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The influence of male and female overweight/obesity on IVF outcomes: a cohort study based on registration in Western China

Abstract

Background

Overweight/obesity can affect fertility, increase the risk of pregnancy complications, and affect the outcome of assisted reproductive technology (ART). However, due to confounding factors, the accuracy and uniformity of published findings on IVF outcomes have been disputed. This study aimed to assess the effects of both male and female body mass index (BMI), individually and in combination, on IVF outcomes.

Methods

This retrospective cohort study included 11,191 couples undergoing IVF. Per the Chinese BMI standard, the couples were divided into four groups: normal; female overweight/obesity; male overweight/obesity; and combined male and female overweight/obesity. The IVF outcomes of the four groups were compared and analysed.

Results

Regarding the 6569 first fresh IVF-ET cycles, compared with the normal weight group, the female overweight/obesity and combined male/female overweight/obesity groups had much lower numbers of available embryos and high-quality embryos (p < 0.05); additionally, the fertilization (p < 0.001) and normal fertilization rates (p < 0.001) were significantly decreased in the female overweight/obesity group. The combined male/female overweight/obesity group had significant reductions in the available embryo (p = 0.002), high-quality embryo (p = 0.010), fertilization (p = 0.001) and normal fertilization rates (p < 0.001); however, neither male or female overweight/obesity nor their combination significantly affected the clinical pregnancy rate (CPR), live birth rate (LBR) or abortion rate (p > 0.05).

Conclusion

Our findings support the notion that overweight/obesity does not influence pregnancy success; however, we found that overweight/obesity affects the fertilization rate and embryo number and that there are sex differences.

Peer Review reports

Introduction

Overweight/obesity is an important global public health problem because it has not only a negative impact on quality of life but also a severe impact on health [1]. From 1979 to 2016, the number of adult obese women worldwide increased from 69 to 390 million, and the number of adult obese males increased from 31 to 281 million [2]. With its large population base and rapid growth rate, China has the world’s highest number of obese people [3]. According to the “Report on Nutrition and Chronic Disease Status of Chinese Residents (2020)” issued by the State Council of China on December 23, 2020, approximately 600 million people in China are overweight/obese, with an overweight rate of 34.3% and an obesity rate of 16.4% among adults. Body mass index (BMI) is the key indicator for measuring overweight/obesity, and based on data from European and American populations, the World Health Organization (WHO) established an international standard, wherein the normal BMI range is 18.5–24.9 kg/m2, a BMI of 25–29.9 kg/m2 indicates overweight, and a BMI ≥ 30 kg/m2 indicates obesity. As there are racial differences between Asian populations and European and American populations, the BMI standard of the WHO is not suitable for Chinese people [4]. For this reason, the BMI reference standard for Chinese adults is as follows: 18.5–23.9 kg/m2 is the normal range, 24–27.9 kg/m2 indicates overweight, and ≥ 28 kg/m2 indicates obesity [5].

Overweight/obesity can increase the incidences of many diseases, and their onset and progression are closely linked to those of endocrine diseases, which can affect the functions of multiple human systems, such as the reproductive system [6]. As a result, obesity is a risk factor for menstrual disorders and ovulation disorders in women, impairs sperm function and increases the risk of erectile dysfunction in men, thereby reducing fertility in couples [7,8,9].

