Abstract
Background
It is important to recognize that childbirth and the transition to the maternal role constitute a profound identity reconstruction, involving both the physical experience of labor and the psychological adaptation to motherhood, during which many women experience unstable and intense emotional fluctuations. This study compared the pregnancy outcomes among women who exhibit varying emotional states during childbirth.
Method
Pregnant women recruited from a maternal and child health hospital had their maternal mood states assessed using the Profile of Mood States (POMS) during the active period of labor. Based on individual POMS item responses, latent profile analysis (LPA) was conducted to classify maternal emotional patterns during labor and to identify emotional patterns specific to the latent phase. Outcome measures included labor outcomes (e.g., cervical dilation and duration of labor) as well as neonatal health indicators. Analysis of covariance (ANCOVA) was used to compare pregnancy outcomes across different groups.
Results
A total of 244 women giving birth were investigated, among whom two distinct emotional groups emerged based on their experiences during childbirth: a positive mood cohort comprised 213 individuals (87.5%), while the remaining 31 (12.5%,) displayed negative emotional states. Women experiencing negative mood during childbirth displayed extended duration of cervical dilation, lower levels of umbilical artery chloride ion and pH, and higher levels of lactic acid and anion gap. Subsequent adjustments for confounding factors revealed statistically significant disparities in Full dilation of the cervix and duration of contractions (F = 4.898, p = 0.028), umbilical artery pH (F = 4.529, p = 0.034), lactic acid levels (F = 6.792, p = 0.010), and anion gap levels (F = 15.154, p = 0.000) among women.
Conclusion
Negative emotional states during childbirth can prolong Full dilation of the cervix and duration of contractions and increase the risk of subumbilical artery pH. As a result, we recommend that healthcare professionals enhance psychological support and counseling throughout the delivery process to mitigate emotional distress during labor, ultimately leading to improved pregnancy outcomes.
Supplementary Information
The online version contains supplementary material available at https://doi.org/10.1186/s12978-026-02434-6.
Keywords: Pregnancy and birthing care, Mood, Birth outcome, Latent profile analysis
Introduction
Most women of childbearing age have a normal and natural processes of pregnancy and childbirth [1], which regarded as a pivotal event in a woman’s life, encompassing a multidimensional process that includes physical, emotional, social, physiological, cultural, and psychological dimensions [2, 3]. The active period of labor is a crucial stage during which the emotional responses of the mother to take shape, exerting a significant influence on the woman’s emotions and thoughts [4], and potentially affecting the course of labor as well as the subsequent conditions of the mother and the newborn [5–7]. It’s noteworthy that a significant percentage, between 19% and 45%, of postpartum women perceive this process as traumatic [8].
Negative psychological states, including tension, anxiety, and fear, play a significant role in influencing women’s perception of pain and potentially impact their overall labor and childbirth experience [9]. Remarkably, previous studies have shown that over 20% of women undergoing natural childbirth experience emotions such as fear, anxiety, and depression. These emotional responses may influence the progression of labor and are associated with subsequent maternal psychological well-being [10, 11]. Moreover, it’s essential to acknowledge that childbirth also have repercussions on the emotional well-being of pregnant women, potentially contributing to the occurrence of adverse pregnancy outcomes [12].
Adverse pregnancy outcomes are widespread and have, in general, proven resistant to interventions aimed at reducing their occurrence [13]. The pregnancy outcomes includes prolonged labor, cesarean birth, birth traumas [14, 15], low Apgar scores. These outcomes discussed are the main cause of neonatal illness and mortality. The admission situation in the Neonatal Intensive Care Unit (NICU) [16]is an important indicator for assessing the adverse prognosis of newborns, and it is usually caused by complications such as those mentioned above or other perinatal conditions. These consequences not only exert a substantial financial strain on both healthcare systems and families but also engender a disruption in the emotional bonding experienced during the postpartum phase, thereby influencing interactions between mother and infant [17–19]. Vital parameters during childbirth encompass birth heart rate, cord blood pH, lactate levels, anion gap, chloride ion levels, blood sugar, and hemoglobin levels. These indicators hold pivotal significance in assessing the neonate’s condition at the moment of birth. They not only provide insights into the metabolic state of pregnancy and the potential presence of underlying cardiac or pulmonary ailments in the newborn [20, 21], but also dictate the necessity for resuscitation and gauge the efficacy of any intervening measures [22]. However, few studies have explored the relationship between adverse pregnancy outcomes and the negative emotional states experienced by mothers during labor.
