Risk of severe infections after the introduction of biologic DMARDs in people with newly diagnosed rheumatoid arthritis: a population-based interrupted time-series analysis.

OBJECTIVES: To determine the impact of the introduction of biologic DMARDs (bDMARDs) on severe infections among people newly diagnosed with RA compared with non-RA individuals. METHODS: In this population-based retrospective cohort study using administrative data (from 1990-2015) for British Columbia, Canada, all incident RA patients diagnosed between 1995 and 2007 were identified. General population controls with no inflammatory arthritis were matched to RA patients based on age and gender, and were assigned the diagnosis date (i.e. index date) of the RA patients they were matched with. RA/controls were then divided into quarterly cohorts according to their index dates. The outcome of interest was all severe infections necessitating hospitalization or occurring during hospitalization after the index date. We calculated 8-year severe infection rates for each cohort and conducted interrupted time-series analyses to compare severe infection trends in RA/controls with index date during pre-bDMARDs (1995-2001) and post-bDMARDs (2003-2007) periods. RESULTS: A total of 60 226 and 588 499 incident RA/controls were identified. We identified 14 245 severe infections in RA, and 79 819 severe infections in controls. The 8-year severe infection rates decreased among RA/controls with increasing calendar year of index date in the pre-bDMARDs period, but increased over time only among RA, not controls, with index date in the post-bDMARDs period. The adjusted difference between the pre- and post-bDMARDs secular trends in 8-year severe infection rates was 1.85 (P = 0.001) in RA and 0.12 (P = 0.29) in non-RA. CONCLUSION: RA onset after bDMARDs introduction was associated with an elevated severe infection risk in RA patients compared with matched non-RA individuals.

Measuring skill-based health literacy in chronic airway disease patients: the development and psychometric evaluation of the Vancouver airways health literacy tool (VAHLT).

PURPOSE: This article describes the development of the Vancouver airways health literacy tool (VAHLT), a novel measure of skill-based health literacy specific to chronic airway diseases (CADs). Across several phases, psychometric characteristics of the VAHLT were examined and used to guide its development. METHODS: An initial pool of 46 items was developed using input from patients, clinicians, researchers, and policy-makers. An initial patient sample (N = 532) was evaluated and used to inform item revisions. A revised 44-item pool was then evaluated using a second sample, the results of which aided in the selection of a final set of 30 items. The finalized 30-item VAHLT was then psychometrically evaluated using the second sample (N = 318). An item response theory approach was utilized to evaluate the VAHLT by assessing model fit, item parameter estimates, test and item information curves, and item characteristic curves. Reliability was assessed using ordinal coefficient alpha. We additionally assessed differential item functioning between asthma and COPD diagnoses. RESULTS: The VAHLT demonstrated a unidimensional structure and reasonably discriminated patients in the lower range of health literacy estimates. The tool demonstrated strong reliability (α = .920). Two of the 30 items were found to exhibit non-negligible differential item functioning. CONCLUSIONS: This study presents compelling evidence of validity in several areas for the VAHLT, including content and structural validity. Further external validation studies are needed and forthcoming. Overall, this work represents a strong first step towards a novel, skill-based, and disease-specific measure of CAD-related health literacy.

Patient-reported mental health and well-being trajectories in oncology patients during radiation therapy: an exploratory retrospective cohort analysis using the Ontario Cancer Registry.

PURPOSE: Mental health and well-being trajectories are not expected to be homogeneous in diverse clinical populations. This exploratory study aims to identify subgroups of patients with cancer receiving radiation therapy who have different mental health and well-being trajectories, and examine which socio-demographic, physical symptoms, and clinical variables are associated with such trajectories. METHODS: Retrospective analysis of radiation therapy patients diagnosed with cancer in 2017 was conducted using data from the Ontario Cancer Registry (Canada) and linked with administrative health data. Mental health and well-being were measured using items from the Edmonton Symptom Assessment System-revised questionnaire. Patients completed up to 6 repeated measurements. We used latent class growth mixture models to identify heterogeneous mental health trajectories of anxiety, depression, and well-being. Bivariate multinomial logistic regressions were conducted to explore variables associated with the latent classes (subgroups). RESULTS: The cohort (N = 3416) with a mean age of 64.5 years consisted of 51.7% females. Respiratory cancer was the most common diagnosis (30.4%) with moderate to severe comorbidity burden. Four latent classes with distinct anxiety, depression, and well-being trajectories were identified. Decreasing mental health and well-being trajectories are associated with being female; living in neighborhoods with lower income, greater population density, and higher proportion of foreign-born individuals; and having higher comorbidity burden. CONCLUSIONS: The findings highlight the importance of considering social determinants of mental health and well-being, in addition to symptoms and clinical variables, when providing care for patients undergoing radiation therapy.

