Associations between daytime napping and parameters of ovarian reserve among women undergoing assisted reproductive technology.

This study is conducted within the framework of the Tongji Reproductive and Environmental (TREE) study, an ongoing prospective cohort that aims to investigate associations of environmental exposures and lifestyle factors with reproductive health and early pregnancy outcomes [ 24 ]. In brief, couples who were at least 20 years old and seeking assisted reproductive technology (ART) were recruited from the Reproductive Center of Tongji Hospital in Wuhan, China. Between December 2018 and January 2020, a total of 2057 women agreed to participate in the study. A total of 1618 women had complete data encompassing both ovarian reserve parameters and daytime napping. Further, we excluded 127 women due to a history of polycystic ovary syndrome, 84 women due to the history of surgical treatment in ovaries, 157 women due to self-reported endocrine diseases (e.g., diabetes, adrenal diseases, hyperprolactinemia, thyroid diseases, and endometriosis). Ultimately, a total of 1250 women were included in the present analysis (Figure S1). This study received approval from the Tongji Medical College Ethics Committee, and all participants were required to provide informed consent before being enrolled. All participants completed questionnaires under the guidance of research staff. The collected information comprised demographic factors (e.g., age, ethnicity, working status, household income, and educational level), lifestyle habits (e.g., nocturnal sleep duration, nocturnal subjective sleep quality, smoking behavior, alcohol consumption, second-hand smoke exposure, and dietary patterns), and data of physical examination (e.g., height and weight). Each participant was also required to answer the questions about daytime napping: "Did you have the habit of taking daytime naps in the past three months?". If the answer was "Yes", the subsequent question was "How long do you usually nap?". Then, the duration of daytime napping was documented. The reproductive data, which includes gravidity, parity, duration of infertility, and primary infertility diagnosis, was extracted from Tongji Hospital’s electronic medical system. Infertility caused by tubal or pelvic disease, ovulatory dysfunction, diminished ovarian reserve, uterine factors, endometriosis, and female chromosomal abnormalities were classified as female factors in infertility diagnosis. Infertility caused by semen abnormalities, sexual dysfunction (i.e., erectile and ejaculatory dysfunction), and male chromosomal abnormalities were classified as male-factor infertility. Mixed factors were defined as the presence of both female and male factors in one couple. Unexplained factors were defined as infertility with no clear known reason. The body mass index (BMI, kg/m 2 ) was derived by dividing the weight (in kilograms) by the square of height (in meters). In early follicular phase of an unstimulated menstrual cycle (days 2–5), AFC and OV were measured in both right and left ovaries by gynecology specialists at Tongji Hospital. All follicles with diameters between 2 and 10 mm were counted. The volume of each ovary was calculated by applying the following formula: [length (millimeters) × width (millimeters) × height (millimeters)] × (π/6) [ 25 , 26 ]. The total antral follicle count (AFC) was determined by adding the number of follicles in the right and left ovaries. The total ovarian volume (OV) was calculated by summing the volumes of both ovaries. Before any treatment, we collected venous blood samples from each participant on the second to fifth days of an unstimulated menstrual cycle. The blood samples were centrifuged at 3000 rpm for 10 min to obtain serum for subsequent analysis. The serum AMH level was determined using commercial enzyme-linked immunosorbent (ELISA) assays (Ansh