# United Kingdom LFS: Employment: Cat R ISIC Rev. 4: : Women: Aged 15 and over: Thousands: NSA ()

United Kingdom LFS: Employment: Cat R ISIC Rev. 4: : Women: Aged 15 and over: Thousands: NSA () was up 8.7% year on year in Q2 2026, compared with 15.9% in Q1 2026.
The level stood at 461.0 thousands.
That is the lowest reading since Q2 2025.
Over the past ten years it has ranged from −12.9% (Q2 2017) to 17.4% (Q4 2025), averaging 1.8%.

- Source agency: UK Office for National Statistics
- Makrognosis code: `UK.EMP.Q.NSA.MEASURE-LEVEL.NACE-C-R.SEX-F`
- Frequency: quarterly
- Units: thousands
- Coverage: 2001-01-01 to 2026-04-01 (102 observations)
- Page: https://makrognosis.robomacro.com/data/united-kingdom/lfs-employment-cat-r-isic-rev-4-women-aged-15-and-over-thousands-nsa

## Recent data

| Period | Value | Y/Y % |
|---|---:|---:|
| Q2 2026 | 461.0 thousands | 8.7 |
| Q1 2026 | 475.0 thousands | 15.9 |
| Q4 2025 | 431.0 thousands | 17.4 |
| Q3 2025 | 453.0 thousands | 11.6 |
| Q2 2025 | 424.0 thousands | 6.8 |
| Q1 2025 | 410.0 thousands | −1.2 |
| Q4 2024 | 367.0 thousands | −6.9 |
| Q3 2024 | 406.0 thousands | 3.3 |
| Q2 2024 | 397.0 thousands | −0.3 |
| Q1 2024 | 415.0 thousands | 4.8 |
| Q4 2023 | 394.0 thousands | −3.2 |
| Q3 2023 | 393.0 thousands | −4.4 |
| Q2 2023 | 398.0 thousands | −5.2 |
| Q1 2023 | 396.0 thousands | −10.4 |
| Q4 2022 | 407.0 thousands | −8.9 |
| Q3 2022 | 411.0 thousands | −1.9 |
| Q2 2022 | 420.0 thousands | −2.8 |
| Q1 2022 | 442.0 thousands | 12.2 |
| Q4 2021 | 447.0 thousands | 11.2 |
| Q3 2021 | 419.0 thousands | 9.1 |
| Q2 2021 | 432.0 thousands | 6.1 |
| Q1 2021 | 394.0 thousands | −5.1 |
| Q4 2020 | 402.0 thousands | −3.1 |
| Q3 2020 | 384.0 thousands | −3.3 |

## API

```
curl -H "X-API-Key: $MAKROGNOSIS_KEY" \
  "https://makrognosis.robomacro.com/v1/series/UK.EMP.Q.NSA.MEASURE-LEVEL.NACE-C-R.SEX-F"

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