Přehled o publikaci
2025
Air pollution, greenspace, and metabolic syndrome in older Czech and Swiss populations
DALECKÁ, Andrea; Ayoung JEONG; Daniel SZABÓ; Balint TAMASI; Medea IMBODEN et. al.Basic information
Original name
Air pollution, greenspace, and metabolic syndrome in older Czech and Swiss populations
Authors
DALECKÁ, Andrea; Ayoung JEONG; Daniel SZABÓ; Balint TAMASI; Medea IMBODEN; Emmanuel SCHAFFNER; Dirk KEIDEL; Youchen SHEN; Mark NIEUWENHUIJSEN; Marta CIRACH; Kees DE HOOGH; Jelle VLAANDEREN; Roel VERMEULEN; Annette PETERS; Erik MELÉN; Anne PEASEY; Martin BOBÁK; Hynek PIKHART and Nicole PROBST-HENSCH
Edition
Environmental Epidemiology, PHILADELPHIA, Wolters Kluwer Health, 2025, 2474-7882
Other information
Language
English
Type of outcome
Article in a journal
Country of publisher
United States of America
Confidentiality degree
is not subject to a state or trade secret
References:
Organization
Přírodovědecká fakulta – Repository – Repository
UT WoS
001483998700001
EID Scopus
2-s2.0-105005155172
Keywords in English
Metabolic syndrome; Air pollution; Particulate matter; Greenspace; Cross-sectional design
Links
LM2023069, research and development project. LX22NPO5101, research and development project. 857487, interní kód Repo. 857560, interní kód Repo. 874627, interní kód Repo.
Changed: 24/6/2025 00:50, RNDr. Daniel Jakubík
Abstract
V originále
Background: The prevalence of metabolic syndrome (MetS) has increased rapidly, with considerable variation between European countries. The study examined the relationship between air pollutants, greenspace and MetS and its components in Czech and Swiss populations. Methods: Cross-sectional data from the Czech HAPIEE (n=4,931) and the Swiss SAPALDIA (n=4,422) cohorts included participants aged 44-73 years. MetS was defined as abdominal obesity plus two additional components (hypertension, diabetes, low HDL cholesterol, elevated triglycerides). Annual mean concentrations of PM10, PM2.5, NO2 and greenspace (defined as annual mean of NDVI within 500 m) were assigned to the individual residential level. We estimated odds ratios (OR) using multivariable logistic regressions with cluster-robust standard error, controlling for multiple confounders. Results: The prevalence of MetS was significantly higher in Czech (51.1%) compared to Swiss (35.8%) population as were the concentration means of PM10 and PM2.5. In HAPIEE, 5 μg/m3 increase in PM2.5 was associated with 14% higher odds of MetS (OR=1.14; 95% CI 1.01-1.28). In SAPALDIA, no evidence was found for the associations between air pollutants and MetS (e.g. OR=1.01; 95% CI 0.90-1.13 for PM2.5). No protective effects of NDVI on MetS were observed. Upon inspection of MetS components, PM2.5 and PM10 exposures were associated with higher odds of hypertension and elevated TG in HAPIEE only, while PM2.5, PM10 and NO2 were associated with higher odds of diabetes in SAPALDIA only. Conclusion: Individuals with higher exposures to PM2.5 may be at higher risk of MetS. The differential associations with MetS components between the cohorts deserve further investigation.