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Diabetologia

pp 1–11 | Cite as

Long-term exposure to ambient fine particulate matter (PM2.5) and incident type 2 diabetes: a longitudinal cohort study

  • Xiang Qian LaoEmail author
  • Cui Guo
  • Ly-yun Chang
  • Yacong Bo
  • Zilong Zhang
  • Yuan Chieh Chuang
  • Wun Kai Jiang
  • Changqing Lin
  • Tony Tam
  • Alexis K. H. Lau
  • Chuan-Yao Lin
  • Ta-Chien Chan
Article

Abstract

Aims/hypothesis

Information on the associations of long-term exposure to fine particulate matter (with an aerodynamic diameter less than 2.5 μm; PM2.5) with the development of type 2 diabetes is scarce, especially for south-east Asia, where most countries are experiencing serious air pollution. This study aimed to investigate the long-term effects of exposure to ambient PM2.5 on the incidence of type 2 diabetes in a population of Taiwanese adults.

Methods

A total of 147,908 participants without diabetes, at least 18 years of age, were recruited in a standard medical examination programme between 2001 and 2014. They were encouraged to take medical examinations periodically and underwent at least two measurements of fasting plasma glucose (FPG). Incident type 2 diabetes was identified as FPG ≥7 mmol/l or self-reported physician-diagnosed diabetes in the subsequent medical visits. The PM2.5 concentration at each participant’s address was estimated using a satellite-based spatiotemporal model with a resolution of 1 × 1 km2. The 2 year average of PM2.5 concentrations (i.e. the year of and the year before the medical examination) was treated as an indicator of long-term exposure to ambient PM2.5 air pollution. We performed Cox regression models with time-dependent covariates to analyse the long-term effects of exposure to PM2.5 on the incidence of type 2 diabetes. A wide range of covariates were introduced in the models to control for potential effects, including age, sex, education, season, year, smoking status, alcohol drinking, physical activity, vegetable intake, fruit intake, occupational exposure, BMI, hypertension and dyslipidaemia (all were treated as time-dependent covariates except for sex).

Results

Compared with the participants exposed to the first quartile of ambient PM2.5, participants exposed to the second, third and fourth quartiles of ambient PM2.5 had HRs of 1.28 (95% CI 1.18, 1.39), 1.27 (95% CI 1.17, 1.38) and 1.16 (95% CI 1.07, 1.26), respectively, for the incidence of type 2 diabetes. Participants who drank occasionally or regularly (more than once per week) or who had a lower BMI (<23 kg/m2) were more sensitive to the long-term effects of exposure to ambient PM2.5.

Conclusions/interpretation

Long-term exposure to ambient PM2.5 appears to be associated with a higher risk of developing type 2 diabetes in this Asian population experiencing high levels of air pollution.

Keywords

Incident type 2 diabetes Longitudinal cohort Long-term exposure PM2.5 

Abbreviations

AOD

Aerosol optical depth

FPG

Fasting plasma glucose

MET

Metabolic equivalent value

PM

Particulate matter

PM2.5

Particulate matter with an aerodynamic diameter less than 2.5 μm

Notes

Acknowledgements

We appreciate the MJ Health Research Foundation for authorising the use of its health data (authorisation code: MJHR2015002A). We are grateful to the anonymous reviewers and the editors for their valuable comments.

Contribution statement

XQL conceived and designed the study and obtained the funding. L-YC, AKHL and XQL supervised this study. L-YC, AKHL and XQL acquired the data. CG, YB and ZZ searched the literature. ZZ, YB, YCC and WKJ cleaned the data. CL and AKHL estimated the PM2.5 concentration. CG analysed the data. CG, XQL, TT, C-YL and TCC interpreted the results. CG and XQL drafted the manuscript. XQL, CG, TT, C-YL and TCC revised the manuscript. All authors contributed to the content and critical revision of the manuscript and agreed to submit the manuscript for publication. XQL is the guarantor of this work and, as such, had full access to all the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis.

Funding

This work was in part supported by the Environmental Health Research Fund of the Chinese University of Hong Kong (7104946). CG and YB are supported by the PhD Studentship of the Chinese University of Hong Kong.