Most infertile couples need to use ART to meet their fertility needs, and in vitro fertilization–embryo transfer (IVF–ET) is one of the most common forms of ART. It is estimated that by 2100, the percentage of people born by ART may reach 1.4–3.5% of the global population (approximately 157–394 million people); more than 2 million treatment cycles of IVF and intracytoplasmic sperm injection (ICSI) are completed every year [10]. Increasing evidence suggests that female overweight/obesity can negatively affect ART outcomes. The influence of obesity on the outcomes of ART exceeds that of being overweight and has a dose–response relationship [1, 11,12,13,14]. Similarly, several studies based on large populations have found that male overweight/obesity can negatively affect semen parameters and thereby reduce the potential for male fertility [15,16,17,18,19]. However, there is no consistent conclusion regarding the impact of overweight/obesity on embryonic parameters and the pregnancy outcomes of ART, especially IVF [18, 20,21,22,23,24]; therefore, more robust research is necessary. Given that the pregnancy success rate of IVF–ET depends on the health of both members of the couple, it is necessary to evaluate the combined influence of male and female BMI on embryo quality and the pregnancy outcome of IVF treatment. Of the last two retrospective studies evaluating the impact of male and female BMI on the clinical pregnancy rate (CPR) and the live birth rate (LBR), one found that individual or combined male and female overweight/obesity has a negative impact on the LBR after IVF treatment [25]. Another study concluded that there was no significant correlation between male or female overweight and the fertilization rate, embryo score, CPR or LBR [21]. The conclusions of these studies were limited by confounding factors that affected the results of the analysis, such as a small sample size and the inclusion of subjects who smoked; other associated confounding factors were not considered in these studies, and the study populations comprised mainly European or American participants. Therefore, in further research, in addition to considering the above influencing factors and adopting standardized methods that are suitable for measuring the BMIs of individuals of different races, combined male and female BMI and IVF cycle characteristics, including the number of oocytes harvested, endometrial thickness, IVF-ET cycle, number of transferred embryos and embryo quality, should be considered comprehensively.

Although China has the highest incidence of overweight/obese individuals, data on the IVF outcomes of Chinese overweight/obese populations are scarce. Therefore, we studied the effects of BMI on IVF outcomes among Chinese couples. Under the premise of excluding confounding factors that affect IVF outcomes, we systematically reviewed and summarized the data of patients registered as overweight/obesity to investigate the impacts of both male and female BMI, individually and in combination, on the fertilization rate, embryo score, and incidences of clinical pregnancies and live births among couples undergoing IVF treatment.

Materials and methods

Study period and participants

After obtaining approval from the Northwest Women and Children's Hospital, we conducted a prospective cohort study with all couples undergoing their first fresh IVF cycles from 01/2015–12/2020 at the Reproductive Center of Northwest Women and Children's Hospital, for whom male/female weight and height information were available. If the couple was interested in participating, a member of the study team discussed the study in detail and obtain written informed consent prior to the start of the IVF cycle or early in the cycle. Couples were selected according to the following criteria: (1) were undergoing their first fresh oocyte retrieval cycle; (2) had regular menstrual cycles; (3) had ≥ 4 oocytes harvested; (4) were aged between 22 and 36 years; (5) had normal chromosomes; and (6) had no reproductive tract infections, such as mycoplasma, chlamydia or gonorrhoea, in the past three months. The subjects also had none of the following conditions: (1) polycystic ovary syndrome (PCOS); (2) hyperprolactinemia; or (3) diabetes or other diseases that may affect IVF outcomes.

Body mass index assessment

BMI assessment data were abstracted from electronic medical records and patient medical charts. Upon presenting at the Reproductive Center of Northwest Women and Children's Hospital for infertility evaluation, male/female height and weight were measured by medical assistants using standardized protocols per clinical practice. According to the obesity and overweight standards of the Chinese Obesity Working Group, couples were divided into 4 groups: Group 1 (n = 3408, male and female BMI: 18.5 ≤ BMI < 24 kg/m2); Group 2 (n = 1398, female BMI: ≥ 24 kg/m2; male BMI: 18.5 ≤ BMI < 24 kg/m2); Group 3 (n = 4219, female BMI: 18.5 ≤ BMI < 24 kg/m2; male BMI: ≥ 24 kg/m2); and Group 4 (n = 2166, female BMI: ≥ 24 kg/m2; male BMI ≥ 24 kg/m2) (Fig. 1).

Fig. 1
figure 1

Flow chart of the study cohort characteristics

Research method

On the second day after oocytes were harvested, fertilization was judged by the presence of two pronuclei (2PN). If 2PN was displayed, fertilization was considered to have occurred. After fertilization, the cells were cultured in vitro for 72 h (cleavage stage) or 120 h (blastocyst stage) and transferred according to the number and quality of the embryos/blastocysts on that day and the woman’s progesterone value. This study included women who underwent embryo/blastocyst transfer. Beginning on the day of embryo/blastocyst transfer, 60 mg of progesterone (Zhejiang Xianju, China) was injected intramuscularly daily until day 70 or after the achievement of a clinical pregnancy. A biochemical pregnancy was defined as detectable human chorionic gonadotropin (hCG) in blood samples at 12 to 14 days after ET, and a clinical pregnancy was defined as one or more gestational sacs by B ultrasound at 4 to 6 weeks after ET.