Labs, Webster, TX, USA). The concentrations of basal serum FSH, luteinizing hormone, estradiol, testosterone, progesterone, and prolactin were determined using direct chemiluminescence immunoassays (Siemens, Healthcare Diagnostics, Tarrytown, NY, USA). The detection ranges were 0.06–18.00 ng/mL for AMH, 0.30–200.00 mIU/mL for FSH, 1.9–12.5 mIU/mL for luteinizing hormone, 19.5–144.2 pg/mL for estradiol, 15.06–42.41 ng/dL for testosterone, 0–0.91 ng/mL for progesterone, and 2.8–29.2 ng/mL for prolactin. The recovery rates of all hormones ranged from 82.6% to 115.8%. The intra-assay coefficient of variation was ≤ 8.5% and the inter-assay coefficient of variation was ≤ 12.6% for all reproductive hormones. Expert technicians from the medical laboratory at Tongji Hospital collected the blood samples and quantified serum hormone concentrations. Continuous variables were summarized using means and standard deviations, whereas categorical variables were described using counts and proportions (%). We performed student’s t-tests for continuous variables and chi-square tests for categorical variables to examine differences in baseline characteristics across napping status. We used multivariate generalized linear or Poisson regression models to assess the associations of daytime napping with indicators of ovarian reserve and reproductive hormones. The duration of daytime napping was considered as both categorical and continuous variables. The duration of napping for individuals who reported no habit of napping was regarded as zero. According to previous literature [ 27 ], nap duration was categorized into none, ≤ 1 h, and > 1 h. A Poisson distribution and log link function were specified for AFC. The OV, and basal AMH, FSH, luteinizing hormone, estradiol, testosterone, progesterone, and prolactin concentrations were naturally transformed to improve normality. For naturally transformed outcomes and AFC, the corresponding regression coefficients were transformed to percent changes using 100%×[exp(β)–1]. Considering that FSH ≥ 10 IU/L and AMH ≤ 1.1ng/ml are defined as the diagnostic criteria of diminished ovarian reserve, we divided the basal serum FSH and AMH level into normal and abnormal groups according to whether the basal serum FSH was ≥ 10 IU/L or AMH ≤ 1.1ng/ml. Moreover, we performed logistic regression models to evaluate the association of daytime napping with FSH and AMH, and the odds ratio (OR) and 95% CI were reported. Given that insufficient nocturnal sleep duration and sleep quality could affect the ovarian reserve and fecundity [ 12 , 28 ], we conducted stratified analyses to examine whether the relationships between daytime napping and all the investigated outcomes were influenced by subjective sleep quality (good vs. poor) or nocturnal sleep duration (≤ 7 h vs. >7 h). Stratified analyses by age (≤ 30 vs. >30 years) and BMI (< 24 vs. ≥24 kg/m²) were also performed to assess the generalizability of the findings. We conducted several sensitivity analyses to test the robustness of our results. First, we adjusted for night shift experience (yes vs. no) in the association analyses. Secondly, we reanalyzed the relations of daytime napping with ovarian reserve by excluding females diagnosed with DOR ( n = 432) and had history of hormone medicine use ( n = 211). The selection of potential confounders was based on previous literature and subsequently included in the final models according to a directed acyclic graph [ 29 ]. These covariates were included in final models: age (continuous), BMI (continuous), second-hand smoke exposure (never vs. ever), alcohol use (never vs. ever), working status (employed vs. unemployed), nocturnal sleep duration (7, 7 to < 8, or ≥ 8 h), parity (0 vs. ≥1) and household income (≤ 5000, 5001 to < 10000, or ≥ 10000 Yuan per month) (Figure S2). All the statistical analyses were performed using R software (version 4.2.1).

