By PulsHealth. Updated
Research reviewed .
Overview
Fatigue in Apple Health is a reported symptom graded by subjective severity. It does not measure energy expenditure, sleep duration or a sensor-derived recovery score.
What do its category values mean?
| Code | Label | Meaning |
|---|---|---|
| 0 | unspecified | Severity was not specified |
| 1 | notPresent | Symptom was explicitly reported absent |
| 2 | mild | Subjectively mild severity |
| 3 | moderate | Subjectively moderate severity |
| 4 | severe | Subjectively severe severity |
Unspecified is not the same as notPresent. Mild, moderate and severe are subjective labels; the integer codes are not a clinical measurement or a validated pain scale. These values come from Apple’s HKCategoryValueSeverity enumeration.
Can fatigue be compared with sleep and workouts?
Sleep Analysis and workout history can add context when fatigue has also been recorded. Align observations with a defined reporting day or recorded interval and show the denominator of paired observations. If fatigue was entered retrospectively, the saved timestamp may be less precise than workout or sleep timestamps.
Fatigue and sleepiness are different experiences, and a short or long recorded night does not establish why fatigue occurred. Workout calories and heart rate likewise cannot be converted into this symptom category. Describe co-recorded patterns without labeling them overtraining, poor recovery or a medical condition.
What makes a useful fatigue history?
Consistent source labels and explicit notPresent observations help distinguish changing symptoms from changing logging habits. Notes about functional impact can add detail that the category does not contain. A sequence of severe entries is a sequence of subjective reports, not a calibrated physiological decline.
How should logged intervals be read?
This is a logged observation, rather than a regularly sampled sensor reading. Start-to-start gaps describe the saved history and the source’s logging habits. An interval’s length describes what the source saved; it does not by itself establish the symptom’s continuous duration. Record start and end times, source changes and repeated or overlapping entries before interpreting a timeline.
These intervals do not establish continuously measured symptoms or identify a cause. Numeric averages, physiological reference ranges and numeric outlier thresholds do not apply to the category codes.
What did the example data show?
This HealthKit category is not listed in the current PulsHealth sync catalog. No fatigue records were found in the selected database research window; that coverage cannot establish whether corresponding entries exist in Apple Health. Category frequencies, source differences, logging cadence, interval patterns and relationships with other logged observations could not be measured. The absence of records does not establish the absence of the symptom. There is no measured figure or population estimate to infer from this coverage.
Understanding your records
Recording frequency, source and coverage affect what you can conclude from this data. Read the recording guide.