Health of Dennis J. Darland
Mail To: pal at dennisdarland dot com
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Sleep and Health
- About Chronotypes
- I have also read:
Roenneberg, Till - Internal Time: Chronotypes, Social Jet Lag, and Why You're So Tired
- Also see On Sleep
- And see: NY Times article on analyzing medical records
- I think time misperception is one of my biggest problems.
Health and Laughter
- On Norman Cousins (I took the Saturday Review in High School) and Laughter
- On Jim Valvano and Laughter
- For several years I have seldom been laughing - I am going to start trying to laugh using laughter yoga (except practicing alone instead of in a group)
- Laughter Yoga
- Laughter exercises
- More Laughter exercises
Health and Exercise
- Goals in order of priority
- Neck Exercises (60 repetitions of 3 exercises)
- Yoga (meditation - 60 minutes/day)
- Walk 1 mile if weather OK
- Sleep - 6.5 hours/day
- Stationary Bike - 2.2 miles - twice a day
- Stretches - if I find time
- Run to Stay Young
Well - after reading this - I've doubled my stationary cycling from 1.1 miles to 2.1 miles - want to work up to 4.1 miles.
(Odometer doesn't register unless you go extra 0.1 miles). 4.1 miles would be a little over 30 minutes.
I think cycling is easier on knees etc than running is, yet more vigorous than just walking - I plan to continue walking about the same as I have been.
- 6/2/2016 Fixed bug on average weight. I introduced bub in May 2015. Then the battery in the scales wore out. I noticed that the new scales seemed to give me about 5 more pounds. I tried to make the program add 5 pounds on entries on the old scales. Anyway I did it wrong. As I really have no way of knowing when the inaccuracy (if there was one) was introduced, I have gone back the the original, raw, readings.
- NOTE: 9/29/2016 Tooth pulled - letting up on exercise temporarily
- 4/1/2017 Trying to exercise more & especially reduce sugar. - added daily nutrition below.
- Nutrition summary (gathered from diet power program) since 9/1/2007
- Daily Nutrition (gathered from diet power program) since 3/1/2017
- Summary of Labs since 2000 (gathered from lab reports)
- Result of snobol program - Weight, Glucose, blood pressure and pulse averages
- 2/20/2017 - modified program above so I did not need to take glucose measurement every day (0 is just ignored).
- Other fields still are counted - also, one day this month I forgot blood pressure so some other data is missing.
- I decided to make the change because my finger tips need some time to heal.
- Result of snobol program - Sleep, secondary sleep, exercise and yoga averages
- I started on a project of combining most important data in one file: (snobol4 or unicon)
- prepare walking or biking data (miles) - restcmp.sno
- prepare weight & glucose measurement data - glucmp.sno
- prepare nutrition data (miles) - nutrcmp.sno
- Combine data - combine.sno
- Correlate Combined data - comp_map.sno
- Combine data - combine.icn
- Combined data - by combine.sno
- Combined data - by combine.icn
- Correlated data (Including data)
- Correlated data (Summary only)
- Note: Most of October 2015 I had a cold which cut down on exercise.
Glucose - Food Correlations
I tried correlating input of some foods (milk, chocolate, graham crackers & the three combined) with the next days glucose.
The correlation was 0.016 for milk, 0.012 for chocolate, 0.016 for Graham crackers, and 0.010 for the three together.
- Glucose and partial food (high sugar) data
- Snobol program to extract milk data
- Snobol program to extract chocolate data
- Snobol program to extract graham cracker data
- Snobol program to extract milk, chocolate & graham cracker data
- Extract part 1 of data
- Extract part 2 of data
- Milk correlation maple program
- Chocolate correlation maple program
- Graham Cracker correlation maple program
- Milk, chocolate, Graham cracker combined correlation maple program
- Combined script for all 4 correlations
- Combined output
I think the lesson is that the changes in glucose are longer term. One day does not make much difference. It does not mean these foods don't matter long term.
The Resulting Correlations
The columns are the names of the two data types, the correlation, and the number of data points.
NOTE: PO=Personal Observation, DP = Diet Power Program; LA = Lab Reports
A correlation of 1.0 indicates perfect linear correlation. A correlation of -1.0 indicates perfect anti-correlation.
(-2.0 indicates a division by zero was involved in the standard deviation)
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.
- I've added the differences (changes) and time (months since January of year of birth) to the master table.
- Result of APL tests for correlations - I have added deltas (differences) - indicated by 'D' as prefix.
6/27/2015 - Many revisions lately - added some data from new scales - was broken a while - now fixed I think.
6/29/2015 - There had been trouble with the deltas as recently revised - I fixed that today.
- Useful and sufficient data
- Useful but insufficient data
- Useless data
- Bad - because insufficient - data
- Snobol program to analyze Weight, Glucose, Blood Pressure and Pulse records
- I also analyzed my yoga and exercise:
Snobol program to analyze Sleep, Yoga and Exercise Records
- Unicon (really just icon) program to merge data from 4 data files into 1 master file
- C++ (really just c) program to convert data to binary so it can be used by APL program
- APL Functions to correlate data in master combined file - as used for all the correlations in the part above.
- Problems with some APL characters in these pdf's fixed 7/24/2015.
- C++ program to display results of APL - (required too much space for APL)
- Check on APL results with Maple
- Note results were:
Mean Sugar = 104.26 (intake in grams according to dietpower - monthly average)
Mean Glucose = 124.33 (from testing glucose in morning before eating - monthly average)
Standard Deviation Sugar = 18.45
Standard Deviation Glucose = 10.38
Correlation = 0.3319