Effect of anxiety and depression symptoms in pregnancy on Apgar score and birth weight of newborns

Abstract

BACKGROUND

Anxiety and depression during pregnancy are relatively common among pregnant women, with a prevalence rate reaching 30% in some regions of China. Existing studies suggest that maternal psychological states during pregnancy may influence fetal development through neuroendocrine mechanisms and are associated with neonatal outcomes. However, the relationship between these factors and specific neonatal indicators such as Apgar score and birth weight remains incompletely understood.

AIM

To investigate the effects of anxiety and depressive symptoms during pregnancy on the Apgar score and birth weight of newborns.

METHODS

This study enrolled 100 primiparous women who registered and delivered at our hospital between October 2021 and October 2024. Participants were categorized into a normal group (70 cases) and an adverse outcome group (30 cases) based on neonatal outcomes. We collected and compared the general information, sleep status, mode of delivery, fasting blood glucose, and other clinical indicators of the two groups of pregnant women in the third trimester. Using logistic regression analysis, receiver operator characteristic (ROC) curves, and correlation analysis, we examined the relationship between pregnancy anxiety/depression symptoms and neonatal Apgar scores and birth weight.

RESULTS

The adverse outcome group exhibited significantly higher Self-Rating Anxiety Scale (SAS), Self-Rating Depression Scale (SDS), pregnancy stress scores, and fasting blood glucose levels compared to the normal group (all P < 0.05). Additionally, they showed poorer sleep quality, lower natural delivery rates, shorter gestational age, lower newborn birth weight, shorter body length, and lower 5-minute Apgar scores. Logistic regression analysis revealed that SAS, SDS, poor sleep quality, and pregnancy stress scores were independent risk factors for adverse neonatal outcomes (all P < 0.05). ROC analysis demonstrated that SAS and SDS had area under the curve values of 0.958 and 0.979, respectively, indicating strong predictive power for adverse neonatal outcomes (all P < 0.05). Correlation analysis showed negative correlations between anxiety/depression scores and 5-minute Apgar scores (R = -0.60, P < 0.001; R = -0.66, P < 0.001, respectively) and birth weight (R = -0.80, P < 0.001; R = -0.81, P < 0.001, respectively).

CONCLUSION

Pregnancy-related anxiety, depressive symptoms, poor sleep quality, and high stress levels are independent risk factors for adverse neonatal outcomes. The SAS and SDS scales demonstrate strong predictive value for such outcomes. Clinicians should prioritize maternal mental health, which supports healthy neonatal development.

Key Words: Digital subtraction angiography-guided procedure; Drug-eluting bead transcatheter arterial chemoembolization; Transcatheter arterial chemoembolization failure/refractoriness; Hepatocellular carcinoma; Influencing factors

Core Tip: This study demonstrates that anxiety [Self-Rating Anxiety Scale (SAS)] and depression [Self-Rating Depression Scale (SDS)] symptoms during pregnancy are significant independent risk factors for adverse neonatal outcomes, including lower Apgar scores and reduced birth weight. The SAS and SDS showed high predictive value (area under the curve: 0.958 and 0.979, respectively). The findings underscore the critical need for early screening and intervention for maternal psychological distress to improve neonatal health.

INTRODUCTION

Pregnant women are in a uniquely challenging period both physiologically and psychologically. A global survey on maternal psychology revealed that the prevalence of depressive and anxious symptoms during pregnancy was 19.7% and 24.8%, respectively[1]. Data from China indicate that in some regions, economic pressures and marital stressors may lead to prevalence rates of prenatal anxiety and depression as high as 30%, highlighting the widespread prevalence of pregnancy-related psychological issues among expectant mothers[2]. Growing evidence suggests that maternal psychological states during pregnancy may influence fetal development through neuroendocrine and immune regulatory pathways. For instance, Abrishamcar et al[3] found a significant association between maternal stress/depression and DNA methylation patterns in the first year of life. Smew et al[4] demonstrated that the relaxation group exhibited significantly lower preterm birth rates compared to the anxiety/tension group, with newborns averaging 3.5 cm longer at birth, indicating substantial maternal psychological impact on neonatal outcomes. Apgar score and birth weight remain core indicators for assessing neonatal health[5]. The Apgar score comprehensively reflects cardiopulmonary function and neurological responsiveness at birth, while birth weight serves as a critical measure of fetal nutrition and maturity[6]. However, the specific mechanisms linking maternal anxiety/depression symptoms to neonatal Apgar scores and birth weight remain incompletely understood. Therefore, this study aims to investigate the relationship between maternal anxiety and depressive symptoms during pregnancy and neonatal outcomes (Apgar score and birth weight), in order to reveal the underlying mechanisms and thereby improve pregnancy outcomes.

