# Association between a mismatch of maternal/neonatal body size and obstetrical interventions in Switzerland in the 1920s: a cross-sectional study

Nora Haag, Mathilde Le Vu, Adrian Jaeggi, David Baud, David Desseauve, Martin Haeusler, Kaspar Staub, Katarina L Matthes

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Nora Haag, Mathilde Le Vu, Adrian Jaeggi, David Baud, David Desseauve, et al.. Association between a mismatch of maternal/neonatal body size and obstetrical interventions in Switzerland in the 1920s: a cross-sectional study. Swiss Medical Weekly, 2025, 155 (11), pp.4546. 10.57187/s.4546. hal-05399082

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# Association between a mismatch of maternal/neonatal body size and obstetrical interventions in Switzerland in the 1920s: a cross-sectional study

Nora Haagª, Mathilde Le Vuab, Adrian V. Jaeggiª, David Baudcd, David Desseauvece, Martin Haeuslerª, Kaspar Staubª, Katarina L. Matthesª

ª Institute of Evolutionary Medicine, University of Zurich, Zurich, Switzerland

b Research Institute for Environmental and Occupational Health (Irset), UMR_S 1085, National Institute of Health and Medical Research (INSERM), University of Rennes and EHESP School of Public Health, Rennes, France

c Materno-Foetal and Obstetric Research Unit, Woman-Mother-Child Department, University Hospital of Lausanne (CHUV), Lausanne, Switzerland

d University of Lausanne (UNIL), Lausanne, Switzerland

e Obstetric Units, Child Couple University Hospital, University of Grenoble, Grenoble, France

## Summary

**INTRODUCTION:** Human childbirth remains a complex and risky process for both mothers and infants, even with modern advancements in medical care. This study investigated the prevalence of obstetric interventions, namely caesarean sections, episiotomies, and forceps deliveries, along with the role of maternal-fetal body size mismatch in influencing delivery outcomes.

**METHODS:** Utilising two datasets from similar archival sources in two Swiss cities (Basel and Lausanne) from the 1920s, we explored the relevance of a mismatch between the body size of the mother and the foetus as a risk factor for obstetrical interventions and the duration of the expulsion phase during delivery.

**RESULTS:** Over 91% of births (1290/1407 in Basel and 1062/1145 in Lausanne) featured the foetal head in a normal position (either the right or left occiput anterior position). Episiotomies were performed in 8–17% of cases (233/1407 in Basel and 98/1145 in Lausanne) and forceps deliveries in 1–5% (17/1407 in Basel and 54/1145 in Lausanne). Caesarean sections were rare (<1%, 19/1407 in Basel and 6/1145 in Lausanne). Key findings indicated that larger foetal head diameters and narrower pelvic measurements were linked to prolonged expulsion phases and an increased likelihood of intervention. Abnormal head positions and first-time births were also associated with obstetrical interventions. Additionally, rickets was documented in 2% of mothers (23/1145) in Lausanne, correlating with increased forceps use and caesarean section rates.

**CONCLUSION:** This research provides insights into obstetric practices and maternal health conditions over a century ago, emphasising the significant impact of maternal-fetal body size mismatches on childbirth complications in a historical context.

## Introduction

Human childbirth is a complex process, and despite improved medical care, it is still associated with risks for both the mother and child. In the worst cases, it can be fatal for both. The global burden of maternal morbidity and mortality remains high despite progress in recent decades [1]. An estimated 295,000 maternal deaths occurred worldwide in 2017. The global maternal mortality ratio (MMR) was estimated at 211 per 100,000 live births in 2017, a 38% reduction from 2000, when it was 342 per 100,000 [2]. However, there are important geographical disparities, which have been even more pronounced since the 1990s, as the burden of maternal mortality is very high in developing countries [1]. The UN has therefore explicitly included reducing maternal mortality worldwide in the Sustainable Development Goals (SDG Goal 3.1) [3]. Approximately 73% of maternal deaths between 2003 and 2009 were due to direct obstetric causes (e.g. abortion, embolism, intra-partum haemorrhage, hypertension, and pregnancy-related sepsis) and indirect causes (e.g. pre-existing medical conditions and HIV-related maternal deaths) [4]. Neonatal health (e.g., stillbirths and neonatal morbidities or deaths) is closely related to maternal health and remains a major health problem, particularly in developing countries [5].

The traditional explanation for the uniquely precarious birth process of modern humans compared with that of other mammals is the obstetrical dilemma hypothesis [6]. It describes an evolutionary compromise between the selection pressures for giving birth to a large-brained foetus and our pelvic adaptations for walking upright, which led to a shortened hipbone compared with that of our common ancestor with chimpanzees and bonobos. However, many other explanations have been suggested, and the obstetrical dilemma hypothesis remains debated [7–11]. In general, many factors determine whether a birth is complicated. On the infant's side, factors that can affect delivery include neonatal weight, length, head circumference, position, and

Prof. Dr phil. Kaspar Staub
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kaspar.staub[at]iem.uzh.ch
gestational age [9, 12]. For example, it is well documented that an infant's birth weight is associated with gestational age and the mother's height and body shape: taller women and those with obesity generally give birth to larger, heavier infants [13–17]. Pelvic dimensions are also major maternal factors that influence the birth process [13, 15–17]. However, the relationship between maternal height and pelvic size is complex. Short women can have large pelvises [18, 19]. In particular, a potential mismatch between the foetus's and the mother's body dimensions in the form of cephalopelvic disproportion is relevant to the course of birth [20]. Depending on geographical region and its exact definition, cephalopelvic disproportion is estimated to affect between 1% and 8% of women giving birth each year [20]. It is more common in heavier neonates (>4000 g) and even more so in infants with larger head sizes [21, 22].

These factors, among others, cause obstructed labour and other birth complications such as shoulder dystocia, and they prompt hospital obstetricians to perform medical interventions such as episiotomy (i.e., a surgical incision of the perineum and the posterior vaginal wall) or caesarean sections to minimise maternal and neonatal risks [23]. According to the Swiss Federal Statistical Office, in 2017, 32.3% of all births in Switzerland were caesarean sections (51.1% planned and 49.9% emergency caesarean sections). Vaginal operative deliveries (mainly using a vacuum cup) were performed in 11.1% of all births. Episiotomies were performed in 17% of all vaginal births, mainly in cases of instrumental births [24]. In caesarean sections, obstructed labour due to maternal pelvic abnormalities was one of the most important reasons (this diagnosis was 72.6 times more common in caesarean sections than in vaginal deliveries) [25].

However, obstetric practice has changed significantly over the past 100 years [26, 27]. At the beginning of the 20th century, fewer than 1% of all births at the Maternity Hospital in Lausanne were caesarean sections, but other interventions were much more common. An important determinant for these interventions was a tight and small pelvis (at the Maternity Hospital in Basel, 9.3% of births between 1895 and 1907 were assessed by contemporary physicians as involving a narrow pelvis) [28]. As late as the mid-20th century, external dimensions of the pelvis were used as indicators of internal dimensions and size of the birth canal, with relatively good agreement [29–31]. A century ago, mean maternal skeletal dimensions, such as stature, were different from today's standards. In Switzerland at the beginning of the 20th century, people were 10–15 cm shorter on average than today. Apart from the lower standard of living, this was due to widespread iodine deficiency and rickets [32–36]. In addition, undernutrition was more common than overnutrition. Whether the body dimensions of infants were also smaller during the late 19th and the first half of the 20th century is unclear in the literature [36–39].

