# Summer versus winter: the impact of the seasons on oocyte quality in in vitro fertilization cycles

## TL;DR

This study found that oocyte quality in IVF cycles is better in summer than in winter, with more abnormalities observed in winter cycles.

## Contribution

The study provides evidence that seasonal changes affect oocyte morphology and quality during IVF.

## Key findings

- Oocytes collected in summer showed fewer dysmorphisms compared to those collected in winter.
- Winter cycles had higher frequencies of category 2 and 3 oocytes, indicating lower quality.
- Cytoplasmic granularity was more common in winter, while refractile bodies were more frequent in summer.

## Abstract

The aim of this study was to determine the effects of seasons (winter vs. summer) on oocyte quality in infertile women undergoing ovulation induction for in vitro fertilization.

This retrospective cross-sectional study assessed 155 cycles of in vitro fertilization-induced ovulation in women, with 71 and 84 cycles occurring in the summer and winter, respectively. Oocytes were evaluated for quality, with 788 and 713 assessed during summer and winter, and classified according to Nikiforov's categories: (a) category I, good quality; (b) category 2, medium quality; and (c) category 3, low quality.

Thickened zona pellucida (p<0.001), increased perivitelline space (p<0.001), oocyte shape abnormalities (p=0.01), and the presence of refractile bodies (p<0.0001) were more frequent in the summer cycles, whereas cytoplasmic granularity (p<0.001) was more frequent in the winter cycles. In winter, we observed a higher frequency of category 3 (p<0.001) and category 2 (p<0.001) oocytes and a lower frequency of category 1 (p<0.001) oocytes.

Oocyte dysmorphisms were found in 70–80% of cases and were more common in winter. The main features include a thickened zona pellucida, enlarged perivitelline space, irregular shape, and cytoplasmic granularity. This implies better-quality oocytes in the summer than in the winter. However, retrospective studies have limitations due to data collection biases and potential confounding variables such as diet and exercise. Future research is needed to confirm these findings and explore the underlying mechanisms.