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About the results
  1. 1. What did the study find?

    Higher humidity, lower pressure, and stronger winds – in that order – were significantly associated with increased pain.
  2. 2. What kind of weather is most likely to be associated with increased pain?

    A humid and windy day with low pressure.
  3. 3. What kind of weather is least likely be associated with increased pain?

    A dry and calm day with high pressure.
  4. 4. On a 'bad' weather day (humid, low pressure, windy) how much more likely am I to feel an increase of pain?
    On a humid windy day with low pressure, painful days were 20% more likely compared to a day with average weather. This would translate to an increase in the risk of a painful day from, say, 5 in 100 to 6 in 100.
  5. 5. You found no association with temperature? My pain is definitely worse in the cold…

    We wouldn't discount people's experiences, and it's possible to have more pain on a cold day or a warm day depending on what's happening with other weather components. For example, cold days could be more painful if they were also damp and windy. We know that days with low pressure are also windy and humid, and are often associated with cold air. So, this association might explain the association between cold and pain.
    What we did in the analysis was to disentangle the relative importance of the different components of the weather (specifically, temperature, humidity, wind, and pressure). We found that temperature did not have a significant statistical association with pain if anything else was held constant, whereas the other components did. Our results might mean that the cold is merely associated with the other components, and these other components are the primary mechanisms for why pain increases on these days (in other words, being humid and windy with low pressure).
    We also know that our analysis considered the average pattern across the population. It is possible that individuals have a different association from the average, and thus some people feel these results do not match their experience. Future analyses hope to explore different patterns of weather-pain relationship in more detail.
  6. 6. If certain weather could increase my pain, could I avoid this by staying in on 'bad' weather days?

    Some elements of weather (such as wind and rainfall) can be avoided by staying inside. However, others like pressure are similar when indoors compared to outdoors. There is a lag between outdoor and indoor humidity: for example, if the air is very humid outside, there would be a delay while the inside humidity rises to match the outside humidity. Of course, taking baths, cooking, and respiration helps to raise the indoor humidity.
  7. 7. How does the weather cause more pain?

    Our study did not examine the mechanism by which weather influences pain. Other researchers have suggested why different aspects of the weather may influence pain but few have been conclusively proven. Pressure has been suggested to have a direct effect on joints and their altered anatomy in patients with arthritis. We know that how the pressure varies across the Earth has a direct link with the wind (i.e., strong gradients in pressure between locations are associated with strong winds), so wind could have been identified in our study only because of its association with the pressure. Fewer hypotheses exist to explain the possible effect of humidity.
  8. 8. What's the point in this research? You can't change the weather!

    People have been talking about the relationship between weather and pain for over two thousand years, and around three-quarters of people with arthritis believe the weather impacts on their pain and other arthritis-related symptoms. This research validates those beliefs. If you know that certain weather might increase your pain, you can plan your activities around it and plan to do more burdensome activities on days when your pain might be lower. Now that we know more about the relationship between weather and pain, other scientists may start to investigate the mechanisms by which these weather variables influence pain, which may in turn open the door to new innovations in treatment.
  9. 9. You're telling us what we already know (just ask my Grandma).

    Previous research has been inconclusive. This study provides strong evidence of how weather relates to pain, in particular how the various inter-related components of weather are important. This is essential knowledge to develop new treatments and help people to take control of their life, by planning activities in advance.
  10. 10. Do different people respond differently to the weather?

    The effect of pressure and wind speed seems largely consistent across different pain conditions. However, relative humidity appeared to affect patients with osteoarthritis more than with other conditions. We suspect there are people that are more or less sensitive to the weather and that is an analysis we plan to carry out in the future.
  11. 11. Isn't mood more likely to affect pain, rather than weather on its own? When it's warm and sunny you're in a better mood and so you feel less pain.

    Indeed, in our study, mood had a strong relationship with pain. However, this relationship didn't explain the observed association between weather and pain.
  12. 12. How strong were the effects of weather, compared to other factors such as mood and exercise?

    Mood had a stronger association with pain compared to the effect of the weather, whereas physical activity had a similar strength of association as the weather.
  13. 13. People can see what the weather's like. Won't they just report more pain when the weather fits with their beliefs?

    At the start of the study, the majority of participants thought weather did influence pain and the most common beliefs were that rain and cold caused pain. If people reported more pain on rainy or cold days because of this bias, we would have expected to see an association with rainfall and low temperature. However, neither rainfall nor cold were found to be associated with pain, meaning this possible bias does not explain our findings. We also did not find any differences between those with a stronger or a weaker belief in which weather conditions increase pain. This provides reassurance that our results are not explained by people reporting what they thought their pain ought to be, given that day's weather.
  14. 14. Did you measure whether people took medication/pain relief?