Table  1 shows the characteristics of the population according to napping status. This study included 1250 women with an average (± SD) age of 30.9 (± 4.91) years and an average (± SD) BMI of 22.0 (± 3.02) kg/m 2 at enrollment. Nearly half of our participants reported regular daytime napping (49.9%), and 16.8% of the women reported their napping duration as > 1 h. Compared to non-nappers, nappers are older (30.5 ± 4.75 vs. 31.3 ± 5.04 years), have a lower BMI (22.1 ± 3.02 vs. 21.9 ± 3.02 kg/m 2 ) and higher education level (26.0% vs. 46.3% reporting college and above), and more likely to be employed (40.3% vs. 52.9%), reside in urban area (27.0% vs. 40.5%), and have good sleep quality at night (90.4% vs. 94.7%). Table 1 Characteristics of study participants by daytime napping status Overall No-nappers Nappers P ( n  = 1250) ( n  = 626) ( n  = 624) Age (years) 30.9 ± 4.91 30.5 ± 4.75 31.3 ± 5.04 0.02 Body mass index (kg/m 2 ) 22.0 ± 3.02 22.1 ± 3.02 21.9 ± 3.02 0.03 Ethnicity 0.90  Han 1194 (95.5%) 597 (95.4%) 597 (95.7%)  Others 56 (4.5%) 29 (4.6%) 27 (4.3%) Geographic residence setting < 0.001  Urban area 422 (33.8%) 169 (27.0%) 253 (40.5%)  Rural area 828 (66.2%) 457 (73.0%) 371 (59.5%) Educational level < 0.001  Middle and below 519 (41.5%) 310 (49.5%) 209 (33.5%)  High school 279 (22.3%) 153 (24.4%) 126 (20.2%)  College and above 452 (36.2%) 163 (26.0%) 289 (46.3%) Working status < 0.001  Employed 582 (46.6%) 252 (40.3%) 330 (52.9%)  Unemployed 668 (53.4%) 374 (59.7%) 294 (47.1%) Household income (Yuan/month) < 0.001  ≤ 5000 659 (52.7%) 363 (58.0%) 296 (47.4%)  5001–10,000 378 (30.2%) 161 (25.7%) 217 (34.8%)  ≥ 10,000 213 (17.0%) 102 (16.3%) 111 (17.8%) Smoking status 0.07  Never 1187 (95.0%) 587 (93.8%) 600 (96.2%)  Ever 63 (5.0%) 39 (6.2%) 24 (3.8%) Second-hand smoke exposure 0.39  Yes 1072 (85.8%) 531 (84.8%) 541 (86.7%)  No 178 (14.2%) 95 (15.2%) 83 (13.3%) Alcohol consumption 0.70  Never 965 (77.2%) 480 (76.7%) 485 (77.7%)  Ever 285 (22.8%) 146 (23.3%) 139 (22.3%) Gravidity 0.91  0 688 (55.0%) 346 (55.3%) 342 (54.8%)  ≥ 1 562 (45.0%) 280 (44.7%) 282 (45.2%) Parity 0.32  0 1022 (81.8%) 519 (82.9%) 503 (80.6%)  ≥ 1 228 (18.2%) 107 (17.1%) 121 (19.4%) Duration of infertility (years) 3.40 ± 2.77 3.53 ± 2.85 3.27 ± 2.68 0.21 Infertility diagnoses 0.86  Female factors 677 (54.2%) 347 (55.4%) 330 (52.9%)  Male factors 187 (15.0%) 92 (14.7%) 95 (15.2%)  Mix factors 246 (19.7%) 119 (19.0%) 127 (20.4%)  Unexplained 138 (11.0%) 68 (10.9%) 70 (11.2%) Daytime napping (hours)  None 626 (50.1%)  ≤ 1 414 (33.1%)  > 1 210 (16.8%) Nocturnal sleep duration (hours) < 0.001  < 7 72 (5.8%) 30 (4.8%) 42 (6.7%)  7 to < 8 254 (20.3%) 98 (15.7%) 156 (25.0%)  ≥ 8 924 (73.9%) 498 (79.6%) 426 (68.3%) Subjective sleep quality < 0.01  Good 1157 (92.6%) 566 (90.4%) 591 (94.7%)  Poor 93 (7.4%) 60 (9.6%) 33 (5.3%) Night shift experience 0.57  Yes 215 (17.2%) 112 (17.9%) 103 (16.5%)  No 1035 (82.8%) 514 (82.1%) 521 (83.5%) Characteristics of study participants by daytime napping status The distribution of ovarian reserve indicators is presented in Table  2 . The median total AFC number was 11, and median AFC in the right and left ovary were 5 and 6, respectively. The median total, left, and right OV were 4247.96 mm 3 , 1866.11 mm 3 , and 2290.22 mm 3 respectively. The median concentrations of FSH, AMH, basal serum luteinizing hormone, estradiol, testosterone, progesterone, and prolactin concentrations were 7.51 IU/L, 2.70 ng/mL, 3.90 mIU/mL, 39.28 pg/mL, 30.09 ng/dL, 0.52 ng/mL, and 13.93 ng/mL, respectively. Table 2 Distribution of ovarian reserve indicators and basal serum reproductive hormone concentrations among study population ( n  = 1250) Variables N Arithmetic mean Percentiles 25th 50th 75th Ovarian reserve indicators  Total AFC (n) 1249 12.03 7 11 16  Left AFC (n) 1241 5.91 3 5 8  Right AFC (n) 1238 6.22 4 6 8  Total OV (mm 3 ) 1159 5201.70 3067.37 4247.96 5992.33  Left OV (mm 3 ) 1171 2445.10 1180.19 1866.11 2827.43  Right OV (mm 3 ) 1174 2751.31 1437.54 2290.22 3220.79  FSH (IU/L) 1249 8.04 6.37 7.51 8.95  AMH (ng/mL) 1246 3.49 