Thus, this study aimed to identify potential variations in maternal mood states throughout the course of childbirth, and to examine differences in pregnancy outcomes among women exhibiting varying emotional states during the labor process.
Method
We recruited women admitted in active period (when the cervix has dilated nearly complete, 8–10 cm) who were only planning to undergo vaginal delivery at the delivery room of Nantong Maternal and Child Health Hospital between January 2021 and February 2022. Inclusion criteria were (1) Single fetus, cephalic presentation, and full-term pregnancy; (2) Native language is Chinese and able to understand and respond to questions, ensuring comprehension of the study procedures; and (3) Fetal heart rate within the normal range. Women who had (1) Organic disease (e.g., cardiovascular, respiratory, hepatic, or renal disorders) ; (2) Coagulation dysfunction; (3) Narrow pelvic diameter or fetal head basin mismatch; (4) Other conditions affecting emotional disorders; or (5) Mental illness were excluded. Data were collected in the form of questionnaires. All participants were well-informed about the study’s objectives, and their participation was obtained through the signing of consent forms. This study was approved by the Ethics Committee of Affiliated Maternal and Child Health Care Hospital of Nantong University (Ethics No: Y 2020010), and registered in the Chinese Clinical Trial Registry (ChiCTR2000038546).
Maternal mood state during delivery
Mood was measured using the POMS (Profile Mood States) [23]. The POMS used in this study is in the simplified Chinese version. The reliability of Chinese simplified POMS ranged from 0.62 to 0.82, with an average of 0.71 [24]. The original English version consists of 40 items that assess the participant’s current mood on a five-point Likert scale. Answers provide standardized scores for seven identified subscales: tension, anger, fatigue, depression, vigor, confusion, and self-esteem. Elevated scores on the assessment indicate a greater prevalence of negative emotional states, with the exception of two dimensions: vigor and self-esteem. The Profile of Mood States (POMS) exhibits robust internal consistency and demonstrates predictive and construct validity. Trained researchers, following uniform protocols, administered the questionnaires during the intervals between contractions in the active phase of the first stage of labor (when the cervix has dilated nearly complete, 8–10 cm). Prior to the survey, investigators provided comprehensive explanations regarding the study’s objectives and significance, as well as detailed instructions for questionnaire completion. In cases where participants encountered difficulties with the process, investigators offered assistance by reading out the questionnaire items individually and providing aid as required. Rigorous scrutiny of each questionnaire was undertaken by the investigator to minimize instances of omission or incorrect entries, thus safeguarding the credibility and authenticity of the gathered data. Midwives and pediatricians responsible for assessing maternal and neonatal outcomes were blinded to the participants’ POMS scores.
Outcome measures: pregnancy outcomes
The outcome of childbirth mainly includes factors such as duration of cervical dilation, duration of each stage of labor, total labor duration, 1-minute and 5-minute Apgar scores of the newborn, newborn heart rate, neonatal apnea, biochemical indicators of umbilical blood, and NICU transfer. Biochemical indicators of umbilical blood included umbilical artery pH, lactate levels, chloride ion levels, anion gap, and fetal blood glucose. Full dilation of the cervix and duration of contractions, duration of each stage of labor, total labor duration, 1-minute and 5-minute Apgar scores of the newborn, were assessed by midwives. The neonatal apnea and NICU transfer was diagnosed by pediatricians.
Following vaginal delivery, and once the pulsation in the umbilical cord ceased (typically occurring within 1–3 min after birth), a 1 ml sample of blood was collected from the umbilical artery using a heparinized blood gas needle prior to the cord’s ligation. Immediate measurements were performed in the delivery room using the GEM Premier 4000 automatic blood gas analyzer (manufacturer: Instrumentation Laboratory Co.; Country: America), acquiring the level of umbilical artery pH, lactate levels, chloride ion levels, anion gap, and fetal blood glucose. The measurement of umbilical blood biomarkers was performed by laboratory professionals. Supplement material Table 1.
