# United States All employees, thousands, special food services, seasonally adjusted

United States All employees, thousands, special food services, seasonally adjusted was down 6.7% year on year in September 2026, compared with −8.2% in August 2026.
The level stood at 727.9 thousands.
Over the past ten years it has ranged from −49.8% (Apr 2020) to 41.6% (Dec 2021), averaging 3.1%.

- Source agency: U.S. Bureau of Labor Statistics (flat files)
- Makrognosis code: `US.EMP.M.SA.IND-70722300`
- Frequency: monthly
- Units: thousands
- Coverage: 1990-01-01 to 2026-09-01 (441 observations)
- Page: https://makrognosis.robomacro.com/data/united-states/all-employees-thousands-special-food-services-seasonally-adjusted

## Recent data

| Period | Value | Y/Y % |
|---|---:|---:|
| September 2026 | 727.9 thousands | −6.7 |
| August 2026 | 715.9 thousands | −8.2 |
| July 2026 | 720.9 thousands | −7.3 |
| June 2026 | 737.6 thousands | −5.3 |
| May 2026 | 747.8 thousands | −5.3 |
| April 2026 | 759.6 thousands | −4.4 |
| March 2026 | 759.0 thousands | −4.6 |
| February 2026 | 765.0 thousands | −4.1 |
| January 2026 | 762.5 thousands | −4.5 |
| December 2025 | 775.9 thousands | −2.6 |
| November 2025 | 773.3 thousands | −2.8 |
| October 2025 | 777.0 thousands | −2.2 |
| September 2025 | 780.2 thousands | −1.3 |
| August 2025 | 780.0 thousands | −0.9 |
| July 2025 | 778.0 thousands | 0.7 |
| June 2025 | 778.6 thousands | 1.1 |
| May 2025 | 789.7 thousands | 1.6 |
| April 2025 | 794.3 thousands | 2.5 |
| March 2025 | 795.6 thousands | 2.6 |
| February 2025 | 797.9 thousands | 3.1 |
| January 2025 | 798.8 thousands | 3.3 |
| December 2024 | 797.0 thousands | 3.1 |
| November 2024 | 795.7 thousands | 3.2 |
| October 2024 | 794.8 thousands | 3.1 |

## API

```
curl -H "X-API-Key: $MAKROGNOSIS_KEY" \
  "https://makrognosis.robomacro.com/v1/series/US.EMP.M.SA.IND-70722300"

# Python
import requests
r = requests.get("https://makrognosis.robomacro.com/v1/series/US.EMP.M.SA.IND-70722300",
                 headers={"X-API-Key": KEY})
obs = r.json()["observations"]
```