Background
The symptom of back pain affects most adults at some point in their lives [
1], and causes more years lived with disability than any other health condition worldwide [
2]. The societal burden of back pain is driven by the minority of individuals who do not recover from a new back pain episode, and who go on to develop ‘chronic’ back pain (CBP) [
3]. Accordingly, much research has attempted to identify preventable conditions associated with the development of CBP [
4].
CBP is recognized as a complex condition best studied and managed within the context of a biopsychosocial framework, as opposed to a strictly biomedical model. Psychological factors such as depression, anxiety, fear-avoidance, catastrophizing, and self-efficacy have been extensively studied as risk factors for CBP [
5]. Much effort has also been expended to identify specific spine-related conditions linked to CBP [
6‐
9]. Fewer studies, however, have examined the role of medical conditions not involving the spine as risk factors for CBP. Poor general health is a known risk factor for new (‘acute’) back pain [
10] and the acute-to-chronic back pain transition [
4]. Specific medical conditions might have particular importance as risk factors for CBP, especially if such conditions have a causal role in CBP, and if they can be prevented or treated. Self-reported and clinically diagnosed arthritis and joint problems predict CBP and poor back-related outcomes [
11‐
14]. Several proposed explanations for the link between arthritis and CBP include that lower limb arthritis leads to postural or biomechanical changes which place increased stresses on the back [
15]; that pain in the back may originate from or reflect progression of arthritic structures external to the spine (e.g. the hip joint) [
16]; that an underlying propensity to generalized arthritis predisposes to future arthritic involvement of the spinal structures and consequent back pain; that self-reported ‘arthritis’ simply reflects an underlying susceptibility to painful conditions such as back pain; and semantic issues whereby some individuals do not distinguish between the terms ‘arthritis’ and ‘back pain’ [
15]. In addition, cardiovascular risk factors such as diabetes and hypertension have been implicated in back pain and spinal disorders through putative mechanisms involving lumbar arterial atherosclerosis [
17,
18]. Atherosclerotic lesions in branching arteries supplying the lumbar spine may cause impaired nutrition to the vertebrae, intervertebral discs, and nerve roots, leading to disc degeneration and consequent back pain [
18‐
22]. However, it is unclear whether any of these medical conditions actually confer a greater risk of CBP, or whether they are associated with CBP due to other reasons. For instance, individual medical conditions may simply serve as proxies for poor general health, an idea supported by a recent study demonstrating that the number of self-reported conditions predicted future back pain in men [
23]. Much of the research supporting a relationship between medical conditions and CBP consists of cross-sectional studies, which cannot identify temporal sequence, and are particularly prone to confounding by other factors [
15,
17,
24‐
29]. Although there are many possible sources of confounding which might underlie the link between medical conditions and CBP, one important explanation is shared underlying vulnerabilities, either genetic or familial, which predispose to both medical conditions and CBP. Observational study designs using genetically informative samples may be used to examine associations between medical conditions and CBP free of confounding by these shared underlying vulnerabilities.
The aim of this study was to examine the association of self-reported medical conditions with the development of CBP, using a genetically informative longitudinal co-twin control study design to account for confounding due to familial factors, including genetics. Based on prior literature, the self-reported medication conditions examined in this study included arthritis and cardiovascular risk factors/conditions (diabetes, hypertension, and coronary artery disease [CAD]).
Discussion
This study found that among medical conditions examined in individual-level analyses, self-reported arthritis, CAD, hypertension, and a medical comorbidity score were significantly associated with incident CBP at 11-year follow-up, consistent with some prior reports. The associations of specific medical conditions with incident CBP were, to a small degree, accounted for by general comorbidity burden as measured by the medical comorbidity score. Co-twin control analyses indicated that the arthritis-CBP association was confounded by familial predispositions underlying both conditions, arguing against a causal link. However, the results of other co-twin control analyses could not exclude the possibility that there is some effect of CAD and hypertension, and medical comorbidities in general, on the development of CBP.
Variables predictive of a health condition are not necessarily causal [
40]. Self-reported arthritis and joint problems predict CBP and poor back-related outcomes in clinical studies [
11‐
13]. Although some have proposed a ‘knee-spine syndrome’ whereby lower limb arthritis or joint problems lead to biomechanical alterations in activities such as ambulation, which then lead to back pain [
15], many other explanations exist aside from a causal link [
29]. Our individual-level analysis results are consistent with prior studies of the arthritis-back pain relationship, showing that self-reported arthritis is associated with a substantially greater likelihood of developing CBP over 11-year follow-up (OR point estimate = 1.8). Thus, self-reported arthritis may have value as a marker for individuals who are more likely to experience CBP in the future. Although adjustment for other medical comorbidities had minimal effect on the arthritis-incident CBP association, there was no meaningful association between arthritis and incident CBP (OR 0.9) in the within-pair analyses that reflect adjustment for familial confounding. Strong inferences cannot be made based on the within-pair analyses due to the small sample sizes and wide confidence intervals involved, however, this overall pattern of results suggests a role of shared genetic factors in the arthritis-CBP relationship, and argues against arthritis being an actual determinant of future CBP. The role of shared genetics in the arthritis-CBP relationship is supported by the recent results of a large-scale genetic association study involving more than 158,000 individuals, which found large-magnitude genetic correlations (0.63) between self-reported CBP and self-reported osteoarthritis [
41].