Potential confounders
Various demographic factors were taken into account as potential confounding variables due to their probable association with both the exposure and outcomes. These factors encompassed details about the mother, including age, height, pregnancy weight gain, gestational age, education level, place of residence, marital status, occupation, parity, pregnancy complications, pain level before (The parturient reported the intensity of the pain by using a numerical rating scale at 3 cm cervical dilation) and after labor analgesia, and weight and length of newborn. Additionally, basic characteristics of the spouse/partner (e.g., age, height, weight, occupation, and educational attainment, labor analgesia) were collected. These data were obtained from clinical electronic medical records or reported by the pregnant participants during face-to-face interviews conducted by trained investigators. The spouse/partner was not enrolled as an independent study participant.
Statistical analysis
Mplus version 8.0 and IBM SPSS Statistics version 26.0 were employed for data analysis. Estimate values in lieu of missing values of four main outcome variables by using the expectation maximization (EM) algorithm before proceeding to the inferential test. Latent profiles analysis was used for classifying different mood condition for women during delivery, which was used to describe similarities and differences among individuals concerning the observed continuous variables (i.e., the mood status in this study) relate to each other [25]. The 7 sub-scales of mood condition (i.e., tension, anger, fatigue, depression, vigor, confusion, and self-esteem) were used as variables in the latent profile models.
As a first step, unconditional models with different numbers of latent profiles were estimated. Model comparisons were based on the Bayesian Information Criterion (BIC) and adjusted Bayesian Information Criterion (aBIC) [26], the Akaike Information Criterion (AIC) [27]. We utilized information criteria (AIC, BIC, and aBIC), where lower values indicate better fit, and likelihood-based tests (VLMR-LRT and BLRT) to compare the fit of k-profiles with k-1 profiles. Non-significant values (p ≥ 0.05) favored the k-1 profile. To assess classification accuracy, we reported the relative entropy, which ranges from 0.0 to 1.0, with higher values indicating greater accuracy. Additionally, we examined the average posterior probability of profile membership, where values ≥ 0.80 indicated a robust profile solution.
We assessed differences between the various profiles concerning socio-demographic characteristics using SPSS. Independent variables were selected for inclusion in the multinomial regression models if they were associated with p values < 0.05 in the univariate analysis. The relationship between mood status in delivery and birth outcomes was conducted through Student’s t test. To compare birth outcomes between groups adjusting for socio-demographic characteristics, we employed analysis of covariance (ANCOVA). p values < 0.05 were considered indicative of statistical significance. We also conducted a sensitivity analysis: the total scores of the POMS scale were calculated and grouped according to the quartile, and the lowest and highest tertiles were defined as the “low” and “high” groups, and the differences in delivery outcomes between the high-scoring group and the low-scoring group were compared.
Results
Latent profile of mood state
Taking the 7 items of the POMS scale as explicit indicators, 1 ~ 6 potential profile models were selected to conduct exploratory potential profile analysis of the mood state of women during the active period of childbirth. The model fit indices for different class solutions are presented in Table 1. Although AIC, BIC, and aBIC values continued to decrease with an increasing number of classes, the entropy values showed a declining trend after the two-class model, indicating reduced classification accuracy in more complex models. Meanwhile, the Entropy values showed a gradual decrease, consistently exceeding 0.8. Moreover, for category sizes of 4 to 6, there was a subgroup constituting less than 5% of the sample. In addition, the pLRT and pBLRT were statistically significant only for the two-class model, while they became non-significant for models with three or more classes. Considering model fit, classification accuracy, and interpretability, the two-class model was selected as the optimal solution.
Table 1.
Fit indices of the 1 to 6-profile latent models
| Group | AIC | BIC | aBIC | Entropy | pLRT | pBLRT | Class probabilities |
|---|---|---|---|---|---|---|---|
| 1 | 9860.91 | 9909.87 | 9865.492 | - | - | - | 1 |
| 2 | 9059.174 | 9136.111 | 9066.374 | 0.991 | 0.0053 | 0.0058 | 12.5/87.5 |
| 3 | 8743.757 | 8848.672 | 8753.575 | 0.965 | 0.0524 | 0.0554 | 75.6/19.0/5.4 |
| 4 | 8556.077 | 8688.97 | 8568.514 | 0.925 | 0.0826 | 0.0866 | 8.4/26.1/3.7/61.8 |
| 5 | 8450.862 | 8611.732 | 8465.917 | 0.892 | 0.2235 | 0.2295 | 45.1/20.0/8.2/23.0/3.7 |
| 6 | 8401.714 | 8590.561 | 8419.387 | 0.900 | 0.1395 | 0.1451 | 43.4/14.5/12.0/18.3/3.7/8.2 |
Characterization of latent profiles
A total of 276 women were assessed for eligibility. Among them, 32 were excluded due to not meeting inclusion criteria or declining participation. The remaining participants were enrolled and followed up, and finally 244 women completed all assessments and were included in the analysis. Plot the responses of categories 1 and 2 to the 7 entries in the POMS scale (Fig. 1). The abscissa represents the seven entries in the scale, and the ordinate represents the mean responses. In category 1, there was a higher degree of expression in the negative mood items (tension, anger, fatigue, depression, and confusion). This indicated that women in this category experienced more negative moods during delivery, leading to its designation as “negative mood-dominant,” encompassing 12.5%(n = 31) of the 244 participants totally. In contrast, category 2, which accounted for 87.5%(n = 214) of all participants, exhibited a “positive mood dominant” pattern in the POMS scale. Specifically, women in this category displayed predominately positive moods during delivery.
