. https://journals.lww.com/pain/citation/ 2020/08000/pain,_nicotine,_and_tobacco_smoking__current_state.2.aspx.

11. Weinberger, Andrea H. et al. “Perceived interrelations of pain and cigarette smoking in a sample of adult smokers living with HIV/AIDS.” Nicotine and Tobacco Research, vol. 21, no. 4, April 2019, pp. 489-496. https://academic.oup.com/ntr/article-abstract/21/4/489/4830708.

12. Powers, Jessica M. et al. “Smokers with pain are more likely to report use of e-cigarettes and other nicotine products.” Experimental and Clinical Psychopharmacology, vol. 28, no. 5, October 2020. https://psycnet.apa.org/fulltext/2019-67904-001.html.

13. Page, Matthew J. et al. “The PRISMA 2020 statement: an updated guideline for reporting systematic reviews.” BMJ, vol. 372, March 2021. https://www.bmj.com/content/372/bmj.n71.short.

14. Downes, Martin J. et al. “Development of a critical appraisal tool to assess the quality of cross-sectional studies (AXIS).” BMJ Open, vol. 6, no. 12, 2016. https://bmjopen.bmj.com/content/6/12/e011458. short.

15. Lisa, Bero et al. “The risk of bias in observational studies of exposures (ROBINS-E) tool: concerns arising from application to observational studies of exposures.” Systematic reviews, vol. 7, December 2018. https://link.springer.com/article/10.1186/s13643-018-0915-2.

16. Howard, Balshem et al. “GRADE guidelines: 3. Rating the quality of evidence.” Journal of Clinical Epidemiology, vol. 64, no. 4, April 2011, pp. 401-406. https://www.sciencedirect.com/science/article/ pii/S089543561000332X.

17. Getahun Kebede, Beyera et al. “Profile of individuals with low back pain and factors defining chronicity of pain: a population-based study in Ethiopia.” Quality of Life Research, vol. 31, no. 9, May 2022, pp. 2645-2654. https://link.springer.com/article/10.1007/s11136-022-03148-5.

18. Sungwoo, Choi et al. “Association between chronic low back pain and degree of stress: a nationwide cross-sectional study.” Scientific Reports, vol. 11, no. 1, July 2021. https://www.nature.com/articles/s41598-021-94001-1.

19. Depintor, Jidiene Dylese Presecatan et al. “Prevalence of chronic spinal pain and identification of associated factors in a sample of the population of Sao Paulo, Brazil: cross-sectional study.” Sao Paulo Medical Journal, vol. 134, no. 5, 2016, pp. 375-384.

20. Green, Bart N. et al. “Association between smoking and back pain in a cross-section of adult Americans.” Cureus, vol. 8, no. 9, September 2025. https://www.cureus.com/articles/5220-association-between-smoking-and-back-pain-in-a-cross-section-of-adult-americans. pdf.

21. Schembri, Emanuel et al. “Is chronic low back pain and radicular neuropathic pain associated with smoking and a higher nicotine dependence? A cross-sectional study using the DN4 and the Fagerström Test for Nicotine Dependence.” Agri: Journal of the Turkish Society of Algology, vol. 33, no. 3, April 2023, pp. 155-167. https://jag.journal agent.com/agri/pdfs/AGRI_33_3_155_167.pdf.

22. Schembri, Emanuel et al. “Nicotine dependence and the international association for the study of pain neuropathic pain grade in patients with chronic low back pain and radicular pain: is there an association?.” The Korean Journal of Pain, vol. 33, no. 4, 2020, pp. 359-377. https:// synapse.koreamed.org/articles/1159166.

23. Xu, Hao-Ran et al. “Association between smoking and incident back pain: a prospective cohort study with 438 510 participants.” Journal of Global Health, vol. 13, November 2023. https://pmc.ncbi.nlm.nih.gov/ articles/PMC10663706/.

24. Yang, Qi-Hao et al. “Association between smoking and pain, functional disability, anxiety and depression in patients with chronic low back pain.” International Journal of Public Health, vol. 68, 2023. https:// www.ssph-journal.org/journals/international-journal-of-public-health/ articles/10.3389/ijph.2023.1605583/pdf.

25. Dai, Yan et al. “Association of cigarette smoking with risk of chronic musculoskeletal pain: a meta-analysis.” Pain Physician, vol. 24, no. 8, December 2021. https://www.painphysicianjournal.com/current/pdf? article=NzM2MA%3D%3D&journal=140.

26. Shiri, Rahman et al. “The association between smoking and low back pain: A meta-analysis.” The American Journal of Medicine, vol. 123, no. 1, January 2010. https://www.sciencedirect.com/science/article/abs/ pii/S000293430900713X.

27. Çelik, Sercan Bulut et al. “Evaluation of the neuropathic pain in the smokers.” Agri, vol. 29, no. 3, October 2017, pp. 122-126. https://jag. journalagent.com/z4/download_fulltext.asp?pdir=agri&plng=eng&un=AGRI-68815.

28. Shemory, Scott T. et al. “Modifiable risk factors in patients with low back pain.” Orthopedics, vol. 39, no. 3, 2016, pp. e413-e416. https:// journals.healio.com/doi/abs/10.3928/01477447-20160404-02.

29. Shaw, William S. et al. “Psychiatric disorders and risk of transition to chronicity in men with first onset low back pain.” Pain Medicine, vol. 11, no. 9, September 2010, pp. 1391-1400. https://academic.oup. com/painmedicine/article-abstract/11/9/1391/1859495.

30. Zvolensky, Michael J. et al. “Chronic pain and cigarette smoking and nicotine dependence among a representative sample of adults.” Nicotine & Tobacco Research, vol. 11, no. 12, October 2009, pp. 1407-1414. https://academic.oup.com/ntr/article-abstract/11/12/ 1407/1067364.

31. Ferreira, Paulo H. et al. “Nature or nurture in low back pain? Results of a systematic review of studies based on twin samples.” European Journal of Pain, vol. 17, no. 7, January 2013, pp. 957-971. https://onlinelibrary.wiley.com/doi/abs/10.1002/j.1532-2149.2012. 00277.x.

32. Parreira, Patricia et al. “Risk factors for low back pain and sciatica: An umbrella review.” The Spine Journal, vol. 18, no. 9, September 2018, pp. 1715-1721. https://www.sciencedirect.com/science/article/pii/S1529 943018302432.

33. Shiri, Rahman et al. “Cardiovascular and lifestyle risk factors in lumbar radicular pain or clinically defined sciatica: a systematic review.” European Spine Journal, vol. 16, May 2007, pp. 2043-2054. https://link. springer.com/article/10.1007/s00586-007-0362-6.

34. Cook, Chad E. et al. “Risk factors for first time incidence sciatica: a systematic review.” Physiotherapy Research International, vol. 19, no. 2, December 2013, pp. 65-78. https://onlinelibrary.wiley.com/ doi/abs/10.1002/pri.1572.

35. Shiri, Rahman and Kobra Falah-Hassani. “The effect of smoking on the risk of sciatica: a meta-analysis.” The American Journal of Medicine, vol. 129, no. 1, January 2016, pp. 64-73. https://www.sciencedirect. com/science/article/pii/S0002934315009055.

36. Green, Bart N. et al. “A scoping review of biopsychosocial risk factors and co-morbidities for common spinal disorders.” PLoS One, vol. 13, no. 6, June 2018. https://journals.plos.org/plosone/article?id=10.1371/ journal.pone.0197987.