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A spatial structural equation model for health outcomes. (English) Zbl 1134.62074

Summary: Population level risk factors in spatial epidemiology (e.g., socioeconomic deprivation) are often not directly available but indirectly measured through census or other sources. This paper considers multiple health outcomes (e.g., mortality, hospital admissions) in relation to unmeasured latent constructs of population morbidity, established as relevant to explaining spatial contrasts in such health outcomes. The constructs are derived using a factor analytic approach in which observed area social indicators are measures of a smaller set of latent constructs. The constructs are allowed to be spatially correlated as well as correlated with one another. The possibility of nonlinear construct effects is considered using a spline regression. A case study considers suicide mortality and self-harm contrasts in 32 London boroughs, in relation to two latent constructs: area deprivation and social fragmentation.

MSC:

62P10 Applications of statistics to biology and medical sciences; meta analysis
62H25 Factor analysis and principal components; correspondence analysis
62P25 Applications of statistics to social sciences
62H11 Directional data; spatial statistics

Software:

WinBUGS; BayesDA; SemiPar
Full Text: DOI

References:

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