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PURPOSE OF REVIEW: This review highlights recently published studies on osteoarthritis (OA) epidemiology, including topics related to understudied populations and joints, imaging, and advancements in artificial intelligence (AI) methods. RECENT FINDINGS: Contemporary research has improved our understanding of the burden of OA in typically understudied regions, including ethnic and racial minorities in high-income countries, the Middle East and North Africa (MENA) and Latin America. Efforts have also been made to explore the burden and risk factors in OA in previously understudied joints, such as the hand, foot, and ankle. Advancements in OA imaging techniques have occurred alongside the developments of AI methods aiming to predict disease phenotypes, progression, and outcomes. SUMMARY: Continuing efforts to expand our knowledge around OA in understudied populations will allow for the creation of targeted and specific interventions and inform policy changes aimed at reducing disease burden in these groups. The burden and disability associated with OA is notable in understudied joints, warranting further research efforts that may lead to effective therapeutic options. AI methods show promising results of predicting OA phenotypes and progression, which also may encourage the creation of targeted disease modifying OA drugs (DMOADs).
Subject(s)
Artificial Intelligence , Osteoarthritis , Humans , Osteoarthritis/therapy , Osteoarthritis/drug therapy , Diagnostic Imaging , Risk Factors , PhenotypeABSTRACT
OBJECTIVE: To summarize the current state of the literature regarding multi-joint osteoarthritis (MJOA) and discuss important future directions. DESIGN: A narrative review of the author's work and other key references on this topic with a focus on the Johnston County studies, definitions of MJOA and their impact, multi-site pain in osteoarthritis (OA), genetics and biomarkers in MJOA, and perspectives on future work. RESULTS: MJOA is variably defined and lacks a clear consensus definition, making comprehensive study challenging. Involvement of both symptoms and structural changes of OA in multiple joints in an individual is common, but patterns vary by sex, race/ethnicity, and other factors. Outcomes (e.g., general health, function, falls, mortality) are negatively impacted by a greater whole-body OA burden. Recent genetic and biomarker studies including whole-body OA assessments have begun to shed some light on potentially unique factors in the MJOA population. CONCLUSIONS: Consideration of MJOA is essential for ongoing study of OA phenotypes, epidemiology, risk factors, genetics, biomarkers, and outcomes, to fully understand and eventually limit the negative impact of OA burden on health.
Subject(s)
Osteoarthritis , Humans , Osteoarthritis/epidemiology , Biomarkers , Phenotype , Ethnicity , North Carolina/epidemiologyABSTRACT
OBJECTIVE: To better understand the pathogenesis of knee osteoarthritis (OA) through identification of serum diagnostics. DESIGN: We conducted multiple reaction monitoring mass spectrometry analysis of 107 peptides in baseline sera of two cohorts: the Foundation for National Institutes of Health (NIH) (n = 596 Kellgren-Lawrence (KL) grade 1-3 knee OA participants); and the Johnston County Osteoarthritis Project (n = 127 multi-joint controls free of radiographic OA of the hands, hips, knees (bilateral KL=0), and spine). Data were split into (70%) training and (30%) testing sets. Diagnostic peptide and clinical data predictors were selected by random forest (RF); selection was based on association (p < 0.05) with OA status in multivariable logistic regression models. Model performance was based on area under the curve (AUC) of receiver operating characteristic (ROC) and precision-recall (PR) curves. RESULTS: RF selected 23 peptides (19 proteins) and body mass index (BMI) as diagnostic of OA. BMI weakly diagnosed OA (ROC-AUC 0.57, PR-AUC 0.812) and only symptomatic OA cases. ACTG was the strongest univariable predictor (ROC-AUC 0.705, PR-AUC 0.897). The final model (8 serum peptides) was highly diagnostic (ROC-AUC 0.833, 95% confidence interval [CI] 0.751, 0.905; PR-AUC 0.929, 95% CI 0.876, 0.973) in the testing set and equally diagnostic of non-symptomatic and symptomatic cases (AUCs 0.830-0.835), and not significantly improved with addition of BMI. The STRING database predicted multiple high confidence interactions of the 19 diagnostic OA proteins. CONCLUSIONS: No more than 8 serum protein biomarkers were required to discriminate knee OA from non-OA. These biomarkers lend strong support to the involvement and cross-talk of complement and coagulation pathways in the development of OA.