Before the rise in living standards in the 20th century, conditions of scarcity were relatively common in countries that are now considered developed [40]. For some newly developing countries and regions, malnutrition and conditions such as rickets and iodine deficiency remain a problem. In addition, optimal obstetric care is not always available within a reasonable timeframe, especially in remote areas. For settings where caesarean sections are performed

only in exceptional emergencies, the knowledge of risk factors related to maternal and infant size disparities is helpful. Historical data from developed countries can provide valuable information. However, few contemporary studies have used this information, despite rich data in European maternity hospital archives from the early 20th century. In this study, we digitised and analysed extensive, nearly complete information on 2500 births collected in the early 1920s in the maternity hospitals of Lausanne and Basel. These two sites were chosen for their wealth of data. We addressed the following research questions: How common were obstetric interventions such as caesarean sections, episiotomies, and forceps deliveries? Was the mismatch between the mother's body size and the foetus's body size a relevant risk factor for such interventions and for the duration of the expulsion phase during delivery (as a proxy for a complicated birth)? We approached these questions through the lens of historical epidemiology and evolutionary medicine using quantitative methods rather than classical approaches in medical history. Therefore, a comprehensive qualitative text analysis of obstetric textbooks is outside the scope of this paper.

## Data and methods

### Historical context of the data

The early 1920s marked a transitional phase after the crisis years at the end of the First World War and the 1918–19 influenza pandemic (“Spanish flu”). Switzerland was not directly involved in WWI but was affected by major economic disruptions. Although the socioeconomic conditions during the final years of the war (1917 and 1918) were not severe enough to cause famine (as in Russia), adverse effects on nutritional status in general and neonatal health were evident. The 1918–19 influenza pandemic likely exacerbated these effects [14, 38, 41]. In a longer-term context, Switzerland was already one of the wealthiest countries in Europe in terms of gross domestic product (GDP) at the beginning of the 20th century [42]. This article focuses on two medium-to-large cities in southwest and northwest Switzerland: French-speaking Lausanne (70,000 inhabitants in 1925) and German-speaking Basel (145,000 inhabitants in 1925). Other indicators of the standard of living also showed an upward trend during this period: overall mortality rates, particularly infant and child mortality, declined. Life expectancy increased, and the health burden due to infectious diseases declined [42–45]. Using average height as an indicator of the standard of living, Switzerland approximately corresponded to the central European average at the beginning of the 20th century. Comparable sources for this paper present data from women born between 1890 and 1899 with an average height of 158–162 cm [33].

### The maternity hospitals in Lausanne and Basel

This study takes advantage of the fact that all births in large Swiss maternity hospitals were carefully documented and preserved in the early 20th century. At that time, Switzerland had only a handful of maternity hospitals. The hospitals in Lausanne and Basel, the two with the most data, were included. In both cities, the cantonal maternity hospitals were the only maternity hospitals in the city. Both hos-
pitals' birth registers include births to women from the up-
per and lower socioeconomic classes and both complicated
and uncomplicated births.

The cantonal hospital of Lausanne became a university
hospital with the opening of the medical faculty of the
University of Lausanne in 1890 [46–50]. Since the 1890s,
there have been no specific restrictions on admissions [51].
Over the years, an increasing proportion of all births in the
city took place in this hospital. Most of these births were
to parents from the city and its immediate surroundings. A
comparison of the number of births in the registers with the
official birth statistics shows that in 1910, 37% of all births
in the city of Lausanne took place in this hospital, and in
1920, the proportion increased to 66% [52]. In Basel, the
Chair of Gynaecology and Obstetrics was established at
the university in 1887. Most patients (>85%) were resi-
dents of the city of Basel. Around 1920, 60% of all births
in Basel took place at the university hospital [14].

This study combines two similar datasets from identical
archival sources to address the research questions. For the
Lausanne dataset, individual data were transcribed from
the birth records of the Canton of Vaud Maternity Hospital
(Archives cantonales vaudoises, K VIII e 256-262, 1922).
This series of archives covers full calendar years. In the
books, each birth record extends over four pages and con-
tains much precise information about the mother, the in-
fant, and the birth itself. A total of 1145 cases were used
from the archive books in 1922 (excluding non-birth-re-
lated cases, miscarriages, and multiple births). Individual
data from Basel were extracted from the birth records of
the Canton of Basel City University Maternity Hospital
(kept at the State Archives Basel City, Sanität X29), where
births have been recorded in detail since 1896. The Basel
archive series covers about one-third of each calendar year
(3-4 months). An individual birth record extends over five
pages and contains detailed information on the mother, the
birth, and the infant. Incomplete records are scarce [38].
Data from three years for Basel were combined to approxi-
mate the size of the dataset from Lausanne: 1921 (covering
August to December, n = 510), 1922 (January to March, n
= 423), and 1923 (May to July, n = 474). In total, the Basel
dataset contained 1407 births.

The demographic data included the mother's date of birth,
place of residence, occupation, marital status, age, height
(cm), general and skeletal condition (signs of rickets or
not), waist circumference just before delivery (cm), and
age at menarche. Obstetric measurements (all in cm) in-
cluded the interspinous distance (the distance between the
two anterior superior iliac spines), the intercristal distance
(the widest distance between the two iliac cristae), and
the conjugata externa (the distance from the upper edge
of the symphysis to the processus spinosus of the fifth
lumbar vertebra) (appendix figure S1). Solid evidence in-
dicates that external pelvic measurements correlate well
with internal measurements [53, 54]. Parity and date of last
menstruation were also recorded. Maternal mortality was
recorded, as well as the number of obstetric interventions
performed (caesarean section, episiotomy, forceps deliv-
ery, and extraction). Because forceps deliveries and cae-
sarean sections were relatively uncommon, these two inter-
ventions were classified together as the next stage of inter-
vention after episiotomy. During birth, the dilation, expul-

sion, and postpartum phases were recorded for each birth.
The two most common vertex presentations that are gener-
ally associated with the least risk were categorised as nor-
mal. These are the left occipito-anterior (LOA) and right
occipito-anterior (ROA) positions, which were recorded in
Lausanne with the French terms OIGA (Occipito-lliaque
Gauche Antérieure) and OIDA (Occipito-lliaque Droite
Antérieure), respectively, and in Basel with the German
terms "erste vordere Hinterhauptslage" (HHL I) and
"zweite vordere Hinterhauptslage" (HHL II), respectively.
All other head positions and foetal presentations were clas-
sified as abnormal. For the infant, the vital status at birth
and in the first days after birth (early neonatal mortality),
date of birth, gestational age in weeks, and sex were
recorded. Anthropometric data included birthweight, head
circumference, length, placental weight and size, and post-
natal weight after several days during the hospital stay (in-
fant weight loss).

Ethics statement

This study was approved by the Cantonal Ethics Commit-
tee of the Canton of Zurich (BASEC number 2021-00628).
Approval meant that informed consent was not required,
as the study was based on historical data from the 1920s.
Data collection was performed between 01.07.2021 and
31.07.2024. In the archives, the study team had access
to non-anonymised personal information in the historical
medical records, but in agreement with the ethics commit-
tee, the data were fully anonymised in the course of the
study.

