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

Breckenkamp J, Razum O, Spallek J, Berger K, Chaix B, Sauzet O (2021)
BMC public health 21(1): 1346.

Zeitschriftenaufsatz | Veröffentlicht | Englisch
 
Download
OA 881.82 KB
Autor*in
Breckenkamp, JürgenUniBi; Razum, OliverUniBi; Spallek, Jacob; Berger, Klaus; Chaix, Basile; Sauzet, OdileUniBi
Abstract / Bemerkung
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 240m (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.
Stichworte
Cardiovascular risk factors; Geographic distribution; Spatial scale
Erscheinungsjahr
2021
Zeitschriftentitel
BMC public health
Band
21
Ausgabe
1
Art.-Nr.
1346
eISSN
1471-2458
Finanzierungs-Informationen
Open-Access-Publikationskosten wurden durch die Universität Bielefeld gefördert.
Page URI
https://pub.uni-bielefeld.de/record/2956148

Zitieren

Breckenkamp J, Razum O, Spallek J, Berger K, Chaix B, Sauzet O. A method to define the relevant ego-centred spatial scale for the assessment of neighbourhood effects: the example of cardiovascular risk factors. BMC public health. 2021;21(1): 1346.
Breckenkamp, J., Razum, O., Spallek, J., Berger, K., Chaix, B., & Sauzet, O. (2021). A method to define the relevant ego-centred spatial scale for the assessment of neighbourhood effects: the example of cardiovascular risk factors. BMC public health, 21(1), 1346. https://doi.org/10.1186/s12889-021-11356-w
Breckenkamp, Jürgen, Razum, Oliver, Spallek, Jacob, Berger, Klaus, Chaix, Basile, and Sauzet, Odile. 2021. “A method to define the relevant ego-centred spatial scale for the assessment of neighbourhood effects: the example of cardiovascular risk factors”. BMC public health 21 (1): 1346.
Breckenkamp, J., Razum, O., Spallek, J., Berger, K., Chaix, B., and Sauzet, O. (2021). A method to define the relevant ego-centred spatial scale for the assessment of neighbourhood effects: the example of cardiovascular risk factors. BMC public health 21:1346.
Breckenkamp, J., et al., 2021. A method to define the relevant ego-centred spatial scale for the assessment of neighbourhood effects: the example of cardiovascular risk factors. BMC public health, 21(1): 1346.
J. Breckenkamp, et al., “A method to define the relevant ego-centred spatial scale for the assessment of neighbourhood effects: the example of cardiovascular risk factors”, BMC public health, vol. 21, 2021, : 1346.
Breckenkamp, J., Razum, O., Spallek, J., Berger, K., Chaix, B., Sauzet, O.: A method to define the relevant ego-centred spatial scale for the assessment of neighbourhood effects: the example of cardiovascular risk factors. BMC public health. 21, : 1346 (2021).
Breckenkamp, Jürgen, Razum, Oliver, Spallek, Jacob, Berger, Klaus, Chaix, Basile, and Sauzet, Odile. “A method to define the relevant ego-centred spatial scale for the assessment of neighbourhood effects: the example of cardiovascular risk factors”. BMC public health 21.1 (2021): 1346.
Alle Dateien verfügbar unter der/den folgenden Lizenz(en):
Creative Commons Namensnennung 4.0 International Public License (CC-BY 4.0):
Volltext(e)
Access Level
OA Open Access
Zuletzt Hochgeladen
2022-01-06T08:41:17Z
MD5 Prüfsumme
90baf728982907820ec319eb7406a043


Zitationen in Europe PMC

Daten bereitgestellt von Europe PubMed Central.

References

Daten bereitgestellt von Europe PubMed Central.

Export

Markieren/ Markierung löschen
Markierte Publikationen

Open Data PUB

Web of Science

Dieser Datensatz im Web of Science®
Quellen

PMID: 34233639
PubMed | Europe PMC

Suchen in

Google Scholar