The health potential of neighborhoods: A population-wide study in the Netherlands

Background: While differences in population health across neighborhoods with different socioeconomic characteristics are well documented, health disparities across neighborhoods with similar socioeconomic characteristics are less well understood. We aimed to estimate population health inequalities, both within and between neighborhoods with similar socioeconomic status, and assessed the association of neighborhood characteristics and socioeconomic spillover effects from adjacent neighborhoods. Methods: Based on Dutch whole-population data we determined the percentage of inhabitants with good o... Mehr ...

Verfasser: L.H. Dekker
R.H. Rijnks
J.O. Mierau
Dokumenttyp: Artikel
Erscheinungsdatum: 2021
Reihe/Periodikum: SSM: Population Health, Vol 15, Iss , Pp 100867- (2021)
Verlag/Hrsg.: Elsevier
Schlagwörter: Population health / Self-assessed health / Chronic disease / Neighborhoods / Spatial epidemiology / Spatial spillover effects / Public aspects of medicine / RA1-1270 / Social sciences (General) / H1-99
Sprache: Englisch
Permalink: https://search.fid-benelux.de/Record/base-29172863
Datenquelle: BASE; Originalkatalog
Powered By: BASE
Link(s) : https://doi.org/10.1016/j.ssmph.2021.100867

Background: While differences in population health across neighborhoods with different socioeconomic characteristics are well documented, health disparities across neighborhoods with similar socioeconomic characteristics are less well understood. We aimed to estimate population health inequalities, both within and between neighborhoods with similar socioeconomic status, and assessed the association of neighborhood characteristics and socioeconomic spillover effects from adjacent neighborhoods. Methods: Based on Dutch whole-population data we determined the percentage of inhabitants with good or very good self-assessed health (SAH) and the percentage of inhabitants with at least one chronic disease (CD) in 11,504 neighborhoods. Neighborhoods were classified by quintiles of a composite neighborhoods socioeconomic status score (NSES). A set of spatial models was estimated accounting for spatial effects in the dependent, independent, and error components of the model. Results: Substantial population health disparities in SAH and CD both within and between neighborhoods NSES quintiles were observed, with the largest SAH variance in the lowest NSES group. Neighborhoods adjacent to higher SES neighborhoods showed a higher SAH and a lower prevalence of CD. Projected impacts from the spatial regressions indicate how modest changes in NSES among the lowest socioeconomic neighborhoods can contribute to population health in both low- and high-SES neighborhoods. Conclusion: Population health differs substantially among neighborhoods with similar socioeconomic characteristics, which can partially be explained by a spatial socio-economic spillover effect.