Has the incidence of total joint arthroplasty in rheumatoid arthritis decreased in the era of biologics use? A population-based cohort study.

OBJECTIVES: To determine whether the introduction of biological DMARDs (bDMARDs) was associated with reduced incidences of total hip and knee arthroplasty (THA/TKA) among patients with RA compared with OA. METHODS: Using a population-based cohort in British Columbia, Canada, RA and OA patients diagnosed between 1995 and 2007 were divided into semi-annual cohorts according to diagnosis date. For each cohort, we calculated 8-year incidence rates of THA and TKA. We compared levels and trends of THA/TKA incidence in RA/OA patients diagnosed during pre-bDMARDs (1995-2001) and post-bDMARDs (2003-2007) periods using interrupted time-series analysis, adjusting for baseline characteristics. Adjusted 8-year total joint arthroplasty incidence estimated for RA/OA cohorts diagnosed five years after bDMARDs introduction were compared with expected rates assuming no bDMARDs introduction, based on extrapolation of pre-bDMARDs trends. RESULTS: We identified 60 227 RA and 288 260 OA incident cases. For cohorts diagnosed pre-bDMARDs, 8-year THA/TKA incidence rates increased over time in both RA and OA. For cohorts diagnosed post-bDMARDs, these rates decreased over time in RA but continued to increase for OA. For RA, differences between the post- and pre-bDMARDs secular trends in incidence rates were -0.49 (P = 0.002) for THA and -0.36 (P = 0.003) for TKA, compared with +0.40 (P = 0.006) and +0.54 (P < 0.001), respectively, for OA. For RA cohorts diagnosed five years after bDMARDs introduction, 8-year incidences were 26.9% and 12.6% lower for THA and TKA, respectively, than expected rates. In contrast, corresponding rates in OA were higher by 11.7% and 16.6%, respectively. CONCLUSION: Arthritis onset after bDMARDs introduction is associated with a significant reduction in THA/TKA incidence in RA, but not in OA. The reduction reflects a significant improvement in RA treatment during the biological era.

The impact of lookback windows on the prevalence and incidence of chronic diseases among people living with HIV: an exploration in administrative health data in Canada.

BACKGROUND: We described the impact of different lengths of lookback window (LW), a retrospective time period to observe diagnoses in administrative data, on the prevalence and incidence of eight chronic diseases. METHODS: Our study populations included people living with HIV (N = 5151) and 1:5 age-sex-matched HIV-negative individuals (N = 25,755) in British Columbia, Canada, with complete follow-up between 1996 and 2012. We measured period prevalence and incidence of diseases in 2012 using LWs ranging from 1 to 16 years. Cases were deemed prevalent if identified in 2012 or within a defined LW, and incident if newly identified in 2012 with no previous cases detected within a defined LW. Chronic disease cases were ascertained using published case-finding algorithms applied to population-based provincial administrative health datasets. RESULTS: Overall, using cases identified by the full 16-year LW as the reference, LWs ≥8 years and ≥ 4 years reduced the proportion of misclassified prevalent and incidence cases of most diseases to < 20%, respectively. The impact of LWs varied across diseases and populations. CONCLUSIONS: This study underscored the importance of carefully choosing LWs and demonstrated data-driven approaches that may inform these choices. To improve comparability of prevalence and incidence estimates across different settings, we recommend transparent reporting of the rationale and limitations of chosen LWs.

