Browsing by Author "Schwartz, Todd A"

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    Association between general joint hypermobility and knee, hip, and lumbar spine osteoarthritis by race: a cross-sectional study.
    (Arthritis research & therapy, 2018-04-18) Flowers, Portia PE; Cleveland, Rebecca J; Schwartz, Todd A; Nelson, Amanda E; Kraus, Virginia B; Hillstrom, Howard J; Goode, Adam P; Hannan, Marian T; Renner, Jordan B; Jordan, Joanne M; Golightly, Yvonne M
    BACKGROUND:Osteoarthritis (OA) prevalence differs by race. General joint hypermobility (GJH) may be associated with OA, but differences by race are not known. This community-based study examined the frequency of GJH and its relationship with knee, hip, and lumbar spine OA by race (African American vs. Caucasian). METHODS:Data were from the Johnston County OA project, collected 2003-2010. GJH was defined as Beighton score ≥4. OA symptoms were defined as the presence of pain, aching, or stiffness on most days separately at the knee, hip, and lower back. Radiographic OA (rOA) of the knee or hip was defined as Kellgren-Lawrence grade 2-4. Lumbar spine rOA was disc space narrowing grade ≥1 and osteophyte grade ≥2 in ≥ 1 at the same lumbar level. Lumbar spine facet rOA was present in ≥ 1 lumbar levels. Separate logistic regression models stratified by race were used to examine the association between hypermobility and rOA or OA symptoms at each joint site, adjusting for age, sex, previous joint injury, and body mass index (BMI). RESULTS:Of 1987 participants, 1/3 were African-American and 2/3 were women (mean age 65 years, mean BMI 31 kg/m2). Nearly 8% of Caucasians were hypermobile vs. 5% of African-Americans (p = 0.03). Hypermobility was associated with lower back symptoms in Caucasians (adjusted odds ratio (aOR) 1.54, 95% confidence interval (CI) 1.00, 2.39), but not in African-Americans (aOR 0.77, 95% CI 0.34, 1.72). Associations between hypermobility and other knee, hip, or lumbar spine/facet OA variables were not statistically significant. CONCLUSIONS:General joint hypermobility was more common in Caucasians than African-Americans. Although there were no associations between hypermobility and rOA, the association between hypermobility and lower back symptoms may differ by race.
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    Association of Biomarkers with Individual and Multiple Body Sites of Pain: The Johnston County Osteoarthritis Project.
    (Journal of pain research, 2022-01) Norman, Katherine S; Goode, Adam P; Alvarez, Carolina; Hu, David; George, Steven Z; Schwartz, Todd A; Danyluk, Stephanie T; Fillipo, Rebecca; Kraus, Virginia B; Huebner, Janet L; Cleveland, Rebecca J; Jordan, Joanne M; Nelson, Amanda E; Golightly, Yvonne M

    Introduction

    Biochemical biomarkers may provide insight into musculoskeletal pain reported at individual or multiple body sites. The purpose of this study was to determine if biomarkers or pressure-pain threshold (PPT) were associated with individual or multiple sites of pain.

    Methods

    This cross-sectional analysis included 689 community-based participants. Self-reported symptoms (ie, pain, aching, or stiffness) were ascertained about the neck, upper back/thoracic, low back, shoulders, elbows, wrist, hands, hips, knees, ankles, and feet. Measured analytes included CXCL-6, RANTES, HA, IL-6, BDNF, OPG and NPY. A standard dolorimeter measured PPT. Logistic regression was used determine the association between biomarkers and PPT with individual and summed sites of pain.

    Results

    Increased IL-6 and HA were associated with knee pain (OR=1.30, 95% CI 1.03, 1.64) and (OR=1.32, 95% CI 1.01, 1.73) respectively; HA was also associated with elbow/wrist/hand pain (OR=1.60, 95% CI 1.22, 2.09). Those with increased NPY levels were less likely to have shoulder pain (OR=0.56, 95% CI 0.33, 0.93). Biomarkers HA (OR=1.50, 95% CI 1.07, 2.10), OPG (OR=1.74, 95% CI 1.00, 3.03), CXCL-6 (OR=1.75, 95% CI 1.02, 3.01) and decreased PPT (OR=3.97, 95% CI 2.22, 7.12) were associated with multiple compared to no sites of pain. Biomarker HA (OR=1.57, 95% CI 1.06, 2.32) and decreased PPT (OR=3.53, 95% CI 1.81, 6.88) were associated with multiple compared to a single site of pain.