MATERIALS AND METHODS

Research object

This study adopted a case-control study design, selecting 100 primiparous women who established pregnancy records and delivered at our hospital between October 2021 and October 2024 as the study subjects.

Inclusion criteria: (1) Singleton pregnancy and gestational age between 14 weeks and 37 weeks at enrollment; (2) Intact communication and cognitive function; (3) Local permanent residents who agreed to return for postpartum follow-up; (4) Provided written informed consent; and (5) Had a prenatal record at our hospital and planned to deliver here.

Exclusion criteria: (1) Pre-existing diagnosis of depression, anxiety, or other mental disorders before pregnancy; (2) Occurrence of miscarriage, fetal developmental abnormalities, or stillbirth during pregnancy; (3) Presence of severe obstetric complications or other serious pregnancy-related conditions; (4) Presence of intellectual or cognitive impairment, unable to complete questionnaire assessments independently; or (5) Inability to cooperate in completing the relevant procedures of this study for any other reason.

Sample size calculation: According to Kendall's sample size estimation principle[7], the required sample size should be 5 to 10 times the number of independent variables. This study included 15 independent variables, and the initial estimated sample size range was 75-150 cases. Considering approximately a 15% rate of invalid questionnaires, the final sample size was increased to a range of 88-176 cases. During the actual survey, 115 questionnaires were distributed, 110 were retrieved, and after review, 100 valid questionnaires were obtained, resulting in an effective questionnaire recovery rate of 86.96%. All valid questionnaire data were included in the final statistical analysis.

Methods

Psychological assessment: During the third trimester, the psychological status of pregnant women was assessed using the Self-Rating Anxiety Scale (SAS) and the Self-Rating Depression Scale (SDS) during routine prenatal examinations. Both scales consist of 20 items each, employing a 1-4-point scoring system. The cut-off scores for SAS and SDS were 50 and 53, respectively, with higher scores indicating more severe anxiety or depressive symptoms. In this study, the Cronbach’s α for SAS and SDS were 0.81 and 0.82, respectively. Based on the scores from these two scales at the time of hospital admission, the corresponding standard scores for each pregnant woman were calculated[8].

Collection of general information: General data including maternal age, gestational age, SAS and SDS scores, as well as disease-related information such as employment status during pregnancy, sleep quality, pregnancy stress status, gravidity, and mode of delivery were collected.

Assessment of pregnancy stress: Pregnancy stress was evaluated using the Pregnancy Stress Rating Scale (PSRS)[9]. This scale consists of 30 items, with 27 of them distributed across three dimensions such as parental role identification stress, while the remaining 3 are independent items not included in the dimensional scoring. All items are rated on a 4-point scale from 0 to 3, with the total score ranging from 0 to 90. A higher score indicates a greater level of pregnancy stress. In this study sample, the scale demonstrated a Cronbach's α coefficient of 0.87, indicating good reliability.

Pregnancy outcome follow-up and grouping

Based on medical records, the collected pregnancy outcome indicators primarily included gestational age at delivery, mode of delivery, as well as neonatal birth weight, length, and Apgar score. In this study, neonates meeting any of the following criteria were defined as having an "adverse outcome": (1) Birth weight < 2500 g; and (2) 5-minute Apgar score < 7. Accordingly, the cases were divided into a normal group (70 cases) and an adverse outcome group (30 cases).

