Air pollution, greenspace, and metabolic syndrome in older Czech and Swiss populations
Status PubMed-not-MEDLINE Jazyk angličtina Země Spojené státy americké Médium electronic-ecollection
Typ dokumentu časopisecké články
PubMed
40351522
PubMed Central
PMC12063789
DOI
10.1097/ee9.0000000000000393
PII: EE-D-24-00147
Knihovny.cz E-zdroje
- Klíčová slova
- Air pollution, Cross-sectional design, Greenspace, Metabolic syndrome, Particulate matter,
- Publikační typ
- časopisecké články MeSH
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 the Czech and Swiss populations. METHODS: Cross-sectional data from the Czech Health, Alcohol and Psychosocial Factors in Eastern Europe (HAPIEE) (n = 4,931) and the Swiss cohort Study on Air Pollution and Lung and Heart Diseases in Adults (SAPALDIA) (n = 4,422) cohorts included participants aged 44-73 years. MetS was defined as abdominal obesity plus two additional components (hypertension, diabetes, low high-density lipoprotein cholesterol, and elevated triglycerides). Annual mean concentrations of PM10, PM2.5, NO2, and greenspace (defined as the annual mean of normalized difference vegetation index 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 the Czech (51.1%) compared with Swiss (35.8%) population as were the concentration means of PM10 and PM2.5. In HAPIEE, a 5 μg/m3 increase in PM2.5 was associated with 14% higher odds of MetS (OR = 1.14; 95% confidence interval [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 normalized difference vegetation index on MetS were observed. Upon inspection of MetS components, PM2.5 and PM10 exposures were associated with higher odds of hypertension and elevated triglycerides 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.
Department of Clinical Science and Education Södersjukhuset Karolinska Institute Stockholm Sweden
German Center for Diabetes Research Neuherberg Germany
IBE Medical Faculty Ludwig Maximilians Universität München Munich Germany
Institute for Risk Assessment Sciences Utrecht University Utrecht the Netherlands
Institute of Epidemiology and Health Care University College London London United Kingdom
RECETOX Faculty of Science Masaryk University Brno Czech Republic
Swiss Tropical and Public Health Institute Allschwil Switzerland
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Kaur J. A comprehensive review on metabolic syndrome. Cardiol Res Pract. 2014;2014:1–21. PubMed PMC
Saklayen MG. The global epidemic of the metabolic syndrome. Curr Hypertens Rep. 2018;20:12. PubMed PMC
Chew NWS, Ng CH, Tan DJH, et al. . The global burden of metabolic disease: data from 2000 to 2019. Cell Metab. 2023;35:414–428.e3. PubMed
Farsang C, Naditch-Brule L, Perlini S, Zidek W, Kjeldsen SE; GOOD investigators. Inter-regional comparisons of the prevalence of cardiometabolic risk factors in patients with hypertension in Europe: the GOOD survey. J Hum Hypertens. 2009;23:316–324. PubMed
Zhou B, Carrillo-Larco RM, Danaei G, et al. . Worldwide trends in hypertension prevalence and progress in treatment and control from 1990 to 2019: a pooled analysis of 1201 population-representative studies with 104 million participants. Lancet. 2021;398:957–980. PubMed PMC
Silveira Rossi JL, Barbalho SM, Reverete de Araujo R, Bechara MD, Sloan KP, Sloan LA. Metabolic syndrome and cardiovascular diseases: going beyond traditional risk factors. Diabetes Metab Res Rev. 2022;38:e3502. PubMed
Lu W, Pikhart H, Tamosiunas A, et al. . Prevalence, awareness, treatment and control of hypertension, diabetes and hypercholesterolemia, and associated risk factors in the Czech Republic, Russia, Poland and Lithuania: a cross-sectional study. BMC Public Health. 2022;22:883. PubMed PMC
Liang M, Pan Y, Zhong T, Zeng Y, Cheng ASK. Effects of aerobic, resistance, and combined exercise on metabolic syndrome parameters and cardiovascular risk factors: a systematic review and network meta-analysis. Rev Cardiovasc Med. 2021;22:1523–1533. PubMed
Zang ST, Luan J, Li L, et al. . Air pollution and metabolic syndrome risk: evidence from nine observational studies. Environ Res. 2021;202:111546. PubMed
Sagheer U, Al-Kindi S, Abohashem S, et al. . Environmental pollution and cardiovascular disease. JACC Adv. 2024;3:100805. PubMed PMC
Han S, Zhang F, Yu H, et al. . Systemic inflammation accelerates the adverse effects of air pollution on metabolic syndrome: findings from the China health and retirement longitudinal study (CHARLS). Environ Res. 2022;215:114340. PubMed
Dabass A, Talbott EO, Rager JR, et al. . Systemic inflammatory markers associated with cardiovascular disease and acute and chronic exposure to fine particulate matter air pollution (PM2.5) among US NHANES adults with metabolic syndrome. Environ Res. 2018;161:485–491. PubMed
