The cumulative model is a way of viewing your profile that prioritizes continuity and usability over treating each measurement as an isolated event.
It exists to solve a practical problem:
In real life, you rarely measure everything at the same time — yet you still want a coherent picture of your current body state.
TL;DR
A cumulative view is not “the last measurement”.
It is the latest valid state per measurement point.
Why the Cumulative Model Exists
A single measurement session is a snapshot — a complete record of what you measured at that moment.
But over time:
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some measurements change frequently (weight, waist)
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others change slowly (height, limb lengths)
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some are only measured occasionally
Re-entering everything every time is unnecessary and often impractical.
The cumulative model was created to:
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reduce repetitive input
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preserve continuity across sessions
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allow partial measurements without breaking interpretation
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keep derived metrics and indexes usable between full measurements
It is a structural convenience, not an intelligent estimator.
What the Cumulative Model Is (and Is Not)
What it is
The cumulative model is a composite view built by:
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Ordering all measurements chronologically
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Taking the most recent valid value for each measurement point
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Assembling them into a single, complete body model
No averaging. No prediction. No inference.
What it is not
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It does not create new data
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It does not smooth values
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It does not replace real measurements
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It does not imply that values were measured together
It simply maps forward existing data.
How It Differs From a Single Past Measurement
| Aspect | Single Measurement | Cumulative Model |
|---|---|---|
| Represents | One moment in time | Best-known current state |
| Uses values from | That session only | Multiple sessions |
| Requires full input | Yes | No |
| Suitable for history review | Yes | No |
| Suitable for current interpretation | Limited | Yes |
| Can mix measurement dates | No | Yes (by design) |
Where You’ll Find It
Inside the Body Composition module, the cumulative model is available from:
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The Body Composition → Measurement Date Selector
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Alongside individual measurement dates
You can switch between:
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Individual measurements → historical snapshots
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Cumulative view → current composite state
The active view is always clearly labeled.
How the Cumulative Model Behaves
When a value is not re-entered:
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The last valid value is carried forward
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Dependent indexes remain calculable
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Interpretation remains continuous
When a value is updated:
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It replaces the previous value from that point onward
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History remains intact
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No retroactive changes occur
This allows partial measurements without breaking the model.
When the Cumulative Model Is Useful
Use the cumulative model when:
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Performing frequent, partial measurements (Partial & Targeted Measurements)
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Updating only what changed
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Reviewing current interpretation between full sessions
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Avoiding repetitive input
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Maintaining continuity for AI interpretation and indexes
Typical examples:
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Weekly weight + waist, monthly full measurement
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Short intervention phase with targeted checks
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Interim tracking between clinic or scan visits
Important
If overused without awareness, carried-forward values can create the appearance of continuity without new information. Short-term interpretation becomes less precise, and long-term overuse can lead to an invalid profile for interpretation.
Best Practice Summary
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Use individual measurements for history and comparison
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Use cumulative view for continuity and current interpretation
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Re-measure key values intentionally
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Do not rely on carry-over indefinitely
Key takeaway
The cumulative model is a tool to improve usability, not a shortcut for bad habits.