Skip to main content

Advertisement

SpringerLink
Log in

Outdoor fine and coarse particles and hospital admissions for cardiovascular diseases: a large-scale case-crossover study

  • Published:
Air Quality, Atmosphere & Health Aims and scope Submit manuscript

Abstract

Despite high levels of air pollution in the Middle East, there are relatively few studies of its impacts on population health. In this study, associations between short-term exposure to PM2.5 and PM10-2.5 and hospitalization for cardiovascular diseases (CVDs) were evaluated in a study from Isfahan, Iran. In a bidirectional case-crossover design, patients who lived in Isfahan and were admitted with a CVD diagnosis in one of 15 hospitals between March 2010 and to March 2012 were included. Time-stratified conditional logistic regression with covariates of SO2 level, weekend/weekday, temperature, dew point, and wind speed was applied to quantify the odds ratio of CVD admission per interquartile range (IQR) increase in PM. Mean (IQR) concentrations of PM2.5 and PM10-2.5 were 60.1 (39.00–63.00) and 62.4 (37.88–93.00) µg/m3, respectively, with 25,541 CVD admissions. There were indications of small (1–2% per IQR) increases in risk of admissions that were robust to covariate adjustment with no discernable patterns for different lags. For both PM2.5 and PM10-2.5, there were indications of larger associations for female gender and younger ages. For PM2.5, much higher ORs were observed in summer (1.21 (0.95 CI: 1.12, 1.31)) and autumn (1.14 (1.07, 1.21)) for lag period 0–1; while the PM10-2.5 effect was most prominent in autumn (1.28 (1.22, 1.33)). Small increases in risk of CVD admission were associated with exposure to fine and coarse particle levels with high seasonal variability.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2

Similar content being viewed by others

References

  • Adar SD, Filigrana PA, Clements N, Peel JL (2014) Ambient coarse particulate matter and human health: a systematic review and meta-analysis. Current Environ Health Reports 1(3):258–274. https://doi.org/10.1007/s40572-014-0022-z

    Article  Google Scholar 

  • Al Hanai AH, Antkiewicz DS, Hemming JDC, Shafer MM, Lai AM, Arhami M, Schauer JJ (2019) Seasonal variations in the oxidative stress and inflammatory potential of PM2. 5 in Tehran using an alveolar macrophage model; the role of chemical composition and sources. Environ Int 123:417–427

    Article  CAS  Google Scholar 

  • Bell ML, Son J-Y, Peng RD, Wang Y, Dominici F (2015) Ambient PM2. 5 and risk of hospital admissions do risks differ for men and women? Epidemiol (Cambridge Mass) 26(4):575

    Article  Google Scholar 

  • Bell ML, Zanobetti A, Dominici F (2013) Evidence on vulnerability and susceptibility to health risks associated with short-term exposure to particulate matter: a systematic review and meta-analysis. Am J Epidemiol 178(6):865–876. https://doi.org/10.1093/aje/kwt090

    Article  Google Scholar 

  • Bowry ADK, Lewey J, Dugani SB, Choudhry NK (2015) The burden of cardiovascular disease in low- and middle-income countries: epidemiology and management. Can J Cardiol 31(9):1151–1159. https://doi.org/10.1016/j.cjca.2015.06.028

    Article  Google Scholar 

  • Brauer M, Freedman G, Frostad J, van Donkelaar A, Martin RV, Dentener F, Cohen A (2016) Ambient air pollution exposure estimation for the Global Burden of Disease 2013. Environ Sci Technol 50(1):79–88. https://doi.org/10.1021/acs.est.5b03709

    Article  CAS  Google Scholar 

  • Burroughs Peña MS, Rollins A (2017) Environmental exposures and cardiovascular disease: a challenge for health and development in low- and middle-income countries. Cardiol Clin 35(1):71–86. https://doi.org/10.1016/j.ccl.2016.09.001

    Article  Google Scholar 

  • Carracedo-Martínez E, Taracido M, Tobias A, Saez M, Figueiras A (2010) Case-crossover analysis of air pollution health effects: a systematic review of methodology and application. Environ Health Perspect 118(8):1173–1182. https://doi.org/10.1289/ehp.0901485

    Article  Google Scholar 

  • Chang C-C, Chen P-S, Yang C-Y (2015) Short-term effects of fine particulate air pollution on hospital admissions for cardiovascular diseases: a case-crossover study in a tropical city. J Toxicol Environ Health A 78(4):267–277. https://doi.org/10.1080/15287394.2014.960044

