Effect of body mass index on ovarian reserve and ART outcomes in infertile women: a large retrospective study.

Table  3 compared embryo outcomes across various BMI groups. In both the overall cohort and the age subgroups of 20–30 years and 30–35 years, we observed a decline in the number of oocytes retrieved, mature oocytes, and 2PNs with increasing BMI. However, for patients aged 35–45 years, no significant differences were found among the BMI groups. For patients aged 20–30 years, the overweight group showed a substantial reduction in the quality of transferred embryos compared to the normal weight group, which aligned with trends observed in the overall population. Despite variations in fertilization and blastocyst formation rates in the overall population, there were no significant differences across BMI groups after age stratification. Table 3 Embryo and pregnancy outcomes of each BMI group Age category Parameter Lean < 18.5 (kg/m 2 ) Normal weight 18.5–24.9 (kg/m 2 ) Overweight 25-29.9 (kg/m 2 ) Obese ≥ 30 (kg/m 2 ) P value Overall No. of oocytes retrieved 12.0 (7.0, 17.0) * 11.0 (7.0, 16.0) 10.0 (6.0, 15.0) * 9.0 (5.0, 14.0) * < 0.001 No. of mature oocytes 10.0 (6.0, 15.0) * 9.0 (6.0, 14.0) 9.0 (5.0, 13.0) * 8.0 (5.0, 12.0) * < 0.001 No. of 2PNs 7.0 (4.0, 11.0) * 6.0 (4.0, 10.0) 6.0 (3.0, 9.0) * 5.0 (3.0, 8.0) * < 0.001 Normal fertilization rate (%) 66.7 (52.9, 80.0) 66.7 (50.0, 80.0) 66.7 (50.0, 80.0) * 64.3 (50.0, 80.0) < 0.001 Blastocyst formation rate (%) 71.4 (50.0, 87.5) 68.4 (50.0, 86.7) 66.7 (42.9, 85.7) * 75.0 (50.0, 90.9) < 0.001 Embryo quality, n (%) < 0.001 High-quality embryos 1450 (84.9) 10,980 (84.1) 2019 (80.7) * 208 (86.0) Low-quality embryos 258 (15.1) 2073 (15.9) 482 (19.3) 34 (14.0) Implantation rate (%) 44.8 (1046/2334) 45.2 (7820/17290) 46.7 (1515/3246) 53.3 (153/287) * 0.020 Clinical pregnancy rate (%) 52.0 (888/1708) 52.4 (6847/13061) 52.5 (1314/2502) 58.7 (142/242) 0.271 Biochemical pregnancy rate (%) 4.8 (82/1708) 5.7 (739/13061) 6.1 (152/2502) 5.4 (13/242) 0.363 Ongoing pregnancy rate (%) 46.4 (793/1708) 45.6 (5960/13061) 45.2 (1132/2502) 52.5 (127/242) 0.167 Ectopic pregnancy rate (%) 0.8 (13/1708) 0.8 (104/13061) 0.9 (23/2502) 0 (0/242) 0.487 Miscarriage rate (%) 11.1 (99/888) 13.4 (920/6847) 14.5 (191/1314) 13.4 (19/142) 0.148 Live birth rate (%) 46.2 (721/1561) 45.0 (5289/11761) 44.0 (957/2174) 46.5 (93/200) 0.590 20–30 years No. of oocytes retrieved 14.0 (9.0, 19.0) 13.0 (9.0, 18.0) 13.0 (9.0, 17.0) * 10.5 (7.0, 17.0) * < 0.001 No. of mature oocytes 11.0 (7.0, 16.0) 11.0 (8.0, 16.0) 11.0 (7.0, 15.0) * 9.0 (5.0, 13.0) * < 0.001 No. of 2PNs 8.0 (5.0, 12.0) 8.0 (5.0, 11.0) 7.0 (4.0, 10.0) * 6.0 (3.0, 9.0) * < 0.001 Normal fertilization rate (%) 66.7 (53.3, 80.0) 66.7 (50.0, 80.0) 65.0 (50.0, 78.6) 63.4 (50.0, 78.4) 0.006 Blastocyst formation rate (%) 70.0 (50.0, 87.5) 70.0 (50.0, 85.7) 69.6 (50.0, 85.7) 72.7 (50.0, 90.9) 0.406 Embryo quality, n (%) < 0.001 High-quality embryos 869 (85.6) 5207 (85.4) 867 (79.7) * 96 (86.5) Low-quality embryos 146 (14.4) 892 (14.6) 221 (20.3) 15 (13.5) Implantation rate (%) 47.3 (664/1403) 49.1 (4024/8188) 51.8 (739/1426) 54.7 (75/137) 0.057 Clinical pregnancy rate (%) 55.2 (560/1015) 56.9 (3471/6101) 58.1 (632/1088) 61.3 (68/111) 0.436 Biochemical pregnancy rate (%) 5.0 (51/1015) 5.5 (335/6101) 6.7 (73/1088) 7.2 (8/111) 0.280 Ongoing pregnancy rate (%) 50.8 (516/1015) 51.2 (3126/6101) 50.5 (549/1088) 55.0 (61/111) 0.823 Ectopic pregnancy rate (%) 0.5 (5/1015) 0.8 (47/6101) 1.3 (14/1088) 0 (0/111) 0.141 Miscarriage rate (%) 8.8 (49/560) 10.7 (372/3471) 12.5 (79/632) 11.8 (8/68) 0.218 Live birth rate (%) 50.8 (482/948) 50.2 (2822/5616) 49.3 (472/957) 48.9 (45/92) 0.915 30–35 years No. of oocytes retrieved 11.0 (7.0, 16.0) 11.0 (7.0, 16.0) 11.0 (7.0, 15.0) * 9.0 (5.0, 13.0) * < 0.001 No. of mature oocytes 9.0 (6.0, 14.0) 10.0 (6.0, 14.0) 9.0 (6.0, 13.0) * 8.0 (5.0, 11.5) * < 0.001 No. of 2PNs 7.0 (4.0, 10.0) 7.0 (4.0, 10.0) 6.0 (4.0, 10.0) 5.0 (3.0, 8.0) < 0.001 Normal fertilization rate