Advertisement

International Journal of Public Health

, Volume 62, Issue 7, pp 775–786 | Cite as

Impact of preventable risk factors on stroke in the EPICOR study: does gender matter?

  • Slavica Trajkova
  • Angelo d’Errico
  • Fulvio Ricceri
  • Francesca Fasanelli
  • Valeria Pala
  • Claudia Agnoli
  • Rosario Tumino
  • Graziella Frasca
  • Giovanna Masala
  • Calogero Saieva
  • Paolo Chiodini
  • Amalia Mattiello
  • Carlotta SacerdoteEmail author
  • Salvatore Panico
Original Article

Abstract

Objectives

The effect of modifiable stroke risk factors in terms of prevented cases remains unclear due to sex-specific disease rate and risk factors prevalence. Our aim was to estimate their impact on stroke by gender through population-attributable fraction (PAF), preventive fraction (PF) and their combination in EPIC-Italian cohort.

Methods

43,976 participants, age 34–75, and free of cardiovascular disease at baseline (1993–1998) were followed up for almost 11 years. Adjusted hazard ratios and PAF were estimated using Cox models.

Results

We identified 386 cases. In males, the burden for stroke was 17% (95% CI 4–28%) for smoking and 14% (95% CI 5–22%) for alcohol consumption. In females, hypertension was carrying the biggest burden with 18% (95% CI 9–26%) followed by smoking 15% (95% CI 7–22%). Their combination was 46% (95% CI 32–58%) in males and 48% (95% CI 35–59%) in females. PF for current smokers was gender unequal [males 21% (95% CI 15–27%) females 9% (95% CI 1–17%)].

Conclusions

Half of strokes are attributable to potentially modifiable factors. The proportion of prevented cases is gender unbalanced, encouraging sex-specific intervention.

Keywords

Stroke Gender medicine Risk factors Cohort study Population-attributable fraction Preventive fraction 

Notes

Acknowledgements

EPICOR is supported by Compagnia di San Paolo. The Italian EPIC collaboration is supported by the Italian Association for Cancer Research (AIRC). The founders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Compliance with ethical standards

Conflict of interest

Authors have no conflicts of interest in connection with the paper.

Informed consent

All participants gave written informed consent, and the study was approved by the local ethics committees in the participating countries and the ethical review board of the International Agency for Research on Cancer (IARC).

Supplementary material

38_2017_993_MOESM1_ESM.docx (24 kb)
Supplementary material 1 (DOCX 23 kb)