Liang D, Li Z, Vlaanderen J, et al. . A state-of-the-science review on high-resolution metabolomics application in air pollution health research: current progress, analytical challenges, and recommendations for future direction. Environ Health Perspect. 2023;131:056002. PubMed PMC
Patwary MM, Sakhvidi MJZ, Ashraf S, et al. . Impact of green space and built environment on metabolic syndrome: a systematic review with meta-analysis. Sci Total Environ. 2024;923:170977. PubMed
Markevych I, Schoierer J, Hartig T, et al. . Exploring pathways linking greenspace to health: theoretical and methodological guidance. Environ Res. 2017;158:301–317. PubMed
de Keijzer C, Tonne C, Basagaña X, et al. . Residential surrounding greenness and cognitive decline: a 10-year follow-up of the Whitehall II Cohort. Environ Health Perspect. 2018;126:077003. PubMed PMC
Matthiessen C, Lucht S, Hennig F, et al. ; Heinz Nixdorf Recall Study Investigative Group. Long-term exposure to airborne particulate matter and NO 2 and prevalent and incident metabolic syndrome – results from the Heinz Nixdorf recall study. Environ Int. 2018;116:74–82. PubMed
Voss S, Schneider A, Huth C, et al. . Long-term exposure to air pollution, road traffic noise, residential greenness, and prevalent and incident metabolic syndrome: results from the population-based KORA F4/FF4 cohort in Augsburg, Germany. Environ Int. 2021;147:106364. PubMed
Eze IC, Schaffner E, Foraster M, et al. . Long-term exposure to ambient air pollution and metabolic syndrome in adults. PLoS One. 2015;10:e0130337. PubMed PMC
Yu Y, Paul K, Arah OA, et al. . Air pollution, noise exposure, and metabolic syndrome – a cohort study in elderly Mexican-Americans in Sacramento area. Environ Int. 2020;134:105269. PubMed PMC
Wang Y, Liu F, Yao Y, et al. . Associations of long-term exposure to ambient air pollutants with metabolic syndrome: the Wuhan Chronic Disease Cohort Study (WCDCS). Environ Res. 2022;206:112549. PubMed
Ke P, Xu M, Xu J, et al. . Association of residential greenness with the risk of metabolic syndrome in Chinese older adults: a longitudinal cohort study. J Endocrinol Invest. 2022;46:327–335. PubMed
Vlaanderen J, de Hoogh K, Hoek G, et al. . Developing the building blocks to elucidate the impact of the urban exposome on cardiometabolic-pulmonary disease. Environ Epidemiol. 2021;5:e162. PubMed PMC
Peasey A, Bobak M, Kubinova R, et al. . Determinants of cardiovascular disease and other non-communicable diseases in Central and Eastern Europe: rationale and design of the HAPIEE study. BMC Public Health. 2006;6:255. PubMed PMC
Martin BW, Ackermann-Liebrich U, Leuenberger P, et al. . SAPALDIA: methods and participation in the cross-sectional part of the Swiss study on air pollution and lung diseases in adults. Soz Praventivmed. 1997;42:67–84. PubMed
Ackermann-Liebrich U, Kuna-Dibbert B, Probst-Hensch NM, et al. ; SAPALDIA team. Follow-up of the Swiss Cohort Study on Air Pollution and Lung Diseases in Adults (SAPALDIA 2) 1991–2003: methods and characterization of participants. Soz Praventivmed. 2005;50:245–263. PubMed
Alberti KGMM, Zimmet P, Shaw J. Metabolic syndrome—a new world‐wide definition. A consensus statement from the international diabetes federation. Diabet Med. 2006;23:469–480. PubMed
Felber Dietrich D, Ackermann-Liebrich U, Schindler C, et al. ; Sapaldia team. Effect of physical activity on heart rate variability in normal weight, overweight and obese subjects: results from the SAPALDIA study. Eur J Appl Physiol. 2008;104:557–565. PubMed PMC
Jasiukaitienė V, Lukšienė D, Tamošiūnas A, Radišauskas R, Bobak M. The impact of metabolic syndrome and lifestyle habits on the risk of the first event of cardiovascular disease: results from a cohort study in Lithuanian urban population. Medicina (Kaunas). 2020;56:18. PubMed PMC
Boyd R, Leigh B, Stuart P. Capillary versus venous bedside blood glucose estimations. Emerg Med J. 2005;22:177–179. PubMed PMC
Topping J, Reardon M, Coleman J, et al. . A comparison of venous versus capillary blood samples when measuring blood glucose using a point-of-care, capillary-based glucometer. Prehosp Disaster Med. 2019;34:506–509. PubMed
Shen Y, de Hoogh K, Schmitz O, et al. . Europe-wide air pollution modeling from 2000 to 2019 using geographically weighted regression. Environ Int. 2022;168:107485. PubMed
de Hoogh K, Chen J, Gulliver J, et al. . Spatial PM2.5, NO2, O3 and BC models for Western Europe – evaluation of spatiotemporal stability. Environ Int. 2018;120:81–92. PubMed
Didan K, Barreto Munoz A. MODIS Vegetation Index User’s Guide (MOD13 Series). The University of Arizona; 2019.