1.51 2.70 4.60 Reproductive hormones  Luteinizing hormone (mIU/mL) 1249 4.35 2.97 3.90 5.14  Estradiol (pg/mL) 1246 44.82 30.82 39.28 50.53  Testosterone (ng/dL) 1238 30.74 22.64 30.09 38.40  Progesterone (ng/mL) 1236 0.67 0.38 0.52 0.67  Prolactin (ng/mL) 1241 18.93 10.07 13.93 19.63 Abbreviations: AFC Antral follicle count, OV Ovarian volume, FSH Follicle-stimulating hormone, AMH Anti-müllerian hormone Distribution of ovarian reserve indicators and basal serum reproductive hormone concentrations among study population ( n  = 1250) Abbreviations: AFC Antral follicle count, OV Ovarian volume, FSH Follicle-stimulating hormone, AMH Anti-müllerian hormone In both crude and adjusted models, we consistently observed that napping for ≤ 1 h during the daytime was associated with lower concentrations of FSH (Table  3 ). Consistently, compared with the women who did not have a napping habit, those who reported ≤ 1 h of daytime napping were less likely to FSH ≥ 10 IU/L (adjusted OR = 0.57, 95% CI: 0.38, 0.84) (Table S3). After adjusting for relevant covariates, the duration of daytime napping was associated with a 2.39% (95% CI: 0.24%, 4.58%) increase in total AFC. However, we observed null associations between daytime napping and left or right AFC and OV (Table S1-S2). Figure  1 (numeric data in Table S4) lists the associations between daytime napping and serum reproductive hormones. We observed that ≤ 1 h of daytime napping was associated with decreased serum testosterone level (percent change = –15.22%, 95%CI: −26.98%, −1.57%). Fig. 1 Percent changes (95% CI) in basal serum reproductive hormone concentrations associated with daytime napping.The models were adjusted for age, body mass index, second-hand smoke exposure, alcohol use, working status, household income, parity, and nocturnal sleep duration Percent changes (95% CI) in basal serum reproductive hormone concentrations associated with daytime napping.The models were adjusted for age, body mass index, second-hand smoke exposure, alcohol use, working status, household income, parity, and nocturnal sleep duration Table 3 Percent changes (95% CI) in ovarian reserve indicators associated with duration of daytime napping Duration of daytime napping Total AFC Total OV FSH AMH Crude models  None Ref Ref Ref Ref  ≤ 1 h –2.39 (–5.85, 1.19) 3.30 (–4.19, 11.38) –4.37 (–8.16, −0.42) –6.57 (–16.68, 4.76)  > 1 h 3.64 (–0.87, 8.33) 1.82 (–7.34, 11.88) –4.42 (–9.17, 0.59) 6.08 (–8.19, 22.58)  Continuous 1.97 (–0.16, 4.14) 1.13 (–3.30, 5.77) –2.37 (–4.69, 0.02) –2.11 (–4.40, 0.23) Adjusted models a  None Ref Ref Ref Ref  ≤ 1 h 0.24 (–3.48, 4.08) 4.19 (–3.62, 12.64) –6.77 (–10.53, −2.84) –1.03 (–11.35, 10.50)  > 1 h 3.89 (–0.67, 8.62) 0.38 (–8.59, 10.24) –3.35 (–8.06, 1.61) 7.33 (–6.09, 22.67)  Continuous 2.39 (0.24, 4.58) 0.59 (–3.80, 5.18) –2.08 (–4.38, 0.26) 4.62 (–1.77, 11.42) Abbreviations : AFC Antral follicle count, OV Ovarian volume, FSH Follicle-stimulating hormone, AMH Anti-müllerian hormone a Models were adjusted for age, body mass index, second-hand smoke exposure, alcohol use, working status, household income, parity, and nocturnal sleep duration Percent changes (95% CI) in ovarian reserve indicators associated with duration of daytime napping Abbreviations : AFC Antral follicle count, OV Ovarian volume, FSH Follicle-stimulating hormone, AMH Anti-müllerian hormone a Models were adjusted for age, body mass index, second-hand smoke exposure, alcohol use, working status, household income, parity, and nocturnal sleep duration In addition, we found nocturnal sleep duration and subjective sleep quality modified some associations between daytime napping and ovarian reserve indicators. As shown in Figure  2 (numeric data in Table S5), daytime napping was positively associated with total AFC among women who reported nocturnal sleep duration ≤ 7 h (percent change for a unit increase = 12.14%, 95% CI: 5.69%, 18.90%), but not among women who reported > 7 h of nocturnal sleep (percent change for a unit increase = 1.29%, 95% CI: −1.01%, 3.63%; P for interaction = 0.01). Among women