Declined Live Birth Rate from In Vitro Fertilization Fresh Cycles Performed during Chinese New Year Holiday Season

doi:10.21203/rs.3.rs-2461052/v1

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Declined Live Birth Rate from In Vitro Fertilization Fresh Cycles Performed during Chinese New Year Holiday Season

https://doi.org/10.21203/rs.3.rs-2461052/v1

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Objective: To investigate whether there is an impact of the Chinese New Year (CNY) holiday season on the outcomes of In Vitro Fertilization (IVF) fresh embryo transfer cycles.

Study Design: A retrospective study

Subjects: 4,688 patients receiving their first IVF fresh cycle attempt between January 2017 and October 2021 were included in the study, of which 4,449 women underwent IVF during non-holiday seasons, while 239 women were treated during the CNY holiday season.

Main Outcome Measure(s): The primary outcome was the live birth rate (LBR).

Result(s): The liver birth rate (LBR) of IVF performed during the CNY holiday season was 32.22%, significantly lower than that of the non-holiday season (43.38%, p<0.001). Multivariate logistic regression demonstrated that the CNY holiday season (OR=0.62, 95%CI 0.47-0.82, p=0.001) was an independent factor associated with the live birth rate. Propensity score matching (PSM) data analysis showed the LBR in the CNY holiday season group is 31.78% versus 42.64% in the non-holiday season group (p=0.005). Inverse probability of treatment weighting (IPTW) data also indicated that the CNY holiday season had a lower LBR than the non-holiday season (OR=0.64, 95%CI 0.47-0.87, p=0.005).

Conclusion: This research demonstrated for the first time the existence of a decline in the LBR of IVF performed during the CNY holiday season. IVF performed during the Chinese New Year holiday season results in a declined live birth rate. The abrupt lifestyle change, emotional stress, and traveling may have contributed to such an effect.

Health sciences/Medical research/Outcomes research

Health sciences/Medical research/Epidemiology

The Chinese New Year (CNY), also known as the Spring Festival, marks the beginning of a new year according to the traditional lunar calendar, appears between late January to late February, and comes with the biggest holiday celebration in Chinese culture. While the official CNY holiday spans 7 days in China mainland, including three days off and the allocation of two adjacent weekends (before and after the CNY’s Day), the festivity typically lasts over a month, with nearly a one-month long holiday preparation prior to the CNY and then at least a 15-day celebration from the CNY’s Eve to the 15th day of lunar January, known as the Lantern Festival. Throughout the holiday preparation and celebration, the vast majority of people have to engage with long-distance travel, frequent and massive shopping, thorough residence cleaning, extensive food preparation, family gatherings, social outings, etc. These activities bring abrupt changes to daily work and life routines, causing significant amount of psychological stress amid festival joys. It is highly likely that such behavioral and psychological changes associated with the CNY holiday may affect fertility, which may result in unusual demand for cyclical treatment for some pregnant women receiving in vitro fertilization (IVF). There was study showed Chinese New Year was associated with increased mortality risk from pulmonary embolism¹.

Several studies have implicated that environmental and social factors may affect pregnancy and IVF outcomes. One study revealed that the New Year's Day and the beginning of Norway's summer break were two peaks for early preterm birth, which may reflect a holiday-related pattern of unintended conception ². Hviid performed a large national cohort study and demonstrated that autumn during gestation was associated with an extremely high rate of preterm birth in Denmark ³. Katharine F.B. et al ⁴ showed that the oocyte retrieval in the summer was associated with a higher rate of clinical pregnancy and LBR among frozen embryo transfers than that in the winter. Zhao M. et al’s work ⁵ also suggested a temperature effect on winter IVF outcomes. However, there has not been any study to investigate whether the CNY holiday season impacts the IVF outcomes. The present study aimed at determining whether the CNY holiday season impacts the IVF outcomes differently compared to other months. We examined the monthly IVF outcomes at our center to investigate how significantly the CNY holiday season affects the IVF outcomes.

Ethical Approval

The Research Ethics Committee approved this study at the Second Hospital affiliated with Hebei Medical University (Approval Letter No. 2022-R060). We conducted a retrospective study on fresh embryo transfer (ET) cycles performed between January 2016 and December 2021 at the Second Hospital of Hebei Medical University reproductive center.