Quality control

This study implemented rigorous quality control measures. All research personnel received uniform training to ensure consistent assessment standards. Data were collected using standardized scales widely adopted both domestically and internationally, all of which demonstrated good reliability in this study. Questionnaires were distributed and collected on-site immediately for data acquisition to ensure questionnaire completeness. Data management utilized a dual independent entry and cross-verification mechanism, and a database was established using professional statistical software with set value ranges and logical check rules. Collinearity diagnostics were performed on all independent variables prior to statistical analysis to ensure model stability.

Statistical analysis

Data analysis was performed using SPSS 27.0 software. Measurement data conforming to a normal distribution are expressed as mean ± SD, and intergroup comparisons were conducted using the t-test. Count data are expressed as n (%), and intergroup comparisons were conducted using the χ² test. The influencing factors of adverse outcomes were analyzed by multivariate Logistic regression. The predictive efficacy of influencing factors on pregnancy outcomes was analyzed using the receiver operator characteristic (ROC) curve. Furthermore, Pearson correlation analysis was used to examine the relationships between anxiety and depression levels and neonatal Apgar scores and birth weight. The test level was set at α = 0.05, and a P value < 0.05 was considered statistically significant.

RESULTS

Comparison of clinical data between the two groups of neonates

The proportion of pregnant women working during pregnancy (43.33% vs 65.71%) and the rate of natural delivery (23.33% vs 81.43%) in the adverse outcome group were significantly lower than those in the normal group (P < 0.05). Conversely, the proportion of poor sleep status (36.67% vs 22.86%), SAS score (57.23 ± 8.18 vs 40.77 ± 4.06), SDS score (56.23 ± 6.13 vs 41.01 ± 5.06), pregnancy stress scale score (53.13 ± 6.75 vs 47.56 ± 6.41), and fasting blood glucose (6.35 ± 0.77 mmol/L vs 6.03 ± 0.65 mmol/L) were significantly higher than those in the normal group (all P < 0.05). Additionally, the gestational age (37.00 ± 2.38 weeks vs 38.67 ± 2.03 weeks), birth weight (2712.15 ± 532.75 g vs 2986.45 ± 237.13 g), length (47.83 ± 3.49 cm vs 49.63 ± 1.46 cm), and 5-minute Apgar score (9.54 ± 0.45 vs 9.76 ± 0.28) of neonates in the adverse outcome group were significantly lower than those in the normal group (P < 0.05; Table 1).

Table 1 Comparison of clinical data between the two groups of neonates.