Establishing content validity of LIMB-Q Kids: a new patient-reported outcome measure for lower limb deformities.

PURPOSE: To establish the content validity of LIMB-Q Kids, a new patient-reported outcome measure (PROM) for children with lower limb deformities. This study focused on three key components of content validity, i.e., comprehension, comprehensiveness, and relevance. METHODS: Cognitive debriefing interviews (CDIs) with children with lower limb deformities were performed, and expert input from parents and clinicians directly involved in the care of children with lower limb deformities was obtained. CDIs were conducted with children from sites in Australia, Canada, and the USA. All interviews were recorded and transcribed verbatim. Analyses were conducted using the reparative approach, which involved close examination of the transcribed interviews and summarising edits after each interview. RESULTS: Forty patients, experts, and parents reviewed LIMB-Q Kids and provided feedback. At the start, LIMB-Q Kids had 10 scales and 124 total items. Five rounds of input was obtained from children, parents, and experts. Overall, 37 new items were added. Thirty-three of the new items were included to measure symptoms experienced in different parts of the legs. Final version of LIMB-Q Kids had 11 scales and 159 items. CONCLUSION: This study established content validity of the LIMB-Q Kids, a new PROM for children with lower limb deformities. An international field-test study is underway. Translation and cultural adaptation are underway for sites where English is not the first language. Scoring algorithms will be developed, following which the scale could be used to inform clinical practice and research.

Estimating Disease Prevalence in Administrative Data.

PURPOSE: Disease prevalence estimates from population-based administrative databases are often biased due to measurement (misclassification) errors. The purpose of this article is to review the methodology for estimating disease prevalence in administrative data, with a focus on bias correction. SOURCE: Several approaches to bias correction in administrative data were reviewed and application of these methods was demonstrated using an example from the literature: physician claims and hospitalization data were employed to estimate diabetes prevalence in Ontario, Canada. FINDINGS: Misclassification bias in prevalence estimates from administrative data can be reduced by developing and selecting an optimal algorithm for case identification, applying a bias correction formula, or using statistical modelling. An algorithm for which sensitivity equals positive predictive value provides an unbiased estimate of prevalence. Bias reduction methods generally require information about the measurement properties of the algorithm, such as sensitivity, specificity, or predictive value. These properties depend on disease type, prevalence, algorithm definition (including the observation window), and may vary by population and time. Prevalence estimates can be improved by applying multivariable disease prediction models. CONCLUSION: Frequency of a positive case identification algorithm in administrative data is generally not equivalent to disease prevalence. Although prevalence estimates can be corrected for bias using known measurement properties of the algorithm, these properties may be difficult to estimate accurately; therefore, disease prevalence estimates based on administrative data must be treated with caution.

Prevalence of joint-specific osteoarthritis and joint pain in British Columbia, Canada.

The objective is to determine the prevalence of self-reported physician-diagnosed osteoarthritis (OA) and musculoskeletal symptoms (pain, stiffness or discomfort) in specific joints among adults in British Columbia (BC), Canada. We carried out a cross-sectional mixed-mode survey in a random population sample of persons 18 years of age and older. Estimates were weighted to reflect the age and sex distribution of the population of BC. We obtained responses from 2,233 individuals. Overall, 18.4% (95% CI 16.8-20.1) of the adult population reported OA. Of those, more than 40% had OA in multiple sites. Prevalence ranged from 8.8% (95% CI 7.6-10.1) in the knee to 2.7% (2.1-3.5) in the foot. One-year prevalence of symptoms ranged from 49.1% (47.0-51.2) in the lower back to 23.3% (21.5-25.1) in the hip. Females reported more symptoms and OA than males in all joints. The most common site of self-reported physician-diagnosed OA in BC is the knee, but OA in the hands, hips, and feet is also common. Having OA in one joint is a strong predictor of OA in other joints.

Reducing the burden of low back pain: results from a new microsimulation model.

