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

United Kingdom LFS: Employment: Cat S ISIC Rev. 4: : Men: Aged 15 and over: Thousands: NSA () was down 7.5% year on year in Q2 2026, compared with −5.5% in Q1 2026.
The level stood at 369.0 thousands.
That is the lowest reading since Q2 2020.
Over the past ten years it has ranged from −12.3% (Q2 2018) to 16.4% (Q1 2025), averaging 1.1%.

- Source agency: UK Office for National Statistics
- Makrognosis code: `UK.EMP.Q.NSA.MEASURE-LEVEL.NACE-C-S.SEX-M`
- 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-s-isic-rev-4-men-aged-15-and-over-thousands-nsa

## Recent data

| Period | Value | Y/Y % |
|---|---:|---:|
| Q2 2026 | 369.0 thousands | −7.5 |
| Q1 2026 | 363.0 thousands | −5.5 |
| Q4 2025 | 355.0 thousands | −4.1 |
| Q3 2025 | 379.0 thousands | 2.2 |
| Q2 2025 | 399.0 thousands | 12.7 |
| Q1 2025 | 384.0 thousands | 16.4 |
| Q4 2024 | 370.0 thousands | 5.4 |
| Q3 2024 | 371.0 thousands | 7.2 |
| Q2 2024 | 354.0 thousands | 4.7 |
| Q1 2024 | 330.0 thousands | −6.2 |
| Q4 2023 | 351.0 thousands | 0.0 |
| Q3 2023 | 346.0 thousands | 3.9 |
| Q2 2023 | 338.0 thousands | −5.3 |
| Q1 2023 | 352.0 thousands | −5.6 |
| Q4 2022 | 351.0 thousands | −1.4 |
| Q3 2022 | 333.0 thousands | 0.3 |
| Q2 2022 | 357.0 thousands | 4.7 |
| Q1 2022 | 373.0 thousands | 9.4 |
| Q4 2021 | 356.0 thousands | −0.3 |
| Q3 2021 | 332.0 thousands | −1.5 |
| Q2 2021 | 341.0 thousands | 3.0 |
| Q1 2021 | 341.0 thousands | −3.9 |
| Q4 2020 | 357.0 thousands | −5.3 |
| Q3 2020 | 337.0 thousands | −4.8 |

## API

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

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