Statistical analysis

Continuous variables are presented as the mean and standard deviation (SD), and categorical variables were described with the chi-square test. Analysis of variance was used for comparisons between groups, and for p ≤ 0.05, the least significant difference (LSD) t test was used to compare groups, with Group 1 as the reference. A linear regression model was employed to assess the associations of BMI status with the individual available embryo rate, high-quality embryo rate, fertilization rate and cleavage rate by calculating the β-coefficient and 95% confidence interval (CI). The odds ratio (OR) and 95% CI were calculated using a multivariate logistic regression model. Model 1 was adjusted for male and female age. Model 2 was adjusted for female age, male age, infertility duration, the number of available embryos, the left testicular volume, the right testicular volume, and the oestradiol (E2), follicle-stimulating hormone (FSH), progesterone (P), and luteinizing hormone (LH) levels on the day that the hCG level was measured. Two-sided p values less than 0.05 were considered significant. All analyses were conducted using SAS 9.4.

Results

A total of 11,191 couples with 6569 first fresh embryo transfer cycles were analysed; we included only the first IVF treatment cycle. The numbers of first fresh IVF–ET cycles in Groups 1, 2, 3 and 4 were 1947, 871, 2434, and 1317, respectively.

Table 1 shows the data on the basic characteristics of the subjects.

Table 1 Demographics of study samples by male and female BMI status

After the exclusion of patients with fewer than 4 harvested oocytes, there was no significant difference in the number of oocytes harvested among the four groups (p > 0.05), suggesting that when the number of oocytes harvested was ≥ 4, overweight/obesity did not affect the number of oocytes harvested during IVF. Although the left testicular volumes of the men in Group 3 and Group 4 were significantly different from those of the men in Group 1 (p < 0.05), their left testicular volumes were within the normal range (testicular volume ≥ 12 ml). Even when we restricted the ages of both spouses to between 22 and 36 years, the baseline distribution of the variables, including age, among the four groups was still unbalanced. For this reason, we established Model 2 to adjust for the variables contributing to the baseline imbalance.

Table 2 shows the IVF outcomes of the four groups with no adjustments for the baseline imbalances of male and female age or other variables. There were no significant differences in the available embryo rate, high-quality embryo rate, cleavage rate, implantation rate, CPR, abortion rate, or LBR (p > 0.05) among the four groups. Compared with those of Group 1, the fertilization rate and the normal fertilization rate of Groups 2 and 4 and the blastocyst rate of Group 3 were significantly different (p < 0.05).

Table 2 Comparison of clinical outcomes from IVF treatment between male and female BMI status

Table 3 shows the IVF outcomes of the four groups after adjustments were made for the baseline imbalances in male and female age and other variables. Compared with those of Group 1, the available embryo rate, fertilization rate, and normal fertilization rate of Groups 2 and 4 were all significantly reduced (p < 0.05), and the high-quality embryo rate [adjusted β-coefficient − 1.11, 95% CI (− 1.96, − 0.27)] of Group 4 was significantly reduced (p = 0.010).

