I had been doing one-month tracking experiments for years. Each produced specific insights. None had given me the full annual picture of my own patterns.
For 12 months I tracked daily: weight (morning, fasted), energy 1-5, mood 1-5, sleep duration, plus what I had done that day in several categories.
Here is what the data showed about what actually drives my wellness baseline.
The setup
Tracked daily, end of day, in a notebook:
- Weight (morning, fasted, in kg)
- Energy 1-5
- Mood 1-5
- Hours of sleep previous night
- Exercise yes/no and intensity
- Alcohol yes/no
- Significant stress yes/no
- Notable food choices (specifically high or low quality eating)
Took about 3 minutes per day. Sustained for 365 days (missed maybe 8 days).
The strongest predictor of high-energy days
By a substantial margin: previous-night sleep duration.
Days following 7+ hours of sleep averaged energy 4.0/5. Days following less than 6.5 hours averaged 2.8/5. A 1.2-point difference attributable to sleep alone.
This was larger than I expected. I had assumed exercise, food, and other factors would matter more. The sleep effect dominated everything else.
The strongest predictors of mood
Slightly more complicated than energy:
- Sleep duration (similar effect to energy)
- Exercise that day (about 0.6 point difference)
- Meaningful social interaction (about 0.5 point difference)
- Time outside (about 0.4 point difference)
The interesting finding: these effects were largely additive. A day with all four factors (good sleep + exercise + social + outside) averaged 4.5/5 for mood. A day with none averaged 2.5/5.
The strongest predictors of weight
Weight tracking over a year reveals patterns that monthly tracking misses.
The strongest predictors of weight changes:
- Alcohol (next-day weight typically up 1-2 lbs from water retention)
- High-sodium meals (similar effect, transient)
- Significant stress periods (modest weight gain over weeks)
- Travel periods (weight gain from disrupted patterns)
What did NOT correlate strongly with weight:
- Specific food types beyond sodium
- Exercise on specific days
- Time of meals
- Specific macronutrient ratios
The data suggests that for me, weight is more affected by gross patterns (alcohol, stress, travel disruption) than by specific food choices.
The seasonal patterns
Twelve months covered all four seasons. Several seasonal patterns emerged:
- Winter mood was lower (about 0.5 point reduction November-February)
- Winter weight was higher (about 3-5 lbs heavier than summer)
- Summer energy was higher (about 0.3 point improvement)
- Sleep was more consistent in summer (less seasonal variation)
The seasonal effects were real but smaller than expected. The day-to-day factors mattered more than the season.
The day-of-week patterns
Some predictable patterns:
- Mondays: lower mood (about 0.4 below average)
- Tuesday-Thursday: most consistent baseline
- Friday-Saturday: highest mood
- Sunday: highest morning, lower evening
These patterns were consistent enough to be reliable. Helpful for planning important meetings, exercise, social activities.
What I learned about my own patterns
The macro insights from a year of tracking:
1. Sleep is foundational. Almost every other variable depends on adequate sleep. Protect it relentlessly.
2. The combination matters. Single positive factors help. Multiple positive factors stack to create excellent days.
3. Negative factors compound. Bad sleep + alcohol + stress produces substantially worse outcomes than any single factor.
4. Specific dietary obsessions did not matter as much as I thought. Gross patterns (sodium, alcohol) mattered. Specific food rules did not show clear effects.
5. Tracking itself changes behavior. Knowing I would record patterns nudged me toward better choices. The Hawthorne effect was useful.
What I changed because of the data
Several specific changes based on what the year revealed:
1. Sleep became truly non-negotiable. 7+ hours target with explicit phone-off-by-9 PM rule.
2. Reduced weeknight alcohol. The next-day cost was too consistent to ignore.
3. Daily walks even when busy. The mood and energy benefits were too consistent to skip.
4. Stopped weighing daily. The fluctuations were noise rather than signal in most cases. Switched to weekly weighing.
5. Stopped specific food restrictions. The data did not support strict dietary rules. Returned to general moderate eating.
What surprised me about the year
Things I had not expected:
The boring fundamentals were the dominant variables. Sleep, exercise, sun, social interaction. These are the things wellness influencers underweight in favor of supplements, specific diets, and protocols.
Stress affected everything. Stressful weeks showed up in weight, sleep, mood, energy simultaneously. Stress management is wellness management.
Consistency mattered more than intensity. Daily moderate exercise outperformed occasional intense exercise. Consistent moderate sleep outperformed cycling between extremes.
Most "wellness optimization" advice was noise. The dramatic claims about specific protocols mostly did not show up in my data. The boring advice about basics was strongly supported.
What I learned about tracking
Several meta-observations from a year of daily tracking:
1. 12 months is the right minimum for seasonal patterns. Shorter periods miss the annual cycle.
2. Multiple variables tracked together reveal interactions. Single-variable tracking misses patterns.
3. Daily tracking is sustainable. Detailed tracking is not. Three minutes a day is sustainable for years. Thirty minutes a day is not.
4. The data will tell you something uncomfortable. For me it was the alcohol effects. Yours will be different but there will be one.
5. Most of the value is in the accumulated picture. Individual data points are noise. Patterns over months are signal.
This is not health advice
Your data will be different. Your patterns will be different. The point of writing this is the methodology — sustained tracking reveals patterns intuition misses.
Most wellness advice is generic because it is written for anyone. Your wellness data is specific to you. The patterns you find will inform decisions better than any general advice.
The takeaway
A year of self-tracking reveals the actual drivers of your wellness baseline. The drivers are usually fewer and more fundamental than wellness culture suggests.
If you want to actually improve your wellness rather than just consume content about wellness, track yourself for at least 6 months. Look at what the data says actually matters. Make changes based on that. The compounding effect over years is substantial.