Statistical methods

Logistic regression models were used to estimate the risk
of episiotomy (yes or no) or caesarean section/forceps de-
ivery (yes or no) in the presence of several explanatory
variables. For episiotomy, the following explanatory vari-
ables were included: sex, parity, head position, maternal
height, birthweight, the ratio of the conjugata externa to
head circumference (3 groups: normal; large vs small [3rd
tercile conjugata externa vs 1st tercile head circumference],
and small vs large [1st tercile conjugata externa vs 3rd ter-
cile head circumference]), and the duration of the expul-
sion phase (3 groups: terciles). Because of the low number
of females who underwent caesarean section or forceps de-
livery (Lausanne: n = 60, Basel: n = 35), the model only
included sex, parity, head position, head circumference
(continuous in cm), and conjugata externa (continuous in
cm) as explanatory variables. To make the expulsion phase
comparable in both data sets, the duration of the phase
was z-transformed and modelled using a linear regres-
sion model, including sex, parity, head position, maternal
height, birth weight, and the ratio of the conjugata externa
to head circumference as explanatory variables. Because
maternal height and pelvic breadth measurements (crests)
are strongly correlated, we only used maternal height as
an explanatory variable in the model for the episiotomy
and expulsion phases. However, a sensitivity analysis with
crests is shown in the supplementary material. In addition,
a sensitivity analysis was performed for these two models
(the number of births for caesarean section/forceps was too
low), including only primiparous women. Because of the
multicollinearity between gestational age and head circum-
ference, gestational age was only controlled for in sensi-
tivity analyses (a univariable analysis including gestation-
al age is shown in the supplementary material). For the
Lausanne dataset, additional information was available on
the maternal body morphology (normal, thin, or obese) and
whether the mother had rickets; for Basel, additional infor-
mation included socioeconomic position (SEP) based on
the partner's occupation. Univariable analyses were per-
formed for these additional variables. Model assumptions
regarding multicollinearity, homoscedasticity, and inde-
pendence were fulfilled for all models. The assumption
of normally distributed residuals was not completely ful-
filled for the dependent variable "expulsion time", but ev-
idence shows that Gaussian models are robust even when
this assumption is violated [55]. The sample size is rela-
tively large; in addition, the predictors are relatively nor-
mally distributed or only slightly skewed, so the results are
assumed to be robust (appendix figure S2).

All statistical analyses were performed using R version
4.3.2.

Results

Data from 1407 births in Basel and 1145 births in Lausanne between 1921 and 1923 were included in the analysis. Episiotomy was performed in 16.6% of births in Basel and 8.6% of births in Lausanne (8.0% difference, 95% confidence interval (CI) 5.4 to 10.6, p <0.001) (table 1). In Basel, however, forceps delivery was performed in 1.2% of the births, compared with 4.7% in Lausanne (3.5% difference, 95% CI 2.1 to 4.9, p <0.001). In Basel, 19 caesarean sections were performed, and in Lausanne, 6 were performed (1.4% vs 0.5% of all births, difference not significant). The foetal head position was normal in over 90% of births (the difference between Basel and Lausanne was not significant). In Basel, the mothers were slightly older on average than in Lausanne (28.7 years vs 28.0 years, p = 0.003). They were marginally taller (158.0 cm vs 156.5 cm, p <0.001) and had a slightly larger conjugata externa (19.9 cm vs 19.6 cm, p <0.001). Their infants were slightly heavier (3282.0 g vs 3205.9 g, p <0.001) with a larger head circumference (34.7 cm vs 34.5 cm, p = 0.001). The mean expulsion phase was longer in Basel than in Lausanne (52.2 min vs 33.1 min, p <0.001), and there were more first births in Basel than in Lausanne (51.7% vs 36.9%, p <0.001). By contrast, no significant difference was observed in the rate of premature births (<37 weeks), number of stillbirths, the proportion of female neonates, or the mean intercristal distance. The distribution plots in figure S2 show that most continuous body dimensions tended towards symmetry.

Regarding the duration of the expulsion phase (figure 1), a
very large infant head circumference in combination with a
small maternal conjugata externa led to a significantly pro-
longed expulsion phase (z = 0.37 [95% CI 0.12–0.62] for
Basel and z = 0.29 [95% CI 0.06–0.52] for Lausanne, ex-
pressed in z-values). Of the other co-factors, a higher par-
ity led to a significantly shorter expulsion phase, and an
abnormal foetal position led to a considerably longer ex-
pulsion phase in Basel and Lausanne. These factors were
significant in both the univariable and multivariable mod-
els. The significant association between the ratio of the
conjugata externa to head circumference remained when

the model was reduced to first births, when the maternal in-
tercristal distance was included in the model instead of ma-
ternal height, and when the model was additionally adjust-
ed for SEP in Basel and for the health or rickets status of
the mother in Lausanne (appendix figures S3A, S4A, S5A,
S6A, and S7A).

The risk of performing an episiotomy was lower for female infants (significant in Lausanne) and with increased parity (figure 2). A large head circumference combined with a small conjugata externa significantly increased the risk of episiotomy in Basel (odds ratio (OR) 2.03, 95% CI 1.04–3.80), and the trend was the same but not significant in Lausanne (OR 1.35, 95% CI 0.58–2.91). When the expulsion phase was particularly long (3rd tercile), the risk of an episiotomy was also higher. The effect of the pelvis-to-head circumference ratio became somewhat less pronounced when the model was reduced to first births, when the intercristal distance was used in the model instead of maternal height, and when the model was additionally adjusted for SEP in Basel and for the health status of the mother in Lausanne in the sensitivity analyses (appendix figures S3B, S4B, S5B, S6B, and S7B).

An abnormal foetal position and a higher head circumfer-
ence were associated with forceps use or caesarean sec-
tion in the simplified models (not fully adjusted for all co-
factors) (figure 3). By contrast, the risk was lower with a
longer conjugata externa and a higher parity. In general,
physician-recorded maternal rickets was not associated
with the duration of the expulsion phase or with episioto-
my, but it was associated with a higher risk of forceps
use or caesarean section (OR 6.98, 95% CI 2.44–17.5).
However, overall maternal health status and maternal body
shape (thin or obese), as assessed by a physician, did not
have a significant effect in any model in Lausanne (appen-
dix figures S5C, S6C, and S7C).

Discussion

Using historical data sets from the 1920s from Basel and
Lausanne, which each had only one maternity hospital, we
showed that in over 90% of births, the position of the foetal
head was either right occiput anterior or left occiput ante-
rior (i.e., considered normal); episiotomy was performed
in 8–17% of births and forceps delivery was performed
in 1–5%, while caesarean sections were rarely performed
(<1% of all births). Regarding the primary exposure vari-
able, a large foetal head diameter and a short conjuga-
ta externa (as an indicator of an anteroposteriorly narrow
pelvis), either alone or in combination with each other,
tended to prolong the expulsion phase and increase the risk
of intervention. Abnormal head position and first births
were also associated with prolonged expulsion phase and
increased intervention risk. Rickets (noted by physicians in
2% of Lausanne mothers) increased the risk of forceps de-
livery or caesarean section.