Table 3 The association between BMI status and IVF treatment outcomes

Discussion

This is the largest study to date evaluating the individual and combined effects of male and female BMI on embryonic development and the CPR, LBR, and abortion rates after IVF. Our research indicated that being overweight/obese reduces the number of available embryos and high-quality embryos among couples undergoing IVF treatment and adversely affects the available embryo rate, high-quality embryo rate, and normal fertilization rate, with sex differences. Therefore, overweight/obesity may affect embryo formation and early development. There is evidence that obesity is associated with an increased risk of infertility and adverse pregnancy outcomes [15, 26, 27]. The meta-analysis report also stated that women with increased BMI have worse IVF outcomes than women with a normal BMI, namely, higher cycle cancellation rates, fewer harvested oocytes, fewer available embryos, and lower LBRs, and the number of abortions among women with a BMI ≥ 30 kg/m2 is also increased (OR 1.52, 95% CI 1.28–1.81, p < 0.001) [14, 28,29,30,31]. However, these studies are affected by confounding factors such as the ages of members of the couple, the number of IVF–ET cycles, male BMI, a small sample size, differences in BMI standards by race and the number of harvested oocytes, and these confounding variables do affect the accuracy of evaluations of pregnancy outcomes. Our study fully considered these confounding variables. Previous studies have shown that the number of aspirated oocytes is a predictor for IVF treatment outcomes [32, 33]. The harvesting of too few oocytes affects not only the number of available embryos but also the quality of the oocytes and embryos, which then affects the IVF outcome [34]. Therefore, we excluded patients with fewer than 4 harvested oocytes, and in the general data analysis, we further compared the number of harvested oocytes among the four groups and found no statistically significant difference (P = 0.059).

To reduce the impact of multiple transplant cycles on the results of IVF, we assessed only the first fresh transplant cycle. Even when we restricted the ages of both spouses to between 22 and 36 years, the baseline distribution of the variables, including age, among the four groups was still unbalanced, and we further adjusted for the ages of both spouses. After excluding these confounding factors, our research indicated that overweight/obesity does not affect the CPR, LBR or abortion rate after IVF. This is similar to the results of Petersen et al. [25], who showed that compared with normal weight, neither individual nor combined overweight/obesity significantly reduces the LBR after IVF. In addition, Xie et al. analysed the relationship between prepregnancy BMI and pregnancy and the perinatal period in 398,368 Chinese women and concluded that after adjusting for confounding factors such as age, race, educational level, residential area, occupation, smoking status, passive smoking and alcohol consumption, there was no significant association between female prepregnancy BMI and birth defects and miscarriage [35]. At the same time, we found that when the number of harvested oocytes was not less than 4, there was no significant difference in the number of harvested oocytes between the overweight/obesity group and the normal weight group; however, female overweight/obesity significantly reduced the rates of available embryos (adjusted β-coefficient − 1.32, 95% CI (− 2.53, 0.12), p = 0.031), fertilization (adjusted β-coefficient − 2.46, 95% CI (− 3.50, 1.42), p < 0.001), and normal fertilization (adjusted β-coefficient − 2.91, 95% CI (− 4.00, 1.83), p < 0.001). Combined male and female overweight/obesity also significantly reduced the rate of high-quality embryos (adjusted β-coefficient − 1.11, 95% CI (− 1.96, 0.27), p = 0.010), and the individual female and combined male and female overweight/obesity groups had much lower numbers of available embryos and high-quality embryos (p < 0.05).

Increasing attention has been given to the impact of male BMI on the outcomes of IVF. Schliep suggested that the BMI of both males and females (rather than one party) jointly affects the pregnancy success rate of IVF treatment [21]. Anifandis suggested that male BMI has a greater impact on embryo quality than female BMI [24]. However, our research indicated that male overweight/obesity had no adverse effects on the numbers of available embryos or high-quality embryos and no significant adverse effects on other IVF outcomes. This may be related to the fact that we controlled for a male age of 36 years, as the increase in male age increases the sperm DNA fragmentation index (DFI) and reduces the normal morphological rate [36, 37]. A number of studies have shown that increased sperm DFI can affect embryonic development and even increase the partner's abortion rate [38, 39]. Regarding the effect of male BMI on the LBR and CPR, our research results are consistent with the conclusions of Le and Schliep [21, 40], namely, that compared with normal male BMI, increased male BMI has no significant effect on the CPR and LBR after IVF (p > 0.05). In contrast, the results of Anfandis’s study [24] suggest that compared with overweight men, regardless of their partner’s BMI, the CPR of normal-weight men is increased; however, the sample size in these studies was small, and important potential confounding factors, such as male and female age, that might affect the conclusion were not considered. Previous studies have shown that age and sex hormone levels affect fertility [41]. A recent meta-analysis showed that an increased male BMI significantly reduced the CPR and LBR after ART (P < 0.05) [23], which might further affect the sperm DFI by affecting changes in sex hormone parameters. In our initial baseline data, there were significant differences in age and sex hormone levels that might further affect sperm DFI by affecting changes in sex hormone parameters. In our initial baseline data, there were significant differences in age and sex hormone levels (FSH days) among the men and women in each group (p < 0.05). To reduce the effects of these factors, we established an adjustment model for age and other influencing factors. After these factors were excluded, our conclusions were more reliable.