rate (%) 68.4 (53.8, 81.8) 66.7 (50.0, 80.0) 66.7 (50.0, 80.0) * 64.3 (50.0, 77.8) * 0.016 Blastocyst formation rate (%) 75.0 (50.0, 88.9) 71.4 (50.0, 87.5) 66.7 (50.0, 85.7) 75.0 (51.3, 93.0) 0.015 Embryo quality, n (%) 0.322 High-quality embryos 472 (84.7) 4192 (83.0) 783 (81.6) 84 (86.6) Low-quality embryos 85 (15.3) 857 (17.0) 177 (18.4) 13 (13.4) Implantation rate (%) 43.7 (324/742) 45.8 (2986/6516) 49.4 (605/1224) 54.6 (59/108) 0.015 Clinical pregnancy rate (%) 49.7 (277/557) 52.5 (2652/5052) 54.4 (522/960) 57.7 (56/97) 0.251 Biochemical pregnancy rate (%) 5.0 (28/557) 6.0 (301/5052) 4.4 (42/960) 5.2 (5/97) 0.233 Ongoing pregnancy rate (%) 43.6 (243/557) 45.1 (2278/5052) 47.2 (453/960) 53.6 (52/97) 0.189 Ectopic pregnancy rate (%) 1.1 (6/557) 0.9 (44/5052) 0.7 (7/960) 0 (0/97) 0.716 Miscarriage rate (%) 12.3 (34/277) 14.1 (374/2652) 14.6 (76/522) 10.7 (6/56) 0.718 Live birth rate (%) 42.4 (208/491) 45.1 (1983/4399) 46.8 (379/809) 48.7 (38/78) 0.409 35–45 years No. of oocytes retrieved 6.0 (4.0, 11.0) 7.0 (4.0, 11.0) 7.0 (4.0, 11.0) 7.0 (3.0, 12.0) 0.907 No. of mature oocytes 5.0 (3.0, 9.0) 6.0 (3.0, 10.0) 6.0 (3.0, 9.0) 5.0 (3.0, 9.5) 0.960 No. of 2PNs 3.0 (2.0, 7.0) 4.0 (2.0, 7.0) 4.0 (2.0, 7.0) 4.0 (2.0, 7.0) 0.788 Normal fertilization rate (%) 66.7 (50.0, 83.3) 66.7 (50.0, 83.3) 66.7 (50.0, 81.8) 66.7 (50.0, 83.3) 0.158 Blastocyst formation rate (%) 60.0 (40.0, 84.3) 62.5 (33.3, 85.7) 60.0 (33.3, 83.3) 75.0 (24.7, 83.8) 0.555 Embryo quality, n (%) 0.758 High-quality embryos 109 (80.1) 1581 (83.0) 369 (81.5) 28 (82.4) Low-quality embryos 27 (19.9) 324 (17.0) 84 (18.5) 6 (17.6) Implantation rate (%) 30.7 (58/189) 31.3 (810/2586) 28.7 (171/596) 45.2 (19/42) 0.133 Clinical pregnancy rate (%) 37.5 (51/136) 37.9 (724/1908) 35.2 (160/454) 52.9 (18/34) 0.205 Biochemical pregnancy rate (%) 2.2 (3/136) 5.4 (103/1908) 8.1 (37/454) 0 (0/34) 0.014 Ongoing pregnancy rate (%) 25.0 (34/136) 29.1 (556/1908) 28.6 (130/454) 41.2 (14/34) 0.314 Ectopic pregnancy rate (%) 1.5 (2/136) 0.7 (13/1908) 0.4 (2/454) 0 (0/34) 0.594 Miscarriage rate (%) 31.4 (16/51) 24.0 (174/724) 22.5 (36/160) 27.8 (5/18) 0.611 Live birth rate (%) 25.4 (31/122) 27.7 (484/1746) 26.0 (106/408) 33.3 (10/30) 0.735 Note   BMI body mass index; 2PN two pronuclei * P  < .05 as compared with the normal weight group Embryo and pregnancy outcomes of each BMI group Note   BMI body mass index; 2PN two pronuclei * P  < .05 as compared with the normal weight group The results of multiple linear regression analysis about embryo outcomes were shown in Supplemental Table 4 . In the overall cohort, the number of oocytes retrieved, mature oocytes, and 2PNs was significantly lower in the overweight group compared to the normal weight group. This trend persisted across the age subgroups of 20–30 and 30–35 years. However, in the 35–45 years age subgroup, only the number of 2PNs showed a significant decline in the overweight group when compared to their normal weight counterparts. Regarding blastocyst formation, a significant reduction was observed in the overall overweight and obese groups compared to the normal weight group. When analyzed by age strata, the obese group in the 20–30 years category showed a notably lower rate of blastocyst formation. In the 30–35 years subgroup, a significant decrease was observed only in the overweight group. Notably, among participants aged 35–45 years, there were no significant differences in blastocyst formation rates across all BMI categories. Table  3 also presented the pregnancy outcomes across different BMI groups.No statistically significant differences were found in the rates of clinical pregnancy, biochemical pregnancy, ongoing pregnancy, miscarriage, or live birth among the BMI groups within each age stratum. After accounting for potential confounding factors, multivariate logistic regression analysis was conducted to explore the impact of BMI on pregnancy outcomes (Supplemental Table 5 ). In the overall cohort, the obese group exhibited higher rates of clinical