To review the range of ways in which 'rurality' is defined and measured, and the implications of this for policy makers (section 2).

To review existing methods of measuring deprivation and to determine how well they identify rural deprivation (section 3).

To advise on what measures currently (if any) are best placed to detect rural deprivation (section 4).

To identify any existing methods of measuring distance and access in the public or commercial sector (section 5).

The way in which rurality is defined will have important implications for the way in which service needs and problems of access are interpreted.

Peripherality appears to be associated with high levels of disadvantage (including poor health status). However, when rural areas are defined on the basis of alternative measures, such as settlement size and population density, the problems faced by peripheral communities tend not to be captured.

Measures of rurality alter with the scale at which analysis takes place. Key aspects of rurality (and indeed rural deprivation) cannot always be gauged from standard indicators where the unit of analysis is too large to capture the greater degree of heterogeneity that characterizes rural areas.

Indicators that capture deprivation in an urban context (e.g. car ownership, unemployment) should not be expected to perform similarly in rural areas.

When focused studies have been undertaken, significant problems relating to employment, low incomes, housing, transport and education have been revealed in rural areas.

The assumption that rural environments are inevitably 'healthier' is increasingly open to challenge – rural mortality advantages disappear after controlling for socio-economic status and limiting long-term illness appears to be subject to a U-shaped pattern of prevalence, the highest rates being observed in the most urban and the most peripheral areas.

Service deprivation emerges as a key component of disadvantage in rural areas. For example, a recent survey of British local authorities found that rural authorities traditionally spent less on social care services and direct provision. Accessibility problems, self-reliance, lower expectations of services and a lack of anonymity also combine to ensure that service needs are not explicitly registered.

Three main options have emerged for the development of more appropriate indicators of measuring rural disadvantage. These are 1) measures that reflect multiple dimensions of deprivation; 2) the use of direct measures of service need rather than proxies; and 3) methods that enable planners to develop people-based rather than area-based policies in heterogeneous rural areas.

When, as is often the case, deprivation is used as a 'proxy measure' for specific service need, direct methods provide more robust and transparent indicators than general (or summary) deprivation indicators. In recent years there has been considerable progress in developing needs estimates that are both directly tailored for specific service sectors (e.g. employment, housing, education, health) and that are created for functionally meaningful units (e.g. schools, general practices, primary care trusts) rather than census administrative areas.

Of the summary measures of deprivation that are available, the Index of Multiple Deprivation 2000 is found to exhibit the closest overall association with standardised illness and mortality ratios. It also has by far the strongest association in rural areas, suggesting that it is able to best express rural disadvantage as it impacts upon health status.

The investigation of utilisation is of key interest to service providers who are seeking to monitor equity of access. Nevertheless, it is generally accepted that, because utilisation is influenced by some factors that lie outside the control of service providers, potential accessibility (the physical availability of services) is a more realistic and legitimate target for policy intervention.

Reviewing recent developments in the measurement and modelling of potential accessibility, we find that, using travel time (which is generally superseding the use of straight line distance), more people in rural areas appear to have reasonable access to basic services than has been thought in the past. In light of this rural service providers might more usefully focus on the question of how to improve access to more specialist services.

With regard to capturing the additional costs of providing rural services, modelling (which includes simulation, algorithm and cover range approaches) has proved useful in helping planners to quantify the resources required to achieve basic access standards. The modelling of service accessibility has also made explicit the fact that activities such as ambulance response times do vary between rural and urban contexts.