We are unaware of similar modern studies that have
analysed comparable historical datasets from maternity
hospitals, so we cannot compare our results with other
studies of historical data. While traditional external pelvic
measurements such as interspinous, intercristal, and conju-
gata externa provide valuable insights into pelvic dimen-
sions, their routine use has declined with the advent of
advanced imaging technologies. These modern methods,
<table><caption>**Table 1:**
Summary of the two samples from Lausanne and Basel for outcomes/interventions and all co-factors, continuous variables (including individual body measurements and ratios), and categorical variables. SD: Standard deviation; CI: Confidence interval.</caption><thead><tr><th rowspan="2"></th><th rowspan="2"></th><th colspan="2">Basel</th><th colspan="2">Lausanne</th><th colspan="3">Difference (Basel vs Lausanne)</th></tr><tr><th>n/value</th><th>%</th><th>n/value</th><th>%</th><th>Difference</th><th>95% CI</th><th>p</th></tr></thead><tbody><tr><td rowspan="3">Year</td><td>1921</td><td>510</td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>1922</td><td>423</td><td></td><td>1145</td><td></td><td></td><td></td><td></td></tr><tr><td>1923</td><td>474</td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td></td><td>Total</td><td>1407</td><td></td><td>1145</td><td></td><td></td><td></td><td></td></tr><tr><td rowspan="3">Episiotomy</td><td>No</td><td>1174</td><td>83.4</td><td>1047</td><td>91.4</td><td></td><td></td><td></td></tr><tr><td>Yes</td><td>233</td><td>16.6</td><td>98</td><td>8.6</td><td>8.0</td><td>5.4 to 10.6</td><td>p &lt;0.001</td></tr><tr><td>Missing</td><td>0</td><td>0.0</td><td>0</td><td>0.0</td><td></td><td></td><td></td></tr><tr><td></td><td>Total</td><td>1407</td><td>100.0</td><td>1145</td><td>100.0</td><td></td><td></td><td></td></tr><tr><td rowspan="3">Forceps</td><td>No</td><td>1390</td><td>98.8</td><td>1091</td><td>95.3</td><td></td><td></td><td></td></tr><tr><td>Yes</td><td>17</td><td>1.2</td><td>54</td><td>4.7</td><td>-3.5</td><td>2.1 to 4.9</td><td>p &lt;0.001</td></tr><tr><td>Missing</td><td>0</td><td>0.0</td><td>0</td><td>0.0</td><td></td><td></td><td></td></tr><tr><td></td><td>Total</td><td>1407</td><td>100.0</td><td>1145</td><td>100.0</td><td></td><td></td><td></td></tr><tr><td rowspan="3">Caesarean section</td><td>No</td><td>1388</td><td>98.6</td><td>1139</td><td>99.5</td><td></td><td></td><td></td></tr><tr><td>Yes</td><td>19</td><td>1.4</td><td>6</td><td>0.5</td><td>0.8</td><td>0.0 to 1.6</td><td>p = 0.056</td></tr><tr><td>Missing</td><td>0</td><td>0.0</td><td>0</td><td>0.0</td><td></td><td></td><td></td></tr><tr><td></td><td>Total</td><td>1407</td><td>100.0</td><td>1145</td><td>100.0</td><td></td><td></td><td></td></tr><tr><td rowspan="3">Foetal position</td><td>Abnormal</td><td>117</td><td>8.3</td><td>83</td><td>7.2</td><td>1.1</td><td>-1.1 to 3.2</td><td>p = 0.356</td></tr><tr><td>Normal</td><td>1290</td><td>91.7</td><td>1062</td><td>92.8</td><td></td><td></td><td></td></tr><tr><td>Missing</td><td>0</td><td>0.0</td><td>0</td><td>0.0</td><td></td><td></td><td></td></tr><tr><td></td><td>Total</td><td>1407</td><td>100.0</td><td>1145</td><td>100.0</td><td></td><td></td><td></td></tr><tr><td rowspan="4">Maternal height (cm)</td><td>n</td><td>949</td><td></td><td>1102</td><td></td><td></td><td></td><td></td></tr><tr><td>Mean</td><td>158.0</td><td></td><td>156.5</td><td></td><td>1.5</td><td>0.9 to 2.1</td><td>p &lt;0.001</td></tr><tr><td>SD</td><td>6.3</td><td></td><td>6.5</td><td></td><td></td><td></td><td></td></tr><tr><td>Missing</td><td>458</td><td>32.6</td><td>43</td><td>3.8</td><td></td><td></td><td></td></tr><tr><td rowspan="4">Sex of neonate</td><td>Female</td><td>690</td><td>49.0</td><td>580</td><td>50.7</td><td>-1.6</td><td>-5.6 to 2.3</td><td>p = 0.440</td></tr><tr><td>Male</td><td>712</td><td>50.6</td><td>555</td><td>48.5</td><td></td><td></td><td></td></tr><tr><td>Missing</td><td>5</td><td>0.4</td><td>10</td><td>0.9</td><td></td><td></td><td></td></tr><tr><td>Total</td><td>1407</td><td>100.0</td><td>1145</td><td>100.0</td><td></td><td></td><td></td></tr><tr><td rowspan="4">Stillbirth</td><td>No</td><td>1343</td><td>95.5</td><td>1107</td><td>96.7</td><td></td><td></td><td></td></tr><tr><td>Yes</td><td>61</td><td>4.3</td><td>35</td><td>3.1</td><td>1.3</td><td>-0.3 to 2.8</td><td>p = 0.113</td></tr><tr><td>Missing</td><td>3</td><td>0.2</td><td>3</td><td>0.3</td><td></td><td></td><td></td></tr><tr><td>Total</td><td>1407</td><td>100.0</td><td>1145</td><td>100.0</td><td></td><td></td><td></td></tr><tr><td rowspan="4">Birthweight (g)</td><td>n</td><td>1399</td><td></td><td>1139</td><td></td><td></td><td></td><td></td></tr><tr><td>Mean</td><td>3282.0</td><td></td><td>3205.9</td><td></td><td>76.2</td><td>33.2 to 119.0</td><td>p &lt;0.001</td></tr><tr><td>SD</td><td>551.4</td><td></td><td>544.3</td><td></td><td></td><td></td><td></td></tr><tr><td>Missing</td><td>8</td><td>0.6</td><td>6</td><td>0.5</td><td></td><td></td><td></td></tr><tr><td rowspan="4">Head circumference (cm)</td><td>n</td><td>1365</td><td></td><td>1114</td><td></td><td></td><td></td><td></td></tr><tr><td>Mean</td><td>34.7</td><td></td><td>34.5</td><td></td><td>0.2</td><td>0.1 to 0.3</td><td>p = 0.001</td></tr><tr><td>SD</td><td>1.6</td><td></td><td>1.5</td><td></td><td></td><td></td><td></td></tr><tr><td>Missing</td><td>42</td><td>3</td><td>31</td><td>2.7</td><td></td><td></td><td></td></tr><tr><td rowspan="4">Maternal