During the past decade, there has been growing research
interest in the impact of neighborhood of residence on
health (1). Most studies have used the multilevel modeling
technique (2). With this approach, standard errors for the
measures of association between neighborhood factors and
health are corrected for the nonindependence of individuals
within neighborhoods (3, 4), and measures of variation
based on random effects (e.g., neighborhood-level variance)
allow quantifying the magnitude of variations in outcomes
among neighborhoods (5–8). However, our hypothesis was
that the multilevel approach may provide only limited information
on the spatial distribution of outcomes, both when
modeling variations and investigating associations, since it
fragments space into administrative neighborhoods and
ignores spatial associations between them.
This methodological question was motivated by an epidemiologic
investigation of spatial variations in mental disorders
in Malmo¨, Sweden, using data on all 65,830 residents
aged 40–59 years in 2001 geocoded at their exact place of
residence. Several previous studies that investigated neighborhood
variations in mental health as a general category
reported only weak variations between neighborhoods (9–
12). Such variations were usually explained by differences
in neighborhood composition (9–11), but some analyses
During the past decade, there has been growing researchinterest in the impact of neighborhood of residence onhealth (1). Most studies have used the multilevel modelingtechnique (2). With this approach, standard errors for themeasures of association between neighborhood factors andhealth are corrected for the nonindependence of individualswithin neighborhoods (3, 4), and measures of variationbased on random effects (e.g., neighborhood-level variance)allow quantifying the magnitude of variations in outcomesamong neighborhoods (5–8). However, our hypothesis wasthat the multilevel approach may provide only limited informationon the spatial distribution of outcomes, both whenmodeling variations and investigating associations, since itfragments space into administrative neighborhoods andignores spatial associations between them.This methodological question was motivated by an epidemiologicinvestigation of spatial variations in mental disordersin Malmo¨, Sweden, using data on all 65,830 residentsaged 40–59 years in 2001 geocoded at their exact place ofresidence. Several previous studies that investigated neighborhoodvariations in mental health as a general categoryreported only weak variations between neighborhoods (9–12). Such variations were usually explained by differencesin neighborhood composition (9–11), but some analyses
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