Skip to main content
Download PDF

Effect of body mass index on pregnancy outcomes in young women with low-prognosis POSEIDON criteria after in vitro fertilization/intracytoplasmic sperm injection

Journal of Ovarian Research volume 18, Article number: 59 (2025) Cite this article

Abstract

Background

The aim of this study was to investeigate the pregnancy outcomes of young women with low prognosis according to the POSEIDON criteria after IVF/ICSI cycles and to explore the effect of body mass index (BMI) on pregnancy outcomes.

Methods

This was a retrospective cohort study conducted in women who underwent their first IVF/ICSI cycle treatment between January 2018 and December 2020, Among them, these patients who met criteria for POSEIDON group1and 3 were further categorized into four groups according to the China body mass index(BMI) classification, we analyzed the effect of BMI on pregnancy outcomes.

Results

A total of 29,354 patients were conducted first IVF/ICSI cycle between January 2018 and December 2020 in our reproductive center, 5981 women who met the criteria for POSEIDON 1 and POSEIDON 3 were further categorized into four groups according to the China body mass index(BMI) classification. There were not significant differences in the implantation rate and clinical pregnancy rate, regardless of fresh embryo transfer or frozen embryo transfer among the four groups (P > 0.05). The miscarriage rate of fresh embryo transfer was significantly higher in obese patients (P < 0.05), while the live birth rate of fresh embryo transfer and the cumulative live birth rate are significantly lower in obese patients(P < 0.05). BMI was a significant and independent predictor of the miscarriage rate of fresh embryo transfer (adjusted OR 1.111; 95% CI 1.042–1.184; p = 0.001) and the cumulative live-birth rate (adjusted OR 0.937; 95% CI 0.900–0.975; p = 0.001).

Conclusions

Our study indicated that obesity negatively impacts the IVF/ICSI outcomes of young women with low prognosis, including higher miscarriage rate and lower live birth-rate and cumulative live-birth rate. In our study, we found that BMI was the best independent predictor of the miscarriage rate of fresh embryo transfer and cumulative live-birth rate of low-prognosis patients under 35 years old. Thus the best way to reduce these complications for young patients with a poor prognosis was to keep their BMI between 18.5 kg/m2 and 24 kg/m2.

Introduction

It is well known that there is still a long way to go for the medical management of patients with a poor prognosis. Alviggi et al. proposed the POSEIDON criteria in 2016 [1], following the Bologna criteria in 2011 [2]. Several studies have addressed the issue that an increase in female age is associated with fewer euploid embryos [3] and more implantation failure, especially for women over 35 years old. Therefore, age is a dominant factor in a successful pregnancy and a healthy baby, and the age of women is the main factor in giving birth. It is another point of confusion for clinicians that large numbers of women with obesity who are undergoing in vitro fertilization/intracytoplasmic sperm injection (IVF/ICSI) have shown more difficulties related to body mass index (BMI, kg/m2), in addition to age. A recent study has shown that the risk ratio of infertility is 1.18 [95% confidence interval (CI): 1.05–1.31] per 1-unit increment of BMI when BMI exceeds 30 kg/m2 [4]. Many trials have revealed a progressive impairment of in vitro fertilization (IVF) outcome in women with obesity, including poorer implantation, clinical pregnancy, live birth, and higher miscarriage rates, compared with normal-BMI patients [5, 6]. However, few studies have explored the impact of BMI among low-prognosis patients undergoing IVF. Thus, the objective of our study is to evaluate the effect of BMI on IVF outcomes in a large cohort of young women with low prognosis undergoing IVF/ICSI cycles.

Methods

Study design and population

This retrospective cohort study was approved by the ethics committee of the Peking University Third Hospital. All young low-prognosis patients who underwent their first IVF/ICSI treatments during the period from January 2018 to December 2020 were enrolled. Young low- prognosis was defined according to the POSEIDON criteria Group 1 and Group 3 (age < 35 years old, number of oocytes retrieved ≤ 9, used standard ovarian stimulation protocols). The exclusion criteria were as follows: (1)age ≥ 35 years old, (2)chromosomal abnormality, (3)preimplantation genetic testing (PGT) cycles, (4)uterine malformations, (5)using non-standard ovarian stimulation protocol and (6)fertility preservation. Young low-prognosis patients were further categorized into four groups according to the China BMI classification [7], namely, underweight (BMI < 18.5 kg/m2), normal weight (18.5 ≤ BMI < 24 kg/m2), overweight (24 ≤ BMI < 28 kg/m2), and obese (BMI ≥ 28 kg/m2). A flowchart of the patient selection process is presented in Fig. 1.

