Are weather conditions associated with chronic musculoskeletal pain? Review of results and methodologies
Are weather conditions associated with chronic musculoskeletal pain? Review of results and methodologies
Many people believe that weather influences chronic musculoskeletal pain. Previous studies on this association are narratively reviewed, with particular focus on comparing methodologies and summarising study findings in light of study quality. We searched 5 databases (Medline, Embase, Web of Science, PsycINFO, and Scopus) for observational studies on the association between weather variables and self-reported musculoskeletal pain severity. Of 4707 located articles, 43 were eligible for inclusion. The majority (67%) found some association between pain and a weather variable. Temperature, atmospheric pressure, relative humidity, and precipitation were most often investigated. For each weather variable, some studies found an association with pain (in either direction), and others did not. Most studies (86%) had a longitudinal study design, usually collecting outcome data for less than a month, from fewer than 100 participants. Most studies blinded participants to study aims but were at a high risk of misclassification of exposure and did not meet reporting requirements. Pain severity was most often self-reported (84%) on a numeric rating scale or visual analog scale. Weather data were collected from local weather stations, usually on the assumption that participants stayed in their home city. Analysis methods, preparation of weather data, and adjustment for covariates varied widely between studies. The association between weather and pain has been difficult to characterise. To obtain more clarity, future studies should address 3 main limitations of the previous literature: small sample sizes and short study durations, misclassification of exposure, and approach to statistical analysis (specifically, multiple comparisons and adjusting for covariates).
668-683
Beukenhorst, Anna L.
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Schultz, David M.
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McBeth, John
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Sergeant, Jamie C.
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Dixon, William G.
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April 2020
Beukenhorst, Anna L.
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Schultz, David M.
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McBeth, John
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Sergeant, Jamie C.
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Dixon, William G.
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Beukenhorst, Anna L., Schultz, David M., McBeth, John, Sergeant, Jamie C. and Dixon, William G.
(2020)
Are weather conditions associated with chronic musculoskeletal pain? Review of results and methodologies.
Pain, 161 (4), .
(doi:10.1097/j.pain.0000000000001776).
Abstract
Many people believe that weather influences chronic musculoskeletal pain. Previous studies on this association are narratively reviewed, with particular focus on comparing methodologies and summarising study findings in light of study quality. We searched 5 databases (Medline, Embase, Web of Science, PsycINFO, and Scopus) for observational studies on the association between weather variables and self-reported musculoskeletal pain severity. Of 4707 located articles, 43 were eligible for inclusion. The majority (67%) found some association between pain and a weather variable. Temperature, atmospheric pressure, relative humidity, and precipitation were most often investigated. For each weather variable, some studies found an association with pain (in either direction), and others did not. Most studies (86%) had a longitudinal study design, usually collecting outcome data for less than a month, from fewer than 100 participants. Most studies blinded participants to study aims but were at a high risk of misclassification of exposure and did not meet reporting requirements. Pain severity was most often self-reported (84%) on a numeric rating scale or visual analog scale. Weather data were collected from local weather stations, usually on the assumption that participants stayed in their home city. Analysis methods, preparation of weather data, and adjustment for covariates varied widely between studies. The association between weather and pain has been difficult to characterise. To obtain more clarity, future studies should address 3 main limitations of the previous literature: small sample sizes and short study durations, misclassification of exposure, and approach to statistical analysis (specifically, multiple comparisons and adjusting for covariates).
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Published date: April 2020
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Local EPrints ID: 491483
URI: http://eprints.soton.ac.uk/id/eprint/491483
ISSN: 0304-3959
PURE UUID: 079b4720-344c-490b-b8e2-f2e4a2f316a5
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Date deposited: 25 Jun 2024 16:32
Last modified: 26 Jun 2024 02:11
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Author:
Anna L. Beukenhorst
Author:
David M. Schultz
Author:
John McBeth
Author:
Jamie C. Sergeant
Author:
William G. Dixon
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