pregnancy and ongoing pregnancy compared to those with normal weight (clinical pregnancy: aOR = 1.424; 95% CI, 1.093–1.856; ongoing pregnancy: aOR = 1.474; 95% CI, 1.133–1.916). However, in the age subgroup analysis, significant differences were observed only in the individuals aged 30–35 years (aOR = 1.654; 95% CI, 1.093–2.502). Additionally, the risk of ectopic pregnancy in the overweight group (aOR = 1.919; 95% CI, 1.042–3.536) was significantly higher compared to those with normal weight in the 20–30 years age subgroup. Whether in all cycles or subgroup cycles analysis, biochemical pregnancy, miscarriage, and live birth rates were not associated with BMI after adjustment for confounders. The study analyzed a cohort of 5,721 patients with singleton pregnancies and live births to evaluate perinatal outcomes (Table  4 ). Singleton pregnancies among overweight or obese women showed a higher likelihood of cesarean delivery. Additionally, birth weight increased significantly across all overweight categories, leading to higher prevalence of macrosomia. Overweight and obese individuals had a greater incidence of poor maternal outcomes, such as gestational diabetes mellitus and gestational hypertension, compared to individuals with normal weight across all age subgroups. Within the age subgroup of 30–35 years, the incidence of placenta previa was significantly lower in the overweight group compared to the normal weight group. Table 4 Perinatal outcomes of each BMI group Age category Parameter Lean < 18.5 (kg/m 2 ) Normal weight 18.5–24.9 (kg/m 2 ) Overweight 25-29.9 (kg/m 2 ) Obese ≥ 30 (kg/m 2 ) P value Overall Number of patients 563 4313 763 82 Gestational age (w) 39.0 (38.3, 39.7) 39.0 (38.3, 39.6) 39.0 (38.0, 39.6) 38.8 (37.7, 39.1) * 0.002 Mode of delivery, n (%) < 0.001 Vaginal 201 (35.7) * 1251 (29.0) 151 (19.8) * 7 (8.5) * Cesarean section 362 (64.3) * 3062 (71.0) 612 (80.2) * 75 (91.5) * PTB (< 37w) 38 (6.7) 271 (6.3) 58 (7.6) 10 (12.2) 0.105 Very PTB (< 32w) 1 (0.2) 27 (0.6) 8 (1.0) 0 0.212 Sex, n (%) 0.402 Male 317 (56.3) 2286 (53.0) 416 (54.5) 41 (50.0) Female 246 (43.7) 2027 (47.0) 347 (45.5) 41 (50.0) Birthweight, g 3100.0 (2900.0, 3400.0) * 3250.0 (3000.0, 3550.0) 3400.0 (3100.0, 3700.0) * 3300.0 (3117.5, 3762.5) < 0.001 LBW ( 4000 g), n (%) 14 (2.5) 157 (3.6) 63 (8.3) * 13 (15.9) * < 0.001 Placenta previa, n (%) 17 (3.0) 113 (2.6) 14 (1.8) 3 (3.7) 0.469 HDP, n (%) 5 (0.9) 78 (1.8) 51 (6.7) * 7 (8.5) * < 0.001 GDM, n (%) 16 (2.8) 208 (4.8) 72 (9.4) * 8 (9.8) < 0.001 20–30 years Number of patients 377 2265 366 37 Gestational age (w) 39.0 (38.3, 39.7) 39.0 (38.3, 39.7) 39.0 (38.0, 39.7) 38.6 (37.5, 39.1) * 0.010 Mode of delivery, n (%) < 0.001 Vaginal 144 (38.2) 724 (32.0) 73 (19.9) * 2 (5.4) * Cesarean section 233 (61.8) 1541 (68.0) 293 (80.1) * 35 (94.6) * PTB (< 37w) 19 (5.0) 131 (5.8) 23 (6.3) 5 (13.5) 0.209 Very PTB (< 32w) 1 (0.3) 13 (0.6) 2 (0.5) 0 0.852 Sex, n (%) 0.657 Male 213 (56.5) 1212 (53.5) 198 (54.1) 22 (59.5) Female 164 (43.5) 1053 (46.5) 168 (45.9) 15 (40.5) Birthweight, g 3100.0 (2900.0, 3400.0) * 3300.0 (3000.0, 3550.0) 3400.0 (3100.0, 3700.0) * 3300.0 (3200.0, 4025.0) < 0.001 LBW ( 4000 g), n (%) 8 (2.1) 86 (3.8) 32 (8.7) * 9 (24.3) * < 0.001 Placenta previa, n (%) 10 (2.7) 50 (2.2) 4 (1.1) 0 0.350 HDP, n (%) 2 (0.5) 40 (1.8) 17 (4.6) * 3 (8.1) * < 0.001 GDM, n (%) 10 (2.7) 88 (3.9) 23 (6.3) 5 (13.5) * 0.002 30–35 years Number of patients 161 1652 302 36 Gestational age (w) 39.0 (38.1, 39.7) 39.0 (38.3, 39.6) 39.0 (38.0, 39.6) 39.0 (38.0, 39.3) 0.344 Mode of delivery, n (%) 0.001 Vaginal 51 (31.7) 454 (27.5) 56 (18.5) * 4 (11.1) Cesarean section 110 (68.3) 1198 (72.5) 246 (81.5) * 32 (88.9) PTB (< 37w) 14 (8.7) 99 (6.0) 26 (8.6) 3 (8.3) 0.232 Very PTB (< 32w) 0 11 (0.7) 6 (2.0) 0 0.060 Sex, n (%) 0.337 Male 93 (57.8) 871 (52.7) 159 (52.6) 15 (41.7) Female 68 (42.2) 781 (47.3) 143 (47.4) 21 (58.3) Birthweight, g 3150.0 (2900.0, 3400.0) * 3255.0 (3000.0, 3500.0) 3400.0 (3097.5, 3700.0) * 3345.0 (3000.0, 3637.5) < 0.001 LBW ( 