    Article  CAS  Google Scholar 

  • Chen D, Zhang F, Yu C, Jiao A, Xiang Q, Yu Y, Zhang Y (2019) Hourly associations between exposure to ambient particulate matter and emergency department visits in an urban population of Shenzhen. China. Atmospheric Environ 209((December 2018)):78–85. https://doi.org/10.1016/j.atmosenv.2019.04.021

    Article  CAS  Google Scholar 

  • Chen Y-C, Weng Y-H, Chiu Y-W, Yang C-Y (2015) Short-term effects of coarse particulate matter on hospital admissions for cardiovascular diseases: a case-crossover study in a tropical city. J Toxicol Environ Health A 78(19):1241–1253

    Article  CAS  Google Scholar 

  • Chiu H-F, Tsai S-S, Weng H-H, Yang C-Y (2013) Short-term effects of fine particulate air pollution on emergency room visits for cardiac arrhythmias: a case-crossover study in Taipei. J Toxicol Environ Health A 76(10):614–623. https://doi.org/10.1080/15287394.2013.801763

    Article  CAS  Google Scholar 

  • Cohen AJ, Brauer M, Burnett R, Anderson HR, Frostad J, Estep K, Forouzanfar MH (2017) Estimates and 25-year trends of the global burden of disease attributable to ambient air pollution: an analysis of data from the Global Burden of Diseases Study 2015. The Lancet 389(10082):1907–1918. https://doi.org/10.1016/S0140-6736(17)30505-6

    Article  Google Scholar 

  • Gaziano TA, Bitton A, Anand S, Abrahams-Gessel S, Murphy A (2010) Growing epidemic of coronary heart disease in low- and middle-income countries. Curr Probl Cardiol 35:72–115. https://doi.org/10.1016/j.cpcardiol.2009.10.002

    Article  Google Scholar 

  • Hadley MB, Vedanthan R, Fuster V (2018) Air pollution and cardiovascular disease: a window of opportunity. Nat Rev Cardiol 15(4):193–194. https://doi.org/10.1038/nrcardio.2017.207

    Article  Google Scholar 

  • He F, Shaffer ML, Rodriguez-colon S, Yanosky JD, Bixler E, Cascio WE (2011) Acute effects of fine particulate air pollution on cardiac arrhythmia: the APACR study. Environ Health Perspect 119(7):927–932. https://doi.org/10.1289/ehp.1002640

    Article  Google Scholar 

  • Hwang, S., Chi, M., Guo, S., Lin, Y., Chou, C., Lin, C. (2018). Seasonal variation and source apportionment of PM 2 . 5 -bound trace elements at a coastal area in southwestern Taiwan, 9101–9113.

  • Ito K, Mathes R, Ross Z, Nádas A, Thurston G, Matte T (2010) Fine particulate matter constituents associated with cardiovascular hospitalizations and mortality in New York City. Environ Health Perspect 119(4):467–473

    Article  Google Scholar 

  • Janes H, Sheppard L, Lumley T (2005) Case-crossover analyses of air pollution exposure data. Epidemiology 16(6):717–726. https://doi.org/10.1097/01.ede.0000181315.18836.9d

    Article  Google Scholar 

  • Kermani M, Goudarzi G, Shahsavani A, Dowlati M, Asl FB, Karimzadeh S, Tabibi R (2018) Estimation of short-term mortality and morbidity attributed to fine particulate matter in the ambient air of eight Iranian cities. Annals of Global Health 84(3):408–418. https://doi.org/10.29024/aogh.2308

    Article  Google Scholar 

  • Khazaei M, Darejeh M, Beigi AM, Fahiminia M (2016) Patterns of annual fluctuation of dust concentrations along with meteorological parameters : a case study in Qom province, central Iran. JAir Pollut Health 1(Spring):99–110

    Google Scholar 

  • Landrigan PJ, Fuller R, Acosta NJR, Adeyi O, Arnold R, Basu N(Nil), Zhong M (2018) The Lancet Commission on pollution and health. The Lancet 391(10119):462–512. https://doi.org/10.1016/S0140-6736(17)32345-0

    Article  Google Scholar 

  • Liang R, Zhang B, Zhao X, Ruan Y, Lian H, Fan Z (2014) Effect of exposure to PM2. 5 on blood pressure a systematic review and meta-analysis. J Hypertension 32(11):2130–2141

    Article  CAS  Google Scholar 

  • Lim SS, Vos T, Flaxman AD, Danaei G, Shibuya K, Adair-Rohani H, George S (2012) A comparative risk assessment of burden of disease and injury attributable to 67 risk factors and risk factor clusters in 21 regions, 1990–2010: a systematic analysis for the Global Burden of Disease Study 2010. The Lancet 380:2224–2260. https://doi.org/10.1016/S0140-6736(12)61766-8

