Keywords obstetrical interventions - cesarean section rate - robson classification - united
arab emirates - women
Introduction
The crude rate of cesarean section (CS) deliveries is considered an important global
indicator when measuring the access to obstetric care.[1 ] In 1985, the World Health Organization (WHO) stated that there was no justification
for any region to have a CS rate higher than 10 to 15%.[2 ] However, this rate has been increased over the last two decades; especially in middle-
and high-income countries.[3 ] The reason behind increased CS rates is considered multifactorial, with contributions
from both medical factors, such as increase of high-risk pregnancies[4 ] and preterm deliveries[5 ], and psychosocial factors, such as a CS on demand.[6 ]
[7 ]
It is well known that CS carry its own risks for maternal and infant morbidity and
for subsequent pregnancies.[8 ] Therefore, the rise in CS rates is becoming a major public health concern, and the
factors that are causing this phenomenon, as well as the strategies to reduce CS rates,
are intensively analyzed.[9 ]
[10 ] However, to propose and implement effective measures to reduce the CS rates, it
is first essential to identify which groups of women are undergoing CS and to investigate
the underlying reasons in different settings. The Robson 10-group classification system
is one of the best methods that fulfills the current international and institutional
needs to monitor and analyze CS rates.[1 ] Applying the Robson classification to the data should allow the identification of
the subgroup(s) that are predominantly contributing to the steady increase in the
overall CS rate.
The United Arab Emirates (UAE) is a young country with families tending to have large
numbers of children. A recent publication by Tahlak et al showed that the CS rate
has increased in the past 15 years from 1 in every 5 births to 1 in every 3 births.[11 ] New insurance policies have encouraged the private sectors to develop a more sophisticated
management that may be associated with an increase in health care costs.
The increase in multiple pregnancies and in the CS rate has led to an increased rate
of hysterectomy and of other obstetrical complications. Nowadays, it is common for
any obstetrician working in the UAE to come across and manage pregnant women who have
had more than three CSs. The increase of obstetrical complications has resulted in
a burdensome government health system that desires to encourage high birth rates,
but at the same time to decrease birth complications. The purpose of the present study
is to evaluate obstetrics management in governmental tertiary hospitals in Dubai,
UAE. We aim to assess the current obstetrics management in relation to clinical and
maternal and child health outcomes, in order to determine whether the increase in
CS rates is genuinely due to changes in patient epidemiology and in risk factors or
merely due to changes in obstetric management.
Methods
Data Source and Study Variables
Information on all deliveries that occurred in the Dubai Health Authority (DHA) between
January 1st , 2016, until September 30th , 2016, was accessed from delivery registries of hospitals in Latifa and in Dubai.
A well designed questionnaire form was used to collect clinical data and information
on maternal medical conditions, labor and delivery events, neonatal outcomes, and
other maternal characteristics. The maternal characteristics included maternal age,
nationality, parity, and gestational age. Data were also collected for maternal conditions
or diseases, such as diabetes, hypertensive disorders during pregnancy, and history
of previous CS. Upon acquisition, the data was sorted according to the Robson 10-group
classification system.[12 ]
The outcome of the pregnancy was categorized by induction use, and its indication,
augmentation, interventions and rupture of the membrane. Information about the route
of delivery (normal vaginal delivery [NVD], forceps, vacuum, emergency CS, elective
CS), the type of anesthesia used, the condition of the perineum, that is, whether
the delivery was associated with tears or episiotomy, along with its degree, and whether
the patient lost blood and received a blood transfusion, were also included. The following
complications were also documented: antepartum and postpartum hemorrhage, abruption,
placenta previa, shoulder dystocia, cord prolapse, hysterectomy, ruptured uterus,
and tubal ligation. In addition, information was documented about the position of
the fetus and about the status that identified whether the fetus had any anomaly,
scalp injury, or intrauterine growth retardation, or was classified as an intrauterine
death. In addition, it was recorded whether the delivery was performed by an obstetrician
or a midwife. We suggest that changes in the maternal characteristics (e.g., increases
in the maternal age), as well as maternal conditions or diseases (e.g., multifetal
pregnancy) can lead to changes in the obstetric practice (e.g., increases in the induction
rates). Therefore, a sequential model was used to identify the effect of each factor
and of each group of elements. Finally, we have adjusted for fetal or infant characteristics,
including gestational age, small for gestational age, and birth weight.