with poor sleep quality but not in those with good sleep quality, we observed a positive association between daytime napping and total OV (percent change = –1.35%, 95% CI: −5.78%, 3.28% for the women with good sleep quality; percent change = 22.06%, 95% CI: −0.21%, 49.30% for the women with bad sleep quality; P for interaction = 0.01). Furthermore, the subjective quality of sleep modified the relationships between nap duration and serum concentrations of estradiol ( P for interaction = 0.03, Table S6). The positive associations between nap duration and serum estradiol concentrations were more evident among women with bad sleep quality. The associations between daytime napping and ovarian reserve indicators remained consistent across age and BMI subgroups (Table S7). Our results were largely unchanged after additionally adjusting for night shift work experience, and after excluding women with DOR and had history of hormone medicine use. Specifically, after further adjusting for the night shift experience, daytime napping remained positively correlated with AFC (percentage change = 2.46%, 95% CI: 0.30%, 4.64%) (Table S8-S9). Similarly, after excluding women diagnosed with DOR to eliminate potential reverse causality, the association between daytime napping and FSH remained significant (percentage change = –4.30%, 95% CI: −8.04%, −0.41%) (Table S10-S11). Sensitivity analysis excluding women with hormone medication history yielded consistent findings: ≤1 h of napping was associated with lower FSH (–6.39%; 95% CI: −10.49%, −2.10%), and napping duration remained positively linked to AFC (2.46%; 95% CI: 0.07%, 4.88%; Table S12-S13). Fig. 2 Associations of daytime napping with total AFC and total OV stratified by ( A ) nocturnal sleep duration and ( B ) subjective sleep quality. The models were adjusted for age, body mass index, second-hand smoke exposure, alcohol use, working status, parity, and household income. The models for subjective sleep quality were further adjusted for nocturnal sleep duration. Abbreviation s: AFC, antral follicle count; OV, ovarian volume Associations of daytime napping with total AFC and total OV stratified by ( A ) nocturnal sleep duration and ( B ) subjective sleep quality. The models were adjusted for age, body mass index, second-hand smoke exposure, alcohol use, working status, parity, and household income. The models for subjective sleep quality were further adjusted for nocturnal sleep duration. Abbreviation s: AFC, antral follicle count; OV, ovarian volume

The prevalence of female infertility is 14.2% globally, and this rate is still increasing by 0.370% per year [ 1 , 2 ]. Multiple factors contribute to the decline in female fecundity, with diminished ovarian reserve being one of the predominant factors [ 3 , 4 ]. Impaired ovarian reserve can give rise to several reproductive disorders, including poor response to ovarian stimulation, irregular menstrual cycles, recurrent pregnancy loss, and preeclampsia [ 5 – 8 ]. These conditions can subsequently lead to a myriad of social and psychological problems, such as economic instability, anxiety, depression, and post-traumatic stress disorders [ 9 ]. Therefore, identifying potential risk and protective factors that can affect ovarian reserve is of great importance to improve female fertility and general well-being. Nowadays, several lifestyle factors, including smoking, nutrition patterns, alcohol use, and sleep characteristics, have been reported to affect ovarian reserve [ 10 – 12 ]. Daytime napping represents a ubiquitous phenomenon observed across diverse cultures and age groups [ 13 ]. In China, daytime napping is a commonly adopted lifestyle behavior, with its prevalence significantly surpassing that in numerous Western populations [ 14 ]. Recently, daytime napping has been considered to influence circadian rhythms, and an epidemiological study reported that daytime napping was related to altered circadian rhythm in menopausal women [ 15 ]. Animal evidence has shown that dysregulated circadian rhythm can disrupt the estrous cycle and reduce