    Conclusion

    Biomarkers of inflammation (HA, OPG, IL-6 and CXCL-6), pain (NPY) and PPT may help to understand the etiology of single and multiple pain sites.
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    Limited educational attainment and radiographic and symptomatic knee osteoarthritis: a cross-sectional analysis using data from the Johnston County (North Carolina) Osteoarthritis Project
    (2010) Callahan, Leigh F; Shreffler, Jack; Siaton, Bernadette C; Helmick, Charles G; Schoster, Britta; Schwartz, Todd A; Chen, Jiu-Chiuan; Renner, Jordan B; Jordan, Joanne M
    Introduction: Applying a cross-sectional analysis to a sample of 2,627 African-American and Caucasian adults aged >= 45 years from the Johnston County Osteoarthritis Project, we studied the association between educational attainment and prevalence of radiographic knee osteoarthritis and symptomatic knee osteoarthritis. Methods: Age-and race-adjusted associations between education and osteoarthritis outcomes were assessed by gender-stratified logistic regression models, with additional models adjusting for body mass index, knee injury, smoking, alcohol use, and occupational factors. Results: In an analysis of all participants, low educational attainment (= 12 years), by using fully adjusted models. In the subset of postmenopausal women, these associations tended to be weaker but little affected by adjustment for hormone replacement therapy. Men with low educational attainment had 85% higher odds of having symptomatic knee osteoarthritis by using fully adjusted models, but the association with radiographic knee osteoarthritis was explained by age. Conclusions: After adjustment for known risk factors, educational attainment, as an indicator of socioeconomic status, is associated with symptomatic knee osteoarthritis in both men and women and with radiographic knee osteoarthritis in women.
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    Quantification of the whole-body burden of radiographic osteoarthritis using factor analysis.
    (Arthritis Res Ther, 2011) Nelson, Amanda E; DeVellis, Robert F; Renner, Jordan B; Schwartz, Todd A; Conaghan, Philip G; Kraus, Virginia B; Jordan, Joanne M
    INTRODUCTION: Although osteoarthritis (OA) commonly involves multiple joints, no widely accepted method for quantifying whole-body OA burden exists. Therefore, our aim was to apply factor analytic methods to radiographic OA (rOA) grades across multiple joint sites, representing both presence and severity, to quantify the burden of rOA. METHODS: We used cross-sectional data from the Johnston County Osteoarthritis Project. The sample (n = 2092) had a mean age of 65 ± 11 years, body mass index (BMI) 31 ± 7 kg/m2, with 33% men and 34% African Americans. A single expert reader (intra-rater κ = 0.89) provided radiographic grades based on standard atlases for the hands (30 joints, including bilateral distal and proximal interphalangeal [IP], thumb IP, metacarpophalangeal [MCP] and carpometacarpal [CMC] joints), knees (patellofemoral and tibiofemoral, 4 joints), hips (2 joints), and spine (5 levels [L1/2 to L5/S1]). All grades were entered into an exploratory common factor analysis as continuous variables. Stratified factor analyses were used to look for differences by gender, race, age, and cohort subgroups. RESULTS: Four factors were identified as follows: IP/CMC factor (20 joints), MCP factor (8 joints), Knee factor (4 joints), Spine factor (5 levels). These factors had high internal consistency reliability (Cronbach's α range 0.80 to 0.95), were not collapsible into a single factor, and had moderate between-factor correlations (Pearson correlation coefficient r = 0.24 to 0.44). There were no major differences in factor structure when stratified by subgroup. CONCLUSIONS: The 4 factors obtained in this analysis indicate that the variables contained within each factor share an underlying cause, but the 4 factors are distinct, suggesting that combining these joint sites into one overall measure is not appropriate. Using such factors to reflect multi-joint rOA in statistical models can reduce the number of variables needed and increase precision.