Blastocyst formation rate for Asians versus Caucasians and within body mass index categories.

Purpose There are well-documented racial and ethnic disparities for in vitro fertilization (IVF) outcomes, including disparities in clinical pregnancy and live birth rate. Obesity has also been associated with an increase in the risk of infertility and reduction in the efficacy of fertility treatment. However, there are limited data regarding the potential effect of race and obesity on in vitro embryo development. The purpose of this study was to determine whether blastocyst formation rates vary with race and body mass index (BMI).

This retrospective analysis included 1134 fresh autologous cycles (N = 8266 embryos), which took place from January 2013 to December 2016. Women were categorized as Caucasian, Asian (not Indian), and Indian (South Asian) and by BMI categories (normal, overweight, and obese). Regression analyses were performed using race and BMI as the primary predictor variables and blastocyst formation as the outcome.

Compared to Caucasian, the adjusted OR for blastocyst development was 0.85 (95% CI 0.72–1.00) for Asian women and 1.15 (95% CI 0.95–1.38) for Indian women. Women who were overweight (aOR 0.93; 95% CI 0.77–1.12) or obese (aOR 0.92; 95% CI 0.74–1.12) had similar odds of blastocyst formation comparing to women with normal BMI. Furthermore, analyses examining combined effects of race and BMI revealed no differences in blastocyst formation among Asian or Indian women with varied BMI categories compared to Caucasian women with normal BMI.

Blastocyst formation did not differ based on race or BMI.

Blastocyst, In vitro fertilization, Obesity, BMI, Race

African American, Asian, and Hispanic women experience a lower success rate with IVF compared with non-Hispanic white women [1]. Multiple studies including analyses using large databases have found reduced clinical pregnancy and lower live birth rates among Black, Asian, and Hispanic women [2, 3]. In another US study examining IVF success rates, Baker et al. [4] noted an increased risk of late loss and decrease in live birth rate for Asian and African American women compared with Caucasian women. The reasons for racial and ethnic differences in the success of fertility treatments have not been well explained. Socioeconomic disparities by education, gaps in insurance coverage, and differences in cultural beliefs have been found to be related to the use of IVF [5], and these factors may differ between races. Caucasian women who use IVF are more highly educated and are more likely to be in middle-to-high-income bracket compared with women from other racial groups [5, 6]. In addition, minority women in the USA may be biologically or environmentally more susceptible to gynecologic diseases than white women. For instance, African American women tend to have a higher incidence of fibroids as compared to Caucasian women [7], and South Asian (Indian) women have higher rates of insulin resistance and polycystic ovarian syndrome [8]. Although there are data such as these regarding racial differences in factors affecting IVF outcome, the differences in the in vitro development of embryos for women of different races are not examined carefully. The ASRM Ethics Committee has emphasized that addressing the gap in reproductive research related to race and ethnic disparities is critical to achieving reproductive health equity [9]. In addition to race, obesity is another important factor to consider given that it is very common in the USA [10, 11] and has been associated with reduction in IVF success as seen in the studies mentioned below. As is true for race, the reasons for the decrease in IVF success rate associated with obesity are not clear. In the general population, obesity may interfere with ovulation and lead to an increased risk of pregnancy complications, including miscarriage, gestational diabetes, hypertensive disorders, fetal macrosomia, stillbirth, and congenital anomalies [12–14]. It is plausible that obesity could affect in vitro development of embryos given one study having suggested an effect of obesity on follicular development and oocyte quality [15]. An increase in the required gonadotropin dosage for egg stimulation, a reduction in the number and quality of mature oocytes, decreased fertilization rates, and fewer and/or poorer quality embryos available for transfer have been reported for obese women [16–23]. Leary et al. [24] showed that obesity alters the phenotype of the oocyte thus impacting the development of oocytes and preimplantation embryos especially the blastocyst stage. Although there is evidence that race and obesity may affect IVF and pregnancy outcomes, it is less clear whether there are also racial and BMI disparities in embryo in vitro development, which is a prerequisite for the success in IVF treatment. Given the knowledge gap in the field, the objective of the current work was to determine whether blastocyst formation varies by race and BMI. Knowledge of these potential differences could be important for counseling patients and for optimizing laboratory protocols.