    Article  Google Scholar 

  • Luo C, Zhu X, Yao C, Hou L, Zhang J, Cao J, Wang A (2015) Short-term exposure to particulate air pollution and risk of myocardial infarction: a systematic review and meta-analysis. Environ Sci Pollut Res 22(19):14651–14662

    Article  CAS  Google Scholar 

  • Ma Y, Zhang H, Zhao Y, Zhou J, Yang S (2017) Short-term effects of air pollution on daily hospital admissions for cardiovascular diseases in western China. Environ Sci Pollut Res 24:14071–14079. https://doi.org/10.1007/s11356-017-8971-z

    Article  CAS  Google Scholar 

  • Marzouni MB, Moradi M, Zarasvandi A, Akbaripoor S, Hassanvand MS, Neisi A, Barari K (2017) Health benefits of PM10 reduction in Iran. Int J Biometeorol. https://doi.org/10.1007/s00484-017-1316-2

    Article  Google Scholar 

  • Newell K, Kartsonaki C, Bong K, Lam H, Kurmi OP (2017) Cardiorespiratory health effects of particulate ambient air pollution exposure in low-income and middle-income countries : a systematic review and meta-analysis. The Lancet Planetary Health 1(9):e368–e380. https://doi.org/10.1016/S2542-5196(17)30166-3

    Article  Google Scholar 

  • Nuvolone D, Balzi D, Chini M, Scala D, Giovannini F, Barchielli A (2011) Short-term association between ambient air pollution and risk of hospitalization for acute myocardial infarction: results of the cardiovascular risk and air pollution in Tuscany (RISCAT) study. Am J Epidemiol 174(1):63–71

    Article  Google Scholar 

  • Rabiei K, Hosseini SM, Sadeghi E, Jafari-Koshki T, Rahimi M, Shishehforoush M, Mohebi MB (2017) Air pollution and cardiovascular and respiratory disease: rationale and methodology of CAPACITY study. ARYA Atherosclerosis 13(6):264

    Google Scholar 

  • Rubin, DB. (2004). Multiple imputation for nonresponse in surveys (Vol. 81). John Wiley & Sons.

  • Shah ASV, Langrish JP, Nair H, Mcallister DA, Hunter AL, Donaldson K, Mills NL (2013) Global association of air pollution and heart failure a systematic review and meta analysis. The Lancet 382:21. https://doi.org/10.1016/S0140-6736(13)60898-3

    Article  CAS  Google Scholar 

  • Shah ASV, Lee KK, McAllister DA, Hunter A, Nair H, Whiteley W, Mills NL (2015) Short term exposure to air pollution and stroke: systematic review and meta-analysis. The BMJ 350:h1295. https://doi.org/10.1136/BMJ.H1295

    Article  Google Scholar 

  • Shin HH, Fann N, Burnett RT, Cohen A, Hubbell BJ (2014) Outdoor fine particles and nonfatal strokes: systematic review and meta-analysis. Epidemiology Cambridge, Mass 25(6):835

    Article  Google Scholar 

  • Sicard, P., Khaniabadi, YO., Perez, S., Gualtieri, M., Marco, A. De. (2019). Effect of O3 , PM10 and PM2.5 on cardiovascular and respiratory diseases in cities of France , Iran and Italy, 32645–32665.

  • Soleimani Z, Teymouri P, Darvishi A, Mesdaghinia A, Middleton N, Griffin DW (2020) An overview of bioaerosol load and health impacts associated with dust storms : a focus on the Middle East. Atmospheric Environ 223((July2019)):117187. https://doi.org/10.1016/j.atmosenv.2019.117187

    Article  CAS  Google Scholar 

  • Song X, Liu Y, Hu Y, Zhao X, Tian J, Ding G, Wang S (2016) Short-term exposure to air pollution and cardiac arrhythmia: a meta-analysis and systematic review. Int J Environ Res Public Health 13(7):642. https://doi.org/10.3390/ijerph13070642

    Article  CAS  Google Scholar 

  • Su C, Breitner S, Schneider A, Liu L, Franck U, Peters A, Pan X (2016) Short-term effects of fine particulate air pollution on cardiovascular hospital emergency room visits: a time-series study in Beijing, China. Int Arch Occup Environ Health 89(4):641–657. https://doi.org/10.1007/s00420-015-1102-6