    Yes, we asked people once at the start of the study; we didn't ask them to record their medication use every day as we thought this would be too much data recording and cause people to drop out of the study.
  15. 15. How can you know whether medication had more of an impact on pain levels than weather?

    In this study we did not record medication every day, and therefore we are not able to know the extent to which this affects people's pain levels within our study.
  16. 16. Pain is very subjective. How can you compare different people's pain?

    For our analysis, we only compared pain levels within individuals, not between people. The analysis considered days on which an individual had a meaningful increase in pain, then compared the weather on that day to the weather on a day within the same month when they didn't have an increase in pain.
  17. 17. Is there anything I can do to reduce the negative impact of the weather on pain? For example, using a dehumidifier or cold packs?

    We haven't studied this, but we hope it's an area of future research. The charity Versus Arthritis offer great tips and advice on how to manage the symptoms during cooler and warmer temperatures. You can visit their website to find out more.
  18. 18. Why have people with arthritis been advised to spend time in warm climates?

    Patients have anecdotally reported a positive benefit of spending time in warmer climates for many years. The prevailing high pressure systems and associated dry, calm air may have a positive effect on their pain levels.
  19. 19. How can wind speed affect pain if you're indoors?

    It is likely not the wind per se that affects pain, but the other meteorological variables that the wind is related to. Strong gradients of atmospheric pressure across the UK appear to be related to days where a higher than average number of people report pain. When the pressure gradient is strong, the winds tend to be strong as well.
  20. 20. Why did you use relative humidity rather than an absolute measure of water vapour in the air such as specific humidity, mixing ratio, or dewpoint temperature?

    The results were similar for whatever measure of atmospheric moisture was used. For the specific type of analysis in this study, relative humidity fit the conditions needed for the analysis better than the other measures.
About the study
  1. 1. What question did Cloudy with a Chance of Pain try and answer?

    For thousands of years, people have reported that weather affects their pain. Our study tried to answer that question. We were also interested to learn what aspect of the weather affects pain the most (for example, wind, pressure, temperature, or humidity).
  2. 2. How did it work?

    Anyone interested could visit the Cloudy with a Chance of Pain website to check eligibility (17 years+, living with a chronic pain condition for at least three months, live in the UK), then download an app to their Android or Apple phone. After filling in a short questionnaire and a consent form, people were asked to answer ten quick questions every day on the app. The GPS functionality in their phone allowed us to match their location to local weather data.
  3. 3. What questions were people asked?

    On a five-level scale, people were asked to rate the following every day:
    Pain severity
    Morning stiffness
    Waking up feeling tired
    Impact of pain
    Sleep quality
    Time spent outside
    Physical activity
  4. 4. How many people signed up to take part?

    13,207 downloaded the app. For the analysis, we used data from 2,658 participants. This figure was lower because the analysis could only include people who had at least one time where they had a meaningful increase in their pain and where that could be paired with a time within the same month when their pain didn't increase.
  5. 5. How long did the study run for?

    15 months: from January 2016 until April 2017.
  6. 6. In which locations did people take part?

    From all across the UK, with people from every single postcode area in the country (124).
  7. 7. Why have previous studies into the relationship between weather and pain been inconclusive?

    Limitations of previous studies included:
    - Not studying a large and varied enough group of people
    - Not tracking weather and symptoms for long enough, through seasons
    - Not recording weather conditions where people are living and working
  8. 8. Who funded the study?

    Versus Arthritis (previously Arthritis Research UK)
  9. 9. On average, how long did people enter their data for?

    For the data used in the analysis, people entered data into the app for just under 6 months, typically on around 75% of possible days.
  10. 10. Who took part?

    People who had the following pain conditions took part: arthritis, fibromyalgia/widespread chronic pain, migraine and neuropathic pain. The majority of people had some form of arthritis. In the final analysis, there were mainly women (83%) and the median age was 51.
  11. 11. Are people still using the app to track their symptoms against the weather now?

    The study finished and the dataset used for the results was locked in 2017. The intention was always to keep the app open for people to keep tracking their symptoms if they found it useful for their own knowledge. Two years later people are still using the app for this purpose. This data is not being formally collected as part of the study dataset.The app is not open to
  12. 12. What's next for the app and this study?

    Cloudy with a Chance of Pain is now closed to recruitment and therefore the study app is not open to new subscribers. The study team are continuing to analyse the data to examine patterns of changing symptoms with time, and further explore the relationship between symptoms and the weather.

Interested in hearing more? Check out our blog.