Category: 3. Business

Introduction

Natural childbirth is widely recognized as a relatively safe delivery method for mothers, offering faster postpartum recovery and effectively avoiding the short- and long-term complications associated with cesarean sections.^1–3 However, the labor process for natural delivery is often prolonged, particularly for first-time mothers, and it is difficult to avoid pain caused by uterine contractions during labor. This pain not only impacts the delivery process but may also pose certain risks to maternal and neonatal safety.^4–6 Labor pain, one of the primary physiological challenges faced by mothers during childbirth, primarily stems from uterine contractions, cervical dilation, and pressure on the birth canal. Such pain can trigger significant psychological stress in mothers, potentially reducing the efficiency of contractions, prolonging labor duration, and consequently increasing the likelihood of cesarean delivery and other complications.^7–9 Although traditional supine delivery facilitates medical monitoring, it has been associated with potential disadvantages, including increased reports of maternal discomfort, compromised hemodynamics (eg, supine hypotensive syndrome), and potential narrowing of the pelvic outlet compared to upright positions, potentially exacerbating maternal discomfort and hindering fetal descent.^10–12

In recent years, non-pharmacological interventions have gained increasing attention in obstetric research and clinical practice as part of a broader movement towards humanized childbirth care.¹³ Studies have shown that evidence-based, woman-centered labor care not only facilitates smoother delivery but also effectively reduces the risk of adverse outcomes.^14,15 Among these interventions, free positioning and mindful relaxation techniques have garnered significant attention for their role in supporting the delivery process. Free positioning during labor transcends the limitations of traditional supine delivery, allowing mothers to choose positions such as standing, squatting, kneeling, or lying on their sides according to their needs and comfort. This autonomy in movement is thought to optimize the pelvic angle (potentially increasing the anteroposterior diameter), facilitate the descent and rotation of the fetus by utilizing gravity, and may reduce soft tissue resistance, thereby potentially reducing delivery difficulties and associated pain.^16–18 However, widespread implementation of free positioning faces challenges, including staff training requirements, resource constraints (eg, availability of birthing aids like balls or stools), and adherence to conventional protocols in some settings.^14,19 Meanwhile, mindful relaxation techniques (MRTs), often rooted in Mindfulness-Based Stress Reduction (MBSR) principles adapted for childbirth, involve deliberate attention regulation, non-judgmental awareness of present-moment sensations (including pain), breathing regulation, progressive muscle relaxation, and positive emotional guidance.^20,21 The core aim of MRTs is to help mothers modulate their psychological and physiological stress responses, thereby reducing the affective and cognitive components of pain perception, alleviating anxiety, and enhancing their overall sense of control and childbirth experience.^22,23 Despite documented benefits, the integration of structured MRTs into routine antenatal education and intrapartum care remains variable and is not yet standard practice globally.^24,25

Although previous studies have separately explored the roles of free positioning and mindful relaxation techniques in childbirth, rigorous research evaluating their combined application in natural delivery remains notably scarce. Systematic reviews highlight the independent benefits but lack robust evidence on synergistic effects.^26,27 Considering the complementary physiological and psychological effects of these two approaches, a synergistic interaction is theoretically plausible: free positioning primarily addresses biomechanical factors and physiological pain pathways (eg, optimizing fetal position and reducing soft tissue strain), while MRTs target the psychological and neurocognitive aspects of pain processing (eg, reducing fear-tension-pain cycles and enhancing pain coping mechanisms).^28,29 This combined approach may lead to greater overall pain reduction and labor efficiency than either intervention alone. Therefore, this study aims to examine the combined intervention’s efficacy in alleviating labor pain and shortening labor duration, thereby providing a basis for further optimization of obstetric care strategies. This investigation is particularly relevant within our institutional context in China, where there is a growing national emphasis on promoting natural childbirth and enhancing maternal satisfaction within the healthcare system,³⁰ yet barriers to implementing comprehensive non-pharmacological approaches persist.

Subjects and Methods

Study Subjects

Study Design and Ethical Considerations

This retrospective cohort study included pregnant women who delivered at Wuxi Second People’s Hospital between August 2023 and October 2024. The study was approved by the Ethics Committee of Wuxi Second People’s Hospital (Approval No.: 2022–081) and conducted in accordance with the 1964 Helsinki Declaration and its later amendments. Due to the retrospective nature of the study, the requirement for informed consent was waived by the IRB. Data collection employed an “opt-out” method, consistent with national regulations and ethical standards for minimal-risk retrospective research using anonymized data. Potential participants were informed about the study via hospital noticeboards and electronic platforms; those declining participation within two weeks were excluded. No objections were registered.

All collected data were strictly confidential and anonymized before analysis to protect participants’ privacy. Access to the data was limited to authorized research personnel only, and all data handling complied with institutional and national data protection regulations to ensure data security throughout the study.

Participants

After screening electronic medical records against predefined criteria, a total of 120 eligible participants were identified and included in the analysis. Participants were categorized into two groups based on the documented care received during delivery: the research group (n = 60), who received the combined intervention of free positioning and mindful relaxation techniques, and the Control Group (n = 60), who received routine delivery care.

Inclusion and Exclusion Criteria

Inclusion Criteria

Participants were required to meet the following criteria:

Singleton pregnancy at full-term gestation;

No absolute indications for cesarean delivery and the ability to undergo natural childbirth;

Availability of complete and traceable clinical records;

Normal communication abilities and clear consciousness.

Exclusion Criteria

Participants were excluded if they met any of the following conditions:

Presence of pregnancy complications such as hypertensive disorders of pregnancy or gestational diabetes;

High-risk pregnancies, including advanced maternal age or multiple pregnancies;

Abnormal pelvic structure or birth canal deformities;

Coagulation disorders or cognitive impairments;

Concurrent cardiac, pulmonary, or other major organ dysfunction.

Interventions

Control Group: Routine Delivery Care

Participants received standard obstetric care per hospital protocol. This included continuous fetal heart rate monitoring and assessment of cervical dilation. Upon reaching active labor (cervix dilated ≥3 cm), participants were transferred to the delivery room. Midwives provided continuous presence and support. Participants were typically guided to adopt supine or semi-recumbent positions as labor progressed and were instructed on breathing and pushing techniques during the second stage. Psychological support included verbal encouragement and physical reassurance (eg, hand-holding, gentle stroking).

Research Group: Combined Intervention (Free Positioning + Mindful Relaxation)

Midwives delivering this intervention had completed a standardized 40-hour training program covering: 1) Theory and evidence for free positioning and mindful relaxation; 2) Practical demonstration and supervised practice of all positions and mindfulness techniques; 3) Communication skills for guiding women; and 4) Documentation requirements. Training was based on WHO recommendations²² and FIGO guidelines.³¹

Free Positioning: During the active phase of labor (cervical dilation ≥3 cm), midwives introduced and demonstrated a variety of labor positions to the participants. Women were encouraged to move freely and select positions based on their comfort and individual preference, with midwives providing support and assistance for any necessary position changes. Commonly adopted positions included: recumbent positions (semi-recumbent, right lateral, and left lateral), standing positions (standing upright beside the bed while holding onto support), sitting positions (seated on the delivery bed or a low stool with hands supporting and body slightly leaning back), squatting positions (feet apart, supported by holding onto a chair or bed edge, often with midwife assistance), and kneeling positions (kneeling on a soft mat with knees apart and leaning forward on a pillow or blanket). There were no fixed time requirements for any specific posture; changes in position occurred as frequently as desired by the woman or in response to discomfort, allowing for a flexible, real-world application of the intervention.

Mindful Relaxation Techniques (MRTs): Upon admission to the delivery room (with cervical dilation ≥3 cm), guided mindful relaxation sessions were initiated and offered continuously throughout labor, particularly during contractions. Each session typically lasted 10–20 minutes and was flexibly adjusted to align with the pattern of uterine contractions and the participant’s level of concentration. While maintaining a self-selected labor position, participants were guided by midwives through a structured mindfulness protocol. This included sensory focus, wherein women were provided with a real object (such as an apple or orange) and instructed to observe its color, shape, and texture, touch its surface, and appreciate its aroma. This was followed by internalization, where they were guided to close their eyes, mentally recall the object’s characteristics, and focus attention while clearing the mind of distractions. A calm ambiance was created using continuous instrumental music played at a moderate volume (40–60 dB). During guided imagery, participants were encouraged to use their imagination to mentally explore the object in greater detail, promoting immersive concentration. In the breath regulation phase, midwives guided a transition from shallow, rapid breathing to deep, steady diaphragmatic breathing, synchronized with silent counting from one to ten and back. Finally, in the reflection stage, participants were instructed to open their eyes, then close them again to recall and verbalize their experience. This protocol, adapted from Mindfulness-Based Childbirth and Parenting (MBCP) principles,³² aimed to alleviate maternal stress, enhance emotional and physical relaxation, and improve women’s coping with labor pain.

Observation Indicators

In this retrospective cohort study, all observation indicators were extracted from standardized medical and nursing records. To reduce bias arising from inconsistent data collection, especially for subjective measures (eg, pain or psychological states), only data recorded by trained staff using standardized tools during the clinical process were included. Records with missing or retrospectively added assessments were excluded to enhance data reliability. The specific indicators evaluated were as follows:

Duration of Labor

Labor duration was segmented into the first, second, and third stages, with total labor time subsequently calculated. These data were obtained from partogram records maintained by midwives in real time during delivery. Comparative analysis was conducted between the intervention and control groups to evaluate differences in labor progression.

Pain Levels

Pain intensity during labor was evaluated using a multidimensional framework based on the Verbal Rating Scale (VRS) recommended by the World Health Organization in 1980. This included three components: (1) the VRS, which classifies pain into four levels—0 (no pain), 1 (mild pain that does not interfere with sleep or daily life), 2 (moderate pain requiring non-narcotic interventions), and 3 (severe pain requiring narcotic analgesia and often accompanied by autonomic symptoms); (2) the Pain Rating Index (PRI), consisting of 15 descriptors, each rated from 0 to 3 (no, mild, moderate, or severe pain), with higher scores indicating greater overall pain perception; and (3) the Visual Analogue Scale (VAS), a 10-cm horizontal ruler labeled from 0 (no pain) to 10 (worst imaginable pain), where participants marked the intensity of their pain. Only assessments recorded by midwives during labor were included in the analysis.

Perineal Tears

The degree of perineal trauma was classified based on clinical records according to standard obstetric grading criteria. These included: intact perineum (no laceration), Grade I (superficial tears of the vaginal or perineal mucosa), Grade II (tears involving the perineal muscle layer and/or posterior vaginal wall), Grade III (tears extending to the external anal sphincter), and Grade IV (full-thickness tears involving the rectal mucosa). Grading was performed by attending midwives or obstetricians immediately postpartum and documented in delivery notes.

Sense of Labor Control

Maternal sense of control during childbirth was measured using the Labor Agentry Scale (LAS), which comprises 29 items rated on a 7-point Likert scale, yielding a total score between 29 and 203. Higher scores represent greater perceived control and agency during labor. In this retrospective analysis, only LAS questionnaires completed within two hours postpartum and documented in full by trained staff were considered valid.

Negative Emotions

Psychological states, specifically anxiety and depression, were assessed using the Self-Rating Anxiety Scale (SAS) and the Self-Rating Depression Scale (SDS), respectively. Each scale includes 20 items rated on a 4-point scale, with a total score of 80. Higher scores indicate more severe emotional distress. In order to ensure consistency, only data collected at standardized time points (within one week before intervention and within 30 minutes postpartum) and documented under supervision were included in the analysis.

Pregnancy Outcomes

Pregnancy outcomes were assessed by recording postpartum hemorrhage volume within two hours of delivery and evaluating neonatal health using the Apgar scoring system. The Apgar score includes five parameters—skin color, heart rate, respiratory effort, muscle tone, and reflex response—each rated from 0 to 2, with a maximum total of 10. Scores were categorized as 10 (optimal condition), 7–9 (mild concerns), or <7 (requires immediate intervention). These scores were extracted from standardized neonatal assessment forms filled by neonatal nurses or pediatricians at 1 and 5 minutes after birth.

Data Analysis

A priori sample size calculation was performed using G*Power 3.1.²⁵ Based on pilot data (unpublished) and previous studies,^6,18 a medium effect size (Cohen’s d = 0.65) for the primary outcome (pain VAS score) was assumed. To achieve 80% power (α=0.05, two-tailed t-test), 60 participants per group were required. This justified the final sample size of n=120 (60 per group).

GraphPad Prism 8 was used for graphical presentation. SPSS 26.0 was used for statistical analysis. Quantitative data were assessed for normality using the Shapiro–Wilk test and visual inspection of Q-Q plots. Normally distributed data are presented as Mean ± Standard Deviation (SD) and compared using Independent Samples t-tests. Non-normally distributed data are presented as Median (Interquartile Range, IQR) and compared using Mann–Whitney U-tests. Qualitative data are presented as Number (Percentage, %) and compared using Chi-square (χ²) or Fisher’s exact test, as appropriate. Effect sizes are reported (Cohen’s d for t-tests, Cramer’s V for χ²). A two-tailed P value < 0.05 was considered statistically significant. No adjustments for multiple comparisons were made for secondary outcomes, consistent with exploratory analysis in this retrospective design; findings should be interpreted accordingly.

Results

Baseline Data

The control group included 60 participants, aged 25–35 years (Mean ± SD: 28.44 ± 2.63 years); gestational age 37–42 weeks (39.02 ± 0.94 weeks); body weight 50–78 kg (63.15 ± 6.22 kg).

The research group included 60 participants, aged 25–35 years (28.96 ± 2.58 years); gestational age 37–42 weeks (39.07 ± 1.02 weeks); body weight 50–78 kg (63.74 ± 6.18 kg).

No significant differences existed in baseline characteristics (P > 0.05, Table 1), confirming comparability.