Inclusion Criteria

Patients undergoing their first IVF cycles during January 2017 and October 2021
Patients were implemented at the fresh cycle
Patients with the outcome of live birth

Exclusion Criteria

Patients with incomplete data of variables

Implementation procedure

All patients undergoing their first IVF cycle during January 2017 and October 2021 were included except patients with incomplete data recording. Two days after oocyte retrieval (day 3), two embryos were transferred as fresh cycles, and in some cases the transfer was performed with blastocysts on day 5, then the luteal-phase support was administered [90 mg progesterone gel (Merck Serono) plus 20 mg/day dydrogesterone. Based on the embryo transfer dates, participants were divided into the CNY holiday season (the entire January and February) group (CNY group) and the non-holiday season (months other than Jan and Feb) group (N-CNY group).

Data Retrieval

Data were retrieved from HIS (Hospital Information System) database of our hospital including patients' age, classification of infertility, duration of infertility, and education. All included subjects had been tested for their baseline serum levels of follicle-stimulating hormone (FSH) (μIU/mL), luteinizing hormone (LH) (μIU/mL), estrogen (E2) (pg/mL), progesterone (P) (ng/mL), testosterone (T) (ng/mL), prolactin (PRL) (ng/mL), and anti-Müllerian hormone (AMH) (ng/mL). The tests were performed using commercial kits (Siemens Healthcare Diagnostics) with an automated chemiluminescence immunoassay analyzer. In addition, treatment protocols for superovulation and numbers of retrieved oocytes were also obtained from the database.

Outcomes

Live birth, defined as the delivery of at least one live born neonate in a given embryo transfer cycle, was the primary outcome. Clinical pregnancy was used as the secondary outcome and was defined by the evidence of fetal cardiac activity by sonograph 30 days after the embryo transfer, with ectopic pregnancy included. The outcomes also included miscarriage and pregnancy loss before 20 weeks.

Statistical Analysis

Continuous variables with normal distribution were presented as the mean, followed by standard deviation. The abnormal distribution of continuous variables was introduced as the median and the interquartile range from the first to the third quartile (Q1-Q3). Student's t-test and Wilcoxon rank-sum test were used for normally and abnormally distributed quantitative data. Chi-square or Fisher's exact test analyzed categorical variables.

Propensity score matching (PSM) was performed to match patients in the N-CNY group with patients in the CNY group. The propensity score data set was constructed using the multivariable logistic regression model, including age, infertility years, education, FSH, E2, P, PRL, LH, T, AMH, and classification of infertility. We used caliper matching with the caliper 0.02 of the pooled standard deviation of the logit of the propensity score. Patients in the CNY group were matched 1:2 to patients in the N-CNY group.

The propensity score data generated the inverse probability of treatment weighting (IPTW) data. To balance those observable characteristics, each patient was weighted by the inverse probability in the two groups.

Multivariate logistic regression was used to assess the association between the live birth rate and the two treatment groups for the primary endpoint. The model was adjusted by those variates whose p-value was no more than 0.10. Those variates with clinical meanings related to the primary endpoint were adjusted, ignoring the p-value. The results were expressed as adjusted odds ratios (ORs) with 95% confidence intervals (95% CIs). We analyzed the PSM data set and the IPTW data set for sensitivity analysis. All hypothesis tests were two-sided, and a p-value<0.05 was considered statistically significant.

Sample size was calculated based on the EPV (events per variable) principle of multivariable analysis. A minimum of 5⁶ and a maximum of 10-15⁷ endpoint events for each multivariate was requested. Ten variants were assumed to be analyzed leads to 150 live births. As study reported 40%⁸ ~ 50%⁹, 375 samples were needed.

Stata SE 13 (Serial number 401306302851), R software version 4.2.0 (http://cran.r-project.org/), and easy-R (www.empowerstats.com) were used for statistical analysis. GraphPad was used to generate figures.

Patient and Clinical Characteristics

A total of 4,688 women (Figure 1) receiving IVF with the first fresh embryo transfer (ET) cycle were included in the analysis. The lowest LBR by the month when ET was performed appeared in Jan (35.1%) and Feb (20.0%), while the LBR with ET in all other months ranged between 37.4% and 47.5% (Figure 2).