Outcome Measures and Other Variables
The primary outcome was the intrapartum CS rate. Vaginal instrumental (vacuum or forceps)
birth, pharmacological sedation or analgesia, epidural anesthesia, and augmentation
of labor with oxytocin were secondary outcomes.
Data Analysis and Statistics
All of the collected data were entered into SPSS Statistics for Windows, Version 21.0
(IBM Corp., Armonk, NY, USA) for statistical analysis. Descriptive statistics were
computed for the sociodemographic variables. The overall data was recorded as a percentage
of the total. The differences were determined using the Chi-squared test, and the
statistical significance was recorded for non-parametric data. We fit several multiple
regression models with an α of 0.05 and a power of 80% to better understand the predictability
of obstetrical interventions and outcomes. The potential determinants of primary CS
were categorized into several groups: maternal characteristics, maternal conditions
or diseases, factors related to obstetric practice, and fetal or infant characteristics.
All of the analyses were conducted with the SPSS Statistics for Windows, Version 20.0
(IBM Corp., Armonk, NY, USA). The semipartial correlation in multiple linear regression
was calculated using the Stata Statistical Software: Release 14 (Statacorp, College
Station, TX, USA). The semipartial correlation (semipartial R2 ) in multiple linear regression was calculated using STATA version 14, College Station,
Texas 77845 USA.
Ethics Statement
The present study was approved by the institutional review board of the DHA, Dubai
(DSREC-08/2016_07). The aggregate reporting of data and coding assured to enhance
the confidentiality of information.
Results
A total of 5,461 pregnancies were recorded with a gestational age from 24 to 42 weeks.
[Table 1 ] shows the characteristics of all births/pregnancies. The majority (2,374; 43.5%)
of the women was between 20 and 29 years old, UAE nationals (2,941; 54%), having previous
1 to 4 parities (3,536; 65%), with gestational age of 37 to 41 weeks (4,498; 82%),
and booked with the hospital for regular visits (5,060; 93%). A total of 1,291 (24%)
women had a history of previous CS, of which 78 (2%) had more than 3 previous CSs.
The labor was spontaneous in 2,221 (45%) women, and augmented or induced in 1,634
(33%) ([Table 1 ]).
Table 1
Demographic and clinical characteristics of the mothers, birth indication, and complications
Characteristic
All Women n = 5461 (n; %)
Maternal Age (years old)
< 20 (76; 1.5%)
20–29 (2,361; 43.5%)
30–34 (1,673; 31%)
≥35 (1,300; 24%)
Nationality
UAE national (2,923; 54%)
Non-UAE national (2,504; 46%)
Parity
0 (1,370; 25%)
1–4 (3,516; 65%)
> 4 (535; 10%)
Gestational age (weeks)
24–28 (65; 1%)
28–36 (807; 15%)
37–41 (4,498; 82%)
≥41 (91; 2%)
Diabetes
None (4,345; 79%)
IDDM (80; 2%)
NIDDM (43; 1%)
Gestational (986; 18%)
Hypertension
None (5,092; 94%)
High BP (263; 5%)
Preeclamptic (73; 1%)
Previous CS
None (849; 46.5%)
1 (474; 26%)
2 (273; 15%)
3 (151; 8.3%); > 3 (77; 4.2%)
Booked
Yes (5,060; 93%)