Table 1 Comparison of Baseline Data Between the Two Groups (Mean ± SD)

Labor Duration

As shown in Figure 1, the research group exhibited significantly shorter labor durations across all three stages compared to the control group. Specifically, the mean duration of the first stage of labor was markedly reduced in the research group (240.69 ± 25.96 minutes) compared to the control group (362.47 ± 31.94 minutes), with a large effect size (Cohen’s d = 4.22, 95% CI: 112.15–131.41, p < 0.001). The second stage of labor was also significantly shorter in the research group (42.32 ± 10.69 minutes) versus the control group (52.14 ± 12.23 minutes), with a moderate to large effect size (Cohen’s d = 0.87, 95% CI: 6.29–13.35, p < 0.001). For the third stage, the research group showed a mean duration of 5.11 ± 2.56 minutes, significantly less than the control group’s 8.74 ± 2.85 minutes (Cohen’s d = 1.35, 95% CI: 2.78–4.48, p < 0.001). Overall, the total labor duration was significantly reduced by approximately 135 minutes in the research group (291.23 ± 28.65 minutes) compared to the control group (426.56 ± 40.69 minutes), with a large effect size (Cohen’s d = 3.86, 95% CI: 121.30–149.36, p < 0.001).

Figure 1 Comparison of Labor Duration Between the Two Groups. Note: *Indicates P < 0.05 compared to the control group.

Pain Levels

As shown in Figure 2, pain levels following the intervention were significantly lower in the research group across all assessment dimensions. On the Visual Analog Scale (VAS), the research group reported a mean score of 4.32 ± 1.03, significantly lower than the control group’s 5.23 ± 1.24 (Cohen’s d = 0.80, 95% CI: 0.65–1.17, p < 0.001), indicating a moderate to large effect size. Similarly, the Pain Rating Index (PRI) scores were reduced in the research group (2.49 ± 0.45) compared to the control group (2.94 ± 0.78), with a moderate effect size (Cohen’s d = 0.71, 95% CI: 0.28–0.62, p < 0.001). In terms of Present Pain Intensity (PPI), the research group scored 25.45 ± 2.14, significantly lower than the control group’s 28.77 ± 2.56 (Cohen’s d = 1.42, 95% CI: 2.67–3.97, p < 0.001), reflecting a large effect size. These findings indicate that the combined intervention of free positioning and mindful relaxation techniques was effective in significantly alleviating both the sensory and cognitive-affective components of labor pain.

Figure 2 Comparison of VRS Scores Between the Two Groups. Note: *Indicates a significant difference between the two groups, P<0.05.

Perineal Laceration

As illustrated in Figure 3, the distribution of perineal outcomes differed significantly between the two groups (P < 0.05). In the research group, 35.00% (21/60) of participants had an intact perineum, 41.67% (25/60) experienced Grade I lacerations, 21.67% (13/60) had Grade II lacerations, and 1.67% (1/60) sustained Grade III lacerations. In comparison, the control group showed 23.33% (14/60) with an intact perineum, 30.00% (18/60) with Grade I lacerations, 35.00% (21/60) with Grade II lacerations, and 11.67% (7/60) with Grade III lacerations. These findings indicate a higher proportion of intact perineum and first-degree lacerations but a lower incidence of more severe (Grade II and III) tears in the research group, suggesting a protective effect of the intervention on perineal outcomes.

Figure 3 Comparison of Perineal Laceration Degrees Between the Two Groups. Note: *Indicates a significant difference between the two groups, P<0.05.

Labor Control

The analysis of Labor Agentry Scale (LAS) scores revealed a statistically significant difference between the two groups. Participants in the research group reported a higher sense of control during labor, with a mean LAS score of 152.41 ± 8.11, compared to 144.22 ± 9.11 in the control group (d = 0.95; 95% CI: 5.42–10.96; P < 0.001). This suggests that the combined intervention notably enhanced participants’ perceived autonomy and empowerment throughout the birthing process. See Table 2.

Table 2 Comparison of LAs Scores Between the Two Groups (Mean ± SD)

Negative Emotions

The analysis of post-intervention psychological outcomes indicated that participants in the research group experienced significantly lower levels of anxiety and depression compared to those in the control group. Specifically, the Self-Rating Anxiety Scale (SAS) scores were 46.23 ± 2.35 in the research group versus 55.98 ± 2.47 in the control group (t = 22.152, P < 0.001; d = 4.10; 95% CI: 8.99–10.23). Similarly, Self-Rating Depression Scale (SDS) scores were 45.22 ± 1.73 in the research group and 54.56 ± 2.14 in the control group (t = 26.291, P < 0.001; d = 4.71; 95% CI: 8.63–10.06). These findings suggest that the combined intervention was highly effective in reducing negative emotional responses during labor. See Table 3.

Table 3 Comparison of Anxiety and Depression Scores Between the Two Groups ()

Pregnancy Outcomes

Postpartum outcomes revealed significant differences between the two groups. The mean volume of bleeding within 2 hours postpartum was markedly lower in the research group (155.89 ± 22.21 mL) compared to the control group (204.58 ± 30.88 mL), indicating improved hemostatic outcomes (d = 1.79; 95% CI: 40.65–57.59; P < 0.001). Apgar scores were slightly higher in the research group (8.44 ± 1.56) compared to the control group (8.05 ± 1.11); however, the difference was not statistically significant (d = 0.28; 95% CI: 0.13–0.73; P = 0.145), indicating comparable neonatal conditions between groups. See Figure 4.

Figure 4 Comparison of Postpartum 2-Hour Blood Loss and Neonatal Apgar Scores Between the Two Groups. Note: *Indicates a significant difference between the two groups, P<0.05.

Discussion

This study aimed to evaluate the effects of free positioning combined with mindfulness relaxation techniques on labor pain relief and labor duration reduction. The results showed that this combined intervention significantly shortened the duration of each stage of labor, alleviated labor pain, improved maternal sense of control and emotional status during labor, and reduced postpartum blood loss, demonstrating favorable clinical outcomes. These findings are consistent with multiple previous studies, further validating the value of this integrated intervention model in promoting natural childbirth.

Firstly, the significant shortening of labor duration is one of the core findings of this study. The intervention group’s average duration of the first stage of labor was markedly shorter than that of the control group (240.69 minutes vs 362.47 minutes), with an overall labor time reduction of approximately 135 minutes and a very large effect size (Cohen’s d = 3.86). This result aligns with the conclusions of Mansfield et al’s systematic review on free positioning facilitating labor progress, which indicated that freedom of movement and position changes could reduce the risk of prolonged cervical dilation and extended second stage of labor.³³ The mechanism may be related to multiple factors: free positioning allows the mother to utilize gravity to assist fetal descent, relieve pressure on the birth canal during uterine contractions, facilitate better alignment of the fetal head with the birth canal curve, and reduce birth canal resistance.³⁴ Moreover, alternating between different positions can improve pelvic morphology and blood circulation, helping relax the pelvic floor muscles and thus accelerating labor.³⁵

In addition, the effect of mindfulness relaxation in alleviating labor pain and improving emotional state may also partly be attributed to the potential regulation of the neuroendocrine system. Although this study did not directly measure neuroendocrine-related indicators, existing literature shows that mindfulness interventions can reduce sympathetic nervous system activity, enhance parasympathetic tone, and regulate the hypothalamic-pituitary-adrenal (HPA) axis reactivity, thereby decreasing the secretion of stress hormones such as cortisol and norepinephrine.^36–38 This neuroendocrine balance adjustment helps lower pain sensitivity, relieve anxiety and tension, increase pain threshold, and enhance maternal sense of control and adaptability during labor. In this study, women in the intervention group performed better in subjective pain scores (VAS, PPI, etc)., anxiety and depression scales (SAS/SDS), and labor control scores (LAS), indirectly supporting the plausibility of this mechanism. This dual physiological–psychological pathway suggests that the combined intervention of free positioning and mindfulness relaxation not only improves clinical outcomes but may also have favorable neuroregulatory and mind-body synergistic effects, warranting further exploration at the physiological mechanism level.

Simultaneously, the intervention group showed a significantly enhanced sense of labor control (LAS scores significantly higher than control), indicating that this intervention model improved maternal autonomy and self-efficacy. A high sense of control during labor is closely related to reduced labor anxiety, decreased frequency of obstetric interventions, and promotion of vaginal delivery.³⁹ This is because free positioning and mindfulness relaxation allow mothers to actively choose comfortable postures and psychological adjustment methods, increasing their mastery over the delivery process and reducing fear and helplessness.⁴⁰ This result is also supported by studies by Li and Guo, who reported that psychological support and self-regulation strategies during labor significantly improve maternal delivery satisfaction and psychological health.^41,42

This study also observed a significantly lower incidence of severe perineal lacerations (grade II and above) and a notable reduction in postpartum blood loss in the intervention group. Free positioning (eg, semi-sitting, lateral, squatting) can reduce perineal tension, promote natural soft tissue expansion, and decrease the risk of mechanical injury.⁴³ Mindfulness relaxation may contribute by lowering stress responses, improving vascular tone and tissue perfusion, thereby facilitating local repair and hemostasis.⁴⁴ These findings are consistent with Hughes’ review on perineal protection strategies, which emphasizes the importance of posture adjustment and emotional interventions in reducing perineal trauma and postpartum hemorrhage.⁴⁵

In summary, this study confirms that free positioning combined with mindfulness relaxation techniques significantly promotes labor pain relief, shortens labor duration, reduces perineal trauma, and improves maternal psychological state. The mechanisms involve physiological and mechanical optimization (such as fetal descent and pelvic morphology changes), neuroendocrine regulation (reduced sympathetic excitation and enhanced analgesia), and psychological-behavioral enhancement of labor control. The synergy of these mechanisms improves the overall childbirth experience and facilitates smooth natural delivery.

Limitations

Although the results show that free positioning combined with mindfulness relaxation techniques have positive effects on labor pain relief, labor duration reduction, emotional improvement, and childbirth experience enhancement, several limitations should be fully considered when interpreting the findings. First, this study is a retrospective cohort design and is limited by the completeness and accuracy of existing medical records, which may introduce information and recall bias. Since randomization and blinding were not performed, there may be uncontrolled baseline differences and selection bias between the intervention and control groups, affecting the rigor of causal inference. Moreover, potential confounders such as maternal social support, fear of childbirth, experience level of birth attendants, and fetal position were not fully controlled, which could partially interfere with the assessment of intervention effects.

Second, the sample size is relatively small and drawn from a single center, which may affect the representativeness and generalizability of the results. Future studies should validate these findings through multicenter, large-sample, prospective randomized controlled trials to strengthen external validity and causal inference. Additionally, as this study did not include single free positioning or single mindfulness intervention groups, it cannot clearly evaluate the independent contribution of each component nor conclude whether true synergistic effects exist. Therefore, the term “combined intervention effect” should be used cautiously to indicate superior effects compared with routine care but not to prove interaction between interventions.

Finally, although literature suggests that mindfulness interventions may exert effects via neuroendocrine regulation—such as reducing sympathetic activity, modulating the HPA axis, and decreasing stress hormone secretion^36–38—this study did not directly measure neuroendocrine markers, so these remain hypothetical explanations that need further mechanistic research to validate their biological basis.

Conclusion

The results of this study preliminarily suggest that free positioning combined with mindfulness relaxation interventions may help shorten labor duration, relieve labor pain, improve emotional state, and enhance maternal sense of control during childbirth, thereby promoting smooth natural delivery. This non-pharmacological, low-cost intervention model has certain potential for clinical promotion, especially in resource-limited or humanized childbirth-focused settings.

However, given the retrospective design, lack of randomization, blinding, and long-term follow-up, causal interpretations should be cautious. Additionally, the synergistic effects of the combined intervention cannot be separated to clarify individual components’ independent effects. Future research should employ more rigorous prospective randomized controlled trials or factorial design studies to further elucidate intervention mechanisms and explore applicability and sustainability across different populations and labor stages.

In summary, the current findings provide valuable preliminary evidence supporting non-pharmacological interventions to promote natural childbirth, warranting further exploration and validation in higher-quality studies to assess feasibility and effectiveness for broader application.

Disclosure

The authors report no conflicts of interest in this work.

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Introduction

Type 2 diabetes mellitus (T2DM) is a chronic metabolic disorder characterized by insulin resistance, hyperglycaemia, and various metabolic abnormalities.¹ Over the past few decades, the global prevalence of T2DM has continuously increased at an alarming rate, with estimates suggesting that more than 463 million people worldwide are currently living with diabetes, the vast majority of which are T2DM cases.² This surge is largely driven by rising obesity rates, unhealthy lifestyles, and population aging.³ T2DM is not only a major cause of morbidity and mortality but also places a tremendous economic burden on healthcare systems due to the frequent development of complications, including cardiovascular disease, nephropathy, and neuropathy.⁴

Among the numerous complications associated with T2DM, abnormal fat distribution plays a pivotal role in the progression of the disease and the development of insulin resistance.⁵ Visceral fat is known to contribute significantly to conditions related to metabolic dysfunction, such as dyslipidaemia, hypertension, and inflammation. Subcutaneous fat, though less harmful than visceral fat, also can contribute to metabolic derangements when present in excess.⁶ Given the importance of fat distribution in the pathophysiology of T2DM, understanding the factors that influence fat storage and distribution is critical for the development of effective therapeutic interventions.⁷

Thyroid hormones are well-established regulators of metabolism and energy expenditure.⁸ These hormones, including free triiodothyronine (FT3) and free thyroxine (FT4), play key roles in lipid metabolism, thermogenesis, and glucose homeostasis. Thyroid-stimulating hormone (TSH), which is produced by the pituitary gland, regulates the synthesis and secretion of both FT3 and FT4.^9,10 In clinical practice, thyroid function is typically evaluated by measuring thyroid hormone levels, with deviations from normal levels indicating either hypo- or hyperthyroidism.^11,12 Interestingly, research has demonstrated that even in euthyroid individuals (those with normal thyroid function), variations in thyroid hormone levels may have significant metabolic consequences.^13,14

Several studies^15–17 have explored the interplay between thyroid hormones and fat distribution, particularly in relation to obesity and metabolic syndrome. One study¹⁸ found that individuals with elevated FT3 levels tend to have higher body fat percentages, particularly involving visceral fat, which is associated with greater risks of insulin resistance and cardiovascular diseases. Conversely, higher FT4 levels are linked to lower body fat and improved metabolic profiles, suggesting a protective role of FT4 in fat metabolism. These findings are consistent with the known metabolic effects of thyroid hormones, with FT3 being the more metabolically active hormone that increases the basal metabolic rate and promotes lipid oxidation.¹⁹

However, the relationship between thyroid hormone levels and fat distribution in T2DM patients remains poorly understood. Most studies of this relationship have focused on general populations or individuals with obesity, without specifically examining T2DM patients. Given the unique metabolic characteristics of T2DM patients, including insulin resistance and altered glucose metabolism, it is important to investigate how thyroid hormone levels influence fat distribution in this population.