General information of participants is shown in Table 1 and Figure 3. The percentages of patients by years of education at ≤6, 6~9, 9~12, and above 12 were 3.06%, 31.87%, 18.88%, and 46.19%, respectively, in the N-CNY group, versus 2.09%, 28.03%, 25.94%, 43.93%, respectively, in the CNY group (p=0.048). The average baseline E2 level in the N-CNY group was 49.75±52.11 (median 40) pg/ml, versus 45.69±48.82 (median 39) pg/ml in the CNY group (p=0.047). The average baseline LH level in the N-CNY group (7.26±110.64 μIU/ml, median 4.44) was significantly higher than that of the CNY group (4.56±2.42 μIU/ml, median 4.11) (p=0.002). The serum baseline FSH, P, PRL, T, and AMH levels were comparable between the two groups. There were no statistical differences between these two groups for age, infertility years, and classification of infertility.

Outcomes of Assisted Reproductive Technology (ART) for all participants

There were significant differences in use of ovarian stimulation treatment protocols between N-CNY group and CNY group(p<0.001). In the N-CNY group, there were 0.36% (16/4449) treated by natural cycles or short cycles, 24.79% (1103/4449) by antagonist protocol, 44.35% (1973/4449) by GnRH agonist protocol, and 30.50% (1357/4449) by depot GnRHa protocol, respectively. In contrast, there were none treated by natural cycles or short cycles, 35.56% (85/239) by antagonist protocol, 42.68% (102/239) by GnRH agonist protocol, and 21.76% (52/239) by depot GnRHa protocol in the CNY group.

In the N-CNY group, 50.80% (2264/4449) had clinical pregnancy, versus 41.42% (99/239) in the CNY group (p=0.004). Of 4,449 women in the N-CNY group, 1,930 had live birth (43.38%), while 77 of 239 women (32.22%) in the CNY group had live birth (p<0.001). There was no statistical difference in the number of oocytes retrieved and pregnancy loss between the two groups (Table 2).

Live birth results for all participants

Table 3 and Figure 4 present the live birth results after adjustment by logistic regression, indicating that the age (OR=0.5, 95% CI 0.42-0.60, p<0.001), serum baseline level of T (OR=1.14, 95%CI 1.01-1.28, p=0.036), AMH (OR=1.15, 95%CI 1.01-1.32, p=0.036), the CNY holiday season (OR=0.62, 95%CI=0.47-0.82, p=0.001), number of oocytes retrieved (OR=1.17, 95%CI 1.09-1.25, p<0.001) were independent factors associate with the outcome of live birth.

Multivariate logistic analysis for participants receiving IVF during regular wintertime

The CNY group had a lower live birth rate than others whose embryo transfer took place from Nov. to Dec., known as regular wintertime in north Chinav (OR=0.61, 95%CI 0.45-0.84, p=0.002). Meanwhile, T level (OR=1.35, 95% CI 1.04-1.76, p=0.024) and number of oocytes retrieved (OR=1.25, 95%CI=1.07-1.46, p=0.004) were independent factors associated with live birth rate (Table 4).

Outcome of ART for matched participants

The general characters of participants before and after matching are shown in Table 5. All variables were comparable.

As shown in Table 6, 97 of 236 women from the CNY group had clinical pregnancy (41.10%). In contrast, 232 of 469 from the N-CNY group had clinical pregnancy (49.47%). The CNY group had a significantly lower clinical pregnancy rate than that of the N-CNY group (p=0.036).

For live birth, 75 of 236 (31.78%) women had live birth in the CNY group, versus 200 of all 469 (42.64%) women in the N-CNY group (p=0.005). In addition, there was no difference in pregnancy loss between the two groups (p=0.239).

Comparison of live birth for IPTW data

Based on the IPTW data analysis, the CNY group also showed a lower live birth rate than that of the N-CNY group (OR=0.64, 95%CI 0.47-0.87, p=0.005) (Table 7).

Higher morbidity in hospitals during off-hours such as holidays and nighttime has been reported in numerous medical specialties. Studies have suggested that the obstetrics often encounter severe adverse neonatal events at nighttime ¹⁰ and on weekends ¹¹. In this study, we examined the monthly IVF outcome for fresh embryo transfer cycles retrospectively and found that the lowest monthly live birth rate resulted from procedures performed in January and February, apparently the CNY holiday season. Precisely, the embryo transfer month with the lowest live birth rate was February, even 15.1% lower than January. We have several speculations for this live birth rate decline in the CNY holiday season.