Fig. 1
figure 1

Study flow chart

Full size image

Clinical settings

Patients accepted standard ovarian stimulation protocols, such as long gonadotropin-releasing hormone (GnRH) agonist and antagonist protocols. Ovarian stimulation regimen and dosage of gonadotropins selection was based on female age、BMI、 AMH、AFC and other characteristics by experienced physicians. Once two or three follicles reached a mean diameter of 17 mm, recombiant hCG(250 mg, Ovidrel, Merck)was used to trigger ovulation. Transvaginal oocyte retrieval was performed with the standard operating procedure 36–38 h after triggering. The collected oocytes were inseminated via IVF or ICSI and then embryos of day 3 or the blastocyst stage were transfered after egg retrieval.. The surplus embryos were vitrified for later frozen embryo transfer(FET)cycles. Progesterone intravaginal gel (Crinone 8% 90 mg/day, Merck-Serono) was provided as support for the luteal phase. The protocol selection of the FET cycle depends on whether the patient’ s menstrual cycle is regular or not. In the natural cycle, the endometrium and ovulation were monitored with vaginal ultrasound, and progesterone was administered on the 3rd day after ovulation, followed by embryo transfer, where for day-3 embryos, it was scheduled on the 3rd day after ovulation, or for blastocysts, it was scheduled on the 5th day. In the artificial FET protocol, estradiol valerate (Progynova 4 mg/day, Schering, Berlin, Germany) was supplemented from the 2nd-4th day during menstruation, and the medicine dosage can be adjusted in terms of endometrial thickness. When the endometrial thickness reaches ≥ 8 mm, progesterone administration was initiated and continues for 12 weeks of pregnancy. Embryo transfer was scheduled on the 5th day after luteal support for day-3 embryos or on the 7th day for blastocysts. A blood test for HCG was performed on the 14th day after ET (embryo transfer). A gynecological ultrasound was done to confirm intrauterine pregnancy on the 30th day after ET. Luteal support was discontinued at 8–9 weeks of pregnancy. During the artificial cycle, the medication was gradually reduced starting from the 10th week of pregnancy and completely stopped by the 12th week.

The primary outcome is the cumulative live birth rate (CLBR), defined as the probability of live birth from ovarian stimulation during the study period, including all fresh and frozen embryos transferred from that stimulation. Live birth is classified as the birth of at least one living infant after 28 weeks. The secondary outcome is the rates of implantation, clinical pregnancy, miscarriage, live birth rate (LBR) and characteristics of stimulation procedures, including the number of oocytes retrieved, the number of 2 pro-nucleus (2PN) zygotes and the number of high-quality embryos.

Statistical analysis

All statistical management and analyses were performed using SPSS 25.0 software (IBM Corp., Armonk, NY, USA). One-way analysis of variance (ANOVA) and the post hoc Bonferroni test were used for comparisons of continuous variables between the groups based on the distribution of the data. The chi-square test was used for comparisons of categorical variables, and we also adopted Fisher's exact test if necessary. Continuous variables and categorical variables are represented as the mean ± standard deviation (SD) and frequencies (%), respectively. Logistic regression analysis was used to analyze the elements associated with the miscarriage rate of fresh embryo transfer (ET) and CLBR in the first stimulation cycles; adjusted odds ratios (aORs) and 95% CIs were calculated. A P value of < 0.05 was considered to indicate statistical significance.

Results

A total of 29,354 patients underwent their first IVF/ICSI cycle between January 2018 and December 2020 in our reproductive center, 5981 women met the criteria for POSEIDON 1 and POSEIDON 3 (Fig. 1). In our study, Group 1 included 4,058 individuals, and Group 3 included 1,923 individuals. Baseline characteristics across different BMI groups were described in Table 1. These patients underwent a total of 7543 ET cycles, including fresh ET cycles and FET cycles.

Table 1 Baseline characteristics of the patients
Full size table

Table 1 showed the baseline characteristics of infertile women among the four BMI categories. Women with normal weight had the highest mean age of all four groups, and the difference was statistically significant (p = 0.001), although all the women were under 35 years old. Patients with elevated BMI have increased average infertility duration and antral follicular count (AFC), and the results imply statistical significance (p < 0.001). Compared with underweight or normal-weight patients, women in the overweight and obesity categories had higher anti-Müllerian hormone (AMH) levels (p < 0.001). The basal serum FSH level decreased with increasing BMI (p < 0.001). In the normal weight group, the basal serum E2 level was significantly lower than that in the underweight and obesity groups (p = 0.001). Among all BMI categories, the basal serum LH level was the highest in underweight patients (p < 0.001). No statistically significant difference was found among the four groups in terms of infertility caused by male factors, tubal factors or other multiple factors. Compared with women in the other BMI categories, women with overweight or obesity have more diagnoses of polycystic ovary syndrome (PCOS)-factor infertility.

Endocrine characteristics and embryology outcomes in the four groups were presented in Table 2. In terms of the controlled ovarian stimulation (COS) cycles, lower starting dosages of gonadotropin (Gn) and longer durations of ovarian stimulation were performed in women who were overweight and obese than in those in the underweight and normal weight groups (p < 0.05). There was no significant difference in the total dose of gonadotrophin among the four groups (p = 0.137). Compared with the patients with overweight or obesity, women in the underweight and normal-weight categories had higher E2 and P values on the trigger day (p < 0.001), while there were no statistically significant differences in the LH values on the trigger day among groups (p = 0.952). In the obese group, the number of oocytes retrieved and 2PN zygotes was the lowest compared to the other three groups (p = 0.001). The results showed that no statistically significant differences existed in the numbers of high-quality embryos (p = 0.169).

Table 2 Endocrine characteristics and IVF outcomes
Full size table

The clinical outcomes of the BMI groups were shown in Table 3. No difference was identified in the implantation rate and clinical pregnancy rate, regardless of whether fresh ET or FET was performed, across all BMI categories (p > 0.05). Among all BMI categories, the live birth rate of fresh ET was the highest in underweight patients (p < 0.05). The miscarriage rate of fresh ET and live birth rate of fresh ET and FET were the worst in patients with obesity (p < 0.05).