Subject(s)
Osteoarthritis, Knee , Humans , Osteoarthritis, Knee/diagnostic imaging , Knee Joint/pathology , Proteomics , Biomarkers , PeptidesABSTRACT
Over the last 30 years, knowledge of the epidemiology of osteoarthritis (OA) has dramatically advanced, and Osteoarthritis and Cartilage has been on the forefront of disseminating research findings from large OA cohort studies, including the Johnston County OA Project (JoCoOA). The JoCoOA is a population-based, prospective longitudinal cohort that began roughly 30 years ago with a key focus on understanding prevalence, incidence, and progression of OA, as well as its risk factors, in a predominantly rural population of Black and White adults 45+ years old in a county in the southeastern United States. Selected OA results that will be discussed in this review include racial differences, lifetime risk, biomarkers, mortality, and OA risk factors. The new Johnston County Health Study will also be introduced. This new cohort study of OA and comorbid conditions builds upon current OA knowledge and JoCoOA infrastructure and is designed to reflect changes in demographics and urbanization in the county and the region.
Subject(s)
Osteoarthritis, Knee , Humans , Middle Aged , Osteoarthritis, Knee/diagnostic imaging , Cohort Studies , Prospective Studies , Radiography , Risk FactorsABSTRACT
OBJECTIVE: To examine associations of vibration sensitivity and pressure pain sensitivity with knee osteoarthritis (OA) outcomes across sex and race, which may relate to known sex and race disparities in clinical outcomes. DESIGN: Data were from the 2013-2015 visit of the Johnston County Osteoarthritis Project. Exposures were vibration perception threshold (VPT) measured at the bilateral medial femoral condyle (MFC) and first metatarsophalangeal joint (MTP), and pressure pain threshold (PPT) measured at the bilateral upper trapezius. Outcomes were knee pain severity and presence of knee symptoms, radiographic knee OA, and symptomatic knee OA in each knee. Cross-sectional associations of the exposures with the outcomes were examined using logistic regression models, overall and separately by sex and race. RESULTS: In the VPT and PPT analyses, 851 and 862 participants (mean age 71 years, 68% female, 33% Black, body mass index 31 kg/m2) and 1585 and 1660 knees were included, respectively. Higher VPT (lower vibration sensitivity) at the MFC and first MTP joint was associated with all outcomes. Lower PPT (greater pressure pain sensitivity) was associated with greater knee pain severity. Associations of VPT and PPT with all outcomes were similar among females and males and Black and White individuals. CONCLUSIONS: Diminished vibration perception and greater pressure pain sensitivity were cross-sectionally associated with worse knee OA outcomes. Despite differences in VPT and PPT among females and males and Black and White adults, associations with knee OA outcomes did not differ by sex or race, suggesting neurophysiological differences do not relate to established disparities.
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Physical activity (PA) and weight management are critical components of an effective knee and hip osteoarthritis (OA) management plan, yet most people with OA remain insufficiently active and/or overweight. Clinicians and their care teams play an important role in educating patients with OA about PA and weight management, eliciting patient motivation to engage in these strategies, and referring patients to appropriate self-management interventions. The purpose of this review is to educate clinicians about the current public health and clinical OA guidelines for PA and weight management and highlight a variety of evidence-based self-management interventions available in community and clinical settings and online.
Subject(s)
Osteoarthritis, Hip , Humans , Osteoarthritis, Hip/therapy , Knee Joint , ExerciseABSTRACT
INTRODUCTION: To examine the incidence and progression of foot osteoarthritis (OA), as well as associated factors, in a community-based cohort. METHODS: Baseline (2013-2015) and follow-up (2016-2018) foot radiographs were available for 541 participants (71% women, mean age 69 years; 35% Black, 53% with obesity). The LaTrobe Foot Atlas was used to examine osteophytes (OP, score 0-3) and joint space narrowing (JSN, score 0-3) at 5 joint sites. Incident foot radiographic OA (rOA) was a baseline score <2 OP and JSN in all 5 joints with ≥2 OP or JSN at follow-up in any of the joints. Progression was a worsening OP or JSN score in a joint with baseline foot rOA. At baseline and follow-up, participants reported presence/absence of foot symptoms and completed the Foot and Ankle Outcome Score (FAOS) for each foot. Joint-based logistic regression models with generalized estimating equations were used to examine associations (adjusted odds ratio [aOR], 95% confidence interval [CI]) of foot rOA incidence and progression and with covariates. RESULTS: Among 928 feet without baseline rOA, 4% developed incident foot rOA (2% of those developed symptoms). Among 154 feet with baseline foot rOA, 55% had radiographic progression (16% of those had symptoms). Women and those with higher body mass index (BMI) were more likely to have incident foot rOA (aOR [95% CI] = 4.10 [1.22, 13.8] and 1.60 [1.31, 1.97], respectively); history of gout was associated with incidence or progression of foot rOA (2.75 [1.24, 6.07]. BMI was associated with worse scores on all FAOS subscale (aORs range 1.21-1.40). CONCLUSION: Progression of foot rOA is common but not necessarily related to worsening symptoms. BMI may be a modifiable risk factor for foot OA.