Patient population The present study was based on retrospective analysis of fresh autologous cycles undertaken between January 1, 2013, and December 31, 2016, at the Stanford Medicine Fertility and Reproductive Health. Data regarding clinical demographics and embryo progression were extracted from the data reported to the Society for Assisted Reproductive Technology and from the program’s electronic medical record system for the IVF laboratory (BabySentry). All fresh autologous cycles which led to at least one fertilized oocyte on the day after oocyte retrieval were eligible for inclusion. Criteria for exclusion were as follows: research cycles, day 3 and day 4 transfer cycles, oocyte banking cycles, embryo banking cycles performed before day 5, cycles without 2 pronuclei (PN) the day after retrieval, first cycles with missing data on race, BMI, and cycles of patients not belonging to Caucasian, Asian (not Indian), and Indian (South Asian) races, which represented the vast majority of racial background. A total of 2000 patient cycles were initially identified, including multiple cycles from the same patient (Fig. 1). To avoid potential effects of prior cycle treatments on the outcome and correlation between cycles from the same patient, we only included the first cycle for each patient in the analysis. Further examination of data quality revealed one cycle with data missing regarding cleavage and thus was removed from subsequent analysis. The final dataset included 1134 eligible cycles (see Fig. 1). Predictor variables Race and BMI were predictors. Race data was collected from the medical records as self-reported by the patient and was kept as a categorical variable (Caucasian, Asian-not Indian, and Indian-South Asian). BMI for each patient was calculated from clinically measured height and weight at patient’s first visit using standard formula [25]. In consistency with the WHO guidelines, BMI was originally investigated as a categorical variable (underweight, < 18.5 kg/m2; normal, 18.5–24.9 kg/m2; overweight, 25.0–29.9 kg/m2; obese, ≥ 30.0 kg/m2) [26]. Because of limited proportion of underweight observations in our study population (< 4%), we combined underweight with normal BMI category. In consideration of different BMI thresholds for Asian population compared to Caucasian standards, we additionally developed a BMI indicator better reflecting Asian population (Indian: normal or underweight < 22.9 kg/m2, overweight 23.0–24.9 kg/m2, obese ≥ 25.0 kg/m2; Asians other than Indians: normal or underweight < 23.0 kg/m2, overweight 23.0–27.5 kg/m2, obese ≥ 27.5 kg/m2) [27–29]. Outcome variable Blastocyst formation was the key outcome of interest and was composed as a dichotomized variable (0: no; 1: yes). Blastocyst formation rate for descriptive statistics was defined as the number of blastocysts divided by the number of 2 PN embryos for each racial and BMI category. Data analysis There were 15 cycles with missing values for FSH dosage which were imputed by the mean. Patient level descriptive characteristics (age, BMI, FSH dosage, etiology of infertility, number of oocytes retrieved) were compared across three ethnicity groups (Caucasian, Asian, Indian). Multiple comparisons of categorical variables were conducted by chi-squared test. One-way ANOVA or Kruskal-Wallis equality-of-populations rank test was appropriately applied to compare continuous variables across three racial groups depending on normality and homoscedasticity. Bonferroni correction was applied for multiple comparisons. To evaluate the association between race, BMI, and blastocyst formation, we performed generalized estimating equation (GEE) methodology with exchangeable correlation structure because of multiple embryos available for each patient. Multiple blastocysts from single patient were identified by patient ID. Association was assessed by both bivariate and multivariable analysis. Multivariable model adjusted for patient age (≤ 30, 31–35, 36–40, 