    Article  CAS  Google Scholar 

  • Talebi, SM., Tavakoli-Ghinani, T. (2008). Levels of PM10 and its chemical composition in the atmosphere of the city of Isfahan. Iranian Journal of Chemical Engineering(IJChE), 5(3), 62–67. Retrieved from http://www.ijche.com/article_15184.html

  • Tsiouri V, Kakosimos KE, Kumar P (2015) Concentrations, sources and exposure risks associated with particulate matter in the Middle East Area—a review. Air Qual Atmos Health 8:67–80. https://doi.org/10.1007/s11869-014-0277-4

    Article  CAS  Google Scholar 

  • Wang Y, Eliot MN, Wellenius GA (2014) Short-term changes in ambient particulate matter and risk of stroke: a systematic review and meta-analysis. J Am Heart Assoc 3(4):1–22. https://doi.org/10.1161/JAHA.114.000983

    Article  Google Scholar 

  • Zanobetti A, Schwartz J (2005) The effect of particulate air pollution on emergency admissions for myocardial infarction: a multicity case-crossover analysis. Environ Health Perspect 113(8):978–982. https://doi.org/10.1289/EHP.7550

    Article  Google Scholar 

Download references

Funding

This study was financially supported by the Crisis Management Office of Isfahan Provincial Governor, and Isfahan’s Department of Environment (grant number 90/7588).

Author information

Authors and Affiliations

  1. Department of Community Medicine, Tehran University of Medical Sciences, Tehran, Iran

    Mojgan Karbakhsh

  2. Department of Epidemiology and Biostatistics, School of Public Health, Isfahan University of Medical Sciences, Isfahan, Iran

    Marjan Mansourian

  3. Interventional Cardiology Research Center, Cardiovascular Research Institute, Isfahan University of Medical Sciences,, Isfahan, Iran

    Marzieh Taheri

  4. Isfahan Cardiovascular Research Center , Cardiovascular Research Institute, Isfahan University of Medical Sciences, Isfahan, Iran

    Katayoun Rabiei & Nizal Sarrafzadegan

  5. Department of Biostatistics and Epidemiology, School of Public Health, Isfahan University of Medical Sciences, Isfahan, Iran

    Sayed Mohsen Hosseini

  6. Department of Anesthesiology, School of Medicine, Isfahan University of Medical Sciences, Isfahan, Iran

    Mojtaba Rahimi

  7. Central Laboratory and Air Pollution Monitoring, Isfahan Province Environmental Monitoring Center, Isfahan Department of Environment, Isfahan, Iran

    Babak Sadeghian

  8. Cardiac Rehabilitation & Prevention, Faculty of Medicine, University of British Columbia, Vancouver, BC, Canada

    Sammy Chan

  9. School of Population and Public Health, Faculty of Medicine, University of British Columbia, Vancouver, BC, Canada

    Nizal Sarrafzadegan

  10. Faculty of Medicine, School of Population and Public Health, The University of British Columbia, Vancouver, BC, Canada

    Michael Brauer

  11. Pediatric Cardiovascular Research Center, Cardiovascular Research Institute, Isfahan University of Medical Sciences, Isfahan, Iran

    Marjan Mansourian

Authors
  1. Mojgan Karbakhsh
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Marjan Mansourian
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Marzieh Taheri
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Katayoun Rabiei
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Sayed Mohsen Hosseini
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Mojtaba Rahimi
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Babak Sadeghian
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. Sammy Chan
    View author publications

    You can also search for this author in PubMed Google Scholar

  9. Nizal Sarrafzadegan
    View author publications

    You can also search for this author in PubMed Google Scholar

  10. Michael Brauer
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Nizal Sarrafzadegan.

Additional information

Publisher's note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Appendices

Appendix 1 Time series plot of PM2.5 and PM10-2.5

figure a

Appendix 2 Correlation matrix of PM and SO2 levels and meteorological variables

Season

PM10

PM2.5

PM10-2.5

SO2

Temperature

Dew point

Wind Speed

Spring

PM10

r *

 

.692

.936

 − .086

.305

.153

.182

p value

 

 < 0.001

 < 0.001

.241

 < 0.001

.037

.013

PM2.5

r *

.692

 

.393

.075

.170

 − .199

.211

p value

 < 0.001

 

 < 0.001

.475

.104

.056

.042

PM10-2.5

r *

.936

.393

 

.234

.297

.245

.307

p value

.000

.000

 

.024

.004

.018

.003

SO2

r *

 − .086

.075

.234

 

.318

 − .148

 − .008

p value

.241

.475

.024

 

 < 0.001

.043

.918

Summer

PM10

r *

 