The present study aimed to elucidate the relationship between thyroid hormones (FT3, FT4, and TSH) and fat distribution, specifically in terms of visceral fat area (VFA) and subcutaneous fat area (SFA), in T2DM patients with normal thyroid function. By characterizing these relationships, a goal of this study was to provide insight into the potential roles of thyroid hormones in the pathophysiology of T2DM and its complications. This information, in turn, can support the development of targeted treatments for metabolic management in T2DM patients.

Materials and Methods

Study Design and Participants

This cross-sectional study included 2,956 T2DM patients recruited from a tertiary hospital between 2021 and 2023. The initial dataset contained 10,416 entries. The inclusion criteria were: (1) age ≥18 years, (2) confirmed diagnosis of T2DM according to the World Health Organization (WHO) criteria, and (3) availability of complete data for VFA, SFA, and thyroid hormone levels (FT3, FT4, and TSH). The exclusion criteria were applied as follows: duplicate entries (6,237 cases), missing age or age <18 years (7 cases), incomplete VFA or SFA data (875 cases), unconfirmed T2DM diagnosis (31 cases), presence of thyroid disease (122 cases), and missing FT3/FT4/TSH data (188 cases). After these exclusions, 2,956 patients with complete data were included in the final analysis.

The study was approved by the Institutional Review Board of the hospital, and written informed consent was obtained from all participants prior to enrolment.

Data Collection

Demographic and Clinical Characteristics

Baseline demographic and clinical data were collected from medical records and included: age, gender, body mass index (BMI), and waist-to-hip ratio (WHR); blood pressure (systolic and diastolic); and lifestyle factors such as smoking status (never, quit, occasionally, or daily) and alcohol consumption (never, quit, occasionally, or daily).

Thyroid Hormone Measurements

Fasting blood samples were obtained in the morning from all participants for the measurement of thyroid hormone levels.²⁰ Serum FT3, FT4, and TSH levels were measured using enzyme-linked immunosorbent assays (ELISAs). To explore differences in fat distribution across varying levels of thyroid hormones, we stratified participants into three groups (low, normal, and high), based on serum FT3, FT4, and TSH levels. The cutoffs for these categories were defined according to standard clinical reference ranges used in routine laboratory practice and prior studies on thyroid function in euthyroid individuals: FT3 (low <1.8, normal 1.8–3.8, high >3.8 pg/mL), FT4 (low <0.78, normal 0.78–1.86, high >1.86 ng/dL), and TSH (low <0.38, normal 0.38–5.57, high >5.57 mU/L). These ranges were chosen to ensure consistency with clinical definitions and to assess potential trends across the spectrum of thyroid hormone concentrations within the euthyroid range. Quality control procedures were applied to ensure measurement accuracy, and extreme values were addressed based on statistical feedback. Specifically, values for creatinine (Cr), FT4, and TSH were adjusted as follows: Cr (151.72 μmol/L and 103.9 μmol/L), FT4 (7.71 ng/dL), and TSH (97.743 mU/L). These adjustments corrected data entry inconsistencies or biologically implausible values, improving data integrity and minimizing potential bias. Sensitivity analyses indicated these corrections did not materially alter the study’s main findings.

Fat Distribution Assessment

Fat distribution was assessed by measuring VFA and SFA via bioelectrical impedance analysis (BIA)²¹ using the DUALSCAN HDS-2000 instrument (Omron Healthcare, Kyoto, Japan). Measurements were taken after an overnight fast and voiding of the bladder. The device calculates body impedance through weak electrical currents passing through the body, and participant data (hospital number, height, weight, age, gender) were entered for precise calculations. The abdominal measurement unit on the device measured abdominal shape, and impedance measurements allowed for calculation of VFA and SFA according to the manufacturer’s protocols.

Statistical Analysis

Descriptive Statistics

The baseline characteristics of the study population are presented as means ± standard deviations for normally distributed continuous variables, medians (interquartile ranges) for skewed variables, and as frequencies and percentages for categorical variables. Differences in baseline characteristics were assessed using the t-test for normally distributed continuous variables, the Mann–Whitney U-test for skewed variables, and the Chi-square test for categorical variables. Skewed variables (eg, triglycerides [TG], alanine transaminase [ALT]) were analyzed without log transformation. The level of statistical significance was set at P<0.05.

Correlation Analysis

Correlations between levels of thyroid hormones (FT3, FT4, TSH) and fat distribution measures (VFA, SFA) were analyzed via Pearson or Spearman correlation analysis based on the distribution of the data. Correlation results were evaluated at a significant level of P<0.05.

Multivariate Regression Analysis

Multiple linear regression models were employed to evaluate the independent effects of FT3, FT4, and TSH on VFA and SFA after adjusting for potential confounding variables, including age, gender, and BMI. Based on multicollinearity analyses, BMI and WHR were excluded from final models involving FT4 to avoid obscuring its significance in relation to fat distribution. Regression coefficients, confidence intervals, and P-values were reported for all predictors. All analyses were conducted using a statistical software package with significance set at P<0.05.

Handling of Outliers

Extreme values identified for Cr, FT4, and TSH measurements were corrected based on statistical review and clinical evaluation to enhance the robustness of the findings. A total of five values were adjusted: two for Cr (151.72 and 103.9 μmol/L), one for FT4 (7.71 ng/dL), and two for TSH (97.743 mU/L and one additional unreported outlier). These corrections addressed data entry inconsistencies or biologically implausible values, thus improving data quality and minimizing potential bias. Sensitivity analyses performed to assess the impact of these corrections showed no material changes in the direction, magnitude, or statistical significance of the associations between thyroid hormone levels and fat distribution. All statistical analyses in this study were performed using SPSS version 28.0 (IBM Corp., Armonk, NY, USA) and R software (version 4.2.2, R Foundation for Statistical Computing, Vienna, Austria), with results considered statistically significant at P<0.05.

Results

Baseline Characteristics of the Study Population

The baseline characteristics of the study participants (n=2,956) are summarized in Table 1, with stratification by gender. The mean age of the participants was 56.2 years, and the study population included a higher proportion of males (58.6%) than females (41.4%). Males had a significantly higher WHR and systolic blood pressure than females (both P<0.001). Lifestyle factors also showed gender-specific differences, with males reporting higher smoking and alcohol consumption rates than females. BMI did not differ significantly between the male and female groups (P=0.077).

Table 1 The Basic Characteristics Stratified by Gender

Thyroid Hormone Levels and Fat Distribution in T2DM Patients

Table 2 presents the distribution of VFA and SFA across groups of patients with different categories of thyroid hormone levels (decreased, normal, and increased) for FT3, FT4, and TSH. Notably, patients with elevated FT3 levels (>3.8 pg/mL) show higher mean values for VFA (79.75 ± 40.12 cm²) and SFA (148.96 ± 57.06 cm²) compared to those with normal (1.8–3.8 pg/mL) or decreased (<1.8 pg/mL) FT3 levels (all P<0.001). Conversely, no significant variation in VFA and SFA values was observed for patients in different FT4 categories (decreased, normal, increased), suggesting a lesser impact of FT4 alone on fat distribution (P>0.05). Upon analysis according to the TSH categories, slightly higher values of VFA (82.39 ± 49.75 cm²) and SFA (162.44 ± 61.38 cm²) were observed in the elevated TSH group (>5.57 mU/L) compared with the decreased and normal TSH groups (all P<0.05 for both VFA and SFA).

Table 2 The Basic Characteristics Stratified by Age

Correlation Between Thyroid Hormone Levels and Fat Distribution in T2DM Patients

Correlation analyses revealed significant relationships between thyroid hormone levels and fat distribution parameters (Table 3). FT3 was positively correlated with both VFA (r=0.248, P<0.001) and SFA (r=0.190, P<0.001), indicating that a higher FT3 level is associated with greater fat accumulation. FT4, on the other hand, tended to show a weak inverse correlation with both VFA (r=–0.018, P=0.321) and SFA (r=–0.019, P=0.283), although these relationships were not statistically significant. TSH showed a weak but significant positive correlation with both VFA (r=0.064, P=0.001) and SFA (r=0.072, P<0.001), indicating an association with fat distribution but a weaker association than that observed between FT3 and fat distribution.

Table 3 The Distribution of VFA and SFA According to Thyroid Hormones

Correlation Between Thyroid Hormone Levels and Fat Distribution

Correlation analyses revealed significant associations between thyroid hormone levels and fat distribution parameters (Table 4). FT3 was positively correlated with both VFA (r = 0.248, P < 0.001) and SFA (r = 0.190, P < 0.001), indicating that higher FT3 levels were associated with greater visceral and subcutaneous fat accumulation. FT4 showed weak negative correlations with VFA (r = –0.018, P = 0.321) and SFA (r = –0.019, P = 0.283), but these associations were not statistically significant. TSH demonstrated weak yet significant positive correlations with both VFA (r = 0.064, P = 0.001) and SFA (r = 0.072, P < 0.001), although the strength of these relationships was less pronounced compared with FT3.

Table 4 The Correlation Between Thyroid Hormones and VFA and SFA

Predictive Values of Thyroid Hormones for Abnormal Fat Distribution

To further evaluate the independent effects of thyroid hormones on fat distribution, multivariate linear regression models were constructed after adjusting for potential confounding factors, including age, gender, and BMI (Table 5). FT3 remained independently and positively associated with both VFA (Coef = 8.06, 95% CI: 5.87–10.24, P < 0.001) and SFA (Coef = 9.71, 95% CI: 6.62–12.79, P < 0.001). In contrast, FT4 was inversely associated with VFA (Coef = –12.20, 95% CI: –17.36 to –7.03, P < 0.001) and SFA (Coef = –16.68, 95% CI: –23.98 to –9.38, P < 0.001), suggesting a potential protective role of FT4 against abnormal fat accumulation. TSH did not show significant associations with either VFA or SFA (all P > 0.05), indicating a relatively minor impact compared with FT3 and FT4.

Table 5 The Multivariate Linear Regression Between Thyroid Hormones and VFA and SFA

Gender and Age-Specific Variations in Fat Distribution Among T2DM Patients

Additional analyses with patient stratification by age and gender were conducted to further elucidate the relationships between thyroid hormone levels and fat distribution in T2DM patients. As shown in Table S1, the associations between FT3 and fat distribution parameters were consistent across age groups, with younger and middle-aged adults showing similar patterns of correlation for FT3 with VFA and SFA. Among women, FT4 exhibited a more pronounced inverse relationship with VFA, and this effect was not observed in men. Gender differences were also evident in the correlation of TSH and fat distribution, with men showing a stronger association of TSH with VFA and SFA compared with women (P<0.05 for interaction).

Discussion

The present investigation of the associations between thyroid hormone levels (FT3, FT4, and TSH) and fat distribution, specifically VFA and SFA, in T2DM patients revealed the following significant associations: FT3 was positively correlated with both VFA and SFA, while FT4 was inversely associated with these fat distribution measures. TSH displayed a weak positive association that did not persist after adjustment for confounding variables. These results suggest a nuanced role for thyroid hormones in fat metabolism and distribution in T2DM patients with normal thyroid function, supporting a potential role for FT3 and FT4 as biomarkers for evaluating metabolic risk in this population.

The strong positive associations between FT3 and both VFA and SFA in our cohort align with FT3’s known role as an active thyroid hormone involved in regulating metabolic rate and energy expenditure.²² FT3’s influence on lipolysis and fat accumulation may explain the observed associations, as higher FT3 levels likely stimulate greater metabolic turnover, promoting fat mobilization and deposition, particularly in visceral regions.²³ The accumulation of visceral fat is closely linked to insulin resistance, systemic inflammation, and cardiovascular complications, all of which are prevalent in T2DM patients.²⁴ Our findings are consistent with those of prior studies^25,26 indicating that elevated FT3 levels are associated with higher body fat percentages and greater metabolic risks, especially in populations predisposed to obesity and diabetes.

The relationship between FT3 and fat distribution also could be influenced by the unique metabolic environment of T2DM.²⁷ Insulin resistance, a hallmark of T2DM, is associated with altered lipid metabolism and may exacerbate FT3’s effects on fat accumulation.²⁸ While FT3 promotes lipid oxidation and energy consumption, its effects in the context of T2DM may be compounded by impaired glucose and lipid regulation, resulting in disproportionate fat deposition, particularly in visceral areas.²⁹ Thus, T2DM patients with elevated FT3 levels may be at increased risk of accumulating metabolically active visceral fat, predisposing them to worsened metabolic control and cardiovascular risk. This highlights the potential utility of FT3 as a biomarker for assessing fat-related metabolic risks in T2DM.³⁰

The observed positive association between FT3 levels and fat accumulation may appear paradoxical considering the known lipolytic effects of FT3. However, previous research has suggested several mechanisms underlying this relationship in insulin-resistant states. Elevated FT3 levels in T2DM patients could reflect compensatory hypersecretion intended to overcome reduced thyroid hormone sensitivity at peripheral tissues,³⁰ potentially due to alterations in thyroid hormone receptor expression or signaling pathways. Additionally, impaired peripheral conversion of T4 to active T3 caused by chronic inflammation or metabolic dysfunction may lead to higher FT3 secretion from the thyroid gland to maintain metabolic homeostasis. These compensatory adjustments may paradoxically leads to the association of elevated circulating FT3 levels with greater fat accumulation, especially visceral fat, in individuals with insulin resistance and metabolic disturbances.³¹

Unlike FT3, FT4 displayed an inverse relationship with VFA and SFA, suggesting a potential protective role of FT4 in fat metabolism among T2DM patients.³² FT4, often considered less metabolically active than FT3, appears to exert a regulatory influence on fat storage, potentially attenuating fat accumulation in both visceral and subcutaneous regions.³³ This finding aligns with the hypothesis that FT4 supports metabolic homeostasis and thereby contributes to favorable fat distribution patterns in T2DM patients. Previous studies^14,34 have shown that lower FT4 levels are linked to increased fat mass and metabolic risk, further corroborating our finding that higher FT4 levels might protect against excessive fat accumulation.