4000 g), n (%) 6 (3.7) 57 (3.5) 24 (7.9) * 4 (11.1) 0.001 Placenta previa, n (%) 4 (2.5) 50 (3.0) 6 (2.0) 3 (8.3) 0.186 HDP, n (%) 3 (1.9) 28 (1.7) 22 (7.3) * 2 (5.6) < 0.001 GDM, n (%) 6 (3.7) 99 (6.0) 34 (11.3) * 3 (8.3) 0.003 35–45 years Number of patients 25 396 95 9 Gestational age (w) 38.9 (37.7, 39.1) 38.7 (38.0, 39.1) 38.7 (38.0, 39.4) 38.0 (36.9, 39.1) 0.618 Mode of delivery, n (%) 0.609 Vaginal 6 (24.0) 73 (18.4) 22 (23.2) 1 (11.1) Cesarean section 19 (76.0) 323 (81.6) 73 (76.8) 8 (88.9) PTB (< 37w) 5 (20.0) 41 (10.4) 9 (9.5) 2 (22.2) 0.302 Very PTB (< 32w) 0 3 (0.8) 0 0 0.805 Sex, n (%) 0.195 Male 11 (44.0) 203 (51.3) 59 (62.1) 4 (44.4) Female 14 (56.0) 193 (48.7) 36 (37.9) 5 (55.6) Birthweight, g 3100.0 (2625.0, 3285.0) 3200.0 (2935.0, 3500.0) 3400.0 (3100.0, 3680.0) * 3150.0 (2975.0, 3445.0) < 0.001 LBW ( 4000 g), n (%) 0 14 (3.5) 7 (7.4) 0 0.217 Placenta previa, n (%) 3 (12.0) 13 (3.3) 4 (4.2) 0 0.153 HDP, n (%) 0 10 (2.5) 12 (12.6) * 2 (22.2) * < 0.001 GDM, n (%) 0 21 (5.3) 15 (15.8) * 0 0.001 Note   BMI body mass index; PTB preterm birth; HDP hypertensive disorders of pregnancy; GDM gestational diabetes mellitus; LBW low birth weight * P  < .05 as compared with the normal weight group Perinatal outcomes of each BMI group Note   BMI body mass index; PTB preterm birth; HDP hypertensive disorders of pregnancy; GDM gestational diabetes mellitus; LBW low birth weight * P  < .05 as compared with the normal weight group A multivariate logistic regression analysis was conducted to assess the influence of BMI on pregnancy outcomes, adjusting for confounding factors such as maternal age, years of infertility, number and type of embryos transferred, and cause of infertility (Supplemental Table 6 ). No significant differences in perinatal outcomes were observed between the lean and normal groups, except regarding the mode of delivery. In the overall cohort, both the overweight and obese groups showed higher rates of macrosomia (overweight group: aOR = 2.398; 95% CI, 1.762–3.262; obese group: aOR = 5.238; 95% CI, 2.806–9.779), gestational hypertension (overweight group: aOR = 3.873; 95% CI, 2.687–5.581; obese group: aOR = 5.633; 95% CI, 2.482–12.786), and gestational diabetes mellitus (overweight group: aOR = 2.025; 95% CI, 1.526–2.688; obese group: aOR = 2.315; 95% CI, 1.092–4.909) compared to the normal weight group. For individuals aged 20–30 years, both the overweight and obese groups had an increased risk of macrosomia (overweight group: aOR = 2.368; 95% CI, 1.537–3.649; obese group: aOR = 8.710; 95% CI, 3.885–19.529), gestational hypertension (overweight group: aOR = 2.729; 95% CI, 1.522–4.895; obese group: aOR = 4.591; 95% CI, 1.317- 16.000), and gestational diabetes mellitus (overweight group: aOR = 1.647; 95% CI, 1.020–2.659; obese group: aOR = 4.402; 95% CI, 1.627–11.914).Among individuals aged 30–35 years, both overweight and obese groups had an increased risk of macrosomia (overweight group: aOR = 2.487; 95% CI, 1.505–4.109; obese group: aOR = 3.752; 95% CI, 1.257–11.201) and gestational hypertension (overweight group: aOR = 4.682; 95% CI, 2.610–8.398; obese group: aOR = 4.545; 95% CI, 1.011–20.440), while only the overweight group demonstrated a significantly higher risk of gestational diabetes mellitus (aOR = 1.953; 95% CI, 1.286–2.964). For individuals aged 35–45 years, both the overweight and obese groups had a significantly higher prevalence of gestational hypertension (overweight group: aOR = 5.580; 95% CI, 2.395–14.291; obese group: aOR = 10.503; 95% CI, 1.669–66.107). However, the incidence of gestational diabetes mellitus was notably higher only in the overweight group (aOR = 3.525; 95% CI, 1.720–7.225) compared to individuals with normal weight. Additionally, the risk of very preterm birth in the overweight group (aOR = 2.808; 95% CI, 1.005–7.841) and the risk of placenta previa in the obese group (aOR = 3.854; 95% CI, 1.094–13.571) was significantly higher compared to those with normal weight in the age subgroup of 30–35 years.