Duality of interest

The authors declare that there is no duality of interest associated with this manuscript.

Supplementary material

125_2019_4825_MOESM1_ESM.pdf (156 kb)
ESM (PDF 156 kb)

References

  1. 1.
    Hay S (2017) Global, regional, and national incidence, prevalence, and years lived with disability for 328 diseases and injuries for 195 countries, 1990–2016: a systematic analysis for the Global Burden of Disease Study 2016. Lancet 390:49CrossRefGoogle Scholar
  2. 2.
    Steel N (2017) Global, regional, and national age-sex specific mortality for 264 causes of death, 1980–2016: a systematic analysis for the Global Burden of Disease Study 2016. Lancet 390:1151–1210CrossRefGoogle Scholar
  3. 3.
    World Health Organization (2016) Global report on diabetes. World Health Organization, GenevaGoogle Scholar
  4. 4.
    Donnelly R, Emslie-Smith AM, Gardner ID, Morris AD (2000) ABC of arterial and venous disease: vascular complications of diabetes. BMJ 320(7241):1062–1066.  https://doi.org/10.1136/bmj.320.7241.1062 CrossRefPubMedPubMedCentralGoogle Scholar
  5. 5.
    Sjølie AK, Stephenson J, Aldington S et al (1997) Retinopathy and vision loss in insulin-dependent diabetes in Europe: the EURODIAB IDDM Complications Study. Ophthalmology 104(2):252–260.  https://doi.org/10.1016/S0161-6420(97)30327-3 CrossRefPubMedGoogle Scholar
  6. 6.
    Perneger TV, Brancati FL, Whelton PK, Klag MJ (1994) End-stage renal disease attributable to diabetes mellitus. Ann Intern Med 121(12):912–918.  https://doi.org/10.7326/0003-4819-121-12-199412150-00002 CrossRefPubMedGoogle Scholar
  7. 7.
    Zimmet P, Alberti K, Shaw J (2001) Global and societal implications of the diabetes epidemic. Nature 414(6865):782–787.  https://doi.org/10.1038/414782a CrossRefPubMedGoogle Scholar
  8. 8.
    Brook RD, Rajagopalan S, Pope CA et al (2010) Particulate matter air pollution and cardiovascular disease. Circulation 121(21):2331–2378.  https://doi.org/10.1161/CIR.0b013e3181dbece1 CrossRefPubMedGoogle Scholar
  9. 9.
    Wang B, Xu D, Jing Z, Liu D, Yan S, Wang Y (2014) Effect of long-term exposure to air pollution on type 2 diabetes mellitus risk: a systemic review and meta-analysis of cohort studies. Eur J Endocrinol 171(5):R173–R182.  https://doi.org/10.1530/EJE-14-0365 CrossRefPubMedGoogle Scholar
  10. 10.
    Park SK, Wang W (2014) Ambient air pollution and type 2 diabetes: a systematic review of epidemiologic research. Curr Environ Health Rep 1(3):275–286.  https://doi.org/10.1007/s40572-014-0017-9 CrossRefPubMedPubMedCentralGoogle Scholar
  11. 11.
    Balti EV, Echouffo-Tcheugui JB, Yako YY, Kengne AP (2014) Air pollution and risk of type 2 diabetes mellitus: a systematic review and meta-analysis. Diabetes Res Clin Pract 106(2):161–172.  https://doi.org/10.1016/j.diabres.2014.08.010 CrossRefPubMedGoogle Scholar
  12. 12.
    Yang B-Y, Qian ZM, Li S et al (2018) Ambient air pollution in relation to diabetes and glucose-homoeostasis markers in China: a cross-sectional study with findings from the 33 communities Chinese health study. Lancet Planet Health 2(2):e64–e73.  https://doi.org/10.1016/S2542-5196(18)30001-9 CrossRefPubMedGoogle Scholar
  13. 13.
    Honda T, Puna VC, Manjourides J, Suh H (2017) Associations between long-term exposure to air pollution, glycosylated hemoglobin and diabetes. Int J Hyg Environ Health 220(7):1124–1132.  https://doi.org/10.1016/j.ijheh.2017.06.004 CrossRefPubMedPubMedCentralGoogle Scholar
  14. 14.
    Jerrett M, Brook R, White LF et al (2017) Ambient ozone and incident diabetes: a prospective analysis in a large cohort of African American women. Environ Int 102:42–47.  https://doi.org/10.1016/j.envint.2016.12.011 CrossRefPubMedPubMedCentralGoogle Scholar
  15. 15.
    Eze IC, Foraster M, Schaffner E et al (2017) Long-term exposure to transportation noise and air pollution in relation to incident diabetes in the SAPALDIA study. Int J Epidemiol 46(4):1115–1125.  https://doi.org/10.1093/ije/dyx020 CrossRefPubMedPubMedCentralGoogle Scholar
  16. 16.