Our gender-stratified analysis suggested that the protective effect of FT4 may be more pronounced in females than in males. A potential mechanism may be related to estrogen. Estrogen has been shown to influence fat distribution by favoring subcutaneous over visceral fat storage, and this effect may interact with the influence of FT4 on metabolism.³⁵ In postmenopausal women, who experience shifts in both thyroid hormone levels and fat distribution, maintaining adequate FT4 levels might help mitigate visceral fat accumulation.³⁶ This interplay warrants further investigation to explore whether FT4 could be targeted in gender-specific interventions aimed at improving fat distribution and metabolic outcomes in T2DM patients.

TSH demonstrated a weak positive correlation with VFA and SFA, which did not remain significant after adjustment for age, gender, and BMI.³⁷ As a regulatory hormone, TSH primarily influences thyroid hormone synthesis and secretion rather than directly impacting metabolism or fat storage. This may explain its limited association with fat distribution in our cohort. Although previous research³⁸ suggested a link between higher TSH levels and obesity, our results indicate that TSH may have minimal impact on fat distribution in euthyroid individuals with normal FT3 and FT4 levels. The lack of a significant association between TSH and fat accumulation after adjustment highlights the importance of considering FT3 and FT4 independently when assessing thyroid hormone-related metabolic risks in T2DM patients.

The relatively weak and statistically nonsignificant adjusted associations observed between TSH and fat distribution parameters may be explained by the role of TSH primarily as a centrally controlled regulator of thyroid function, rather than a direct peripheral mediator of metabolic processes. TSH exerts indirect metabolic effects by influencing thyroid hormone synthesis and secretion, whereas peripheral tissues primarily respond to circulating FT3 and FT4 levels. Furthermore, existing research supports the notion that peripheral metabolic activities and fat metabolism are predominantly regulated by thyroid hormones at the tissue level, with TSH having limited direct effects outside the central axis.³⁹ These findings align with our observation that FT3 and FT4 showed more robust associations with fat distribution compared with TSH.

Overall, our results are consistent with previous studies^40,41 that described a positive association of FT3 with body fat and an inverse relationship of FT4 with fat accumulation. Similar findings in general populations suggest that these thyroid hormone relationships extend to T2DM patients, who exhibit distinct metabolic profiles due to insulin resistance and dyslipidemia. Studies in non-diabetic populations have linked higher FT3 levels with increased visceral and subcutaneous fat, reinforcing our observations that FT3 may predispose T2DM patients to adverse fat accumulation patterns.⁴² Moreover, a study by Mele et al³⁶ demonstrated that FT4 levels are inversely correlated with adiposity, suggesting that FT4 might contribute to a healthier fat distribution pattern. However, our study’s focus on euthyroid T2DM patients provides novel insights and fills a gap in the literature, as few studies have exclusively examined this population.

As noted above, the significant associations between FT3 and measures of fat distribution suggest that FT3 could serve as a useful biomarker for identifying T2DM patients at risk for excessive visceral fat accumulation. Accordingly, monitoring of FT3 levels in T2DM patients may help clinicians identify individuals with heightened metabolic and cardiovascular risks linked to visceral adiposity. Moreover, our finding regarding the protective role of FT4 against abnormal fat distribution highlight the potential benefits of preserving or optimizing FT4 levels to promote a favorable fat distribution in T2DM patients. Personalized treatment approaches that consider individual thyroid hormone profiles could enhance metabolic management, potentially facilitating measures to reduce fat accumulation and improve metabolic outcomes in T2DM patients. Interventions focusing on lifestyle modification or pharmacotherapy tailored to regulate patients’ FT3 and FT4 levels could provide targeted benefits.

The observed gender-specific differences in the effect of FT4 on fat distribution underscore the importance of considering gender in metabolic research. Among the women in our study, we observed a more pronounced inverse relationship between FT4 and VFA, suggesting that FT4 may offer stronger protective effects in women. Estrogen likely interacts with FT4, influencing fat distribution patterns that favour subcutaneous over visceral storage. This interaction is particularly relevant for postmenopausal women, who experience hormonal shifts that might exacerbate visceral fat accumulation. Thus, strategies to maintain adequate FT4 levels could mitigate these effects, supporting metabolic health in postmenopausal T2DM patients. Future studies should explore the existence and effects of interactions between estrogen and thyroid hormones to better understand their combined effects on fat distribution in T2DM patients.

The present study also has several limitations that should be considered. The cross-sectional design prevents us from establishing causality, leaving it unclear whether thyroid hormone changes precede or result from altered fat distribution. A longitudinal study design is required to clarify causal pathways. Additionally, the exclusion of T2DM patients with thyroid dysfunction restricts the generalizability of our findings, as the relationship between thyroid hormones and fat distribution may differ in patients with hypo- or hyperthyroidism. The used of BIA for measurement of VFA and SFA may also limit the precision of the data, compared with that produced by imaging modalities such as MRI or CT, but BIA offers the advantage of being a practical, non-invasive method for large-scale studies. Residual confounding is another limitation. Although we controlled age, gender, BMI, education, blood pressure, and lipid profiles, other clinically relevant factors were not available in our dataset. Examples include the duration of diabetes, glycemic control (HbA1c), the use of specific antidiabetic medications, smoking status, and physical activity. These factors may influence both thyroid hormone metabolism and fat distribution, and their absence from our analysis may introduce bias. Therefore, residual confounding cannot be excluded and should be considered when interpreting our findings. Future studies should aim to account for these variables to provide a more comprehensive understanding of the impacts of different thyroid hormones on fat distribution.

Finally, this study provides insight for the directions of future research. Longitudinal investigations tracking thyroid hormone levels and fat distribution over time are needed to clarify potential causal relationships in T2DM populations. Complementary mechanistic studies, including observational analyses and experimental models, may help determine whether variations in FT3 and FT4 drive fat accumulation or represent compensatory responses. Elucidating the molecular pathways linking thyroid hormones with lipid metabolism will be particularly important. In addition, examination of other thyroid hormone metabolites, such as T2 and reverse triiodothyronine (rT3), may broaden our understanding of thyroid hormone regulation of fat distribution and metabolic health.

Conclusion

In conclusion, this study highlights significant associations between thyroid hormones and fat distribution in euthyroid T2DM patients. Elevated FT3 levels were linked to increased visceral and subcutaneous fat, whereas higher FT4 levels were associated with more favourable fat distribution. These findings provide new insights into the metabolic roles of thyroid hormones and suggest that they may serve as useful indicators for identifying patients at higher metabolic risk. Future longitudinal and mechanistic studies are warranted to validate these associations and to explore their potential relevance for personalized metabolic management in T2DM.

Data Sharing Statement

The datasets generated and analyzed during the present study are available from the corresponding author on reasonable request.

Ethics Approval and Informed Consent

The study was approved by the Institutional Review Board of the Affiliated Hospital of Southwest Medical University. All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards. Written informed consent was obtained from all participants prior to enrolment.

Acknowledgments

We thank Medjaden, Inc. for scientific editing of this paper.

Funding

The study was funded by the Youth Fund of Medical Association (No. 16213).

Disclosure

The authors report no conflicts of interest in this work.

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19. Hatziagelaki E, Paschou SA, Schön M, Psaltopoulou T, Roden M. NAFLD and thyroid function: pathophysiological and therapeutic considerations. Trends Endocrinol Metab. 2022;33(11):755–768. doi:10.1016/j.tem.2022.08.001

20. Ward CR. Chapter 69 – Thyroid Storm. In: Silverstein DC, Hopper K, editors. Small Animal Critical Care Medicine. 2nd ed. St. Louis: W.B. Saunders; 2015:364–367.

21. Lai C-L, Lu H-K, Huang A-C, Chu L-P, Chuang H-Y, Hsieh K-C. Bioimpedance analysis combined with sagittal abdominal diameter for abdominal subcutaneous fat measurement. Front Nutr. 2022;9.

22. Hoermann R, Pekker MJ, Midgley JEM, Dietrich JW. The role of supporting and disruptive mechanisms of FT3 homeostasis in regulating the hypothalamic–pituitary–thyroid axis. Therapeu Adv Endocrinol Metabo. 2023;14:20420188231158163. doi:10.1177/20420188231158163

23. Hu Y, Zhou F, Lei F, et al. The nonlinear relationship between thyroid function parameters and metabolic dysfunction-associated fatty liver disease. Front Endocrinol. 2023;14.

24. Rohm TV, Meier DT, Olefsky JM, Donath MY. Inflammation in obesity, diabetes, and related disorders. Immunity. 2022;55(1):31–55. doi:10.1016/j.immuni.2021.12.013

25. Sun X, Chen L, Wu R, Zhang D, He Y. Association of thyroid hormone with body fat content and lipid metabolism in euthyroid male patients with type 2 diabetes mellitus: a cross-sectional study. BMC Endocr Disord. 2021;21(1):241. doi:10.1186/s12902-021-00903-6

26. Yu L, Liu Y, Wang Y, et al. Increased thyroid hormone sensitivity is correlated with visceral obesity in patients with type 2 diabetes. Lipids health Dis. 2024;23(1):337. doi:10.1186/s12944-024-02320-9

27. Bouazza A, Favier R, Fontaine E, Leverve X, Koceir E-A. Potential applications of thyroid hormone derivatives in obesity and type 2 diabetes: focus on 3,5-diiodothyronine (3,5-T2) in psammomys obesus (fat sand rat) model. Nutrients. 2022;14(15):3044. doi:10.3390/nu14153044

28. DeFronzo RA. Insulin resistance, lipotoxicity, type 2 diabetes and atherosclerosis: the missing links. The Claude Bernard Lecture 2009. Diabetologia. 2010;53(7):1270–1287. doi:10.1007/s00125-010-1684-1

29. Emiroğlu C, Özdemir Ç, Görpelioğlu S, Aypak C. The relationship between thyroid hormones, metabolic syndrome and HOMA-IR in people with obesity or overweight. Clin Diabetol. 2022;11(5):333–339. doi:10.5603/DK.a2022.0043

30. Biondi B, Kahaly GJ, Robertson RP. Thyroid dysfunction and diabetes mellitus: two closely associated disorders. Endocrin Rev. 2019;40(3):789–824. doi:10.1210/er.2018-00163

31. Holtorf K. Peripheral thyroid hormone conversion and its impact on TSH and metabolic activity. J Restorat Med. 2014;3(1):30–52. doi:10.14200/jrm.2014.3.0103

32. Cao B, Li K, Ke J, Zhao D. Impaired sensitivity to thyroid hormones is associated with the change of abdominal fat in euthyroid type 2 diabetes patients: a retrospective cohort study. J Diabe Res. 2024;2024(1):8462987. doi:10.1155/2024/8462987

33. Freedland ES. Role of a critical visceral adipose tissue threshold (CVATT) in metabolic syndrome: implications for controlling dietary carbohydrates: a review. Nutr Metab. 2004;1(1):12.

34. Sanyal D, Raychaudhuri M. Hypothyroidism and obesity: an intriguing link. Indian J Endocrinol Metab. 2016;20(4):554–557. doi:10.4103/2230-8210.183454

35. Mazza E, Troiano E, Ferro Y, et al. Obesity, dietary patterns, and hormonal balance modulation: gender-specific impacts. Nutrients. 2024;16(11):1629. doi:10.3390/nu16111629

36. Mele C, Mai S, Cena T, et al. The pattern of TSH and fT4 levels across different BMI ranges in a large cohort of euthyroid patients with obesity. Front Endocrinol. 2022;13.

37. Shaoba A, Basu S, Mantis S, Minutti C. Serum thyroid-stimulating hormone levels and body mass index percentiles in children with primary hypothyroidism on levothyroxine replacement. J Clin Res Pediatr Endocrinol. 2017;9(4):337–343. doi:10.4274/jcrpe.3661

38. Witte T, Völzke H, Lerch MM, et al. Association between serum thyroid-stimulating hormone levels and visceral adipose tissue: a population-based study in Northeast Germany. Euro Thyroid J. 2017;6(1):12–19. doi:10.1159/000450977

39. McAninch EA, Bianco AC. Thyroid hormone signaling in energy homeostasis and energy metabolism. Ann N Y Acad Sci. 2014;1311:77–87. doi:10.1111/nyas.12374

40. Biondi B. Thyroid and obesity: an intriguing relationship. J Clin Endocrinol Metab. 2010;95(8):3614–3617. doi:10.1210/jc.2010-1245

41. Mullur R, Liu -Y-Y, Brent GA. Thyroid hormone regulation of metabolism. Physiol Rev. 2014;94(2):355–382. doi:10.1152/physrev.00030.2013

42. Tacke F, Horn P, Wai-Sun Wong V, et al. EASL–EASD–EASO clinical practice guidelines on the management of metabolic dysfunction-associated steatotic liver disease (MASLD). J Hepatol. 2024;81(3):492–542.

Following 2 successful workshops on AI in the energy sector, held in September 2025, the European Commission organises a third workshop on the use of AI in the renewables and buildings sectors. 

