Browsing by Author "De Jong, T."
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- ItemThe identification of possible future provincial boundaries for South Africa based on an intramax analysis of journey-to-work data(Operations Research Society of South Africa, 2008) Nel, J. H.; Krygsman, Stephan C.; De Jong, T.ENGLISH SUMMARY : National census data contain information on place of residence and place of work. It is possible to combine this information and create journey-to-work ows. The process of establishing these ows are presented in this paper. The intramax method is explained and used to identify functional regions based upon these ows. Interesting applications, such as the demarcation of regions in South Africa are considered and solutions to disputed areas are put forward. The process of the creation of the current provincial boundaries are discussed. New boundaries, based on the intramax analysis of the journey-to-work data are proposed for four or ve new provinces. Results compare favourably with those from a principal component and cluster analysis, which has previously been used to demarcate the South African space economy into a hierarchy of development regions.
- ItemUrban–rural inequalities in suicide mortality : a comparison of urbanicity indicators(Biomed Central, 2017-10-30) Helbich, M.; Bluml, V.; De Jong, T.; Plener, P. L.; Kwan, M. P.; Kapusta, N. D.Background: Urban–rural disparities in suicide mortality have received considerable attention. Varying conceptualizations of urbanity may contribute to the conflicting findings. This ecological study on Germany assessed how and to what extent urban–rural suicide associations are affected by 14 different urban–rural indicators. Methods: Indicators were based on continuous or k-means classified population data, land-use data, planning typologies, or represented population-based accessibility indicators. Agreements between indicators were tested with correlation analyses. Spatial Bayesian Poisson regressions were estimated to examine urban–rural suicide associations while adjusting for risk and protective factors. Results: Urban–rural differences in suicide rates per 100,000 persons were found irrespective of the indicator. Strong and significant correlation was observed between different urban–rural indicators. Although the effect sign consistently referred to a reduced risk in urban areas, statistical significance was not universally confirmed by all regressions. Goodness-of-fit statistics suggested that the population potential score performs best, and that population density is the second best indicator of urbanicity. Numerical indicators are favored over classified ones. Regional planning typologies are not supported. Conclusions: The strength of suicide urban–rural associations varies with respect to the applied indicator of urbanicity. Future studies that put urban–rural inequalities central are recommended to apply either unclassified population potentials or population density indicators, but sensitivity analyses are advised.