    Hansen AB, Ravnskjaer L, Loft S et al (2016) Long-term exposure to fine particulate matter and incidence of diabetes in the Danish nurse cohort. Environ Int 91:243–250.  https://doi.org/10.1016/j.envint.2016.02.036 CrossRefPubMedGoogle Scholar
  17. 17.
    Zhang Z, Chang L-Y, Lau AK et al (2017) Satellite-based estimates of long-term exposure to fine particulate matter are associated with C-reactive protein in 30 034 Taiwanese adults. Int J Epidemiol 46(4):1126–1136.  https://doi.org/10.1093/ije/dyx069 CrossRefPubMedPubMedCentralGoogle Scholar
  18. 18.
    Lao XQ, Zhang Z, Lau AKH et al (2018) Exposure to ambient fine particulate matter and semen quality in Taiwan. Occup Environ Med 75(2):148–154.  https://doi.org/10.1136/oemed-2017-104529 CrossRefPubMedGoogle Scholar
  19. 19.
    Zhang Z, Guo C, Lau AK et al (2018) Long-term exposure to fine particulate matter, blood pressure, and incident hypertension in Taiwanese adults. Environ Health Perspect 126(1):017008.  https://doi.org/10.1289/EHP2466 CrossRefPubMedPubMedCentralGoogle Scholar
  20. 20.
    Wu X, Tsai SP, Tsao CK et al (2017) Cohort profile: the Taiwan MJ cohort: half a million Chinese with repeated health surveillance data. Int J Epidemiol 46(6):1744–1744g.  https://doi.org/10.1093/ije/dyw282 CrossRefPubMedGoogle Scholar
  21. 21.
    American Diabetes Association (2014) Diagnosis and classification of diabetes mellitus. Diabetes Care 37(Supplement_1):S81–S90.  https://doi.org/10.2337/dc14-S081 CrossRefGoogle Scholar
  22. 22.
    Lin C, Li Y, Yuan Z, Lau AK, Li C, Fung JC (2015) Using satellite remote sensing data to estimate the high-resolution distribution of ground-level PM2.5. Remote Sens Environ 156:117–128.  https://doi.org/10.1016/j.rse.2014.09.015 CrossRefGoogle Scholar
  23. 23.
    Lin C, Li Y, Lau AKH et al (2016) Estimation of long-term population exposure to PM2.5 for dense urban areas using 1-km MODIS data. Remote Sens Environ 179:13–22.  https://doi.org/10.1016/j.rse.2016.03.023 CrossRefGoogle Scholar
  24. 24.
    Liu Y (2014) Monitoring PM2.5 from space for health: past, present, and future directions. EM (Pittsburgh Pa) 6:6–10Google Scholar
  25. 25.
    Wang ML (2016) MJ Health Research Foundation, MJ Health Resource Center, Technical Report. Available from www.mjhrf.org/file/en/report/MJHRF-TR-01MJ%20Health%20Database.pdf. Accessed 20 Jan 2018
  26. 26.
    Puett RC, Hart JE, Schwartz J, Hu FB, Liese AD, Laden F (2011) Are particulate matter exposures associated with risk of type 2 diabetes? Environ Health Perspect 119(3):384–389.  https://doi.org/10.1289/ehp.1002344 CrossRefPubMedGoogle Scholar
  27. 27.
    Lao XQ, Deng HB, Liu X et al (2018) Increased leisure-time physical activity associated with lower onset of diabetes in 44,828 adults with impaired fasting glucose. Brit J Sport Med [Article online]. Available from http://bjsm.bmj.com/content/early/2018/01/12/bjsports-2017-098199. Accessed 28 April 2018
  28. 28.
    Pan W-H, Flegal KM, Chang H-Y, Yeh W-T, Yeh C-J, Lee W-C (2004) Body mass index and obesity-related metabolic disorders in Taiwanese and US whites and blacks: implications for definitions of overweight and obesity for Asians. Am J Clin Nutr 79(1):31–39.  https://doi.org/10.1093/ajcn/79.1.31 CrossRefPubMedGoogle Scholar
  29. 29.
    Chen H, Burnett RT, Kwong JC et al (2013) Risk of incident diabetes in relation to long-term exposure to fine particulate matter in Ontario, Canada. Environ Health Perspect 121(7):804–810.  https://doi.org/10.1289/ehp.1205958 CrossRefPubMedPubMedCentralGoogle Scholar
  30. 30.
    Coogan PF, White LF, Yu J et al (2016) PM2.5 and diabetes and hypertension incidence in the Black Womenʼs Health Study. Epidemiol 27:202–210Google Scholar
  31. 31.
    Qiu H, Schooling CM, Sun S et al (2018) Long-term exposure to fine particulate matter air pollution and type 2 diabetes mellitus in elderly: a cohort study in Hong Kong. Environ Int 113:350–356.  https://doi.org/10.1016/j.envint.2018.01.008 CrossRefPubMedGoogle Scholar
  32. 32.