41–45, > 45), nulligravida, total dose of FSH (dichotomized at mean, < 3750 IU, ≥ 3750 IU), infertility (male factor, diminished ovarian reserve, polycystic ovarian syndrome, recurrent pregnancy loss, endometriosis, age, tubal disease, uterine factor, ovarian disorder, gestational carrier cycle, single gene disorder, unexplained infertility, 2 or more diagnoses, other), number of embryos (2PNs), and number of retrieved oocytes. Due to data unavailability, we did not control for genetic defects of embryos. To estimate effect modification by BMI, we first included the interaction term (race × BMI) in the model. However, the interaction term was insignificant (p = 0.936). To further investigate the potential differences in blastocyst formation with race and BMI, we performed the fully adjusted model to assess the joint effects of two predictors on the outcome (main Table 5) and to additionally evaluate the association stratified by each of the BMI and race categories separately (Appendix Table 6). Two-sided p value of less than 0.05 was considered statistically significant. All analyses were conducted using STATA Version 14.2 (StataCorp LLC, Texas). Table 5. | (aOR, 95% CI) | Blastocyst Formationa | || |---|---|---|---| | Race | ||| | BMI | Caucasian | Asian (not Indians) | Indian (South Asian) | | Normal (ref) | 1.00 | 0.85 (0.72, 1.00) | 1.15 (0.95, 1.38) | | Overweight | 0.99 (0.81, 1.22) | 0.79 (0.63, 1.00) | 1.06 (0.83, 1.37) | | Obese | 0.91 (0.75, 1.12) | 0.79 (0.60, 1.01) | 1.05 (0.83, 1.32) | aModel additionally adjsuted for women's age, nulligravida, infertility, number of embryos, number of oocytes, and FSH dosage Table 1. | Overall (N=1134) | Caucasian (N=534) | Asian (not Indian) (N=352) | Indian (South Asian) (N=248) | P-value | | |---|---|---|---|---|---| | Patient Age (Mean ± SD) | 37.1 ± 4.4 | 37.4 ± 4.4 | 37.7 ± 4.5 | 35.7 ± 4.0 | <0.001a | | Patient Age (%) | ||||| | <30 | 5.1 | 4.5 | 6.3 | 4.8 | <0.001b | | ≥30 and <35 | 28.9 | 26.8 | 22.2 | 43.2 | | | ≥35 and <40 | 37.7 | 37.1 | 40.1 | 35.5 | | | ≥40 and <45 | 26.3 | 29.6 | 28.1 | 16.5 | | | ≥46 | 2.0 | 2.1 | 3.4 | 0 | | | BMI, Median (IQR) | 22.7 (20.7-25.8) | 23.0 (21.0-26.3) | 21.5 (19.8-23.8) | 24.0 (21.5-27.4) | <0.001c | | BMI Categories (%) | ||||| | Normal Weight | 71.4 | 69.7 | 83.8 | 57.7 | <0.001b | | Overweight | 18.9 | 18.4 | 12.5 | 29.0 | | | Obese | 9.7 | 12.0 | 3.7 | 13.3 | | | Nulligravida (%) | 30.3 | 29.6 | 29.8 | 32.9 | 0.61b | | FSH dosage (Mean ± SD) | 3740.7 ± 1328.1 | 3816.2 ± 1323.2 | 3722.8 ± 1296.4 | 3603.7 ± 1375.8 | 0.11a | | Infertility Diagnosis (%) | ||||| | Male Factor | 21.3 | 22.7 | 18.5 | 22.2 | 0.17b | | DOR | 19.9 | 19.5 | 24.4 | 14.5 | | | PCOS | 6.6 | 5.1 | 6.3 | 10.5 | | | Recurrent Pregnancy Loss | 8.1 | 8.4 | 6.0 | 10.5 | | | Endometriosis | 6.2 | 5.2 | 6.3 | 8.1 | | | Age | 6.3 | 7.9 | 6.3 | 2.8 | | | Tubal Disease | 4.5 | 3.8 | 4.3 | 6.5 | | | Uterine Factor | 2.3 | 2.4 | 2.6 | 1.6 | | | Ovarian Disorder | 3.2 | 3.8 | 2.6 | 2.8 | | | Gestational Carrier Cycle | 1.2 | 1.3 | 1.4 | 0.8 | | | Single Gene Disorder | 2.4 | 3.0 | 1.7 | 2.0 | | | Unexplained Infertility | 12.4 | 10.9 | 5.7 | 13.3 | | | 2 or more Diagnoses | 21.6 | 22.10 | 20.74 | 21.77 | | | Other | 5.6 | 6.2 | 30.4 | 4.4 | | | Retrieved Oocyte Number, Median (IQR) | 10 (6-16) | 10 (6-17) | 10 (6-15) | 10 (7-16) | 0.17c | aoneway ANOVA bChi-square test cKruskal-Wallis equality-of-populations rank test