Owing to the long-lasting tradition, the vast majority, if not all, of Chinese people inevitably experience abrupt changes in their daily life, such as unhealthy diet, frequent tobacco and alcohol consumption related to family and social gatherings, and sleep deprivation, etc. Although such a lifestyle change just lasts two months, it may compromise overall health condition and therefore affect IVF success rates ¹². People tend to gain weight from eating excessively during the holiday season ^13,14 thus taking up more salt, sugar, and fatty food than usual, leading to imbalanced nutrition, which is no exception for the CNY. Fatty meals can have acute adverse effects on oocyte mitochondria ¹⁵, and high-fat diets are detrimental to male fertility ¹⁶. A prospective study concluded that five Chinese food patterns, and the western food style "Puffed food-Candy-Bakery" were related to a lower likelihood of achieving biochemical pregnancy ¹⁷. A primate study involving a short-term high-fat western-style diet before IVF treatment demonstrated that high-fat diet reduces blastocyst numbers, dysregulates RNA binding and mitochondrial function ¹⁸. Consumption of higher sugar-containing beverage is associated with lower number of total, mature, and fertilized oocytes as well as lower number of top-quality embryos after ovarian stimulation ¹⁹. Higher intake of supplemental folic acid, vitamin B12, vitamin D, produce with low pesticide residue, whole grains, dairy, soy foods and seafood were defined as pro-fertility diet, which was associated with an increased probability of live birth of women undergoing IVF ²⁰. During the CNY holiday season, people tend to change their diet in order to acquire more tasty foods, which contain more fat, salt, sugar. Such diet pattern shift could therefore reduce the intake of pro-fertility nutriments.

Frequent family and social gatherings during the CNY holiday season create occasions for excessive tobacco exposure and alcohol consumption. On one hand, smokers typically smoke more as cigarette gifting and sharing is part of the CNY tradition. On the other hand, non-smokers increasingly suffer from secondhand smoke at many occasions. It has been suggested that sharing cigarettes in China is a significant impediment to smoking cessation ²¹. According to a previous study, exposure to tobacco by women increased the risk of implantation failure by 17% and reduced the live birth success by 19% following IVF ²². Such negative impacts of tobacco exposure depend on hormonal status, individual health conditions, the amount of tobacco exposure, the total length of exposure time, and personal sensitivity to cigarettes ²³. Compelling evidence has demonstrated that smoking negatively influences IVF outcomes ^24-26. Moreover, using of both e-cigarette and regular cigarette by women was associated with small-for-gestational-age birth ^27,28. A meta-analysis across twenty different studies with 5,865 subjects in total showed that the exposure to smoking had negative impacts on semen ²⁹, which may reduce the efficacy of assisted reproductive technology (ART). Also, smoking induces DNA damage in sperms ^30,31 thereby influencing IVF outcomes ^24,32. Altogether, increased tobacco exposure by both partners may contribute to the LBR decline from IVF performed during the CNY holiday season.

The CNY holiday celebration is widely linked to alcohol abuse ³³. One study found that female and male alcohol consumption is a primary risk factor for IVF ³⁴. Female alcohol consumption was associated with a decreased number of oocyte retrieval and an increased risk of miscarriage. For males, one additional drink per day increased the risk of not achieving a live birth and drinking one month before IVF increased the risk of spontaneous miscarriage. When both of the couple drink, as few as four alcoholic drinks per week may cause a decrease in IVF live birth rate ³⁵.

It’s common that people change their sleep patterns drastically and even get sleep deprived due to festival celebration and holiday travel. The traditional celebration involves staying up late or even staying up all night long on New Year’s Eve. A systematic review showed female and male fertility and IVF outcomes may suffer from decreased sleep duration and chronotype ³⁶.

Besides above-mentioned lifestyle changes, emotional stress is another critical factor for live birth of IVF performed during the CNY holiday season. During the CNY holiday season, patients feel stressed from making decisions about whether or not to interact with certain relatives or friends due to financial pressures as travel, gifts purchasing, entertaining, and alcohol consumption can be significant expenses. One study showed that holiday sedentary behavior can have an indirect impact on anxiety through neurobiological markers³⁷. Stress also increased by traveling and interacting with visitors during the Chinese New Year holiday season. Patients receiving IVF during this period would be stressed from IVF itself and the CNY preparation and celebration. Several studies showed that stress had negative impacts on IVF outcomes, i.e., number of oocyte retrieval, fertilization, pregnancy, spontaneous abortion, live birth, multiple gestations, and low birth weight. A meta-analysis including 43 articles showed that psychological stress might diminish IVF success rates, possibly due to hypothalamic dysfunction either via neurotransmission alterations, catecholamine depletion, or interference with hypothalamic receptors for neurotransmitters ³⁸. Elevated glucocorticoid levels due to stress could have inhibitory effects on steroidogenesis, spermatogenesis, and sperm maturation. A study indicated that psychological stress among men at the time of oocyte retrieval had negative impacts on sperm quality ³⁹. Moreover, a cross-sectional study showed a negative association between self-reported stress and sperm parameters ⁴⁰.

