Objective. With aging and obesity trends, the incidence and prevalence of osteoarthritis (OA) is expected to rise in Canada, increasing the demand for health resources. Resource planning to meet this increasing need requires estimates of the anticipated number of OA patients. Using administrative data from Alberta, we estimated OA incidence and prevalence rates and examined their sensitivity to alternative case definitions. Methods. We identified cases in a linked data set spanning 1993 to 2010 (population registry, Discharge Abstract Database, physician claims, Ambulatory Care Classification System, and prescription drug data) using diagnostic codes and drug identification numbers. In the base case, incident cases were captured for patients with an OA diagnostic code for at least 2 physician visits within 2 years or any hospital admission. Seven alternative case definitions were applied and compared. Results. Age-and sex-standardized incidence and prevalence rates were estimated to be 8.6 and 80.3 cases per 1,000 population, respectively, in the base case. Physician claims data alone captured 88% of OA cases. Prevalence rate estimates required 15 years of longitudinal data to plateau. Compared to the base case, estimates are sensitive to alternative case definitions. Conclusion. Administrative databases are a key source for estimating the burden and epidemiologic trends of chronic diseases such as OA in Canada. Despite their limitations, these data provide valuable information for estimating disease burden and planning health services. Estimates of OA are mostly defined through physician claims data and require a long period of longitudinal data.

Methods: This cross-sectional study includes members of the Framingham Foot Study. A validated exam of the foot was used to assess the presence of hallux valgus, hallux rigidus, and plantar fasciitis. To determine foot type, center of pressure excursion index (CPEI) measurements were recorded using the TekScan Matscan (1.4 sensors/ cm2) system. CPEI is a dynamic measure of foot type that uses the concavity of the center of pressure curve in the metatarsal head region, normalized to foot width during the stance phase of gait. In a prior study by Hillstrom et al., utilizing the emed-x plantar pressure system (4 sensors/cm2), CPEI thresholds discriminated planus, rectus (normal arch), and cavus (high arch) feet. Due to the differences in system resolution, a scaling equation was developed in order to determine the equivalent CPEI threshold on a TekScan Matscan system that differentiated planus from non-planus (rectus and cavus) feet. This threshold was defined as a CPEI 19.4% on a TekScan Matscan system. Crude and adjusted logistic regression models, using generalized estimating equations (GEE) to account for the correlation between left and right feet, were used to calculate odds ratios for the relation between foot type and the prevalence of hallux rigidus, hallux valgus, and plantar fasciitis. Adjusted models included age, sex and body mass index (BMI). Results: This study included 2,994 participants (5,778 feet) with an age range of 36-98 years and 55% women. The results are shown in Table 1. Approximately 74% of the study population (mean age¼65.5AE9.9 years) was classified as having pes planus in at least one foot. Those with flat feet were at an increased odds for hallux valgus (OR 1.6, 95% CI 1.4, 1.8) and hallux rigidus (OR 1.6, 95% CI 1.1, 2.3). These results remained significant when adjusted for age, gender, and BMI. Conclusions: Those with planus foot type had a higher odds of hallux valgus and hallux rigidus, but not plantar fasciitis. The high prevalence rate of pes planus in the Framingham cohort may be because the average participant is 66 years old and arch height has been shown to decrease with age. Further, CPEI recordings may be more sensitive to less severe cases of pes planus, contributing to this high prevalence rate. Hallux valgus and hallux rigidus was more prevalent in pes planus versus non-planus feet. This is important because foot structure and function are potentially modifiable factors for these pathologies that have implications for prevention and treatment.

menopause. The mean age was 56.9 AE 10.7years. The intensity of pain was >50/100mm in 64.2% of patients, on a visual analogic scale at the time of diagnosis. Median pain duration was 1 year (Interquartile range: 7months-3.5 years). Obesity was present in 52% of patients, hypertension in 37.2% and diabetes in 8.8%. Knee x-ray showed that 35.5% of patients were beyond grade III according to Kellgen and Lawrence classification. Bilateral bi-compartmental knee osteoarthritis was found in 38.5% of patients, followed by bilateral tri-compartmental knee osteoarthritis in 14.2%. Pain intensity did not correlate with radiological findings whereas there was a positive correlation between pain and Lequesne disability index. Conclusion: Knee osteoarthritis is common in patients in Cameroon. Most patients present at later stages of the disease with a high disability index in a setting where access to health care is limited.

IMS Disease Analyzer database) The cost includes all medical cost to the patients in the cohort, and colligated in the Disease Analyzer database (all consultations with GPs and all resulting drug prescriptions). The evaluated cost is therefore the annual cost of treatment given to an osteoarthritic patient. RESULTS: A total of 18,976 patients suffering from osteoarthritis were followed. For these patients, who had an average age of 66, all consultations with GPs as well as all resulting drug prescriptions were valued both in terms of societal cost and cost to health insurance. The average annual cost of disease management by a GP of a patient suffering from osteoarthritis is therefore valued at €755 societal cost, of which around 60% (€447) is paid by health insurance. The annual cost of treatment by a GP of a patient suffering from hip osteoarthritis is significantly lower at the societal level (€715) than at the health insurance level (€425) compared to patients suffering from osteoarthritis in the knee or elsewhere, despite their higher age. CONCLUSIONS: No literary data evaluating the cost of an osteoarthritic patient currently exists. The closest data is that produced by a COART® France study (Le Pen and coll, Revue du rhumatisme, December 2005). The prevalence of osteoarthritis has been estimated at around 4 million sufferers, even though this figure may be conservative, we can estimate that the cost of osteoarthritis treatment is around 3 billion euros. We are sure that further data will be added to existing ones.

ence-in-difference method was used to estimate changes in fracture rates two years before and after ZOL or OBP initiation. Generalized estimating equation models were used to test the hypothesis of differential changes in fracture rates between ZOL and OBP users, controlling for age, gender, treatment (ZOL vs. OBP), and time (pre-period vs. follow-up period). RESULTS: A total of 3,102 ZOL and 36,961 OBP users met the study criteria. Over the two-year follow-up, ZOL users experienced a significant reduction in fracture rates compared to the two-year prior to ZOL (13.4% vs. 11.2%; pϭ0.008) while fracture rates significantly increased for OBP users (9.0% vs. 9.5%; pϭ0.019). Multivariate regression estimated that the probability of experiencing any fracture decreased by 1.97% between pre-and follow up period for ZOL users (pϭ0.004), increased by 0.46% for OBP users (pϭ0.001), and the difference-in-difference effect was 2.43%, suggesting that ZOL users experienced a significant decrease in fracture rates relative to OBP users (pϽ0.001). CONCLUSIONS: This is the first comparative analysis evaluating fracture rates two years before and two years after the initiation of ZOL and OBP. Use of ZOL significantly reduced fracture rates, compared with the use of OBP.