References

  1. Abramson BL, Melvin RG (2014) Cardiovascular risk in women: focus on hypertension. Can J Cardiol 30:553–559. doi: 10.1016/j.cjca.2014.02.014 CrossRefPubMedGoogle Scholar
  2. Agnoli C, Krogh V, Grioni S et al (2011) A priori-defined dietary patterns are associated with reduced risk of stroke in a large italian cohort. J Nutr 141:1552–1558. doi: 10.3945/jn.111.140061.In CrossRefPubMedGoogle Scholar
  3. Aschengrau A, Seage GR (2014) Essentials of epidemiology in public health, 3rd edn. Jones and Bartlett Learning, BurlingtonGoogle Scholar
  4. Asplund K, Tuomilehto J, Stegmayr B et al (1988) Diagnostic criteria and quality control of the registration of stroke events in the MONICA project. Acta Med Scand Suppl 728:26–39PubMedGoogle Scholar
  5. Di Carlo A, Lamassa M, Baldereschi M et al (2003) Sex differences in the clinical presentation, resource use, and 3-month outcome of acute stroke in Europe data from a multicenter multinational hospital-based registry. Stroke 34:1114–1119. doi: 10.1161/01.STR.0000068410.07397.D7 CrossRefPubMedGoogle Scholar
  6. Diep L, Kwagyan J, Kurantsin-Mills J et al (2010) Association of physical activity level and stroke outcomes in men and women: a meta-analysis. J Women’s Heal 19:1815–1822. doi: 10.1089/jwh.2009.1708 CrossRefGoogle Scholar
  7. Feigin VL, Roth GA, Naghavi M et al (2016) Global burden of stroke and risk factors in 188 countries, during 1990–2013: a systematic analysis for the Global Burden of Disease Study 2013. Lancet Glob Heal 4422:1–12. doi: 10.1016/S1474-4422(16)30073-4 CrossRefGoogle Scholar
  8. Geer EB, Shen W (2009) Gender differences in insulin resistance, body composition, and energy balance. Gend Med 6:60–75. doi: 10.1016/j.genm.2009.02.002 CrossRefPubMedPubMedCentralGoogle Scholar
  9. Giralt D, Domingues-Montanari S, Mendioroz M et al (2012) The gender gap in stroke: a meta-analysis. Acta Neurol Scand 125:83–90. doi: 10.1111/j.1600-0404.2011.01514.x CrossRefPubMedGoogle Scholar
  10. Glader E, Stegmayr B, Norrving B et al (2003) Sex differences in management and outcome after stroke. Stroke 34:1970–1975. doi: 10.1161/01.STR.0000083534.81284.C5 CrossRefPubMedGoogle Scholar
  11. Goldstein LB, Bushnell CD, Adams RJ et al (2011) Guidelines for the primary prevention of stroke: a guideline for healthcare professionals from the American Heart Association/American Stroke Association. Stroke 42:517–584. doi: 10.1161/STR.0b013e3181fcb238 CrossRefPubMedGoogle Scholar
  12. Greenland S, Drescher K (1993) Maximum likelihood estimation of the attributable fraction from logistic models. Biometrics 49:865–872CrossRefGoogle Scholar
  13. Haast RAM, Gustafson DR, Kiliaan AJ (2012) Sex differences in stroke. J Cereb Blood Flow Metab 32:2100–2107. doi: 10.1038/jcbfm.2012.141 CrossRefPubMedPubMedCentralGoogle Scholar
  14. Hildebrandt M, Bender R, Gehrmann U, Blettner M (2006) Calculating confidence intervals for impact numbers. BMC Med Res Methodol 6:32. doi: 10.1186/1471-2288-6-32 CrossRefPubMedPubMedCentralGoogle Scholar
  15. Jamc C, Pilote L, Dasgupta K et al (2007) A comprehensive view of sex-specific issues related to cardiovascular disease. Can Med Assoc J 176:S1–S44. doi: 10.1503/cmaj.051455 CrossRefGoogle Scholar
  16. Kaaks R, Slimani N, Riboli E (1997) Pilot phase studies on the accuracy of dietary intake measurements in the EPIC project: overall evaluation of results. Int J Epidemiol 26:26–36. doi: 10.1093/ije/26.suppl_1.S26 CrossRefGoogle Scholar
  17. Lim SS, Vos T, Flaxman AD et al (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. Lancet 380:2224–2260. doi: 10.1016/S0140-6736(12)61766-8 CrossRefPubMedPubMedCentralGoogle Scholar
  18. Lozano R, Naghavi M, Foreman K et al (2012) Global and regional mortality from 235 causes of death for 20 age groups in 1990 and 2010: a systematic analysis for the Global Burden of Disease Study 2010. Lancet 380:2095–2128. doi: 10.1016/S0140-6736(12)61728-0 CrossRefPubMedGoogle Scholar
  19. Matsumoto C, Miedema MD, Ofman P et al (2014) An expanding knowledge of the mechanisms and effects of alcohol consumption on cardiovascular disease. J Cardiopulm Rehabil Prev 34:159–171. doi: 10.1097/HCR.0000000000000042 CrossRefPubMedGoogle Scholar
  20. McCullough LD, Hurn PD (2003) Estrogen and ischemic neuroprotection: an integrated view. Trends Endocrinol Metab 14:228–235. doi: 10.1016/S1043-2760(03)00076-6 CrossRefPubMedGoogle Scholar
  21. Mostofsky E, Mukamal KJ, Giovannucci EL et al (2016) Key findings on alcohol consumption and a variety of health outcomes From the Nurses’ Health Study. Am J Public Heal 106:1586–1591. doi: 10.2105/AJPH.2016.303336 CrossRefGoogle Scholar
  22. Musha H, Hayashi A, Kida K et al (2006) Gender difference in the level of high-density lipoprotein cholesterol in elderly Japanese patients with coronary artery disease. Intern Med 45:241–245. doi: 10.2169/internalmedicine.45.1528 CrossRefPubMedGoogle Scholar
  23. Newson R (2012) Scenario comparisons: How much good can we do? National Heart and Lung Institute, Imperial College London 18th UK Stata Users’ Group MeetingGoogle Scholar
  24. Newson R (2013) Attributable and unattributable risks and fractions and other scenario comparisons. Stata J 13:672–698CrossRefGoogle Scholar
  25. Newson R (2015) PUNAFCC: Stata module to compute population attributable fractions for case-control and survival studies. In: Stat. Softw. Components. https://ideas.repec.org/c/boc/bocode/s457354.html. Accessed 4 May 2017
  26. O’Donnell MJ, Xavier D, Liu L et al (2010) Risk factors for ischaemic and intracerebral haemorrhagic stroke in 22 countries (the INTERSTROKE study): a case-control study. Lancet 376:112–123. doi: 10.1016/S0140-6736(10)60834-3 CrossRefPubMedGoogle Scholar
  27. O’Donnell MJ, Chin SL, Rangarajan S et al (2016) Global and regional effects of potentially modifiable risk factors associated with acute stroke in 32 countries (INTERSTROKE): a case-control study. Lancet 388:761–775. doi: 10.1016/S0140-6736(16)30506-2 CrossRefPubMedGoogle Scholar
  28. Palli D, Berrino F, Vineis P et al (2003) A molecular epidemiology project on diet and cancer: the EPIC-Italy Prospective Study. Design and baseline characteristics of participants. Tumori 89:586–593CrossRefGoogle Scholar
  29. Patra J, Taylor B, Irving H et al (2010) Alcohol consumption and the risk of morbidity and mortality for different stroke types—a systematic review and meta-analysis. BMC Public Health 10:258. doi: 10.1186/1471-2458-10-258 CrossRefPubMedPubMedCentralGoogle Scholar
  30. Peters SAE, Huxley RR, Woodward M (2013) Smoking as a risk factor for stroke in women compared with men: a systematic review and meta-analysis of 81 cohorts, including 3,980,359 individuals and 42,401 strokes. Stroke 44:2821–2829. doi: 10.1161/STROKEAHA.113.002342 CrossRefPubMedGoogle Scholar
  31. Peters SAE, Huxley RR, Woodward M (2014) Diabetes as a risk factor for stroke in women compared with men: a systematic review and meta-analysis of 64 cohorts, including 775 385 individuals and 12 539 strokes. Lancet 383:1973–1980. doi: 10.1016/S0140-6736(14)60040-4 CrossRefPubMedGoogle Scholar
  32. Poorthuis MHF, Algra AM, Algra A et al (2017) Female- and male-specific risk factors for stroke: a systematic review and meta-analysis. JAMA Neurol 74:75–81. doi: 10.1001/jamaneurol.2016.3482 CrossRefPubMedGoogle Scholar
  33. Reynolds K, Lewis LB, Nolen JDL, Kinney GL (2003) Alcohol consumption and risk of stroke: a meta-analysis. JAMA 289:579–588CrossRefGoogle Scholar
  34. Rose G (1965) Standardisation of observers in blood-pressure measurement. Lancet 1:673–674. doi: 10.1016/S0140-6736(65)91827-1 CrossRefPubMedGoogle Scholar
  35. Rothman KJ (2012) Epidemiology : an introduction, 2nd edn. Oxford University Press, OxfordGoogle Scholar
  36. Rothman KJ, Greenland S, Lash TL (2008) Modern epidemiology, 3rd edn. Lippincott Williams and Wilkins, PhiladelphiaGoogle Scholar
  37. Wang H, Naghavi M, Allen C et al (2015) Global, regional, and national life expectancy, all-cause mortality, and cause-specific mortality for 249 causes of death, 1980–2015: a systematic analysis for the Global Burden of Disease Study 2015. Lancet 388:1459–1544. doi: 10.1016/S0140-6736(16)31012-1 CrossRefGoogle Scholar
  38. Wannamethee SG, Papacosta O, Lawlor DA et al (2012) Do women exhibit greater differences in established and novel risk factors between diabetes and non-diabetes than men? The British Regional Heart Study and British Women’s Heart Health Study. Diabetologia 55:80–87. doi: 10.1007/s00125-011-2284-4 CrossRefPubMedGoogle Scholar
  39. Wareham NJ, Jakes RW, Rennie KL et al (2003) Validity and repeatability of a simple index derived from the short physical activity questionnaire used in the European Prospective Investigation into Cancer and Nutrition (EPIC) study. Public Heal Nutr 6:407–413. doi: 10.1079/PHN2002439 CrossRefGoogle Scholar

