Patients with chronic pain commonly believe their pain is related to the weather. Scientific evidence to support their beliefs is inconclusive, in part due to difficulties in getting a large dataset of patients frequently recording their pain symptoms during a variety of weather conditions. Smartphones allow the opportunity to collect data to overcome these difficulties. Our study Cloudy with a Chance of Pain analysed daily data from 2658 patients collected over a 15-month period. The analysis demonstrated significant yet modest relationships between pain and relative humidity, pressure and wind speed, with correlations remaining even when accounting for mood and physical activity. This research highlights how citizen-science experiments can collect large datasets on real-world populations to address long-standing health questions. These results will act as a starting point for a future system for patients to better manage their health through pain forecasts.

BackgroundGout has an increasing global prevalence. Underutilization of urate-lowering therapy (ULT) is thought to be common, via both suboptimal dosing and poor medication adherence. The aims of this study were to determine the prevalence of self-reported gout and the key predictors of ULT use in those with gout in a representative population survey in South Australia.MethodsData were obtained from the Spring 2015 South Australian Health Omnibus Survey, a multilevel, systematic, survey in a representative population sample involving face-to-face interviews (n = 3005). This study analyzed responses from respondents aged ≥ 25 years (n = 2531) about self-reported gout, ULT use, sociodemographic factors, lifestyle factors, and comorbidities, using survey weighting. Univariate and subsequent adjusted logistic regression analyses on self-reported gout were performed. ULT use was divided into three categories (never use, prior use, and current use) and these data were analyzed using a multinomial logistic regression model.ResultsSelf-reported gout prevalence was 6.8% (95% CI 5.8, 7.9). The mean age of respondents with gout was 64 years (standard deviation 16) and 82% were male. As expected, older age, male gender, lower socioeconomic status (SES), and higher body mass index (BMI) were associated with gout, as were high alcohol consumption, current smoking, other forms of arthritis, and hypertension or hypercholesterolemia medication, after adjustment for sociodemographic variables. Two thirds of respondents with gout reported ULT use (36% current; 29% previous) with only 55% continuing treatment. Predictors of ULT use included male gender, low SES, and concomitant cholesterol-lowering therapy. Respondents with gout with a higher BMI were more likely to remain on ULT.ConclusionsDespite gout being a common, potentially disabling joint disease, only 55% of respondents with gout in this study adhered to ULT. Identification of key predictors of ULT use will provide guidance on prescribing strategy in clinical practice and on the quality of gout care in the community.Electronic supplementary materialThe online version of this article (10.1186/s13075-018-1633-9) contains supplementary material, which is available to authorized users.