IDEAS home Printed from https://ideas.repec.org/a/plo/pone00/0221015.html
   My bibliography  Save this article

Investigating the effect of lifestyle risk factors upon number of aspirated and mature oocytes in in vitro fertilization cycles: Interaction with antral follicle count

Author

Listed:
  • Lana Salih Joelsson
  • Evangelia Elenis
  • Kjell Wanggren
  • Anna Berglund
  • Anastasia N Iliadou
  • Carolyn E Cesta
  • Sunni L Mumford
  • Richard White
  • Tanja Tydén
  • Alkistis Skalkidou

Abstract

Introduction: There is evidence demonstrating that certain lifestyle factors have a detrimental effect on fertility. Since such factors often coexist, possible synergistic effects merit further investigation. Thus we aimed to examine the cumulative impact of lifestyle factors on in vitro fertilization (IVF) early reproductive treatment outcomes and their interaction with measures of ovarian reserve. Materials and methods: By following women who were starting their first fresh IVF cycle in 2 cohorts, the “Lifestyle study cohort” (hypothesis generating cohort, n = 242) and the “UppSTART study” (validation cohort, n = 432) in Sweden, we identified two significant risk factors acting independently, smoking and BMI, and then further assessed their cumulative effects. Results: Women with both these risk factors had an Incidence Rate Ratio (IRR) of 0.75 [(95% CI 0.61–0.94)] regarding the number of aspirated oocytes compared to women without these risk factors. Concerning the proportion of mature oocytes in relation to the total number of aspirated oocytes, the interaction between BMI and Antral Follicle Count (AFC) was significant (p-value 0.045): the lower the value of AFC, the more harmful the effect of BMI with the outcome. Conclusions: Data shows that there is an individual as well as a cumulative effect of smoking and BMI on the number of aspirated and mature oocytes in fresh IVF treatment cycles. AFC might modify associations between BMI and the proportion of mature oocytes in relation to the total number of aspirated oocytes. These results highlight the importance of lifestyle factors on IVF early reproductive outcomes and provide additional evidence for the importance of preconception guidance for the optimization of IVF cycle outcome.

Suggested Citation

  • Lana Salih Joelsson & Evangelia Elenis & Kjell Wanggren & Anna Berglund & Anastasia N Iliadou & Carolyn E Cesta & Sunni L Mumford & Richard White & Tanja Tydén & Alkistis Skalkidou, 2019. "Investigating the effect of lifestyle risk factors upon number of aspirated and mature oocytes in in vitro fertilization cycles: Interaction with antral follicle count," PLOS ONE, Public Library of Science, vol. 14(8), pages 1-15, August.
  • Handle: RePEc:plo:pone00:0221015
    DOI: 10.1371/journal.pone.0221015
    as

    Download full text from publisher

    File URL: https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0221015
    Download Restriction: no

    File URL: https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0221015&type=printable
    Download Restriction: no