BACKGROUND: Low back pain (LBP) causes the highest morbidity burden globally. The purpose of the present study was to project and compare the impact of three strategies for reducing the population health burden of LBP: weight loss, ergonomic interventions, and an exercise program. METHODS: We have developed a microsimulation model of LBP in Canada using a new modeling platform called SimYouLate. The initial population was derived from Cycle 1 (2001) of the Canadian Community Health Survey (CCHS). We modeled an open population 20 years of age and older. Key variables included age, sex, education, body mass index (BMI), type of work, having back problems, pain level in persons with back problems, and exercise participation. The effects of interventions on the risk of LBP were obtained from the CCHS for the effect of BMI, the Global Burden of Disease Study for occupational risks, and a published meta-analysis for the effect of exercise. All interventions lasted from 2021 to 2040. The population health impact of the interventions was calculated as a difference in years lived with disability (YLDs) between the base-case scenario and each intervention scenario, and expressed as YLDs averted per intervention unit or a proportion (%) of total LBP-related YLDs. RESULTS: In the base-case scenario, LBP in 2020 was responsible for 424,900 YLDs in Canada and the amount increased to 460,312 YLDs in 2040. The effects of the interventions were as follows: 27,993 (95% CI 23,373, 32,614) YLDs averted over 20 years per 0.1 unit change in log-transformed BMI (9.5% change in BMI) among individuals who were overweight and those with obesity, 19,416 (16,275, 22,557) YLDs per 1% reduction in the proportion of workers exposed to occupational risks, and 26,058 (22,455, 29,661) YLDs averted per 1% increase in the proportion of eligible patients with back problems participating in an exercise program. CONCLUSIONS: The study provides new data on the relationship between three types of interventions and the resultant reductions in LBP burden in Canada. According to our model, each of the interventions studied could potentially result in a substantial reduction in LBP-related disability.

Magnetic resonance imaging predictors (cartilage, osteophytes and meniscus) of prevalent and 3-year incident medial and lateral tibiofemoral knee joint tenderness and patellofemoral grind.

OBJECTIVE: To identify magnetic resonance imaging (MRI) predictors (cartilage [C], osteophytes [O] and meniscus [M] scores) of prevalent and 3-year incident medial tibiofemoral (MTF) and lateral tibiofemoral (LTF) knee joint tenderness and patellofemoral (PF) grind.  METHODS: Population-based knee pain cohort aged 40-79 was assessed at baseline (N = 255), 3- and 7-year follow-up (N = 108 × 2 = 216). COM scores were measured at 6/8/6 subregions respectively. Age-sex-BMI adjusted logistic models predicted prevalence versus relevant COM predictors (medial, lateral or patellar / trochlear groove scores). Fully adjusted models also included all relevant COM predictors. Binary generalized estimating equations models predicting 3-year incidence were also adjusted for individual follow-up time between cycles. RESULTS: Significant predictors of prevalent MTF tenderness: medial femoral cartilage (fully adjusted odds ratio [aOR] 1.84; 95% confidence interval [CI] 1.11, 3.05), female (aOR = 3.05; 1.67, 5.58), BMI (aOR = 1.53 per 5 units BMI; 1.10, 2.11). Predictors of prevalent LTF tenderness: female (aOR = 2.18; 1.22, 3.90). There were no predictors of prevalent PF grind in the fully adjusted model. However, medial patellar osteophytes was predictive in the age-sex-BMI adjusted model. There were no predictors of 3-year incident MTF tenderness. Predictors of 3-year incident LTF tenderness: female (aOR = 3.83; 1.25, 11.77). Predictors of 3-year incident PF grind: lateral patellar osteophytes (aOR = 4.82; 1.69, 13.77). In the age-sex-BMI adjusted model, patellar cartilage was also a predictor. CONCLUSION: We explored potential MRI predictors of prevalent and 3-year incident MTF/LTF knee joint tenderness and PF grind. These findings could guide preemptive strategies aimed at reducing these symptoms in the present and future (3-year incidence).

Specific manifestations of knee osteoarthritis predict depression and anxiety years in the future: Vancouver Longitudinal Study of Early Knee Osteoarthritis.