Many studies assessed the impact of psychological stress on IVF outcomes. Ebbesen demonstrated that stressful life-events have a negative impact on the chances of successful IVF outcome ⁴¹. A meta-analysis showed a small but significant association between stress and reduced pregnancy chances in female patients receiving ART ⁴² . A study on 160 infertile women undergoing IVF demonstrated that psychological stress was negatively linked to IVF outcomes ⁴³. Women with excessive stress may have a very high risk of not achieving a successful live birth delivery ⁴⁴. Several evaluation methods have been used for assessing psychological stress. PHQ-9 (Patient Health Questionnaire-9) and PHQ-2 (Patient Health Questionnaire-2) are easy-to-use measures of depressive symptoms that are suitable for infertility patients ⁴⁵. Haimovici et al. evaluated psychological stress by questionnaires and visual analog scales, and analyzed cytokines in serum, semen, cervicovaginal, and follicular fluids. This study speculated that stress-induced cytokines in both partners may be indicative of IVF failure ⁴⁶. A study testing the influence of psychological stress on embryo cleavage kinetics ⁴⁷ demonstrated that a stress management program offered to the infertile couples, was able to retard first embryo cleavage and accelerate embryo compaction. Taken together, avoiding psychological stress on both partners receiving IVF is beneficial to increase the success rate.

Travel also affects IVF outcomes. People have many travel plans during the Chinese New Year holiday season, so patients tend to rush to have their IVF to be completed prior to traveling. On the other hand, medical staff may also travel, leading to work shift changes during the holiday season that may impact the IVF outcome ^48,49. For instance, during the CNY holiday season, patients may have their follow-ups handled by doctors and nurses who may not be familiar with their situations. Future studies are warranted to assess the potential effect of medical staff changes on IVF outcomes.

Limitations

Firstly, as a retrospective study, some variables, which may have negative impact on the live birth rate, were not recorded, such as smoking, BMI changing, sleep quantity and quality, travel, and psychological stress. Secondly, our study focused on the live birth rate of the first fresh implantation cycle, while the cumulative live birth rate during the holiday season compared with the non-holiday season is still unknown. Thirdly, our results are only based on data from our IVF center. It’s unclear whether the holiday season impacts other cities as social cultures vary across China. Future prospective multi-center studies will provide new insights into those above factors that may affect the live birth rate.

This study for the first time demonstrated the existence of a previously unknown decline in the live birth rate from IVF fresh cycles whose embryo transfer occurred during the CNY holiday season. It is possible that the transient but dramatic and mostly unhealth life-style changes associated with the CNY celebration, emotional stress and increased travel may all contribute to this decline. It is advisable that patients should avoid receiving their IVF in the CNY holiday season, if possible at all. More importantly, future studies are encouraged to identify the detailed mechanisms underlying the effects of the Chinese New Year holiday season on IVF outcomes, and to develop effective strategies to improve outcomes for patients admitted during the CNY holiday season.

Funding Statement: This study was supported by Jiajia Zhai’s Scientific Research Fund Project of Hebei Provincial Health and Family Planning Commission (20211494); Guimin Hao’s Natural Science Foundation of Hebei Province (Beijing-Tianjin-Hebei Cooperation Special Project) (H2019206707), Science and Technology Program of Hebei (20377714D).

Ethics approval and consent to participate

This work was approved by the ethical committee of The Second Hospital of Hebei Medical University (Approvalnumber:2022-R060). All subjects signed their informed consents before treatments. All procedures were performed in accordance with the relevant guidelines and regulations.

Funding

This study was supported by Natural Science Foundation of Hebei Province (Beijing-Tianjin-Hebei Cooperation Special Project) under Grant (H2019206707), S&T Program of Hebei under Grant (20377714D), Hebei Province Medical Science Research Key Project (20211494).

