The relationship of the built and food environments with the metabolic syndrome in the Athens metropolitan area: a sex-stratified spatial analysis in the context of the ATTICA epidemiological study

Abstract

Purpose

The built and food environments are widely acknowledged to play an important role in defining human health by influencing, among others, behaviors such as nutrition habits and physical activities. The aim of this study was to identify the spatial variability of the sex-specific prevalence of the metabolic syndrome (MetS) and its environmental determinants in the Athens metropolitan area.

Methods

Data on the prevalence of the MetS were provided by the ATTICA epidemiological study for 2749 participants, with complete data for geographical identification (1375 women [44 years old {SD = 14 years}] and 1374 men [45 years old {SD = 13 years}]), while socioeconomic, demographic, and environmental characteristics were provided by official national and international databases.

Results

Approximately 20% of the people residing in the study area were diagnosed with MetS, with its prevalence being almost two times higher in men compared to women. Areas more extensively covered by green urban spaces and sports facilities were shown to have a lower prevalence of MetS, while greater density and availability of supermarkets and street markets were inversely related to MetS prevalence in both sexes. In addition, the present analysis revealed that the beneficial role of the built environment’s characteristics on MetS prevalence was significantly stronger in the male population, while the preventive effect of the food environment’s characteristics was almost 1.5 times stronger in the female population

Conclusion

Although individualized prevention and treatment approaches are necessary to decrease the burden of MetS, environmental modifications that promote healthy behaviors represent an essential health approach.

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Data availability

The data are available upon request. For expression of interest, please contact Prof. Demosthenes Panagiotakos (dbpanag@hua.gr).

Code availability

Not applicable.

References

  1. 1.

    Panagiotakos DB, Pitsavos C, Skoumas Y, Stefanadis C (2007) The association between food patterns and the metabolic syndrome using principal components analysis: the ATTICA Study. J Am Diet Assoc 107(6):979–997. https://doi.org/10.1016/j.jada.2007.03.006

    Article  PubMed  Google Scholar 

  2. 2.

    Saklayen MG (2018) The global epidemic of the metabolic syndrome. Curr Hypertens Rep 20(2):12. https://doi.org/10.1007/s11906-018-0812-z

    Article  PubMed  PubMed Central  Google Scholar 

  3. 3.

    Qi L, Cho YA (2008) Gene-environment interaction and obesity. Nutr Rev 66(12):684–694. https://doi.org/10.1111/j.1753-4887.2008.00128.x

    Article  PubMed  PubMed Central  Google Scholar 

  4. 4.

    Kastorini CM, Milionis HJ, Esposito K, Giugliano D, Goudevenos JA, Panagiotakos DB (2011) The effect of Mediterranean diet on metabolic syndrome and its components: a meta-analysis of 50 studies and 534,906 individuals. J Am Coll Cardiol 57(11):1299–1313. https://doi.org/10.1016/j.jacc.2010.09.073

    CAS  Article  PubMed  Google Scholar 

  5. 5.

    Faka A, Chalkias C, Georgousopoulou EN, Tripitsidis A, Pitsavos C, Panagiotakos DB (2019) Identifying determinants of obesity in Athens, Greece through global and local statistical models. Spat Spatio-Temporal Epidemiol 29:31–41. https://doi.org/10.1016/j.sste.2019.02.002

    Article  Google Scholar 

  6. 6.

    Thompson Coon J, Boddy K, Stein K, Whear R, Barton J, Depledge MH (2011) Does participating in physical activity in outdoor natural environments have a greater effect on physical and mental wellbeing than physical activity indoors? A systematic review. Environ Sci Technol 45(5):1761–1772. https://doi.org/10.1021/es102947t

    CAS  Article  PubMed  Google Scholar 

  7. 7.

    Gong Y, Palmer S, Gallacher J, Marsden T, Fone D (2016) A systematic review of the relationship between objective measurements of the urban environment and psychological distress. Environ Int 96:48–57. https://doi.org/10.1016/j.envint.2016.08.019

    Article  PubMed  Google Scholar 

  8. 8.