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BACKGROUND: Shoulder pain is a leading cause of disability. Occupations requiring high upper extremity demands may put workers at greater risk of shoulder injury and resulting pain. We examined associations of occupation with shoulder pain and upper extremity disability in the Johnston County Osteoarthritis Project. METHODS: Work industry and occupational tasks for the longest job held were collected from participants. At follow-up ranging from 4-10 years later, participants were asked about shoulder symptoms (pain, aching, or stiffness occurring most days of 1 month in the last year) and given a 9-item, modified Disabilities Arm Shoulder and Hand (DASH) questionnaire to categorize disability from 0-4 (none-worst). Logistic regression and cumulative logit regression models were used to estimate associations with prevalent shoulder symptoms and with worse disability category, respectively. Models were adjusted for cohort, age, sex, race, education and time to follow-up. Sex- and race-stratified associations were evaluated. RESULTS: Among 1560 included participants, mean age was 62 years (standard deviation ± 9 years); 32% were men, and 31% were Black. Compared to the managerial/professional industry, higher odds of both shoulder symptoms and worse upper extremity disability were seen for most industrial groups with physically demanding jobs, particularly the service industry. Work that often or always required lifting/moving > 10 lbs. was associated with higher odds of shoulder symptoms. Work that sometimes or always required heavy work while standing was associated with higher odds of shoulder symptoms, and this association was stronger among men and White workers. CONCLUSION: Physically demanding occupations were associated with increased occurrence of shoulder pain and disability. Mitigating specific physical work demands may reduce shoulder-related disability.
Subject(s)
Disability Evaluation , Occupational Diseases , Osteoarthritis , Shoulder Pain , Upper Extremity , Humans , Male , Female , Middle Aged , Cross-Sectional Studies , Shoulder Pain/epidemiology , Shoulder Pain/etiology , Shoulder Pain/diagnosis , Occupational Diseases/epidemiology , Occupational Diseases/diagnosis , Occupational Diseases/etiology , Upper Extremity/physiopathology , Aged , Osteoarthritis/epidemiology , Follow-Up Studies , Surveys and QuestionnairesABSTRACT
OBJECTIVE: To evaluate knee osteoarthritis (KOA) and multijoint osteoarthritis (MJOA), and to compare features by sex and race and ethnicity in a population-based cohort. METHODS: Participants (n = 544) enrolled in the Johnston County Health Study (JoCoHS) as of January 2023 were categorized by radiographic and symptomatic KOA and MJOA phenotypes, and frequencies were compared by sex and race and ethnicity. Symptoms were assessed according to the Knee Injury and Osteoarthritis Outcome Score (KOOS) and pain, aching, and stiffness (PAS) scores at various joints. Models produced estimates (odds ratio [OR] or mean ratios [MR] and 95% CI) adjusted for age, BMI (kg/m2), and education. RESULTS: Men had twice the odds of having MJOA-6 (≥ 3 lower extremity joints affected); there were no significant differences in MJOA phenotypes by race and ethnicity. Women had 50% higher odds of having KOA or having various features of KOA. Women reported significantly worse KOOS Symptoms scores (MR 1.25). Black participants had higher odds of more severe KOA (OR 1.47), subchondral sclerosis (OR 2.06), and medial tibial osteophytes (OR 1.50). Black participants reported worse KOOS Symptoms than White participants (MR 1.18). Although not statistically significant, Hispanic participants (vs non-Hispanic participants) appeared to have lower odds of radiographic changes but reported worse symptoms. CONCLUSION: Preliminary findings in the diverse JoCoHS cohort suggest more lower extremity- predominant MJOA in men compared to women. Women and Black participants had more KOA features and more severe symptoms. Hispanic participants appear to have higher pain and symptoms scores despite having fewer structural changes. Studies in diverse populations are needed to understand the burden of OA.