BACKGROUND: To evaluate whether knee osteoarthritis (OA) manifestations predict depression and anxiety using cross-sectional and longitudinal prediction models. METHODS: A population-based cohort (n = 122) with knee pain, aged 40-79, was evaluated at baseline, 3 and 7 years. Baseline predictors were: age decade; sex; BMI ≥ 25; physical exam knee effusion; crepitus; malalignment; quadriceps atrophy; flexion; flexion contracture; Kellgren-Lawrence (KL) x-ray grade (0/1/2/3+); WOMAC pain ≥25; WOMAC stiffness ≥25; self-reported knee swelling; and knee OA diagnosis (no/probable/definite). Depression and anxiety, cutoffs 5+ and 7+ respectively, were measured via the Hospital Anxiety and Depression Scale. We fit logistic models at each cycle using multivariable models selected via lowest Akaike's information criterion. RESULTS: Baseline depression model: sex (female OR = 0.27; 0.10, 0.76) and KL grade (KL 1 OR = 4.21; 1.31, 13.48). Three-year depression model: KL grade (KL 1 OR = 18.92; 1.73, 206.25). Seven-year depression model: WOMAC stiffness ≥25 (OR = 3.49; 1.02, 11.94) and flexion contracture ≥1 degree (OR = 0.23; 0.07, 0.81). Baseline anxiety model: knee swelling (OR = 4.11; 1.51, 11.13) and age (50-59 vs. 40-49 OR = 0.31 [0.11, 0.85]; 60-69 OR = 0.07 [0.01, 0.42]). Three-year anxiety model: WOMAC stiffness ≥25 (OR = 5.80; 1.23, 27.29) and KL grade (KL 1 OR = 6.25; 1.04, 37.65). Seven-year anxiety model: sex (female OR = 2.71; 0.87, 8.46). CONCLUSION: Specific knee OA-related manifestations predict depression and anxiety cross-sectionally, 3 years in the future, and for depression, 7 years in the future. This information may prove useful to clinicians in helping to identify patients most at risk of present or future depression and anxiety, thus facilitating preemptive discussions that may help counter that risk.

The use of latent variable mixture models to identify invariant items in test construction.

PURPOSE: Patient-reported outcome measures (PROMs) are frequently used in heterogeneous patient populations. PROM scores may lead to biased inferences when sources of heterogeneity (e.g., gender, ethnicity, and social factors) are ignored. Latent variable mixture models (LVMMs) can be used to examine measurement invariance (MI) when sources of heterogeneity in the population are not known a priori. The goal of this article is to discuss the use of LVMMs to identify invariant items within the context of test construction. METHODS: The Draper-Lindely-de Finetti (DLD) framework for the measurement of latent variables provides a theoretical context for the use of LVMMs to identify the most invariant items in test construction. In an expository analysis using 39 items measuring daily activities, LVMMs were conducted to compare 1- and 2-class item response theory models (IRT). If the 2-class model had better fit, item-level logistic regression differential item functioning (DIF) analyses were conducted to identify items that were not invariant. These items were removed and LVMMs and DIF testing repeated until all remaining items showed MI. RESULTS: The 39 items had an essentially unidimensional measurement structure. However, a 1-class IRT model resulted in many statistically significant bivariate residuals, indicating suboptimal fit due to remaining local dependence. A 2-class LVMM had better fit. Through subsequent rounds of LVMMs and DIF testing, nine items were identified as being most invariant. CONCLUSIONS: The DLD framework and the use of LVMMs have significant potential for advancing theoretical developments and research on item selection and the development of PROMs for heterogeneous populations.

Efficacy of commonly prescribed analgesics in the management of osteoarthritis: a systematic review and meta-analysis.