Research has shown that cardiovascular disease and related risk factors (abdominal aortic atherosclerosis in particular) are associated with disc degeneration and back pain [
19,
20,
22], prompting speculation that treatment of cardiovascular risk factors/conditions might also help to prevent CBP or minimize its impact [
22,
42‐
44]. Results from our individual-level analyses of hypertension and CAD are consistent with earlier reports that these conditions are associated with future back pain or spine-related symptoms [
18,
22]. These associations were slightly smaller when adjusting for the comorbidity score, indicating that a small component of these associations might be due to hypertension and CAD reflecting manifestations of poor general health (and CBP might also reflect another aspect of general health). However, although the within-pair analyses for hypertension and CAD were limited by imprecision, the comparable magnitude estimates of association as compared to the individual-level analyses argue against shared underlying predispositions to cardiovascular risk factors/conditions and back pain as a complete explanation for why cardiovascular factors predict future back pain [
42]. These findings leave open the possibility that there is a causal effect of hypertension, CAD, and/or general medical comorbidity on the development of CBP.
Our finding that diabetes is not associated with future CBP largely fits in the context of prior longitudinal studies. One such study of diabetes’ association with future back pain also yielded a null association [
45]. However, other studies examining the association of diabetes with the future occurrence of other spine-related phenotypes such as physician-diagnosed lumbar disc herniation and general musculoskeletal pain (including back pain) have found positive associations [
22,
44]. Thus, the association of diabetes with musculoskeletal pain may be driven by non-back locations, or may pertain only to certain subsets of people with back pain.
To our knowledge, this is the first longitudinal co-twin control study of back pain in a US sample. Co-twin control studies are often performed to sharpen our understanding of why two phenotypes, such as CBP and arthritis, might be associated. In our application of the co-twin control approach we observed that shared familial factors, including genetic factors, may underlie the association of arthritis and CBP. Support for shared genetic influences on CBP and arthritis come from other recent work by our group: a genome-wide meta-analysis of CBP identified and replicated a variant in the gene
SOX5, previously implicated in osteoarthritis [
46‐
48], that was a significant predictor of CBP [
49]. Future genetic studies may benefit from harnessing knowledge regarding genetic influences on CBP shared with other musculoskeletal phenotypes, such as arthritis. For instance, multivariate genome-wide association studies, in which genetic associations with several traits are analyzed together, have advantages in statistical power over univariate analyses of each trait separately, in some instances [
50].
Our study had limitations with regards to the definitions used for the predictor and outcome variables of interest. Similar to most prior longitudinal studies showing relationships between medical conditions and back pain [
22,
23,
44], our study relied entirely on self-report. For instance, ‘arthritis’ in the current study may have reflected either osteoarthritis or inflammatory arthritis in the major lower extremity joints (i.e. hip or knee), or the hand joints, or elsewhere. Similarly, ‘diabetes’ in the current study may reflect either type 1 or type 2 diabetes. We expect that these self-report definitions used in our study reflect the influence of the most prevalent underlying conditions, such that the ‘arthritis’ variable mainly reflects the most commonly symptomatic arthritic conditions affecting older adults (knee osteoarthritis, hip osteoarthritis, and hand osteoarthritis), the ‘diabetes’ variable is largely informed by those with type 2 diabetes, and soforth. Although these definitions might have resulted in misclassification of medical conditions, it is reassuring that our findings in the individual-level analyses (which did not adjust for familial confounding) generally showed associations consistent with prior work [
11‐
14,
18,
23], arguing against differential misclassification due to self-report. Our longitudinal sample was restricted to individuals with no prior back problems diagnosed by a doctor at baseline. Since back pain is a symptom, which does not require a clinician assessment per se, clinician-diagnosed back problems may be an imperfect proxy for back pain. Additionally, we applied a different back pain definition at follow-up to assess incident CBP, which did not specify a minimum duration of pain needed to constitute ‘chronic’ or the particular location in the back where pain was experienced (thoracic or lumbar). However, given the high agreement between general back pain questions and lumbar-specific questions [
51], and that thoracic pain without concurrent lumbar pain is less common [
52], it is likely that our results are driven by lumbar-location pain [
36]. Another limitation of this study was that the within-pair analyses conducted were limited by a small number of discordant twin pairs. Future co-twin control studies may consider evaluating these medical risk factors across multiple twin samples to produce larger samples of discordant pairs. Last, participants in the current study included male veterans only, due to the male-only composition of the VET Registry. These results may not be generalizable to women. Moreover, study participants were healthy and fit at the time of their military service two decades prior and may be more active than the general population. It is therefore unclear whether our study findings related to medical conditions- many of which are associated with physical activity levels- would extend to a more sedentary population.
Acknowledgements
Most importantly, the authors gratefully acknowledge the continued cooperation and participation of the members of the VET Registry and their families. Without their contribution this research would not have been possible.