Group		Adverse outcome group (n = 30)	Normal group (n = 70)	t/χ2	P value
Age (year)		29.17 ± 2.23	28.87 ± 2.12	0.629	0.531
Gestational week		37.83 ± 1.78	38.17 ± 2.01	0.795	0.428
BMI (kg/m2)		25.28 ± 1.56	25.48 ± 1.45	0.619	0.538
Education	Primary school	7 (23.33)	15 (21.43)	0.077	0.994
	Junior high school	7 (23.33)	17 (24.29)
	High school	8 (26.67)	18 (25.71)
	College or above	8 (26.67)	20 (28.57)
SAS score		57.23 ± 8.18	40.77 ± 4.06	10.481	0.000
SDS score		56.23 ± 6.13	41.01 ± 5.06	12.923	0.000
Did you work during pregnancy	Yes	13 (43.33)	46 (65.71)	4.349	0.037
	No	17 (56.67)	24 (34.29)
Occupation	Administrative organ	1 (3.33)	4 (5.71)	5.267	0.261
	Public institution	1 (3.33)	14 (20.00)
	Enterprise	10 (33.33)	21 (30.00)
	Freelancer	6 (20.00)	10 (14.29)
	Farming	0 (0.00)	0 (0.00)
	Student	0 (0.00)	0 (0.00)
	Othe	12 (40.00)	21 (30.00)
Monthly income (yuan)	< 5000	21 (70.00)	40 (57.14)	1.814	0.404
	5000-10000	7 (23.33)	26 (37.14)
	> 10000	2 (6.67)	4 (5.71)
Family history of mental illness	Have	0 (0.00)	0 (0.00)	-	1.000
	None	30 (100.00)	70 (100.00)
The impact of the epidemic on pregnancy	Hardly	14 (46.67)	44 (62.86)	6.202	0.185
	Occasionally	9 (30.00)	18 (25.71)
	Sometimes	5 (16.67)	8 (11.43)
	Often	1 (3.33)	0 (0.00)
	Always	1 (3.33)	0 (0.00)
Payment method for medical expenses	Employee medical insurance	5 (16.67)	22 (31.43)	2.633	0.268
	Resident medical insurance	14 (46.67)	30 (42.86)
	Out-of-pocket	11 (36.67)	18 (25.71)
Pregnancy times		2.07 ± 0.78	1.91 ± 0.74	0.929	0.355
Sleep condition	Good	6 (20.00)	33 (47.14)	6.548	0.038
	Average	13 (43.33)	21 (30.00)
	Poor	11 (36.67)	16 (22.86)
Pregnancy stress scale score		53.13 ± 6.75	47.56 ± 6.41	3.929	0.000
Fasting blood glucose (mmol/L)		6.35 ± 0.77	6.03 ± 0.65	2.054	0.043
Mode of delivery	Spontaneous delivery	7 (23.33)	57 (81.43)	30.789	0.000
	Forceps delivery	10 (33.33)	6 (8.57)
	Cesarean section	13 (43.33)	7 (10.00)
Gestational age (weeks)		37.00 ± 2.38	38.67 ± 2.03	3.585	0.001
Newborn weight (g)		2712.15 ± 532.75	2986.45 ± 237.13	2.708	0.011
Head circumference (cm)		32.67 ± 2.04	32.84 ± 10.67	0.133	0.895
Body length (cm)		47.83 ± 3.49	49.63 ± 1.46	2.722	0.010
5-minute Apgar score (points)		9.54 ± 0.45	9.76 ± 0.28	2.487	0.017

Data were showed as mean ± SD or n (%). BMI: Body mass index; SAS: Self-Rating Anxiety Scale; SDS: Self-Rating Depression Scale.

Logistic regression analysis of factors influencing adverse neonatal outcomes

Using the occurrence of adverse neonatal outcomes as the dependent variable (assigned values: Yes = 1, no = 0), and the factors with P < 0.05 from sections 2.1 and 2.2 as independent variables. Measurement data including SAS, SDS, PSRS score, fasting blood glucose, and gestational age were entered as actual values. Assignments were as follows: Employment during pregnancy (yes = 0, no = 1), sleep quality (good = 0, fair = 1, poor = 2), mode of delivery (spontaneous delivery = 0, forceps delivery = 1, cesarean section = 2). After univariate analysis, factors with P < 0.05 were tested for collinearity, revealing severe collinearity for employment during pregnancy, which was consequently excluded. SAS [variance inflation factor (VIF) = 5.157, tolerance = 0.468], SDS (VIF = 6.974, tolerance = 0.524), sleep quality (VIF = 5.754, tolerance = 0.595), PSRS score (VIF = 5.709, tolerance = 0.528), fasting blood glucose (VIF = 6.128, tolerance = 0.506), mode of delivery (VIF = 6.247, tolerance = 0.427), and gestational age (VIF = 5.174, tolerance = 0.534) showed no collinearity issues (VIF ≤ 10, tolerance ≥ 0.1). Multivariate logistic regression analysis identified SAS, SDS, poor sleep quality, and PSRS score as independent risk factors for adverse neonatal outcomes (all P < 0.05), as shown in Figure 1.

Figure 1 Binary logistic regression analysis of factors influencing adverse outcomes in newborns. A: Single factor forest plot; B: Multi factor forest plot. SAS: Self-Rating Anxiety Scale; SDS: Self-Rating Depression Scale.