Park YS, Kang SH, Jang SI, Park EC. Association between lifestyle factors and the risk of metabolic syndrome in the South Korea. Sci Rep. 2022;12:13356. PubMed PMC
VanWormer JJ, Boucher JL, Sidebottom AC, Sillah A, Knickelbine T. Lifestyle changes and prevention of metabolic syndrome in the heart of new Ulm project. Prev Med Rep. 2017;6:242–245. PubMed PMC
Hoveling LA, Liefbroer AC, Bültmann U, Smidt N. Understanding socioeconomic differences in metabolic syndrome remission among adults: what is the mediating role of health behaviors? Int J Behav Nutr Phys Act. 2021;18:147. PubMed PMC
World Health Organization. Diet, nutrition and the prevention of chronic diseases: report of a joint WHO/FAO expert consultation.; 2002.
Panczak R, Galobardes B, Voorpostel M, Spoerri A, Zwahlen M, Egger M; Swiss National Cohort and Swiss Household Panel. A Swiss neighbourhood index of socioeconomic position: development and association with mortality. J Epidemiol Community Health. 2012;66:1129–1136. PubMed PMC
Abadie A, Athey S, Imbens GW, Wooldridge J. When should you adjust standard errors for clustering? National Bureau of Economic Research. 2017;C21.
Guo Q, Zhao Y, Xue T, Zhang J, Duan X. Association of PM2.5 and its chemical compositions with metabolic syndrome: a nationwide study in middle-aged and older Chinese adults. Int J Environ Res Public Health. 2022;19:14671. PubMed PMC
Xiao Y, Liu C, Lei R, et al. . Associations of PM2.5 composition and green space with metabolic syndrome in a Chinese essential hypertensive population. Chemosphere. 2023;343:140243. PubMed
Gu Y, Henze DK, Nawaz MO, Cao H, Wagner UJ. Sources of PM25‐associated health risks in Europe and corresponding emission‐induced changes during 2005–2015. Geohealth. 2023;7:e2022GH000767. PubMed PMC
Song J, Lu M, Lu J, et al. . Acute effect of ambient air pollution on hospitalization in patients with hypertension: a time-series study in Shijiazhuang, China. Ecotoxicol Environ Saf. 2019;170:286–292. PubMed
Niedermayer F, Wolf K, Zhang S, et al. . Sex-specific associations of environmental exposures with prevalent diabetes and obesity – results from the KORA fit study. Environ Res. 2024;252:118965. PubMed
Pitchika A, Hampel R, Wolf K, et al. . Long-term associations of modeled and self-reported measures of exposure to air pollution and noise at residence on prevalent hypertension and blood pressure. Sci Total Environ. 2017;593-594:337–346. PubMed
Labib SM, Lindley S, Huck JJ. Spatial dimensions of the influence of urban green-blue spaces on human health: a systematic review. Environ Res. 2020;180:108869. PubMed
Jimenez RB, Lane KJ, Hutyra LR, Fabian MP. Spatial resolution of normalized difference vegetation index and greenness exposure misclassification in an urban cohort. J Expo Sci Environ Epidemiol. 2022;32:213–222. PubMed PMC
Yang BY, Qian ZM, Li S, et al. . Long-term exposure to ambient air pollution (including PM1) and metabolic syndrome: The 33 Communities Chinese Health Study (33CCHS). Environ Res. 2018;164:204–211. PubMed
Luo C, Wei T, Jiang W, et al. . The association between air pollution and obesity: an umbrella review of meta-analyses and systematic reviews. BMC Public Health. 2024;24:1856. PubMed PMC
Qin P, Luo X, Zeng Y, et al. . Long-term association of ambient air pollution and hypertension in adults and in children: a systematic review and meta-analysis. Sci Total Environ. 2021;796:148620. PubMed
Kutlar Joss M, Boogaard H, Samoli E, et al. . Long-term exposure to traffic-related air pollution and diabetes: a systematic review and meta-analysis. Int J Public Health. 2023;68:1605718. PubMed PMC