Fig. 1.
Potential profile of maternal mood during labor. Note: The horizontal coordinate represents the dimension of the POMS scale question, and the vertical coordinate represents the original average score of the sample in this dimension
Demographic characteristics
In this study, a total of 244 women in childbirth participated, and the study analyzed sociodemographic disparities between women and their husbands based on distinct mood dominance during childbirth. The findings demonstrated noteworthy dissimilarities between women characterized by negative mood dominance and those exhibiting positive mood dominance in terms of their husbands’ occupation (p = 0.046), pain level at 3 cm cervical dilation (p = 0.004) and after labor analgesia(p < 0.001). However, no significant differences were observed in maternal factors such as age, height, weight gain during pregnancy, gestational age, place of residence, floating population status, marital status, maternal occupation, maternal education level, parity, gravidity, husband’s age, height, weight, education level, labor analgesia and newborn birth weight or length (p > 0.05) Table 2.
Table 2.
Baseline characteristics of the study population by profile, with mean (SD) or number (%)
| Variables | Groups(N = 244) | |||
|---|---|---|---|---|
| Negative mood dominance(n = 31) | Positive mood dominance(n = 214) | Total n (%) | p | |
| Pregnant women | ||||
| Age mean(± SD) | 27.26 ± 2.569 | 27.17 ± 3.080 | 27.18 ± 3.015 | 0.885 |
| Height mean(± SD), cm | 161.52 ± 4.647 | 162.25 ± 5.089 | 162.16 ± 5.032 | 0.450 |
| Residence | 1.000 | |||
| City | 21(67.7) | 148(69.5) | 169(69.3) | |
| Village | 10(32.3) | 65(30.5) | 75(30.7) | |
| Floating population | 1.000 | |||
| Yes | 2(6.5) | 14(6.6) | 14(5.7) | |
| No | 29(93.5) | 199(93.4) | 228(93.4) | |
| Marriage | 0.658 | |||
| Unmarried | 0(0.0) | 4(1.6) | 4(1.6) | |
| Married | 31(12.7) | 209(85.7) | 240(98.4) | |
| Job | 0.420 | |||
| Public institution | 19(61.3) | 128(60.1) | 147(60.2) | |
| Worker | 1(3.2) | 7(3.3) | 8(3.3) | |
| Unemployed | 7(22.6) | 29(13.6) | 36(14.8) | |
| Liberal profession | 4(12.9) | 49(23.0) | 53(21.7) | |
| Education level | 0.948 | |||
| Junior high school and below | 3(9.7) | 18(8.5) | 21(8.6) | |
| High/vocational school | 2(6.5) | 21(9.9) | 23(9.4) | |
| College degree and undergraduate | 25(80.6) | 167(78.4) | 192(78.7) | |
| Master’s degree and above | 1(3.2) | 7(3.3) | 8(3.3) | |
| Parity | 0.600 | |||
| 0 | 31(100.0) | 206(96.7) | 237(97.1) | |
| 1 | 0(0.0) | 7(3.3) | 7(2.9) | |
| Gravidity mean(± SD) | 1.29 ± 0.461 | 1.35 ± 0.709 | 1.34 ± 0.682 | 0.638 |
| Pregnancy complication | 0.601 | |||
| Yes | 6(19.4) | 33(15.5) | 39(16.0) | |
| No | 25(80.6) | 180(74.5) | 205(84.0) | |
| Pain level at 3 cm cervical dilation mean(± SD) | 8.50 ± 0.694 | 7.53 ± 1.742 | 7.66 ± 1.676 | 0.004 |
