Clinical criteria for the classification of patients with hip pain associated with osteoarthritis (OA) were developed through a multicenter study. Data from 201 patients who had experienced hip pain for most days of the prior month were analyzed. The comparison group of patients had other causes of hip pain, such as rheumatoid arthritis or spondylarthropathy. Variables from the medical history, physical examination, laboratory tests, and radiographs were used to develop different sets of criteria to serve different investigative purposes. Multivariate methods included the traditional “number of criteria present” format and “classification tree” techniques. Clinical criteria: A classification tree was developed, without radiographs, for clinical and laboratory criteria or for clinical criteria alone. A patient was classified as having hip OA if pain was present in combination with either 1) hip internal rotation ≥15º, pain present on internal rotation of the hip, morning stiffness of the hip for ≤60 minutes, and age >50 years, or 2) hip internal rotation <15º and an erythrocyte sedimentation rate (ESR) ≤45 mm/hour; if no ESR was obtained, hip flexion ≤115º was substituted (sensitivity 86%; specificity 75%). Clinical plus radiographic criteria: The traditional format combined pain with at least 2 of the following 3 criteria: osteophytes (femoral or acetabular), joint space narrowing (superior, axial, and/or medial), and ESR <20 mm/hour (sensitivity 89%; specificity 91%). The radiographic presence of osteophytes best separated OA patients and controls by the classification tree method (sensitivity 89%; specificity 91%). The “number of criteria present” format yielded criteria and levels of sensitivity and specificity similar to those of the classification tree for the combined clinical and radiographic criteria set. For the clinical criteria set, the classification tree provided much greater specificity. The value of the radiographic presence of an ostophyte in separating patients with OA of the hip from those with hip pain of other causes is emphasized.

BackgroundThere is limited epidemiological research that provides insight into the complex web of causative and moderating factors that links housing conditions to a variety of poor health outcomes. This study explores the relationship between housing conditions (with a primary focus on the functional state of infrastructure) and common childhood illness in remote Australian Aboriginal communities for the purpose of informing development of housing interventions to improve child health.MethodsHierarchical multi-level analysis of association between carer report of common childhood illnesses and functional and hygienic state of housing infrastructure, socio-economic, psychosocial and health related behaviours using baseline survey data from a housing intervention study.ResultsMultivariate analysis showed a strong independent association between report of respiratory infection and overall functional condition of the house (Odds Ratio (OR) 3.00; 95%CI 1.36-6.63), but no significant association between report of other illnesses and the overall functional condition or the functional condition of infrastructure required for specific healthy living practices. Associations between report of child illness and secondary explanatory variables which showed an OR of 2 or more included: for skin infection - evidence of poor temperature control in the house (OR 3.25; 95%CI 1.06-9.94), evidence of pests and vermin in the house (OR 2.88; 95%CI 1.25-6.60); for respiratory infection - breastfeeding in infancy (OR 0.27; 95%CI 0.14-0.49); for diarrhoea/vomiting - hygienic state of food preparation and storage areas (OR 2.10; 95%CI 1.10-4.00); for ear infection - child care attendance (OR 2.25; 95%CI 1.26-3.99).ConclusionThese findings add to other evidence that building programs need to be supported by a range of other social and behavioural interventions for potential health gains to be more fully realised.

Background: Poor housing conditions in remote Indigenous communities in Australia are a major underlying factor in poor child health, including high rates of skin infections. The aim of this study is to test approaches to data collection, analysis and feedback for a follow-up study of the impact of housing conditions on child health.