Our study has several advantages, including its relatively large sample size, prospective evaluation, consideration of the combined impact of male and female BMI, use of standardized methods to measure BMI, full consideration of confounding factors affecting IVF outcomes and establishment of an adjustment model. Nevertheless, our research still has some limitations. Due to the unavailability of relevant data from other IVF centres in China, the research data are limited to our research centre. It is recommended that future research include more effective and reliable multicentre research data and further explore the influence of overweight and obesity on IVF outcomes. Additionally, the influence of mental health on IVF outcomes has increasingly become a concern. The decision to undergo IVF is a significant financial and emotional investment. The fear of not being able to conceive or of a failed pregnancy can place considerable pressure on couples. However, current research suggests that stress levels and mental health may affect IVF outcomes [42, 43]. Future research should consider the mental health of IVF-ET patients as a confounding factor. In addition, due to energy and time constraints, although we measured male and female BMI in strict accordance with the Chinese BMI standards, we did not distinguish the degree of obesity, nor did we compare the quality of M2 oocytes and blastocysts. Future work is needed to evaluate these confounding factors. Finally, our study indicated that there was no significant difference in smoking status among the four groups, but other lifestyle factors in the entire sample, such as alcohol consumption, could not be considered. However, the impact of alcohol consumption on IVF outcomes is controversial [44, 45]. In our other related studies, we found that the number of people who drank alcohol in the included population was very small. Thus, we do not think that alcohol consumption is the main source of bias in our research. In any case, given that alcohol consumption may adversely affect IVF results [46], future studies should include valid and reliable measurements of alcohol consumption, in addition to other confounding lifestyle factors, when assessing the effect of BMI on IVF outcomes.

Conclusion

In summary, this study clearly identified the negative effects of overweight/obesity on the fertilization rate and embryo quality after IVF treatment. In addition, there are sex differences. However, a larger, well-designed study is needed to verify the results obtained in this study. It is recommended that future studies obtain more data from other domestic IVF centres and try to explore the mechanism of the influence of BMI on embryo quality and the fertilization rate.

Data availability

The datasets used and/or analysed during the current study are available from the corresponding author on reasonable request.

References

  1. Kaidar-Person O, Bar-Sela G, Person B. The two major epidemics of the twenty-first century: obesity and cancer. Obes Surg. 2011;21:1792–7.

    Article  Google Scholar 

  2. Collaboration NCDRF. Trends in adult body-mass index in 200 countries from 1975 to 2014: a pooled analysis of 1698 population-based measurement studies with 19.2 million participants. Lancet. 2016;387:1377–96.

    Article  Google Scholar 

  3. Fang C, Liang Y. Social disparities in body mass index (BMI) trajectories among Chinese adults in 1991–2011. Int J Equity Health. 2017;16:146.

    Article  Google Scholar 

  4. Cheng TO. Chinese body mass index is much lower as a risk factor for coronary artery disease. Circulation. 2004;109: e184.

    Article  Google Scholar 

  5. Zhou BF. Cooperative Meta-Analysis Group of the Working Group on Obesity in C: predictive values of body mass index and waist circumference for risk factors of certain related diseases in Chinese adults–study on optimal cut-off points of body mass index and waist circumference in Chinese adults. Biomed Environ Sci. 2002;15:83–96.

    Google Scholar 

  6. van der Steeg JW, Steures P, Eijkemans MJ, Habbema JD, Hompes PG, Burggraaff JM, Oosterhuis GJ, Bossuyt PM, van der Veen F, Mol BW. Obesity affects spontaneous pregnancy chances in subfertile, ovulatory women. Hum Reprod. 2008;23:324–8.