Gaio V, Roquette R, Dias CM, Nunes B. Ambient air pollution and lipid profile: systematic review and meta-analysis. Environ Pollut. 2019;254:113036. PubMed
Yang BY, Liu KK, Markevych I, et al. . Association between residential greenness and metabolic syndrome in Chinese adults. Environ Int. 2020;135:105388. PubMed
Li X, Wang Q, Feng C, et al. . Associations and pathways between residential greenness and metabolic syndromes in Fujian Province. Front Public Health. 2022;10:1014380. PubMed PMC
de Keijzer C, Basagaña X, Tonne C, et al. . Long-term exposure to greenspace and metabolic syndrome: a Whitehall II study. Environ Pollut. 2019;255:113231. PubMed PMC
Zhao Y, Bao WW, Yang BY, et al. . Association between greenspace and blood pressure: a systematic review and meta-analysis. Sci Total Environ. 2022;817:152513. PubMed
Luo Y, Huang W, Liu X, et al. . Greenspace with overweight and obesity: a systematic review and meta‐analysis of epidemiological studies up to 2020. Obes Rev. 2020;21:e13078. PubMed
Prince SA, Kristjansson EA, Russell K, et al. . A Multilevel analysis of neighbourhood built and social environments and adult self-reported physical activity and body mass index in Ottawa, Canada. Int J Environ Res Public Health. 2011;8:3953–3978. PubMed PMC
Dendup T, Feng X, Clingan S, Astell-Burt T. Environmental risk factors for developing Type 2 diabetes mellitus: a systematic review. Int J Environ Res Public Health. 2018;15:78. PubMed PMC
Paquet C, Coffee NT, Haren MT, et al. . Food environment, walkability, and public open spaces are associated with incident development of cardio-metabolic risk factors in a biomedical cohort. Health Place. 2014;28:173–176. PubMed
Shukla A, Bunkar N, Kumar R, et al. . Air pollution associated epigenetic modifications: transgenerational inheritance and underlying molecular mechanisms. Sci Total Environ. 2019;656:760–777. PubMed
Wu S, Deng F, Niu J, Huang Q, Liu Y, Guo X. Association of heart rate variability in taxi drivers with marked changes in particulate air pollution in Beijing in 2008. Environ Health Perspect. 2010;118:87–91. PubMed PMC
He D, Xi B, Xue J, Huai P, Zhang M, Li J. Association between leisure time physical activity and metabolic syndrome: a meta-analysis of prospective cohort studies. Endocrine. 2014;46:231–240. PubMed
Son JY, Choi HM, Fong KC, Heo S, Lim CC, Bell ML. The roles of residential greenness in the association between air pollution and health: a systematic review. Environ Res Lett. 2021;16:093001.
Bergmann N, Gyntelberg F, Faber J. The appraisal of chronic stress and the development of the metabolic syndrome: a systematic review of prospective cohort studies. Endocr Connect. 2014;3:R55–R80. PubMed PMC
Hong A, Sallis JF, King AC, et al. . Linking green space to neighborhood social capital in older adults: the role of perceived safety. Soc Sci Med. 2018;207:38–45. PubMed
Shao J, Chen D, Zhang H, et al. . Influence of perceived stress on health-promoting behaviors in patients with metabolic syndrome: the multiple mediating roles of adaptability and social support. Zhejiang Da Xue Xue Bao Yi Xue Ban. 2022;51:19–26. PubMed PMC
Eze IC, Foraster M, Schaffner E, et al. . Long-term exposure to transportation noise and air pollution in relation to incident diabetes in the SAPALDIA study. Int J Epidemiol. 2017;46:1115–1125. PubMed PMC
Münzel T, Sørensen M, Gori T, et al. . Environmental stressors and cardio-metabolic disease: part II–mechanistic insights. Eur Heart J. 2016;38:ehw294. PubMed PMC
Eminson K, Cai YS, Chen Y, et al. . Does air pollution confound associations between environmental noise and cardiovascular outcomes? - A systematic review. Environ Res. 2023;232:116075. PubMed