age (years)</td><td>n</td><td>1407</td><td></td><td>1133</td><td></td><td></td><td></td><td></td></tr><tr><td>Mean</td><td>28.7</td><td></td><td>28.0</td><td></td><td>0.7</td><td>0.2 to 1.6</td><td>p = 0.003</td></tr><tr><td>SD</td><td>5.8</td><td></td><td>5.9</td><td></td><td></td><td></td><td></td></tr><tr><td>Missing</td><td>0</td><td>0</td><td>12</td><td>1</td><td></td><td></td><td></td></tr><tr><td rowspan="4">Intercristal distance (cm)</td><td>n</td><td>1237</td><td></td><td>1120</td><td></td><td></td><td></td><td></td></tr><tr><td>Mean</td><td>28.5</td><td></td><td>28.6</td><td></td><td>-0.1</td><td>-0.2 to 0.1</td><td>p = 0.118</td></tr><tr><td>SD</td><td>1.5</td><td></td><td>1.6</td><td></td><td></td><td></td><td></td></tr><tr><td>Missing</td><td>170</td><td>12.1</td><td>25</td><td>2.2</td><td></td><td></td><td></td></tr><tr><td rowspan="4">Conjugata externa (cm)</td><td>n</td><td>1231</td><td></td><td>1056</td><td></td><td></td><td></td><td></td></tr><tr><td>Mean</td><td>19.9</td><td></td><td>19.6</td><td></td><td>0.3</td><td>0.2 to 0.4</td><td>p &lt;0.001</td></tr><tr><td>SD</td><td>1.3</td><td></td><td>1.6</td><td></td><td></td><td></td><td></td></tr><tr><td>Missing</td><td>176</td><td>12.5</td><td>89</td><td>7.8</td><td></td><td></td><td></td></tr><tr><td rowspan="4">Duration of expulsion phase (min)</td><td>n</td><td>1348</td><td></td><td>1073</td><td></td><td></td><td></td><td></td></tr><tr><td>Mean</td><td>52.2</td><td></td><td>33.1</td><td></td><td>19.0</td><td>14.2 to 24.0</td><td>p &lt;0.001</td></tr><tr><td>SD</td><td>71.8</td><td></td><td>44.1</td><td></td><td></td><td></td><td></td></tr><tr><td>Missing</td><td>59</td><td>4.2</td><td>72</td><td>6.3</td><td></td><td></td><td></td></tr><tr><td rowspan="3">Gestational age (weeks)</td><td>n</td><td>1194</td><td></td><td>1141</td><td></td><td></td><td></td><td></td></tr><tr><td>Mean</td><td>39.8</td><td></td><td>40.1</td><td></td><td>-0.2</td><td>-0.5 to -0.1</td><td>p &lt;0.001</td></tr><tr><td>SD</td><td>2.5</td><td></td><td>2.7</td><td></td><td></td><td></td><td></td></tr></tbody></table>
<table><tbody><tr><td rowspan="5">Gestational age categories (weeks)</td><td>Missing</td><td>213</td><td>15.1</td><td>4</td><td>0.3</td><td></td><td></td><td></td></tr><tr><td>&lt;37</td><td>83</td><td>5.9</td><td>74</td><td>6.5</td><td>-0.6</td><td>-2.5 to 1.4</td><td>p = 0.612</td></tr><tr><td>37 to 41</td><td>795</td><td>56.5</td><td>709</td><td>61.9</td><td></td><td></td><td></td></tr><tr><td>≥41</td><td>315</td><td>22.4</td><td>358</td><td>31.3</td><td></td><td></td><td></td></tr><tr><td>Missing</td><td>214</td><td>15.2</td><td>4</td><td>0.3</td><td></td><td></td><td></td></tr><tr><td></td><td>Total</td><td>1407</td><td>100.0</td><td>1145</td><td>100.0</td><td></td><td></td><td></td></tr><tr><td rowspan="5">Parity</td><td>1</td><td>727</td><td>51.7</td><td>423</td><td>36.9</td><td>14.7</td><td>10.8 to 18.6</td><td>p &lt;0.001</td></tr><tr><td>2</td><td>358</td><td>25.4</td><td>279</td><td>24.4</td><td></td><td></td><td></td></tr><tr><td>≥3</td><td>322</td><td>22.9</td><td>421</td><td>36.8</td><td></td><td></td><td></td></tr><tr><td>Missing</td><td>0</td><td>0.0</td><td>22</td><td>1.9</td><td></td><td></td><td></td></tr><tr><td>Total</td><td>1407</td><td>100.0</td><td>1145</td><td>100.0</td><td></td><td></td><td></td></tr><tr><td rowspan="5">Maternal socioeconomic position background</td><td>Low</td><td>331</td><td>23.5</td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Medium</td><td>728</td><td>51.7</td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>High</td><td>318</td><td>22.6</td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Housewives</td><td>21</td><td>1.5</td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Missing</td><td>9</td><td>0.6</td><td></td><td></td><td></td><td></td><td></td></tr><tr><td rowspan="4">Maternal obesity</td><td>Yes</td><td></td><td></td><td>41</td><td>3.6</td><td></td><td></td><td></td></tr><tr><td>No</td><td></td><td></td><td>1081</td><td>94.4</td><td></td><td></td><td></td></tr><tr><td>Missing</td><td></td><td></td><td>23</td><td>2.0</td><td></td><td></td><td></td></tr><tr><td>Total</td><td></td><td></td><td>1145</td><td>100.0</td><td></td><td></td><td></td></tr><tr><td rowspan="4">Maternal undernutrition</td><td>Yes</td><td></td><td></td><td>23</td><td>2.0</td><td></td><td></td><td></td></tr><tr><td>No</td><td></td><td></td><td>1099</td><td>96.0</td><td></td><td></td><td></td></tr><tr><td>Missing</td><td></td><td></td><td>23</td><td>2.0</td><td></td><td></td><td></td></tr><tr><td>Total</td><td></td><td></td><td>1145</td><td>100.0</td><td></td><td></td><td></td></tr><tr><td rowspan="4">Maternal goitre</td><td>Yes</td><td></td><td></td><td>47</td><td>4.1</td><td></td><td></td><td></td></tr><tr><td>No</td><td></td><td></td><td>1075</td><td>93.9</td><td></td><td></td><td></td></tr><tr><td>Missing</td><td></td><td></td><td>23</td><td>2.0</td><td></td><td></td><td></td></tr><tr><td>Total</td><td></td><td></td><td>1145</td><td>100.0</td><td></td><td></td><td></td></tr><tr><td rowspan="4">Maternal rickets</td><td>Yes</td><td></td><td></td><td>23</td><td>2.0</td><td></td><td></td><td></td></tr><tr><td>No</td><td></td><td></td><td>1122</td><td>98.0</td><td></td><td></td><td></td></tr><tr><td>Missing</td><td></td><td></td><td>23</td><td>2.0</td><td></td><td></td><td></td></tr><tr><td>Total</td><td></td><td></td><td>1145</td><td>100.0</td><td></td><td></td><td></td></tr></tbody></table>