    File URL: https://libkey.io/10.1371/journal.pone.0221015?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. van Buuren, Stef & Groothuis-Oudshoorn, Karin, 2011. "mice: Multivariate Imputation by Chained Equations in R," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 45(i03).
    2. Mette Wulf Christensen & Hans Jakob Ingerslev & Birte Degn & Ulrik Schiøler Kesmodel, 2016. "Effect of Female Body Mass Index on Oocyte Quantity in Fertility Treatments (IVF): Treatment Cycle Number Is a Possible Effect Modifier. A Register-Based Cohort Study," PLOS ONE, Public Library of Science, vol. 11(9), pages 1-15, September.
    3. Schenker, Nathaniel & Taylor, Jeremy M. G., 1996. "Partially parametric techniques for multiple imputation," Computational Statistics & Data Analysis, Elsevier, vol. 22(4), pages 425-446, August.
    4. Daniel F. Heitjan & Roderick J. A. Little, 1991. "Multiple Imputation for the Fatal Accident Reporting System," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 40(1), pages 13-29, March.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. repec:jss:jstsof:45:i02 is not listed on IDEAS
    2. Encarnita Mariotti-Ferrandiz & Hang-Phuong Pham & Sophie Dulauroy & Olivier Gorgette & David Klatzmann & Pierre-André Cazenave & Sylviane Pied & Adrien Six, 2016. "A TCRβ Repertoire Signature Can Predict Experimental Cerebral Malaria," PLOS ONE, Public Library of Science, vol. 11(2), pages 1-17, February.
    3. Maaz Gardezi & J. Gordon Arbuckle, 2019. "Spatially Representing Vulnerability to Extreme Rain Events Using Midwestern Farmers’ Objective and Perceived Attributes of Adaptive Capacity," Risk Analysis, John Wiley & Sons, vol. 39(1), pages 17-34, January.
    4. Chaton, Corinne & Gouraud, Alexandre, 2020. "Simulation of fuel poverty in France," Energy Policy, Elsevier, vol. 140(C).
    5. Brunori, Paolo & Salas-Rojo, Pedro & Verme, Paolo, 2022. "Estimating Inequality with Missing Incomes," GLO Discussion Paper Series 1138, Global Labor Organization (GLO).
    6. Rebecca R. Andridge & Roderick J. A. Little, 2010. "A Review of Hot Deck Imputation for Survey Non‐response," International Statistical Review, International Statistical Institute, vol. 78(1), pages 40-64, April.
    7. Patrick Lloyd‐Smith, 2021. "The economic benefits of recreation in Canada," Canadian Journal of Economics/Revue canadienne d'économique, John Wiley & Sons, vol. 54(4), pages 1684-1715, November.
    8. Kwon, Tae Yeon & Park, Yousung, 2015. "A new multiple imputation method for bounded missing values," Statistics & Probability Letters, Elsevier, vol. 107(C), pages 204-209.
    9. Kristian Kleinke & Jost Reinecke, 2013. "Multiple imputation of incomplete zero-inflated count data," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 67(3), pages 311-336, August.
    10. Taylor, Jeremy M. G. & Murray, Susan & Hsu, Chiu-Hsieh, 2002. "Survival estimation and testing via multiple imputation," Statistics & Probability Letters, Elsevier, vol. 58(3), pages 221-232, July.
    11. Wenqing Jiang & Jiangjie Zhou & Baosheng Liang, 2023. "An Improved Dunnett’s Procedure for Comparing Multiple Treatments with a Control in the Presence of Missing Observations," Mathematics, MDPI, vol. 11(14), pages 1-16, July.
    12. Patrick M. Joyce & Donald Malec & Roderick J. A. Little & Aaron Gilary & Alfredo Navarro & Mark E. Asiala, 2014. "Statistical Modeling Methodology for the Voting Rights Act Section 203 Language Assistance Determinations," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 109(505), pages 36-47, March.
    13. Gabriele Beissel Durrant, 2009. "Imputation Methods for Handling Item-Nonresponse in the Social Sciences: A Methodological Review," Working Papers id:2007, eSocialSciences.
    14. Madero-Cabib, Ignacio & Fasang, Anette Eva, 2016. "Gendered work-family life courses and financial well-being in retirement," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 27, pages 43-60.
    15. Shu Yang & Jae Kwang Kim, 2020. "Asymptotic theory and inference of predictive mean matching imputation using a superpopulation model framework," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 47(3), pages 839-861, September.
    16. Noémi Kreif & Richard Grieve & Iván Díaz & David Harrison, 2015. "Evaluation of the Effect of a Continuous Treatment: A Machine Learning Approach with an Application to Treatment for Traumatic Brain Injury," Health Economics, John Wiley & Sons, Ltd., vol. 24(9), pages 1213-1228, September.
    17. Abhilash Bandam & Eedris Busari & Chloi Syranidou & Jochen Linssen & Detlef Stolten, 2022. "Classification of Building Types in Germany: A Data-Driven Modeling Approach," Data, MDPI, vol. 7(4), pages 1-23, April.
    18. Boonstra Philip S. & Little Roderick J.A. & West Brady T. & Andridge Rebecca R. & Alvarado-Leiton Fernanda, 2021. "A Simulation Study of Diagnostics for Selection Bias," Journal of Official Statistics, Sciendo, vol. 37(3), pages 751-769, September.
    19. Timm Bönke & Markus M. Grabka & Carsten Schröder & Edward N. Wolff & Lennard Zyska, 2019. "The Joint Distribution of Net Worth and Pension Wealth in Germany," Review of Income and Wealth, International Association for Research in Income and Wealth, vol. 65(4), pages 834-871, December.
    20. Christopher J Greenwood & George J Youssef & Primrose Letcher & Jacqui A Macdonald & Lauryn J Hagg & Ann Sanson & Jenn Mcintosh & Delyse M Hutchinson & John W Toumbourou & Matthew Fuller-Tyszkiewicz &, 2020. "A comparison of penalised regression methods for informing the selection of predictive markers," PLOS ONE, Public Library of Science, vol. 15(11), pages 1-14, November.
    21. Liangyuan Hu & Lihua Li, 2022. "Using Tree-Based Machine Learning for Health Studies: Literature Review and Case Series," IJERPH, MDPI, vol. 19(23), pages 1-13, December.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:plo:pone00:0221015. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: plosone (email available below). General contact details of provider: https://journals.plos.org/plosone/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.