| Pain level after labor analgesia mean(± SD) | 2.68 ± 0.945 | 1.85 ± 1.031 | 1.96 ± 1.055 | < 0.001 |
| Gestational weeks mean(± SD), week | 39.39 ± 1.054 | 39.07 ± 1.185 | 39.11 ± 1.172 | 0.160 |
| labor analgesia | 26(83.9) | 178(83.6) | 204(83.6) | 0.602 |
| Birth weight mean(± SD), g | 3402.26 ± 402.266 | 3353.00 ± 387.735 | 3359.26 ± 389.110 | 0.511 |
| Birth length mean(± SD), cm | 50.19 ± 1.108 | 49.97 ± 0.884 | 50.00 ± 0.916 | 0.209 |
| Husband condition | ||||
| Age mean(± SD), years | 29.16 ± 6.679 | 28.56 ± 2.865 | 28.64 ± 3.576 | 0.376 |
| Height mean(± SD), cm | 175.23 ± 5.626 | 175.47 ± 5.019 | 175.43 ± 5.092 | 0.800 |
| Weight mean(± SD), kg | 77.139 ± 15.318 | 75.419 ± 11.290 | 75.637 ± 11.853 | 0.459 |
| Occupation(n = 241) | 0.046 | |||
| Public institution | 18(58.0) | 130(61.9) | 148(61.4) | |
| Worker | 6(19.4) | 12(5.7) | 18(7.5) | |
| Unemployed | 0(0.0) | 5(2.4) | 5(2.1) | |
| Liberal profession | 7(22.6) | 63(30.0) | 70(29.0) | |
| Education level(n = 233) | 0.405 | |||
| Junior high school and below | 4(12.9) | 14(6.9) | 18(7.7) | |
| High/vocational school | 1(3.2) | 22(10.9) | 23(9.9) | |
| College degree and undergraduate | 25(80.7) | 156(77.2) | 181(77.7) | |
| Master’s degree and above | 1(3.2) | 10(5.0) | 11(4.7) | |
Birth outcomes
Mood grouping was used as the independent variable to compare pregnancy outcomes between “positive mood- dominant” and “negative mood- dominant” women. The results indicated that there were statistical significance in Full dilation of the cervix and duration of contractions, cord blood pH, lactate level, anion gap, and chloride ion level among women categorized into different mood groups during childbirth. Specifically, the duration of full cervical dilation (p = 0.043) was longer in “negative mood-dominated” women than those in “positive mood-dominated” women. Moreover, fetal cord blood pH in women with negative mood dominance at delivery was significantly lower than those in the positive mood predominance (p = 0.011). Additionally, within the “negative mood- dominant” group, the umbilical artery chloride ion level was lower than that in the “positive mood- dominant” group (p = 0.047). The levels of lactate (p = 0.009) and anion gap (p < 0.001) in cord blood were notably higher among women who experienced a negative mood state during delivery, as opposed to those in a positive mood condition (Table 3). After controlling for confounding variables (husband’s occupation and pain level), the results of covariance showed that there were still statistically significant differences in Full dilation of the cervix and duration of contractions (F = 4.898, p = 0.028), umbilical artery pH (F = 4.529, p = 0.034), lactate levels (F = 6.792, p = 0.01) and anion gap level (F = 15.154, p < 0.001). (Table 4).
Table 3.
