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Weather patterns associated with pain in chronic-pain sufferers

Weather patterns associated with pain in chronic-pain sufferers
Weather patterns associated with pain in chronic-pain sufferers

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.

0003-0007
E555-E566
Schultz, David M.
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Beukenhorst, Anna L.
1b1be652-59a9-4331-933b-37c0dc6c8db9
Yimer, Belay Birlie
35af844b-99da-44ae-959a-edfe713eb3c3
Cook, Louise
d582445f-cc55-4748-a103-22806309e054
Pisaniello, Huai Leng
bfdc8d85-b7df-4d76-ba0f-a465a7dd2370
House, Thomas
5446b598-4f58-4cad-9c97-0988d46cc0a2
Gamble, Carolyn
0554881f-d758-4e4a-8a95-17b1e717426d
Sergeant, Jamie C.
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McBeth, John
98012716-66ba-480b-9e43-ac53b51dce61
Dixon, William G.
8fcb2256-4094-4f58-9777-4248ad245166
Schultz, David M.
a85d5745-d1be-42fd-a4a8-45122ee5a243
Beukenhorst, Anna L.
1b1be652-59a9-4331-933b-37c0dc6c8db9
Yimer, Belay Birlie
35af844b-99da-44ae-959a-edfe713eb3c3
Cook, Louise
d582445f-cc55-4748-a103-22806309e054
Pisaniello, Huai Leng
bfdc8d85-b7df-4d76-ba0f-a465a7dd2370
House, Thomas
5446b598-4f58-4cad-9c97-0988d46cc0a2
Gamble, Carolyn
0554881f-d758-4e4a-8a95-17b1e717426d
Sergeant, Jamie C.
12663aff-2633-432e-a8c4-bedfbe1a35a6
McBeth, John
98012716-66ba-480b-9e43-ac53b51dce61
Dixon, William G.
8fcb2256-4094-4f58-9777-4248ad245166

Schultz, David M., Beukenhorst, Anna L., Yimer, Belay Birlie, Cook, Louise, Pisaniello, Huai Leng, House, Thomas, Gamble, Carolyn, Sergeant, Jamie C., McBeth, John and Dixon, William G. (2020) Weather patterns associated with pain in chronic-pain sufferers. Bulletin of the American Meteorological Society, 101 (5), E555-E566. (doi:10.1175/BAMS-D-19-0265.1).

Record type: Article

Abstract

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.

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More information

Published date: 1 May 2020
Additional Information: Publisher Copyright: © 2020 American Meteorological Society.

Identifiers

Local EPrints ID: 491982
URI: http://eprints.soton.ac.uk/id/eprint/491982
ISSN: 0003-0007
PURE UUID: 3784b596-e43b-4343-a773-94aa5b5cdc68
ORCID for John McBeth: ORCID iD orcid.org/0000-0001-7047-2183

Catalogue record

Date deposited: 10 Jul 2024 16:34
Last modified: 12 Jul 2024 02:17

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Contributors

Author: David M. Schultz
Author: Anna L. Beukenhorst
Author: Belay Birlie Yimer
Author: Louise Cook
Author: Huai Leng Pisaniello
Author: Thomas House
Author: Carolyn Gamble
Author: Jamie C. Sergeant
Author: John McBeth ORCID iD
Author: William G. Dixon

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