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PURPOSE OF REVIEW: Osteoarthritis (OA) is a complex heterogeneous disease with no effective treatments. Artificial intelligence (AI) and its subfield machine learning (ML) can be applied to data from different sources to (1) assist clinicians and patients in decision making, based on machine-learned evidence, and (2) improve our understanding of pathophysiology and mechanisms underlying OA, providing new insights into disease management and prevention. The purpose of this review is to improve the ability of clinicians and OA researchers to understand the strengths and limitations of AI/ML methods in applications to OA research. RECENT FINDINGS: AI/ML can assist clinicians by prediction of OA incidence and progression and by providing tailored personalized treatment. These methods allow using multidimensional multi-source data to understand the nature of OA, to identify different OA phenotypes, and for biomarker discovery. We described the recent implementations of AI/ML in OA research and highlighted potential future directions and associated challenges.
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Physical activity (PA) is important for managing osteoarthritis (OA), but many patients are inactive. Research is needed on strategies to leverage clinical encounters to engage patients in PA. Guided by the socioecological model of health behavior, this study aimed to engage stakeholders in the process of refining an Osteoarthritis Physical Activity Care Pathway (OA-PCP). Six focus groups and seven individual interviews were conducted with key stakeholders. Focus groups were specific to stakeholder roles and included patients with OA, support partners, and clinic personnel (n = 6 focus groups). Interview participants were local and national PA program representatives (n = 7 interviews). Data were analyzed by thematic analysis. Themes identified in the data included ways the OA-PCP can help patients with OA address challenges to PA engagement, strategies for connecting patients with PA resources, methods for implementing OA-PCP into clinical settings and potential use of PA trackers in the OA-PCP program. Stakeholders' comments were summarized into key recommendations for OA-PCP. Some recommendations reinforced and led to refinements in planned aspects of OA-PCP, including tailoring to individual patients, involvement of a support partner, and addressing pain with PA. Other recommendations resulted in larger changes for OA-PCP, including the addition of three email- or mail-based contacts and not requiring use of a PA tracker. The refined OA-PCP program is being evaluated in an exploratory trial, with the ultimate goal of establishing a PA program for OA that can be successfully implemented in clinical settings.
Subject(s)
Osteoarthritis , Stakeholder Participation , Exercise , Humans , Osteoarthritis/therapy , Primary Health Care , Qualitative ResearchABSTRACT
PURPOSE OF REVIEW: This narrative review summarizes the last 5 years of published, peer-reviewed research on the use of musculoskeletal ultrasound (US) in osteoarthritis (OA). RECENT FINDINGS: Multiple features relevant to OA can be visualized on US, including synovitis, erosion, enthesitis, osteophytes, cartilage damage, meniscal extrusion, and popliteal cysts. US can be used to confirm a diagnosis of OA or make an alternate diagnosis in the clinical setting. When a standardized protocol is used, US is a reliable modality for assessment of the features of OA. Findings on US can predict progression and response to therapy in OA of the hand and knee and can allow characterization of risk factors in a cost-effective, non-invasive, repeatable manner. US is becoming more widely used in OA imaging and has clear value in addition to radiography and clinical assessment. US will likely prove useful in defining phenotypes and providing treatment guidance in OA.
Subject(s)
Osteoarthritis, Knee , Ultrasonography , Humans , Knee Joint , Magnetic Resonance Imaging , Osteoarthritis, Knee/diagnostic imaging , Synovitis/diagnostic imagingABSTRACT
BACKGROUND: To obtain information on feasibility and acceptability, as well as preliminary data on efficacy, of an Osteoarthritis Physical activity Care Pathway (OA-PCP). METHODS: This was a single group pilot study involving 60 participants with symptomatic, physician diagnosed knee or hip OA, recruited from primary care clinics. Participants self-reported completing less than 150 min per week of moderate-to-vigorous physical activity (MVPA) at baseline. The 3-month OA-PCP intervention involved 3 physical activity (PA) coaching calls (focused on goal setting), three check-in emails and linkage with community-based or online resources to support PA. Efficacy outcomes were collected at baseline and 4-month follow-up. The primary efficacy outcome was minutes of MVPA, assessed via accelerometer. Secondary outcomes included minutes of light intensity activity, sedentary minutes, step counts, and Western Ontario and McMaster Universities (WOMAC) pain and function subscales. Participants were also asked to rate the helpfulness of the OA-PCP intervention on a scale of 0-10. Differences in efficacy outcomes between baseline and 4-month follow-up were assessed using paired t-tests. RESULTS: Among participants beginning the study, 88% completed follow-up assessments and ≥ 90% completed each of the intervention calls. Average daily minutes of MVPA was 8.0 at baseline (standard deviation (SD) = 9.9) and 8.9 at follow-up (SD = 12.1, p = 0.515). There were no statistically significant changes in light intensity activity, sedentary time or step counts. The mean WOMAC pain score improved from 8.1 (SD = 3.6) at baseline to 6.2 (SD = 3.8) at follow-up (p < 0.001); the mean WOMAC function score improved from 26.2 (SD = 13.2) to 20.2 (SD = 12.5; p < 0.001). The mean rating of helpfulness was 7.6 (SD = 2.5). CONCLUSIONS: Results supported the feasibility and acceptability of the study, and participants reported clinically relevant improvements in pain and function. PA metrics did not improve substantially. Based on these results and participant feedback, modifications including enhanced self-monitoring are being made to increase the impact of the OA-PCP intervention on PA behavior. TRIAL REGISTRATION: NCT03780400, December 19, 2018.
