J2.8 The Relationship between Weather and Pain Severity: Results from Cloudy with a Chance of Pain, A U.K. National Smartphone Study

Monday, 7 January 2019: 3:45 PM
North 228AB (Phoenix Convention Center - West and North Buildings)
David M. Schultz, Univ. of Manchester, Manchester, U.K.; and A. Beukenhorst, B. B. Yimer, L. Cook, A. Gasparrini, Y. Goldschmidt, T. El-Hay, B. Hellman, A. Vicedo-Cabrera, M. Maclure, R. Silva, J. Pisaniello, T. House, M. Lunt, C. Sanders, J. Sergeant, J. McBeth, and W. G. Dixon

Cloudy With a Chance of Pain: A Smartphone Study Examining the Association between Weather and Chronic Pain

David M. Schultz, Jamie Sargeant, John McBeth, Louise Cook, Caroline Sanders, John Ainsworth, Rashmi Lakshminarayana, William G Dixon

Many people suffering from arthritis and other chronic pain conditions have long felt some kind of link between their symptoms and the weather. The largest review of previously published scientific studies investigating any link yields an inconclusive result. The reason for such an inconclusive result is not surprising given the small sample sizes (typically less than 100 patients) and most studies lasting a few weeks at most. Not being exposed to the full-range of weather conditions over the course of the year, or even being exposed to outside weather conditions, further complicates the analysis. Finally, the weather data used was poorly considered in most cases. To resolve these issues, we are undertaking the largest study to date to ask how the pain of patients with chronic pain relates to the weather. Specifically, we are curious about which weather variables provide the most signal and whether there is a time lag. The goal is to identify a plausible physically-based link between the weather and symptoms in people living with chronic pain.

Cloudy With a Chance of Pain (http://cloudywithachanceofpain.com/) is an interdisciplinary study funded by Arthritis Research UK and the UK Medical Research Council. Patients download an app to their smartphone in which they record ten measures each day (eight are specific to their symptoms, whereas two are associated with the amount of time spent outside and level of physical activity). Using the phone’s GPS, the data from the closest weather station to their location is downloaded and linked with their symptoms. For 14 months starting in January 2016, over 13,000 people downloaded the app and participated in the study, producing over 5 million records.

Statistical results from the study will be presented, showing that the relationship between weather and pain is more complicated than the simple data analyses that have been presented in the past. These statistics are consistent with the observed weather patterns associated with events where the top decile of events with a large number of participants report pain and the bottom decile with a few participants report pain.

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