While AI holds immense potential to enhance manufacturing, optimisation, and improving maintenance, several challenges hinder effective implementation. These include data silos, lack of collaboration, and varying business models. The workshop will explore the role of the Commission in facilitating the swift and safe deployment of AI technologies in these sectors, discuss the ongoing work in the matter and inform about policy actions of the future Strategic Roadmap for Digitalisation and AI in the energy sector. 

The event is addressing stakeholders from digital and energy value chains, including technology providers, IT suppliers, SMEs, aggregators, system integrators, digital solutions providers, data centre operators, cloud service providers, consumers, energy communities, appliance manufacturers, research community, energy intensive industries, building operators, car manufacturers and providers of e-mobility solutions. 

The draft agenda will follow shortly but it is already possible to register.

Related links

The solution: Making sustainability everyone’s business

GEA’s response to the Scope 3 challenge is not to create a new sustainability silo, but to weave decarbonization into the very fabric of its operations from governance, innovation, product design, to sales. The result is a strategy that aligns climate goals with commercial advantage.

The transformation began by redefining who owns sustainability. It started at the top: the Global Executive Committee leads by example – while the Chief Sustainability Officer, as part of the GEC, ensures that climate considerations are embedded in every strategic decision. Executive compensation is directly linked to emissions reductions, including Scope 3, signaling to leadership and shareholders alike that this is core business, not corporate responsibility.

But the shift goes far beyond governance. In 2023, GEA launched its first internal “Sustainathon,” a company-wide innovation sprint modeled on hackathons, designed to crowdsource ideas from employees for reducing product-related emissions. Over five months, 88 employees across divisions developed more than 60 proposals – from energy-saving software tweaks to bold redesigns of key machinery. The winning teams received funding and direct support from top management. “The Sustainathon promotes fresh thinking and encourages employees to develop radical solutions to reduce the emissions of popular GEA products,” explains Wolfgang Deis, GEA Innovation Process Manager.

With a mobilized workforce and incentives in place, GEA turned to the challenge of reducing emissions across its value chain. The answer: enable customers and suppliers to cut their own emissions, while growing business in the process.

One breakthrough came with the Add Better ecolabel, a third-party validated label that identifies GEA machines and systems that outperform their predecessors by a measurable margin in energy or water efficiency. It’s a simple but powerful proposition for factory operators: invest in new equipment that not only performs better but cuts costs and emissions. GEA’s E-Bake solutions, for example, modernize the baking process with electric heating systems that cut energy use by up to 40% compared to gas models.

Retrofit options enable a switch from gas to electric, saving up to 14%. As resource-efficient technologies, they proudly carry the Add Better label. “Solutions in our Add Better portfolio help customers tackle rising energy costs, resource scarcity, and operational risks,” explains Sterley.

For a holistic analysis of an entire production process, GEA supports customers with Add Better Consulting – a dedicated strategy service that helps set priorities, define roadmaps, and develop effective transition plans. As the essential starting point, Add Better Consulting turns ambition into actionable plans, providing tailored decarbonization strategies, plant transition blueprints, and concrete budget considerations.

Building on these foundations, GEA brings the strategies and blueprints to life with NEXUS, an integrated engineering service solution that optimizes entire production systems – from heating and cooling to cleaning and recovery. The goal is to reengineer processes, not just machines. These end-to-end solutions unlock deep energy and emissions savings, while enhancing operational resilience. For example, GEA’s innovative low-carbon heat network at Heineken’s Manchester brewery demonstrates how integrating sustainable heat recovery solutions can significantly reduce energy consumption and emissions in large-scale manufacturing

These initiatives have helped GEA cut product-related emissions by a third since 2019.

These are not compliance-driven activities. For GEA, sustainability has become a platform for innovation, competitive advantage, and long-term growth. With 41.6% of its revenue already coming from its sustainable product portfolio, and with a target of 60% by 2030, GEA is effectively transforming its business model and the industrial ecosystem in which it operates.

Welcome address by Philip R. Lane, Member of the Executive Board of the ECB, at the 5th WE_ARE_IN Macroeconomics and Finance Conference 2025

Frankfurt am Main, 21 October 2025

It is an honour to participate in the fifth edition of the WE_ARE_IN Macroeconomics and Finance Conference and I congratulate the organising committee for putting together an excellent programme.

Let me start this speech by outlining how the ECB makes monetary policy decisions.^[1] As expressed in our monetary policy statement:^[2]

The Governing Council is determined to ensure that inflation stabilises at its 2% target in the medium term. It will follow a data-dependent and meeting-by-meeting approach to determining the appropriate monetary policy stance. In particular, the Governing Council’s interest rate decisions will be based on its assessment of the inflation outlook and the risks surrounding it, in light of the incoming economic and financial data, as well as the dynamics of underlying inflation and the strength of monetary policy transmission. The Governing Council is not pre-committing to a particular rate path.

My aim today is to review one dimension of this multi-pronged assessment: how we assess the strength of monetary policy transmission. In what follows, I describe some of the analysis that has underpinned this assessment in recent monetary policy meetings.

I will begin by outlining the contribution of monetary policy to financial conditions before reviewing aggregate credit dynamics. Next, I will move to three key factors in determining monetary transmission: first, heterogeneity across member countries; second, the implications of a high level of uncertainty for monetary transmission; and third, the transmission impact of external factors, namely trade tensions and the exchange rate.

Between July 2022 and September 2023, the ECB raised interest rates from -50 basis points to 400 basis points.^[3] After a nine-month holding phase, the monetary policy easing cycle started in June 2024. Between then and June 2025, we lowered our policy rates by a cumulative 200 basis points. Since June, our policy rates have remained unchanged.

In capturing the impact of changes in policy rates on the wider financial environment, it is useful to assess blended measures such as financial conditions indices (FCIs), which synthesise the information from a variety of financial asset prices. As such, FCIs extend the concept of the monetary policy stance to a wider set of financial markets and beyond the level of accommodation or restrictiveness that is under the central bank’s direct control. Akin to a stance measure, loose or tight financial conditions tend to stimulate or dampen economic activity, thus representing an upside or downside force acting on inflation.

Typically, FCIs combine – in a static manner that does not allow for feedback from the economy – a broad set of financial variables, including risk-free rates, sovereign and corporate spreads, equity valuations and exchange rates. It is a standard part of our assessment to study a range of FCI measures, including those developed at the ECB, international policy organisations and private-sector versions. Today, I will focus on a new addition to the family of FCI measures: a new “Macro-Finance” FCI that has been developed by ECB staff in order to overcome the “lack of feedback” problem. ^[4]

The new methodology incorporates mutual feedback between macroeconomic and financial dynamics, such that the Macro-Financial FCI reflects the joint dynamics of macroeconomic variables and financial conditions. As can be seen from the left panel of Chart 1, the overnight rate (€STR), which is closely tied to our policy rates, typically comoves with and sets the direction of the overall index. But there are also several phases in which financial conditions have moved even when the policy rate was stable (Chart 1, left panel).

The decomposition (Chart 1, middle panel) illustrates that, at the onset of the global financial crisis in 2008, plummeting risk asset prices (dark green area) turned from being a stimulative influence on the FCI to acting as a sudden and sharply tightening factor. The widening of sovereign bond spreads during the European debt crisis (light blue area) also provided extra restriction in the years around 2012. During the episode when policy rates were close to their lower bound, compressed long-term nominal rates and negative real interest rates were important sources of accommodation. As a result, the Macro-Finance FCI reached historically supportive levels in late 2021. It then climbed rapidly in the run-up to the first interest rate hike in July 2022, since the term structure of interest rates sequentially moved higher well ahead and in anticipation of our rate hikes and quantitative tightening.

In recent years, the Macro-Finance FCI peaked around the end of the 2022–23 monetary tightening cycle. The increase in the index during this period was primarily driven by rising risk-free rates, with adjustments in risk assets playing a more limited role. Since the peak of the tightening cycle, the index has indicated that financial conditions have become noticeably less restrictive, supported by lower short-term interest rates and higher valuations for risk assets, although this has been partly offset by a stronger euro.

Despite this easing, the level of the Macro-Finance FCI remains well above its historical sample average. In part, this can be attributed to a permanent component to the 2022 shift in the monetary policy stance: the re-anchoring of inflation expectations at the two per cent target means that markets do not expect a return to the “low for long” rate environment that had been expected before the pandemic to continue on an open-ended basis.

The new index outperforms other measures when it comes to describing the macroeconomic dynamics of the euro area (Chart 1, right panel). In this regard, it is key to understand that the financial prices and yields that are aggregated into the Macro-Finance FCI influence bank loan dynamics and loan pricing: this summary statistic of (mostly market-based) financial conditions can be interpreted as an important determinant of broader funding conditions, including those set by the banks, which can be collectively labelled as “financing conditions”. In the next section, we turn to a review of credit dynamics.

Lending rates have been declining broadly in line with historical regularities (Chart 2). But there is a detectable difference between developments in the lending rates to households and to firms: the relatively muted decrease in long-term market rates has contained the decline in the cost of household loans, which tend to be priced off the longer end of the term structure of interest rates and have longer fixed-rate periods, relative to loans to enterprises. As outlined above, this is consistent with a permanent component in the 2022 upward shift in policy rates, with no return expected to the “low for long” zone.

In terms of credit volumes, household borrowing, primarily for home purchases, has increased steadily. According to the bank lending survey (BLS), the recovery in mortgage demand is supported by improved housing market prospects and lower interest rates (Chart 3, panel A). Corporate borrowing is also gradually recovering, though BLS responses suggest that corporate demand for credit remains subdued, also reflecting global uncertainty and trade tensions.^[5]

This evidence raises the question of how credit is evolving compared to past regularities, given macroeconomic conditions and considering the current phase of the policy cycle. The strength of credit dynamics relative to the broader economy can be gauged through a credit-to-GDP gap analysis, which captures the deviation of the credit-to-GDP ratio from historical benchmarks.^[6] This gap can be estimated using a range of methodologies, from simple univariate approaches to more sophisticated models that account for the broader state of the economy. Regardless of the method, the gap remains in negative territory (Chart 3, panel B). This may reflect both structural factors and cyclical conditions. However, using multivariate models to control for prevailing cyclical conditions does not change the inference: credit seems to be weak if assessed against past regularities.^[7]

A number of structural shifts have been cited to explain a diminished role of credit in advanced economies. For example, households spend less on durable goods and more on services, for which they do not typically need to borrow. Demographic trends can reinforce these trends and explain why mortgages might be in lower demand than in the past. Also, spending on intangible assets – including intellectual property, software and code – has surpassed tangible investments as a share of GDP in major economies since the global financial crisis. And intangibles tend to be financed using internal funds or equity, being harder to pledge as collateral for loans. Even the AI-related investment boom in physical infrastructure, including data centres, has been primarily financed by equity.

But such structural shifts matter less for the euro area than for other economies, which leaves the effects of the previous tightening cycle as an important candidate explanation for the persistent weakness in credit that we observe today.^[8] That is, the current credit dynamics most likely reflect the cross-currents arising from the recent easing overlapping with the delayed effects of the past tightening, together with the fact that there is a permanent component to the rate tightening compared to the pre-pandemic levels. For instance, lending rates on new loans are still above those on outstanding loans, and BLS indicators show that the cumulative tightening has not yet been fully reversed.

A range of other factors that are not unrelated to the cycle may also help explain why the credit gap indicators remain negative. Heightened risk perceptions and higher bank funding costs, combined with declining excess liquidity, have played a role. In addition, pressures from supervisory and regulatory requirements to maintain solid balance sheets amid rising uncertainties, alongside the goal of supporting financial stability, have kept credit standards tight through the cycle, even as monetary policy has been eased in recent quarters. At the same time, financing from non-bank lenders has remained contained since the start of the monetary policy tightening, despite their secular increasing role in funding the real economy.

Looking in more detail at the sources of external financing for firms other than borrowing from banks, corporate bond issuance has benefited from foreign inflows into euro area bond funds in recent quarters, amid a shift in investor cross-border funds in favour of the euro area. Non-listed equities have also increased recently, likely reflecting activities of private equity funds. One segment of non-bank financing that has been growing significantly in recent years is private credit. Private credit generally refers to non-bank corporate credit provided through bilateral agreements or small “club deals” involving lenders outside the realm of securities investors or commercial banks. Despite a clear expansion in the euro area over recent years, the lion’s share of private credit is originated in the United States.^[9] Although numbers vary depending on the exact definition of private credit and source, the size of private credit in the United States is well above €1 trillion, while for the euro area numbers range from around €100 billion to around €300 billion.^[10] Taken together, non-bank financing has not grown enough to counteract the weakness in bank lending. The dynamics of all the sources of external finance for euro area firms, including equity financing, but also trade credit and non-bank financing, remain contained by historical standards (Chart 4), hence overall measures of the credit gap, as shown in Chart 3, remain negative.

On net, the ongoing transmission of monetary policy easing to credit volumes has been more gradual than anticipated building on past regularities. Equally unusual has been the pronounced heterogeneity across sectors and across borrower characteristics, which I will discuss next.

Heterogeneity in the transmission of monetary policy can affect its overall macroeconomic impact. Differences in sectoral balance sheets and sectoral exposures to macroeconomic shocks can influence the responses of households, firms and banks to changes in financing conditions.^[11]

For instance, the growth rate of loans to the manufacturing sector, although recently supported by the surge in activity due to frontloading of euro area shipments to the United States, has been weaker than that of loans to the services sector (Chart 5, Panel A).^[12] As manufacturing is capital-intensive, this development connects to the anaemic growth in investment in recent years. Moreover, manufacturing is also working-capital intensive, and therefore especially affected by the cost channel of monetary policy. That a stronger recovery in the manufacturing sector has so far not materialised helps explain a weaker pass‑through of monetary easing via the cost channel than would normally be expected. The underlying reasons could be related to the greater exposure of manufacturing to the external environment, a topic that I will get back to later. By contrast, credit dynamics in the services sector have been driven largely by real estate and leasing activities, supported by recovering domestic demand for housing and durable goods in the euro area.