    Article  Google Scholar 

  7. Sundaram R, Mumford SL, Buck Louis GM. Couples’ body composition and time-to-pregnancy. Hum Reprod. 2017;32:662–8.

    Article  CAS  Google Scholar 

  8. Andersson AM, Jorgensen N, Main KM, Toppari J, Rajpert-De Meyts E, Leffers H, Juul A, Jensen TK, Skakkebaek NE. Adverse trends in male reproductive health: we may have reached a crucial “tipping point.” Int J Androl. 2008;31:74–80.

    Article  Google Scholar 

  9. Katib A. Mechanisms linking obesity to male infertility. Cent Eur J Urol. 2015;68:79–85.

    Article  Google Scholar 

  10. Faddy MJ, Gosden MD, Gosden RG. A demographic projection of the contribution of assisted reproductive technologies to world population growth. Reprod Biomed Online. 2018. https://doi.org/10.1016/j.rbmo.2018.01.006.

    Article  Google Scholar 

  11. Rittenberg V, Seshadri S, Sunkara SK, Sobaleva S, Oteng-Ntim E, El-Toukhy T. Effect of body mass index on IVF treatment outcome: an updated systematic review and meta-analysis. Reprod Biomed Online. 2011;23:490–9.

    Article  Google Scholar 

  12. Luke B, Brown MB, Stern JE, Missmer SA, Fujimoto VY, Leach R. Female obesity adversely affects assisted reproductive technology (ART) pregnancy and live birth rates. Hum Reprod. 2011;26:245–52.

    Article  Google Scholar 

  13. Pinborg A, Gaarslev C, Hougaard CO, Andersen AN, Andersen PK, Boivin J, Schmidt L. Influence of female bodyweight on IVF outcome: a longitudinal multicentre cohort study of 487 infertile couples. Reprod Biomed Online. 2011;23:401–2.

    Article  Google Scholar 

  14. Supramaniam PR, Mittal M, McVeigh E, Lim LN. The correlation between raised body mass index and assisted reproductive treatment outcomes: a systematic review and meta-analysis of the evidence. Reprod Health. 2018;15:34.

    Article  Google Scholar 

  15. Pini T, Parks J, Russ J, Dzieciatkowska M, Hansen KC, Schoolcraft WB, Katz-Jaffe M. Obesity significantly alters the human sperm proteome, with potential implications for fertility. J Assist Reprod Genet. 2020;37:777–87.

    Article  CAS  Google Scholar 

  16. Raad G, Azouri J, Rizk K, Zeidan NS, Azouri J, Grandjean V, Hazzouri M. Adverse effects of paternal obesity on the motile spermatozoa quality. PLoS ONE. 2019;14: e0211837.

    Article  CAS  Google Scholar 

  17. Sermondade N, Faure C, Fezeu L, Shayeb AG, Bonde JP, Jensen TK, Van Wely M, Cao J, Martini AC, Eskandar M, et al. BMI in relation to sperm count: an updated systematic review and collaborative meta-analysis. Hum Reprod Update. 2013;19:221–31.

    Article  CAS  Google Scholar 

  18. Campbell JM, Lane M, Owens JA, Bakos HW. Paternal obesity negatively affects male fertility and assisted reproduction outcomes: a systematic review and meta-analysis. Reprod Biomed Online. 2015;31:593–604.

    Article  Google Scholar 

  19. Macdonald AA, Stewart AW, Farquhar CM. Body mass index in relation to semen quality and reproductive hormones in New Zealand men: a cross-sectional study in fertility clinics. Hum Reprod. 2013;28:3178–87.

    Article  CAS  Google Scholar 

  20. Wang X, Hao J, Zhang F, Li J, Kong H, Guo Y. Effects of female and male body mass indices on the treatment outcomes and neonatal birth weights associated with in vitro fertilization/intracytoplasmic sperm injection treatment in China. Fertil Steril. 2016;106:460–6.

    Article  Google Scholar 

  21. Schliep KC, Mumford SL, Ahrens KA, Hotaling JM, Carrell DT, Link M, Hinkle SN, Kissell K, Porucznik CA, Hammoud AO. Effect of male and female body mass index on pregnancy and live birth success after in vitro fertilization. Fertil Steril. 2015;103:388–95.