    Markevych I, Schoierer J, Hartig T, Chudnovsky A, Hystad P, Dzhambov AM, de Vries S, Triguero-Mas M, Brauer M, Nieuwenhuijsen MJ, Lupp G, Richardson EA, Astell-Burt T, Dimitrova D, Feng X, Sadeh M, Standl M, Heinrich J, Fuertes E (2017) Exploring pathways linking greenspace to health: theoretical and methodological guidance. Environ Res 158:301–317. https://doi.org/10.1016/j.envres.2017.06.028

    CAS  Article  PubMed  Google Scholar 

  9. 9.

    Kotzeva M, Brandmüller T, Lupa I, Önnerfors A, Corselli-Nordblad L, Coyette C, Johansson A, Strandell H, Pascal W (2016) Urban Europe—statistics on cities, towns, and suburbs [WWW Document]. https://doi.org/10.2785/91120

  10. 10.

    Matthiessen C, Lucht S, Hennigh F, Ohlwein S, Jakobs H, Jöckel KH, Moebus S, Hoffmann B, Heinz Nixdorf Recall Study Investigative Group (2018) Long-term exposure to airborne particulate matter and NO2 and prevalent and incident metabolic syndrome—results from the Heinz Nixdorf Recall Study. Environ Int 116:74–82. https://doi.org/10.1016/j.envint.2018.02.035

    CAS  Article  PubMed  Google Scholar 

  11. 11.

    Faka A, Chalkias C, Montano D, Georgousopoulou EN, Tripitsidis A, Koloverou E, Tousoulis D, Pitsavos C, Panagiotakos DB (2018) Association of socio-environmental determinants with diabetes prevalence in the Athens metropolitan area, Greece: a spatial analysis. Rev Diabet Stud 14(4):381–389. https://doi.org/10.1900/RDS.2017.14.381

    Article  PubMed  PubMed Central  Google Scholar 

  12. 12.

    Faka A, Chalkias C, Magriplis E, Georgousopoulou EN, Tripitsidis A, Pitsavos C, Panagiotakos DB (2020) The influence of socio-environmental determinants on hypertension. A spatial analysis in Athens metropolitan area, Greece. J Prevent Med Hyg 61(1):E76–E84. https://doi.org/10.15167/jpmh2020.21.1.988

    CAS  Article  Google Scholar 

  13. 13.

    Alter DA, Eny K (2005) The relationship between the supply of fast-food chains and cardiovascular outcomes. Can J Public Health 96(3):173–177. https://doi.org/10.1007/BF03403684

    Article  PubMed  PubMed Central  Google Scholar 

  14. 14.

    Tsiampalis T, Faka A, Kouvari M, Psaltopoulou T, Pitsavos C, Chalkias C, Panagiotakos DB (2020) The impact of socioeconomic and environmental determinants on Mediterranean diet adherence: a municipal-level spatial analysis in Athens metropolitan area, Greece. Int J Food Sci Nutr 1–12. Advance online publication. https://doi.org/10.1080/09637486.2020.1791057

  15. 15.

    Panagiotakos DB, Georgousopoulou EN, Pitsavos C, Chrysohoou C, Metaxa V, Georgiopoulos GA, Kalogeropoulou K, Tousoulis D, Stefanadis C, ATTICA Study group (2015) Ten-year (2002–2012) cardiovascular disease incidence and all-cause mortality, in urban Greek population: the ATTICA Study. Int J Cardiol 180:178–184. https://doi.org/10.1016/j.ijcard.2014.11.206

    Article  PubMed  Google Scholar 

  16. 16.

    Panagiotakos D, Pitsavos C, Chrysohoou C, Skoumas I, Stefanadis C, ATTICA Study (2008) Five-year incidence of cardiovascular disease and its predictors in Greece: the ATTICA study. Vasc Med 13(2):113–121. https://doi.org/10.1177/1358863x07087731

    Article  PubMed  Google Scholar 

  17. 17.