Table 3 Pregnancy outcomes of studied patients
Full size table

Figure 2 demonstrated the multiple logistic regression analysis of the miscarriage rate of fresh ET and the cumulative live birth rate in patients with BMI ≥ 24 kg/m2. After adjustments for several confounding factors, BMI ≥ 24 kg/m2 (i.e., women with overweight or obesity) was a significant and independent predictor of the miscarriage rate of fresh ET (aOR 1.111; 95% CI 1.042–1.184; p = 0.001) and the cumulative live birth rate (aOR 0.937; 95% CI 0.900–0.975; p = 0.001).

Fig. 2
figure 2

Multivariate logistic regression analysis of the miscarriage rate of fresh ET and the cumulative live-birth rate

Full size image

Table 4 showed the pregnancy outcomes of PCOS patients, with no significant difference according to BMI groups (p > 0.05), including implantation rate, clinical pregnancy rate, miscarriage rate and live birth rate.

Table 4 Pregnancy outcomes of studied patients with PCOS
Full size table

Table 5 depicted the ovarian function indicators and pregnancy outcomes of non-PCOS studied patients. With increasing BMI, AMH and AFC both increased, while the basal serum FSH level decreased, all of which were statistically significant differences (p < 0.05). The pregnancy outcomes were the same as those of the general studied patients: there was no significant difference in the implantation rate and clinical pregnancy rate among the different groups, and compared to the other 3 groups, the miscarriage rate of the obese group was the highest, while the live birth rate was the lowest (p < 0.05) regardless of whether fresh ET or FET was performed.

Table 5 Baseline characteristics and pregnancy outcomes of studied patients without PCOS
Full size table

Discussion

This single-center retrospective study demonstrated the impact of the BMI classification on pregnancy outcomes in young(age < 35 years old) POSEIDON patients. While the age was highly related to the aeuploid embryo and live birth outcome, one of the crucial factors in the POSEIDON classification was the female age [8]. Studies explored that there is a significant decrease in clinical pregnancy rate and a significant increase in miscarriage rate by increasing female age and BMI [9,10,11]. To the best of our knowledge, this was the first study to assess the pregnancy outcomes for young POSEIDON patients according to the BMI classification, to avoid the impact of age-related pregnancy outcomes.

We found that the age of obese group was not the highest, but the duration of infertility was indeed the longest among four BMI categories. Another study also showed the increased time of conception in the obese people [12]. Our study indicated that the number of PCOS was rising with BMI increasing. A recent study illustrated that the risk of PCOS is partly due to the increase of BMI resulting in the dysregulation of the complement system and the concurrent upregulation of its inhibitors [13]. AMH and AFC increases as BMI grows, which might be closely related to the rising proportion of PCOS. In our study, high-quality embryos was not different among four BMI groups, which is similar to other studies [14,15,16]. Our study showed that the increase of BMI was negatively correlated with basal serum FSH and LH levels, and same as another report [17], which uncovered the obese women have lower FSH and LH levels in the early follicular phase. There was no significant impact of obesity on the ovarian function, suggested by the AFC, AMH and FSH of obese people, possibly because of the increased number of PCOS in obesity women. Among different BMI groups, there was no difference for pregnant outcomes of PCOS patients, including implantation rate, pregnancy rate, miscarriage rate and live birth rate. However, our research indicated the same outcomes for non-PCOS patients – the best ovarian functions remain in the obese people, based on the data from AFC, AMH and FSH of different BMI groups. During the process of COS, the starting dosage of Gn for obese patients was lower than normal weight women and the duration of ovarian stimulation was the longest in obese women compared with other groups. In 2011, two studies pointed out the decrease number of oocytes retrieval in the obese women [18, 19]. These decreased assisted reproductive technologies (ART) outcomes may be related to the decrease trophectoderm cell number and the blastocyst formation with BMI increasing [19].

Although our study showed that no matter it is fresh ET or FET, the implantation rate and clinical pregnancy rate were the worst in obese patients than other groups, there were no statistically significant differences among all BMI groups. These findings were inconsistent with three previous studies [5, 6, 9]. The variance might be caused by no statistically significant differences in the number of high-quality embryos among groups in our study with low prognosis patients. A recent meta-analysis found the similar result [20]. The mechanisms of obesity effects on oocyte and embryos developments are complex. The accumulated fats were associated with a higher prevalence of mitochondrial dysfunction and insulin resistance in the body [21, 22], which causes spindle anomalies, chromosome segregation, and oocyte development [23]. A neurotransmitter peptide named NPY stimulated fat angiogenesis and proliferation via kisspeptin cells [24]and it also promoted appetite [25]. Meanwhile, NPY impaired follicle development though a promoting apoptosis and anti-proliferation effect [26]. However, previous experiments reported that there is no statistical difference in the proportion of euploid embryos among different BMI groups [27, 28], where the results are similar to our analysis.