A total of 30,746 first fresh cycles were included at our center between January 2016 and May 2023. It was categorized into four groups based on pre-pregnancy BMI: 3,072 cycles in the lean group, 22,996 in the normal group, 4,272 in the overweight group, and 406 in the obese group. Table  1 displayed the baseline characteristics of infertile patients across the different BMI groups. Significant differences were observed among the groups in various characteristics, including age, BMI, duration of infertility, type of infertility, basal sex hormone levels, surgical procedures, ovarian stimulation protocols, and the dose and duration of gonadotropin treatment. Table 1 Baseline characteristics of the study cycles (BMI categorization) Parameter Lean < 18.5 (kg/m 2 ) Normal weight 18.5–24.9 (kg/m 2 ) Overweight 25-29.9 (kg/m 2 ) Obese ≥ 30 (kg/m 2 ) P value Number of patients 3072 22,996 4272 406 Age (y) 30.0 (27.0, 33.0) * 31.0 (29.0, 35.0) 32.0 (29.0, 36.0) * 31.0 (28.0, 34.0) < 0.001 BMI (kg/m2) 17.8 (17.2, 18.3) * 21.4 (20.1, 22.9) 26.4 (25.6, 27.5) * 31.2 (30.5, 32.5) * < 0.001 Duration of infertility (y) 3.0 (2.0, 4.0) 3.0 (1.5, 4.0) 3.0 (2.0, 5.0) * 3.0 (2.0, 6.0) * < 0.001 Type of infertility, n (%) < 0.001 Primary infertility 2185 (71.1) * 14,087 (61.3) 2607 (61.0) 263 (64.8) Secondary infertility 887 (28.9) * 8908 (38.7) 1665 (39.0) 143 (35.2) Basal FSH (ng/mL) 7.8 (6.7, 9.3) 7.4 (6.3, 8.8) 7.1 (5.9, 8.4) 6.8 (5.8, 8.4) < 0.001 Basal LH (mIU/mL) 2.6 (1.6, 4.2) 2.7 (1.6, 4.5) 2.9 (1.7, 4.8) * 3.1 (1.9, 5.7) * < 0.001 Basal P (ng/mL) 0.9 (0.7, 1.2) * 0.8 (0.6, 1.1) 0.7 (0.5, 1.0) * 0.6 (0.4, 0.9) * < 0.001 Basal E2 (pg/mL) 2736.0 (1759.0, 4325.0) * 2223.0(1434.0, 3609.0) 1802.0(1178.0, 2808.5) * 1654.0(1096.0, 2474.0) * < 0.001 AMH level (ng/mL) 3.5 (2.0, 5.8) * 3.3 (1.8, 5.5) 3.0 (1.6, 5.0) * 2.6 (1.5, 4.4) * < 0.001 Main infertility factor, n (%) Female factor 1506 (49.0) * 12,384 (53.9) 2298 (53.8) 201 (49.5) < 0.001 Male factor 652 (21.2) * 3767 (16.4) 701 (16.4) 60 (14.8) Female and male factors 630 (20.5) 4791 (20.8) 880 (20.6) 97 (23.9) Unknown 284 (9.2) 2054 (8.9) 393 (9.2) 48 (11.8) Fertilization method, n (%) < 0.001 IVF 2032 (66.1) 15,732 (68.4) 2927 (68.5) 287 (70.7) ICSI 1040 (33.9) * 7264 (31.6) 1345 (31.5) 119 (29.3) Dose of Gn (IU) 4710.0 (3300.0, 6450.0) * 5100.0 (3750.0, 6900.0) 6000.0 (4350.0, 7800.0) * 6900.0 (5250.0, 9300.0) * < 0.001 Duration of Gn (d) 10.0 (9.0, 11.0) 10.0 (9.0, 11.0) 10.0 (9.0, 11.0) * 10.0 (9.0, 11.0) * < 0.001 Ovarian stimulation protocols, n (%) < 0.001 GnRH agonist 1709 (55.6) * 12,067 (52.5) 2032 (47.6) * 170 (41.9) * GnRH antagonist 1153 (37.5) * 8508 (37.0) 1766 (41.3) * 191 (47.0) * Others 210 (6.8) * 2421 (10.5) 474 (11.1) 45 (11.1) Endometrial thickness (mm) 11.1 (9.5, 12.8) 11.0 (9.3, 12.9) 11.2 (9.4, 13.1) * 11.0 (9.6, 12.8) < 0.001 No. of embryos transferred, n (%) < 0.001 1 1082 (63.3) * 8833 (67.6) 1758 (70.3) 197 (81.4) * 2 626 (36.7) * 4228 (32.4) 744 (29.7) 45 (18.6) * Embryo type transferred, n (%) 0.401 Cleavage embryo 1510 (88.4) 11,534 (88.3) 2248 (89.8) 218 (90.1) Blastocyst 198 (11.6) 1527 (11.7) 254 (10.2) 24 (9.9) Note   BMI body mass index; LH luteinizing hormone; P progesterone; E2 estradiol; Gn gonadotropin; IVF in vivo fertilization; ICSI intracytoplasmic sperm injection; AMH Anti Mullerian hormone * P  < 0.05 as compared with the normal weight group Baseline characteristics of the study cycles (BMI categorization) Note   BMI body mass index; LH luteinizing hormone; P progesterone; E2 estradiol; Gn gonadotropin; IVF in vivo fertilization; ICSI intracytoplasmic sperm injection; AMH Anti Mullerian hormone * P  < 0.05 as compared with the normal weight group Supplemental Fig.  1 shows AMH levels across different BMI groups within each age subgroup. Overall, AMH levels were significantly lower in the overweight and obese groups compared to the normal weight group ( P  < 0.001). Across all age subgroups, AMH levels generally decreased with increasing BMI, reaching statistical significance only in the age subgroups of 20–30 and 30–35 years. In contrast, AMH levels did not differ significantly among the groups for individuals aged 35–45 years ( P  = 0.430). Figure  1 illustrates the distribution of AMH relative to BMI across various age subgroups. BMI and AMH exhibited a significant negative correlation overall ( r = -0.070, P  < 0.001), as well as within the age subgroups of 20–30 years ( r = -0.037, P  < 0.001) and 30–35 years ( r = -0.050, P  < 0.001). Fig. 1 Changes in Anti-Müllerian hormone (AMH) levels with increasing body mass index (BMI) Changes in Anti-Müllerian hormone (AMH) levels with increasing body mass index (BMI) A multiple linear regression model adjusted for age was used to further assess the relationship between BMI and AMH (Table  2 ). Regardless of whether BMI was treated as a continuous or categorical variable, a significant negative correlation between BMI and AMH was observed overall and for women aged 20–30 years or 30–35 years (all P  ≤ 0.001). However, for individuals aged 35–45 years, no significant differences were found. Table 2 Multivariate linear regression analysis of the association between BMI and AMH Overall 20–30 years 30–35 years 35–45 years Parameter β (95% CI) P value β (95% CI) P value β (95% CI) P value β (95% CI) P value BMI (kg/m2) a -0.011 (-0.014, -0.008) < 0.001 -0.011 (-0.016, -0.007) < 0.001 -0.013 (-0.018, -0.008) < 0.001 -0.003 (-0.011, 0.005) 0.519 BMI category b Lean -0.022 (-0.054, 0.009) 0.167 -0.034 (-0.074, 0.006) 0.098 0.003 (-0.051, 0.057) 0.920 -0.030 (-0.134, 0.075) 0.579 Normal weight 0 (Reference) 0 (Reference) 0 (Reference) 0 (Reference) Overweight -0.063 (-0.090, -0.036) < 0.001 -0.079 (-0.120, -0.037) < 0.001 -0.075 (-0.120, -0.030) 0.001 -0.001 (-0.062, 0.060) 0.966 Obese -0.257 (-0.338, -0.176) < 0.001 -0.326 (-0.442, -0.211) < 0.001 -0.219 (-0.349, -0.088) 0.001 -0.184 (-0.395, 0.027) 0.087 Note   BMI body mass index; CI confidence interval; AMH Anti-Müllerian hormone The results of the multivariate linear regression analysis with AMH as the dependent variable and age and BMI as independent variables a BMI was analyzed as a continuous variable b BMI was analyzed as a categorical variable Multivariate linear regression analysis of the association between BMI and AMH Note   BMI body mass index; CI confidence interval; AMH Anti-Müllerian hormone The results of the multivariate linear regression analysis with AMH as the dependent variable and age and BMI as independent variables a BMI was analyzed as a continuous variable b BMI was analyzed as a categorical variable Among women aged 20–30 years, a modest yet significant difference in AFC was observed between the normal weight and lean groups(Supplemental Fig.  2 ). However, there were no significant differences in AFC between the overweight or obese group and the normal weight group across the overall cohort or within various age subgroups.