    Pitsavos C, Panagiotakos DB, Chrysohoou C, Stefanadis C (2003) Epidemiology of cardiovascular risk factors in Greece: aims, design and baseline characteristics of the ATTICA study. BMC Public Health 3:32. https://doi.org/10.1186/1471-2458-3-32

    Article  PubMed  PubMed Central  Google Scholar 

  18. 18.

    Tsiampalis T, Panagiotakos DB (2020) Missing-data analysis: socio-demographic, clinical and lifestyle determinants of low response rate on self-reported psychological and nutrition related multi-item instruments in the context of the ATTICA epidemiological study. BMC Med Res Methodol 20(1):148. Published 2020 Jun 8. https://doi.org/10.1186/s12874-020-01038-3

  19. 19.

    United Nations Educational Scientific and Cultural Organization Institute for Statistics: International Standard Classification of Education ISCED (2011) Montréal, 2012

  20. 20.

    Prastacos P, Chrysoulakis N, Kochilakis G (2011) Urban Atlas, land use modelling and spatial metric techniques. Barcelona: Proceedings of the 51st European Congress of the Regional Science Association International, 30 August–2 September 2011

  21. 21.

    Brewer CA, Pickle L (2002) Evaluation of methods for classifying epidemiological data on choropleth maps in series. Ann Assoc Am Geogr 92(4):662–681

    Article  Google Scholar 

  22. 22.

    Lisabeth LD, Diez Roux AV, Escobar JD, Smith MA, Morgenstern LB (2007) Neighborhood environment and risk of ischemic stroke: the brain attack surveillance in Corpus Christi (BASIC) Project. Am J Epidemiol 165(3):279–287

    CAS  Article  Google Scholar 

  23. 23.

    Roux AVD, Merkin SS, Arnett D, Chambless L, Massing M, Nieto FJ, Watson RL (2001) Neighborhood of residence and incidence of coronary heart disease. N Engl J Med 345(2):99–106

    Article  Google Scholar 

  24. 24.

    Krishnan S, Cozier YC, Rosenberg L, Palmer JR (2010) Socioeconomic status and incidence of type 2 diabetes: results from the Black Women's Health Study. Am J Epidemiol 171(5):564–570

    Article  Google Scholar 

  25. 25.

    Chaix B, Bean K, Leal C, Thomas F, Havard S, Evans D, Pannier B (2010) Individual/neighborhood social factors and blood pressure in the RECORD Cohort Study: which risk factors explain the associations? Hypertension 55(3):769–775

    CAS  Article  Google Scholar 

  26. 26.

    Leal C, Bean K, Thomas F, Chaix B (2011). Are associations between neighborhood socioeconomic characteristics and body mass index or waist circumference based on model extrapolations? Epidemiology 694–703

  27. 27.

    Hickman C (2013) “To brighten the aspect of our streets and increase the health and enjoyment of our city”: The National Health Society and urban green space in late-nineteenth century London. Landsc Urban Plan 118:112–119

    Article  Google Scholar 

  28. 28.

    World Health Organisation (2016) European healthy cities network 2016. Available: 〈http://www.euro.who.int/en/health-topics/environment-and-health/urban-health/activities/healthy-cities/who-european-healthy-cities-network/what-is-a-healthycity〉.

  29. 29.

    Yang BY, Hu LW, Jalaludin B, et al (2020) Association Between Residential Greenness, Cardiometabolic Disorders, and Cardiovascular Disease Among Adults in China. JAMA Netw Open 3(9):e2017507. Published 2020 Sep 1. https://doi.org/10.1001/jamanetworkopen.2020.17507

  30. 30.

    Wang K, Lombard J, Rundek T et al (2019) Relationship of neighborhood greenness to heart disease in 249 405 US Medicare Beneficiaries. J Am Heart Assoc 8(6):e010258. https://doi.org/10.1161/JAHA.118.010258

    Article  PubMed  PubMed Central  Google Scholar 

  31. 31.

    Astell-Burt T, Feng X, Kolt GS (2014) Greener neighborhoods, slimmer people? Evidence from 246,920 Australians. Int J Obes 38:156–159. https://doi.org/10.1038/ijo.2013.64

    CAS  Article  Google Scholar 

  32. 32.