pregnancy success in rodent species [ 16 , 17 ]. In humans, circadian rhythm disorders have been associated with higher FSH levels, fewer mature oocytes, and advanced menopausal age [ 10 , 18 , 19 ]. Research indicates that daytime napping can mitigate the neuroendocrine stress response and inflammatory markers caused by sleep loss [ 20 ]. Furthermore, disruptions in sleep architecture, such as fragmentation and circadian misalignment, are known to adversely affect the hypothalamic-pituitary-gonadal (HPG) axis, thereby compromising ovarian function and overall reproductive function [ 21 , 22 ]. However, the impact of daytime napping on ovarian reserve remains poorly understood. Therefore, we explored the associations between daytime napping and parameters of ovarian reserve among women undergoing assisted reproductive technology (ART). Antral follicle count (AFC), anti-Müllerian hormone (AMH) level, follicle-stimulating hormone (FSH) levels, and ovarian volume (OV) are routinely used in clinical practice to reflect the condition of ovarian reserve [ 23 ]. We also determined a series of reproductive hormone levels in an unstimulated menstrual cycle as indicators of reproductive and sexual function.

Among 1250 women undergoing ART, we found that women with ≤ 1 h of daytime napping were inversely related to basal FSH, testosterone concentrations, and the odds of abnormal FSH. Moreover, we identified a small but significantly positive relationship between the duration of daytime napping and total AFC. Nocturnal sleep duration and subjective sleep quality modified the associations between daytime napping and ovarian reserve indicators. Daytime napping was associated with higher total AFC in women with ≤ 7 h of nocturnal sleep, and also associated with higher total OV and basal serum estradiol concentration in women with bad sleep quality. Several epidemiological studies have indicated that dysregulated sleep patterns can impair the female reproductive function, manifested as irregular menstrual cycles [ 30 – 32 ], abnormal fluctuations in reproductive hormones [ 33 ], and prolonged time to conceive among the general public [ 34 , 35 ]. In addition, there was a clear high frequency of poor sleep quality in women before and throughout IVF procedures [ 36 , 37 ]. In infertile women, sleep disorders are associated with the lower number of retrieved oocytes [ 24 ], low pregnancy rate [ 38 ], and the risks of polycystic ovary syndrome [ 39 ], and premature ovarian failure [ 40 ]. However, no research has yet examined the effects of daytime napping on ovarian function. Daytime napping is a universal phenomenon observed in diverse cultures and age groups [ 41 – 44 ]. In human studies, proper daytime napping has been positively associated with good cognition [ 45 ], and work productivity [ 46 ], but negatively associated with hypertension [ 47 , 48 ], obesity [ 49 ], and the risk of low birth weight [ 27 ]. Our study revealed a positive association between daytime napping and multiple ovarian reserve markers, including higher total AFC and lower basal FSH and testosterone concentrations. These findings provide consistent evidence across both ultrasound markers and endocrine profiles. suggesting a potential beneficial effect on female fecundity. Specifically, the association between moderate napping (≤ 1 h) and a more favorable hormonal balance suggests that napping may serve as a marker of, or a protective factor for, preserved ovarian reserve. Consequently, while our data suggest a potential beneficial effect on female fecundity, these results highlight the importance of considering daytime napping in the context of reproductive health. However, given the limited human evidence about daytime napping and female fertility, more research is needed to validate our findings. Ovarian reserve is clinically assessed using markers such as AMH, AFC, and basal FSH, which reflect the quantity and quality of the remaining follicular pool. Previous research has indicated that sleep disturbances can negatively impact these markers. For