.652

.962

.256

.084

 − .011

.154

p value

 

 < 0.001

 < 0.001

 < 0.001

.257

.882

.035

PM2.5

r *

.652

 

.420

.520

.375

.174

.299

p value

 < 0.001

 

 < 0.001

 < 0.001

 < 0.001

.096

.004

PM10-2.5

r *

.962

.420

 

.401

.210

.214

.242

p value

 < 0.001

 < 0.001

 

 < 0.001

.044

.039

.020

SO2

r *

.256

.520

.401

 

.436

 − .065

.158

p value

 < 0.001

 < 0.001

 < 0.001

 

 < 0.001

.379

.031

Autumn

PM10

r *

 

.703

.915

 − .106

 − .182

 − .492

 − .240

p value

 

 < 0.001

 < 0.001

.155

.014

 < 0.001

.001

PM2.5

r *

.703

 

.355

.294

 − .292

 − .329

 − .297

p value

 < 0.001

 

.001

.005

.005

.002

.004

PM10-2.5

r *

.915

.355

 

.052

 − .014

 − .313

.022

p value

 < 0.001

.001

 

.625

.899

.003

.838

SO2

r *

 − .106

.294

.052

 

 − .432

 − .077

 − .125

p value

.155

.005

.625

 

 < 0.001

.307

.096

Winter

PM10

r *

 

.485

.901

 − .201

.057

 − .098

 − .095

p value

 

 < 0.001

 < 0.001

.007

.450

.193

.209

PM2.5

r *

.485

 

.058

 − .266

.132

.320

.027

p value

 < 0.001

 

.592

.012

.217

.002

.804

PM10-2.5

r *

.901

.058

 

 − .071

.396

.116

.325

p value

 < 0.001

.592

 

.507

 < 0.001

.277

.002

SO2

r *

 − .201

 − .266

 − .071

 

.152

 − .089

.299

p value

.007

.012

.507

 

.043

.240

 < 0.001

Total

PM10

r *

 

.629

.914

 − .029

.067

 − .028

 − .098

p value

 

 < 0.001

 < 0.001

.437

.069

.442

.008

PM2.5

r *

.629

 

.260

.123

.158

.210

 − .124

p value

 < 0.001

 

 < 0.001

.018

.002

 < 0.001

.018

PM10-2.5

r *

.914

.260

 

.137

.044

.041

.204

p value

 < 0.001

 < 0.001

 

.009

.399

.433

 < 0.001

SO2

r *

 − .029

.123

.137

 

 − .318

 − .191

 − .043

p value

.437

.018

.009

 

 < 0.001

 < 0.001

.241

  1. * Pearson correlation coefficient

Appendix 3 Quartiles of PM2.5, PM10-2.5, and PM10 during the study period (µg/m.3)

 

Quartiles

PM2.5

PM10

PM10-2.5

Overall

Q1

8.00–39.00

38.46–99.47

0.12–37.88

Q2

39.00–51.00

99.47–150.16

37.88–62.00

Q3

51.00–62.00

150.16–170.43

62.00–93.00

Q4

62.00–130.00

170.43–349.06

93.00–227

Spring

Q1

23.06–32.00

44.67–106.59

10.86–57.41

Q2

32.00–43.00

106.59–143.48

57.41–72.67

Q3

43.00–54.00

143.48–166.22

72.67–100.5

Q4

54.00–100.07

166.22–263.03

100.5–177.00

Summer

Q1

32.14–49.00

57.33–69.62

0.12–30.17

Q2

49.00–57.00

96.62–157.65

30.17–43.33

Q3

57.00–66.04

157.65–170.37

43.33–79.79

Q4

66.04–111.00

170.37–324.00

79.79–227.00

Autumn

Q1

13.09–50.00

57.50–126.83

3.33–45.93

Q2

50.00–55.50

126.83–166.92

45.93–74.5

Q3

55.50–68.25

166.92–182.17

74.5–104.17

Q4

69.25–130.00

182.17–349.06

10.17–178.33

Winter

Q1

8.00–26.00

38.46–75.27

2.05–33.62

Q2

26.00–40.33

75.27–123.59

33.62–50.00

Q3

40.33–52.99

123.59–155.60

50.00–82.11

Q4

52.99–96.05

155.60–267.39

82.11–161.02

Appendix 4 Crude and adjusted odds ratios for an IQR increase in PM2.5 and PM10-2.5 for lag period 0-1 stratified by diagnostic categories

Diagnosis category

PM2.5

PM10-2.5

Crude OR (95%CI)