OBJECTIVE: Pain management is a cornerstone of osteoarthritis (OA) management. The aim of this review is to obtain current, literature-based estimates of the effect of common pharmacologic treatments on pain reduction in OA. METHODS: A MEDLINE search (2006-2016) was conducted for randomized controlled trials studying acetaminophen, oral NSAIDs, topical NSAIDs, COX-2 inhibitors, and opioids in the treatment of OA pain. Drug effect on pain was estimated using relative change in pain, and expressed as percentage change. An overall effect for each drug category was obtained as a weighted average of study-specific effects, with weights based on each study's sample size. RESULTS: Twenty-nine studies were included. The effect on pain was estimated in a total of 43 treatment arms (acetaminophen n = 6, oral NSAIDs n = 9, topical NSAIDs n = 8, COX-2 inhibitors n = 9, and opioids n = 11). Relative (%) changes in pain were found to be as follows: acetaminophen = 32.5, oral NSAIDs = 34.3, topical NSAIDs = 40.9, COX-2 inhibitors = 36.9, and opioids = 35.4. CONCLUSION: The effects of 5 major drug categories in the treatment of OA pain were reviewed with data extracted from 29 studies published from 2006 to 2016. Acetaminophen was found to have an RC value close to that of oral NSAIDs. The effects of oral NSAIDs, COX-2 inhibitors, and opioids in controlling pain were similar to what has been demonstrated in previous literature. Topical NSAIDs were found to have a greater RC than oral NSAIDs.

Burden of musculoskeletal disorders in the Eastern Mediterranean Region, 1990-2013: findings from the Global Burden of Disease Study 2013.

OBJECTIVES: We used findings from the Global Burden of Disease Study 2013 to report the burden of musculoskeletal disorders in the Eastern Mediterranean Region (EMR). METHODS: The burden of musculoskeletal disorders was calculated for the EMR's 22 countries between 1990 and 2013. A systematic analysis was performed on mortality and morbidity data to estimate prevalence, death, years of live lost, years lived with disability and disability-adjusted life years (DALYs). RESULTS: For musculoskeletal disorders, the crude DALYs rate per 100 000 increased from 1297.1 (95% uncertainty interval (UI) 924.3-1703.4) in 1990 to 1606.0 (95% UI 1141.2-2130.4) in 2013. During 1990-2013, the total DALYs of musculoskeletal disorders increased by 105.2% in the EMR compared with a 58.0% increase in the rest of the world. The burden of musculoskeletal disorders as a proportion of total DALYs increased from 2.4% (95% UI 1.7-3.0) in 1990 to 4.7% (95% UI 3.6-5.8) in 2013. The range of point prevalence (per 1000) among the EMR countries was 28.2-136.0 for low back pain, 27.3-49.7 for neck pain, 9.7-37.3 for osteoarthritis (OA), 0.6-2.2 for rheumatoid arthritis and 0.1-0.8 for gout. Low back pain and neck pain had the highest burden in EMR countries. CONCLUSIONS: This study shows a high burden of musculoskeletal disorders, with a faster increase in EMR compared with the rest of the world. The reasons for this faster increase need to be explored. Our findings call for incorporating prevention and control programmes that should include improving health data, addressing risk factors, providing evidence-based care and community programmes to increase awareness.

A Practical ANOVA Approach for Uncertainty Analysis in Population-Based Disease Microsimulation Models.

OBJECTIVES: To provide a practical approach for calculating uncertainty intervals and variance components associated with initial-condition and dynamic-equation parameters in computationally expensive population-based disease microsimulation models. METHODS: In the proposed uncertainty analysis approach, we calculated the required computational time and the number of runs given a user-defined error bound on the variance of the grand mean. The equations for optimal sample sizes were derived by minimizing the variance of the grand mean using initial estimates for variance components. Finally, analysis of variance estimators were used to calculate unbiased variance estimates. RESULTS: To illustrate the proposed approach, we performed uncertainty analysis to estimate the uncertainty associated with total direct cost of osteoarthritis in Canada from 2010 to 2031 according to a previously published population health microsimulation model of osteoarthritis. We first calculated crude estimates for initial-population sampling and dynamic-equation parameters uncertainty by performing a small number of runs. We then calculated the optimal sample sizes and finally derived 95% uncertainty intervals of the total cost and unbiased estimates for variance components. According to our results, the contribution of dynamic-equation parameter uncertainty to the overall variance was higher than that of initial parameter sampling uncertainty throughout the study period. CONCLUSIONS: The proposed analysis of variance approach provides the uncertainty intervals for the mean outcome in addition to unbiased estimates for each source of uncertainty. The contributions of each source of uncertainty can then be compared with each other for validation purposes so as to improve the model accuracy.