Pregnancy outcomes in different mood states groups
| Outcomes | Groups | |||
|---|---|---|---|---|
| Negative mood dominance (n = 31) | Positive mood dominance (n = 213) | t/X² | p | |
| Full dilation of the cervix and duration of contractions, s | 33.55 ± 3.914 | 32.35 ± 2.935 | 2.033 | 0.043 |
| First stage of labor, min | 392.58 ± 121.606 | 393.54 ± 147.824 | -0.04 | 0.968 |
| Second stage of labor, min | 48.81 ± 31.564 | 47.33 ± 29.132 | 0.261 | 0.794 |
| Third stage of labor, min | 6.52 ± 2.174 | 6.06 ± 2.473 | 0.971 | 0.332 |
| total labor, min | 447.58 ± 128.490 | 449 ± 157.864 | -0.056 | 0.948 |
| Apgar 1 min | 9.87 ± 0.542 | 9.87 ± 0.542 | 0.024 | 0.981 |
| Apgar 5 min | 9.97 ± 0.180 | 9.99 ± 0.118 | -0.742 | 0.459 |
| Neonatal heart rate | 143.32 ± 1.617 | 141.86 ± 0.654 | 0.803 | 0.423 |
| Umbilical artery pH | 7.188 ± 0.086 | 7.220 ± 0.080 | -2.575 | 0.042 |
| Umbilical artery pH | ||||
| <7.1 | 3(9.68%) | 11(5.16%) | 1.978 | 0.372 |
| 7.1 ~ 7.2 | 14(45.16%) | 81(38.03%) | ||
| ≥ 7.2 | 14(45.16%) | 121(56.81%) | ||
| chloride, mmol/L | 102.923 ± 2.027 | 103.729 ± 2.113 | -1.995 | 0.047 |
| Lactate, mmol/L | 5.425 ± 2.056 | 4.644 ± 1.444 | 2.651 | 0.009 |
| Anion gap, mmol/L | 15.537 ± 2.822 | 13.390 ± 2.770 | 4.027 | < 0.001 |
| Fetal glucose | 5.139 ± 0.889 | 5.031 ± 1.106 | -0.45 | 0.653 |
| Birth asphyxia | 0(0.0) | 1(0.4%) | 0.146 | 1.000 |
| Transfer to NICU | 0(0.0) | 2(0.8%) | 0.293 | 1.000 |
Table 4.
Birth outcomes in different mood states group during childbirth
| Groups | ||||
|---|---|---|---|---|
| Outcomes | Negative mood dominance(n = 31) | Positive mood dominance(n = 213) | F | P |
| Full dilation of the cervix and duration of contractions, s | 33.55 ± 3.914 | 32.37 ± 2.944 | 4.898 | 0.028 |
| First stage of labor, min | 392.58 ± 121.606 | 393.70 ± 147.990 | 0.001 | 0.977 |
| Second stage of labor, min | 48.81 ± 31.564 | 47.40 ± 29.582 | 0.017 | 0.896 |
| Third stage of labor, min | 6.51 ± 2.174 | 6.07 ± 2.484 | 0.922 | 0.338 |
| total labor, min | 447.58 ± 128.490 | 449.55 ± 154.050 | 0.003 | 0.955 |
| Apgar 1 min | 9.87 ± 0.428 | 9.87 ± 0.547 | 0.025 | 0.874 |
| Apgar 5 min | 9.97 ± 0.180 | 9.99 ± 0.119 | 0.970 | 0.326 |
| Neonatal heart rate | 143.32 ± 9.001 | 141.82 ± 9.575 | 0.625 | 0.430 |
| Placental weight, g | 510.00 ± 46.332 | 507.14 ± 46.282 | 0.015 | 0.902 |
| Umbilical artery pH | 7.188 ± 0.086 | 7.220 ± 0.079 | 4.529 | 0.034 |
| chloride, mmol/L | 102.923 ± 2.027 | 103.729 ± 2.116 | 2.610 | 0.108 |
| Lactate, mmol/L | 5.425 ± 2.056 | 4.641 ± 1.446 | 6.792 | 0.010 |
| Anion gap, mmol/L | 15.537 ± 2.822 | 13.380 ± 2.740 | 15.154 | < 0.001 |
| Fetal glucose | 5.139 ± 0.889 | 5.031 ± 1.089 | 0.903 | 0.761 |
Adjust for husband occupation and pain level at 3 cm cervical dilation
Sensitivity analysis
To mitigate the possibility of generating false positives, we opted to stratify the scores obtained from the Profile of Mood States (POMS) scale into high and low POMS Score. Subsequent to this categorization, we conducted post hoc analyses to discern disparities in delivery outcomes between the high-scoring and low-scoring cohorts. Remarkably, the ultimate outcomes closely aligned with our research discoveries, indicating a potential association between negative emotional states during childbirth and prolonged cervical dilation, as well as elevated indicators of fetal acidosis. (Supplement material Table 2)
Discussion
The identification of distinct emotional profiles underscores the multidimensional nature of maternal affect during labor. In this study, differences between the “negative mood” profile and the “positive mood” profile were associated with variations in labor characteristics and neonatal metabolic indicators. In particular, differences in labor duration and acid–base measures (e.g., umbilical cord blood pH and lactate levels) were observed between groups. These findings suggest a potential link between maternal emotional patterns and childbirth outcomes.