    Liu C, Yang C, Zhao Y et al (2016) Associations between long-term exposure to ambient particulate air pollution and type 2 diabetes prevalence, blood glucose and glycosylated hemoglobin levels in China. Environ Int 92:416–421CrossRefGoogle Scholar
  33. 33.
    Andersen ZJ, Raaschou-Nelsen O, Ketzel M et al (2012) Diabetes incidence and long-term exposure to air pollution: a cohort study. Diabetes Care 35(1):92–98.  https://doi.org/10.2337/dc11-1155 CrossRefPubMedGoogle Scholar
  34. 34.
    Krämer U, Herder C, Sugiri D et al (2010) Traffic-related air pollution and incident type 2 diabetes: results from SALIA cohort study. Environ Health Perspect 118(9):1273–1279.  https://doi.org/10.1289/ehp.0901689 CrossRefPubMedPubMedCentralGoogle Scholar
  35. 35.
    Coogan PF, White LF, Jerrett M et al (2012) Air pollution and incidence of hypertension and diabetes mellitus in black women living in Los Angeles. Circulation 125(6):767–772.  https://doi.org/10.1161/CIRCULATIONAHA.111.052753 CrossRefPubMedPubMedCentralGoogle Scholar
  36. 36.
    Park SK, Adar SD, O’Neill MS et al (2015) Long-term exposure to air pollution and type 2 diabetes mellitus in a multiethnic cohort. Am J Epidemiol 181(5):327–336.  https://doi.org/10.1093/aje/kwu280 CrossRefPubMedPubMedCentralGoogle Scholar
  37. 37.
    OʼDonovan G, Chudasama Y, Grocock S et al (2017) The association between air pollution and type 2 diabetes in a large cross-sectional study in Leicester: the CHAMPIONS study. Environ Int 104:41–47.  https://doi.org/10.1016/j.envint.2017.03.027 CrossRefPubMedGoogle Scholar
  38. 38.
    Weinmayr G, Hennig F, Fuks K et al (2015) Long-term exposure to fine particulate matter and incidence of type 2 diabetes mellitus in a cohort study: effects of total and traffic-specific air pollution. Environ Health 14:1–8CrossRefGoogle Scholar
  39. 39.
    Rajagopalan S, Brook RD (2012) Air pollution and type 2 diabetes: mechanistic insights. Diabetes 61(12):3037–3045.  https://doi.org/10.2337/db12-0190 CrossRefPubMedPubMedCentralGoogle Scholar
  40. 40.
    Ying Z, Xu X, Bai Y et al (2014) Long-term exposure to concentrated ambient PM2.5 increases mouse blood pressure through abnormal activation of the sympathetic nervous system: a role for hypothalamic inflammation. Environ Health Perspect 122(1):79–86.  https://doi.org/10.1289/ehp.1307151 CrossRefPubMedGoogle Scholar
  41. 41.
    Mendez R, Zheng Z, Fan Z, Rajagopalan S, Sun Q, Zhang K (2013) Exposure to fine airborne particulate matter induces macrophage infiltration, unfolded protein response, and lipid deposition in white adipose tissue. Am J Transl Res 5:224–234PubMedPubMedCentralGoogle Scholar
  42. 42.
    Pereira Filho M, Pereira L, Arbex FF et al (2008) Effect of air pollution on diabetes and cardiovascular diseases in São Paulo, Brazil. Braz J Med Biol Res 41(6):526–532.  https://doi.org/10.1590/S0100-879X2008005000020 CrossRefPubMedGoogle Scholar
  43. 43.
    Zhang Z, Hoek G, Chang L-Y et al (2017) Particulate matter air pollution, physical activity and systemic inflammation in Taiwanese adults. Int J Hyg Environ Health 221:41–47CrossRefGoogle Scholar
  44. 44.
    Sun Q, Yue P, Deiuliis JA et al (2009) Ambient air pollution exaggerates adipose inflammation and insulin resistance in a mouse model of diet-induced obesity. Circulation 119(4):538–546.  https://doi.org/10.1161/CIRCULATIONAHA.108.799015 CrossRefPubMedGoogle Scholar
  45. 45.
    Houstis NE, Rosen ED, Lander ES (2006) Reactive oxygen species play a causal role in multiple forms of insulin resistance. Nature 440(7086):944–948.  https://doi.org/10.1038/nature04634 CrossRefPubMedGoogle Scholar
  46. 46.
    Coogan PF, White LF, Yu J et al (2016) Long term exposure to NO2 and diabetes incidence in the Black Womenʼs Health Study. Environ Res 148:360–366.  https://doi.org/10.1016/j.envres.2016.04.021 CrossRefPubMedPubMedCentralGoogle Scholar
  47. 47.
    Münzel T, Gori T, Babisch W, Basner M (2014) Cardiovascular effects of environmental noise exposure. Eur Heart J 35(13):829–836.  https://doi.org/10.1093/eurheartj/ehu030 CrossRefPubMedPubMedCentralGoogle Scholar

Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2019

Authors and Affiliations

  • Xiang Qian Lao
    • 1
    Email author
  • Cui Guo
    • 1
  • Ly-yun Chang
    • 2
    • 3
  • Yacong Bo
    • 1
  • Zilong Zhang
    • 1
  • Yuan Chieh Chuang
    • 2
  • Wun Kai Jiang
    • 2
  • Changqing Lin
    • 4
    • 5
  • Tony Tam
    • 6
  • Alexis K. H. Lau
    • 4
    • 5
  • Chuan-Yao Lin
    • 7
  • Ta-Chien Chan
    • 8
  1. 1.Jockey Club School of Public Health and Primary CareThe Chinese University of Hong Kong, 421, 4/F School of Public Health, Prince of Wales HospitalSha TinHong Kong SAR, China
  2. 2.MJ Health Research Foundation, MJ GroupTaipeiTaiwan
  3. 3.Institute of SociologyAcademia SinicaTaipeiTaiwan
  4. 4.Division of Environment and SustainabilityThe Hong Kong University of Science and TechnologyKowloonHong Kong
  5. 5.Department of Civil and Environmental EngineeringThe Hong Kong University of Science and TechnologyKowloonHong Kong
  6. 6.Department of SociologyThe Chinese University of Hong KongMa Liu ShuiHong Kong
  7. 7.Research Center for Environmental ChangesAcademia SinicaTaipeiTaiwan
  8. 8.Research Center for Humanities and Social SciencesAcademia SinicaTaipeiTaiwan

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