What blood_glucose measures
blood_glucose is the day’s average of all glucose readings from the winning source, in milligrams per decilitre.
| Field | blood_glucose |
|---|---|
| Unit | mg/dL |
| Reported | Daily average, on days with at least one reading |
| Window | Midnight to midnight, profile local time |
| Wearable required | Yes, a meter or a monitor writing to the platform |
| API | GET /api/v1/profile/biomarker/{externalId}?categories=vitals&types=blood_glucose plus a date range |
| Webhook | BiomarkerCreatedIntegrationEvent. Entries update in place, upsert on id. |
Data sources
| Platform | Record | Notes |
|---|---|---|
| iOS, HealthKit | bloodGlucose | CGM companion apps such as Dexcom, glucometer apps, and manual entries in the Health app |
| Android, Health Connect | BloodGlucoseRecord | Same kinds of apps, Samsung Health, and manual entries |
| Direct integrations | Provider-dependent | |
| Phone only | Manual entries only |
Readings carry a recording method, automatic or manual. An account that wants to exclude manually typed readings can ask Sahha to filter them.
How Sahha calculates blood_glucose
- Pick one source for the day within the blood category, which also covers blood pressure. One source wins per day; readings from different apps are never blended.
- Average that source’s readings with an end time inside the local day.
Absence means no reading that day.
Interpreting the value
Two very different users produce this field. A fingerprick user contributes one to four readings a day, so the average is a rough fasting or post-meal figure. A CGM user contributes a reading every few minutes, so the average is a smoothed daily mean that hides everything interesting about the curve.
The daily mean is a long-term signal. Averaged over weeks it tracks overall glycaemic control, which is the basis of the glucose management indicator used with continuous monitors [1]. As a daily number it says little.
Everything glucose-specific needs the readings. Time in range, variability, and the response to a meal are calculated from the individual samples. Those are data logs, delivered by webhook, not this biomarker.
Related scores and insights
Blood glucose is not a score factor and has no trend or comparison insight.
Use cases
A weekly average with a reading count. Show the 7-day mean and how many readings it rests on. The count tells you, and the user, whether it is a CGM average or three fingerpricks.
GET /api/v1/profile/biomarker/{externalId}?categories=vitals&types=blood_glucose&startDateTime=2026-08-26&endDateTime=2026-09-02Meal response, from data logs. Pair glucose data logs with the energy_intake and carbohydrate nutrition biomarkers for a logged meal. See energy intake for how the nutrition side is sourced.
Limitations
- Sparse for most users, dense for a few. Design for both.
- Manual entries are included by default unless filtered.
- Clinical context is required for any glucose feature. The biomarker is a wellness summary.
- Absence is not zero.
Related guides
- Blood pressure for the other logged vital
- Biomarkers vs data logs for per-reading access
- Data dictionary in the developer docs
References
- Bergenstal RM, Beck RW, Close KL, et al. Glucose management indicator (GMI): a new term for estimating A1C from continuous glucose monitoring. Diabetes Care. 2018;41(11):2275-2280. https://doi.org/10.2337/dc18-1581