Modification of the original CCI was necessary where data on the severity of renal or liver disease were not collected; these were classified as 2. Remoteness (rurality of residence) was determined using the Accessibility/Remoteness Index of Australia [ 10] with groups ranging from 1 'highly accessible' and 5 'very remote'.
Differences in the group characteristics; age, socioeconomic status (using postcode to assess against the Socioeconomic Index for Advantage (SEIFA), [ 40] remoteness (using the Accessibility and Remoteness Index for Australia [ 41]), marital status, and age of infant were assessed.
Demographic data were compared to the Census data and the Australian Study of Health and Relationships data for similarly aged men and women. 2 Census data [ 21] Remoteness defined in accordance with the Australian Standard Geographical Classification-Remoteness Area System in 2010.
There is increasing evidence that contextual effects, such as availability of health services, socio-economic deprivation [ 14, 15], aggregate social capital [ 16- 19] and remoteness [ 20- 22] influence the experience of disease and health.
Rankings are from 1 (not at all) to 4 (very) Remoteness 2 Only two hours from the airport in Manchester, N.H., and minutes from the popular ski town North Conway, the White Mountains aren't tough to reach.
Client residential postcodes were used to determine disadvantage (Socio-Economic Indexes for Areas [SEIFA]; cut points: higher NSW half [>991] versus lower NSW half [<=991]) [ 57] and remoteness (Access/Remoteness Index of Australia [ARIA]; major cities versus regional remote towns) [ 58].
One of the products that eventually came forth was ARIA+, a system that creates an index, with values ranging from 0 (high accessibility) to 15 (high remoteness), based on road distance measurements from over 12,000 populated localities to the nearest urban areas in five categories based on population size.
ARIA is a continuous varying index with values ranging from 0 (high accessibility) to 15 (high remoteness), and is based on road distance measurements from over 12,000 populated localities to the nearest Service Centres in five size categories based on population size.
The nodal crime-generating and crime-attracting characteristics of stations are explored by examining: 1) the connectedness of particular stations to the rest of the transit system; and 2) the remoteness of the station from the central business district.
The ARIA+ scores localities according to their proximity to service centres using a continuous scale from 0 (high accessibility) to 15 (high remoteness).
This pattern of differences in predictors for the two types of stigma was broadly consistent with the results of mixed Within-Between ANOVAs as indicated by significant interactions between stigma type and each of the predictors (p < 0.05) except remoteness of residence (p = 0.60).
