Research and analysis

Childcare accessibility by neighbourhood, England: Ofsted’s methodology

Published 4 June 2024

Applies to England

Spatial accessibility of childcare

Spatial accessibility refers to the ease with which people can reach services near to where they live. For example, if a park is close to your house and you can get there easily, it has high spatial accessibility for you.

A measure of spatial accessibility captures both the capacity of childcare relative to population size and how close providers are to users of childcare. One measure of this is a supply-to-demand ratio to show the number of childcare places per resident child within a ward or local authority. This measure provides a good starting point and the sector has widely used this to assess the availability of childcare. However, this method has several drawbacks.

Limitations of existing methods

A supply-to-demand ratio only considers parents and providers that are within a defined administrative boundary, such as a local authority or ward. It does not account for parents who may travel across a boundary to access a childcare provider. For example, if a parent lives on the boundary of a local authority or ward, they may be likely to access childcare in a neighbouring one.

As the areas we are looking at become more detailed and precise (‘granular’ data), supply-to-demand ratios are likely to get less relevant. This is because it becomes more likely that a parent will travel across a boundary to access childcare. In smaller areas, such as lower super output areas, it is also more likely there may not be any childcare provision, which means that a supply-to-demand ratio cannot work at all.

We also know that parents are more likely to use facilities that are close to them, so travel time is an important factor in accessing facilities. This is not accounted for using a simple supply-to-demand ratio method.

There is also considerable variation in access to childcare across the country, and within administrative boundaries. Producing an average supply-to-demand ratio does not allow us to see the areas that have very high or very low access to childcare within a local authority.

Multi-modal 2-step floating catchment method

To address some of these limitations, we used a multi-modal 2-step floating catchment method (MM-2SFCA), which has previously been used to analyse healthcare accessibility.^{[footnote 1]} We have applied this method to analyse childcare accessibility. The method is a special form of the standard provider-to-population ratio and considers supply, potential demand and travel time. The method relies on the assumptions that parents are more likely to use childcare that is closer to them, and that there is generally a limit on how far parents will travel to reach a desired childcare provider. Multi-modal estimates include travel by car, by public transport and on foot to better reflect how parents are likely to access childcare providers near to their home.

The idea of a ‘floating catchment’ means that we do not rely on administrative boundaries, which can be arbitrary. The output of this method is the same as a traditional supply-to-demand ratio, and therefore can be easily interpreted, but includes several improvements.

A key benefit of this method is the ability to look at a hyperlocal level – that is, focusing on a very small area in a community. We have produced this analysis at Census output area (OA) level. OAs contain 40 to 250 households, with an average of 28 children aged 7 and under per OA. We have aggregated results and presented them at LSOA level in this publication.

As discussed earlier, there is hyperlocal variation in access to childcare across the country. This method enables us to determine where the childcare ‘hotspots’ and ‘coldspots’ are located.

Applied to childcare in England, the method involves 2 steps:

Step 1

a. We define a catchment for each childcare provider using travel time data. This is an area in which parents can reach the provider within a 15-minute drive or 25 minutes by public transport, including a 15-minute walk.

b. Using these catchments, we can estimate the number of children that can easily reach this childcare provider. For each provider, we calculate a ratio of childcare places to local children.

Step 2

c. We define a catchment around every output area in England using travel time data. Output areas account for between 40 and 250 households. This catchment includes locations reachable by parents living in that output area within a 15-minute drive or 25 minutes by public transport, including a 15-minute walk.

d. For every output area in England, we calculate which childcare providers fall within its catchment and add together the childcare ratios for these provides from step 1. This gives a score of childcare accessibility for every output area in England: how many childcare places are accessible from that output area per local child.

In the analysis, we have used travel time catchments of 15 minutes for car and 25 minutes for public transport. This includes a maximum walking time of 15 minutes for users of public transport.

We chose 15 minutes and 25 minutes based on a reasonable estimate for the maximum time that parents may travel to access childcare, but these times could be adjusted in future with additional evidence to show how long parents are willing to travel. We used the longer travel time for public transport as it is likely that users of public transport are willing to travel for longer to reach a similar distance. The distribution of scores is also more appropriate with varying travel times because access using different modes of transport is more closely aligned.

Within each catchment, each childcare provider is assumed to be reachable. However, as we know that parents are more likely to use childcare that is close to them, we applied a ‘distance decay function’ so that the places from providers that are closer to the centre point of an OA (a ‘centroid’) receive more weight than those further away.^{[footnote 2]} The ‘distance decay’ effect states that the interaction between 2 locales declines as the distance between them increases.

The distance decay function is a Gaussian function of the form ^{[footnote 3]}.

Where i is the demand node (OA population weighted centroid), j is the location of supply (childcare providers), d_ij is the travel time from demand node i to supply node j, and d_m is the size of the catchment area (varying size for public transport and driving).

As part of the multi-modal estimate, we split the population of children to estimate those that are expected to travel by car or by public transport. To do this, we calculated the average number of 0- to 7-year-old children per household in an OA from Census 2021. We then used this combined with estimates of car ownership within households per OA to calculate the population that are likely to travel to their childcare provider by car.

We used the following calculations to estimate the accessibility scores by transport mode:

In these calculations, A_{i, p} and A_{i, c} are the public transport accessibility scores and driving accessibility scores at demand node i, respectively; D_{k, p}  and D_{k, c}  are the public transport mode population and driving mode population at demand node k, respectively; d_{kj, p} and d_{kj, c} are the public transport and car travel times from demand node k to facility j, respectively; f is the distance decay function, and S_j is the number of places offered at supply node (provider) j .