    Article  Google Scholar 

  22. Sermondade N, Huberlant S, Bourhis-Lefebvre V, Arbo E, Gallot V, Colombani M, Freour T. Female obesity is negatively associated with live birth rate following IVF: a systematic review and meta-analysis. Hum Reprod Update. 2019;25:439–51.

    Article  CAS  Google Scholar 

  23. Mushtaq R, Pundir J, Achilli C, Naji O, Khalaf Y, El-Toukhy T. Effect of male body mass index on assisted reproduction treatment outcome: an updated systematic review and meta-analysis. Reprod Biomed Online. 2018;36:459–71.

    Article  Google Scholar 

  24. Anifandis G, Dafopoulos K, Messini CI, Polyzos N, Messinis IE. The BMI of men and not sperm parameters impact on embryo quality and the IVF outcome. Andrology. 2013;1:85–9.

    Article  CAS  Google Scholar 

  25. Petersen GL, Schmidt L, Pinborg A, Kamper-Jorgensen M. The influence of female and male body mass index on live births after assisted reproductive technology treatment: a nationwide register-based cohort study. Fertil Steril. 2013;99:1654–62.

    Article  Google Scholar 

  26. Broughton DE, Moley KH. Obesity and female infertility: potential mediators of obesity’s impact. Fertil Steril. 2017;107:840–7.

    Article  Google Scholar 

  27. Talmor A, Dunphy B. Female obesity and infertility. Best Pract Res Clin Obstet Gynaecol. 2015;29:498–506.

    Article  Google Scholar 

  28. Kudesia R, Wu H, Hunter Cohn K, Tan L, Lee JA, Copperman AB, Yurttas Beim P. The effect of female body mass index on in vitro fertilization cycle outcomes: a multi-center analysis. J Assist Reprod Genet. 2018;35:2013–23.

    Article  Google Scholar 

  29. Luke B. Adverse effects of female obesity and interaction with race on reproductive potential. Fertil Steril. 2017;107:868–77.

    Article  Google Scholar 

  30. Ding W, Zhang FL, Liu XC, Hu LL, Dai SJ, Li G, Kong HJ, Guo YH. Impact of female obesity on cumulative live birth rates in the first complete ovarian stimulation cycle. Front Endocrinol. 2019;10:516.

    Article  Google Scholar 

  31. Xue X, Shi W, Zhou H, Tian L, Zhao Z, Zhou D, Shi J. Cumulative live birth rates according to maternal body mass index after first ovarian stimulation for in vitro fertilization: a single center analysis of 14,782 patients. Front Endocrinol. 2020;11:149.

    Article  Google Scholar 

  32. Briggs R, Kovacs G, MacLachlan V, Motteram C, Baker HW. Can you ever collect too many oocytes? Hum Reprod. 2015;30:81–7.

    Article  Google Scholar 

  33. Drakopoulos P, Blockeel C, Stoop D, Camus M, de Vos M, Tournaye H, Polyzos NP. Conventional ovarian stimulation and single embryo transfer for IVF/ICSI. How many oocytes do we need to maximize cumulative live birth rates after utilization of all fresh and frozen embryos? Hum Reprod. 2016;31:370–6.

    Google Scholar 

  34. Cohen Y, Tannus S, Alzawawi N, Son WY, Dahan M, Buckett W. Poor ovarian response as a predictor for live birth in older women undergoing IVF. Reprod Biomed Online. 2018;36:435–41.

    Article  Google Scholar 

  35. Xie D, Yang W, Wang A, Xiong L, Kong F, Liu Z, Xie Z, Wang H. Effects of pre-pregnancy body mass index on pregnancy and perinatal outcomes in women based on a retrospective cohort. Sci Rep. 2021;11:19863.

    Article  CAS  Google Scholar 

  36. Rex AS, Wu C, Aagaard J, Fedder J. DNA fragmentation in human spermatozoa and pregnancy rates after intrauterine insemination. Should the DFI threshold be lowered? J Clin Med. 2021;10:1310.

    Article  CAS  Google Scholar 

  37. Evenson DP, Djira G, Kasperson K, Christianson J. Relationships between the age of 25,445 men attending infertility clinics and sperm chromatin structure assay (SCSA(R)) defined sperm DNA and chromatin integrity. Fertil Steril. 2020;114:311–20.