No (401; 7%)
Vaginal birth after cesarean
Yes (261; 6%)
External cephalic version
Yes (28; 0.7%)
Birth indication
NVD (3,422; 63%)
Forceps (12; 0.2%)
Vacuum (170; 3%)
Emergency CS (1,316; 24%)
Elective CS (508; 9%)
Anesthesia
None (3,655; 67%)
Spinal (1,307; 24%)
General (361; 7%)
Epidural (138; 2%)
Perineum
Intact (2,727; 53%)
1° (790; 15%)
2° (484; 9%)
3 or 4° (40; 1%)
Episiotomy (983; 19%)
Multiple tears (24; 0.5%)
Cervical (22; 0.5%)
Para urethral (81; 2%)
Induction
Nil (4,295; 78.6%)
Dinoprostone Vaginal Suppository (930; 17%)
ARM (165; 3%)
Oxytocin (20; 0.4%)
Balloon (53; 1%)
Indication for induction
PRM (119; 22%)
SIUGR (58; 11%)
HTN (31; 6%)
Diabetes (147; 27%)
Fetal distress (67; 13%)
PP (91; 17%)
Blood group isoimmunization/Chorioamnionitis/ Cholestasis (22; 4%)
Re-induction
Yes (45; 3%)
No (1,741; 97%)
Pain relief
Nil (2,395, 44%)
Non-pharma (602; 11%)
Pethidine (1,257; 23%)
Nitrous oxide (508; 9%)
Non-pharma and Entonox (160; 3%)
Pethidine and Entonox (541; 10%)
Ruptured membrane †
Spontaneous (2,490; 58%)
Artificial (1,778; 42%)
Amniotic fluid liquor
Nil (31; 1%)
Clear (3,528; 86%)
Scanty (4; 0.1%)
Meconium (465; 11%)
Blood stained (53; 1%)
Type of labor
Spontaneous (2,221; 45%)
Augmented (788; 16%)
Induced (846; 17%)
No labor (1,067; 22%)
Estimated blood loss†
< 500 ml (3,537; 65%)
500–999 ml (1,586; 29%)
1,000–2,000 ml (284; 5.5%)
> 2,000 ml (24; 0.5%)
Complications†
Antepartum hemorrhage (25; 0.5%)
Postpartum hemorrhage (151; 3%)
Placental abruption (45; 1%)
Placenta previa (47; 1%)
Shoulder dystocia (26; 0.5%)
Cord prolapse (8; 0.2%)
Hysterectomy (5; 0.1%)
Ruptured uterus (3; 0.1%)
Placenta complete†
Yes (5,008; 96%)
No (187; 4%)
Strep B
Yes (782; 14%)
Blood transfusion
Yes (84; 1.5%)
Rh negative
Yes (194; 4%)
Tubal Ligation
Yes (73; 1.3%)
Stem cell collected
Yes (208; 4%)
Abbreviations: ARM, artificial rupture of the membrane; BP, blood pressure; CS, cesarean
section; HTN, hypertension; IDDM, insulin-dependent diabetes mellitus; NIDDM, noninsulin-dependent
diabetes mellitus; NVD, normal vaginal delivery; PP, prolonged pregnancy; PRM, premature
rupture of the membrane; SIUGR, suspected intrauterine growth restriction; UAE, The
United Arab Emirates.
The birth indication rate was: 64% NVD, 24% emergency CS, 9% elective CS, 3% vacuum,
and 0.3% forceps ([Fig. 1 ]). The rate of vaginal birth after previous CS was 261 (6%), of external cephalic
version was 28 (0.7%), and of induction was 1,168 (21.4%). Anesthesia was used in
1,806 (33%) cases. Artificial rupture of the membrane was performed in 1,778 (42%)
of the women, and 522 (12%) of the women had amniotic fluid liquor ([Table 1 ]).
Fig. 1 Types of deliveries are presented in number and percentage.
[Table 2 ] and [Fig. 2 ] show number of CSs and its relative size in each group according to Robson classification.
Multiparous women with previous CS (group 5), women with multiple pregnancies (group
9), and women with a single transverse or oblique lie (group 9), constituted the the
largest groups in our study (p < 0.001).