particularly MRI pelvimetry, offer more accurate and detailed assessments, improving the prediction of labour outcomes and management of childbirth. However, despite their superior precision, advanced imaging techniques are mainly reserved for specific circumstances due to their availability and cost, such as in cases of breech or twin pregnancies. Moreover, most pelvimetric studies have concluded that the sensitivity of such simple linear dimensions to predict the risk of dystocia in births with cephalic presentations was too low to be clinically relevant [56, 57].

However, traditional clinical pelvimetry remains vital in settings where advanced imaging is inaccessible [54]. At the population level, studies have suggested that clinical pelvimetry can offer valuable predictive information, especially when combined with other maternal and foetal factors. Moreover, the transition from clinical to imaging-based pelvimetry reflects broader trends in obstetric practice, where technological advancements continually reshape clinical decision-making. These developments underscore the importance of integrating both traditional and

<figure><img src="image_3.png" /><figcaption>**Figure 1:** Expulsion time coefficients and 95% confidence intervals (CIs) from the linear regression model. All explanatory variables were mutually adjusted. The models were performed separately for Lausanne and Basel. To make the expulsion phase comparable between Basel and Lausanne, the expulsion time was z-transformed. "Conjug. Ext vs Head circum" shows the ratio of the conjugata externa to head circumference (3 groups: normal; large vs small [3rd tercile conjugata externa vs 1st tercile head circumference]; and small vs large [1st tercile conjugata externa vs 3rd tercile head circumference]).</figcaption></figure>
modern approaches to optimise maternal and foetal outcomes [53].

Our study has several limitations. First, sample selection bias may have affected the two datasets. Although around two-thirds of all births in the two cities occurred at these hospitals at the beginning of the 1920s, it is unclear whether our results are generalisable to the remaining home births. Interventions and abnormal births may have been more common among hospital births than among all births. Second, medical interventions during labour are often stepwise when complications arise. Although the birth registers analysed may allow a precise reconstruction of all birth sequences and the reasons behind interventions, this detailed analysis was not possible for our dataset of around 2500 births due to time and effort constraints. More in-depth medical-historical analyses should be conducted. Third, the elasticity of the soft tissue plays a major role in the processes under consideration, in addition to the bony shape of the maternal pelvis. Unfortunately, we were unable to include these soft tissue factors in our analysis. In addition, maternal body mass index and weight gain during pregnancy, which might affect the weight of the infant, as well as any pathological process, were not available. Fourth, it is immediately apparent from examining the birth registers that both hospitals worked according to precise internal and obstetric guidelines. Unfortunately, despite intensive archive research, these guidelines could not

be reconstructed. The two hospitals may have measured and documented the variables of interest differently, which could explain specific differences observed in our data. Obstetric textbooks and literature from this period should be consulted in a more in-depth medical-historical analysis to gain a better understanding of the use of these interventions. Finally, the observed differences may also reflect differences in patient populations between French-speaking southern Switzerland and German-speaking northern Switzerland, with potentially varying socioeconomic and cultural differences.

## Conclusion

Our study provides insights into the health situation and obstetric practice over 100 years ago, when obstetric processes were precisely documented in the maternity hospitals. At that time, maternal body shape and health differed considerably due to living conditions, and modern obstetric methods were not yet widely used. Under these conditions, the mismatch between maternal body shape and the foetus was an important factor in complicated births.

## Data sharing statement

The data are available in a public, open-access repository at https://doi.org/10.5281/zenodo.15576871, and the statis-

<table><caption>**Figure 2:** Episiotomy odds ratios (ORs) and 95% confidence intervals (CIs) from the logistic regression model. All explanatory variables were mutually adjusted. The models were performed separately for Lausanne and Basel. "Conjug. Ext vs Head circum" shows the ratio of the conjugata externa to head circumference (3 groups: normal; large vs small [3rd tercile conjugata externa vs 1st tercile head circumference]; and small vs large [1st tercile conjugata externa vs 3rd tercile head circumference]).</caption><thead><tr><th>Explanatory variable</th><th>Factor</th><th>Lausanne</th><th>Basel</th></tr></thead><tbody><tr><td rowspan="2">Sex</td><td>male</td><td>-</td><td>-</td></tr><tr><td>female</td><td>0.49 (0.30-0.81)</td><td>0.70 (0.47-1.05)</td></tr><tr><td>Parity</td><td>-</td><td>0.70 (0.52-0.88)</td><td>0.52 (0.35-0.72)</td></tr><tr><td rowspan="2">Child position</td><td>normal</td><td>-</td><td>-</td></tr><tr><td>non-normal</td><td>0.29 (0.05-1.02)</td><td>0.81 (0.32-1.82)</td></tr><tr><td>Maternal height in 10cm</td><td>-</td><td>1.32 (0.89-2.00)</td><td>1.30 (0.94-1.82)</td></tr><tr><td>Birthweight in 100gr</td><td>-</td><td>1.02 (0.97-1.08)</td><td>1.03 (0.99-1.08)</td></tr><tr><td rowspan="3">Conjug. Ext vs Head circum.</td><td>normal</td><td>-</td><td>-</td></tr><tr><td>large-small</td><td>0.92 (0.33-2.20)</td><td>0.60 (0.24-1.31)</td></tr><tr><td>small-large</td><td>1.35 (0.58-2.91)</td><td>2.03 (1.04-3.80)</td></tr><tr><td rowspan="3">Expulsion phase</td><td>1st tercile</td><td>-</td><td>-</td></tr><tr><td>2nd tercile</td><td>2.47 (1.13-5.72)</td><td>0.66 (0.34-1.29)</td></tr><tr><td>3rd tercile</td><td>8.06 (3.92-18.0)</td><td>1.63 (0.87-3.09)</td></tr></tbody></table>

<figure><img src="image_4.png" /><figcaption>**Figure 3:** Forceps and caesarean section odds ratios (OR) and 95% confidence intervals (CIs) from the logistic regression model. All explanatory variables were mutually adjusted. The models were performed separately for Lausanne and Basel.</figcaption></figure>

<table><thead><tr><th>Explanatory variable</th><th>Factor</th><th>Lausanne</th><th>Basel</th></tr></thead><tbody><tr><td rowspan="2">Sex</td><td>male</td><td>-</td><td>-</td></tr><tr><td>female</td><td>0.91 (0.49-1.65)</td><td>0.67 (0.31-1.42)</td></tr><tr><td>Parity</td><td>-</td><td>0.60 (0.45-0.77)</td><td>0.98 (0.77-1.17)</td></tr><tr><td rowspan="2">Child position</td><td>normal</td><td>-</td><td>-</td></tr><tr><td>non-normal</td><td>5.75 (2.61-12.0)</td><td>5.62 (2.39-12.4)</td></tr><tr><td>Head circumference in cm</td><td>-</td><td>1.63 (1.30-2.06)</td><td>1.54 (1.23-1.96)</td></tr><tr><td>Conjugata Externa in cm</td><td>-</td><td>0.92 (0.74-1.10)</td><td>0.80 (0.57-1.10)</td></tr></tbody></table>

<figure><img src="image_5.png" /></figure>
tical codes can be found at https://github.com/KaMatthes/
Obstetrical_interventions_1922.

Acknowledgments

The authors would like to thank Lukas Helm, Joël Floris, Kaspar Pohl, Laura Grogg, Nikola Koepke, and Ulrich Woitek for their help in collecting and preparing the data and for previous collaborations. They also express gratitude to the staff of the Basel-Stadt and Vaud State Archives for their help and support.

Financial disclosure

Swiss National Science Foundation (Project-No. 156683, Project-No. 197305 & Project-No. 310030_212984).

Potential competing interests

All authors have completed and submitted the International Committee of Medical Journal Editors form for disclosure of potential conflicts of interest. – *AVI* received grants from Swiss National Science Foundation and support for attending meetings and/or travel from the University of Zurich. – *MH* received grants from Swiss National Science Foundation 310030_212984. – No other potential conflict of interest related to the content of this manuscript was disclosed.