Author's Roles

Jiajia Zhai and Junyan Zhang made substantial contributions to the design and conception of this study. Jiajia Zhai was involved in the data acquisition, analysis, and interpretation. Junyan Zhang and Jingfang He were responsible for statistical analysis and making tables and figures. Guanqun Li reviewed all the references and amended the expression of this article. Guimin Hao was in charge of the protocol and approved the submitted version. All authors were involved in drafting and giving final approval of this article.

Data availability

The datasets analyzed during the current study available from the corresponding author on reasonable request.

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Table I. Baseline characters of all participants

	Non-holiday Season (n=4449)	Holiday Season (n=239)	p-value
Age
Mean±sd	30.88±4.45	31.19±4.72	0.293
Min-max	20-48	21-48
Infertility years
≤5 year	3637 (81.75%)	193 (80.75%)	0.396
5~10 years	707 (15.89%)	43 (17.99%)
>10 year	105 (2.36%)	3 (1.26%)
Education
≤6 years	136 (3.06%)	5 (2.09%)	0.048
6-9 years	1418 (31.87%)	67 (28.03%)
9~12 years	840 (18.88%)	62 (25.94%)
>12 year	2055 (46.19%)	105 (43.93%)
FSH
Mean±sd	7.99±3.21	7.64±2.31	0.207#
Median(q1-q3)	7.53(6.36-8.96)	7.34(6.16-8.77)
E2
Mean±sd	49.75±52.11	45.69±48.82	0.047#
Median(q1-q3)	40(27-58)	39(24.5-53)
P
Mean±SD	1.04±3.88	0.7±0.56	0.544#
Median(Q1-Q3)	0.6(0.38-0.9)	0.59(0.38-0.86)
PRL
Mean±SD	18.09±97.21	15.76±17.11	0.921#
Median(Q1-Q3)	12.5(9.23-17.28)	12.41(9.34-17.06)
LH
Mean±SD	7.26±110.64	4.56±2.42	0.002#
Median(Q1-Q3)	4.44(3.25-6.24)	4.11(3.02-5.61)
T
Mean±SD	0.43±0.17	0.44±0.16	0.776#
Median(Q1-Q3)	0.44(0.32-0.56)	0.44(0.32-0.57)
AMH
Mean±SD	3.03±2.05	3.01±2.16	0.582#
Median(Q1-Q3)	2.59(1.56-4.01)	2.56(1.59-3.62)
Classification of infertility			0.307
Primary	2232 (50.17%)	128 (53.56%)
Secondary	2217 (49.83%)	111 (46.44%)

AMH, anti-Müllerian hormone; E2, estrogen; FSH, Follicle-Stimulating Hormone;

LH, luteinizing hormone; P, progesterone; PRL, prolactin; T, testosterone
# Mann-Whitney test

Table II. Outcome of ART for all participants

	Non-holiday Season (n=4449)	Holiday Season (n=239)	p-value
Treatment regimen
Natural cycles or short cycle	16 (0.36%)	0 (0.00%)	<0.001
Antagonist protocol	1103 (24.79%)	85 (35.56%)
GnRH agonist protocol	1973 (44.35%)	102 (42.68%)
Depot GnRHa protocol	1357 (30.50%)	52 (21.76%)
Number of oocytes
0-5	877 (19.74%)	55 (23.11%)	0.458
6~10	1578 (35.52%)	76 (31.93%)
11~15	1291 (29.06%)	73 (30.67%)
16 and more	697 (15.69%)	34 (14.29%)
Clinical pregnancy
No	2185 (49.11%)	140 (58.58%)	0.004
Yes	2264 (50.89%)	99 (41.42%)
Pregnancy loss
No	4115 (92.49%)	217 (90.79%)	0.334
Yes	334 (7.51%)	22 (9.21%)
Live birth
No	2519 (56.62%)	162 (67.78%)	<0.001
Yes	1930 (43.38%)	77 (32.22%)

# Mann-Whitney test

Table III. Univariate analysis and Multivariate logistic analysis for all participants