Adjusted OR* (95%CI)

Adjusted OR (0.95 CI)

Crude OR (95%CI)

Adjusted OR* (95%CI)

Adjusted OR (0.95 CI)

Hypertensive heart disease (I10–I15)

1.01 (0.94–1.08)

1.00 (0.93–1.08)

0.99 (0.93, 1.08)

1.03 (0.98–1.09)

1.03 (0.97–1.09)

1.02 (0.96, 1.08)

Ischemic heart diseases (I20–I25)

1.00 (0.97–1.04)

1.00 (0.96–1.04)

1.01 (0.98, 1.05)

1.02 (0.99–1.05)

1.01 (0.98–1.04)

1.02 (0.99, 1.05)

Conduction disorders and blocks (I44–I45)

0.99 (0.79–1.27)

0.98 (0.77–1.26)

0.99 (0.77, 1.29)

1.05 (0.85–1.29)

1.04 (0.84–1.29)

1.01 (0.82, 1.26)

Cardiac arrest (I46)

1.12 (0.93–1.34)

1.12 (0.93–1.35)

1.09 (0.90, 1.32)

1.03 (0.89–1.19)

1.01 (0.87–1.17)

1.04 (0.89, 1.22)

Arrhythmias (I47–I49)

1.01 (0.89–1.13)

0.98 (0.87–1.11)

1.02 (0.89, 1.16)

1.06 (0.97–1.16)

1.03 (0.94–1.13)

1.07 (0.96, 1.17)

Heart failure (I50)

1.08 (0.97–1.20)

1.08 (0.97–1.21)

1.06 (0.94, 1.18)

0.98 (0.89–1.07)

0.97 (0.89–1.07)

1.02 (0.93, 1.12)

Cerebrovascular diseases (I60–I69)

0.97 (0.89–1.05)

0.97 (0.89–1.06)

1.02 (0.94, 1.11)

1.03 (0.96–1.10)

1.03 (0.96–1.10)

1.04 (0.97, 1.11)

Other and unspecified disorders of circulatory system (I99)

1.03 (0.95–1.12)

1.03 (0.95–1.12)

1.05 (0.97, 1.15)

1.08 (1.01–1.16)

1.07 (0.99–1.14)

1.07 (1.00, 1.15)

  1. *Adjusted for daily temperature, dew point, if the case day was a weekday or not, and wind speed
  2. ¶Adjusted for SO2 level, daily temperature, dew point, if the case day was a weekday or not, and wind speed

Appendix 5 Crude and adjusted odds ratios for an IQR increase in PM10 in relation to all cardiovascular diseases for lag period 0-1, stratified by gender, age groups, and season

Overall disease

PM10

Crude OR (0.95 CI)

Adjusted OR* (0.95 CI)

Adjusted OR (0.95 CI)

Gender

Female

1.08 (1.05–1.11)

1.08 (1.05–1.11)

1.04 (1.01, 1.07)

Male

1.04 (1.01–1.07)

1.03 (1.01–1.06)

1.02 (0.99, 1.04)

Age group

 < 35

1.08 (1.02–1.14)

1.07 (1.01–1.13)

1.02 (0.97, 1.07)

35–64

1.06 (1.03–1.10)

1.06 (1.03–1.10)

1.03 (1.00, 1.06)

 ≥ 65

1.06 (1.03–1.10)

1.06 (1.03–1.10)

1.03 (1.00, 1.06)

Season

Spring

0.93 (0.90, 0.96)

0.91 (0.88, 0.94)

0.89 (0.86, 0.93)

Summer

1.03 (0.99, 1.08)

1.04 (1.00, 1.09)

1.16 (1.11, 1.21)

Autumn

1.23 (1.19, 1.27)

1.25 (1.21, 1.29)

1.19 (1.14, 1.23)

Winter

1.03 (0.99, 1.07)

1.06 (1.02, 1.10)

1.08 (1.04, 1.13)

  1. *Adjusted for daily temperature, dew point, if the case day was a weekday or not, and wind speed
  2. Adjusted for SO2 level, daily temperature, dew point, if the case day was a weekday or not, and wind speed

Appendix 6 Crude and adjusted odds ratios for an IQR increase in PM10 for lag period 0-1 stratified by diagnostic categories

Diagnosis category

PM10

Crude OR (95%CI)

Adjusted OR* (95%CI)

Adjusted OR (0.95 CI)

Hypertensive heart disease (I10–I15)

1.04 (0.99, 1.10)

1.04 (0.98, 1.10)

1.01 (0.96, 1.06)

Ischemic heart diseases (I20–I25)