At the firm level, credit growth is increasingly concentrated among larger and less risky firms (Chart 5, panel B). Results from the survey on the access to finance of enterprises (SAFE) confirm that small firms have experienced a more muted decline in external financing costs than larger producers. This points to contained transmission via the balance sheet channel and the risk-taking channel of monetary policy. Smaller firms, being more vulnerable to current macroeconomic risks, have therefore suffered sharper balance sheet losses. At the same time, banks have been more reluctant to extend credit to riskier borrowers.^[13] Since small firms also face greater obstacles in accessing alternative sources of funding, banks’ reluctance to lend further tightens the financial constraints facing smaller and riskier firms and weighs on their ability to invest.^[14]

Household loan dynamics have also shown dispersion across countries, highlighting the role of both the collateral and cash-flow channels in monetary transmission during the tightening and easing phases of the cycle (Chart 6, panel A). Differences in national mortgage markets are a key factor, reflecting institutional features such as the share of adjustable-rate mortgages (ARMs) and their maturities.^[15] Historical regularities show that the pass-through is stronger in mortgage markets with a higher share of adjustable-rate mortgages and shorter maturities, reflecting both the larger movements in short-term compared to long-term market rates and the faster repricing of the total stock of outstanding loans when fixation periods are shorter.^[16] Indeed, over the past two decades, floating-rate mortgages — which are more reactive to the policy rates – have become less popular in the major euro area economies. The shift in the types of mortgages means monetary policy takes longer to work its way into households’ debt payments. This delay in transmission means that, despite recent rate cuts, average mortgage rates are expected to rise further and drag on consumption for a number of years to come as households remortgage on to higher rates after completing long-term fixed deals.^[17] Moreover, through the collateral channel, recent interest rate cuts have pushed up asset values more in countries with high ARM shares, thereby boosting collateral values.

After a period of declining mortgage applications during the tightening period, mortgage applications have started to increase in recent quarters. Higher income households, however, have maintained lower mortgage applications compared to the pre-tightening period (Chart 6, panel B). Instead, mortgage application growth has come mostly from lower-income households, possibly reflecting the need to maintain consumption or housing purchase plans in spite of declining real wages and with less savings, especially if they spend a large share of their income on basic goods. Thus, we see a shift in the composition of mortgage demand.^[18]

Summing up, the change in borrower composition and the muted risk appetite of banks point towards the risk-taking and balance sheet channels of monetary policy operating less strongly for lower-income households and smaller firms during the easing cycle. Since these groups typically have higher marginal propensities to consume and invest, this heterogeneity in transmission may reduce the effectiveness of recent interest rate cuts in stimulating aggregate demand in the current context of high global uncertainty.^[19]

An important factor that may distort and at times suppress the transmission of monetary policy is uncertainty. Over the past year, economic policy uncertainty has risen sharply, reaching record levels in April, largely driven by trade tensions and geopolitical risks (Chart 7, left panel). Financial market volatility has, instead, remained subdued (Chart 7, right panel). While uncertainty has eased somewhat in recent months, it remains at historically high levels on both sides of the Atlantic according to newspaper-based measures, close to the peak seen during the COVID-19 pandemic.

Monitoring elevated uncertainty is crucial in analysing credit dynamics for two main reasons.

First, it directly lowers credit demand and credit supply. ECB staff finds that unexpected increases in economic policy uncertainty have a negative effect on bank lending in the euro area.^[20] When economic policy uncertainty spikes unexpectedly, households and businesses tend to delay their consumption and investment decisions, as the value of waiting for additional information increases.^[21] As a result, the financing needs and loan demand of firms drop in synch, as shown in recent BLS replies. On the lender side, banks may adopt a more cautious stance as well, delaying the approval of new loans and thereby affecting the availability of credit within the economy.^[22] These effects are amplified if financial market volatility spikes up.

Second, ECB staff also finds that elevated uncertainty diminishes the impact of monetary policy easing on firms’ investment.^[23] Even when a central bank lowers rates to encourage banks to lend and firms and households to borrow, spend and invest, the impact may be weaker or slower during periods of heightened uncertainty.

On its own terms, if uncertainty weakens monetary transmission, this implies that a more powerful monetary intervention is required to deliver a given policy objective. At the same time, monetary policymakers must strike a balance between the incentives to act more powerfully and the incentives to wait and see whether an uncertainty spike self-corrects in a timely manner. ^[24] As noted in our September monetary policy statement, uncertainty has declined compared to the peaks in the second quarter but remains elevated compared to historical norms.

The strength of monetary policy transmission depends on the configuration of the macroeconomic shocks hitting the euro area. Two (interconnected) external shocks are currently shaping euro area macroeconomic dynamics. First, a large portion of the uncertainty highlighted above stems from outside the EU, reflecting unpredictable shifts in foreign economic policies and concerns about the future course of geopolitical tensions. Second, there has been a substantial appreciation of the euro.

The recent tariff agreement between the EU and the United States has eased trade policy uncertainty and overall economic policy uncertainty to some extent, yet important questions remain. A key source of risk is the ongoing tensions in US-China trade relations. If these tensions persist, Chinese exporters would have stronger incentives to redirect shipments toward non‑US markets, heightening competition for European firms.^[25] Such increased competition would weigh on demand in export-intensive and import-competing European sectors, reducing corporate earnings and weakening the transmission of monetary easing through the cash flow and balance sheet channels. In addition to these demand-side effects, trade tensions may disrupt supply chains, amplifying the risk faced by banks in lending to firms participating in international trade and thus amplifying conditions of uncertainty.^[26]

Trade fragmentation is also heightening concerns about elevated risks to economic conditions. According to the BLS, perceived risks related to the economic outlook have been contributing to a tightening of credit standards since the last quarter of 2024 (Chart 8, panel A), despite the fact that policy rates have been reduced for much of this period.

Based on the sector-country allocation of bank credit to firms that trade with the United States, the greater risk lies with loans to exporters. This is due to the higher relative size of these exposures, and to the specifics of the July tariff agreement, which introduced a broad-based US tariff of 15 per cent for EU goods, although with some exceptions and carveouts (Chart 8, panel B).^[27] Looking ahead, it is crucial to keep an eye on the asset quality of lenders that have significant exposure to tariffs. While so far there are limited signs of deterioration in asset quality, banks’ perception of lending to firms more affected by tariffs could impair the supply of credit, weakening the monetary policy easing impulse.

Households currently benefit from a strong labour market, a low and stable inflation outlook and favourable conditions in the housing markets. However, those working in certain sectors, in particular manufacturing, are increasingly worried about the negative effects of tariffs, expecting income declines and tighter credit access. As a result, they anticipate submitting fewer credit applications (Chart 9, panel A). At the same time, lower-income households are starting to report increasing difficulties in meeting mortgage payments (Chart 9, panel B). Higher financial distress rates of households pose a downside risk for the transmission of the recent interest rate cuts.^[28]

Turning to the impact of euro appreciation on monetary transmission, there are two broad channels. First, euro appreciation affects credit demand and credit supply through its impact on macroeconomic dynamics. Second, euro appreciation affects the balance sheets and funding conditions of banks.

In relation to the former channel, euro appreciation is typically associated with slower growth and lower inflation over a multi-year horizon. At the same time, the impact varies across euro area corporates, such that it is important to take into account the differences across bank-firm pairs. In one direction, the appreciation of the euro against the US dollar and other currencies lowers price competitiveness for European exporters and import competers. In the other direction, firms that do not have large USD-denominated revenues but pay for intermediate input costs (e.g. energy) in foreign currencies (especially the dollar) benefit from a term-of-trade improvement from euro appreciation.^[29]

For credit supply, the net impact via the real economy depends on their client mix: institutions more exposed to tradable sectors may face tougher conditions, but banks with a high presence in the non‑tradable economy may benefit from the stronger purchasing power of their customers (Chart 8, panel B). On the one hand, market analysts are already discounting exposures to the United States in their estimates of euro area banks’ profitability prospects (Chart 10, panel A), despite the overall positive expectations for the sector.^[30] On the other hand, an appreciation of the euro improves the euro area’s terms of trade by lowering import prices, supporting real incomes and potentially making borrowers’ balance sheets stronger, eventually increasing banks’ willingness to serve customer segments benefiting from cheaper imports.

Turning to the latter channel, the depreciation of the dollar has a direct impact on the effective quantity of USD-denominated liquidity. USD-denominated assets constitute an integral part of the liquidity management practices of banks, both for those with active business lines in the United States and for those that use liquid dollar assets as hedging devices.

During the tariff turmoil, the unusual combination of a sell-off in US Treasury securities and a weakening dollar made it more difficult for euro area banks to rely on their USD-denominated liquid assets – once considered safe havens offering downside protection – to cushion lending and funding pressures.^[31] Banks with lower USD-denominated liquidity buffers saw their bond spreads widen more sharply. While the USD LCR is not mechanically affected by movements in the exchange rate and the liquidity regulation in the EU generally does not require banks to hold LCR levels in foreign currencies above 100 per cent, excessively low levels of USD LCR may become a source of fragility for banks during episodes of large exchange rate volatility.^[32] Since the euro area banking system has made progress in increasing their USD LCRs in recent years (Chart 10, panel B), it did not experience sizeable liquidity strains even at the height of the exchange rate volatility in early April, though the episode may have altered the algebra of liquidity management for the remainder of the year.^[33]

Since euro appreciation reflects a global portfolio rebalancing that has triggered higher capital inflows into the euro, this may provide a windfall of funding opportunities for euro area banks while also creating the market conditions that have further contributed to the compression of bank bond spreads. Against this backdrop, bank bond issuance activity has rebounded since May, including a pickup in USD-denominated bonds.^[34] Moreover, globally active euro area banks, for which USD funding represents a non-negligible share of total liabilities, can pass through the easier funding conditions to other banks via interbank money market lending.^[35]

Euro appreciation also generates valuation losses on the asset side of euro area banks but also effective funding cost reductions on the liability side. The repercussions of these two countervailing effects on the intermediation capacity of banks and credit supply depends on the aggregate net exposure but also on whether exposures via assets and liabilities are unevenly distributed in the cross-section.

Exposures on the asset side can be sizeable. Total USD exposures represented almost 10 per cent of the assets of the euro area banking system in the second quarter of 2025.^[36] Among the banks with USD asset exposures, the interquartile range of the ratio of these exposures over total assets lies between 5 per cent and 25 per cent as at the second quarter of 2025, with around one half of the overall exposures accounted for by loans of banking groups active outside of the euro area (Chart 11, Panel A). In general, the valuation impact is relatively contained when cast against the capital buffers of the euro area banking system or previous episodes of valuation losses associated with, for instance, fluctuations in the value of sovereign holdings.

Moreover, euro area banks also have a substantial part of liabilities denominated in USD, with an interquartile range ranging between 7 per cent and 28 per cent as at the second quarter of 2025, and with a total amount similar to that of assets. A substantial share (43 per cent) of USD-denominated liabilities is provided by financial entities (Chart 11, panel B) and is therefore relatively volatile, especially during market turbulence. Overall, the net exposure in USD is rather stable over time: for banks with USD exposures, it is close to zero for the median bank and slightly negative in the aggregate at -2 per cent of banks’ assets. Moreover, reflecting the asset-liability management practices and the business models of banks with significant USD activity, net exposures are typically relatively unreactive to fluctuations in the exchange rate, policy rates or the business cycle. At the same time, the combined presence of substantial USD-denominated off-balance sheet exposures and volatile funding means that sudden changes in these net exposures cannot be ruled out. An increased probability of such a risk event would then generate pressures on both sides of banks’ balance sheets and potentially downward pressure on on-balance sheet exposures like loans to the real economy.^[37] Moreover, the composition of USD liabilities, dominated by funding from financial customers and with a limited share of retail deposits, can exacerbate these pressures by making funding more flight‑prone, thereby increasing vulnerability in a stress scenario.

My aim in this speech has been to showcase some of the analysis that has underpinned our assessment of the strength of monetary transmission in recent monetary policy meetings. In overall terms, monetary policy transmission is progressing smoothly. Yet, within this overall favourable environment, the analysis reported above highlights that it is also important to take into account significant differences across different types of banks, firms and households, across different sectors and across countries.

More generally, the analysis shows that the strength of monetary transmission is time-varying and also depends on the configuration of domestic and external macroeconomic shocks hitting the euro area economy. Accordingly, it makes sense to maintain a meeting-by-meeting and data-dependent approach to assessing the strength of monetary transmission at any given point in time. In turn, this feeds into our overall monetary policy decision making, alongside our other assessment criteria: the inflation outlook and the risks surrounding it, together with the dynamics of underlying inflation.

Introduction

Student enjoyment pertains to the sense of pleasure or satisfaction that students derive from the learning process. Enjoyment of a learning activity fosters sustained motivation, enthusiasm, and positive emotions that enhance the overall learning experience.^1,2 This aspect of education is closely intertwined with both student interest and motivation. While these three concepts share connections, they represent distinct dimensions of a student’s engagement with learning. Student interest involves the curiosity and attraction that they feel toward a particular subject or activity, whereas motivation encompasses the factors that drive students to dedicate themselves to the learning process.³ According to the Self-Determination Theory, motivation is enhanced when learners experience autonomy in learning, feeling of competence, and sense of relatedness to other students.⁴ Similarly, constructivist theory emphasizes that learning is most engaging when students actively construct knowledge through hands-on activities, real-world problem-solving, and collaborative interaction.⁵ This indicates that motivation is dependent on multiple factors that include the learner’s psychological needs, personal values, and the social context in which learning occurs. The synergy of enjoyment, interest, and motivation is crucial for the academic achievement of students, as these elements significantly influence student engagement with the overall learning experience.^2–7 This combination contributes to a positive and effective learning atmosphere, fostering not only academic success but also a genuine passion for knowledge.^4,8 While these concepts may overlap, each would play a distinctive role in shaping and enhancing the overall quality of the student’s learning experience.