A recent predictive model based on the research [29] of low prognosis patients with pregnancy failure pointed out that the low prognosis patients experiencing pregnancy failure is related to BMI > 24 kg/m2, which is different from our results. Although the implantation rate of obese group was the worst in our research, there was no statistical differences among different BMI groups, where the reason might be the elimination of the key factor for the pregnancy outcomes – age. Miscarriage rate was apparently worst in patients with obesity as shown in our study. Multiple researches suggested a relationship between obesity and increased miscarriage rate [30, 31]. We found live birth rate was the worst in the obese women, no matter fresh ET or FET. Similarly, a meta-analysis indicate that the increase of BMI is associated with worse live birth rate [32, 33]. Compared with normal weight women, the obese women have better ovarian function (higher AFC, AMH and lower FSH), as well as the similar number of high-quality embryos, the percentage of implantation and clinical pregnancy, but miscarriage rate was higher and live birth rate was lower. A time-lapse study including 7180 embryos reported that obese women’s embryos had cleavage delayed compared with normal weight women [34]. Two studies showed that the effect of obesity on fatty acid composition and concentration may have an effect on embryo function [14, 15]. Several studies suggested a number of obesity-related factors, such as endometrial gene expression, hormone receptor expression patterns, proteomic analysis of the endometrium, leptin and pro-inflammatory markers [35,36,37,38,39], increase the miscarriage risk. Meanwhile, these factors might also possibly increase the risk of pregnancy complications such as pre-eclampsia, gestational diabetes and pro-longed duration of labor, shoulder dystocia, caesarean delivery, macrosomia, and increased blood loss [6, 40,41,42] Our research showed that the increasing of risks of the miscarriage caused by obesity may lower the cumulative live birth rate. It is complex for the mechanisms of how obesity influences younger women with low prognosis reproductive function. A study implied that the lipids and the inflammatory markers caused by obesity in the follicular fluid impair the follicle development [43], leading to the increasing impairment in low prognosis patients.

Our results suggested that the miscarriage rate of fresh ET increases 11.1% and cumulative live birth rate decreases 6.3% for each additional BMI unit when BMI exceeds 24 kg/m2. Although the standards of BMI research vary among previous studies, BMI was an independent risk factor of miscarriage rate for the overweight and obese patients. Recent research[44] of predictive factors for POSEIDON patients’ pregnancy outcomes showed a negative relation between BMI and live birth rate (OR 0.9; 95% CI 0.9–1.0; p < 0.001) for BMI ≤ 23.4 kg/m2, but for BMI > 23.4 kg/m2, it shows a non-significant relation (OR 1.0; 95% CI 0.9–1.1; p = 0.999), which is different from our research. Different BMI standards and research people might contribute to the different research results between us. Our research targets more on the younger women with low prognosis. Thus, reducing weight may reduce these complications for the younger POSEIDON patients with high BMI. However, 3 randomized trials[45,46,47] in recent years showed no better pregnant outcomes for infertile obese patients losing weights before pregnancy.

The drawbacks in our current research: the primary one is the inherent limitations of retrospective study. Inconsistent COS protocol might affect the number of oocytes retrieved, which further influence the finalization of low prognosis patients. Furthermore, due to the time limitation, we cannot follow the research of all the FET cycles after the first time of IVF.

Conclusions

Our study indicates that the obesity negatively impacts IVF/ICSI outcomes of younger women with low prognosis, especially for the stage after implantation, including the miscarriage rate, live birth rate and cumulative live birth rate. BMI is the best independent predictor of the miscarriage rate of fresh ET and CLBR for low prognosis patients under 35 years old. The effects of obesity on younger women with low prognosis still need to be required by large sample size and prospective research.

Data Availability

No datasets were generated or analysed during the current study.

Abbreviations

BMI:

Body mass index

IVF/ICSI:

In vitro fertilization/intracytoplasmic sperm injection

ET:

Embryo transfer

PGT:

Preimplantation genetic testing

GnRH:

Gonadotropin-releasing hormone

FET:

Frozen embryo transfer

CLBR:

Cumulative live birth rate

LBR:

Live birth rate

2PN:

2 Pro-nucleus

ANOVA:

One-way analysis of variance

SD:

Standard deviation

aORs:

Adjusted odds ratios

AFC:

Antral follicular count

AMH:

Anti-Müllerian hormone

PCOS:

Polycystic ovary syndrome

COS:

Controlled ovarian stimulation

Gn:

Gonadotropin

ART:

Assisted reproductive technologies

References

  1. Alviggi C, Andersen CY, Buehler K, Conforti A, De Placido G, Esteves SC, et al. A new more detailed stratification of low responders to ovarian stimulation: from a poor ovarian response to a low prognosis concept. Fertil Steril. 2016;105(6):1452–3. Available from: https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=pubmed&dopt=Abstract&list_uids=26921622&query_hl=1https://doiorg.publicaciones.saludcastillayleon.es/10.1016/j.fertnstert.2016.02.005.

  2. Ferraretti AP, La Marca A, Fauser BC, Tarlatzis B, Nargund G, Gianaroli L. Eshre consensus on the definition of 'poor response' to ovarian stimulation for in vitro fertilization: the bologna criteria. Hum Reprod. 2011;26(7):1616–24. Available from: http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=pubmed&dopt=Abstract&list_uids=21505041&query_hl=1https://doiorg.publicaciones.saludcastillayleon.es/10.1093/humrep/der092

  3. Ata B, Kaplan B, Danzer H, Glassner M, Opsahl M, Tan SL, et al. Array cgh analysis shows that aneuploidy is not related to the number of embryos generated. Reprod Biomed Online. 2012;24(6):614–20. Available from: http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=pubmed&dopt=Abstract&list_uids=22503277&query_hl=1https://doiorg.publicaciones.saludcastillayleon.es/10.1016/j.rbmo.2012.02.009