Fig. 2 Robson 10-group classification system. The deliveries in Blue are normal vaginal
deliveries, and those on orange are number of cesarean sections in each category.
Table 2
Robson 10-group classification system
No. of deliveries
n = 5,461
No. of CSs
1,824; 33%
Robson categories*
Category 1
253; 4.6%
Category 1 with CS
16; 1%
Category 2
122; 2%
Category 2 with CS
49; 3%
Category 3
618; 11%
Category 3 with CS
104; 6%
Category 4
276; 5%
Category 4 with CS
43; 2.4%
Category 5
263; 5%
Category 5 with CS
181; 10%
Category 6
47; 1%
Category 6 with CS
26; 1.4%
Category 7
111; 2%
Category 7 with CS
42; 2%
Category 8
301; 5.5%
Category 8 with CS
179; 9.8%
Category 9
320; 6%
Category 9 with CS
161; 9%
Category 10
218; 4%
Category 10 with CS
133; 7%
Abbreviation: CS, cesarean section.
* The ten categories are:
(1) Primiparous women with a single cephalic pregnancy ≥ 37 weeks of gestation, in
spontaneous labor
(2) Primiparous women with a single cephalic pregnancy, ≥ 37 weeks of gestation, submitted
to induction of labor or to CS prior to the onset of labor
(3) Multiparous women without a previous uterine scar, with a single cephalic pregnancy
≥ 37 weeks of gestation, in spontaneous labor
(4) Multiparous women without a previous uterine scar, with a single cephalic pregnancy
≥ 37 weeks of gestation, submitted to induction of labor or to CS prior to the onset
of labor
(5) Multiparous women with 1 or more previous uterine scar(s) and a single cephalic
pregnancy ≥ 37 weeks of gestation
(6) Primiparous women with a single breech pregnancy
(7) Multiparous women with a single breech pregnancy, with/without previous uterine
scar(s)
(8) Women with multiple pregnancies with/without previous uterine scar(s)
(9) Women with a single pregnancy with a transverse or oblique lie, with/without previous
uterine scar(s)
(10) Women with a single cephalic pregnancy at ≤ 36 weeks of gestation
The antenatal history showed that 993 (18%) of the women had gestational diabetes
mellitus (GDM), while 80 (2%), and 43 (1%) had type 1 and type 2 diabetes, respectively.
In addition, 265 (5%) of the women had high blood pressure, and 73 (1%) had preeclampsia.
The percentage of multiple gestations was 3.5% (1,824) of all pregnancies. The prevalence
of non-vertex presentation was 15%, and the overall CS rate was 33% (1,824 out of
5,428), with 46.5% (849 out of 1,824) primary CS, and 53.5% (975 out of 1,824) repeated
CS. Neonatal data showed that the majority of babies were boys (2,811; 51.4%), and
that the delivery was led mostly by a doctor (2,809; 51.5%). The births were multiple
in 177 (3.2%) of the pregnancies, with 3% having a breech presentation, and other
3% in other positions. We fit several multiple regression models to better understand
the predictability of obstetrical interventions and outcomes ([Table 3 ]). Several variables were found to be strongly correlated with statistical significance.
[Table 4 ] depicts the multiple regression models of parity, birth indication, gestational
age, perineal injury, and birth weight. All of the variables that were statistically
significant predictors remained statistically significant at the same p values when the semipartial R2 was calculated. There were several significant predictors of maternal diabetes, of
hypertension, and of birth weight ([Table 5 ]).
