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Open Access 01-12-2021 | Research

A method to define the relevant ego-centred spatial scale for the assessment of neighbourhood effects: the example of cardiovascular risk factors

Authors: Jürgen Breckenkamp, Oliver Razum, Jacob Spallek, Klaus Berger, Basile Chaix, Odile Sauzet

Published in: BMC Public Health | Issue 1/2021

Abstract

Introduction

The neighbourhood in which one lives affects health through complex pathways not yet fully understood. A way to move forward in assessing these pathways direction is to explore the spatial structure of health phenomena to generate hypotheses and examine whether the neighbourhood characteristics are able to explain this spatial structure. We compare the spatial structure of two cardiovascular disease risk factors in three European urban areas, thus assessing if a non-measured neighbourhood effect or spatial processes is present by either modelling the correlation structure at individual level or by estimating the intra-class correlation within administrative units.

Methods

Data from three independent studies (RECORD, DHS and BaBi), covering each a European urban area, are used. The characteristics of the spatial correlation structure of cardiovascular risk factors (BMI and systolic blood pressure) adjusted for age, sex, educational attainment and income are estimated by fitting an exponential model to the semi-variogram based on the geo-coordinates of places of residence. For comparison purposes, a random effect model is also fitted to estimate the intra-class correlation within administrative units. We then discuss the benefits of modelling the correlation structure to evaluate the presence of unmeasured spatial effects on health.

Results

BMI and blood pressure are consistently found to be spatially structured across the studies, the spatial correlation structures being stronger for BMI. Eight to 22% of the variability in BMI were spatially structured with radii ranging from 100 to 240 m (range). Only a small part of the correlation of residuals was explained by adjusting for the correlation within administrative units (from 0 to 4 percentage points).

Discussion

The individual spatial correlation approach provides much stronger evidence of spatial effects than the multilevel approach even for small administrative units. Spatial correlation structure offers new possibilities to assess the relevant spatial scale for health. Stronger correlation structure seen for BMI may be due to neighbourhood socioeconomic conditions and processes like social norms at work in the immediate neighbourhood.

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Title: A method to define the relevant ego-centred spatial scale for the assessment of neighbourhood effects: the example of cardiovascular risk factors
Authors: Jürgen Breckenkamp
Oliver Razum
Jacob Spallek
Klaus Berger
Basile Chaix
Odile Sauzet
Publication date: 01-12-2021
Publisher: BioMed Central
Published in: BMC Public Health / Issue 1/2021
Electronic ISSN: 1471-2458
DOI: https://doi.org/10.1186/s12889-021-11356-w

At a glance: The STEP trials

Springer Medicine

A method to define the relevant ego-centred spatial scale for the assessment of neighbourhood effects: the example of cardiovascular risk factors

Abstract

Introduction

Methods

Results

Discussion

At a glance: The STEP trials

Springer Medicine

Abstract

Introduction

Methods

Results

Discussion

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