Small Area Indices of Multiple Deprivation in South Africa

2009 ◽  
Vol 95 (2) ◽  
pp. 281-297 ◽  
Author(s):  
Michael Noble ◽  
Helen Barnes ◽  
Gemma Wright ◽  
Benjamin Roberts
Phytotaxa ◽  
2021 ◽  
Vol 512 (3) ◽  
Author(s):  
GIDEON F. SMITH ◽  
RONELL R. KLOPPER

The little-known Aloe labiaflava (Asphodelaceae subfam. Alooideae), which has for long been regarded as a hybrid between A. davyana and A. longibracteata, is reinstated as an accepted species endemic to a small area in the western Mpumalanga province of South Africa. It differs from both A. davyana and A. longibracteata in several reproductive morphological characters not present in these two species, especially by almost invariably producing only a single inflorescence per flowering season and by having a perianth that is distinctly flared at the mouth, with especially the external, apical ⅓ of the perianth conspicuously yellow.


2016 ◽  
Vol 13 (9) ◽  
pp. 921-928 ◽  
Author(s):  
Stephen Zwolinsky ◽  
James McKenna ◽  
Andy Pringle ◽  
Paul Widdop ◽  
Claire Griffiths ◽  
...  

Background:Increasingly the health impacts of physical inactivity are being distinguished from those of sedentary behavior. Nevertheless, deleterious health prognoses occur when these behaviors combine, making it a Public Health priority to establish the numbers and salient identifying factors of people who live with this injurious combination.Methods:Using an observational between-subjects design, a nonprobability sample of 22,836 participants provided data on total daily activity. A 2-step hierarchical cluster analysis identified the optimal number of clusters and the subset of distinguishing variables. Univariate analyses assessed significant cluster differences.Results:High levels of sitting clustered with low physical activity. The Ambulatory & Active cluster (n = 6254) sat for 2.5 to 5 h·d−1 and were highly active. They were significantly younger, included a greater proportion of males and reported low Indices of Multiple Deprivation compared with other clusters. Conversely, the Sedentary & Low Active cluster (n = 6286) achieved ≤60 MET·min·wk−1 of physical activity and sat for ≥8 h·d−1. They were the oldest cluster, housed the largest proportion of females and reported moderate Indices of Multiple Deprivation.Conclusions:Public Health systems may benefit from developing policy and interventions that do more to limit sedentary behavior and encourage light intensity activity in its place.


2019 ◽  
Vol 42 (4) ◽  
pp. 772-777
Author(s):  
Steven L Senior

Abstract Background The English Indices of Multiple Deprivation (IMD) is widely used as a measure of deprivation. However, similarly ranked areas can differ substantially in the underlying domains of deprivation. These domains contain a richer set of data that might be useful for classifying local authorities. Clustering methods offer a set of techniques to identify groups of areas with similar patterns of deprivation. Methods Hierarchical agglomerative (i.e. bottom-up) clustering methods were applied to domain scores for 152 upper tier local authorities. Advances in statistical testing allow clusters to be identified that are unlikely to have arisen from random partitioning of a homogeneous group. The resulting clusters are described in terms of their subdomain scores and basic geographic and demographic characteristics. Results Five statistically significant clusters of local authorities were identified. These clusters only partially reflect different levels of overall deprivation. In particular, two clusters share similar overall IMD scores but have contrasting patterns of deprivation. Conclusion Hierarchical clustering methods identify five distinct clusters that do not correspond closely to quintiles of deprivation. This approach may help to distinguish between places that face similar underlying challenges, and places that appear similar in terms of overall deprivation scores, but that face different challenges.


PLoS ONE ◽  
2017 ◽  
Vol 12 (8) ◽  
pp. e0181260 ◽  
Author(s):  
Daniel John Exeter ◽  
Jinfeng Zhao ◽  
Sue Crengle ◽  
Arier Lee ◽  
Michael Browne

2016 ◽  
Vol 11 (1) ◽  
pp. 36-58 ◽  
Author(s):  
Andrew J. E. Charman ◽  
Leif M. Petersen ◽  
Laurence E. Piper ◽  
Rory Liedeman ◽  
Teresa Legg

In this article, we describe a research approach to undertaking a small area census to identify informal economy activity, using a mixture of quantitative and qualitative tools. The method focuses on enterprise activity. The approach enables the researcher to record a broader spectrum of informal micro-enterprises through identifying businesses in situ within an area of sufficient scale to broadly reflect area-level market conditions and business dynamics. The approach comprises an enterprise census, a survey of all identified micro-enterprises in key sectors, in-depth interviews, and participatory research techniques. The article reports on the application of this method in eight case sites, located in township settlements within five major cities in South Africa. The research identified 9,400 individual enterprises, entailing 10,220 primary and secondary activities, distributed within a population of 325,000 and comprising 97,000 households. The approach permits significant advances to our understanding of the spatial dynamics of the informal sector. The research data has enabled the researcher to make original contributions to understanding informal enterprise activities in grocery retailing, liquor trade, and traditional medicine sectors.


2016 ◽  
Vol 26 (suppl_1) ◽  
Author(s):  
K Bozorgmehr ◽  
O Razum ◽  
J Szecsenyi ◽  
W Maier ◽  
C Stock

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