  4. Hernaez A, Rogne T, Skara KH, Haberg SE, Page CM, Fraser A, et al. Body mass index and subfertility: multivariable regression and mendelian randomization analyses in the norwegian mother, father and child cohort study. Hum Reprod. 2021;36(12):3141–51. Available from: http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=pubmed&dopt=Abstract&list_uids=34668019&query_hl=1https://doiorg.publicaciones.saludcastillayleon.es/10.1093/humrep/deab224

  5. Provost MP, Acharya KS, Acharya CR, Yeh JS, Steward RG, Eaton JL, et al. Pregnancy outcomes decline with increasing body mass index: analysis of 239,127 fresh autologous in vitro fertilization cycles from the 2008–2010 society for assisted reproductive technology registry. Fertil Steril. 2016;105(3):663–69. Available from: http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=pubmed&dopt=Abstract&list_uids=26627120&query_hl=1https://doiorg.publicaciones.saludcastillayleon.es/10.1016/j.fertnstert.2015.11.008

  6. Kawwass JF, Kulkarni AD, Hipp HS, Crawford S, Kissin DM, Jamieson DJ. Extremities of body mass index and their association with pregnancy outcomes in women undergoing in vitro fertilization in the united states. Fertil Steril. 2016;106(7):1742–50. Available from: http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=pubmed&dopt=Abstract&list_uids=27666564&query_hl=1https://doiorg.publicaciones.saludcastillayleon.es/10.1016/j.fertnstert.2016.08.028

  7. Zhou B. [predictive values of body mass index and waist circumference to risk factors of related diseases in chinese adult population]. Zhonghua Liu Xing Bing Xue Za Zhi. 2002;23(1):5–10. Available from: http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=pubmed&dopt=Abstract&list_uids=12015100&query_hl=1

  8. Esteves SC, Alviggi C, Humaidan P, Fischer R, Andersen CY, Conforti A, et al. The poseidon criteria and its measure of success through the eyes of clinicians and embryologists. Front Endocrinol (Lausanne). 2019;10:814. Available from: http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=pubmed&dopt=Abstract&list_uids=31824427&query_hl=1https://doiorg.publicaciones.saludcastillayleon.es/10.3389/fendo.2019.00814

  9. Goldman RH, Farland LV, Thomas AM, Zera CA, Ginsburg ES. The combined impact of maternal age and body mass index on cumulative live birth following in vitro fertilization. Am J Obstet Gynecol. 2019;221(6):611–17. Available from: http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=pubmed&dopt=Abstract&list_uids=31163133&query_hl=1https://doiorg.publicaciones.saludcastillayleon.es/10.1016/j.ajog.2019.05.043

  10. Hu L, Bu Z, Guo Y, Su Y, Zhai J, Sun Y. Comparison of different ovarian hyperstimulation protocols efficacy in poor ovarian responders according to the bologna criteria. Int J Clin Exp Med. 2014;7(4):1128–34. Available from: http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=pubmed&dopt=Abstract&list_uids=24955194&query_hl=1

  11. Laru J, Nedelec R, Koivuaho E, Ojaniemi M, Jarvelin MR, Tapanainen JS, et al. Bmi in childhood and adolescence is associated with impaired reproductive function-a population-based cohort study from birth to age 50 years. Hum Reprod. 2021;36(11):2948–61. Available from: http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=pubmed&dopt=Abstract&list_uids=34364312&query_hl=1https://doiorg.publicaciones.saludcastillayleon.es/10.1093/humrep/deab164

  12. Gesink LD, Maclehose RF, Longnecker MP. Obesity and time to pregnancy. Hum Reprod. 2007;22(2):414–20. Available from: http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=pubmed&dopt=Abstract&list_uids=17095518&query_hl=1https://doiorg.publicaciones.saludcastillayleon.es/10.1093/humrep/del400

  13. Butler AE, Moin A, Sathyapalan T, Atkin SL. Components of the complement cascade differ in polycystic ovary syndrome. Int J Mol Sci. 2022;23(20). Available from: http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=pubmed&dopt=Abstract&list_uids=36293087&query_hl=1https://doiorg.publicaciones.saludcastillayleon.es/10.3390/ijms232012232

  14. Matorras R, Exposito A, Ferrando M, Mendoza R, Larreategui Z, Lainz L, et al. Oocytes of women who are obese or overweight have lower levels of n-3 polyunsaturated fatty acids compared with oocytes of women with normal weight. Fertil Steril. 2020;113(1):53–61. Available from: http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=pubmed&dopt=Abstract&list_uids=32033723&query_hl=1https://doiorg.publicaciones.saludcastillayleon.es/10.1016/j.fertnstert.2019.08.059

  15. Bellver J, De Los SM, Alama P, Castello D, Privitera L, Galliano D, et al. Day-3 embryo metabolomics in the spent culture media is altered in obese women undergoing in vitro fertilization. Fertil Steril. 2015;103(6):1407–15. Available from: http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=pubmed&dopt=Abstract&list_uids=25935493&query_hl=1https://doiorg.publicaciones.saludcastillayleon.es/10.1016/j.fertnstert.2015.03.015

  16. Bellver J, Brandao P, Alegre L, Meseguer M. Blastocyst formation is similar in obese and normal weight women: a morphokinetic study. Hum Reprod. 2021;36(12):3062–73. Available from: http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=pubmed&dopt=Abstract&list_uids=34601596&query_hl=1https://doiorg.publicaciones.saludcastillayleon.es/10.1093/humrep/deab212

