Objective: To identify how Culturally and Linguistically Diverse (CALD) communities are defined in epidemiological research in Australia and provide a definition of CALD status that aids the consistency and interpretability of epidemiological studies. Methods: Peer-reviewed literature from January 2015 to May 2020 was searched via four databases (Ovid Medline combined with PubMed, Embase, Emcare, and CINAHL) to identify quantitative studies of CALD people in Australia. Results: A total of 108 studies met the criteria for inclusion in the review. Country of birth was the most commonly used CALD definition (n = 33, 30.6%), with combinations of two or more components also frequently used (n = 31, 28.7%). No studies used all the components suggested as core to defining CALD status. including country of birth, languages other than English spoken at home, English proficiency, and indigenous status. Conclusions: There was considerable inconsistency in how CALD status was defined. The review suggests that CALD status would best be defined as people born in non-English speaking countries, and/or who do not speak English at home. Additionally, indigenous peoples should be considered separately. This recommended definition will support the better identification of potential health disparity and needs in CALD and indigenous communities.

We aimed to develop and test a literature-based model for symptoms that associate with cardiac causes of syncope. Seven studies (the derivation sample) reporting ≥2 predictors of cardiac syncope were identified (4 Italian, 1 Swiss, 1 Canadian, and 1 from the United States). From these, 10 criteria were identified as diagnostic predictors. The conditional probability of each predictor was calculated by summation of the reported frequencies. A model of conditional probabilities and a priori probabilities of cardiac syncope was constructed. The model was tested in four datasets of patients with syncope (the test sample) from Calgary (n=670; 21% had cardiac syncope), Amsterdam (n=503; 9%), Milan (n=689; 5%) and Rochester (3877; 11%). In the derivation sample ten variables were significantly associated with cardiac syncope: age, gender, structural heart disease, low number of spells, brief or absent prodrome, supine syncope, effort syncope, and absence of nausea, diaphoresis and blurred vision. Fitting the test datasets to the full model gave C-statistics of 0.87 (Calgary), 0.84 (Amsterdam), 0.72 (Milan) and 0.71 (Rochester). Model sensitivity and specificity were 92% and 68% for Calgary, 86% and 67% for Amsterdam, 76% and 59% for Milan, and 73% and 52% for Rochester. A model with 5 variables (age, gender, structural heart disease, low number of spells, and lack of prodromal symptoms) was as accurate as the total set. A simple literature-based Bayesian model of historical criteria can distinguish patients with cardiac syncope from other patients with syncope with moderate accuracy.

The aim of this study was to investigate the impact of motorcycle to car transitioning and urbanisation on traffic injury rates in Thailand. Analysis of two consecutive surveys of a large national cohort study. Thailand. The data derived from 57,154 Thai Cohort Study (TCS) participants who provided relevant data on both the 2005 and 2009 surveys. Motorcycle and car traffic crash injury self-reported in 2009, with twelve months’ recall. In 2009, 5608(10%) participants reported a traffic crash injury. Most crashes involved a motorcycle (74%). Car access increased and motorcycle use decreased between 2005 and 2009. Among those who used a motorcycle at both time points, traffic injury incidence was 2.8 times greater compared to those who did not use a motorcycle at either time point. Multivariable logistic regression models were used to test longitudinal and cross sectional factors associated with traffic crash injury: in the adjusted model, cars were negatively and motorcycles positively associated with injury. Living in an urban area was not injury protective in the adjusted model of traffic crash injury. Ongoing urbanisation in Thailand can be expected to lead to further reductions in road traffic injuries based on transition from motorcycles to cars in urban areas. Cities, however, do not provide an intrinsically safer traffic environment. To accommodate a safe transition to car use in Thailand, traffic infrastructural changes anticipating the growing car density in urban areas is warranted.