Understanding Correlations in Trendwell

You've been tracking for a few weeks. Now Trendwell shows you correlations: "Sleep quality correlates with your weight trend." What does that mean? And what should you do about it?

Here's how to understand and use correlations in Trendwell.

What Is a Correlation?

A correlation means two things tend to vary together:

Positive correlation: When one goes up, the other tends to go up

• Example: High stress days AND higher BP readings

Negative correlation: When one goes up, the other tends to go down

• Example: More sleep AND lower weight

No correlation: They don't seem related

• Example: Caffeine intake and your weight (maybe)

Key Insight: Correlation means relationship, not causation. But consistent correlation suggests a lever worth testing.

How Trendwell Shows Correlations

Correlation Strength

Strength	What It Means
Strong	Clear pattern in your data
Moderate	Noticeable pattern, some noise
Weak	Pattern exists but inconsistent
None	No apparent relationship

Example Correlations

"Poor sleep nights correlate with weight being higher the next day (moderate)"

"High-sodium days correlate with elevated BP readings 24-48 hours later (strong)"

"Movement days correlate with better energy ratings (moderate)"

Reading Your Correlations

Strong Correlations

What they mean: This input clearly affects your outcome

What to do:

• This is a high-priority lever
• Test it with intentional changes
• Likely to matter for your goals

Moderate Correlations

What they mean: There's a relationship, but other factors also matter

What to do:

• Worth paying attention to
• Test if strong correlations are already optimized
• May become clearer with more data

Weak/No Correlations

What they mean: This input doesn't seem to affect your outcome much (for YOU)

What to do:

• Don't prioritize this input
• Focus elsewhere
• May change with more data or different circumstances

Important Caveats

Correlation ≠ Causation

Just because two things correlate doesn't mean one causes the other:

• Both could be caused by a third factor
• The relationship could be coincidental
• But for practical purposes, if the correlation is consistent, it's worth acting on

Your Data, Your Body

Correlations are personal:

• Your correlations may differ from others
• What affects your friend's weight may not affect yours
• Trust YOUR data over generic advice

More Data = Better Insights

Early correlations (2-3 weeks) are preliminary. With more data:

• Patterns become clearer
• False correlations disappear
• True patterns strengthen

Acting on Correlations

The Experiment Approach

When you see a correlation:

1. Hypothesize: "I think improving this input will improve my outcome"

2. Test: Change that ONE input for 2-4 weeks

3. Measure: Did the outcome change?

4. Conclude: Correlation confirmed or not?

Example

Correlation shown: Poor sleep correlates with higher BP

Hypothesis: "If I improve my sleep, my BP will improve"

Test: Earlier bedtime for 3 weeks, track BP

Measure: Compare BP average before vs. after

Conclusion: "My BP dropped 6 points. Sleep is indeed a key lever for me."

Multiple Correlations

When multiple inputs show correlations:

Prioritize by Strength

Focus on strongest correlations first—they're your biggest levers.

Consider Controllability

Strong correlation + high control = priority target

Test One at a Time

If you change multiple inputs, you won't know what helped.

When Correlations Don't Make Sense

Possible Explanations

• Not enough data: Give it more time
• Confounding factors: Something else is driving both
• Measurement issues: Inconsistent tracking creates noise
• It's real but unexpected: Your body is unique

What to Do

• Keep tracking
• Look for patterns in the noise
• Discuss surprising findings with healthcare providers

The Bottom Line

Correlations in Trendwell:

1. Show relationships between your inputs and outcomes
2. Are personalized to YOUR data
3. Suggest (not prove) causal relationships
4. Guide prioritization of your efforts
5. Become more reliable with more data

Use correlations to identify your most impactful inputs, then test them to confirm.

Next Steps

• Read: Finding Your Blood Pressure Correlations
• Read: Finding Your Weight Correlations
• Read: Running Energy Experiments
• Review: Your current correlations in Trendwell
• Test: Your strongest correlation with intentional changes

Correlations are where data becomes actionable. Use them wisely.

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Last updated: January 2026