Subject(s)
Exercise Therapy/methods , Osteoarthritis, Hip/therapy , Osteoarthritis, Knee/therapy , Aged , Feasibility Studies , Female , Humans , Male , North Carolina , Osteoarthritis, Hip/physiopathology , Osteoarthritis, Knee/physiopathology , Outcome Assessment, Health Care , Pain Measurement , Pilot Projects , TelemedicineABSTRACT
Rheumatic and musculoskeletal diseases (RMDs) are common, with osteoarthritis (OA) being the most prevalent. RMDs, including OA, are associated with significant pain and functional limitations, as well as mortality rates up to 1.6-fold higher than in the general population. Most studies of OA and mortality have focused on knee and hip OA. Some, but not all, of these studies suggest an increased risk of death, however risks may differ by region. Reasons for discordant findings may be due to methodological considerations including definition of OA, study design, length of follow-up, and whether variables that can change and develop over time, such as measures of OA, body mass index (BMI) and comorbidities, were re-assessed during the follow-up period. Research has shown that the prognosis of OA is similar to that seen in rheumatoid arthritis (RA) patients, in many respects. In RA, disability and comorbidities are the most important predictors of mortality, although pain may be more prominent in the prognosis of OA mortality. The data suggest that addressing functional limitations and pain seen with OA could potentially reduce the increased mortality that has been observed in these individuals. Further study is needed concerning the potential excess mortality attributable to lower body OA, as well as associated disability, pain and comorbidities.
Subject(s)
Osteoarthritis, Hip , Osteoarthritis, Knee , Body Mass Index , Comorbidity , Humans , Knee Joint , Mortality, Premature , Osteoarthritis, Hip/mortality , Osteoarthritis, Knee/mortalityABSTRACT
In the most recent years, an extraordinary research effort has emerged to disentangle osteoarthritis heterogeneity, opening new avenues for progressing with therapeutic development and unravelling the pathogenesis of this complex condition. Several phenotypes and endotypes have been proposed albeit none has been sufficiently validated for clinical or research use as yet. This review discusses the latest advances in OA phenotyping including how new modern statistical strategies based on machine learning and big data can help advance this field of research.
Subject(s)
Osteoarthritis , Precision Medicine , Big Data , Forecasting , Humans , Osteoarthritis/classification , PhenotypeABSTRACT
Osteoarthritis (OA) is a painful joint disease affecting more than 32.5 million adults in the US and over 350 million adults worldwide. The prevalence is expected to rise continually over the next several decades with significant impacts to societal health and economic costs as well as individuals' daily activities and quality of life. In 2008, the Centers for Disease Control and Prevention (CDC) and the Arthritis Foundation (AF) led a collaborative effort to address approaches to reduce the burden of OA via public health interventions, policies (systems and environmental), and communication strategies. This collaboration resulted in the National Public Health Agenda for OA (OA Agenda), which was vetted by more than 75 stakeholder organisations and released in 2010. The OA Agenda listed ten recommendations focused on public health interventions for OA including weight management, physical activity, self-management education, and injury prevention, and policies, systems, communication, research and evaluation. In 2011, the CDC and AF mobilised the OA Action Alliance (OAAA), a national coalition of organisations concerned with mitigating the public health impact of OA, to operationalise the recommendations set forth in the OA Agenda. Since then, the OAAA has grown to include more than 110 organisations that work collectively to increase awareness about the prevention and management of OA, provide educational resources, and expand access to evidence-based programmes for target audiences including individuals with OA, community-based organisations, healthcare systems and providers, and policymakers. This review highlights the OAAA's progress to date in addressing the OA Agenda recommendations; successes and challenges in delivery of effective communication, programmes, and resources; and future implications.
