BackgroundResidential property is reported as the most valuable asset people will own and therefore provides the potential to be used as a socio-economic status (SES) measure. Location is generally recognised as the most important determinant of residential property value.Extending the well-established relationship between poor health and socio-economic disadvantage and the role of residential property in the overall wealth of individuals, this study tested the predictive value of the Relative Location Factor (RLF), a SES measure designed to reflect the relationship between location and residential property value, and six cardiometabolic disease risk factors, central obesity, hypertriglyceridemia, reduced high density lipoprotein (HDL), hypertension, impaired fasting glucose, and high low density lipoprotein (LDL). These risk factors were also summed and expressed as a cumulative cardiometabolic risk (CMR) score.MethodsRLF was calculated using a global hedonic regression model from residential property sales transaction data based upon several residential property characteristics, but deliberately blind to location, to predict the selling price of the property. The predicted selling price was divided by the actual selling price and the results interpolated across the study area and classified as tertiles. The measures used to calculate CMR were collected via clinic visits from a population-based cohort study. Models with individual risk factors and the cumulative cardiometabolic risk (CMR) score as dependent variables were respectively tested using log binomial and Poisson generalised linear models.ResultsA statistically significant relationship was found between RLF, the cumulative CMR score and all but one of the risk factors. In all cases, participants in the most advantaged and intermediate group had a lower risk for cardio-metabolic diseases. For the CMR score the RR for the most advantaged was 19% lower (RR = 0.81; CI 0.76-0.86; p <0.0001) and the middle group was 9% lower (RR = 0.91; CI 0.86-0.95; p <0.0001) than the least advantaged group.ConclusionsThis paper advances the understanding of the nexus between place, health and SES by providing an objective spatially informed SES measure for testing health outcomes and reported a robust association between RLF and several health measures.
Each year the proportion of Australians who rent their home increases and, for the first time in generations, there are now as many renters as outright homeowners. Researchers and policy makers, however, know very little about housing conditions within Australia’s rental housing sector due to a lack of systematic, reliable data. In 2020, a collaboration of Australian universities commissioned a survey of tenant households to build a data infrastructure on the household and demographic characteristics, housing quality and conditions in the Australian rental sector. This data infrastructure was designed to be national (representative across all Australian States and Territories), and balanced across key population characteristics. The resultant Australian Rental Housing Conditions Dataset (ARHCD) is a publicly available data infrastructure for researchers and policy makers, providing a basis for national and international research.
The relationship between the wellbeing of society and understanding of land market structure and behaviour is an important research theme for understanding socioeconomic status (SES). Traditional SES area based measures of income, occupation and education are generally applied in the examination of a broad spectrum of societal issues. This paper examines the contribution of understanding the spatial variation of SES based upon residential property sales data unrestricted by the traditional artificial geographic boundaries in which SES is assumed uniform. Originality lies in identifying the locational component of residential property wealth as a proxy for SES. It includes market behavioural characteristics that reflect both the context and composition at particular locations. This provides a broader understanding of SES than income, occupation and education. The analysis uses a hedonic regression model based on transactions of detached housing. The model is specified using only available property attributes as independent variables and is therefore blind to location. The residuals from this hedonic model are used to calculate the relative location factor (RLF) for each transaction property. These were interpolated as a continuous surface capable of predicting values at the individual property level or aggregated to a spatial unit relevant to the particular application. There was a significant correlation with the traditional SES indicators and health outcomes that have traditionally been shown to have a correlation with SES.
Research applying residential property value as a socioeconomic status measure is increasing. The literature includes several measures of residential property value socioeconomic status, all of which highlight location as an important component. This paper examines the drivers of the location component of residential property value that form the basis of its application as a socioeconomic status measure. The metropolitan area of Adelaide, South Australia, is used as a study area to analyse the composition and context embodied in residential property location value. The focus of this paper is to provide an understanding of the drivers of residential property value calculated as the relative location factor, deliberately constructed to reflect the effect on value due to location. The analysis reduced the traditional composition measures of social structure into a smaller number of factors using principal component analysis and regressed these against relative location factor. A spatial lens was applied to the results using Moran’s I to visualise the composition and context influence embodied in relative location factor. The results provided a significantly enhanced understanding of both the composition and context of socioeconomic status wealth that may be a more suitable socioeconomic status measure than the traditional composition measures of income, education and occupation. This paper provides an original interpretation of the contribution and use of residential property location value enabling a broader understanding of socioeconomic status, concluding that relative location factor provided a more informed measure of socioeconomic status, capable of enhancing social science and health research and policy formation.
Purpose -Spatially enabled taxation systems provide public policy makers in Australia with a conundrum. For the Valuers General who provide the fiscal cadastre for the taxation system, spatial enablement could lead to a central role in State Government taxation or to a sidelined role. This paper aims to address this issue. Design/methodology/approach -The paper uses a survey of Valuers General. Findings -The paper establishes the current extent of adoption of spatially enabled taxation systems, identifies current provision and uses of valuation data and explores possible future provision and uses of such data.Research limitations/implications -The sample size for survey may limit its use elsewhere. Practical implications -The paper concludes that further integration and a unified national policy approach would be preferable. Originality/value -The first published paper to establish the current extent of adoption of spatially enabled taxation systems and to identify current provision and uses of valuation data in Australasia.
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