	Univariate analysis					Multivariate analysis
	n(%)		OR(95%CI)		Crude P	OR(95%CI)	Adjusted P
Age
≤35	3950 (84.26%)		1.0
>35	738 (15.74%)		0.43 (0.36, 0.52)		<0.001	0.50(0.42, 0.60)	<0.001
Education
≤6 years	141 (3.01%)		1.0
6-9 years	1485 (31.68%)		1.05 (0.74, 1.49)		0.786
9~12 years	902 (19.24%)		0.93 (0.65, 1.33)		0.682
>12 year	2160 (46.08%)		1.09 (0.77, 1.54)		0.635
Infertility years
≤5 year	3830 (81.7%)		1.0
5~10 years	750 (16%)		1.07 (0.92, 1.26)		0.380
>10 year	108 (2.3%)		0.79 (0.53, 1.17)		0.245
FSH
≤10	3968 (84.64%)		1.0
>10	720 (15.36%)		0.79 (0.67, 0.93)		0.004	0.96(0.81, 1.14)	0.641
E2
≤55	3411 (72.76%)		1.0
>55	1277 (27.24%)		0.84 (0.74, 0.96)		0.010	0.86(0.75, 0.98)	0.026
P
≤1	3761 (80.23%)		1.0
>1	927 (19.77%)		0.97 (0.84, 1.12)		0.664
PRL
≤10	1452 (30.97%)		1.0
>10	3236 (69.03%)		1.01 (0.89, 1.14)		0.918
LH
≤5	2822 (60.2%)		1.0
>5	1866 (39.8%)		1.03 (0.92, 1.16)		0.624
T
≤0.45	2530 (53.97%)		1.0
>0.45	2158 (46.03%)		1.23 (1.10, 1.38)		0.001	1.14(1.01, 1.28)	0.036
AMH
≤3	2740 (58.45%)		1.0
>3	1948 (41.55%)		1.47 (1.31, 1.66)		<0.001	1.15(1.01, 1.32)	0.036
Reason of infertility
Primary	2360 (50.34%)	1.0
Secondary	2328 (49.66%)	0.86 (0.76, 0.96)		0.010		0.98(0.87, 1.11)	0.778
Treatment regimen
Natural cycles or short cycle	16 (0.34%)	1.0
Antagonist protocol	1188 (25.34%)	1.65 (0.53, 5.14)		0.3903
GnRH agonist protocol	2075 (44.26%)	2.40 (0.77, 7.48)		0.1299
Depot GnRHa protocol	1409 (30.06%)	2.64 (0.85, 8.21)		0.0946
Oocyte retrieval season
Non-summer time	2573 (55.14%)	1.0
Summer time(May-August)	2093 (44.86%)	1.10 (0.98, 1.23)		0.120
Holiday season
Non holiday season (Mar. ~ Dec.)	4449 (94.9%)	1.0
Holiday season (Jan ~ Feb)	239 (5.1%)	0.62 (0.47, 0.82)		0.001		0.62(0.47, 0.82)	0.001
Number of oocytes retrieval
0-5	932 (19.91%)	1.0
6-10	1654 (35.33%)	1.62 (1.37, 1.92)		<0.001		1.17( 1.09, 1.25)	<0.001
11-15	1364 (29.14%)	2.09 (1.76, 2.49)		<0.001
16 and more	731 (15.62%)	2.06 (1.68, 2.51)		<0.001

AMH, anti-Müllerian hormone; E2, estrogen; FSH, Follicle-Stimulating Hormone;

LH, luteinizing hormone; P, progesterone; PRL, prolactin; T, testosterone

Table IV. Multivariate logistic analysis for participants implanted during wintertime (Jan., Feb., Nov. &Dec.)

	Multivariate analysis
	OR(95%CI)	Adjusted P
Age
≤35
>35	0.71(0.48, 1.07)	0.103
FSH
≤10
>10	0.88(0.58, 1.32)	0.525
E2
≤55
>55	0.89(0.67, 1.19)	0.427
T
≤0.45
>0.45	1.35(1.04, 1.76)	0.024
AMH
≤3
>3	1.25(0.93, 1.66)	0.138
Reason of infertility
Primary
Secondary	0.79(0.61, 1.04)	0.092
Holiday season
Non holiday season wintertime (Nov. ~ Dec.)
Holiday season (Jan. ~ Feb.)	0.61(0.45, 0.84)	0.002
Number of oocytes
0-5
6-10	1.25( 1.07, 1.46)	0.004
11-15
16 and more

AMH, anti-Müllerian hormone; E2, estrogen; FSH, Follicle-Stimulating Hormone;

