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Background/Purpose: “Arthritis-attributable activity limitation” (AAAL) is linked to many potentially modifiable characteristics (e.g., work disability, physical inactivity, obesity). By 2015, prevalence of AAAL among adults ≥18 with arthritis had increased by almost 20% compared with that reported in 2002, and the observed annualized prevalence of AAAL in 2010 had outpaced projections for 2020 (22.7 vs. 22.1 million). Our objective was to investigate the extent to which trends in AAAL prevalence can be explained by changes in characteristics associated with AAAL among U.S. adults with arthritis.\ud \ud Methods: Cross-Sectional data were obtained for participants ≥18 years from years 2002-2017 of the National Health Interview Survey (NHIS, average unweighted sample n=30,076), an ongoing, multistage probability survey designed to be nationally representative of the civilian, non-institutionalized U.S. population. Analyses were restricted to those with self-reported doctor-diagnosed arthritis. AAAL was defined as “yes” to “Are you now limited in any way in any of your usual activities because of arthritis or joint symptoms?” Demographic, health, function, and health care access measures were assessed across 30 variables.\ud \ud We used unconditional logistic regression to estimate prevalence ratios (PR) with 95% confidence intervals (CI) to examine the associations between a priori selected variables and AAAL, modeled the prevalence of AAAL (dependent variable), and estimated a prevalence ratio (PR) for each independent variable in a model containing only that variable and (continuous) calendar year. Next, for 7 variables significantly associated with AAAL (identified with the overall Wald test of model coefficients) we estimated 2 PRs for AAAL trend: 1) average annual increase in AAAL, and 2) overall AAAL increase, (2017 prevalence less 2002 prevalence). Finally, we calculated a series of multivariable-adjusted (MV) models to test changes in the estimated effect of calendar year on AAAL post-adjustment, i.e., addition of a covariate which reduced the significance of the existing trend identified a variable with a significant role in the observed trend relationship.\ud \ud Results: Between 2002 and 2017, prevalence of AAAL among adults with arthritis significantly increased (37.6% (95% CI=36.1-39.1) to 42.9% (41.4-44.4), p-value < 0.0001 test for trend). Initial model PR=1.11 (1.08-1.15). Only 4 variables reduced the PR, driven by: comorbidities (increased number), employment status (increased retired and not in labor force), body mass index (increased overweight), and race/ethnicity (increased non-Hispanic White). The final MV PR was 1.05 (1.02-1.08). The temporal trend in AAAL is largely explained by the temporal trends of the characteristics accounted for in this analysis (Figure).\ud \ud Conclusion: In addition to identifying specific variables which explain some of the trend in increased AAAL between 2002-2017, we rejected many others as contributors. Still, unknown/unmeasured variables (e.g., zip code, urbanization, neighborhood) may account for some of the trend. Meanwhile, interventions can be directed at the subgroups identified here to reduce AAAL impact.

Objectives The objectives of this study were to identify potential mechanisms of the impact of osteoarthritis on mortality and examine the role of modifiable targets (anxiety, depression, insomnia and walking frequency) for health professionals in rheumatology (HPRs).\ud \ud Methods A population-based prospective cohort study was conducted using data from the North Staffordshire Osteoarthritis Project (NorStOP), in which primary care medical record data was linked to self-report information collected by questionnaire in adults aged 50 years and over (n=8066). Individuals were defined as having osteoarthritis if they had consulted general practice for osteoarthritis, identified by Read codes in the primary care medical record, and indicated moderate to severe pain interference in daily life in the Medical Outcomes Short Form 36 at baseline (2002). A Cox proportional hazards analysis was performed to determine the total effect (TE) of osteoarthritis on mortality, both with adjustment for confounding variables (age, sex, education, occupation, smoking status, ischaemic heart disease, chronic obstructive pulmonary disease, non-steroidal anti-inflammatories, obesity, cognitive impairment). Within the Cox model, path analysis was used to decompose the TE to assess the indirect (IE) and direct effects (DE) for each of four potential mediators (anxiety, depression, insomnia, walking frequency; all measured by questionnaire) with adjustment for confounders. Results are expressed as adjusted hazard ratios (aHR); bootstrap resampling was used to generate 95% confidence intervals (95% CIs).\ud \ud Results Mean age of participants was 65.2 (SD 9.8) years and 51.6% were female. 2396 (29.7%) had osteoarthritis. Participants were followed up over 10 years during which time 1188 (14.7%) died. The rate of mortality was greater in those with osteoarthritis (52 deaths per 1000 person years) compared to those without (38 deaths per 1000 person years). Osteoarthritis was significantly associated with mortality (aHR 1.14; 1.00, 1.28). The relationship between osteoarthritis and mortality was mediated by walking frequency, depression and insomnia (anxiety did not mediate the relationship (IE HR 1.00; 0.98, 1.02)). The strongest mediator was walking frequency (TE 1.14; 1.00, 1.29: DE 1.04; 0.91, 1.18: IE 1.08; 1.06, 1.11), followed by depression (IE 1.06; 1.03, 1.08) and insomnia (IE 1.01; 1.00, 1.03).\ud \ud Conclusion This is the first study to examine mediation and highlights the importance of potentially modifiable targets for HPRs to reduce mortality in older adults with osteoarthritis. Encouraging people to maintain levels of physical activity at a population level and targeting a reduction in physical limitation in clinical practice to allow this, is important.

