# United Kingdom LFS: In Employment: Human health & social work activities: : Women: Aged 16 and over: Thousands: NSA ()

United Kingdom LFS: In Employment: Human health & social work activities: : Women: Aged 16 and over: Thousands: NSA () was up 1.7% year on year in Q2 2026, compared with 1.2% in Q1 2026.
The level stood at 3,732.0 thousands.
That is the highest reading since Q4 2024.
Over the past ten years it has ranged from −5.2% (Q1 2023) to 9.7% (Q1 2024), averaging 1.4%.

- Source agency: UK Office for National Statistics
- Makrognosis code: `UK.EMP.Q.NSA.ITEM-I4FI.MEASURE-LEVEL.SEX-F`
- 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-human-health-and-social-work-activities-women-aged-16

## Recent data

| Period | Value | Y/Y % |
|---|---:|---:|
| Q2 2026 | 3,732.0 thousands | 1.7 |
| Q1 2026 | 3,736.0 thousands | 1.2 |
| Q4 2025 | 3,702.0 thousands | 0.1 |
| Q3 2025 | 3,710.0 thousands | −4.2 |
| Q2 2025 | 3,671.0 thousands | −3.8 |
| Q1 2025 | 3,690.0 thousands | −0.4 |
| Q4 2024 | 3,697.0 thousands | 2.1 |
| Q3 2024 | 3,872.0 thousands | 8.1 |
| Q2 2024 | 3,815.0 thousands | 9.1 |
| Q1 2024 | 3,704.0 thousands | 9.7 |
| Q4 2023 | 3,622.0 thousands | 5.3 |
| Q3 2023 | 3,583.0 thousands | 1.1 |
| Q2 2023 | 3,498.0 thousands | −1.2 |
| Q1 2023 | 3,375.0 thousands | −5.2 |
| Q4 2022 | 3,441.0 thousands | −1.8 |
| Q3 2022 | 3,544.0 thousands | 0.5 |
| Q2 2022 | 3,542.0 thousands | 1.8 |
| Q1 2022 | 3,560.0 thousands | 3.2 |
| Q4 2021 | 3,504.0 thousands | 2.9 |
| Q3 2021 | 3,525.0 thousands | 0.9 |
| Q2 2021 | 3,481.0 thousands | −0.7 |
| Q1 2021 | 3,450.0 thousands | −2.1 |
| Q4 2020 | 3,404.0 thousands | −4.2 |
| Q3 2020 | 3,495.0 thousands | −0.03 |

## API

```
curl -H "X-API-Key: $MAKROGNOSIS_KEY" \
  "https://makrognosis.robomacro.com/v1/series/UK.EMP.Q.NSA.ITEM-I4FI.MEASURE-LEVEL.SEX-F"

# Python
import requests
r = requests.get("https://makrognosis.robomacro.com/v1/series/UK.EMP.Q.NSA.ITEM-I4FI.MEASURE-LEVEL.SEX-F",
                 headers={"X-API-Key": KEY})
obs = r.json()["observations"]
```