1.07 (1.03, 1.09)

1.05 (1.02, 1.08)

1.02 (0.99, 1.05)

Conduction disorders and blocks(I44-I45)

1.11 (0.94, 1.33)

1.12 (0.94, 1.34)

1.11 (0.94, 1.32)

Cardiac arrest (I46)

1.01 (0.90, 1.16)

1.02 (0.90, 1.16)

1.01 (0.89, 1.15)

Arrhythmias (I47–I49)

1.08 (0.98, 1.16)

1.07 (0.98, 1.17)

1.09 (1.00, 1.18)

Heart failure (I50)

1.06 (0.98, 1.14)

1.06 (0.98, 1.15)

1.04 (0.96, 1.12)

Cerebrovascular diseases (I60–I69)

1.05 (0.99, 1.12)

1.05 (0.99, 1.12)

1.03 (0.98, 1.09)

Other and unspecified disorders of circulatory system (I99)

1.05 (0.99, 1.12)

1.06 (0.99, 1.12)

1.03 (0.98, 1.09)

  1. *Adjusted for daily temperature, dew point, if the case day was a weekday or not, and wind speed
  2. ¶Adjusted for SO2 level, daily temperature, dew point, if the case day was a weekday or not, and wind speed

Appendix 7 Crude and adjusted odds ratios for an IQR increase in PM2.5 and PM10-2.5 for lag period 0-1 based on gender and age groups in autumn

Overall disease

PM10

Crude OR (95%CI)

Adjusted OR* (95%CI)

Adjusted OR (0.95 CI)

Gender

Female

1.22 (1.16, 1.28)

1.25 (1.19, 1.31)

1.23 (1.16, 1.29)

Male

1.17 (1.11, 1.23)

1.19 (1.13, 1.25)

1.15 (1.09, 1.21)

Age group

 < 35

1.16 (1.04, 1.29)

1.18 (1.05, 1.33)

1.15 (1.02, 1.29)

35–64

1.18 (1.12, 1.24)

1.21 (1.15, 1.27)

1.18 (1.12, 1.25)

 ≥ 65

1.21 (1.15, 1.28)

1.24 (1.17, 1.31)

1.21 (1.14, 1.28)

  1. *Adjusted for daily temperature, dew point, if the case day was a weekday or not, and wind speed
  2. ¶Adjusted for SO2 level, daily temperature, dew point, if the case day was a weekday or not, and wind speed

Appendix 8 Crude and adjusted odds rations for an IQR increase in PM2.5 and PM10-2.5 stratified by diagnostic categories for lag period 0-1 in autumn

Diagnosis category

PM2.5

PM10-2.5

Crude OR (95%CI)

Adjusted OR* (95%CI)

Adjusted OR (0.95 CI)

Crude OR (95%CI)

Adjusted OR* (95%CI)

Adjusted OR (0.95 CI)

Hypertensive heart disease (I10–I15)

1.07 (0.92, 1.23)

1.24 (1.13, 1.37)

1.11 (0.96, 1.29)

1.12 (0.97, 1.29)

1.29 (1.16, 1.42)

1.25 (1.13, 1.39)

Ischemic heart diseases (I20–I25)

1.17 (1.08, 1.26)

1.29 (1.22, 1.36)

1.17 (1.07, 1.27)

1.21 (1.12, 1.31)

1.31 (1.23, 1.38)

1.27 (1.20, 1.35)

Conduction disorders and blocks (I44–I45)

1.19 (0.71, 1.99)

1.45 (0.99, 2.12)

1.06 (0.61, 1.87)

1.16 (0.66, 2.01)

1.64 (1.09, 2.47)

1.58 (1.08, 2.30)

Cardiac arrest (I46)

1.85 (1.15, 2.99)

1.37 (1.02, 1.84)

1.71 (1.05, 2.79)

1.69 (1.05, 2.73)

1.30 (0.94, 1.79)

1.39 (0.97, 1.98)

Arrhythmias (I47–I49)

1.03 (0.79, 1.34)

1.19 (0.99, 1.43)

1.09 (0.83, 1.44)

1.14 (0.88, 1.49)

1.21 (1.00, 1.45)

1.24 (1.03, 1.51)

Heart failure (I50)

1.36 (1.03, 1.79)

1.15 (0.95, 1.38)

1.12 (0.84, 1.49)

1.47 (1.11, 1.94)

1.19 (0.99, 1.45)

1.22 (0.99, 1.49)

Cerebrovascular diseases (I60–I69)

1.01 (0.85, 1.21)

1.19 (1.06, 1.35)

