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. 2017 Aug 9;12(8):e0181266.
doi: 10.1371/journal.pone.0181266. eCollection 2017.

Local weather is associated with rates of online searches for musculoskeletal pain symptoms

Scott Telfer  1 , Nick Obradovich  2   3
Affiliations

Local weather is associated with rates of online searches for musculoskeletal pain symptoms

Scott Telfer et al. PLoS One. .

Abstract

Weather conditions are commonly believed to influence musculoskeletal pain, however the evidence for this is mixed. This study aimed to examine the relationship between local meteorological conditions and online search trends for terms related to knee pain, hip pain, and arthritis. Five years of relative online search volumes for these terms were obtained for the 50 most populous cities in the contiguous United States, along with corresponding local weather data for temperature, relative humidity, barometric pressure, and precipitation. Methods from the climate econometrics literature were used to assess the casual impact of these meteorological variables on the relative volumes of searches for pain. For temperatures between -5°C and 30°C, search volumes for hip pain increased by 12 index points, and knee pain increased by 18 index points. Precipitation had a negative effect on search volumes for these terms. At temperatures >30°C, search volumes for arthritis related pain decreased by 7 index points. These patterns were not seen for pain searches unrelated to the musculoskeletal system. In summary, selected local weather conditions are significantly associated with online search volumes for specific musculoskeletal pain symptoms. We believe the predominate driver for this to be the relative changes in physical activity levels associated with meteorological conditions.

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Conflict of interest statement

Competing Interests: The authors have declared that no competing interests exist.

Figures

Fig 1
Fig 1. Maximum temperatures and searches for pain symptoms.
This figure draws from the estimation of the model in Eq 1 on the weekly search behavior of citizens in 45 US cities between 2011 and 2015. It plots the estimated search activity associated with each maximum temperature bin for each search topic. Search activity for hip pain (panel (a)) and knee pain (panel (b)) increases up to 25–30°C (77-86F) and begins to decline past that point, though the effects of hotter temperatures are estimated with higher uncertainty. Search activity for arthritis symptoms (panel (c)) shows no significant effect of cold temperatures, but shows some decrease for markedly hot maximum temperatures. Search activity for our measure of non-musculoskeletal pain, stomach symptoms (panel (d)), indicates an inverse relationship, with search activity increasing in both cold and hot temperatures relative to more mild temperatures. Shaded error bounds represent 95% confidence intervals.
See this image and copyright information in PMC

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The author received no specific funding for this work.

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