Association of body mass index with knee cartilage damage in an asymptomatic population-based study.

BACKGROUND: Cartilage changes are an important early finding of osteoarthritis (OA), which can exist even before symptoms. Our objective was to determine the prevalence of knee cartilage damage on magnetic resonance imaging (MRI) in an asymptomatic population-based cross-sectional study and to evaluate the association of body mass index (BMI) with cartilage damage. METHODS: Subjects, aged 40-79 years, without knee pain (n = 73) were recruited as a random population sample and assessed for BMI (kg/m2), including current BMI (measured), past BMI at age 25 (self-reported) and change in BMI. Knee cartilage was scored semi-quantitatively (grades 0-4) on MRI. In primary analysis, cartilage damage was defined as ≥2 (at least moderate) and in a secondary analysis as ≥3 (severe). We also conducted a sensitivity analysis by dichotomizing current BMI as <25 vs. ≥25. Logistic regression was used to evaluate the association of each BMI variable with prevalent MRI-detected cartilage damage, adjusted for age and sex. RESULTS: Of 73 subjects, knee cartilage damage ≥2 and ≥3 was present in 65.4% and 28.7%, respectively. The median current BMI was 26.1, median past BMI 21.6, and median change in BMI was a gain of 2.8. For cartilage damage ≥2, current BMI had a non-statistically significant OR of 1.65 per 5 units (95% CI 0.93-2.92). For cartilage damage ≥3, current BMI showed a trend towards statistical significance with an OR of 1.70 per 5 units (95% CI 0.99-2.92). Past BMI and change in BMI were not significantly associated with cartilage damage. Current BMI ≥ 25 was statistically significantly associated with cartilage damage ≥2 (OR 3.04 (95% CI 1.10-8.42)), but not for ≥3 (OR 2.63 (95% CI 0.86-8.03)). CONCLUSIONS: MRI-detected knee cartilage damage was highly prevalent in this asymptomatic population-based cohort. We report a trend towards significance of BMI with cartilage damage severity. Subjects with abnormal current BMI (≥25) had a 3-fold increased odds of cartilage damage ≥2, compared to those with normal BMI. This study lends support towards the role of obesity in the pathogenesis of knee cartilage damage at an asymptomatic stage of disease.

Population Survey Features and Response Rates: A Randomized Experiment.

OBJECTIVES: To study the effects of several survey features on response rates in a general population health survey. METHODS: In 2012 and 2013, 8000 households in British Columbia, Canada, were randomly allocated to 1 of 7 survey variants, each containing a different combination of survey features. Features compared included administration modes (paper vs online), prepaid incentive ($2 coin vs none), lottery incentive (instant vs end-of-study), questionnaire length (10 minutes vs 30 minutes), and sampling frame (InfoCanada vs Canada Post). RESULTS: The overall response rate across the 7 groups was 27.9% (range = 17.1-43.4). All survey features except the sampling frame were associated with statistically significant differences in response rates. The survey mode elicited the largest effect on the odds of response (odds ratio [OR] = 2.04; 95% confidence interval [CI] = 1.61, 2.59), whereas the sampling frame showed the least effect (OR = 1.14; 95% CI = 0.98, 1.34). The highest response was achieved by mailing a short paper survey with a prepaid incentive. CONCLUSIONS: In a mailed general population health survey in Canada, a 40% to 50% response rate can be expected. Questionnaire administration mode, survey length, and type of incentive affect response rates.

The Population Health Model (POHEM): an overview of rationale, methods and applications.

The POpulation HEalth Model (POHEM) is a health microsimulation model that was developed at Statistics Canada in the early 1990s. POHEM draws together rich multivariate data from a wide range of sources to simulate the lifecycle of the Canadian population, specifically focusing on aspects of health. The model dynamically simulates individuals' disease states, risk factors, and health determinants, in order to describe and project health outcomes, including disease incidence, prevalence, life expectancy, health-adjusted life expectancy, quality of life, and healthcare costs. Additionally, POHEM was conceptualized and built with the ability to assess the impact of policy and program interventions, not limited to those taking place in the healthcare system, on the health status of Canadians. Internationally, POHEM and other microsimulation models have been used to inform clinical guidelines and health policies in relation to complex health and health system problems. This paper provides a high-level overview of the rationale, methodology, and applications of POHEM. Applications of POHEM to cardiovascular disease, physical activity, cancer, osteoarthritis, and neurological diseases are highlighted.