A drop in fetal blood pH is considered as the one of the most important diagnostic criteria of Fetal acidosis, and the UK National Institute for Health and Care Excellence (NICE) and Royal College of Obstetricians and Gynaecologists (RCOG) guidelines specify a fetal blood pH < 7.2 as a Grade I indication of an emergency cesarean section [28]. Another study indicates that the umbilical artery pH (UmApH) threshold of 7.10 is associated with an increased risk of adverse neurological sequelae [29]. Moreover, the UmApH is strongly correlated with clinically significant outcomes such as neonatal mortality rate [30]. This is typically associated with placental blood flow compromise and subsequent fetal acidosis caused by fetal hypoxia and hypercapnia [29, 31]. Metabolic acidosis is significantly correlated with fetal hypoxic-ischemic brain injury [32]. In our study, we observed a noteworthy difference in the rate of cord blood pH below 7.2, with a prevalence of 54.84% in the dominant negative mood group, which was obviously higher than that in the dominant positive mood group (43.19%). Furthermore, our analysis of other biochemical markers supports this observation. Prior to controlling for potential confounding variables, we detected significant statistical differences in the postpartum cord blood levels of lactate, anion gap, and chloride ions among women with varying emotional states during childbirth. These differences bear clinical significance. The anion gap mainly consists of lactic acid, phosphoric acid and ketone bodies [33], plays a crucial role in assessing acid-base disturbances. Acidosis is typically associated with an increase in the anion gap, driven by the accumulation of non-chloride anions such as lactate [34]. The level of lactate in umbilical artery blood serves as an indicator of intrauterine distress and hypoxia-ischemia in newborns, influencing the prognosis of the infant [35, 36]. Unlike pH value and base excess, lactate more directly reflects the acid-base status at the time of birth and the pathological condition of fetal metabolic acidosis. Additionally, it is significantly correlated with the degree of neonatal neurological and myocardial injury [35, 37]. Therefore, our findings suggest that the presence of negative emotions during childbirth increases the risk of neonatal acidosis.
From a physiological perspective, this aligns with the Fear-Tension-Pain cycle [38], where negative emotional states like anxiety and anger can trigger catecholamine release [39], potentially inhibiting uterine contractility and lengthening the active phase of labor [40]. Conversely, a protracted labor experience acts as a traumatic stressor that diminishes a mother’s sense of control and security, thus “creating” a negative birth experience [41, 42] Furthermore, according to Mercer’s theory of Becoming a Mother [43], the quality of the birth experience—as reflected in our “positive” vs. “negative” profiles—serves as the foundational step in maternal role attainment. The importance of early labor pain may extend beyond its immediate physiological discomfort and may lie in its potential lasting influence on subsequent emotional experiences. The latent phase of labor is often characterized by uncertainty regarding labor progression and a diminished sense of control, which may render painful experiences particularly emotionally salient [44]. Individual’s cognitive evaluation of early painful events may continue to shape subsequent emotional responses. When pain experienced during early labor exceeds expectations, maternal perceptions of control and coping confidence may be compromised, thereby increasing the risk of anxiety, tension, and other negative emotional states during later stages of labor [45, 46]. Therefore, the association observed in this study may reflect the enduring influence of early labor pain experiences on subsequent mood states.
Furthermore, our investigation has unveiled that negative emotions experienced during the childbirth process can exert an influence on the course of labor, notably impacting the duration of continuous cervical dilation. The cervix of a woman undergoes a gradual dilation process, accompanied by the descent of the fetus into the pelvic region. This intricate process encompasses substantial physiological and psychological changes for women [47]. Primiparous women, in particular, are prone to the impact of negative emotions, resulting in prolonged labor, intensified uterine contractions, and heightened physical discomfort [48]. These negative emotions during childbirth can elevate catecholamine levels, adversely affecting both the delivery process and fetal outcomes [40, 49]. Prolonged labor carries the potential for adverse effects on the fetus, notably increasing the risk of heightened fetal acidosis [50].
