Health Information

1. Raw Health Data
2. Monthly Averages
3. Nutrition vs Exercise vs Glucose
4. Suspected Adverse Reactions
5. Correlations of Monthly Data
6. The Programs

1. Raw Health Data

   1. Raw data for Several variables affecting glucose
   2. Some Raw Data
   3. Some More Raw Data
   4. Nutrition summary (gathered from diet power program) since June 2018 - when I started measuring Peanut Butter & margarine.
   5. Nutrition summary (gathered from diet power program) since 9/1/2007
      Early on I was guessing at peanut butter & margarine. My estimates were way too high which I learned when I started measuring.
      My cholesterol intake was low in spite of the mis-measuring.
   6. Nutrition Obtained from a different program after Diet Power stopped Working
      
   7. Combined Nutrition Info
   8. Combined Nutrition Info Including Less Accurate
   9. Summary of Labs since 2000 (gathered from lab reports)
   10. Summary of Labs done less frequently - correlations below do not include them.
   11. I'm trying to exercise a large consecutive streak (Like duolingo)
   12. Time spent on activities at:
       Time Records
       I started keeping track, because I never seemed to have enough time to do everything I wanted to do!
       

2. Monthly Averages

   1. Result of snobol program - Weight, Glucose, blood pressure and pulse averages
   2. Result of snobol program - Sleep, secondary sleep, exercise and yoga averages
      There were some typos (descending dates) in this file (fixed 1/6/2022). There was error checking for this which was not working - fixed now.
      It would havev also, consequentially affected the correlations below. (they have been rerun now)
   3. Result of snobol program - A few other Items (oxygen, pulse, and temperature)
   4. # of days with # of BMs"
   5. # of times # of days without BM
   6. Other BM info

3. Nutrition vs Exercise vs Glucose

   Compute Coefficients and testing various settings - results will change as I accumulate more testing on the settings

   1. Raw data for Several variables affecting glucose
   2. Processed more accurate monthly data
   3. Processed less accurate monthly data
   4. Raw monthly averages for Several variables affecting glucose
   5. Raw monthly averages for Several variables affecting glucose (more data but less accurate)
   6. Table Of Better General Results For various settings
   7. Table Of Better Specific Results For various settings
   8. Table Of All General Results For various settings
   9. Table Of All Specific Results For various settings
   10. Snobol Program to set constants
   11. Snobol Program to convert monthly average data to form for these programs
   12. Snobol Program to generate Maple Program depending
   13. Generated Maple Program
   14. Sample Maple Output
   15. 1st Snobol Program to massage output of maple Programs
   16. Sample Results with Several Variable Calculations
   17. 2nd Snobol Program to massage output of maple programs
   18. Sample Results with Several Variable Calculations
   19. Icon program to discard some number of low and high coefficients for averaging
   20. Snobol Program Generate Maple Program to Check Coefficients vs Data
   21. Sample Maple Test Program
   22. Snobol Program Massage Maple Program General Output
   23. Snobol Program Massage Maple Program General Output
   24. Snobol Program Massage Maple Program General Output
   25. Snobol Program Massage Maple Program General Output
   26. Icon program to discard worst results
   27. Ruby Program to All Accumulate General Results Into a Table
   28. Ruby Program to Better Accumulate General Results Into a Table
   29. Ruby Program to Accumulate All Specific Results Into a Table
   30. Ruby Program to Accumulate Better Specific Results Into a Table
   31. Intermediate file
   32. Intermediate file
   33. Intermediate file
   34. Intermediate file
   35. shell subscript to run programs
   36. shell script that should gibe very close results for testing
   37. shell scrpt for all data
   38. editing script
   39. editing subscript
   40. editing subscript

4. Suspected Adverse Reactions

   1. Lactose Intolerance
      1. Flatulence - Gas - I've had much trouble with this
      2. Painful BM's - I called it constipation
      3. Fatigue - Severe at times
   2. Gluten intolerance
      1. Rashes - I had severe problems from infant to early 20's
      2. Constipation - Severe problems
      3. Fatigue - Severe at times
      4. Depression and Anxiety - Severe at times
      5. Unexplained aches and pains - Sometimes
   3. Lactose and gluten intolerance
      1. Sinuses - After using lactaid and gluten cutter my sinuses improved dramatically
   4. Caffeine
      1. Totally stopped caffeine 12/6/2022 No Glucose > 100 since 12/10/2022 (as of 1/9/2023)

