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A novel system dynamics model of female obesity and fertility

Author

Listed:
  • Sabounchi, N.S.
  • Hovmand, P.S.
  • Osgood, N.D.
  • Dyck, R.F.
  • Jungheim, E.S.

Abstract

Objectives. Our objective was to create a system dynamics model specific to weight gain and obesity in women of reproductive age that could inform future health policies and have the potential for use in preconception interventions targeting obese women. Methods. We used our system dynamics model of obesity in women to test various strategies for family building, including ovulation induction versus weight loss to improve ovulation. Outcomes included relative fecundability, postpartum body mass index, and mortality. Results. Our system dynamics model demonstrated that obese women who become pregnant exhibit increasing obesity levels over time with elevated morbidity and mortality. Alternatively, obese women who lose weight prior to pregnancy have improved reproductive outcomes but may risk an age-related decline in fertility, which can affect overall family size. Conclusions. Our model highlights important public health issues regarding obesity in women of reproductive age. The model may be useful in preconception counseling of obese women who are attempting to balance the competing risks associated with age-related declines in fertility and clinically meaningful weight loss.

Suggested Citation

  • Sabounchi, N.S. & Hovmand, P.S. & Osgood, N.D. & Dyck, R.F. & Jungheim, E.S., 2014. "A novel system dynamics model of female obesity and fertility," American Journal of Public Health, American Public Health Association, vol. 104(7), pages 1240-1246.
    • Handle: RePEc:aph:ajpbhl:10.2105/ajph.2014.301898_7
    DOI: 10.2105/AJPH.2014.301898
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    Cited by:

    1. Negar Darabi & Niyousha Hosseinichimeh, 2020. "System dynamics modeling in health and medicine: a systematic literature review," System Dynamics Review, System Dynamics Society, vol. 36(1), pages 29-73, January.
    2. Inas S. Khayal & Amro M. Farid, 2017. "The Need for Systems Tools in the Practice of Clinical Medicine," Systems Engineering, John Wiley & Sons, vol. 20(1), pages 3-20, January.
    3. Jose D Meisel & Olga L Sarmiento & Camilo Olaya & Pablo D Lemoine & Juan A Valdivia & Roberto Zarama, 2018. "Towards a novel model for studying the nutritional stage dynamics of the Colombian population by age and socioeconomic status," PLOS ONE, Public Library of Science, vol. 13(2), pages 1-22, February.
    4. John Pastor Ansah & Keith Low Sheng Hng & Salman Ahmad & Cheryl Goh, 2021. "Evaluating the impact of upstream and downstream interventions on chronic kidney disease and dialysis care: a simulation analysis," System Dynamics Review, System Dynamics Society, vol. 37(1), pages 32-58, January.
    5. Sharon Friel & Melanie Pescud & Eleanor Malbon & Amanda Lee & Robert Carter & Joanne Greenfield & Megan Cobcroft & Jane Potter & Lucie Rychetnik & Beth Meertens, 2017. "Using systems science to understand the determinants of inequities in healthy eating," PLOS ONE, Public Library of Science, vol. 12(11), pages 1-18, November.
    6. Chang, Angela Y. & Ogbuoji, Osondu & Atun, Rifat & Verguet, Stéphane, 2017. "Dynamic modeling approaches to characterize the functioning of health systems: A systematic review of the literature," Social Science & Medicine, Elsevier, vol. 194(C), pages 160-167.
    7. Mohammad Reza Davahli & Waldemar Karwowski & Redha Taiar, 2020. "A System Dynamics Simulation Applied to Healthcare: A Systematic Review," IJERPH, MDPI, vol. 17(16), pages 1-27, August.

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