Official Belgian data, explained
Share: Women by municipality in Belgium (2026)
This page maps Share: Women for one nationally comparable 2026 slice. Every figure below uses the same disclosed definition, unit, geography and source.
Population
What this indicator measures
Residents in Statbel's F sex category.
Official Statbel measure for Women.
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
- 50.6%
- Unweighted area mean
- 50.6%
- Minimum
- 47.2%
- Maximum
- 53.8%
Across the valid national comparison set, the median is 50.6 %. Values extend from 47.2 to 53.8 %. This describes geographic variation; it is not a score of local quality.
Geography
Map of Belgium

- 39.7–50112 areas
- 50–50.4112 areas
- 50.4–50.8126 areas
- 50.8–51.3109 areas
- 51.3–54.7106 areas
Areas
Value distribution
| Value | Areas |
|---|---|
| 47.2–47.4 | 1 |
| 47.4–47.7 | 2 |
| 47.7–48 | 1 |
| 48–48.3 | 1 |
| 48.3–48.5 | 4 |
| 48.5–48.8 | 4 |
| 48.8–49.1 | 4 |
| 49.1–49.4 | 19 |
| 49.4–49.6 | 21 |
| 49.6–49.9 | 39 |
| 49.9–50.2 | 65 |
| 50.2–50.5 | 83 |
| 50.5–50.7 | 93 |
| 50.7–51 | 70 |
| 51–51.3 | 52 |
| 51.3–51.6 | 53 |
| 51.6–51.8 | 19 |
| 51.8–52.1 | 16 |
| 52.1–52.4 | 8 |
| 52.4–52.7 | 4 |
| 52.7–53 | 2 |
| 53–53.2 | 1 |
| 53.2–53.5 | 2 |
| 53.5–53.8 | 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 | Watermael-Boitsfort | 21017 | 53.8 % |
|---|---|---|---|---|
| Highest | 2 | Uccle | 21016 | 53.5 % |
| Highest | 3 | Woluwe-Saint-Lambert | 21018 | 53.4 % |
| Highest | 4 | Woluwe-Saint-Pierre | 21019 | 53.1 % |
| Highest | 5 | Fléron | 62038 | 52.9 % |
| Highest | 6 | Montigny-le-Tilleul | 52048 | 52.9 % |
| Highest | 7 | Waterloo | 25110 | 52.7 % |
| Highest | 8 | Waremme | 64074 | 52.6 % |
| Highest | 9 | Drogenbos | 23098 | 52.6 % |
| Highest | 10 | Nivelles | 25072 | 52.5 % |
| Lowest | 565 | Vresse-sur-Semois | 91143 | 47.2 % |
| Lowest | 564 | Herstappe | 73028 | 47.4 % |
| Lowest | 563 | Saint-Josse-ten-Noode | 21014 | 47.7 % |
| Lowest | 562 | Herbeumont | 84029 | 48 % |
| Lowest | 561 | Hastière | 91142 | 48 % |
| Lowest | 560 | Houffalize | 82014 | 48.3 % |
| Lowest | 559 | Bullange | 63012 | 48.4 % |
| Lowest | 558 | Faimes | 64076 | 48.5 % |
| Lowest | 557 | Vleteren | 33041 | 48.5 % |
| Lowest | 556 | Baarle-Hertog | 13002 | 48.6 % |
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