The total sample included 1134 women, of which 534 were Caucasian, 352 were Asian (not Indians), and 248 were Indian (South Asian) (Table 1). Average age at the first treatment cycle was different across racial groups (p < 0.001). Distribution of BMI categories differed across racial groups (p < 0.001). Percentages of women who were overweight or obese were Caucasian, 30.4%; Asian, 31.0%; and Indian, 63.4%. Infertility with two or more etiologies was the primary diagnosis in Caucasian (22.1%), Asian (20.7%), and Indian group (21.8%), followed by male factor among Caucasians (17.0%) and Indians (17.7%), and diminished ovarian reserve among Asians (19.0%). Infertility diagnoses did not differ across three racial groups (p = 0.17). Table 1. | Overall (N=1134) | Caucasian (N=534) | Asian (not Indian) (N=352) | Indian (South Asian) (N=248) | P-value | | |---|---|---|---|---|---| | Patient Age (Mean ± SD) | 37.1 ± 4.4 | 37.4 ± 4.4 | 37.7 ± 4.5 | 35.7 ± 4.0 | <0.001a | | Patient Age (%) | ||||| | <30 | 5.1 | 4.5 | 6.3 | 4.8 | <0.001b | | ≥30 and <35 | 28.9 | 26.8 | 22.2 | 43.2 | | | ≥35 and <40 | 37.7 | 37.1 | 40.1 | 35.5 | | | ≥40 and <45 | 26.3 | 29.6 | 28.1 | 16.5 | | | ≥46 | 2.0 | 2.1 | 3.4 | 0 | | | BMI, Median (IQR) | 22.7 (20.7-25.8) | 23.0 (21.0-26.3) | 21.5 (19.8-23.8) | 24.0 (21.5-27.4) | <0.001c | | BMI Categories (%) | ||||| | Normal Weight or Underweight | 62.3 | 69.7 | 69.0 | 36.7 | <0.001b | | Overweight | 20.2 | 18.4 | 23.0 | 20.2 | | | Obese | 17.6 | 12.0 | 8.0 | 43.2 | | | Nulligravida (%) | 30.3 | 29.6 | 29.8 | 32.9 | 0.61b | | FSH dosage (Mean ± SD) | 3740.7 ± 1328.1 | 3816.2 ± 1323.2 | 3722.8 ± 1296.4 | 3603.7 ± 1375.8 | 0.11a | | Infertility Diagnosis (%) | ||||| | Male Factor | 15.9 | 17.0 | 12.8 | 17.7 | 0.17b | | DOR | 14.9 | 14.2 | 19.0 | 10.5 | | | PCOS | 4.7 | 3.8 | 4.6 | 6.9 | | | Recurrent Pregnancy Loss | 6.3 | 6.0 | 6.0 | 7.3 | | | Endometriosis | 4.0 | 3.9 | 3.7 | 4.4 | | | Age | 4.7 | 5.4 | 5.1 | 2.4 | | | Tubal Disease | 2.9 | 2.1 | 2.6 | 5.2 | | | Uterine Factor | 1.9 | 1.9 | 2.0 | 1.6 | | | Ovarian Disorder | 2.7 | 3.2 | 2.0 | 2.8 | | | Gestational Carrier Cycle | 1.0 | 1.1 | 0.9 | 0.8 | | | Single Gene Disorder | 2.2 | 3.0 | 1.4 | 1.6 | | | Unexplained Infertility | 12.0 | 10.3 | 13.9 | 12.9 | | | 2 or more Diagnoses | 21.6 | 22.1 | 20.7 | 21.8 | | | Other | 5.4 | 6.0 | 5.4 | 4.0 | | | Retrieved Oocyte Number, Median (IQR) | 10 (6-16) | 10 (6-17) | 10 (6-15) | 10 (7-16) | 0.17c | aOneway ANOVA bChi-square test cKruskal-Wallis equality-of-populations rank test The description of embryos by racial groups is shown in Table 2. A total of 8266 embryos were developed during the first cycle including data from all three racial groups. On the patient level, numbers of 2PNs were comparable across racial groups with a median and interquartile range of 6 (3–10), 6 (3–10), and 6 (3–11) for Caucasians, Asians, and Indians, respectively (p = 0.39). The number of blastocysts differed by racial groups with a median and interquartile range of 2 (0–5), 1 (0–4), and 2 (0–5) for Caucasian, Asian, and Indian women separately (p = 0.02). Average patient-level blastocyst formation rates (mean ± SD) differed across racial groups (Caucasian, 0.32 ± 0.30; Asian, 0.28 ± 0.28; Indian, 0.38 ± 0.30, p < 0.001). Additionally, racial-specific blastocyst formation rate also differed within overweight (Caucasian, 0.30 ± 0.32; Asian, 0.25 ± 0.26; Indian, 0.40 ± 0.30, p = 0.02) and obese population (Caucasian, 0.28 ± 0.28; Asian, 0.18 ± 0.24; Indian, 0.36 ± 0.32, p = 0.01) (Table 3). Table 2. | Overall (N=1134) | Caucasian (N=534) | Asian (not Indian) (N=352) | Indian (N=248) | P-value | | |---|---|---|---|---|---| | Total number of embryos (2PNs) | 8266 | 3929 | 2513 | 1824 | n/a | | Number of 2PNs per patient, Median (IQR) | 6 (3-10) | 6 (3-10) | 6 (3-10) | 6 (3-11) | 0.39c | | Total number of cleaved embryos | 8090 | 3869 | 2453 | 1768 | n/a | | Number of cleaved embryos per patient, Median (IQR) | 6 (3-10) | 6 (3-10) | 6 (3-9) | 6 (3-11) | 0.44c | | Total number of blastocysts | 3212 | 1519 | 883 | 810 | n/a | | Number of blastocysts per patient, Median (IQR) | 2 (0-4) | 2 (0-5) | 1 (0-4) | 2 (0-5) | 0.02c | | Average patient-level blastocyst rate (Mean ± SD) | 0.32 ± 0.29 | 0.32 ± 0.30 | 0.28 ± 0.28 | 0.38 ± 0.30 | <0.001a | aOneway ANOVA cKruskal-Wallis equality-of-populations rank test for comparisons among three racial groups Table 3. | Overall (N=1134) | Caucasian (N=534) | Asian (not Indian) (N=352) | Indian (N=248) | P-value | | |---|---|---|---|---|---| | Total