Subject(s)
Exercise/physiology , Obesity/complications , Osteoarthritis/complications , Public Health , Arthralgia , Humans , Quality of Life , Weight Reduction ProgramsABSTRACT
BACKGROUND: This cross-sectional study evaluated associations of joint hypermobility and multiple joint osteoarthritis (MJOA) in a community-based cohort of adults 45+ years of age. METHODS: MJOA and joint hypermobility data were from 1677 participants (mean age 69 years, 68% women) who completed research clinic visits during 2003-2010. Prevalent MJOA was defined in four ways. Radiographic OA (rOA) was defined as Kellgren-Lawrence (KL) > 2 at any included study joint; symptomatic OA (sxOA) required both symptoms and rOA in a joint. Joint hypermobility was defined as a Beighton score of > 4. Separate logistic regression models were used to estimate odds ratios (OR) between joint hypermobility and each MJOA definition, adjusting for age, sex, race, body mass index, and baseline visit. RESULTS: In this cohort, 4% had Beighton score > 4 and 63% met any definition of MJOA. Joint hypermobility was associated with significantly lower odds of radiographic and symptomatic MJOA-1 (multiple joint OA-definition 1: involvement of > 1 IP (interphalangeal) nodes and > 2 sites of hip, knee, and spine; 74 and 58% lower, respectively). However, for the other MJOA definitions (i.e., MJOA-2:involvement of > 2 IP joints, > 1 carpometacarpal [CMC] joints, and knee or hip sites; MJOA-3: involvement of > 5 joint sites from among distal interphalangeal, proximal interphalangeal, CMC, hip, knee, or spine sites; and MJOA-4:involvement of > 2 lower body sites (hip, knee, or spine), there were no statistically significant associations. For associations between site-specific hypermobility and any MJOA definition, most adjusted ORs were less than one, but few were statistically significant. CONCLUSIONS: Overall, joint hypermobility was not positively associated with any definition of prevalent MJOA in this cohort, and an inverse association existed with one definition of MJOA. Longitudinal studies are needed to determine the contribution of hypermobility to the incidence and progression of MJOA outcomes.
Subject(s)
Joint Instability/epidemiology , Osteoarthritis/epidemiology , Aged , Aged, 80 and over , Cross-Sectional Studies , Female , Hip Joint/diagnostic imaging , Hip Joint/physiopathology , Humans , Joint Instability/complications , Joint Instability/physiopathology , Knee Joint/diagnostic imaging , Knee Joint/physiopathology , Male , Middle Aged , North Carolina/epidemiology , Odds Ratio , Osteoarthritis/diagnostic imaging , Osteoarthritis/etiology , Osteoarthritis/physiopathology , Prevalence , Spine/diagnostic imaging , Spine/physiopathologyABSTRACT
BACKGROUND: Chronic low back pain (cLBP) affects millions of Americans and costs billions. Studies suggest a link between cLBP and joint hypermobility. METHODS: We conducted cross-sectional primary analyses of joint hypermobility and cLBP, lumbar spine osteoarthritis (OA), and lumbar facet joint OA (FOA) in 3 large studies-the Generalized Osteoarthritis Study, Genetics of Generalized Osteoarthritis Study, and Johnston County Osteoarthritis Project (total n = 5072). Associations of joint hypermobility and Beighton trunk flexion with cLBP and lumbar OA were estimated using separate adjusted logistic regression models. Adjusted pooled odds ratios (pORs) and 95% confidence intervals (CIs) were then summarized-using random effect univariate, multivariate crude, and adjusted models-and heterogeneity was determined (I2 statistic). RESULTS: In univariate models, hypermobility was associated with symptomatic FOA (pOR = 0.64 [95% CI 0.44, 0.93]) but this result was not found in the multivariate models. In multivariate adjusted models, hypermobility was not significantly associated with cLBP and lumbar OA, but trunk flexion was inversely associated with cLBP (pOR = 0.40 [95% 0.26, 0.62]), spine OA (pOR = 0.66 [95% CI 0.50, 0.87]), symptomatic spine OA (pOR = 0.39 [95% CI 0.28, 0.53]), and symptomatic FOA (pOR = 0.53 [95% CI 0.37, 0.77]). Generally, between-study heterogeneity was moderate-high. CONCLUSIONS: Hypermobility was not associated with cLBP or lumbar OA. The inverse association of trunk flexion with cLBP and lumbar OA may indicate a role for a flexible spine in avoiding or managing these conditions.