Reproductive Biology and Endocrinology (May 2024)

Effects of physical activity on infertility in reproductive females

  • Hanzhi Zhang,
  • Lan Hua,
  • Dan Liu,
  • Xin Su,
  • Jianlin Chen,
  • Jingfei Chen

DOI
https://doi.org/10.1186/s12958-024-01234-6
Journal volume & issue
Vol. 22, no. 1
pp. 1 – 9

Abstract

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Abstract Objectives To explore the relationship between different types of physical activity and female infertility. Methods This study analyzed data from 2,796 female participants aged 18–44 years in the United States, obtained from the National Health and Nutrition Examination Survey (NHANES) database spanning the years 2013 to 2020. Multiple logistic regression analyses and generalized linear models were used to explore the relationship between different types of physical activity and infertility after adjusting for potential confounding factors. Results We found a non-linear relationship between recreational activities and infertility with an inflection point of 5.83 h/week (moderate intensity), while work activities and traffic-related activities did not. On the left side of the inflection point, there was no significant association between recreational activity time and infertility (OR = 0.93, 95% CI: 0.86 to 1.02, P = 0.1146), but on the right side of the inflection point, there was a positive association between recreational activity time and the risk of infertility (OR = 1.04, 95% CI: 1.02 to 1.06, P = 0.0008). Conclusions The relationship between different types of physical activity and female infertility varies. We acknowledge the potential influence of confounding variables on this relationship. However, we have already adjusted for these potential variables in our analysis. Therefore, our findings suggest that appropriate recreational activity programs are essential for promoting reproductive health in women of reproductive age. Nevertheless, it is important to note that the observed association does not imply causality. Given the limitations of cross-sectional studies, further prospective cohort studies are needed to explore the causal relationship while accounting for additional confounding factors.

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