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.
Highlights
It is a commonly held belief that a causal relationship exists between local weather conditions and the joint pain and stiffness associated with musculoskeletal disorders [1,2]
Average maximum temperatures around 0 ̊C produce a reduction of approximately index points in hip pain search activity as compared to the 25–30 ̊C baseline
Average maximum temperatures around 0 ̊C produce a reduction of approximately 12 index points in knee pain search activity as compared to the 25–30 ̊C baseline
Summary
It is a commonly held belief that a causal relationship exists between local weather conditions and the joint pain and stiffness associated with musculoskeletal disorders [1,2]. These previous studies have generally been limited in terms of the time period assessed [3,4], geographical scope [5,6], or have focused on seasonal–rather than precise meteorological—variation [7]. Weather and online searches for musculoskeletal pain view data and Twitter data have the potential to be a rich source of information for healthcare researchers on population and regional level trends [10,11,12]. The potential utility of these data in the area of musculoskeletal health research has been demonstrated, with search volumebased time series data from the Google Trends tool having being found to contain significant seasonality and long term trends for searches related to foot and ankle pain [13]
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