To produce an estimate of the overall accessibility score within an OA, A_i, we took a weighted average of the driving and public transport scores for each OA using estimates of car ownership from Census 2021.

To generate estimates at LSOA, middle super output area, lower tier local authority and upper tier local authority levels, we produced weighted averages of the OA scores according to OA populations of children aged 7 and under to reflect where children live.

Limitations of MM-2SFCAs

This method is an improvement on standard supply-to-demand ratios, but still has several limitations.

First, we assume that parents are only willing to access childcare within their defined catchment area from their OA where they live. This enables us to create accessibility ratios, but it is also likely that some parents will not be using childcare close to their home. They may favour a workplace-based nursery or one that is closer to their place of work. These scenarios are not included in this analysis.

Second, we have used fixed catchment sizes for urban and rural areas. It is likely that travel to nurseries will be different in rural areas, particularly for users of public transport, so varying the size of catchment areas may produce more accurate estimates.

When estimating the population that travel by car to their childcare provider, we assume that children are evenly distributed across all households in an OA. Also, we assume that if a household does have access to at least 1 car, they are using this car to access their childcare provider. This is unlikely to always be the case.

The analysis only counts places from Ofsted-registered provision in England. It is likely that parents living on the borders between England and Wales and England and Scotland may use childcare from either country. Therefore, it is hard to estimate what the true potential capacity and demand for these services is. 

This analysis only considers childcare places in providers registered on Ofsted’s Early Years Register (EYR). It does not include:

• providers that are solely registered on our Childcare Register
• parents who may be using informal childcare, such as care from grandparents
• places in some schools. Early years provision in about 10,000 schools (around 300,000 occupied childcare places) is exempt from registration with Ofsted and recorded differently

We have included a reference to early years in schools within the publication, taken from the Department for Education’s schools census.

We wanted to protect sensitive data about individual providers and to improve the efficiency of calculating accessibility scores when new providers register. To do this, we used the nearest OA population weighted centroid to a childcare provider as a proxy for its location, instead of using its postcode.^{[footnote 2]} As OAs are usually geographically small, this is a suitable assumption. However, in some geographically larger OAs, this may be less appropriate. This means that results may be less accurate for providers located in these larger OAs.

We sourced data on travel time from TravelTime, set for arrival on a weekday morning. The travel time data gives an estimate of actual travel time and is likely to vary by time of day. The analysis may therefore not reflect access for parents who work shift patterns.

We advise caution when comparing small-area estimates of childcare accessibility. In a very small number of instances, data on local travel time may not reflect local connections; this may include areas with new residential developments or one-way roads.

Supply of childcare

The early years and childcare sector is primarily made up of private nurseries, pre-schools and childminders. The childcare provision in this publication refers to:

• childcare on non-domestic premises: these are nurseries, pre-schools, holiday clubs and other group-based settings
• childminders: these are people who look after children for payment or reward, in a home that is not the child’s own. Childminders have the option to register either with Ofsted or with a childminder agency

There are also nannies and childcare on domestic premises in the early years sector. Places are not recorded for nannies and there are very few providers of childcare on domestic premises, so we did not include these in this analysis.

To measure the capacity in the early years sector, we used our publicly available data on places offered within childcare providers.

We routinely collect this when we register and inspect providers. The information on places that we compile and present is a proxy for (representation of) the size and capacity of the early years sector.

Ofsted collects data on the number of childcare places that providers intend to ‘offer’ at registration, and this is updated at inspection. We report data on places only for the providers registered on the EYR. A high proportion of these providers are also registered on the compulsory part of the Childcare Register. As a result, it is important to note that the data covers all places for children aged 0 to 7. This data includes all EYR places for children under 5 and places for 5- to 7-year-olds that are on the compulsory part of the Childcare Register.

The number of places offered by a provider is the legal maximum number of children it can provide childcare for at any one time. Different children can be looked after in the morning and in the evening by any one provider, as long as the maximum number of children is not exceeded at any one point in time. Therefore, places are a proxy for the supply of childcare within an OA.

We have redacted a small number of providers of childcare on non-domestic premises, for providers’ personal safety and for national safety.

Demand for childcare

To estimate the demand for childcare, we used populations of all children aged 0 to 7 to provide a measure of potential demand for childcare. Census 2021 estimates there to be 5.04 million children aged 0 to 7. For more information on the strengths, limitations, users, uses and methods for this data, see the ONS’s quality and methodology Information (QMI).

Demand for childcare is likely to be affected by several factors, including the employment status of parents, access to informal childcare, and the affordability and ease of access to childcare. This actual demand is hard to measure. Therefore, in this analysis, the demand for childcare is instead potential demand.  

As places data includes providers registered on the Childcare Register as well as the EYR, the age range of children included is 0 to 7.

1. M Langford, G Higgs and R Fry, ‘Multi-modal two-step floating catchment area analysis of primary health care accessibility’, in ‘Health and Place’, Volume 38, 2016, pages 70 to 81. ↩

2. For each OA, a single fixed point is established that represents how the population is spatially distributed within the OA. ↩ ↩²

3. Z Tao, Z Yao, H Kong, F Duan and G Li, ‘Spatial accessibility to healthcare services in Shenzhen, China: improving the multi-modal two-step floating catchment area method by estimating travel time via online map APIs’ in ‘BMC Health Services Research’, Volume 18, 2018. ↩