instance, Lin et al. demonstrated that poor sleep quality is associated with impaired ovarian reserve function [ 50 ]. Our findings extend this knowledge by highlighting the modifying role of daytime napping. Both AFC and AMH are reliable indicators for assessing ovarian reserve, and the relationship between AFC and AMH may not be parallel due to rising age [ 51 ]. Although the effect of napping on AFC reported in this study was small (percent change = 2.39%), AFC predicts cycle stimulation response and clinical outcomes and may serve as a guide for the dosing regimen and selection of optimal cycles [ 52 ]. In addition, its importance is the highest in modeling ovarian response [ 53 ]. Therefore, minor changes in AFC may also play an important role in clinical decision-making regarding ovulation induction. Nonetheless, FSH ≥ 10 IU/L is considered as one of the indicators of declining ovarian reserve [ 23 ]. Oocytes have FSH receptors that allow FSH to stimulate the secretion of several bone morphogenetic proteins (BMPs), thereby enhancing the expression and secretion of AMH in women [ 54 , 55 ]. However, this facilitation is more likely to occur in rapidly growing follicles [ 56 ]. Given that the population of the present cohort all had AMH detected on days 2–5 of an unstimulated menstruation, this may partly explain the opposite results for FSH and AMH. Furthermore, the direct link between daytime napping and clinical reproductive outcomes (such as oocyte yield, embryo quality, pregnancy or live birth rates) still requires further validation in future prospective studies. In the current study, we found that daytime napping was associated with higher total AFC and lower FSH. However, the underlying mechanism is not clear. Short or interrupted sleep can lead to clock gene dysregulation, which may further contribute to a reduction in ovarian reserve [ 57 ]. Research findings indicated a positive correlation between daytime napping and enhanced sleep efficiency and quality in pregnant women suffering from insomnia [ 28 ]. Consequently, daytime napping may potentially enhance ovarian reserve by facilitating better nighttime sleep efficiency. Furthermore, activation of inflammatory responses can disrupt follicular growth [ 58 ]. Sleep disturbances can potentially exacerbate follicular atresia through triggering inflammatory responses [ 59 – 61 ]. Faraut et al. found that daytime napping reversed the elevated IL-6 expression associated with sleep deprivation [ 62 , 63 ], which may partly explain the positive associations between daytime napping and ovarian reserve parameters. Moreover, daytime napping has been regarded as a stress-releasing habit in healthy individuals [ 64 ]. Multiple biological pathways may underlie the observed associations between daytime napping and ovarian reserve. Daytime napping could indirectly influence ovarian function by enhancing overall sleep efficiency and decreasing inflammatory factors, such as interleukin-6 (IL-6), which is known to exacerbate follicular atresia when elevated due to sleep disturbances. Furthermore, napping may serve as a stress-releasing habit that modulates the hypothalamic-pituitary-adrenal (HPA) axis. By mitigating excessive HPA activation and physiological stress, daytime napping potentially prevents the desynchronization of the hypothalamic-pituitary-gonadal (HPG) axis, thereby maintaining a more favorable environment for follicular development. This is consistent with our finding that napping was particularly beneficial for women with poor nocturnal sleep quality. Although our study didn’t measure inflammatory markers or HPA axis activity, existing evidence indicates sleep deprivation raises IL-6 levels, and daytime napping may indirectly protect ovarian function by reducing inflammation and regulating cortisol rhythm. Future studies should measure biomarkers to clarify these mechanisms. In a stratified analysis, we found that some effects of daytime napping on ovarian reserve were modified by nocturnal sleep duration or sleep quality. The positive associations of