ROC analysis

ROC analysis demonstrated that the area under the curve (AUC) values for SAS, SDS, poor sleep quality, and PSRS score were 0.958, 0.979, 0.739, and 0.641, respectively. Among these, SAS and SDS showed superior predictive performance, with P < 0.05 (Figure 2).

Figure 2 Receiver operator characteristic curve analysis. SAS: Self-Rating Anxiety Scale; SDS: Self-Rating Depression Scale.

Pearson correlation analysis of the relationship between SAS, SDS scores and neonatal 5-minute Apgar score and birth weight

Pearson correlation analysis was used to examine the relationship between maternal SAS and SDS scores during pregnancy and neonatal 5-minute Apgar scores and birth weight. The results showed that both anxiety and depression scores were negatively correlated with the neonatal 5-minute Apgar score (anxiety: R = -0.60, P < 0.001; depression: R = -0.66,P < 0.001) and birth weight (anxiety: R = -0.80, P < 0.001; depression: R = -0.81, P < 0.001), as shown in Table 2 and Figure 3.

Figure 3 Pearson correlation analysis. A-D: The relationship between Self-Rating Anxiety Scale and Self-Rating Depression Scale scores of pregnant women and 5-minute Apgar scores and birth weight of newborns during pregnancy. SAS: Self-Rating Anxiety Scale; SDS: Self-Rating Depression Scale.

Table 2 Correlation of Self-Rating Anxiety Scale and Self-Rating Depression Scale scores with the occurrence of adverse neonatal outcomes.

Project	5-minute Apgar rating		Birth weight
	r value	P value	r value	P value
Anxiety	-0.60	< 0.001	-0.80	< 0.001
Depression	-0.66	< 0.001	-0.81	< 0.001

DISCUSSION

Pregnancy is a significant life event for women, exerting profound impacts on their physical health, psychological state, and family dynamics. With evolving lifestyles and increasing workplace pressures, the risk of anxiety and depression during pregnancy is showing an upward trend[10]. Relevant studies indicate that prolonged negative emotional states in pregnant women can easily lead to endocrine disorders and a deterioration in living conditions, thereby adversely affecting childbirth[11]. The results of this study demonstrate that poor maternal psychological status during pregnancy is a risk factor for adverse neonatal outcomes, providing a theoretical foundation for clinically improving pregnancy outcomes.

This study collected maternal clinical data and found through comparison that the adverse outcome group had significantly higher SAS scores, SDS scores, prevalence of work during pregnancy, poor sleep quality, PSRS scores, fasting blood glucose levels, and proportion of non-spontaneous deliveries compared to the normal group. Conversely, gestational age, birth weight, length, and 5-minute Apgar scores were significantly lower. This indicates that mothers of neonates with adverse outcomes had poorer psychological status, suboptimal sleep quality, and were in a prolonged state of physiological stress. The underlying mechanism is hypothesized as follows: Poor psychological status or sleep disturbances in pregnant women may activate the hypothalamic-pituitary-adrenal axis, promoting the release of corticotropin-releasing hormone and cortisol[12]. Studies have shown that high cortisol levels during pregnancy can cross the placental barrier, directly inhibiting the expression of genes related to fetal growth, leading to fetal growth restriction and shortened gestational age[13]. Concurrently, psychological stress can trigger inflammatory responses, increasing levels of pro-inflammatory cytokines such as tumor necrosis factor-α and interleukin-6. This may subsequently cause placental hypoperfusion and oxidative stress damage, further impeding fetal neurodevelopment[14]. Additionally, elevated maternal fasting blood glucose, often associated with insulin resistance. The hyperglycemic environment can activate the advanced glycation end products and their receptor signaling pathway, exacerbating placental vascular endothelial dysfunction and apoptosis, thereby increasing the risks of preterm birth and non-spontaneous delivery[15]. These maternal indicators during pregnancy are interrelated, collectively contributing to placental insufficiency and abnormal fetal development, ultimately elevating the risk of adverse neonatal outcomes. The study by Suda-Całus et al[16]. explicitly stated that mothers with diabetes have a higher risk of adverse maternal and infant outcomes, which aligns with the conclusions of this study.