Obesity is a pervasive issue with a rising prevalence worldwide, posing a significant public health challenge. Epidemiological studies have consistently shown a strong association between obesity and chronic conditions such as diabetes and cardiovascular diseases [ 1 ]. Furthermore, obesity adversely affects reproductive health [ 2 ], disrupting sex hormone balance and causing dyslipidemia, which increases the risk of conditions such as polycystic ovary syndrome (PCOS), menstrual irregularities, diminished ovarian reserve, and insulin resistance [ 3 ]. Obesity has a direct and multifaceted impact on the outcomes of assisted reproductive technology (ART) in women experiencing infertility. This influence primarily arises from hormonal imbalances, reduced ovarian response, and impaired embryo implantation [ 3 ]. Numerous studies have consistently demonstrated that obesity is associated with lower rates of implantation, pregnancy, and live birth, as well as higher rates of miscarriage and adverse perinatal outcomes [ 4 – 7 ]. As a result, weight loss has been recommended to improve pregnancy outcomes in young, obese women, underscoring the potential benefits of managing body weight [ 5 ]. However, conclusions in the literature are not uniform, possibly due to variations in study designs and sample sizes. Some studies still suggest that a higher body mass index (BMI) in women does not have a negative impact on pregnancy outcomes following in vitro fertilization [ 8 ]. Excessive fat accumulation can disrupt the endocrine system, thereby interfering with normal ovarian function [ 3 ]. Ovarian reserve, which refers to the quantity and quality of oocytes, serves as a key indicator of reproductive potential and declines with age [ 9 ]. Clinically, markers such as Anti-Müllerian hormone (AMH) levels and Antral Follicle Count (AFC) are commonly used to assess ovarian reserve function and predict the outcomes of ART [ 10 ]. Several studies have explored the relationship between ovarian reserve and BMI. While some research indicates a negative correlation between AMH and BMI [ 11 , 12 ], others suggest a positive correlation [ 13 ], and still, other studies find no significant correlation [ 14 ]. The discrepancies among these findings may be attributed to the limited sample sizes. Understanding how obesity affects ovarian reserve and ART outcomes in infertile women is crucial for developing individualized treatment plans and improving success rates. To address this, we conducted a retrospective study examining the impact of pre-pregnancy BMI on ovarian reserve, as well as pregnancy and perinatal outcomes, following assisted reproductive procedures in infertile patients.

In conclusion, this large retrospective study reveals that a high BMI is associated with diminished ovarian reserve in infertile women, and this association is influenced by age. Although obesity negatively impact certain embryo and perinatal outcomes, it does not significantly correlate with pregnancy outcomes. While weight control remains important for patients undergoing ART, it is crucial to consider the effects of age on treatment outcomes.

