# United Kingdom "LFS: In Employment: Agriculture, forestry & fishing: : People: Aged 16 and over: Thousands: NSA" ()

United Kingdom "LFS: In Employment: Agriculture, forestry & fishing: : People: Aged 16 and over: Thousands: NSA" () was up 5.9% year on year in Q2 2026, compared with 4.4% in Q1 2026.
The level stood at 288.0 thousands.
Over the past ten years it has ranged from −16.7% (Q4 2021) to 35.5% (Q3 2023), averaging −1.2%.

- Source agency: UK Office for National Statistics
- Makrognosis code: `UK.EMP.Q.NSA.ITEM-I4EF.MEASURE-LEVEL`
- Frequency: quarterly
- Units: thousands
- Coverage: 1997-01-01 to 2026-04-01 (118 observations)
- Page: https://makrognosis.robomacro.com/data/united-kingdom/lfs-in-employment-agriculture-forestry-and-fishing-people-aged-16-and

## Recent data

| Period | Value | Y/Y % |
|---|---:|---:|
| Q2 2026 | 288.0 thousands | 5.9 |
| Q1 2026 | 287.0 thousands | 4.4 |
| Q4 2025 | 303.0 thousands | 5.9 |
| Q3 2025 | 310.0 thousands | 5.8 |
| Q2 2025 | 272.0 thousands | −3.2 |
| Q1 2025 | 275.0 thousands | −10.7 |
| Q4 2024 | 286.0 thousands | −11.5 |
| Q3 2024 | 293.0 thousands | −11.7 |
| Q2 2024 | 281.0 thousands | 3.7 |
| Q1 2024 | 308.0 thousands | 16.7 |
| Q4 2023 | 323.0 thousands | 30.8 |
| Q3 2023 | 332.0 thousands | 35.5 |
| Q2 2023 | 271.0 thousands | 7.5 |
| Q1 2023 | 264.0 thousands | 7.3 |
| Q4 2022 | 247.0 thousands | −6.4 |
| Q3 2022 | 245.0 thousands | −14.9 |
| Q2 2022 | 252.0 thousands | −11.9 |
| Q1 2022 | 246.0 thousands | −14.3 |
| Q4 2021 | 264.0 thousands | −16.7 |
| Q3 2021 | 288.0 thousands | −8.3 |
| Q2 2021 | 286.0 thousands | −2.7 |
| Q1 2021 | 287.0 thousands | −11.1 |
| Q4 2020 | 317.0 thousands | −6.2 |
| Q3 2020 | 314.0 thousands | −10.0 |

## API

```
curl -H "X-API-Key: $MAKROGNOSIS_KEY" \
  "https://makrognosis.robomacro.com/v1/series/UK.EMP.Q.NSA.ITEM-I4EF.MEASURE-LEVEL"

# Python
import requests
r = requests.get("https://makrognosis.robomacro.com/v1/series/UK.EMP.Q.NSA.ITEM-I4EF.MEASURE-LEVEL",
                 headers={"X-API-Key": KEY})
obs = r.json()["observations"]
```