This study further conducted logistic regression analysis, revealing that SAS scores, SDS scores, poor sleep quality, and PSRS scores are independent risk factors for adverse neonatal outcomes. This finding is consistent with that of Arvanitidou et al[17], who reported substantial interactions between depression, anxiety, stress, and childbirth problems. The potential mechanism can be analyzed as follows: A meta-analysis showed that pregnant women with high anxiety levels had significantly increased salivary cortisol concentrations[18]. Elevated maternal cortisol and catecholamine levels can persistently act on the placenta, directly causing functional pathological changes. High cortisol levels can downregulate the activity of the placental protective enzyme 11β-hydroxysteroid dehydrogenase type 2 by up to 60%, leading to a substantial influx of active cortisol into the fetal circulation. This directly inhibits the insulin-like growth factor signaling pathway and interferes with normal fetal growth[19]. Furthermore, Duroux et al[20] mentioned in their study that prenatal stress can increase local placental pro-inflammatory cytokine levels by approximately 30%-50%, which synergistically amplifies with oxidative stress, collectively damaging placental vascular endothelium. This subsequently downregulates the function of key nutrient transporters such as glucose transporter protein GLUT1, restricting fetal growth due to impaired nutrient transport. In this context, the maturation of the fetal lungs and nervous system is severely compromised by the intrauterine environment characterized by high inflammation and high cortisol, directly leading to low Apgar scores at birth[21]. Additionally, elevated fasting blood glucose, non-spontaneous delivery, and shorter gestational age share similar causative factors with the clinical outcomes resulting from the aforementioned placental insufficiency and prematurely triggered labor, hence they were excluded in the univariate analysis. Meanwhile, the study plotted ROC curves based on SAS, SDS, poor sleep quality, and PSRS scores. Among these, SAS and SDS demonstrated high AUC values, sensitivity, and specificity, indicating their superior predictive efficacy for adverse neonatal outcomes.

The study employed correlation analysis to examine the relationship between SAS and SDS scores and neonatal Apgar scores and birth weight. It was found that as SAS and SDS scores increased, the risk of adverse neonatal outcomes also rose. The underlying mechanism may be explained as follows: Maternal anxiety levels show a significant negative correlation with the degree of DNA methylation in the placental glucocorticoid receptor gene. When hypomethylation occurs in the promoter region of this gene, the placental stress response to cortisol becomes abnormally amplified[22]. More critically, a high-cortisol environment can induce mitochondrial dysfunction. Research indicates that placental tissue from highly anxious mothers shows a significant reduction in mitochondrial DNA copy number and decreased respiratory chain complex activity[23]. Furthermore, severe psychological distress during pregnancy can suppress the mTOR signaling pathway, downregulating the expression of placental amino acid transporters. This leads to a deficiency in the raw materials necessary for the fetus to synthesize its own proteins, directly resulting in decreased neonatal birth weight[24]. Consequently, the fetus experiences not only growth restriction but also inhibited organ development. This directly explains the comprehensive decline in Apgar scores observed in neonates at birth, which is attributed to neuromuscular response delays.

CONCLUSION

In summary, SAS and SDS scores, poor sleep quality, and PSRS scores are independent risk factors for adverse neonatal outcomes. Elevated SAS and SDS scores are associated with decreased neonatal Apgar scores and reduced birth weight, demonstrating good predictive efficacy for adverse neonatal outcomes. These findings are expected to provide a theoretical basis for clinically improving neonatal outcomes. However, this study also has certain limitations. Firstly, the case-control study design employed in this study included only 30 patients in the adverse outcome group, which may affect the robustness of the results. Secondly, the definition of adverse outcomes in this study was relatively broad, potentially masking the specificity of complex pathophysiological mechanisms. Lastly, the study only assessed the psychological status of pregnant women in the third trimester, leading to excessive confounding factors in the results. Future research should be conducted with larger sample sizes, multicenter designs, and multi-timely observations to further validate the findings of this study.

ACKNOWLEDGEMENTS

We sincerely thank all the participants of this study for their valuable contributions.