  17. De Pergola G, Maldera S, Tartagni M, Pannacciulli N, Loverro G, Giorgino R. Inhibitory effect of obesity on gonadotropin, estradiol, and inhibin b levels in fertile women. Obesity (Silver Spring). 2006;14(11):1954–60. Available from: http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=pubmed&dopt=Abstract&list_uids=17135611&query_hl=1https://doiorg.publicaciones.saludcastillayleon.es/10.1038/oby.2006.228

  18. Shah DK, Missmer SA, Berry KF, Racowsky C, Ginsburg ES. Effect of obesity on oocyte and embryo quality in women undergoing in vitro fertilization. Obstet Gynecol. 2011;118(1):63–70. Available from: http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=pubmed&dopt=Abstract&list_uids=21691164&query_hl=1https://doiorg.publicaciones.saludcastillayleon.es/10.1097/AOG.0b013e31821fd360

  19. Souter I, Baltagi LM, Kuleta D, Meeker JD, Petrozza JC. Women, weight, and fertility: the effect of body mass index on the outcome of superovulation/intrauterine insemination cycles. Fertil Steril. 2011;95(3):1042–47. Available from: http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=pubmed&dopt=Abstract&list_uids=21195401&query_hl=1https://doiorg.publicaciones.saludcastillayleon.es/10.1016/j.fertnstert.2010.11.062

  20. Ribeiro LM, Sasaki L, Silva AA, Souza ES, Oliveira LA, C MGFA, et al. Overweight, obesity and assisted reproduction: a systematic review and meta-analysis. Eur J Obstet Gynecol Reprod Biol. 2022;271:117–27. Available from: http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=pubmed&dopt=Abstract&list_uids=35183001&query_hl=1https://doiorg.publicaciones.saludcastillayleon.es/10.1016/j.ejogrb.2022.01.019

  21. Turner N, Robker RL. Developmental programming of obesity and insulin resistance: does mitochondrial dysfunction in oocytes play a role? Mol Hum Reprod. 2015;21(1):23–30. Available from: http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=pubmed&dopt=Abstract&list_uids=24923276&query_hl=1https://doiorg.publicaciones.saludcastillayleon.es/10.1093/molehr/gau042

  22. Levens ED, Skarulis MC. Assessing the role of endometrial alteration among obese patients undergoing assisted reproduction. Fertil Steril. 2008;89(6):1606–08. Available from: http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=pubmed&dopt=Abstract&list_uids=17531230&query_hl=1https://doiorg.publicaciones.saludcastillayleon.es/10.1016/j.fertnstert.2007.03.079

  23. Machtinger R, Combelles CM, Missmer SA, Correia KF, Fox JH, Racowsky C. The association between severe obesity and characteristics of failed fertilized oocytes. Hum Reprod. 2012;27(11):3198–207. Available from: http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=pubmed&dopt=Abstract&list_uids=22968161&query_hl=1https://doiorg.publicaciones.saludcastillayleon.es/10.1093/humrep/des308

  24. Backholer K, Smith JT, Rao A, Pereira A, Iqbal J, Ogawa S, et al. Kisspeptin cells in the ewe brain respond to leptin and communicate with neuropeptide y and proopiomelanocortin cells. Endocrinology. 2010;151(5):2233–43. Available from: http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=pubmed&dopt=Abstract&list_uids=20207832&query_hl=1https://doiorg.publicaciones.saludcastillayleon.es/10.1210/en.2009-1190

  25. Chen HY, Trumbauer ME, Chen AS, Weingarth DT, Adams JR, Frazier EG, et al. Orexigenic action of peripheral ghrelin is mediated by neuropeptide y and agouti-related protein. Endocrinology. 2004;145(6):2607–12. Available from: http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=pubmed&dopt=Abstract&list_uids=14962995&query_hl=1https://doiorg.publicaciones.saludcastillayleon.es/10.1210/en.2003-1596

  26. Sirotkin AV, Kardosova D, Alwasel SH, Harrath AH. Neuropeptide y directly affects ovarian cell proliferation and apoptosis. Reprod Biol. 2015;15(4):257–60. Available from: http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=pubmed&dopt=Abstract&list_uids=26679167&query_hl=1https://doiorg.publicaciones.saludcastillayleon.es/10.1016/j.repbio.2015.07.004

  27. Bellver J. Bmi and miscarriage after ivf. Curr Opin Obstet Gynecol. 2022;34(3):114–21. Available from: http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=pubmed&dopt=Abstract&list_uids=35645009&query_hl=1https://doiorg.publicaciones.saludcastillayleon.es/10.1097/GCO.0000000000000778

  28. Goldman KN, Hodes-Wertz B, McCulloh DH, Flom JD, Grifo JA. Association of body mass index with embryonic aneuploidy. Fertil Steril. 2015;103(3):744–48. Available from: http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=pubmed&dopt=Abstract&list_uids=25576217&query_hl=1https://doiorg.publicaciones.saludcastillayleon.es/10.1016/j.fertnstert.2014.11.029

  29. Li F, Lu R, Zeng C, Li X, Xue Q. Development and validation of a clinical pregnancy failure prediction model for poor ovarian responders during ivf/icsi. Front Endocrinol (Lausanne). 2021;12:717288. Available from: http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=pubmed&dopt=Abstract&list_uids=34497586&query_hl=1https://doiorg.publicaciones.saludcastillayleon.es/10.3389/fendo.2021.717288

