Official Belgian data, explained
Share: Non-Belgian nationality by municipality in Belgium (2026)
This page maps Share: Non-Belgian nationality for one nationally comparable 2026 slice. Every figure below uses the same disclosed definition, unit, geography and source.
Population
What this indicator measures
Residents recorded in Statbel's ETR nationality category.
Official Statbel measure for Non-Belgian nationality.
Share. Matching-category residents divided by total residents in the same area and reference date × 100.
Indicator dossier
Data passport
- Selected reference period
- 2026
- Geography
- municipalities
- Boundary set
- Statistical sectors 2026
- Measure
- Share
- Unit
- %
- Comparable areas
- 565
- Coverage
- 100%
Latest published slice
How to read the pattern
- Median
- 6.4%
- Unweighted area mean
- 9.1%
- Minimum
- 1.1%
- Maximum
- 55.1%
Across the valid national comparison set, the median is 6.4 %. Values extend from 1.1 to 55.1 %. This describes geographic variation; it is not a score of local quality.
Geography
Map of Belgium
- 0.6–2.922 areas
- 2.9–4.195 areas
- 4.1–5.9137 areas
- 5.9–10.2169 areas
- 10.2–55.6142 areas
Areas
Value distribution
| Value | Areas |
|---|---|
| 1.1–3.4 | 55 |
| 3.4–5.6 | 185 |
| 5.6–7.9 | 114 |
| 7.9–10.1 | 69 |
| 10.1–12.4 | 36 |
| 12.4–14.6 | 25 |
| 14.6–16.9 | 21 |
| 16.9–19.1 | 10 |
| 19.1–21.4 | 7 |
| 21.4–23.6 | 9 |
| 23.6–25.9 | 5 |
| 25.9–28.1 | 2 |
| 28.1–30.4 | 2 |
| 30.4–32.6 | 5 |
| 32.6–34.9 | 5 |
| 34.9–37.1 | 3 |
| 37.1–39.4 | 5 |
| 39.4–41.6 | 1 |
| 41.6–43.9 | 0 |
| 43.9–46.1 | 1 |
| 46.1–48.4 | 0 |
| 48.4–50.6 | 4 |
| 50.6–52.9 | 0 |
| 52.9–55.1 | 1 |
Explore this exact slice in the atlas Download this data as CSV
municipalities
Highest and lowest values
From 565 comparable areas, the table shows a concise descriptive high-and-low sample. Equal values do not imply equal local circumstances.
| Highest | 1 | Baarle-Hertog | 13002 | 55.1 % |
|---|---|---|---|---|
| Highest | 2 | Ixelles | 21009 | 50.5 % |
| Highest | 3 | Saint-Gilles | 21013 | 49.4 % |
| Highest | 4 | Etterbeek | 21005 | 49.4 % |
| Highest | 5 | Raeren | 63061 | 48.6 % |
| Highest | 6 | Saint-Josse-ten-Noode | 21014 | 45 % |
| Highest | 7 | Woluwe-Saint-Lambert | 21018 | 39.4 % |
| Highest | 8 | Bruxelles | 21004 | 38.7 % |
| Highest | 9 | La Calamine | 63040 | 38.5 % |
| Highest | 10 | Schaerbeek | 21015 | 37.9 % |
| Lowest | 565 | Horebeke | 45062 | 1.1 % |
| Lowest | 564 | Koekelare | 32010 | 1.7 % |
| Lowest | 563 | Ohey | 92097 | 2 % |
| Lowest | 562 | Burdinne | 61010 | 2.1 % |
| Lowest | 561 | Maarkedal | 45064 | 2.2 % |
| Lowest | 560 | Wortegem-Petegem | 45061 | 2.3 % |
| Lowest | 559 | Zwalm | 45065 | 2.3 % |
| Lowest | 558 | Wellin | 84075 | 2.3 % |
| Lowest | 557 | Ferrières | 61019 | 2.5 % |
| Lowest | 556 | Gesves | 92054 | 2.5 % |
Method and limitations
Method and limitations
No missing value is imputed. Where colour classes are used, their breaks and colours come from the catalogue; source-declared suppression remains missing.
The area mean gives every published geographic area equal weight. It is not weighted by population, exposure or area size.
Reference population on 1 January.
Read the methodologySources, licence and provenance