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Comparison of a spatial approach with the multilevel approach for investigating place effects on health: the example of healthcare utilisation in France

Chaix, B; Merlo, Juan LU and Chauvin, P (2005) In Journal of Epidemiology and Community Health 59(6). p.517-526
Abstract
Study objective: Most studies of place effects on health have followed the multilevel analytical approach that investigates geographical variations of health phenomena by fragmenting space into arbitrary areas. This study examined whether analysing geographical variations across continuous space with spatial modelling techniques and contextual indicators that capture space as a continuous dimension surrounding individual residences provided more relevant information on the spatial distribution of outcomes. Healthcare utilisation in France was taken as an illustrative example in comparing the spatial approach with the multilevel approach. Design: Multilevel and spatial analyses of cross sectional data. Participants: 10 955 beneficiaries of... (More)
Study objective: Most studies of place effects on health have followed the multilevel analytical approach that investigates geographical variations of health phenomena by fragmenting space into arbitrary areas. This study examined whether analysing geographical variations across continuous space with spatial modelling techniques and contextual indicators that capture space as a continuous dimension surrounding individual residences provided more relevant information on the spatial distribution of outcomes. Healthcare utilisation in France was taken as an illustrative example in comparing the spatial approach with the multilevel approach. Design: Multilevel and spatial analyses of cross sectional data. Participants: 10 955 beneficiaries of the three principal national health insurance funds, surveyed in 1998 and 2000 on continental France. Main results: Multilevel models showed significant geographical variations in healthcare utilisation. However, the Moran's I statistic showed spatial autocorrelation unaccounted for by multilevel models. Modelling the correlation between people as a decreasing function of the spatial distance between them, spatial mixed models gave information not only on the magnitude, but also on the scale of spatial variations, and provided more accurate standard errors for risk factors effects. The socioeconomic level of the residential context and the supply of physicians were independently associated with healthcare utilisation. Place indicators better explained spatial variations in healthcare utilisation when measured across continuous space, rather than within administrative areas. Conclusions: The kind of conceptualisation of space during analysis influences the understanding of place effects on health. In many contextual studies, viewing space as a continuum may yield more relevant information on the spatial distribution of outcomes. (Less)
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author
organization
publishing date
type
Contribution to journal
publication status
published
subject
in
Journal of Epidemiology and Community Health
volume
59
issue
6
pages
517 - 526
publisher
BMJ Publishing Group
external identifiers
  • wos:000229312600017
  • pmid:15911650
  • scopus:20344407312
ISSN
1470-2738
DOI
10.1136/jech.2004.025478
language
English
LU publication?
yes
id
d6b99d47-8869-4b48-a065-03baa7078927 (old id 239008)
date added to LUP
2007-08-07 11:37:46
date last changed
2017-07-30 03:44:47
@article{d6b99d47-8869-4b48-a065-03baa7078927,
  abstract     = {Study objective: Most studies of place effects on health have followed the multilevel analytical approach that investigates geographical variations of health phenomena by fragmenting space into arbitrary areas. This study examined whether analysing geographical variations across continuous space with spatial modelling techniques and contextual indicators that capture space as a continuous dimension surrounding individual residences provided more relevant information on the spatial distribution of outcomes. Healthcare utilisation in France was taken as an illustrative example in comparing the spatial approach with the multilevel approach. Design: Multilevel and spatial analyses of cross sectional data. Participants: 10 955 beneficiaries of the three principal national health insurance funds, surveyed in 1998 and 2000 on continental France. Main results: Multilevel models showed significant geographical variations in healthcare utilisation. However, the Moran's I statistic showed spatial autocorrelation unaccounted for by multilevel models. Modelling the correlation between people as a decreasing function of the spatial distance between them, spatial mixed models gave information not only on the magnitude, but also on the scale of spatial variations, and provided more accurate standard errors for risk factors effects. The socioeconomic level of the residential context and the supply of physicians were independently associated with healthcare utilisation. Place indicators better explained spatial variations in healthcare utilisation when measured across continuous space, rather than within administrative areas. Conclusions: The kind of conceptualisation of space during analysis influences the understanding of place effects on health. In many contextual studies, viewing space as a continuum may yield more relevant information on the spatial distribution of outcomes.},
  author       = {Chaix, B and Merlo, Juan and Chauvin, P},
  issn         = {1470-2738},
  language     = {eng},
  number       = {6},
  pages        = {517--526},
  publisher    = {BMJ Publishing Group},
  series       = {Journal of Epidemiology and Community Health},
  title        = {Comparison of a spatial approach with the multilevel approach for investigating place effects on health: the example of healthcare utilisation in France},
  url          = {http://dx.doi.org/10.1136/jech.2004.025478},
  volume       = {59},
  year         = {2005},
}