  30. Eapen A, Hayes ET, McQueen DB, Beestrum M, Eyck PT, Boots C. Mean differences in maternal body mass index and recurrent pregnancy loss: a systematic review and meta-analysis of observational studies. Fertil Steril. 2021;116(5):1341–48. Available from: http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=pubmed&dopt=Abstract&list_uids=34412893&query_hl=1https://doiorg.publicaciones.saludcastillayleon.es/10.1016/j.fertnstert.2021.06.019

  31. Fabozzi G, Cimadomo D, Allori M, Vaiarelli A, Colamaria S, Argento C, et al. Maternal body mass index associates with blastocyst euploidy and live birth rates: the tip of an iceberg? Reprod Biomed Online. 2021;43(4):645–54. Available from: http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=pubmed&dopt=Abstract&list_uids=34446374&query_hl=1https://doiorg.publicaciones.saludcastillayleon.es/10.1016/j.rbmo.2021.07.006

  32. Sermondade N, Huberlant S, Bourhis-Lefebvre V, Arbo E, Gallot V, Colombani M, et al. Female obesity is negatively associated with live birth rate following ivf: a systematic review and meta-analysis. Hum Reprod Update. 2019 2019;25(4):439–51. Available from: http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=pubmed&dopt=Abstract&list_uids=30941397&query_hl=1https://doiorg.publicaciones.saludcastillayleon.es/10.1093/humupd/dmz011

  33. Tang K, Guo Y, Wu L, Luo Y, Gong B, Feng L. A non-linear dose-response relation of female body mass index and in vitro fertilization outcomes. J Assist Reprod Genet. 2021;38(4):931–39. Available from: http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=pubmed&dopt=Abstract&list_uids=33496916&query_hl=1https://doiorg.publicaciones.saludcastillayleon.es/10.1007/s10815-021-02082-8

  34. Bartolacci A, Buratini J, Moutier C, Guglielmo MC, Novara PV, Brambillasca F, et al. Maternal body mass index affects embryo morphokinetics: a time-lapse study. J Assist Reprod Genet. 2019;36(6):1109–16. Available from: http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=pubmed&dopt=Abstract&list_uids=31062218&query_hl=1https://doiorg.publicaciones.saludcastillayleon.es/10.1007/s10815-019-01456-3

  35. Broughton DE, Moley KH. Obesity and female infertility: potential mediators of obesity's impact. Fertil Steril. 2017;107(4):840–47. Available from: http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=pubmed&dopt=Abstract&list_uids=28292619&query_hl=1https://doiorg.publicaciones.saludcastillayleon.es/10.1016/j.fertnstert.2017.01.017

  36. Argenta P, Svendsen C, Elishaev E, Gloyeske N, Geller MA, Edwards RP, et al. Hormone receptor expression patterns in the endometrium of asymptomatic morbidly obese women before and after bariatric surgery. Gynecol Oncol. 2014;133(1):78–82. Available from: http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=pubmed&dopt=Abstract&list_uids=24680595&query_hl=1https://doiorg.publicaciones.saludcastillayleon.es/10.1016/j.ygyno.2013.12.005

  37. Bellver J, Martinez-Conejero JA, Labarta E, Alama P, Melo MA, Remohi J, et al. Endometrial gene expression in the window of implantation is altered in obese women especially in association with polycystic ovary syndrome. Fertil Steril. 2011;95(7):2335–41, 2341. Available from: http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=pubmed&dopt=Abstract&list_uids=21481376&query_hl=1https://doiorg.publicaciones.saludcastillayleon.es/10.1016/j.fertnstert.2011.03.021

  38. Metwally M, Preece R, Thomas J, Ledger W, Li TC. A proteomic analysis of the endometrium in obese and overweight women with recurrent miscarriage: preliminary evidence for an endometrial defect. Reprod Biol Endocrinol. 2014;12:75. Available from: http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=pubmed&dopt=Abstract&list_uids=25096020&query_hl=1https://doiorg.publicaciones.saludcastillayleon.es/10.1186/1477-7827-12-75

  39. Orostica L, Poblete C, Romero C, Vega M. Pro-inflammatory markers negatively regulate irs1 in endometrial cells and endometrium from women with obesity and pcos. Reprod Sci. 2020;27(1):290–300. Available from: http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=pubmed&dopt=Abstract&list_uids=32046436&query_hl=1https://doiorg.publicaciones.saludcastillayleon.es/10.1007/s43032-019-00026-3

  40. Gonzalez MB, Robker RL, Rose RD. Obesity and oocyte quality: significant implications for art and emerging mechanistic insights. Biol Reprod. 2022 2022;106(2):338–50. Available from: http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=pubmed&dopt=Abstract&list_uids=34918035&query_hl=1https://doiorg.publicaciones.saludcastillayleon.es/10.1093/biolre/ioab228

  41. Koning AM, Kuchenbecker WK, Groen H, Hoek A, Land JA, Khan KS, et al. Economic consequences of overweight and obesity in infertility: a framework for evaluating the costs and outcomes of fertility care. Hum Reprod Update. 2010;16(3):246–54. Available from: http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=pubmed&dopt=Abstract&list_uids=20056674&query_hl=1https://doiorg.publicaciones.saludcastillayleon.es/10.1093/humupd/dmp053

  42. Venkatesh SS, Ferreira T, Benonisdottir S, Rahmioglu N, Becker CM, Granne I, et al. Obesity and risk of female reproductive conditions: a mendelian randomisation study. Plos Med. 2022;19(2):e1003679. Available from: http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=pubmed&dopt=Abstract&list_uids=35104295&query_hl=1https://doiorg.publicaciones.saludcastillayleon.es/10.1371/journal.pmed.1003679