    Article  CAS  Google Scholar 

  38. Borges E Jr, Zanetti BF, Setti AS, Braga D, Provenza RR, Iaconelli A Jr. Sperm DNA fragmentation is correlated with poor embryo development, lower implantation rate, and higher miscarriage rate in reproductive cycles of non-male factor infertility. Fertil Steril. 2019;112:483–90.

    Article  Google Scholar 

  39. Zhu XB, Chen Q, Fan WM, Niu ZH, Xu BF, Zhang AJ. Sperm DNA fragmentation in Chinese couples with unexplained recurrent pregnancy loss. Asian J Androl. 2020;22:296–301.

    Article  CAS  Google Scholar 

  40. Le W, Su SH, Shi LH, Zhang JF, Wu DL. Effect of male body mass index on clinical outcomes following assisted reproductive technology: a meta-analysis. Andrologia. 2016;48:406–24.

    Article  CAS  Google Scholar 

  41. Paasch U, Grunewald S, Kratzsch J, Glander HJ. Obesity and age affect male fertility potential. Fertil Steril. 2010;94:2898–901.

    Article  Google Scholar 

  42. Kong L, Shao Y, Xia J, Han J, Zhan Y, Liu G, Wang X. Quantitative and qualitative analyses of psychological experience and adjustment of in vitro fertilization-embryo transfer patients. Med Sci Monit. 2019;25:8069–77.

    Article  Google Scholar 

  43. Zhou FJ, Cai YN, Dong YZ. Stress increases the risk of pregnancy failure in couples undergoing IVF. Stress. 2019;22:414–20.

    Article  CAS  Google Scholar 

  44. Firns S, Cruzat VF, Keane KN, Joesbury KA, Lee AH, Newsholme P, Yovich JL. The effect of cigarette smoking, alcohol consumption and fruit and vegetable consumption on IVF outcomes: a review and presentation of original data. Reprod Biol Endocrinol. 2015;13:134.

    Article  Google Scholar 

  45. Minguez-Alarcon L, Chavarro JE, Gaskins AJ. Caffeine, alcohol, smoking, and reproductive outcomes among couples undergoing assisted reproductive technology treatments. Fertil Steril. 2018;110:587–92.

    Article  CAS  Google Scholar 

  46. Rossi BV, Berry KF, Hornstein MD, Cramer DW, Ehrlich S, Missmer SA. Effect of alcohol consumption on in vitro fertilization. Obstet Gynecol. 2011;117:136–42.

    Article  Google Scholar 

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Acknowledgements

The authors thank all of the medical staff at The Second Affiliated Hospital of Xi’an Jiao Tong University and Reproductive Center of Northwest Women’s and Children’s Hospital for recording all the data in this study over the years. We thank Aimee Talarski, PhD, from AJE Customer Service for editing the English text of a draft of this manuscript.

Funding

This work was supported by the Scientific Research Project of Shaanxi Provincial Administration of Traditional Chinese Medicine (contracts 2019-ZZ-LC046).

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Authors

Contributions

XL participated in the design of the study and the acquisition of data, performed the statistical analysis, drafted the article and revised it critically. JPX and TC contributed equally to the conception and design. SJS and YH acquired the data and analysed and interpreted the data. JHS and ZZ participated in the interpretation of the data and the revision of the article. All authors read and approved the final manuscript.

Corresponding authors

Correspondence to Junping Xing or Tie Chong.

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Ethics approval and consent to participate

Ethical clearance was obtained from the Northwest Women and Children's Hospital before data collection was initiated. Written consent was obtained from each eligible study participant. Identifying information was not included in the questionnaire to ensure privacy and confidentiality. The right of an individual not to participate in the study was also respected. The completed questionnaire was kept confidential in a locked place.

Competing interests

The authors declare that they have no conflicts of interest.

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Liu, X., Shi, S., Sun, J. et al. The influence of male and female overweight/obesity on IVF outcomes: a cohort study based on registration in Western China. Reprod Health 20, 3 (2023). https://doi.org/10.1186/s12978-022-01558-9

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