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# Appendix

**Supplementary Figure S1:** The three obstetric measurements recorded in the sources: 1) Interspinous distance (distance between the two anterior superior iliac spines); 2) Intercristal distance (most comprehensive distance between the two iliac cristae); 3) Conjugata externa (distance from the upper edge of the symphysis to the processus spinosus of the fifth lumbar vertebra).

<figure><img src="image_6.png" /></figure>
<figure><img src="image_7.png" /><figcaption>Supplementary Figure S2: Density function of the explanatory variables.</figcaption></figure>
**Supplementary Figure S3:** Sensitivity analysis – adjusted for bassin cretes instead of maternal height. All explanatory variables were mutually adjusted. A) Expulsion time - Coefficient and 95% Confidence Interval (CI) from the linear regression model. B) Episiotomy - Odds ratio (OR) and 95% Confidence Interval (CI) from the logistic regression model.

A) Expulsion time

Bassin Cretes - Expulsion phase in z-values: Coefficient (95% CI)

<table><thead><tr><th>Explanatory variable</th><th>Factor</th><th>Lausanne</th><th>Basel</th></tr></thead><tbody><tr><td rowspan="2">Sex</td><td>male</td><td>-</td><td>-</td></tr><tr><td>female</td><td>-0.06 (-0.18-0.07)</td><td>0.10 (-0.02-0.22)</td></tr><tr><td>Parity</td><td>-</td><td>-0.12 (-0.15-0.09)</td><td>-0.17 (-0.20-0.13)</td></tr><tr><td rowspan="2">Child position</td><td>normal</td><td>-</td><td>-</td></tr><tr><td>non-normal</td><td>0.33 (0.07-0.58)</td><td>0.55 (0.32-0.78)</td></tr><tr><td>Bassin Cretes in cm</td><td>-</td><td>-0.02 (-0.06-0.02)</td><td>-0.01 (-0.05-0.04)</td></tr><tr><td>Birthweight in 100gr</td><td>-</td><td>-0.00 (-0.02-0.01)</td><td>0.02 (0.00-0.03)</td></tr><tr><td rowspan="3">Conjug. Ext. vs Head circum.</td><td>normal</td><td>-</td><td>-</td></tr><tr><td>large-small</td><td>-0.02 (-0.24-0.21)</td><td>-0.07 (-0.28-0.13)</td></tr><tr><td>small-large</td><td>0.33 (0.10-0.55)</td><td>0.49 (0.26-0.71)</td></tr></tbody></table>

<figure><img src="image_8.png" /></figure>

B) Episiotomy

Bassin Cretes - Episiotomy: OR (95% CI)

<table><thead><tr><th>Explanatory variable</th><th>Factor</th><th>Lausanne</th><th>Basel</th></tr></thead><tbody><tr><td rowspan="2">Sex</td><td>male</td><td>-</td><td>-</td></tr><tr><td>female</td><td>0.50 (0.31-0.82)</td><td>0.74 (0.53-1.04)</td></tr><tr><td>Parity</td><td>-</td><td>0.68 (0.51-0.87)</td><td>0.60 (0.45-0.76)</td></tr><tr><td rowspan="2">Child position</td><td>normal</td><td>-</td><td>-</td></tr><tr><td>non-normal</td><td>0.29 (0.05-0.99)</td><td>1.07 (0.51-2.09)</td></tr><tr><td>Bassin Cretes in cm</td><td>-</td><td>0.97 (0.83-1.14)</td><td>0.99 (0.88-1.12)</td></tr><tr><td>Birthweight in 100gr</td><td>-</td><td>1.03 (0.98-1.09)</td><td>1.04 (1.01-1.08)</td></tr><tr><td rowspan="3">Conjug. Ext. vs Head circum.</td><td>normal</td><td>-</td><td>-</td></tr><tr><td>large-small</td><td>1.01 (0.36-2.42)</td><td>0.59 (0.27-1.18)</td></tr><tr><td>small-large</td><td>1.09 (0.47-2.31)</td><td>1.52 (0.86-2.62)</td></tr><tr><td rowspan="3">Expulsion phase</td><td>1st tercile</td><td>-</td><td>-</td></tr><tr><td>2nd tercile</td><td>2.55 (1.18-5.89)</td><td>0.96 (0.56-1.66)</td></tr><tr><td>3rd tercile</td><td>7.92 (3.86-17.6)</td><td>1.79 (1.06-3.07)</td></tr></tbody></table>

<figure><img src="image_9.png" /></figure>
**Supplementary Figure S4:** Sensitivity analysis – only first parity is included. All explanatory variables were mutually adjusted. A) Expulsion time - Coefficient and 95% Confidence Interval (CI) from the linear regression model. B) Episiotomy - Odds ratio (OR) and 95% Confidence Interval (CI) from the logistic regression model.

A) Expulsion phase

<table><caption>Only 1st parity - Expulsion phase in z-values: Coefficient (95% CI)</caption><thead><tr><th>Explanatory variable</th><th>Factor</th><th>Lausanne</th><th>Basel</th></tr></thead><tbody><tr><td rowspan="2">Sex</td><td>male</td><td>-</td><td>-</td></tr><tr><td>female</td><td>-0.15 (-0.41-0.10)</td><td>0.28 (0.06-0.49)</td></tr><tr><td rowspan="2">Child position</td><td>normal</td><td>-</td><td>-</td></tr><tr><td>non-normal</td><td>0.55 (-0.06-1.15)</td><td>1.30 (0.85-1.76)</td></tr><tr><td>Maternal height in 10cm</td><td>-</td><td>0.05 (-0.17-0.28)</td><td>-0.14 (-0.31-0.03)</td></tr><tr><td>Birthweight in 100gr</td><td>-</td><td>-0.02 (-0.05-0.01)</td><td>0.04 (0.01-0.07)</td></tr><tr><td rowspan="3">Conjug. Ext. vs Head circum.</td><td>normal</td><td>-</td><td>-</td></tr><tr><td>large-small</td><td>-0.17 (-0.65-0.30)</td><td>-0.14 (-0.51-0.23)</td></tr><tr><td>small-large</td><td>0.32 (-0.20-0.84)</td><td>0.70 (0.27-1.13)</td></tr></tbody></table>

<figure><img src="image_10.png" /></figure>

B) Episiotomy

<table><caption>Only 1st parity - Episiotomy: OR (95% CI)</caption><thead><tr><th>Explanatory variable</th><th>Factor</th><th>Lausanne</th><th>Basel</th></tr></thead><tbody><tr><td rowspan="2">Sex</td><td>male</td><td>-</td><td>-</td></tr><tr><td>female</td><td>0.38 (0.21-0.68)</td><td>0.71 (0.44-1.13)</td></tr><tr><td rowspan="2">Child position</td><td>normal</td><td>-</td><td>-</td></tr><tr><td>non-normal</td><td>0.21 (0.01-1.14)</td><td>0.90 (0.31-2.26)</td></tr><tr><td>Maternal height in 10cm</td><td>-</td><td>1.04 (0.63-1.72)</td><td>1.35 (0.92-2.02)</td></tr><tr><td>Birthweight in 100gr</td><td>-</td><td>1.04 (0.98-1.12)</td><td>1.03 (0.98-1.09)</td></tr><tr><td rowspan="3">Conjug. Ext. vs Head circum.</td><td>normal</td><td>-</td><td>-</td></tr><tr><td>large-small</td><td>0.89 (0.24-2.62)</td><td>0.68 (0.25-1.61)</td></tr><tr><td>small-large</td><td>1.01 (0.30-2.93)</td><td>2.25 (1.01-4.89)</td></tr><tr><td rowspan="3">Expulsion phase</td><td>1st tercile</td><td>-</td><td>-</td></tr><tr><td>2nd tercile</td><td>1.60 (0.54-5.89)</td><td>1.71 (0.45-11.2)</td></tr><tr><td>3rd tercile</td><td>4.61 (1.73-16.0)</td><td>4.54 (1.31-28.6)</td></tr></tbody></table>

<figure><img src="image_11.png" /></figure>
**Supplementary Figure S5:** Analysis including SEP for Basel and maternal body for Lausanne. A) Expulsion time - Coefficient and 95% Confidence Interval (CI) from the linear regression model. B) Episiotomy - Odds ratio (OR) and 95% Confidence Interval (CI) from the logistic regression model. C) Forceps and caesarean section - Odds ratio (OR) and 95% Confidence Interval (CI) from the logistic regression model.