LH, luteinizing hormone; P, progesterone; PRL, prolactin; T, testosterone

Table V. Characters for matched participants

	Non-holiday Season (n=469)	Holiday Season (n=236)	p-value
Age
Mean±sd	31.21±4.54	31.19±4.74	0.96
Min-max	20-46	21- 48
Infertility years
≤5 year	387(82.52%)	190 (80.51%)	0.307
5~10 years	70(14.93%)	43 (18.22%)
>10 year	12(2.56%)	3 (1.27%)
Education
≤6 years	7(1.49%)	5 (2.12%)	0.889
6-9 years	139(29.64%)	67 (28.39%)
9~12 years	110(23.45%)	59 (25%)
>12 year	213(45.42%)	105 (44.49%)
FSH
Mean±sd	7.66±2.41	7.66±2.32	0.891#
Median(q1-q3)	7.35(6.26-8.7)	7.36(6.16-8.84)
E2
Mean±sd	47.58±42.15	46.03±49.01	0.116#
Median(q1-q3)	40(28-59)	39(25-53.25)
P
Mean±SD	0.68±0.61	0.7±0.56	0.449#
Median(Q1-Q3)	0.57(0.36-0.84)	0.59(0.39-0.86)
PRL
Mean±SD	14.46±10.5	15.73±17.2	0.745#
Median(Q1-Q3)	12.74(9.4-16.52)	12.4(9.33-16.91)
LH
Mean±SD	4.58±2.74	4.57±2.43	0.646#
Median(Q1-Q3)	3.95(2.98-5.5)	4.12(3.02-5.62)
T
Mean±SD	0.43±0.16	0.43±0.16	0.602#
Median(Q1-Q3)	0.44(0.32-0.55)	0.44(0.32-0.57)
AMH
Mean±SD	2.95±2.04	2.97±2.13	0.948#
Median(Q1-Q3)	2.41(1.46-3.98)	2.54(1.55-3.6)
Reason of infertility			0.474
Primary	239 (50.96%)	127 (53.81%)
Secondary	230 (49.04%)	109 (46.19%)

AMH, anti-Müllerian hormone; E2, estrogen; FSH, Follicle-Stimulating Hormone;

LH, luteinizing hormone; P, progesterone; PRL, prolactin; T, testosterone

# Mann-Whitney test

Table VI. Outcome of ART for matched participants

	Non-holiday Season (n=469)	Holiday Season (n=236)	p-value
Treatment regimen
Natural cycles or short cycle			0.915
Antagonist protocol	167 (35.61%)	82 (34.75%)
GnRH agonist protocol	205 (43.71%)	102 (43.22%)
Depot GnRHa protocol	97 (20.68%)	52 (22.03%)
Number of oocytes
0-5	101 (21.54%)	55 (23.40%)	0.412
6~10	177 (37.74%)	75 (31.91%)
11~15	121 (25.80%)	71 (30.21%)
16 and more	70 (14.93%)	34 (14.47%)
Clinical pregnancy
No	237 (50.53%)	139 (58.90%)	0.036
Yes	232 (49.47%)	97 (41.10%)
Pregnancy loss
No	437 (93.18%)	214 (90.68%)	0.239
Yes	32 (6.82%)	22 (9.32%)
Live birth
No	269 (57.36%)	161 (68.22%)	0.005
Yes	200 (42.64%)	75 (31.78%)

Table VII. Comparison of live birth for IPTW data

	Multivariate analysis
	OR(95%CI)	Adjusted P
Non holiday season (Mar. ~ Dec.)
Holiday season (Jan ~ Feb)	0.64(0.47, 0.87)	0.005

No competing interests reported.

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Declined Live Birth Rate from In Vitro Fertilization Fresh Cycles Performed during Chinese New Year Holiday Season

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Abstract

Figures

Introduction

Materials And Methods

Ethical Approval

Inclusion Criteria

Exclusion Criteria

Implementation procedure

Data Retrieval

Outcomes

Statistical Analysis

Results

Patient and Clinical Characteristics

Outcomes of Assisted Reproductive Technology (ART) for all participants

Live birth results for all participants

Multivariate logistic analysis for participants receiving IVF during regular wintertime

Outcome of ART for matched participants

Comparison of live birth for IPTW data

Discussion

Limitations

Conclusion

Declarations

References

Tables

Table I. Baseline characters of all participants

Table II. Outcome of ART for all participants

Table III. Univariate analysis and Multivariate logistic analysis for all participants

Table IV. Multivariate logistic analysis for participants implanted during wintertime (Jan., Feb., Nov. &Dec.)

Table V. Characters for matched participants

Table VI. Outcome of ART for matched participants

Table VII. Comparison of live birth for IPTW data

Additional Declarations

Supplementary Files

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