number of embryos (2PNs) | ||||| | Normal or Underweight | 5287 | 2808 | 1789 | 690 | n/a | | Overweight | 1628 | 656 | 571 | 401 | | | Obese | 1351 | 465 | 153 | 733 | | | Number of 2PNs per patient, Median (IQR) | ||||| | Normal or Underweight | 6 (3-10) | 6 (3-11) | 10 (3-10) | 6 (4-11) | 0.60c | | Overweight | 6 (4-10) | 6 (4-9) | 6 (4-9) | 7 (4-11) | 0.23c | | Obese | 6 (3-10) | 6 (3-11) | 5 (3-7) | 6 (3-10) | 0.33c | | Total number of cleaved embryos | ||||| | Normal or Underweight | 5197 | 2773 | 1750 | 674 | n/a | | Overweight | 1585 | 644 | 554 | 387 | | | Obese | 1308 | 452 | 149 | 707 | | | Number of cleaved embryos per patient, Median (IQR) | ||||| | Normal or Underweight | 6 (3-10) | 6 (3-10) | 6 (3-10) | 6 (4-11) | 0.61c | | Overweight | 6 (4-9) | 6 (4-9) | 6 (4-9) | 7 (4-11) | 0.35c | | Obese | 6 (3-10) | 6 (3-11) | 5 (3-7) | 6 (3-10) | 0.33c | | Total number of blastocysts | ||||| | Normal or Underweight | 2126 | 1136 | 669 | 321 | n/a | | Overweight | 592 | 242 | 176 | 174 | | | Obese | 494 | 141 | 38 | 315 | | | Number of blastocysts per patient, Median (IQR) | ||||| | Normal or Underweight | 2 (0-5) | 2 (0-5) | 2 (0-4) | 2 (1-5) | 0.26c | | Overweight | 2 (0-4) | 1 (0-4) | 1 (0-4) | 3 (1-5) | 0.03c | | Obese | 1 (0-4) | 2 (0-4) | 0 (0-2) | 2 (0-5) | 0.03c | | Average patient-level blastocyst rate (Mean ± SD) | ||||| | Normal or Underweight | 0.33 ± 0.29 | 0.33 ± 0.29 | 0.31 ± 0.28 | 0.38 ± 0.29 | 0.10a | | Overweight | 0.30 ± 0.30 | 0.30 ± 0.32 | 0.25 ± 0.26 | 0.40 ± 0.30 | 0.02a | | Obese | 0.31 ± 0.30 | 0.28 ± 0.28 | 0.18 ± 0.24 | 0.36 ± 0.32 | 0.01a | aOneway ANOVA cKruskal-Wallis equality-of-populations rank test for comparisons among three racial groups Independent associations between blastocyst formation, race, and BMI are shown in Table 4. Race was not independently related to blastocyst formation after controlling for BMI and covariates (age, nulligravidity, infertility diagnoses, FSH dosage, number of oocytes retrieved, number of 2PN embryos). Specifically, comparing to Caucasian group, the adjusted OR for blastocyst development in Asian and Indian women was 0.85 (95% CI 0.72–1.00) and 1.15 (95% CI 0.95–1.38), respectively. Similarly, BMI was not independently associated with blastocyst formation neither. After adjusting for race and the same set of covariates, overweight (aOR 0.93; 95% CI 0.77–1.12) and obese (aOR 0.92; 95% CI 0.74–1.12) women had similar odds of blastocyst formation comparing to normal-weight women. Table 4. | Blastocyst Formation | ||| |---|---|---|---| | Racea | Adjusted OR (SE) | 95% CI | P-value | | Caucasian (ref) | 1.00 | || | Asian (not Indians) | 0.85 (0.07) | (0.72, 1.00) | 0.05 | | Indian (South Asian) | 1.15 (0.11) | (0.95, 1.38) | 0.15 | | BMIa | Adjusted OR (SE) | 95% CI | P-value | | Normal (ref) | 1.00 | || | Overweight | 0.93 (0.09) | (0.77, 1.12) | 0.44 | | Obese | 0.92 (0.10) | (0.74, 1.12) | 0.40 | aBesides BMI and race, model additionally adjsuted for women's age, nulligravida, infertility, number of embryos, number of oocytes, and FSH dosage Table 5 presents the joint effect of independent relationship of BMI and race on blastocyst development. Within Caucasian racial group, overweight (aOR 0.99; 95% CI 0.81–1.22) and obese (aOR 0.91; 95% CI 0.75–1.12) women had comparable odds of developing blastocysts compared to normal BMI group. Comparing to normal-weight Caucasian group, the adjusted OR for overweight and obese Asian women was 0.79 (95% CI 0.63–1.00) and 0.79 (95 CI 0.60–1.01), respectively, whereas the adjusted OR for Indian women was 1.06 (95% CI 0.83–1.37) and 1.05 (0.83–1.32). Results concluded from BMI categorized per Caucasian standards are presented in Appendix Tables 1, 2, 3, 4, and 5. Stratified associations based on race-specific BMI thresholds are included in Appendix Table 6. Table 2. | Outcomes | Overall (N=1134) | Caucasian (N=534) | Asian (not Indian) (N=352) | Indian (South Asian) (N=248) | P-value | |---|---|---|---|---|---| | Total