Given the close relationship between motivation and positive learning experiences, student enjoyment can be seen as a complementary driver of engagement, influenced by factors such as teachers’ proficiency, students’ self-efficacy, and the complexity of the subject matter. This perception drives the ongoing search for more engaging and effective instructional formats, highlighting the need to explore and refine pedagogical strategies that address diverse learning needs. Within this context, lectures remain one of the most scrutinized instructional methods in higher education. Over the past decades, the debate about the effectiveness of didactical lectures has persisted, yielding mixed outcomes that reflect the diverse perspectives among educators and the heterogeneous opinions held by students regarding instructional methods.^9–11 Didactic lectures have often faced criticism for their perceived lack of student enjoyment, primarily stemming from their reliance on passive one-way information delivery.^12–14 In contrast to active learning methodologies such as problem-based learning (PBL) or team-based learning (TBL), students frequently perceive didactic lectures as boring or ineffective.^12–14 In response to these critiques, many educators are adopting a more interactive approach to their lectures. They seek to engage students by incorporating entertaining activities such as real-life scenarios¹⁵ games¹⁶ technology¹⁷ or problem-solving components¹⁸ during lectures. However, despite these efforts, there are no universally clear guidelines on how to organize lectures that are not only educational but also enjoyable. Practical tips and useful recommendations published in Medical Teacher offer valuable strategies to help educators transform didactic lectures into interactive, and effective sessions.¹⁹

A skilled lecturer possesses the ability to attract the attention of students and enhance their enjoyment through various innovative techniques that include incorporating personal experiences, telling jokes, and sharing relevant stories.^2,20 The impact of such engaging teaching strategies extends beyond mere enjoyment; they have the potential to significantly influence the overall motivation and performance of students. An instructor with an entertaining and effective teaching style can successfully convey information, fostering a positive and dynamic learning environment that may surpass the positive ratings of active learning.²¹ In contrast, some instructors may lack the talent to effectively engage and motivate their students, resulting in a potential adverse effect on the students’ overall academic performance. However, it is worth noting that Deslauriers et al demonstrated that while students may rate enjoyable lectures positively and even feel they learned more compared to active learning sessions, objective measures showed that actual learning was greater in active learning environments that were perceived lower, indicating that high enjoyment does not necessarily lead to better learning.²²

The ongoing debate about the effectiveness of teacher-based learning methods (or passive instruction) versus student-based learning methods (or active instruction) is persistent despite the numerous studies conducted over the past decades. The multitude of factors influencing students’ enjoyment in both types of instruction could be responsible for the variable preferences or mixed feelings of enjoyment among students. In addition to the educational environment, factors such as teachers’ varying skills and experiences and the difficulty level of certain subjects all contribute to and impact the level of enjoyment experienced during a teaching activity.^1,13,14,22 Since enjoyment influences engagement, the present study aimed to develop and validate an objective instrument for systematically measuring students’ enjoyment in different pedagogical contexts, and to apply it in evaluating the enjoyment of first-year students in Physiology lectures. This kind of tool would help teachers to examine teaching strategies, identify the origins of differences in student enjoyment, and understand how the same strategies will yield different results when used by different teachers or when applied to different contexts. We sought to apply this scale objectively to measure the enjoyment scores of didactic lectures and investigate associated factors. Through this research, we aim to contribute valuable insights into the dynamics of student enjoyment, offering a tool that explores the factors that influence students’ learning experiences.

Methods

Study Design and Participants

In this cross-sectional study, we assessed the enjoyment levels of first-year undergraduate medical and dental students during two physiology lectures. Lectures were delivered by experienced and highly rated professor, followed a didactic format with interactive discussion to encourage student participation and lasted 50 minutes. First-year medical and dental students were chosen to participate in this study because they were newcomers to university health profession education, suggesting that they were unlikely to have developed preferences for specific instructional methods at this early stage. The University Research Ethics Committee granted approval for the study under the reference number “HEC-10-2023/24-F-M.” Informed consent was obtained by first providing students with a briefing sheet detailing the study’s aims and purpose. Students were informed that their participation was entirely voluntary and would not affect their marks or academic evaluation. They were then asked to sign a consent form confirming that they had read and understood the information and agreed to participate in the study. A total of 112 (68%) students participated in the study, with 32 (out of 47) participants from the dental college and 80 (out of 118) from the medical college. The measuring instrument was distributed to all students immediately following the teaching session.

Data Collection Tool

The Learning Enjoyment Scale (LES) was developed by the investigators as a comprehensive and objective measure of students’ enjoyment in the learning process (Figure 1). A brief description of the scale with guidance on its analysis, has been previously published as a data note.^23,24 The scale items are strategically based on the major categories of Bloom’s Taxonomy, specifically focusing on cognitive knowledge and affective attitudes. The LES comprises six items: knowledge, comprehension, application, analysis, concentration, and enjoyment. Students are requested to assess each item using a five-point Likert scale, ranging from 1 to 5 (1 = strongly disagree, 2 = disagree, 3 = unsure, 4 = agree, and 5 = strongly agree). The minimum and maximum total scores across the six items are 6 and 30, respectively. If all responses are agree (ie, Likert scale 4), the total score is 24, representing 80% of the maximum score. Conversely, if all responses are unsure (ie, Likert scale 3), the total score is 18, which accounts for 60% of the maximum score. Consequently, an excellent score is deemed to be above 80% (25–30), an acceptable score falls within the range of 60–80% (18–24), and a low score is defined as less than 60% (< 18). These thresholds facilitate clear interpretation of students’ enjoyment levels and are consistent with educational standards for assessing performance and satisfaction in academic settings.

Figure 1 The Learning Enjoyment Scale. The Learning Enjoyment Scale (LES) is a comprehensive tool developed to assess student enjoyment. (A) contains six items measuring perceived learning, confidence, interest, and overall enjoyment. (B) contains six items assessing factors influencing enjoyment, such as teacher talent, content difficulty, participation, achievement of objectives, stress levels, and skill satisfaction.

The second section of the scale (enjoyment attributes) assesses the influence of various factors on students’ enjoyment. These factors include the teacher’s talent, the complexity of the topic, student participation, fulfillment of objectives, perceived stress levels, and the development of skills. The analysis of this section provides detailed understanding of the specific elements that impact students’ enjoyment during the learning process.

Data Analysis Plan

The statistical analysis for this study was carried out using the Statistical Package for Social Sciences (SPSS), version 26. Reliability analysis was applied to determine the internal consistency of the Learning Enjoyment Scale (LES) through Cronbach’s alpha. The obtained value of Cronbach’s alpha was interpreted, with values greater than 0.7 indicating a good level of internal consistency. General tendencies of the Learning Enjoyment Scale items were analyzed using the mean ± SD. The comparisons and associations between LES items or LES attributes and the total score categories were analyzed using the Spearman correlation and the chi-square test with Fisher’s exact correction, as appropriate. A p-value of <0.05 was considered statistically significant.

Results

Table 1 displays the items of the Learning Enjoyment Scale (LES), the learning domain assessed by each item and the general tendency of students to respond to each item. According to the Likert scale analysis, the overall tendency of students’ responses in this study was “agree”. Reliability and validity of the scale were confirmed in this study: internal consistency was excellent, with a Cronbach’s Alpha of 0.91. Exploratory Factor Analysis (EFA) supported the theoretical six-domain structure, with the first two components explaining 80.5% of the variance. Inter-item correlations ranged from 0.57 to 0.81, indicating meaningful relationships between items. These psychometric properties demonstrate that the LES is a robust and valid instrument for measuring students’ enjoyment in learning contexts.

Table 1 General Tendencies of Students’ Responses to the Learning Enjoyment Scale Items

Table 2 shows the relationships of the six items of the LES with the three categories of the total score (Low, Acceptable and Excellent). The table shows a significant relation between the students’ responses and the LES categories, with “agree” being the most frequent response and “acceptable” being the major LES category.

Table 2 Examining Students’ Responses to Learning Enjoyment Scale Questionnaire Items in Relation to Total Score Categories

Table 3 displays the association between enjoyment attributes and the three categories of the total score. Enjoyment of a learning activity was strongly related to teachers’ talent (P< 0.001), difficulty of the topic (P< 0.001), students’ active participation during the activity (P< 0.001), fulfillment of the objectives (P< 0.001), low level of stress during the activity (P< 0.001) and self-perception of acquired skills (P< 0.001).

Table 3 Relationships Between Enjoyment Attributes and Categories According to the Total Learning Enjoyment Scale

Most dental students (97%) and medical students (95%) showed either acceptable or high enjoyment scores for the Physiology lectures. The difference between students in the two colleges was not statistically significant (Table 4).

Table 4 Comparison of the Total Learning Enjoyment Scale Scores of Dental and Medical Students

Table 5 demonstrates moderate to strong positive Spearman correlations (ρ = 0.35–0.57) between the Total LES Score and all enjoyment attributes, indicating that students with higher LES scores consistently reported more favorable perceptions. The strongest association was observed for “The teacher is talented in teaching” (ρ = 0.57, p < 0.001), suggesting that perceptions of teaching talent are closely aligned with overall enjoyment levels. Other positive correlations further indicate that attributes such as active participation, fulfillment of learning objectives, reduced stress, satisfaction with skills gained, and perceived easiness of topic content also contribute meaningfully to students’ enjoyment.

Table 5 Spearman Correlation Between Total Learning Enjoyment Score and Enjoyment Attributes

Discussion

Enjoyment can be defined as a positive emotional response to learning experiences, characterized by interest, engagement, and satisfaction, which can coexist with the pursuit of academic excellence.²⁵ Because it is a subjective feeling, there is currently no universally accepted instrument for its assessment. Researchers have employed a variety of approaches, including single-question ratings (eg, on a scale from 0 to 6),²⁶ satisfaction questionnaires with open-ended items,^27,28 adapted items from the Achievement Emotions Questionnaire,²⁹ and researcher-designed questionnaires based on enjoyment indicators.³⁰ While these methods provide useful insights, they vary widely in scope, depth, and focus, highlighting the need for a more structured and comprehensive tool that captures multiple dimensions of enjoyment and links them to specific aspects of the learning experience.

The Learning Enjoyment Scale (LES) employed in this study was developed by researchers to directly measure students’ enjoyment following various types of teaching activities. In developing this scale, a direct question about enjoyment was incorporated, alongside additional items assessing students’ perceptions of various learning domains (knowledge, comprehension, application, and analysis) which are recognized to influence enjoyment. The scale reflects students’ satisfaction and self-perception of the knowledge acquired during the completed teaching activity. The psychometric properties, including excellent internal consistency (Cronbach’s Alpha = 0.91), strong inter-item correlations (ranging from 0.57 to 0.81), and support for the theoretical six-domain structure through Exploratory Factor Analysis (explaining 80.5% of the variance), confirm that the LES is a reliable and valid tool for measuring students’ enjoyment in learning contexts. A test–retest reliability is planned for future research to further validate the scale. The LES items are grounded in the major categories of Bloom’s Taxonomy, encompassing cognitive knowledge and affective attitude, while the psychomotor domain is partially addressed in the second section of the scale. Broadly, the scale evaluates students’ perceptions of knowledge, comprehension, application, analysis, interest, and enjoyment attained during the teaching activity. The calculated total LES provides a quantitative value for comparisons across different teaching activities and is categorized as excellent, acceptable, or low. Our findings revealed a significant relationship between students’ responses to the questionnaire items and LES score categories, with “Agree” emerging as the most frequent response and “Acceptable” being the predominant category.

The second section of the LES is excluded from the score calculation but plays a crucial role in assessing specific factors known to influence the overall enjoyment score. This section evaluates key elements impacting enjoyment, including the teacher’s proficiency, the complexity of the topic, active student participation, alignment with learning objectives, perceived stress during the teaching activity, and skill development. Our study demonstrated a significant association between these enjoyment attributes and the total LES score for Physiology lectures. The findings affirm that these factors collectively contribute to the study’s acceptable LES score. Notably, didactic lectures are well received by students when these factors are effectively considered and addressed. It is essential to highlight that these factors, such as teachers’ talent and skills in teaching, are often overlooked in comparisons of teaching methods’ effectiveness, including a large number of studies that praise problem-based learning and team-based learning pedagogy for being superior to lectures in many educational aspects, including enjoyment.^12–14 It is obvious that lectures can be engaging and enjoyable when presented by a talented faculty member and, conversely, uninteresting and ineffective when delivered by a faculty member lacking in presentation skills.

It is not surprising that the conclusion asserting that lectures are old teaching methods focused solely on simple transfer of information to passive listeners has been controversial for decades, as it overlooks the outcomes of interesting lectures delivered by expert talented professors who know how to draw the attention of their students through various interventions, such as stories, past experiences, gestures, a sense of humor, facial expressions, stimulating questions and purposeful movements.^13,31,32 In the absence of an objective tool for evaluation, we can claim that lectures described as ineffective might be just boring due to lack of experience or deficient skills of the presenting instructors. This perception often leads educators to undermine the role of lectures in efficiently conveying vital information to a large audience within a limited timeframe, thus favoring student-centered teaching methods that require minimal instructor input. Our assumption is supported by numerous studies indicating that didactic lectures are effective, or even superior to, alternative teaching methods.^12–14 Additionally, lectures delivered with a sense of humor and teacher’s enthusiasm are not only enjoyable but also more likely to be attended by students.^31,32 This underscores the importance of our proposed Learning Enjoyment Scale and its attributes, providing an objective means of measuring students’ enjoyment and facilitating comparisons across various teaching activities.

Given that the majority of our students expressed agreement and satisfaction with all the enjoyment attributes outlined in the questionnaire, especially the teacher’s talent, the anticipated significant relationship with an acceptable total LES score was validated. However, a previous study showed that although students reported a high enjoyment level of lectures delivered by experienced and highly appraised professors, the actual learning was less than expected.²² Similarly, while activities such as academic games can be more enjoyable and motivating than didactic lectures,³³ evidence indicates that knowledge retention from such games is often comparable to, or even lower than, that achieved through traditional lectures.^34,35 These findings suggest that factors other than enjoyment may play a more significant role in promoting effective learning.