Table 3
Multiple regression models present the predictability of obstetrical interventions
and outcomes. Statistically significant p (p < 0.05) is presented in bold
Maternal age
Nationality
Parity
Gestational age/weeks
Diabetes
Hypertension
Previous cesarean section (CS)
Nationality
0.0001
Parity
0.0000
0.0000
Gestational age/weeks
0.0001
1.0000
1.0000
Diabetes
0.0000
1.0000
0.0009
0.0075
Hypertension
0.0000
1.0000
1.0000
0.0000
0.0000
Previous CS
0.0000
0.2011
0.0000
0.0000
0.0000
1.0000
Birth indication
0.0000
0.0289
1.0000
0.0000
0.0000
0.0000
0.0000
Anesthesia
0.0000
1.0000
0.0001
0.0000
0.0000
0.0000
0.0000
Perineal injury
0.0000
0.0000
0.0000
0.0000
0.0000
0.0065
0.0000
Birth Weight/g
1.0000
0.7611
0.0000
0.0000
1.0000
0.0000
0.0009
Vaginal Birth After Cesarean (VBAC)
0.005
1.0000
0.0000
1.0000
1.0000
1.0000
0.0000
Table 4
Multiple regression and semipartial correlations of parity, birth indication, gestational
age, perineal injury, and birth weight show variables that were statistically significant
predictors. These predictors remained statistically significant when we calculated
the semipartial R2. Statistically significant p (p < 0.05) presented in bold. Only significant results are displayed
Coefficient
Standard error
t
p -value
95% CI
Semipartial R2
and its p -value
Parity (n = 5016, F (14,5001) = 206.12, Eta Sq† = 0.365 Omega Sq‡ = 0.364)
Maternal age
.2227481
.0083859
26.56
0.000
.2063079 0.2391882
0.0895 0.0000
Nationality
−.0819406
.0133661
−6.13
0.000
−.1081441 −0.0557372
0.0048 0.0000
Previous CS
.1933498
.0096646
20.01
0.000
.1744029 0.2122967
0.0507 0.0000
Booked
.1193474
.0256029
4.66
0.000
.0691545 0.1695404
0.0028 0.0000
Birth indication (n = 5016, F (14,5001) = 314.98, Eta Sq† = 0.4686 Omega Sq‡ = 0.4671)
Maternal age
.085875
.0219318
3.92
0.000
.0428791 0.128871
0.0016 0.0001
Nationality
.2063516
.0327676
6.30
0.000
.1421127 0.2705906
0.0042 0.0000
Parity
−8075477
.0327394
−24.67
0.000
−.8717313 −0.7433641
0.0647 0.0000
Gestational age/weeks
−1438536
.0421987
−3.41
0.001
−.2265816 −0.0611257
0.0012 0.0007
Diabetes
−.1065637
.0302752
−3.52
0.000
−.1659163 −0.0472111
0.0013 0.0004
Hypertension
−.1147106
.0367175
−3.12
0.002
−.186693 −0.0427283
0.0010 0.0018
Previous CS
.9132178
.0209711
43.55
0.000
.8721052 0.9543303
0.2015 0.0000
Perineal Injury
−.3564856
.0101073
−35.27
0.000
−.3763004 −0.3366708
0.1322 0.0000
Gestational age/wks (n = 5016, F (14,5001) = 99.80, Eta Sq† = 0.2184 Omega Sq‡ = 0.2162)
Maternal age
−.014594
.0073491
−1.99
0.047
−.0290019 −0.0001868
0.0006 0.0471
Nationality
.0309317
.0110024
2.81
0.005
.0093622 0.0525012
0.0012 0.0050
Parity
.0350506
.0115951
3.02
0.003
.0123192 0.057782
0.0014 0.0025
Diabetes
.0282956
.010138
2.79
0.005
.0084206 0.0481706
0.0012 0.0053
Hypertension
.0618182
.0122706
5.04
0.000
.0377624 0.0858739
0.0040 0.0000
Previous CS
−.054047
.0082078
−6.58
0.000
−.0701379 −0.0379562
0.0068 0.0000
Booked
−.215666
.0208366
−10.35
0.000
−.2565157 −0.1748181
0.0167 0.0000
Birth indication
−.016116
.0047276
−3.41
0.001
−.0253841 −0.006848
0.0018 0.0007
Birth weight/g
.3285245
.0116475
28.21
0.000
.3056903 0.3513587
0.1243 0.0000