daytime napping with total AFC existed only among women who reported ≤ 7 h of nocturnal sleep duration. Sleep deprivation can lead to chronic stress, excessive activation of the HPA axis, and disruption in the secretion of inflammatory cytokines [ 65 ]. On the one hand, daytime napping may alleviate the detrimental effects of bad sleep quality on ovarian reserve by reducing inflammation levels [ 62 ]. On the other hand, several pieces of evidence also indicated that daytime napping reversed cortisol changes induced by sleep restriction [ 66 ], and > 90 min of daytime napping can induce a cortisol arousal response (CAR) [ 67 ], thereby alleviating the negative effects of sleep restriction on ovarian reserve. Moreover, growing evidence indicated poor sleep quality was associated with aging [ 68 , 69 ], metabolic abnormalities [ 70 , 71 ], and hypertension [ 72 , 73 ], which have been reported to be associated with abnormal reproductive hormone fluctuation [ 74 – 76 ]. Taking a daytime nap could potentially enhance the quality of nighttime sleep, thereby influencing overall health and maintaining normal fluctuations in reproductive hormones [ 77 ]. The discrepancy between categorical and continuous analyses, combined with the interaction results, suggests that daytime napping may act as a compensatory mechanism for insufficient nocturnal sleep. The benefits of napping on ovarian reserve appear most pronounced when it supplements a short nocturnal sleep duration, thereby optimizing the total sleep duration. Moreover, stratified analyses indicate that napping might yield more substantial benefits for women experiencing inadequate nocturnal sleep or poor subjective sleep quality. Nevertheless, this exploratory conclusion necessitates further validation in subsequent research. The strengths of our study encompassed a relatively large sample size, concurrent assessment of multiple indicators of ovarian reserve, and consistent determination of female reproductive hormone levels during the early follicular phase to minimize menstrual fluctuation. However, some limitations should be noted. Firstly, the assessment of daytime napping was based on self-reported questionnaires regarding habits over the past three months, which may introduce recall bias and measurement error. Specifically, our simplified categorization did not distinguish between weekday and weekend napping or capture data on nap timing and frequency. While such brief assessments are common in large-scale clinical cohorts to reduce participant burden, they lack the granularity provided by objective measures like actigraphy or detailed sleep diaries. Consequently, our findings should be interpreted with caution, and future research incorporating more precise exposure assessments is warranted. Secondly, due to the observational designation of our study, causality cannot be established. Thirdly, we measured total testosterone in serum, and since only the unbound fraction of testosterone in the circulation is biologically active, free testosterone may be more relevant to clinical outcomes. Its results should be interpreted with more caution. Additionally, since our study participants were from a fertility clinic and may have infertility, we cannot extrapolate our findings to women in the general population. Finally, our results may be biased by some unmeasured factors such as female physical activity, and dietary habits, caffeine consumption, and psychological stress [ 78 – 81 ].

In summary, our results suggested that daytime napping was associated with better ovarian reserve among women undergoing ART, particularly for those who reported ≤ 7 h of nocturnal sleep duration and had bad sleep quality. Our findings revealed that daytime napping is probably a healthy lifestyle habit for female reproductive function, and can weaken the adverse effects of bad nocturnal sleep quality. However, more epidemiological studies are required to verify our results, especially in the general population without infertility diseases.

Supplementary Material 1. Supplementary Material 1.