---
updatedAt: 2025-11-07T19:51:17.000Z
agentTools:
  projectIndex: https://developer.validic.com/llms.txt
---

# Segments

Certain records may consist of multiple activities that make up the entire record. In these cases, the segments object is used to present the different sub-records within the larger record. For instance, a nutrition record can also consist of multiple segments that make up the entire nutrition meal. The Segments object is used to record a specific part as part of a nutrition record. The segment object not only stores high-level information about the entire nutrition record, but it also acts as a container for the detailed items/measurements for the nutrition record.

> 📘 Note: Parsing Segment Data
>
> Segment data is available when a source provides a more granular breakdown of\
> metrics. The handling of segment data is driven by the customer use case. Segments are provided as an array accessed by the 'segments' field. Simply checking the length of that\
> field's value will provide insight into whether segment data is available for processing.

```json Sample Segment Record
{
  "data": [
    {
      "id": "3d5961cd5ba41b344a7fdbb29f44fe16",
      "name": "Unknown",
      "type": "nutrition",
      "user": {
        "uid": "demotestuser1",
        "user_id": "58dbc86SAMPLE001e6b7c7",
        "organization_id": "58cb5SAMPLEda50001f75db3"
      },
      "log_id": "2017-03-29",
      "source": {
        "type": "fitbit"
      },
      "metrics": [
        {
          "type": "energy_consumed",
          "unit": "kcal",
          "value": 319,
          "origin": "unknown"
        },
        {
          "type": "dietary_fiber",
          "unit": "g",
          "value": 6,
          "origin": "unknown"
        },
        {
          "type": "water",
          "unit": "mL",
          "value": 0,
          "origin": "unknown"
        },
        {
          "type": "carbohydrate",
          "unit": "g",
          "value": 50,
          "origin": "unknown"
        },
        {
          "type": "fat",
          "unit": "g",
          "value": 8,
          "origin": "unknown"
        },
        {
          "type": "protein",
          "unit": "g",
          "value": 16,
          "origin": "unknown"
        },
        {
          "type": "sodium",
          "unit": "mg",
          "value": 437000,
          "origin": "unknown"
        }
      ],
      "version": "1.0",
      "category": "other",
      "checksum": "328c016c3a3ac6a3428dcd627bf008f8",
      "end_time": "2017-03-30T03:59:59Z",
      "segments": [
        {
          "name": "Breakfast Summary",
          "metrics": [
            {
              "type": "energy_consumed",
              "unit": "kcal",
              "value": 319,
              "origin": "unknown"
            },
            {
              "type": "dietary_fiber",
              "unit": "g",
              "value": 6,
              "origin": "unknown"
            },
            {
              "type": "carbohydrate",
              "unit": "g",
              "value": 50,
              "origin": "unknown"
            },
            {
              "type": "fat",
              "unit": "g",
              "value": 8,
              "origin": "unknown"
            },
            {
              "type": "protein",
              "unit": "g",
              "value": 16,
              "origin": "unknown"
            },
            {
              "type": "sodium",
              "unit": "mg",
              "value": 437000,
              "origin": "unknown"
            }
          ]
        }
      ],
      "created_at": "2017-03-29T14:54:00.490Z",
      "start_time": "2017-03-29T04:00:00Z",
      "utc_offset": -14400,
      "offset_origin": "profile"
    }
  ]
}
```