number of embryos (2PNs) | 8266 | 3929 | 2513 | 1824 | n/a | | Number of embryos (2PNs), Median (IQR) | 6 (3-10) | 6 (3-10) | 6 (3-10) | 6 (3-11) | 0.39c | | Total number of cleaved embryos | 8090 | 3869 | 2453 | 1768 | n/a | | Number of cleaved embryos, Median (IQR) | 6 (3-10) | 6 (3-10) | 6 (3-9) | 6 (3-11) | 0.44c | | Total number of blastocysts | 3212 | 1519 | 883 | 810 | n/a | | Number of blastocysts, Median (IQR) | 2 (0-4) | 2 (0-5) | 1 (0-4) | 2 (0-5) | 0.02c | | Average patient-level blastocyst rate (%) | 32.0% | 31.7% | 28.4% | 38.6% | <0.001a | aoneway ANOVA cKruskal-Wallis equality-of-populations rank test for comparisons among three racial groups Table 3. | Overall (N=1134) | Caucasian (N=534) | Asian (not Indian) (N=352) | Indian (N=248) | P-value | | |---|---|---|---|---|---| | Total number of embryos (2PNs) | ||||| | Normal or Underwieight | 6016 | 2808 | 2103 | 1105 | n/a | | Overweight | 1499 | 656 | 332 | 511 | | | Obese | 751 | 465 | 78 | 208 | | | Number of 2PNs per patient, Median (IQR) | ||||| | Normal or Underwieight | 6 (3-10) | 6 (3-11) | 10 (3-10) | 6 (4-11) | 0.18c | | Overweight | 6 (3-10) | 6 (4-9) | 6 (3-10) | 6 (3-11) | 0.86c | | Obese | 6 (3-9) | 6 (3-11) | 5 (4-8) | 5 (3-7) | 0.41c | | Total number of cleaved embryos | ||||| | Normal or Underwieight | 5899 | 2773 | 2051 | 1075 | n/a | | Overweight | 1458 | 644 | 324 | 490 | | | Obese | 733 | 452 | 78 | 203 | | | Number of cleaved embryos per patient, Median (IQR) | ||||| | Normal or Underwieight | 6 (3-10) | 6 (3-10) | 6 (3-10) | 6 (4-11) | 0.22c | | Overweight | 6 (3-9) | 6 (4-9) | 6 (3-9) | 6 (3-11) | 0.94c | | Obese | 6 (3-9) | 6 (3-11) | 5 (4-8) | 4 (3-7) | 0.39c | | Total number of blastocysts | ||||| | Normal or Underwieight | 2400 | 1136 | 762 | 502 | n/a | | Overweight | 564 | 242 | 104 | 218 | | | Obese | 248 | 141 | 17 | 90 | | | Number of blastocysts per patient, Median (IQR) | ||||| | Normal or Underwieight | 2 (0-5) | 2 (0-5) | 1 (0-4) | 2 (1-5) | 0.03c | | Overweight | 2 (0-4) | 1 (0-4) | 1 (0-3) | 2 (0-5) | 0.36c | | Obese | 1 (0-4) | 2 (0-4) | 0 (0-2) | 1 (0-5) | 0.23c | | Average patient-level blastocyst rate (Mean ± SD) | ||||| | Normal or Underwieight | 0.33 ± 0.29 | 0.33 ± 0.29 | 0.29 ± 0.28 | 0.39 ± 0.29 | 0.01a | | Overweight | 0.31 ± 0.31 | 0.30 ± 0.32 | 0.25 ± 0.26 | 0.36 ± 0.31 | 0.18a | | Obese | 0.29 ± 0.30 | 0.28 ± 0.28 | 0.16 ± 0.24 | 0.36 ± 0.33 | 0.11a | aone-way ANOVA cKruskal-Wallis equality-of-populations rank test for comparisons among three racial groups Table 4. | Blastocyst Formation | ||| |---|---|---|---| | Racea | Adjusted OR (SE) | 95% CI | P-value | | Caucasian (ref) | 1.00 | || | Asian (excludes Indians) | 0.85 (0.07) | (0.72, 1.00) | 0.05 | | Indian | 1.12 (0.10) | (0.94, 1.34) | 0.20 | | BMIa | Adjusted OR (SE) | 95% CI | P-value | | Normal (ref) | 1.00 | || | Overweight | 0.89 (0.09) | (0.74, 1.08) | 0.24 | | Obese | 0.99 (0.14) | (0.75, 1.30) | 0.92 | abesides BMI and race, model additionally adjsuted for women's age, nulligravida, infertility, number of embryos, number of oocytes, and FSH dosage Table 5. | (aOR, 95% CI) | Blastocyst Formationa | || |---|---|---|---| | Race | ||| | BMI | Caucasian | Asian (not Indians) | Indian (South Asian) | | Normal (ref) | 1.00 | 0.85 (0.72, 1.00) | 1.12 (0.94, 1.34) | | Overweight | 0.89 (0.74, 1.08) | 0.76 (0.59, 0.98) | 1.00 (0.79, 1.27) | | Obese | 0.99 (0.75, 1.30) | 0.84 (0.60, 1.17) | 1.11 (0.80, 1.54) | amodel additionally adjsuted for women's age, nulligravida, infertility, number of embryos, number of oocytes, and FSH dosage Table 6. | Caucasian | Asian (not Indians) | Indian (South Asian) | |||| |---|---|---|---|---|---|---| | aOR (95% CI) | P-value | aOR (95% CI) | P-value | aOR (95% CI) | P-value | | | Normal BMI (ref) | 1.0 | 1.0 | 1.0 | ||| | Overweight | 0.95 (0.70, 1.28) | 0.73 | 0.88 (0.65, 1.18) | 0.40 | 1.05 (0.70, 1.58) | 0.80 | | Obese | 0.92 (0.65, 1.32) | 0.67 | 0.80 (0.49, 1.30) | 0.37 | 1.00 (0.73, 1.37) | 0.98 | | Normal BMI | Overweight | Obese | |||| | aOR (95% CI) | P-value | aOR (95% CI) | P-value | aOR (95% CI) | P-value | | | Caucasian (ref) | 1.0 | 1.0 | 1.0 | ||| | Asian (not Indians) | 0.87 (0.72, 1.05) | 0.15 | 0.77 (0.53, 1.14) | 0.19 | 0.83 (0.43, 1.60) | 0.58 | | Indian (South Asian) | 1.12 (0.89, 1.41) | 0.34 | 1.21 (0.75, 1.94) | 0.44 | 1.18 (0.76, 1.82) | 0.47 |

