Developing a Primary Care–Focused Intervention to Engage Patients With Osteoarthritis in Physical Activity: A Stakeholder Engagement Qualitative Study

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

Osteoarthritis physical activity care pathway (OA-PCP): Results of a feasibility trial

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

The association between walking speed from short- and standard-distance tests with the risk of all-cause mortality among adults with radiographic knee osteoarthritis: data from three large United States cohort studies

Objective: Adults with radiographic knee OA (rKOA) are at increased risk of mortality and walking difficulty may modify this relation. Little is known about specific aspects of walking difficulty that increase mortality risk. We investigated the association of walking speed (objective measure of walking difficulty) with mortality and examined the threshold that best discriminated this risk in adults with rKOA. Methods: Participants with rKOA from the Johnston County Osteoarthritis Project (JoCoOA, longitudinal population-based cohort), Osteoarthritis Initiative and Multicenter Osteoarthritis Study (OAI and MOST, cohorts of individuals with or at high risk of knee OA) were included. Baseline speed was measured via 2.4-meter (m) walk test (short-distance) in JoCoOA and 20-m walk test (standard-distance) in OAI and MOST. To examine the association of walking speed with mortality risk over 9 years, hazard ratios (HR) and 95% confidence intervals (CI) were calculated from Cox regression models adjusted for potential confounders. A Maximal Likelihood Ratio Chi-square Approach was utilized to identify an optimal threshold of walking speed predictive of mortality. Results: Deaths after 9 years of follow-up occurred in 23.3% (290/1244) of JoCoOA and 5.9% (249/4215) of OAI + MOST. Walking 0.2 m/s slower during short- and standard-distance walk tests was associated with 23% (aHR [95%CI]; 1.23 [1.10, 1.39]) and 25% (1.25 [1.09, 1.43]) higher mortality risk, respectively. Walking <0.5 m/s on short-distance and <1.2 m/s standard-distance walk tests, best discriminated those with and without mortality risk. Conclusion: Slower walking speed measured via short- and standard-distance walk tests was associated with increased mortality risk in adults with rKOA

A saturated map of common genetic variants associated with human height

Common single-nucleotide polymorphisms (SNPs) are predicted to collectively explain 40-50% of phenotypic variation in human height, but identifying the specific variants and associated regions requires huge sample sizes. Here, using data from a genome-wide association study of 5.4 million individuals of diverse ancestries, we show that 12,111 independent SNPs that are significantly associated with height account for nearly all of the common SNP-based heritability. These SNPs are clustered within 7,209 non-overlapping genomic segments with a mean size of around 90 kb, covering about 21% of the genome. The density of independent associations varies across the genome and the regions of increased density are enriched for biologically relevant genes. In out-of-sample estimation and prediction, the 12,111 SNPs (or all SNPs in the HapMap 3 panel) account for 40% (45%) of phenotypic variance in populations of European ancestry but only around 10-20% (14-24%) in populations of other ancestries. Effect sizes, associated regions and gene prioritization are similar across ancestries, indicating that reduced prediction accuracy is likely to be explained by linkage disequilibrium and differences in allele frequency within associated regions. Finally, we show that the relevant biological pathways are detectable with smaller sample sizes than are needed to implicate causal genes and variants. Overall, this study provides a comprehensive map of specific genomic regions that contain the vast majority of common height-associated variants. Although this map is saturated for populations of European ancestry, further research is needed to achieve equivalent saturation in other ancestries

A saturated map of common genetic variants associated with human height.

Common single-nucleotide polymorphisms (SNPs) are predicted to collectively explain 40-50% of phenotypic variation in human height, but identifying the specific variants and associated regions requires huge sample sizes &lt;sup&gt;1&lt;/sup&gt; . Here, using data from a genome-wide association study of 5.4 million individuals of diverse ancestries, we show that 12,111 independent SNPs that are significantly associated with height account for nearly all of the common SNP-based heritability. These SNPs are clustered within 7,209 non-overlapping genomic segments with a mean size of around 90 kb, covering about 21% of the genome. The density of independent associations varies across the genome and the regions of increased density are enriched for biologically relevant genes. In out-of-sample estimation and prediction, the 12,111 SNPs (or all SNPs in the HapMap 3 panel &lt;sup&gt;2&lt;/sup&gt; ) account for 40% (45%) of phenotypic variance in populations of European ancestry but only around 10-20% (14-24%) in populations of other ancestries. Effect sizes, associated regions and gene prioritization are similar across ancestries, indicating that reduced prediction accuracy is likely to be explained by linkage disequilibrium and differences in allele frequency within associated regions. Finally, we show that the relevant biological pathways are detectable with smaller sample sizes than are needed to implicate causal genes and variants. Overall, this study provides a comprehensive map of specific genomic regions that contain the vast majority of common height-associated variants. Although this map is saturated for populations of European ancestry, further research is needed to achieve equivalent saturation in other ancestries