What the macronutrient biomarkers measure
Daily logged totals of the energy-bearing nutrients and their components.
| Biomarker | What it is | Unit |
|---|---|---|
protein_intake | Protein consumed | Grams |
carbohydrate_intake | Total carbohydrate, including sugar and fiber | Grams |
sugar_intake | Sugars, a component of carbohydrate | Grams |
fiber_intake | Dietary fiber, a component of carbohydrate | Grams |
fat_intake | Total fat | Grams |
fat_saturated_intake | Saturated fat, a component of fat | Grams |
fat_monounsaturated_intake | Monounsaturated fat, a component of fat | Grams |
fat_polyunsaturated_intake | Polyunsaturated fat, a component of fat | Grams |
fat_trans_intake | Trans fat, a component of fat. Android only. | Grams |
cholesterol_intake | Dietary cholesterol | Milligrams |
All are reported daily, over a midnight-to-midnight window in the profile’s local time zone, on days with at least one log. None requires a wearable.
| Access | |
|---|---|
| API | GET /api/v1/profile/biomarker/{externalId}?categories=nutrition plus one types parameter per field and a date range |
| Webhook | BiomarkerCreatedIntegrationEvent. Entries update in place, upsert on id. |
Data sources
| Platform | Record | Notes |
|---|---|---|
| iOS, HealthKit | dietaryProtein, dietaryCarbohydrates, dietarySugar, dietaryFiber, dietaryFatTotal, dietaryFatSaturated, dietaryFatMonounsaturated, dietaryFatPolyunsaturated, dietaryCholesterol | Written by food loggers such as MyFitnessPal, Cronometer, Lose It, Yazio, and MacroFactor. No trans fat type. |
| Android, Health Connect | NutritionRecord fields, including trans fat | Same apps, plus Samsung Health |
| Direct integrations | None | |
| Phone only | Manual entry, or entries your own app writes |
Which fields a food logger writes varies. Most write protein, carbohydrate, and fat. Fewer write the fat sub-types and cholesterol.
How Sahha calculates macronutrients
- Pick one source for the day, per nutrient. For each field, the source with the highest daily total wins. Ten fields can in principle have ten different winners.
- Sum the winning source’s entries with an end time inside the local day.
Absence for a field means no source logged it that day, which for the sub-types is common even among users who log.
Interpreting the values
Protein is the macro users act on. Grams per kilogram of body weight, using the latest weight, is the number strength and weight-management features present.
The components are subsets. Sugar and fiber sit inside carbohydrate; the four fat sub-types sit inside total fat. Do not stack them next to the totals as if they were additional.
Sub-type coverage is thin. Saturated fat is logged by most apps; the other three fats and cholesterol far less. Design the sub-type view to cope with blanks.
Related scores and insights
None of the ten is a score factor or has a trend or comparison insight. The nutrition recommendations by archetype guide shows how to drive nutrition features from archetypes for users who do not log.
Use cases
A macro split. Protein, carbohydrate, and fat as a three-segment bar, with energy intake as the label. Show the logged-days count for the period.
GET /api/v1/profile/biomarker/{externalId}?categories=nutrition&types=protein_intake&types=carbohydrate_intake&types=fat_intake&startDateTime=2026-08-27&endDateTime=2026-09-03A protein target. Latest weight × a target in grams per kilogram, compared with the logged protein total, for users who log on most days.
A fiber nudge. Fiber is the macro most people under-consume and the one with the clearest guideline [1]. Show it against the guideline only on days with a logged energy total above a floor, to avoid flagging half-logged days.
Limitations
- Logged only.
- Per-nutrient winners can make a day’s macros and energy come from different apps.
- Trans fat is Android only.
- Absence is not zero for any field.
Related guides
- Energy intake for the total these nutrients make up and how source selection works
- Vitamins and minerals for the micronutrient fields
- Weight, height, and BMI for the weight used in per-kilogram targets
- Data dictionary in the developer docs
References
- Quagliani D, Felt-Gunderson P. Closing America’s fiber intake gap: communication strategies from a food and fiber summit. American Journal of Lifestyle Medicine. 2017;11(1):80-85. https://doi.org/10.1177/1559827615588079