To the best of our knowledge, this is the first study to examine the effects of Asian versus Caucasian race and across body mass index categories on blastocyst formation rate in vitro. We found that blastocyst formation in general did not differ by BMI and female race. These findings suggest that racial differences in IVF success rate as seen in previous reports are unlikely to be due to racial differences in the development of the embryos in vitro. We chose to focus on race because multiple studies have shown disparities in cycle treatment and pregnancy outcomes among different racial or ethnicity groups [2, 4, 30–35]. For example, either reduced intrauterine pregnancy rate or live birth rate has been noted for Asian, Black, and Hispanic women following IVF cycles in comparison to Caucasians [2–4]. Given known disparities in IVF success rates, we hypothesized that blastocyst formation may vary by race. However, in our study, we observe that odds of blastocyst development were similar comparing Asian or Indian women to Caucasian population in fresh IVF cycles after controlling for BMI and common confounders. This suggests that the underlying explanation for varied ART outcomes could be factors upstream of blastocyst development, such as different responses to ovarian stimulation [36] or factors downstream of blastocyst development, such as blastocyst quality or endometrial receptivity. One study demonstrates that, compared to Caucasians, Indian women show a lower live birth rate with transfer of similar quality blastocysts in fresh cycles but no difference with frozen embryo transfer [32]. This finding, in conjunction with our results, further suggests that endometrial receptivity may also play a role in varied success rates between Indians and Caucasians rather than racial difference per se, and in vitro embryo development is less likely to be the mechanism for racial disparities in ART outcomes. In addition to race, we assessed the independent effect of BMI on blastocyst development in consideration of documented adverse effects of obesity on the outcomes of IVF cycles. Clinical pregnancy rate and live birth rate following IVF treatment are significantly reduced among women who are overweight or obese [37–41]. Abnormal BMI has also been shown to be an independent predictor of abnormally high level of oxidized low-density lipoprotein (oxLDL) and catalase in follicular fluid; both parameters suggest varied levels of oxidative stress in oocytes and could subsequently compromise oocyte and embryo quality [15]. Very limited research has directly evaluated the impacts of abnormal BMI on blastocyst formation. One smaller study (N = 120) which was conducted by Comstock et al concluded that in vitro blastocyst formation is impacted by BMI; specifically, overweight and obese women have lower blastocyst formation rates compared with women with normal weight [42]. Our study with much larger sample size does not conclude the independent relationship between BMI and blastocyst formation. One possible explanation could be the different outcome definitions. In Comstock et al. study, blastocyst formation rate was defined as the number of good quality blastocysts (3BB or greater) divided by the number of ≥ 5 cell embryos on day 3. Lastly, we evaluated the joint effects of race and BMI. Although no interaction was noticed, we assessed the combined independent effects of race and BMI, and our data do not suggest that overweight or obese Asian or Indian women have decreased odds of blastocyst development in comparison to Caucasian women with normal BMI. To the