Weather Patterns Associated with Pain in Chronic-Pain Sufferers

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.

To tolerate weather and to tolerate pain: two sides of the same coin? The Tromsø Study 7

“…Earlier research has found that chronic pain sufferers experience more pain when meteorological variables fall of normal ranges, ie, when barometric pressure is lower and precipitation, relative humidity, and wind speed are higher than normal. 10,32 Such observations are in line with our result of local minima in CPT coinciding with below-normal barometric pressure and above-normal relative humidity. Earlier research has suggested that chronic pain sufferers have a lower pain tolerance.…”

“… 41 In a study of weather patterns and pain, chronic pain sufferers experienced the most pain on days characterized by below-normal barometric pressure, higher precipitation, above-normal relative humidity, and stronger winds. 32 However, other studies have shown conflicting results; many authors have concluded that the effect of weather on pain is either nonexistent or very small. 3 , 42 These conflicting results could be due to differing methodologies, the complexity underlying pain, and how we experience weather.…”

Understanding the Predictors of Missing Location Data to Inform Smartphone Study Design: Observational Study

“…Participants were required to provide electronic consent for study inclusion. Further details are available elsewhere [ 2 , 3 ].…”

“…To determine what daily average weather conditions participants were exposed to, the app recorded participants’ geolocation, which we could link to weather reports from local weather stations. The analysis of the weather and pain association and the details of data collection are described elsewhere [ 2 , 3 ].…”

“…Smartphone location data can be collected frequently (eg, daily, hourly, continuously) over sustained periods of time [ 1 ]. Studies have used these data to quantify exposure to weather [ 2 , 3 ], air pollution [ 4 ], vicinity to tobacco outlets [ 5 ], or to deliver context-aware messages when participants visited health facilities [ 6 , 7 ]. Smartphones can provide complete and accurate location data, especially when participants are provided with study smartphones, studies are short, and data are collected nearly continuously [ 8 , 9 ].…”