Femoroacetabular impingement and osteoarthritis of the hip.

OBJECTIVE: To outline the clinical presentation, physical examination findings, diagnostic criteria, and management options of femoroacetabular impingement (FAI). SOURCES OF INFORMATION: PubMed was searched for relevant articles regarding the pathogenesis, diagnosis, treatment, and prognosis of FAI. MAIN MESSAGE: In recent years, FAI has been increasingly recognized as a potential precursor and an important contributor to hip pain in the adult population and idiopathic hip osteoarthritis later in life. Femoroacetabular impingement is a collection of bony morphologic abnormalities of the hip joint that result in abnormal contact during motion. Cam-type FAI relates to a non-spherical osseous prominence of the proximal femoral neck or head-neck junction. Pincer-type FAI relates to excessive acetabular coverage over the femoral head, which can occur owing to several morphologic variants. Patients with FAI present with chronic, deep, or aching anterior groin pain most commonly in the sitting position, or during or after activity. Patients might also experience occasional sharp pains during activity. A thorough history should be taken that includes incidence of trauma and exercise frequency. A physical examination should be performed that includes a full hip, low back, and abdominal examination to assess for alternate causes of anterior groin pain. Diagnosis of FAI should be confirmed with radiography. Femoroacetabular impingement can be managed conservatively with rest, modification of activities, medications, and physiotherapy, or it can be treated surgically. CONCLUSION: Femoroacetabular impingement is an important cause of anterior groin pain. Early recognition and intervention by the primary care provider might be critical to alleviating morbidity and preventing FAI progression.

Assessing the impact of health-care access on the severity of low back pain by country: a case study within the GBD framework.

BACKGROUND: The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) is key for policy making. Low back pain is the leading cause of disability in terms of years lived with disability (YLDs). Due to sparse data, a current limitation of GDB is that a uniform severity distribution is presumed based on 12-Item Short Form Health Survey scores derived from US Medical Expenditure Panel Surveys (MEPS). We present a novel approach to estimate the effect of exposure to health interventions on the severity of low back pain by country and over time. METHODS: We extracted treatment effects for ten low back pain interventions from the Cochrane Database, combining these with coverage data from the MEPS to estimate the hypothetical severity in the absence of treatment in the USA. Severity across countries was then graded using the Health Access and Quality Index, allowing estimates of averted and avoidable burden under various treatment scenarios. FINDINGS: We included 210 trials from 36 Cochrane systematic reviews in the network analysis. The pooled effect sizes (measured as a standardised mean difference) for the most effective intervention classes were -0·460 (95% uncertainty interval -0·606 to -0·309) for a combination of psychological and physical interventions and -0·366 (-0·525 to -0·207) for surgery. Globally, access to treatment averted an estimated 17·6% (14·8 to 23·8) of the low back pain burden in 2020. If all countries had provided access to treatment at a level estimated for Iceland with the highest Health Access and Quality Index score, an extra 9·1% (6·4 to 11·2) of the burden of low back pain could be avoided. Even with full coverage of optimal treatment, a large proportion (65·9% [56·9 to 70·4]) of the low back pain burden is unavoidable. INTERPRETATION: This methodology fills an important shortcoming in the GBD by accounting for low back pain severity variations over time and between countries. Assumptions of unequal treatment access increased YLD estimates in resource-poor settings, with a modest decrease in countries with higher Health Access and Quality Index scores. Nonetheless, the large proportion of unavoidable burden indicates poor intervention efficacy. This method, applicable to other GBD conditions, provides policy makers with insights into health gains from improved treatment and underscores the importance of investing in research for new interventions. FUNDING: Bill and Melinda Gates Foundation and Queensland Health.