Copyright information

© Swiss School of Public Health (SSPH+) 2017

Authors and Affiliations

  • Slavica Trajkova
    • 1
  • Angelo d’Errico
    • 2
  • Fulvio Ricceri
    • 1
    • 2
  • Francesca Fasanelli
    • 1
  • Valeria Pala
    • 3
  • Claudia Agnoli
    • 3
  • Rosario Tumino
    • 4
  • Graziella Frasca
    • 4
  • Giovanna Masala
    • 5
  • Calogero Saieva
    • 5
  • Paolo Chiodini
    • 6
  • Amalia Mattiello
    • 7
  • Carlotta Sacerdote
    • 1
    Email author
  • Salvatore Panico
    • 7
  1. 1.Unit of Cancer Epidemiology, Department of Medical SciencesUniversity of Turin and Città della Salute e della Scienza University-Hospital Center for Cancer Prevention (CPO)TurinItaly
  2. 2.Unit of EpidemiologyRegional Health ServiceTurinItaly
  3. 3.Epidemiology and Prevention UnitFondazione IRCCS Istituto Nazionale dei TumoriMilanItaly
  4. 4.Cancer Registry, Department of PreventionRagusaItaly
  5. 5.Cancer Risk Factors and Lifestyle Epidemiology Unit Cancer Research and Prevention Institute-ISPOFlorenceItaly
  6. 6.Department of Physical and Mental Health and PreventionSecond University of NaplesNaplesItaly
  7. 7.Department of Clinical Medicine and SurgeryFederico II UniversityNaplesItaly

Personalised recommendations