5. Correlations of Monthly Data

   1. I have fixed problems introduced when separating the "better" (but less) data from the less accurate (but more) data.
      The columns are the names of the correlation, the two data items, and the number of data points, and minimums and maximums for each item.
      Only pairs of data for which data is available for both in the same month.
      NOTE: PO=Personal Observation, DP = Diet Power Program; LA = Lab Reports
      Usually I only have labs every 3 or 4 months - the others are averages.
      A correlation of 1.0 indicates perfect linear correlation. A correlation of -1.0 indicates perfect anti-correlation.
      The closer the correlation is to 1 the better a straight line can go through all the points.
      If there are only 2 points, a straight line always goes through them, so the correlation will be 1.
      The more points there are, the more significant the correlation.
      However there could be a separate common cause such as improvement (or worsening) of diet or exercise.
      NOTE: Many of these correlations could be purely accidental.
      I am just looking for possibilities.
      
   2. Data with peanut butter and margarine measured - less but more accurate diet data
      
      1. I've added the differences (changes) and time (months since January of year of birth) to the master table.
      2. The correlations were calculated in APL, but changed now to Maple (due to memory limitations).
      3. The Monthly Correlations
      4. Particular Correlations (because all are too many to study)
         
         1. Glucose lab correlations
         2. Glucose daily correlations
         3. Glucose 2 hr daily correlations
         4. Glucose 4 hr daily correlations
         5. Glucose 6 hr daily correlations
         6. Glucose 8 hr daily correlations
         7. Glucose 10 hr daily correlations
         8. Glucose 12 hr daily correlations
         9. A1C correlations
         10. Cholesterol
         11. Triglycerides correlations
         12. LDL correlations
         13. H2O (from scales) correlations
         14. water correlations
         15. sugar correlations
         16. protein correlations
         17. fat correlations
         18. fib correlations
         19. Miles walked, biked or playing pool
   3. Data without peanut butter and margarine measured - more but less accurate diet data
      
      1. I've added the differences (changes) and time (months since January of year of birth) to the master table.
      2. The correlations were calculated in APL, but changed now to Maple (due to memory limitations).
      3. The Monthly Correlations
      4. Particular Correlations (because all are too many to study)
         
         1. Glucose lab correlations
         2. Glucose daily correlations
         3. Glucose 2 hr daily correlations
         4. Glucose 4 hr daily correlations
         5. Glucose 6 hr daily correlations
         6. Glucose 8 hr daily correlations
         7. Glucose 10 hr daily correlations
         8. Glucose 12 hr daily correlations
         9. A1C correlations
         10. Cholesterol
         11. Triglycerides correlations
         12. LDL correlations
         13. H2O (from scales) correlations
         14. water correlations
         15. sugar correlations
         16. protein correlations
         17. fat correlations
         18. fib correlations
         19. Miles walked, biked or playing pool
   4. 1. Linux Script to explore data
      2. Linux Script to explore personal observation data
      3. Linux Script to explore diet power data
      4. Linux Script to explore lab data

6. The Programs

   1. Snobol Program to generate Maple Program depending on order
   2. Generated Maple Program - 1st order
   3. Generated Maple - 1st + matching
   4. Generated Masple - + cross
   5. 1st Snobol Program to massage output of maple Programs
   6. 2nd Snobol Program to massage output of maple programs
   7. Snobol Program Chech predictions of Maple programs vs Data
   8. Unicon (really just icon) program to merge data from 4 data files into 1 master file
   9. Snobol4 program adding differences between monthly data.
   10. Unicon program extracting columns to files.
   11. Generating and running Maple for the correlations
   12. Snobol program to massage output - then sorted using Linux sort.
   13. Unicon program for BM stats (working 9/19/2019)
   14. Unicon program for BM stats (working 9/19/2019)