Objectives The temporal relationship between osteoarthritis and comorbidity is unclear and may vary with socioeconomic status. The aims of this study were to identify if osteoarthritis was associated with onset of common comorbidities, and if the association was moderated by deprivation. Methods Prospective cohort study combining questionnaire and medical record data (n=3910). Associations between osteoarthritis and onset of comorbidity at three year follow-up were examined using regression models. Interaction terms and stratified analysis were used to examine moderation. Results Osteoarthritis was associated with onset of all comorbidities (p

Purpose:\ud Evidence of an association between osteoarthritis (OA) and mortality is conflicting; differences in definitions and anatomical sites explain some of the discordance. The high frequency and increasing prevalence of OA highlights the need to understand its impact and potential association with premature mortality. The aims of this study were to: (i) examine the strength and direction of the association between different clinical case definitions of OA and premature mortality at different anatomical sites (hand, hip, knee and foot) (ii) identify the role of potentially modifiable factors on the pathway between OA at each site and premature mortality using mediation (path analysis) within a Cox proportional hazard model (survival analysis).\ud \ud Methods:\ud A population-based prospective cohort study was conducted using data from the North Staffordshire Osteoarthritis Project (NorStOP), in which primary care medical record data was linked to self-report information collected by questionnaire in adults aged 50 years and over (n= 8066). Different case definitions of OA at each site were derived based on whether individuals had consulted in general practice for OA, selfreported pain in the hand, hip, knee or foot in the baseline questionnaire and indicated moderate to severe pain interference. A Cox proportional hazards analysis was performed to determine the total effect of each case definition of OA on mortality with adjustment for confounders (age, gender, education, occupation, non-steroidal anti-inflammatory drug use, ischaemic heart disease, self-reported cardiovascular disease, diabetes mellitus, smoking, chronic obstructive pulmonary disease and body mass index). Within the Cox model, path analysis was used to decompose the total effects to assess the indirect and direct effects for potential mediators (walking frequency, depression, anxiety, insomnia, and social participation). Results are expressed as hazard ratios (HR); bootstrap resampling was used to generate 95% confidence intervals (95% CIs).\ud \ud Results:\ud Mean age of participants was 65.2 (SD 9.8) years and 51.6% were female. 1515 (18.8%), 1323 (16.4%), 1774 (22.0%) and 1387 (17.2%) had disabling hand, hip, knee and foot OA respectively. Participants were followed up over 10 years during which time 1188 (14.7%) died. Disabling hand, knee and foot OA were significantly associated with premature mortality (adjusted HR 1.18 95% CI 1.02, 1.35; 1.16 95% CI1.02, 1.33; and 1.21 95% CI 1.05, 1.40 respectively); the increased HR for disabling hip OA was not significant (adjusted HR 1.06 95% CI 0.91, 1.23). Low walking frequency, depression, social participation were significant mediators of the relationship between premature mortality and OA (p

Background: Musculoskeletal pain is common in older adults and is associated with a decrease in the Healthy Ageing Index (HAI) (a validated composite ageing measure). Deprivation measures were not included in the HAI. The literature advocates including measures of deprivation in ageing models and a literature review illustrated the need to investigate the relationship between deprivation {individual level deprivation (ILD), area level deprivation (ALD), access to care (ATC) and quality of care (QOC)} and healthy ageing in older people with musculoskeletal pain.\ud \ud Methods: 2949 adults from six general practices aged ≥50 years with complete questionnaires at baseline, 3 and 6 years were analysed. Subject HAI scores (higher scores indicated healthier ageing) were calculated. The questionnaire provided ILD data. ALD was measured using the Index of Multiple Deprivation, ATC by GP Patient Survey and QOC by Quality Outcomes Framework data. Aims: determine whether HAI scores differ by levels of deprivation and establish if associations exist between pain and healthy ageing, and if they are moderated by deprivation at baseline and across 6 years.\ud \ud Results: HAI scores were lower (and associations noted after adjustment for confounders) with greater deprivation across ILD, ALD, ATC and QOC variables at baseline and over 6 years. There were significant interactions between widespread pain and; ILD, ALD, ATC and QOC variables at baseline and ILD and ALD variables over 6 years, translating to significant reductions in healthy ageing.\ud \ud Conclusion: Healthy ageing decreases with pain and deprivation (ILD, ALD, ATC & QOC), demonstrating need to; reduce pains causes, improve treatment, reduce inequality and assess interventions. Deprivation variables should be included in ageing models. Assessing whether unaccounted exposures explain poorer ageing amongst particular practice subjects is warranted. Qualitative approaches could investigate reasons for generally lower HAI scores from service users experiencing greater deprivation.