Students might find enjoyment in didactic lectures because they can passively absorb information without the stress of demonstrating their understanding or skills. It is widely recognized that students may shy away from active participation in class due to anxiety or fear of judgment from their peers or instructors. Encouraging student participation without inducing stress fosters active engagement and promotes effective learning.³⁶ Even seemingly simple interventions, such as incorporating games, problems or humor, have been shown to reduce stress and enhance enjoyment.^16,18,37 Our findings align with this perspective, revealing a low perceived stress level during Physiology lectures. In contrast to more challenging subjects which may be less enjoyable, subjects such as Physiology, which are perceived as easier, are associated with lower stress levels. This is likely due to clarity, organization, and reduced demand for intense attention and deep thinking, which are factors that may contribute to a more conducive learning environment.

Several limitations must be considered when interpreting the results of this study. First, the study focused exclusively on first-year students, whose perceptions may differ from those of students in later years. Additionally, with a response rate of 68%, the impact of nonparticipating students’ perspectives on the results remains uncertain. Furthermore, the self-reported measure introduces the possibility of response bias. Moreover, the evaluation of enjoyment was conducted immediately after lectures, without assessing long-term knowledge retention. Finally, the developed LES was specifically applied to Physiology lectures within a single university in the UAE. Its generalizability and effectiveness should be further explored by applying it to other subjects, different teaching methods, and diverse geographic locations. This broader application would enhance the scale’s validity and provide a more comprehensive understanding of its utility in various educational contexts.

Conclusions

This study confirms that the Learning Enjoyment Scale (LES) is a reliable and valid tool for assessing students’ enjoyment across didactic lectures, demonstrating excellent internal consistency (Cronbach’s α = 0.91) and strong construct validity. Applied to undergraduate physiology lectures, the LES revealed that most students reported acceptable or high enjoyment levels, with no significant differences between medical and dental students. Enjoyment was most strongly associated with perceptions of the teacher’s talent, followed by active participation, fulfillment of learning objectives, reduced stress, satisfaction with skills gained, and perceived ease of content. Future research should explore the application of the LES in evaluating different instructional methods, its potential to predict learning outcomes, and its applicability across diverse disciplines and learning environments.

Data Sharing Statement

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

Ethics Approval and Consent to Participate

This study was approved by the Ethics Committee of RAK Medical and Health Sciences University, UAE (Approval No. HEC-10-2023/24-F-M), and followed the guidelines of the Declaration of Helsinki of the World Medical Association. Informed consent was obtained from all participants involved in the study.

Acknowledgments

The authors express their thanks to the students who participated in this study.

Author Contributions

All authors made a significant contribution to the work reported, whether that is in the conception, study design, execution, acquisition of data, analysis and interpretation, or in all these areas; took part in drafting, revising or critically reviewing the article; gave final approval of the version to be published; have agreed on the journal to which the article has been submitted; and agree to be accountable for all aspects of the work.

Funding

The authors declare that they did not receive any funding towards this study.

Disclosure

The authors declare no competing interests.

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• Data presented at IDWeek 2025 after study stopped early for efficacy
• Primary endpoint met, demonstrating non-inferiority of oral tebipenem HBr compared to intravenous treatment¹
• A new oral option may reduce the need for cUTI treatment in hospital setting
• Data will be shared with regulatory authorities to support regulatory filings

GSK plc (LSE/NYSE: GSK) and Spero Therapeutics (Nasdaq: SPRO) today announced full results of the positive pivotal phase III PIVOT-PO trial evaluating tebipenem HBr, an investigational oral treatment for complicated urinary tract infections (cUTIs), including pyelonephritis (NCT06059846). These results were presented on 20 October 2025 in a late-breaking oral abstract session at ID Week 2025 in Atlanta, USA. 

Complicated UTIs represent an important health issue, with an estimated 2.9 million cases treated annually in the US alone.² These infections are often caused by multidrug-resistant pathogens³ and carry serious risks including organ failure, sepsis, and even death.^3-5 They also result in significant emergency department visits and hospitalisations, contributing to over $6 billion per year in healthcare costs.⁶ Current standard of care includes carbapenem antibiotics in cases of sepsis or resistance to other antibiotics but they are only available for intravenous administration typically occurring in hospital setting.^7,8 

The trial, which was stopped early for efficacy in May, demonstrated non-inferiority of tebipenem HBr compared to intravenous imipenem-cilastatin in hospitalised patients with cUTI, including pyelonephritis, based on the overall response (composite of clinical cure plus microbiological eradication of the bacteria causing the infection) at the test of cure visit. Tebipenem HBr (oral, 600 mg) achieved a 58.5% overall success rate (261/446 participants) compared to 60.2% overall success rate (291/483 participants) for imipenem-cilastatin (intravenous, 500 mg) (adjusted treatment difference: −1.3%; 95% CI: −7.5%, 4.8%). The safety profile of tebipenem HBr was generally similar to that of imipenem-cilastatin and other carbapenem antibiotics. The most frequently reported adverse events (in ≥3% of patients who received tebipenem HBr) were diarrhea and headache; these events were all mild or moderate and non-serious. 

Tony Wood, Chief Scientific Officer, GSK, said: “Complicated UTIs can have serious consequences for patients, including organ failure and sepsis, and oral options for drug-resistant infections are limited. These ground-breaking data show for the first time that cUTIs, including pyelonephritis, can be treated with an oral carbapenem antibiotic as effectively as with an intravenous one. We have a long-standing commitment to delivering novel anti-infectives and are delighted to offer the potential of tebipenem HBr as an effective oral alternative that could be taken at home”. 

Esther Rajavelu, Chief Executive Officer, Spero Therapeutics, said: “These data presented at IDWeek represent the culmination of years of dedicated work by our team in close collaboration with GSK. We are deeply grateful to the physicians, researchers, support staff, and, most importantly, to the patients who made this study, and the ones before it, possible. Along with GSK, we are now focused on advancing tebipenem HBr toward FDA submission and bringing this important therapy to patients in need.”

Dr George Sakoulas, Adjunct Professor Department of Pediatrics, UCSD School of Medicine and Chief Infectious Diseases Sharp Rees Stealy Medical Group, commented: “Increasing antibiotic resistance among community-acquired bacteria that cause cUTIs is greatly amplifying the burden of treatment for patients, clinicians, and payers. The therapeutic flexibility of a new oral antibiotic may reduce the need for intravenous antibiotics to treat cUTI, providing benefit to patients and improving treatment options.”

Secondary endpoints also show:

• Clinical cure (i.e. absence of symptoms) rates at test of cure visit were 93.5% in the tebipenem HBr group (417/446) compared to 95.2% in the imipenem-cilastatin group (460/483) with adjusted treatment difference: −1.6% (95% CI: −4.7%, 1.4%)
• Microbiological response rates at test of cure visit were 60.3% in the tebipenem HBr group (269/446) compared to 61.3% in the imipenem-cilastatin group (296/483) with adjusted treatment difference: −0.8% (95% CI: −6.9%, 5.3%)
• Overall, clinical and microbiological response rates at test of cure in participants with infections caused by antimicrobial-resistant Enterobacterales were consistent with the respective response rates in the primary analysis population. 

GSK plans to work with US regulatory authorities to include the data as part of a filing in Q4 2025. If approved, tebipenem HBr would be the first oral carbapenem antibiotic in the US for patients who suffer from cUTIs, adding to GSK’s growing anti-infectives portfolio and helping address the challenges of antimicrobial resistance (AMR). 

The development of tebipenem HBr is supported in part with federal funds from the U.S. Department of Health and Human Services; Administration for Strategic Preparedness and Response; Biomedical Advanced Research and Development Authority (BARDA), under contract number HHSO100201800015C.  

About tebipenem HBr

Tebipenem pivoxil as hydrobromide salt (Tebipenem HBr) is a late-stage development asset developed in collaboration with Spero Therapeutics. Tebipenem HBr is being developed to treat cUTIs, including pyelonephritis. In September 2022, GSK entered into an exclusive license agreement with Spero Therapeutics for the development and commercialisation of tebipenem HBr in all markets, except certain Asian territories. Under this agreement GSK has sub-licensed back to Spero Therapeutics the rights and responsibility to conduct certain development work including the PIVOT-PO Phase III study, after which sponsorship of the new drug application (NDA) will be transferred to GSK from Spero Therapeutics. Tebipenem HBr has received Qualified Infectious Disease Product (QIDP) and Fast Track designations from the US FDA.

About the PIVOT-PO trial

PIVOT-PO was a global, randomised, double-blind, pivotal, non-inferiority (NI margin: -10%) Phase III clinical trial of oral tebipenem HBr compared to IV imipenem-cilastatin, in hospitalised adult patients with cUTI including pyelonephritis. Patients were randomised 1:1 to receive tebipenem pivoxil (600 mg) orally every six hours, or imipenem-cilastatin (500 mg) IV every six hours, for a total of seven to ten days. Matching placebos were used to maintain blinding. The primary efficacy endpoint was overall response (composite of clinical cure plus microbiological eradication) at the test-of-cure visit (about 17 days from first dose administration of study drug) in patients with qualifying pathogens susceptible to imipenem. The trial enrolled a total of 1,690 patients, with randomisation stratified by age, baseline diagnosis (cUTI or pyelonephritis), and the presence or absence of urinary tract instrumentation. For further details on the trial, refer to clinicaltrials.gov identifier NCT06059846.

About complicated urinary tract infections (cUTIs)

cUTIs are broadly described as any UTI that carries an increased risk of morbidity and mortality.³ Definitions of cUTIs are not currently uniform among international societies and regulatory agencies.^{5, 9} cUTIs encompass a heterogeneous patient population due to the wide range of host factors, comorbidities and urological abnormalities associated with cUTIs.^{5, 9} Risk factors for cUTI include indwelling catheters, ureteric stents, neurogenic bladder, obstructive uropathy, urinary retention, urinary diversion, kidney stones, diabetes mellitus, immune deficiency, urinary tract modification, and UTIs in renal transplant patients.^{3, 10-13}

GSK in infectious diseases

GSK has pioneered innovation in infectious diseases for over 70 years, and the Company’s pipeline of medicines and vaccines is one of the largest and most diverse in the industry, with a goal of developing preventive and therapeutic treatments for multiple disease areas or diseases with high unmet needs globally. Our expertise and capabilities in infectious disease strongly position us to help prevent and treat disease, and potentially mitigate the challenge of antimicrobial resistance (AMR).

About Spero Therapeutics

Spero Therapeutics, headquartered in Cambridge, Massachusetts, is a clinical-stage biopharmaceutical company focused on identifying and developing novel treatments for rare diseases and multi-drug resistant (MDR) bacterial infections with high unmet need. For more information, visit www.sperotherapeutics.com

About GSK

GSK is a global biopharma company with a purpose to unite science, technology, and talent to get ahead of disease together. Find out more at gsk.com.

Cautionary statement regarding forward-looking statements

GSK cautions investors that any forward-looking statements or projections made by GSK, including those made in this announcement, are subject to risks and uncertainties that may cause actual results to differ materially from those projected. Such factors include, but are not limited to, those described in the “Risk Factors” section in GSK’s Annual Report on Form 20-F for 2024, and GSK’s Q2 Results for 2025.

References

1. Hong D. et al, Oral Tebipenem Pivoxil Hydrobromide vs Intravenous Imipenem-Cilastatin in Patients with Complicated Urinary Tract Infections or Acute Pyelonephritis: Efficacy and Safety Results from the Phase 3 PIVOT-PO study, Oral presentation at ID Week 2025, 20 October 2025. 
2. Carreno JJ, et al. Longitudinal, Nationwide, Cohort Study to Assess Incidence, Outcomes, and Costs Associated With Complicated Urinary Tract Infection. Open Forum Infect Dis. 2019;6:ofz446.
3. Sabih A, Leslie SW. Complicated urinary tract infections. In: StatPearls. 2023. StatPearls Publishing: Treasure Island, FL, USA.
4. Vallejo-Torres L, et al. Cost of hospitalised patients due to complicated urinary tract infections: a retrospective observational study in countries with high prevalence of multidrug-resistant Gram-negative bacteria: the COMBACTE-MAGNET, RESCUING study. BMJ Open. 2018;8:e020251.
5. Marantidis J, Sussman RD. Unmet Needs in Complicated Urinary Tract Infections: Challenges, Recommendations, and Emerging Treatment Pathways. Infect Drug Resist. 2023:16:1391-1405.
6. Lodise TP, et al. Hospital admission patterns of adult patients with complicated urinary tract infections who present to the hospital by disease acuity and comorbid conditions: How many admissions are potentially avoidable? Am J Infect Control. 2021;49(12):1528-1534.
7. Cotroneo, N., et al. In Vitro and In Vivo Characterization of Tebipenem, an Oral Carbapenem. Antimicrobial agents and chemotherapy. 2020. 64(8), e02240-19.
8. Maeda M, et al. Efficacy of carbapenems versus alternative antimicrobials for treating complicated urinary tract infections caused by antimicrobial-resistant Gram-negative bacteria: protocol for a systematic review and meta-analysis. BMJ Open. 2023 Apr 21;13(4):e069166.
9. Fernandez MM, et al. Poster presented at ESCMID Global, 27–30 April 2024, Barcelona, Spain. Poster P1023.
10. Bonkat G, et al. Keep it Simple: A Proposal for a New Definition of Uncomplicated and Complicated Urinary Tract Infections from the EAU Urological Infections Guidelines Panel. Eur Urol. 2024;86(3):195-197.
11. Wagenlehner FME, et al. Epidemiology, definition and treatment of complicated urinary tract infections. Nat Rev Urol. 2020;17(10):586-600.
12. Gomila A, et al. Predictive factors for multidrug-resistant gram-negative bacteria among hospitalised patients with complicated urinary tract infections. Antimicrob Resist Infect Control. 2018;7:111.
13. Altunal N, et al. Ureteral stent infections: a prospective study. Braz J Infect Dis. 2017;21(3):361-364.