1.07 (0.89, 1.28)

1.05 (0.87, 1.25)

1.23 (1.09, 1.40)

1.26 (1.11, 1.44)

Other and unspecified disorders of circulatory system (I99)

0.98 (0.83, 1.16)

1.37 (1.21, 1.55)

1.01 (0.85, 1.21)

1.01 (0.85, 1.19)

1.39 (1.23, 1.59)

1.34 (1.18, 1.53)

  1. *Adjusted for daily temperature, dew point, if the case day was a weekday or not, and wind speed
  2. ¶Adjusted for SO2 level, daily temperature, dew point, if the case day was a weekday or not, and wind speed

Appendix 9 Crude and adjusted odds ratios for an IQR increase in PM10 for lag period 0-1 based on gender and age groups in autumn

Overall disease

PM2.5

PM10-2.5

Crude OR (95%CI)

Adjusted OR* (95%CI)

Adjusted OR (0.95 CI)

Crude OR (95%CI)

Adjusted OR* (95%CI)

Adjusted OR (0.95 CI)

Gender

Female

1.13 (1.05, 1.23)

1.19 (1.09, 1.29)

1.13 (1.03, 1.23)

1.33 (1.26, 1.41)

1.37 (1.29, 1.45)

1.34 (1.27, 1.42)

Male

1.11 (1.03, 1.20)

1.16 (1.08, 1.26)

1.15 (1.05, 1.25)

1.21 (1.15, 1.28)

1.25 (1.18, 1.32)

1.21 (1.14, 1.29)

Age group

 < 35

1.32 (1.10, 1.58)

1.33 (1.10, 1.59)

1.20 (0.99, 1.45)

1.23 (1.09, 1.39)

1.23 (1.08, 1.39)

1.24 (1.09, 1.41)

35–64

1.11 (1.03, 1.21)

1.18 (1.09, 1.29)

1.14 (1.05, 1.25)

1.26 (1.19, 1.33)

1.30 (1.23, 1.38)

1.26 (1.19, 1.34)

 ≥ 65

1.09 (1.00, 1.19)

1.14 (1.05, 1.24)

1.11 (1.02, 1.22)

1.30 (1.22, 1.38)

1.33 (1.25, 1.41)

1.30 (1.22, 1.39)

  1. * Adjusted for daily temperature, dew point, if the case day was a weekday or not, and wind speed
  2. ¶ Adjusted for SO2 level, daily temperature, dew point, if the case day was a weekday or not, and wind speed

Appendix 10 Crude and adjusted odds rations for an IQR increase in PM10 stratified by diagnostic categories for lag period 0-1 in autumn

Diagnosis category

PM10

Crude OR (95%CI)

Adjusted OR* (95%CI)

Adjusted OR (95%CI)

Hypertensive heart disease (I10–I15)

1.17 (1.08, 1.28)

1.18 (1.08, 1.29)

1.09 (0.98, 1.19)

Ischemic heart diseases (I20–I25)

1.24 (1.18, 1.30)

1.25 (1.19, 1.31)

1.20 (1.14, 1.26)

Conduction disorders and blocks (I44–I45)

1.45 (1.03, 2.03)

1.46 (1.03, 2.07)

1.51 (1.08, 2.09)

Cardiac arrest (I46)

1.57 (1.22, 2.02)

1.51 (1.15, 1.99)

1.45 (1.09, 1.94)

Arrhythmias (I47–I49)

1.17 (0.99, 1.36)

1.17 (0.99, 1.38)

1.11 (0.93, 1.31)

Heart failure (I50)

1.21 (1.04, 1.43)

1.22 (1.04, 1.43)

1.12 (0.93, 1.34)

Cerebrovascular diseases (I60–I69)

1.21 (1.09, 1.35)

1.22(1.09,1.36)

1.23(1.09,1.38)

Other and unspecified disorders of circulatory system (I99)

1.23 (1.10, 1.38)

1.25 (1.11, 1.39)

1.23 (1.09, 1.38)

  1. *Adjusted for daily temperature, dew point, if the case day was a weekday or not, and wind speed
  2. ¶Adjusted for SO2 level, daily temperature, dew point, if the case day was a weekday or not, and wind speed

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Karbakhsh, M., Mansourian, M., Taheri, M. et al. Outdoor fine and coarse particles and hospital admissions for cardiovascular diseases: a large-scale case-crossover study. Air Qual Atmos Health 15, 1679–1693 (2022). https://doi.org/10.1007/s11869-022-01212-0

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11869-022-01212-0

Keywords

Search

Navigation