Modifying effect of urban parks on socioeconomic inequalities in diabetes prevalence: a cross-sectional population study of Madrid City, Spain.

DIABETES MELLITUS INEQUALITIES SOCIAL SCIENCES

Journal

Journal of epidemiology and community health
ISSN: 1470-2738
Titre abrégé: J Epidemiol Community Health
Pays: England
ID NLM: 7909766

Informations de publication

Date de publication:
07 Mar 2024
Historique:
received: 24 07 2023
accepted: 25 02 2024
medline: 8 3 2024
pubmed: 8 3 2024
entrez: 7 3 2024
Statut: aheadofprint

Résumé

Evidence has shown contradicting results on how the density of urban green spaces may reduce socioeconomic inequalities in type 2 diabetes ( We designed a population-wide cross-sectional study of all adults registered in the primary healthcare centres in the city of Madrid, Spain (n=1 305 050). We obtained georeferenced individual-level data from the Primary Care Electronic Health Records, and census-tract level data on socioeconomic status (SES) and park density. We modelled diabetes prevalence using robust Poisson regression models adjusted by age, country of origin, population density and including an interaction term with park density, stratified by gender. We used this model to estimate the Relative Index of Inequality (RII) at different park density levels. We found an overall RII of 2.90 (95% CI 2.78 to 3.02) and 4.50 (95% CI 4.28 to 4.74) in men and women, respectively, meaning that the prevalence of diabetes was three to four and a half times higher in low SES compared with high SES areas. These inequalities were wider in areas with higher park density for both men and women, with a significant interaction only for women (p=0.008). We found an inverse association between SES and diabetes prevalence in both men and women, with wider inequalities in areas with more parks. Future works should study the mechanisms of these findings, to facilitate the understanding of contextual factors that may mitigate diabetes inequalities.

Sections du résumé

BACKGROUND BACKGROUND
Evidence has shown contradicting results on how the density of urban green spaces may reduce socioeconomic inequalities in type 2 diabetes (
METHODS METHODS
We designed a population-wide cross-sectional study of all adults registered in the primary healthcare centres in the city of Madrid, Spain (n=1 305 050). We obtained georeferenced individual-level data from the Primary Care Electronic Health Records, and census-tract level data on socioeconomic status (SES) and park density. We modelled diabetes prevalence using robust Poisson regression models adjusted by age, country of origin, population density and including an interaction term with park density, stratified by gender. We used this model to estimate the Relative Index of Inequality (RII) at different park density levels.
FINDINGS RESULTS
We found an overall RII of 2.90 (95% CI 2.78 to 3.02) and 4.50 (95% CI 4.28 to 4.74) in men and women, respectively, meaning that the prevalence of diabetes was three to four and a half times higher in low SES compared with high SES areas. These inequalities were wider in areas with higher park density for both men and women, with a significant interaction only for women (p=0.008).
INTERPRETATION CONCLUSIONS
We found an inverse association between SES and diabetes prevalence in both men and women, with wider inequalities in areas with more parks. Future works should study the mechanisms of these findings, to facilitate the understanding of contextual factors that may mitigate diabetes inequalities.

Identifiants

pubmed: 38453450
pii: jech-2023-221198
doi: 10.1136/jech-2023-221198
pii:
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Informations de copyright

© Author(s) (or their employer(s)) 2024. No commercial re-use. See rights and permissions. Published by BMJ.

Déclaration de conflit d'intérêts

Competing interests: None declared.

Auteurs

Elena Plans-Beriso (E)

Department of Epidemiology of Chronic Diseases, National Center For Epidemiology, Instituto de Salud Carlos III, Madrid, Spain.
Public Health and Epidemiology Research Group, Facultad de Medicina y Ciencias de la Salud, Universidad de Alcala de Henares, Alcala de Henares, Spain.
CIBERESP (CIBER of Epidemiology and Public Health), Madrid, Spain.

Pedro Gullon (P)

Public Health and Epidemiology Research Group, Facultad de Medicina y Ciencias de la Salud, Universidad de Alcala de Henares, Alcala de Henares, Spain pedro.gullon@uah.es.

Mario Fontan-Vela (M)

Public Health and Epidemiology Research Group, Facultad de Medicina y Ciencias de la Salud, Universidad de Alcala de Henares, Alcala de Henares, Spain.

Manuel Franco (M)

Social and Cardiovascular Research Group, Facultad de Medicina y Ciencias de la Salud, Universidad de Alcala de Henares, Alcala de Henares, Spain.

Beatriz Perez-Gomez (B)

Department of Epidemiology of Chronic Diseases, National Center For Epidemiology, Instituto de Salud Carlos III, Madrid, Spain.
CIBERESP (CIBER of Epidemiology and Public Health), Madrid, Spain.

Marina Pollan (M)

Department of Epidemiology of Chronic Diseases, National Center For Epidemiology, Instituto de Salud Carlos III, Madrid, Spain.
CIBERESP (CIBER of Epidemiology and Public Health), Madrid, Spain.

Isabel Cura-Gonzalez (I)

Primary Care Research Unit, Madrid Health Service, Madrid, Spain.
Health Services Research on Chronic Patients Network (REDISSEC), Instituto de Salud Carlos III, Madrid, Spain.

Usama Bilal (U)

Urban Health Collaborative, Drexel University, Philadelphia, Pennsylvania, USA.
Epidemiology and Biostatistics, Drexel University, Philadelphia, Pennsylvania, USA.

Classifications MeSH