This retrospective study shows that in infertile women, BMI affects ovarian reserve in an age-related manner. Specifically, BMI does not significantly impact ovarian reserve in patients aged 35–45 years. Additionally, obesity influences embryo outcomes, including the number of oocytes retrieved, mature oocytes, and fertilized oocytes. Obesity also increases the risk of adverse perinatal outcomes such as gestational diabetes mellitus, gestational hypertension, and macrosomia. However, no significant association was found between obesity and poor pregnancy outcomes. Current research on the relationship between BMI and ovarian reserve remains controversial. This study observed an inverse association between obesity and AMH levels. Specifically, AMH concentrations decreased as BMI increased, which is consistent with findings from some previous studies [ 11 , 12 , 18 – 20 ]. Jaswa et al. reported a reduction in AMH levels with higher BMI, which was not attributable to the dilutional effect of increased blood volume [ 11 ]. Bernardi et al. identified significant associations between AMH and various markers of obesity, including current BMI, late adolescent BMI, and leptin [ 12 ]. In contrast, some studies have found no correlation between BMI and ovarian reserve [ 14 ], while others have reported a positive correlation [ 13 , 21 ]. Albu et al. found that in infertile women without severe obesity, an increase in BMI was positively correlated with AMH levels [ 13 ]. Halawaty et al. conducted a cross-sectional study and found no correlation between AMH levels and BMI [ 21 ]. Although the exact mechanism remains unclear, obesity may affect ovarian reserve through altered hormone levels. Elevated aromatase activity in adipose tissue promotes the peripheral conversion of androgens to estrogens, leading to negative feedback on the hypothalamic-pituitary-ovarian (HPO) axis, which can inhibit ovarian folliculogenesis [ 22 ]. Additionally, obesity affects ovarian reserve through specific adipokines. Obese patients exhibit elevated leptin levels in both serum and follicular fluid [ 23 ], which can downregulate AMH expression through the JAK2/STAT3 pathway [ 24 ]. The study revealed that the correlation between BMI and AMH significantly weakened in women aged 35–45 years. This may be due to the substantial decline in ovarian reserve that occurs with age [ 25 ]. In older women, age becomes the primary factor influencing ovarian reserve, while BMI has a lesser impact. The limited number of patients aged 35–45 years in this study could have contributed to this finding. This study found no significant association between AFC and BMI. The accuracy of AFC results is compromised by the inability to distinguish between healthy and atretic follicles during transvaginal ultrasound [ 22 ]. Additionally, the predictive accuracy of AFC is limited in overweight and obese women due to greater inter-cycle and intra-cycle variability [ 26 , 27 ]. In cases where AFC and AMH results are discordant, AMH is considered a more reliable predictor of ovarian reserve [ 28 ]. Therefore, it can still be assumed that overweight and obesity affect ovarian reserve in infertile women. Several studies have demonstrated that obesity significantly impacts oocyte quality [ 29 , 30 ]. Obese women typically have fewer oocytes retrieved and matured compared to non-obese women [ 31 , 32 ], a finding consistent with this study. This study observed significant differences in the number of retrieved oocytes, matured oocytes, and fertilized oocytes among patients with varying BMIs in the age subgroups of 20–30 and 30–35 years, as previously mentioned. Maternal metabolic changes can lead to abnormalities in the follicular fluid microenvironment [ 30 ]. Research indicates that increased inflammation and oxidative stress are associated with reduced oocyte developmental potential [ 29 ]. Additionally, altered mitochondrial activity has been identified as a possible mechanism for poor oocyte quality in obese women [ 33 ]. Mitochondrial dysfunction can impair oocyte maturation, fertilization, and subsequent embryonic development [ 34 ]. Furthermore, obesity’s impact on oocyte quality appears to be age-related, similar to its effect on ovarian reserve. Previous research has explored the effect of BMI on IVF/ICSI outcomes, but the results have been inconsistent. While many studies have shown that obese infertile women tend to have poorer outcomes with ART [ 4 – 7 , 35 – 37 ], others have found no significant difference between obese and non-obese women [ 8 , 38 ]. This study, however, did not find significant correlations between BMI and key pregnancy outcomes, including biochemical pregnancy, miscarriage, and live birth rates. Interestingly, the obese group in this study showed higher rates of clinical and ongoing pregnancies, which challenges the prevailing view that higher BMI negatively affects fertility. Notably, a higher incidence of ectopic pregnancy in the overweight group was observed in a subgroup analysis. This complicates the understanding of the relationship between BMI and pregnancy outcomes. The inconsistencies in findings across studies may stem from differences in study populations, methods of weight classification, sample sizes, exclusion criteria, number of cycles, and other factors contributing to heterogeneity. Moreover, it is well-documented that obesity primarily affects fertility by causing anovulation [ 39 ]. Treatments such as controlled ovarian stimulation and in vitro fertilization are generally effective in overcoming infertility issues related to ovulatory dysfunction. The unexpectedly higher pregnancy rates in obese patients may suggest a selection bias in the normal weight group. Within this group, there exists a higher prevalence of infertility causes not associated with ovulatory dysfunction, which might not respond as effectively to the interventions aimed primarily at inducing ovulation. Obesity in women is associated with a high risk of perinatal complications, and similar results have been consistently reported s in infertile women [ 38 , 40 , 41 ]. In this study, obesity increased the risk of gestational diabetes mellitus, gestational hypertension, and macrosomia. Obesity exerts multifaceted effects on the oocyte, embryo, and endometrium, leading to an increased risk of multiple adverse outcomes [ 42 ]. These effects stem from altered endocrine and metabolic environments due to adipose tissue accumulation. Key mechanisms include insulin resistance, hyperinsulinemia, upregulation of proinflammatory factors, and oxidative stress [ 43 ]. This study has several limitations. As a retrospective analysis, there is a possibility of unmeasured confounders despite adjustments for known factors. Additionally, the sample size for age-stratified analyses and perinatal outcomes was relatively small, which may explain why some results did not show significant differences or diverged from previous findings. To reduce bias from multiple repeat cycles, we included only the first fresh cycles. However, earlier studies have demonstrated that obese patients often require more ART cycles than normal weight patients [ 7 , 44 ], and the outcomes of the first cycle may not fully reflect their true outcomes. The study’s strength lies in its large sample size of over 30,000 cases, which enhances the generalizability of our findings. Data collection from a single center ensured uniformity in the evaluation of indicators across studies. Additionally, analyzing both ovarian reserve and ART outcomes within the same cohort provides a clear depiction of how BMI impacts these factors, thereby aiding in the management of obese infertile patients.

