TY - JOUR
T1 - Weather patterns associated with pain in chronic-pain sufferers
AU - Schultz, David M.
AU - Beukenhorst, Anna L.
AU - Yimer, Belay Birlie
AU - Cook, Louise
AU - Pisaniello, Huai Leng
AU - House, Thomas
AU - Gamble, Carolyn
AU - Sergeant, Jamie C.
AU - McBeth, John
AU - Dixon, William G.
N1 - Funding Information:
Acknowledgments. We thank the 10,584 participants in Cloudy with a Chance of Pain who made this study possible with their dedication to daily reporting of their pain levels. We are grateful for the contributions of our patient and public involvement group throughout the study: Carolyn Gamble, Karen Staniland, Shanali Perara, Simon Stones, Rebecca Parris, Annmarie Lewis, Dorothy Slater, and Susan Moore. We gratefully acknowledge the National Oceanic and Atmospheric Administration/National Climatic Data Center Integrated Surface Database (www.ncdc.noaa.gov/isd) for providing the weather data from surface stations. We gratefully acknowledge imagery in Figs. 4–7 provided by the NOAA/ESRL Physical Sciences Division, Boulder, Colorado, from their website (www.esrl.noaa.gov/psd). We thank Bruce Hellman and Ben James at uMotif Limited, London, for their assistance in app design, data collection, and storage. The study app and website were provided by uMotif Limited. The unique flower-like “motif” symptom-tracking interface is owned by uMotif Limited and protected through EU Design Registrations and a U.S. Design Patent. We thank the three anonymous reviewers for their comments. The study was funded by Versus Arthritis (Grant Reference 21225), with additional support from the Centre for Epidemiology (Grants 21755 and 20380). Schultz was partially supported by the U.K. Natural Environment Research Council (Grants NE/I005234/1, NE/I026545/1, and NE/N003918/1). Beukenhorst was supported by a U.K. Medical Research Council doctoral training partnership (Grant MR/N013751/1). Pisaniello is supported by an Australian postgraduate award and the Ken Muirden Overseas Training Fellowship from Arthritis Australia, an educational research grant funded by the Australian Rheumatology Association.
Publisher Copyright:
© 2020 American Meteorological Society.
PY - 2020/5
Y1 - 2020/5
N2 - The belief that weather influences people's health has been prevalent for millennia. Recent studies on the relationship between weather and pain for those who suffer from chronic pain remain indeterminate, with some studies finding strong effects and others finding no effects; most studies face limitations to their study design or dataset size. To address these limitations, a U.K.-wide smartphone study Cloudy with a Chance of Pain was conducted over 15 months with 10, 584 citizen scientists who suffer from chronic pain, producing the largest dataset both in duration and number of participants. Compared to other similar citizen-science studies, our retention of participants was substantially better, with 15% still entering data nearly every day after 200 days. Analysis of the dataset using synoptic climatology and compositing revealed the daily weather associated with a prevalence of high pain and low pain across the population. Specifically, our results indicate that the top 10% of days with a high percentage of participants (about 20%) experiencing a pain event (represented here by a +1 change or greater in their pain level on a 5-point scale; referred to as a high-pain day) were associated with below-normal pressure, above-normal humidity, higher precipitation rate, and stronger wind. In contrast, the bottom 10% of days with a small percentage of participants (about 10%) experiencing a pain event (a low-pain day) were associated with above-normal pressure, below-normal humidity, lower precipitation rate, and weaker wind. Thus, these synoptic weather patterns support the beliefs of many participants who said that low pressure - and its accompanying weather - was associated with a pain event.
AB - The belief that weather influences people's health has been prevalent for millennia. Recent studies on the relationship between weather and pain for those who suffer from chronic pain remain indeterminate, with some studies finding strong effects and others finding no effects; most studies face limitations to their study design or dataset size. To address these limitations, a U.K.-wide smartphone study Cloudy with a Chance of Pain was conducted over 15 months with 10, 584 citizen scientists who suffer from chronic pain, producing the largest dataset both in duration and number of participants. Compared to other similar citizen-science studies, our retention of participants was substantially better, with 15% still entering data nearly every day after 200 days. Analysis of the dataset using synoptic climatology and compositing revealed the daily weather associated with a prevalence of high pain and low pain across the population. Specifically, our results indicate that the top 10% of days with a high percentage of participants (about 20%) experiencing a pain event (represented here by a +1 change or greater in their pain level on a 5-point scale; referred to as a high-pain day) were associated with below-normal pressure, above-normal humidity, higher precipitation rate, and stronger wind. In contrast, the bottom 10% of days with a small percentage of participants (about 10%) experiencing a pain event (a low-pain day) were associated with above-normal pressure, below-normal humidity, lower precipitation rate, and weaker wind. Thus, these synoptic weather patterns support the beliefs of many participants who said that low pressure - and its accompanying weather - was associated with a pain event.
UR - https://www.scopus.com/pages/publications/85086278258
U2 - 10.1175/BAMS-D-19-0265.1
DO - 10.1175/BAMS-D-19-0265.1
M3 - Article
AN - SCOPUS:85086278258
SN - 0003-0007
VL - 101
SP - E555-E566
JO - Bulletin of the American Meteorological Society
JF - Bulletin of the American Meteorological Society
IS - 5
ER -