### A) Expulsion phase

<table><caption>SEP and Maternal body - Expulsion phase in z-values: Coefficient (95% CI)</caption><thead><tr><th>Explanatory variable</th><th>Factor</th><th>Lausanne</th><th>Basel</th></tr></thead><tbody><tr><td rowspan="3">Socioeconomic position</td><td>low</td><td>-</td><td>-</td></tr><tr><td>medium</td><td>-</td><td>-0.13 (-0.26-0.00)</td></tr><tr><td>high</td><td>-</td><td>-0.11 (-0.26-0.05)</td></tr><tr><td rowspan="3">Maternal body</td><td>normal</td><td>-</td><td>-</td></tr><tr><td>thin</td><td>0.32 (-0.10-0.75)</td><td>-</td></tr><tr><td>obese</td><td>0.21 (-0.11-0.53)</td><td>-</td></tr></tbody></table>

<figure><img src="image_12.png" /></figure>

### B) Episiotomy

<table><caption>SEP and Maternal body - Episiotomy: OR (95% CI)</caption><thead><tr><th>Explanatory variable</th><th>Factor</th><th>Lausanne</th><th>Basel</th></tr></thead><tbody><tr><td rowspan="3">Socioeconomic position</td><td>low</td><td>-</td><td>-</td></tr><tr><td>medium</td><td>-</td><td>1.21 (0.84-1.78)</td></tr><tr><td>high</td><td>-</td><td>1.74 (1.15-2.65)</td></tr><tr><td rowspan="3">Maternal body</td><td>normal</td><td>-</td><td>-</td></tr><tr><td>thin</td><td>2.29 (0.65-6.26)</td><td>-</td></tr><tr><td>obese</td><td>0.56 (0.09-1.86)</td><td>-</td></tr></tbody></table>

<figure><img src="image_13.png" /></figure>

### C) Forceps and caesarean section

<table><caption>SEP and Maternal body - Forceps/CS: OR (95% CI)</caption><thead><tr><th>Explanatory variable</th><th>Factor</th><th>Lausanne</th><th>Basel</th></tr></thead><tbody><tr><td rowspan="3">Socioeconomic position</td><td>low</td><td>-</td><td>-</td></tr><tr><td>medium</td><td>-</td><td>0.87 (0.40-2.05)</td></tr><tr><td>high</td><td>-</td><td>1.04 (0.40-2.70)</td></tr><tr><td rowspan="3">Maternal body</td><td>normal</td><td>-</td><td>-</td></tr><tr><td>thin</td><td>0.80 (0.04-3.91)</td><td>-</td></tr><tr><td>obese</td><td>0.90 (0.14-3.04)</td><td>-</td></tr></tbody></table>

<figure><img src="image_14.png" /></figure>
**Supplementary Figure S6:** Analysis including SEP for Basel and rickets for Lausanne. A) Expulsion time - Coefficient and 95% Confidence Interval (CI) from the linear regression model. B) Episiotomy - Odds ratio (OR) and 95% Confidence Interval (CI) from the logistic regression model. C) Forceps and caesarean section - Odds ratio (OR) and 95% Confidence Interval (CI) from the logistic regression model.

A) Expulsion phase

Rickets - Forceps/CS: OR (95% CI)

<table><thead><tr><th>Explanatory variable</th><th>Factor</th><th>Lausanne</th><th>Basel</th></tr></thead><tbody><tr><td rowspan="3">Socioeconomic position</td><td>low</td><td>-</td><td>-</td></tr><tr><td>medium</td><td>-</td><td>0.87 (0.40-2.05)</td></tr><tr><td>high</td><td>-</td><td>1.04 (0.40-2.70)</td></tr><tr><td rowspan="2">Rickets</td><td>no</td><td>-</td><td>-</td></tr><tr><td>yes</td><td>6.98 (2.44-17.5)</td><td>-</td></tr></tbody></table>

<figure><img src="image_15.png" /></figure>

B) Episiotomy

SEP and Rickets - Episiotomy: OR (95% CI)

<table><thead><tr><th>Explanatory variable</th><th>Factor</th><th>Lausanne</th><th>Basel</th></tr></thead><tbody><tr><td rowspan="3">Socioeconomic position</td><td>low</td><td>-</td><td>-</td></tr><tr><td>medium</td><td>-</td><td>1.21 (0.84-1.78)</td></tr><tr><td>high</td><td>-</td><td>1.74 (1.15-2.65)</td></tr><tr><td rowspan="2">Rickets</td><td>no</td><td>-</td><td>-</td></tr><tr><td>yes</td><td>0.48 (0.03-2.32)</td><td>-</td></tr></tbody></table>

<figure><img src="image_16.png" /></figure>

C) Forceps and caesarean section

Rickets - Forceps/CS: OR (95% CI)

<table><thead><tr><th>Explanatory variable</th><th>Factor</th><th>Lausanne</th><th>Basel</th></tr></thead><tbody><tr><td rowspan="3">Socioeconomic position</td><td>low</td><td>-</td><td>-</td></tr><tr><td>medium</td><td>-</td><td>0.87 (0.40-2.05)</td></tr><tr><td>high</td><td>-</td><td>1.04 (0.40-2.70)</td></tr><tr><td rowspan="2">Rickets</td><td>no</td><td>-</td><td>-</td></tr><tr><td>yes</td><td>6.98 (2.44-17.5)</td><td>-</td></tr></tbody></table>

<figure><img src="image_17.png" /></figure>
**Supplementary Figure S7:** Univariable analysis - only gestational age. A) Expulsion time - Coefficient and 95% Confidence Interval (CI) from the linear regression model. B) Episiotomy - Odds ratio (OR) and 95% Confidence Interval (CI) from the logistic regression model. C) Forceps and caesarean section - Odds ratio (OR) and 95% Confidence Interval (CI) from the logistic regression model.

A) Expulsion phase

Only gestational age - Expulsion phase in z-values: Coefficient (95% CI)

<figure><img src="image_18.png" /></figure>

B) Episiotomy

Only gestational age - Episiotomy: OR (95% CI)

<figure><img src="image_19.png" /></figure>

C) Forceps and caesarean section

Only gestational age - Forceps/CS: OR (95% CI)

<figure><img src="image_20.png" /></figure>