Planning services for older residents with the over-60 share

To plan services for older residents, find the neighbourhoods with the most people over 60 and, within them, the most over 80, then check how far those people are from the services they rely on. The over-60 count shows the size of the need; the over-80 count shows where it is most intense; the distance to the nearest pharmacy, clinic or community centre shows where it is least met.

This article is for home care agencies, pharmacy and clinic networks, senior living developers, councils and charities working with older people. It explains which figures to use, why the oldest band deserves its own attention, a worked example, and how an AI employee can keep a list of priority areas current.

The figures that matter

The Demographics block gives four views of older residents for any area:

• seniors_60_plus: everyone aged 60 and over.
• seniors_pct: their share of all residents.
• age_60_69, age_70_79, age_80_plus: the three oldest ten-year bands, so you can tell a neighbourhood of recently retired people from one where many are very old.
• people_per_km2: density, which affects how many older people one walking route, one care worker's round or one pharmacy can reach.

For most services the 60-plus count is too broad on its own. Many people in their sixties work, drive and need little support. Home care, falls prevention, meal delivery and memory services follow the 80-plus band much more closely. Pharmacies and general practice sit in between: their repeat prescriptions grow with every band from 60 upwards.

Distance matters more with age

A 15-minute walk for a fit adult can be a much longer and harder trip for someone with a walking frame. When you measure access for older residents, use shorter walking areas than you would for the population as a whole, and check barriers: busy roads, hills, missing crossings. A Travel area on foot follows the real paths, which a circle does not. For services people are driven to, a short drive is the fairer measure.

A worked example in Melbourne

A made-up example. A home care agency in Melbourne serves four suburbs and wants to decide where to base a second team. It counts residents in each suburb and looks at the oldest band. The numbers are invented to show the reading.

Invented figures for illustration; not real figures for Melbourne.

Suburb D has the highest share of over-60s, which makes it look like the obvious choice. But Suburb B has far more people over 80, packed more tightly, so a care worker there can make more visits in a day with less driving. The second team goes to Suburb B; Suburb D, older but spread out, may suit a different service such as a weekly community bus.

What the market already provides

Older residents use pharmacies more than anyone, so the pharmacy map is worth a look. xMap's places database lists 866 pharmacies within 10 km of the centre of London (November 2026). Of the 438 nearest the centre, 91 belong to chains such as Boots and Superdrug, and those with a rating average 3.9. That shows the supply. It cannot be set against residents there, though: population figures are not available for the United Kingdom, so for London the measure stops at the count of providers.

866Pharmacies listed

91Chains

347Independent

3.9Average rating

In cities with population figures, such as Toronto, Lyon, Bangkok or Sydney, both halves can be put together: older residents in each district next to the pharmacies, clinics or day centres they can reach. A district with many people over 80 and no pharmacy within a short walk is a clear case for a delivery service, a weekly visit or a new branch, depending on who is asking.

Mistakes to avoid

• Using the share without the count. A small, very old village may hold fewer older people than a large district with a lower share.
• Treating 60 as old. Plan support services on the 70-plus and 80-plus bands.
• Missing the odd peak. A single hexagon with far more older people than its neighbours may be a care home or a retirement complex, which needs a different service from homes on an ordinary street; check unusual peaks on the map.
• Planning on figures alone. The data says where older people live, not who lives alone, who has family nearby or who is unwell. Local knowledge fills that in.
• Forgetting coverage. About 100 countries have figures, among them Canada, Australia, France, Thailand, India and Egypt; not the United Kingdom or the United States.

An AI employee for priority areas

1. A Schedule, every quarter.
2. An Area of interest with the districts you serve.
3. Demographics with Totals for each area, giving age_80_plus and seniors_pct for each.
4. Nearby places counting pharmacies, clinics or community centres in each district, with the distance to the nearest.
5. A Calculated field for over-80s for each service, then Sort and limit.
6. An Email with the top districts and a map.

Ready-made versions: Where seniors need home care most, Older people far from a community centre, Where to build senior living, On-demand minibus zones for older residents and Cooling centres near the most seniors, for heat waves.