In our research, we utilized potential profile analysis to categorize two distinct groups based on maternal mood during the labor process: the positive mood-leading group and the negative mood-leading group. In the existing studies, the positive emotional reactions that mothers gain during childbirth, such as a profound sense of empowerment, control, security and self-esteem, are called positive childbirth experience [51]. Conversely, negative feelings such as anger, depression and frustration have been labeled as components of a negative birth experience [52, 53]. Childbirth experience represents an independent life event intertwined with subjective psychological and physiological processes, shaped by societal and environmental influences. The energy, feelings and experience in the process of childbirth can be evaluated from the perspective of the mother [54, 55]. In our study, there were significant differences in husband occupation, pain level of 3 cm cervical dilation and painless delivery between women in positive childbirth mood and women in negative childbirth mood. Previous research has reported associations between negative childbirth experience emotions and factors such as labor pain, negative emotions in the third trimester, maternal education levels [56], and obstetric violence, including experiences of disrespect during childbirth [57].
In clinical practice, medical professionals are suggested to employ a range of methods and approaches to help mothers alleviate negative emotions during childbirth. One such approach is the provision of systematic childbirth counseling to pregnant women, offering them comprehensive information about the childbirth process [58]. Another valuable resource is the family delivery room, which offers mothers vital familial support and encouragement. Simultaneously, with the expert guidance and assistance of midwives, obstetricians, and gynecologists, it maximizes pain tolerance and mitigates negative psychological and emotional responses in pregnant women. The family-centered maternity care model that provides a stable, non-fragmented environment. Maintaining a consistent physical setting and medical staff throughout the perinatal period fosters a sense of control and trust, buffering the psychological distress and intense emotional fluctuations typically triggered by rotating staff and unfamiliar clinical environments [59, 60].
To the best of our knowledge, this represents delving into the connection between maternal mood states and pregnancy outcomes during delivery. Nonetheless, several limitations warrant consideration. Firstly, our study draws from a single center, and as such, its findings may not be universally applicable to diverse populations. Secondly, we did not assess maternal mental status prior to labor, potentially missing valuable insights into its influence on maternal mood after exposure to the tension-filled delivery ward environment. Furthermore, pain intensity was assessed at approximately 3 cm cervical dilation, whereas mood status was assessed later during labor. As pain was not measured at the time of mood assessment, we were unable to evaluate the contemporaneous relationship between pain and mood, and the observed association should be interpreted with caution. Thirdly, the imbalance in group sizes, with a relatively small number of participants in the negative mood group might have reduced statistical power and affected the stability of the estimates. Conducting surveys during active-phase deliveries may introduce response bias, potentially leading to study results favoring maternal populations with fewer physical or emotional distress experiences. Future research endeavors should delve deeper into the far-reaching implications of maternal mood during childbirth on both the mother and her offspring.
Conclusion
In this study, latent profile analysis was utilized to categorize the emotional states of women during spontaneous labor. Our results provide evidence suggesting that negative mood profiles during labor are associated with less favorable birth outcomes, particularly regarding umbilical cord blood pH and Full dilation of the cervix and duration of contractions. Consequently, we advocate for clinicians to prioritize psychological support and counseling during the delivery process. Furthermore, providing comprehensive childbirth education during pregnancy may help stabilize maternal emotions during labor, potentially reducing the risk of adverse outcomes.
Supplementary Information
Acknowledgements
Thank you to the midwives, babies, and nurses in the Affiliated Maternal and Children Health Care Hospital of Nantong University for their contributions.
Authors' contributions
Ziyi Yang helped conduct the research, analyzing the data, and writing the original and revision manuscript. Dr Feng Zhang helped outline the research design, conducted data collection and statistical analyses, drafted the initial and revised manuscripts, and approved the final manuscript as submitted. Huahua Liu and Zhifang Chen helped the research design, collected and inputted the data, conducted statistical analyses. Qiuhua Cai and Xiaoling Zhu helped draft the initial manuscript, successfully obtained the supporting research grants, and approved the final manuscript as submitted.
Funding
This work was supported by the National Natural Science Foundation of China (No.72274100); Nantong Municipal Scientific Research Project (MS2025063); Nantong Municipal Health Commission Research Projectf(QN2025048); Nantong Municipal Health Commission Research Project (MSZ2023059).
Data availability
Data can be obtained after communication with the corresponding author.
Declarations
Ethics approval and consent to participate
The study was approved by the ethics review committee of Nantong Maternal and Child Health Hospital. All participants received written informed consent. Under the premise of ensuring that subjects have normal cognitive and understanding abilities, a series of studies are conducted after informing them of the research purpose and obtaining informed consent.
Consent for publication
Not applicable.
Competing interests
The authors declare no competing interests.
Footnotes
Publisher’s note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
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Data Availability Statement
Data can be obtained after communication with the corresponding author.