    Dalton AM, Jones AP, Sharp SJ, Cooper AJ, Griffin S, Wareham NJ (2016) Residential neighbourhood greenspace is associated with reduced risk of incident diabetes in older people: a prospective cohort study. BMC Public Health 16(1):1171. Published 2016 Nov 18. https://doi.org/10.1186/s12889-016-3833-z

  33. 33.

    Brown SC, Lombard J, Wang K et al (2016) Neighborhood greenness and chronic health conditions in medicare beneficiaries. Am J Prev Med 51(1):78–89. https://doi.org/10.1016/j.amepre.2016.02.008

    Article  PubMed  Google Scholar 

  34. 34.

    Loo CJ, Greiver M, Aliarzadeh B, Lewis D (2017) Association between neighbourhood walkability and metabolic risk factors influenced by physical activity: a cross-sectional study of adults in Toronto. Canada BMJ open 7(4):e013889

    Article  Google Scholar 

  35. 35.

    Chandrabose M, Cerin E, Mavoa S, Dunstan D, Carver A, Turrell G, Sugiyama T (2019) Neighborhood walkability and 12-year changes in cardio-metabolic risk: the mediating role of physical activity. Int J Behav Nutr Phys Act 16(1):1–11

    Article  Google Scholar 

  36. 36.

    Cohen DA, McKenzie TL, Sehgal A, Williamson S, Golinelli D, Lurie N (2007) Contribution of public parks to physical activity. Am J Public Health 97. https://doi.org/10.2105/AJPH.2005.072447

  37. 37.

    Moore LV, Diez Roux AV, Nettleton JA, Jacobs DR Jr (2008) Associations of the local food environment with diet quality—a comparison of assessments based on surveys and geographic information systems: the multi-ethnic study of atherosclerosis. Am J Epidemiol 167(8):917–924

    Article  Google Scholar 

  38. 38.

    Bodor JN, Rice JC, Farley TA, Swalm CM, Rose D (2010) The association between obesity and urban food environment. J Urban Health 87(5):771–781

    Article  Google Scholar 

  39. 39.

    Giang T, Karpyn A, Laurison H, Hillier A, Burton M, Perry D (2008) Closing the grocery gap in underserved communities: the creation of the Pennsylvania Fresh Food Financing Initiative. J Public Health Manag Pract 14(3):272–279

    Article  Google Scholar 

  40. 40.

    Rose D, Richards R (2004) Food store access and household fruit and vegetable use among participants in the US Food Stamp Program. Public Health Nutr 7(8):1081–1088

    Article  Google Scholar 

  41. 41.

    Robinson PL, Dominguez F, Teklehaimanot S, Lee M, Brown A, Goodchild M (2013) Does distance decay modelling of supermarket accessibility predict fruit and vegetable intake by individuals in a large metropolitan area. J Health Care Poor Underserved 24:172–185

    Article  Google Scholar 

  42. 42.

    Larson NI, Story MT, Nelson MC (2009) Neighborhood environments: disparities in access to healthy foods in the U.S. Am J Prevent Med 36(1):74-81. 14

    Article  Google Scholar 

  43. 43.

    Powell LM, Auld C, Chaloupka FJ, O’Malley PM, Johnston LD (2007) Associations between access to food stores and adolescent body mass index. Am J Prev Med 33(4S):S301–S307

    Article  Google Scholar 

  44. 44.

    Treuhaft S, Karpyn A (2010) The grocery gap: who has access to healthy food and why it matters. The Food Trust

  45. 45.

    He D, Xi B, Xue J, Huai P, Zhang M, Li J (2014) Association between leisure time physical activity and metabolic syndrome: a meta-analysis of prospective cohort studies. Endocrine 46(2):231–240. https://doi.org/10.1007/s12020-013-0110-0

    CAS  Article  PubMed  Google Scholar 

  46. 46.