  43. Robker RL, Akison LK, Bennett BD, Thrupp PN, Chura LR, Russell DL, et al. Obese women exhibit differences in ovarian metabolites, hormones, and gene expression compared with moderate-weight women. J Clin Endocrinol Metab. 2009;94(5):1533–40. Available from: http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=pubmed&dopt=Abstract&list_uids=19223519&query_hl=1https://doiorg.publicaciones.saludcastillayleon.es/10.1210/jc.2008-2648

  44. Li F, Ye T, Kong H, Li J, Hu L, Jin H, et al. Predictive factors for live birth in fresh in vitro fertilization/intracytoplasmic sperm injection treatment in poor ovarian reserve patients classified by the poseidon criteria. Front Endocrinol (Lausanne). 2021;12:630832. Available from: http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=pubmed&dopt=Abstract&list_uids=33967954&query_hl=1https://doiorg.publicaciones.saludcastillayleon.es/10.3389/fendo.2021.630832

  45. Legro RS, Hansen KR, Diamond MP, Steiner AZ, Coutifaris C, Cedars MI, et al. Effects of preconception lifestyle intervention in infertile women with obesity: the fit-plese randomized controlled trial. Plos Med. 2022;19(1):e1003883. Available from: http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=pubmed&dopt=Abstract&list_uids=35041662&query_hl=1https://doiorg.publicaciones.saludcastillayleon.es/10.1371/journal.pmed.1003883

  46. Mutsaerts MA. [randomized trial of a lifestyle program in obese infertile women]. Ned Tijdschr Geneeskd. 2016;160:D916. Available from: http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=pubmed&dopt=Abstract&list_uids=27966406&query_hl=1

  47. Einarsson S, Bergh C, Friberg B, Pinborg A, Klajnbard A, Karlstrom PO, et al. Weight reduction intervention for obese infertile women prior to ivf: a randomized controlled trial. Hum Reprod. 2017;32(8):1621–30. Available from: http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=pubmed&dopt=Abstract&list_uids=28854592&query_hl=1https://doiorg.publicaciones.saludcastillayleon.es/10.1093/humrep/dex235

Download references

Acknowledgements

We express our gratitude to healthcare professionals and laboratory technicians in Reproductive Medical Center of Peking University Third Hospital.

Clinical trial number

Not applicable.

Funding

This research was supported by National Key Research and Development Program(2022YFC2703800).

Author information

Authors and Affiliations

  1. Reproductive Medical Center, Department of Obstetrics and Gynecology, Peking University Third Hospital, Beijing, China

    Yiting Ren, Chen Yang, Tian Tian, Rong Li, Lina Wang & Xiumei Zhen

  2. Department of Obstetrics and Gynecology, The Second Hospital of Shanxi Medical University, Taiyuan City, China

    Yiting Ren

  3. Key Laboratory of Assisted Reproduction, Ministry of Education, Beijing, China

    Xiumei Zhen

Authors
  1. Yiting Ren
    View author publications

    You can also search for this author inPubMed Google Scholar

  2. Chen Yang
    View author publications

    You can also search for this author inPubMed Google Scholar

  3. Tian Tian
    View author publications

    You can also search for this author inPubMed Google Scholar

  4. Rong Li
    View author publications

    You can also search for this author inPubMed Google Scholar

  5. Lina Wang
    View author publications

    You can also search for this author inPubMed Google Scholar

  6. Xiumei Zhen
    View author publications

    You can also search for this author inPubMed Google Scholar

Contributions

Xiumei Zhen, Yiting Ren, Rong Li and Lina Wang devised this research, collect the data, and analyze the results. Chen Yang and Tian Tian participated in the data statistics.

Corresponding author

Correspondence to Xiumei Zhen.

Ethics declarations

Ethics approval and consent to participate

This retrospective cohort study was approved by the ethics committee of the Peking University Third Hospital.A statement confirming that the Ethics Committee is organized and operates according to Good Clinical Practice which is pass ed by NMPA and National Health Commission of the people's Republic of China, ICH-GCP, Biomedical Research Ethics Review invoIving human which is passed by National Health Commission of the people's Republic of China, Helsinki Declaration and ethical principles of International ethical guidelines for biomedical research involving human subjects which is passed by Council for International Organizations of Medical Science (CIOMS).

The name of the ethics committee: Peking University Third Hospital Medical Science Research Ethics Committee.

The committee’s reference number: IRB00006761-M2022261.

Consent for publication

Not applicable.

Competing interests

The authors declare no competing interests.

Additional information

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary Information

Rights and permissions

Open Access This article is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License, which permits any non-commercial use, sharing, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if you modified the licensed material. You do not have permission under this licence to share adapted material derived from this article or parts of it. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by-nc-nd/4.0/.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Ren, Y., Yang, C., Tian, T. et al. Effect of body mass index on pregnancy outcomes in young women with low-prognosis POSEIDON criteria after in vitro fertilization/intracytoplasmic sperm injection. J Ovarian Res 18, 59 (2025). https://doiorg.publicaciones.saludcastillayleon.es/10.1186/s13048-025-01611-8

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doiorg.publicaciones.saludcastillayleon.es/10.1186/s13048-025-01611-8

Keywords

Journal of Ovarian Research

ISSN: 1757-2215

Contact us