Electoral wardE05015582
Cowplain ward, Havant
Cowplain is one of 12 electoral wards of Havant Borough Council, in Hampshire (South East). At the 2021 Census it had 9,203 residents in 3,983 households — 3,220 people per km², the 10th largest of the council's wards by population. It lies in the Fareham and Waterlooville constituency; for county elections it is in the Cowplain & Hart Plain and Waterloo & Stakes North divisions.
Residents, 20219,203council ward average 10,350
Households3,9832.31 residents per household
Density3,220/ km²about 2.86 km² · Havant 2,228
Aged 65+26.2%Havant: 24.3% · under 16: 16.1%
Census 2021
Age of residents
0–44.4% · 409
5–95.5% · 510
10–156.1% · 561
16–193.3% · 302
20–244.6% · 426
25–3411.6% · 1,063
35–4916.6% · 1,525
50–6421.7% · 2,000
65–7413.5% · 1,238
75–848.8% · 812
85+3.9% · 357
Car or van availability
Share of households.
No car or van11.6% · 464
1 car or van37.4% · 1,489
2 cars or vans35.2% · 1,403
3 or more15.8% · 628
Census 2021
Housing tenure
Share of households; Havant overall: 67.9% owned, 18.6% social rented, 12.4% private rented.
Owned outright46.2% · 1,841
With mortgage35.8% · 1,426
Shared ownership0.3% · 10
Social rented5.5% · 219
Private rented12.3% · 490
Type of home
Detached house40.1% · 1,597
Semi-detached house33.4% · 1,328
Terraced house17.7% · 705
Purpose-built flat8.0% · 317
Converted house0.2% · 8
Other conversion0.0% · 1
Above shop / office0.6% · 23
Electoral geography
Ward facts
- Ward code (GSS)
E05015582- Council
- Havant Borough Council
- County council
- Hampshire County Council
- County division
- Cowplain & Hart Plain, Waterloo & Stakes North
- Constituency
- Fareham and Waterlooville
- Region
- South East
- Density rank in council
- 4 of 12
Other wards in the same constituency
Census 2021: Office for National Statistics via Nomis (TS001, TS006, TS007B, TS041, TS044, TS045, TS054) · ward lookups: ONS Open Geography Portal · Open Government Licence v3.0This ward was drawn after the 2021 Census: figures are built up from the 6 census areas (LSOAs) that ONS best-fits to it, so they are close estimates.