    Gong Y, Gallacher J, Palmer S, Fone D (2014) Neighbourhood green space, physical function and participation in physical activities among elderly men: the Caerphilly Prospective study. Int J Behav Nutr Phys Act 11(1):40. Published 2014 Mar 19. https://doi.org/10.1186/1479-5868-11-40

  47. 47.

    Eze IC, Schaffner E, Foraster M, et al (2015) Long-term exposure to ambient air pollution and metabolic syndrome in adults. PLoS One 10(6):e0130337. Published 2015 Jun 23. https://doi.org/10.1371/journal.pone.0130337

  48. 48.

    Bergmann N, Gyntelberg F, Faber J (2014) The appraisal of chronic stress and the development of the metabolic syndrome: a systematic review of prospective cohort studies. Endocr Connect 3(2):R55–R80. https://doi.org/10.1530/EC-14-0031

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  49. 49.

    Rook GA (2013) Regulation of the immune system by biodiversity from the natural environment: an ecosystem service essential to health. Proc Natl Acad Sci USA 110:18360–18367

    CAS  Article  Google Scholar 

  50. 50.

    Lee M, Lim M, Kim J (2019) Fruit and vegetable consumption and the metabolic syndrome: a systematic review and dose-response meta-analysis. Br J Nutr 122(7):723–733. https://doi.org/10.1017/S000711451900165X

    CAS  Article  PubMed  Google Scholar 

  51. 51.

    Zhang Y, Zhang DZ (2018) Associations of vegetable and fruit consumption with metabolic syndrome. A meta-analysis of observational studies. Public Health Nutr 21(9):1693–1703. https://doi.org/10.1017/S1368980018000381

    Article  PubMed  Google Scholar 

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Acknowledgements

The authors would like to thank the ATTICA study group of investigators: Christina Chrysohoou, Yannis Skoumas, Natasa Katinioti, Labros Papadimitriou, Constantina Masoura, Spiros Vellas, Yannis Lentzas, Manolis Kambaxis, Konstanitna Paliou, Vassiliki Metaxa, Ekavi Georgousopoulou, Agathi Ntzouvani, Dimitris Mpougatas, Nikolaos Skourlis, Christina Papanikolaou, Aikaterini Kalogeropoulou, Evangelia Pitaraki, Alexandros Laskaris, Mihail Hatzigeorgiou, Athanasios Grekas, and Eleni Kokkou for assistance in the initial physical examination and/or the follow-up evaluation; Efi Tsetsekou for her assistance in psychological evaluation and follow-up evaluation; and the laboratory team, Carmen Vassiliadou and George Dedousis (genetic analysis), Marina Toutouza-Giotsa, Constantina Tselika, and Sia Poulopoulou (biochemical analysis), and Maria Toutouza for database management. We would also like to thank all the individuals who participated in the ATTICA study.

Funding

The ATTICA study is supported by research grants from the Hellenic Cardiology Society [HCS2002] and the Hellenic Atherosclerosis Society [HAS2003].

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Authors

Contributions

TT wrote the manuscript (interpretation of the results and discussion) and performed the statistical analysis. AF, TP, CC, and CP contributed to the interpretation of the results and discussion. DBP and CP were responsible for the study’s design and implementation and critically reviewed the manuscript.

Corresponding author

Correspondence to Demosthenes B. Panagiotakos.

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Ethics approval and consent to participate

ATTICA study was approved by the bioethics committee of the Athens Medical School. The study was carried out in accordance with the Declaration of Helsinki (1989) of the World Medical Association.

Informed consent

All participants were informed about the study aims and procedures, and written informed consent was obtained from all individual participants included in the study.

Conflict of interest

The authors declare no competing interests.

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Tsiampalis, T., Faka, A., Psaltopoulou, T. et al. The relationship of the built and food environments with the metabolic syndrome in the Athens metropolitan area: a sex-stratified spatial analysis in the context of the ATTICA epidemiological study. Hormones (2021). https://doi.org/10.1007/s42000-021-00293-3

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Keywords

  • Metabolic syndrome
  • Sex-specific
  • Spatial analysis
  • Built environment
  • Food environment
  • ATTICA study