In this retrospective study, we included 30,746 patients who underwent their first in vitro fertilization (IVF) or intracytoplasmic sperm injection (ICSI) cycle at Tongji Hospital between January 2016 and May 2023. Patients with polycystic ovary syndrome, previous ovarian surgery or endometriosis, ovarian cystadenoma, or missing core data such as BMI as well as those with a history of abortion due to cervical insufficiency in a previous single pregnancy, were excluded. For analysis, the participants were categorized into three age subgroups: 20–30 years, 30–35 years, and 35–45 years. Subsequently, they were classified into four BMI groups based on the WHO standard [ 15 ]: lean (< 18.5 kg/m 2 ), normal weight (18.5–24.9 kg/m 2 ), overweight (25.0–29.9 kg/m 2 ), and obese (≥ 30.0 kg/m 2 ). This study adhered to the Declaration of Helsinki for Human Subjects in Medical Research and received approval from the Ethical Committee of the Reproductive Medicine Center, Tongji Hospital, Tongji Medicine College, Huazhong University of Science and Technology (TJ-IRB20230213). The controlled ovarian stimulation (COS) protocols were performed as previously described [ 16 ]. Various protocols, including the gonadotropin-releasing hormone (GnRH) antagonist and GnRH agonist protocols, as well as other protocols like the mild stimulation and luteal phase stimulation protocols, were employed. The selection of each protocol was based on factors such as maternal age, body mass index (BMI), and ovarian reserve. The dosage of recombinant follicle-stimulating hormone (FSH) was tailored to each patient’s ovarian response. Follicular development was monitored through transvaginal ultrasound. Once the leading follicles reached an average diameter of at least 18 mm, an intramuscular injection of 10,000 IU of human chorionic gonadotropin (hCG) was administered to trigger oocyte maturation. Oocyte retrieval was performed 34–36 h after hCG administration. The retrieved oocytes were then fertilized either by conventional insemination or ICSI. The resulting zygotes were cultured until Day 3 or developed further to the blastocyst stage (Day 5 or Day 6). Embryos were either transferred with ultrasonographic guidance or cryopreserved for future use. AMH and AFC are key indicators of ovarian reserve. These test results are typically obtained within the first 12 months before initiating the IVF/ICSI program. Pregnancy outcomes mainly include clinical pregnancy rate, miscarriage rate, live birth rate, and other factors. A positive pregnancy was confirmed through repeated hCG testing two weeks after embryo transfer. Clinical pregnancy was defined as the presence of an intrauterine gestational sac documented by ultrasound. Biochemical pregnancy was defined as a positive pregnancy test without ultrasound evidence of an intrauterine gestational sac. Ongoing pregnancy was defined as an intrauterine pregnancy lasting beyond 12 weeks. Live birth was defined as the delivery of at least one live newborn after 24 weeks of gestation. Miscarriage was defined as the loss of pregnancy before 20 weeks of gestation. Ectopic pregnancy was identified when a gestational sac was located outside the uterine cavity, confirmed via ultrasonography or pathology. The normal fertilization rate was defined as the number of two-pronucleus (2PN) embryos divided by the number of retrieved oocytes in IVF, or the number of 2PN embryos divided by the number of metaphase II (MII) oocytes in ICSI. The implantation rate was calculated as the ratio of fetal heartbeats to the number of embryos transferred. Good-quality cleavage stage embryos were defined as those with 7 or 8 blastomeres, a fragmentation rate of less than 20%, and no evidence of multinucleation. Blastocysts were graded morphologically according to the Gardner scoring system [ 17 ]. According to Chinese expert consensus, high-quality blastocysts are defined as those at stage 3–4 on day 5 or stage 4–6 on day 6, with A or B scores for both inner cell mass and trophectoderm. To minimize bias from twin vanishing syndrome and multiple pregnancies, only patients with singleton pregnancies and live births were considered in the analysis of perinatal outcomes. These outcomes included gestational age, mode of delivery, sex, birth weight, preterm birth, very preterm birth, macrosomia, hypertensive disorders of pregnancy, placenta previa, and gestational diabetes mellitus. The diagnosis of gestational hypertension, including preeclampsia and gestational hypertension, was based on the consensus guidelines of the International Society for the Study of Hypertension in Pregnancy. The diagnosis of gestational diabetes mellitus followed established consensus criteria. Preterm birth (PTB) was defined as delivery occurring before 37 weeks of gestation, and very PTB was defined as delivery before 32 weeks. Statistical analyses were performed using SPSS 26.0 (IBM, Chicago, IL) statistical software. Kolmogorov-Smirnov was used for the normality test and Levene’s test was used for the homogeneity of variance test. Continuous variables were expressed as median values with corresponding first and third quartiles, and group comparisons were made using the Kruskal-Wallis one-way analysis of variance (ANOVA). Categorical variables were presented as proportions or rates (%), and between-group comparisons were performed using the chi-square test or Fisher’s exact test. Bonferroni correction was applied to adjust for multiple comparisons. Pearson’s correlation and multiple linear regression analyses were conducted to explore the relationship between BMI and AMH, including age as a covariate. AMH concentrations were log-transformed before analysis due to their non-normal distribution. Binary logistic regression and multiple linear regression analyses were employed to assess the impact of pre-pregnancy BMI on embryo, clinical and perinatal outcomes, adjusting for covariates such as maternal age, type of infertility, duration of infertility in years, cause of infertility, COS protocols, and fertilization methods. A P-value of less than 0.05 was considered statistically significant.

Below is the link to the electronic supplementary material. Supplemental Figure 1 Levels of Anti-Müllerian hormone (AMH) in different body mass index (BMI) groups. Supplemental Figure 1 Levels of Anti-Müllerian hormone (AMH) in different body mass index (BMI) groups. Supplemental Figure 2 Levels of antral follicle count (AFC) in different body mass index (BMI) groups. Supplemental Figure 2 Levels of antral follicle count (AFC) in different body mass index (BMI) groups. Supplemental Table 1 Baseline characteristics of the study cycles (20 < age ≤ 30) Supplemental Table 1 Baseline characteristics of the study cycles (20 < age ≤ 30) Supplemental Table 2 Baseline characteristics of the study cycles (30 < age ≤ 35) Supplemental Table 2 Baseline characteristics of the study cycles (30 < age ≤ 35) Supplemental Table 3 Baseline characteristics of the study cycles (35 < age ≤ 45) Supplemental Table 3 Baseline characteristics of the study cycles (35 < age ≤ 45) Supplemental Table 4 Multivariate linear regression analysis of the association between BMI and embryo outcomes Supplemental Table 4 Multivariate linear regression analysis of the association between BMI and embryo outcomes Supplemental Table 5 Logistic regression of pregnancy outcomes by BMI categorization Supplemental Table 5 Logistic regression of pregnancy outcomes by BMI categorization Supplemental Table 6 Logistic regression of perinatal outcomes by BMI categorization Supplemental Table 6 Logistic regression of perinatal outcomes by BMI categorization