best of our knowledge, there is no existing research focusing on the association between blastocyst formation and sociodemographic factors. Luke et al.’s study [43] noted racial disparities for IVF outcomes of clinical intrauterine pregnancy and live birth rate within BMI categories. For example, comparing to Caucasian women within the same BMI category, obese Asian women have higher risks of negative intrauterine pregnancy (aOR 1.73; 95% CI 1.21–2.47) and failure of live birth (aOR 2.20; 95% CI 1.18–4.08). In light of comparable results between obese Asian women and normal BMI Caucasian women demonstrated in our study, we suggest that the disparities of ART outcomes by race reported by Luke et al. may be the result of factors other than racial differences in blastocyst formation rate in vitro. Our study has several strengths. This is the first study to examine blastocyst formation within race and BMI categories among infertile women. Second, to ensure the accuracy of the key outcome measure in our study, blastocyst formation was assessed from embryos cultured and graded under the same conditions in the laboratory by embryologists using standard morphologic criteria while being blinded to the patient’s BMI. Furthermore, we place a special focus on Indian race, in consideration of well-documented disparities in reproductive health outcomes among Indian women comparing to women from other Asian backgrounds and Caucasians [35, 44, 45] and the prominent proportion of Indian women in our study population in relation to other Asian races, which grants us with the opportunity to test the hypothesis. The present work also has limitations. Because of the study design, we lack information on other potential confounders including race and weight of male partner and other female factors, such as insulin resistance, which are more predictive of oocyte and embryo quality leading up to the formation of a blastocyst. Likewise, due to data unavailability, we could not account for the possible effects of embryonic genetic defects on blastocyst development, which could have a potential impact on the results. In addition, BMI was calculated based on clinically measured height and weight collected at women’s first clinic visit. We could not monitor possible weight changes overtime, which could introduce fluctuations in BMI distribution in our study. Considering the difficulty of accurately defining races and the existing heterogeneities within the same race, it is challenging to obtain unbiased conclusions, which might render our results open to subjectivity. Live birth rate is ultimately the outcome of most importance for patients. We chose to focus on blastocyst formation rate for this study, because live birth rate can be influenced by many other patient factors. Future larger studies, with greater power to account for the many maternal factors which influence live birth rate, should ideally include live birth rate as well as blastocyst formation rate. Although our study is one of the largest to examine the potential relationship between race, BMI, and blastocyst formation rate, it is possible that our failure to detect a difference in blastocyst formation rates between groups was due to insufficient sample size. Further studies on this topic are warranted. In conclusion, we found that blastocyst formation rate does not differ by female race and BMI. Given the limitations of our retrospective analysis, further studies are warranted. Appendices Funding information We would like to acknowledge support for power analysis on clustered data in the revision of this manuscript from the National Center for Research Resources and the National Center for Advancing Translational Sciences (NCATS) of the National Institutes of Health through Grant Number 1UL1TR001079. Footnotes Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. Rucha Khunte* and Mengmeng Li* contributed equally to this work.

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