Tracking Barometric Changes for Fibromyalgia

What the GRAPH shows

In this example the graph shows that Washington, D.C. has much greater fluctuations in barometric pressure over the sampled time period. Scottsdale, Arizona (green) is next, followed by the least amount of variance in Tampa, Florida (red).

This graph shows the average daily air pressure in the same 3 cities for the year 2004.
Notice the drastic pressure drop in Tampa when there were hurricanes.
This shows Scottsdale to be more moderate.

Using an EXCEL spreadsheet, I imported the historical average barometric 2008 data for 3 cities from :
http://www.wunderground.com/history/
Washington,D.C.
Tampa
Asheville,N.C.

Keep a spreadsheet of your daily local barometric pressure, sampled about twice a day.
Then twice a day fill in your relative "Pain Level".
I used a scale of 1 to 10 (10 being the most painful).
Figure the change in barometric pressure (^B) and the change in your pain level (^P)
between each sample.

In this sample graph Pain and Air Pressure don't rise and fall in unison.
That means this person's pain is not trigered by the amount of pressure.

In this graph our sample person appears to be affected by the amount of CHANGE in the air pressure.
This is shown when the B and P lines both start to change drastictly at the same time.
The yellow line shows ^B / P, the change in barometric pressure divided by the pain level.
This person's pain decreases when the barometer rises, causing the yellow line to go up.
Then the barometer falls and the Pain increases, causing the yellow line to dip below zero.
The yellow line still stays near zero, because the correlation between pain and barometric
change is inversely proportional, so they cancel each other out to some degree.

C = (^B) / (^P / 10)
This graph shows the correlation of air pressure change to the sample person's change in pain levels.
The closer the correlation line comes to Zero, the better the correlation. This graph shows a very stong correlation at first, then followed by more deviation.
A much larger sampling of data is needed to see if this person's pain is directly caused by barometric fluctuations.
Deviations may occur occasionally due to :
1. Errors in reporting
2. Other factors affecting the person's pain level
3. standard deviation allowances

If a year or more of data were collected , this graph would more accurately reflect the Pressure flux to Pain connection.
The closer to the zero line, the more likely this person is affected by changes in barometric air pressure.

Fill in your own data on this worksheet.