Birth weight/g (n = 5016, F (14,5001) = 73.63, Eta Sq† = 0.1709 Omega Sq‡ = 0.1686)
Nationality
.0415472
.012402
3.35
0.001
.017232 0.0658624
0.0019 0.0008
Parity
.0716517
.013048
5.49
0.000
.0460718 0.0972317
0.0050 0.0000
Gestational age/weeks
.4177657
.014811
28.21
0.000
.3887287 0.4468026
0.1319 0.0000
Diabetes
−.033661
.011431
−2.94
0.003
−.0560723 −0.0112513
0.0014 0.0032
Hypertension
.0387665
.013861
2.80
0.005
.011592 0.065941
0.0013 0.0052
Perineum Injury (n = 5016, F (14,5001) = 193.69, Eta Sq† = 0.3516 Omega Sq‡ = 0.3498)
Maternal age
−.071298
.027481
−2.59
0.010
−.1251752 −0.0174224
0.0009 0.0095
Nationality
.1789769
.041109
4.35
0.000
.0983851 0.2595686
0.0025 0.0000
Parity
−1.17556
.040102
−29.31
0.000
−1.254185 −1.09695
0.1114 0.0000
Gestational age/weeks
.2726134
.052752
5.17
0.000
.169195 0.3760318
0.0035 0.0000
Previous CS
.2742744
.030589
8.97
0.000
.2143063 0.3342426
0.0104 0.0000
Birth indication
−.558777
.015842
−35.27
0.000
−.5898361 −0.5277182
0.1613 0.0000
Birth weight/g
.1236014
.046872
2.64
0.008
.031711 0.2154919
0.0009 0.0084
Abbreviation: CS, cesarean section t
∗ , distribution; ∗∗ semipartial regression; † eta squared is an effect size measure for one-way or factorial ANOVA; ‡ Omega squared (ω2) is a measure of effect size, or the degree of association for a
population.
Table 5
Multiple regression and semipartial correlations of diabetes and hypertension show
variables that were statistically significant predictors. Those predictors remained
statistically significant when we calculated the semipartial R2. Statistically significant
p (p < 0.05) presented in bold. Only significant results are displayed
Coefficient
Standard error
t
p -value
95% CI
Semipartial R2
and its p -value
Diabetes
Hypertension
.1074387
.017077
6.29
0.000
.0739587 0.1409187
0.0075 0.0000
Maternal age
−.088283
.010170
−8.68
0.000
−.1082219 −0.0683449
0.0143 0.0000
Hypertension (
n
= 5016, F (14,5001) = 13.13, Eta Sq = 0.0354 Omega Sq = 0.0327)
Maternal age
−.047316
.008424
−5.62
0.000
−.0638325 −0.0308007
0.0061 0.0000
Gestational age/weeks
.0816826
.016213
5.04
0.000
.0498969 0.1134684
0.0049 0.0000
Diabetes
.0730829
.011616
6.29
0.000
.0503089 0.095857
0.0076 0.0000
Previous CS
.0210824
.009470
2.23
0.026
.0025152 0.0396496
0.0010 0.0261
Abbreviation: CS, cesarean section. t -distribution; ∗∗ semipartial regression; † eta squared is an effect size measure for one-way or factorial ANOVA; ‡ Omega squared (ω2) is a measure of effect size, or the degree of association for a
population.
Discussion
Health is one of the key indicators of socioeconomic development in society; and maternal
health is one of the vital health indicators in any country.[13 ] It is well known that the continuum of care has become a core strategy for reducing
maternal, newborn, and child mortality by promoting integrated maternal and neonatal
health services. Over the past few decades, the steady rise in the CS rates have led
to an increased concern among healthcare professionals, governments, policymakers,
and clinicians.[1 ]
[3 ]
[13 ] Several factors, such as the awareness of pregnant women regarding NVD, the deficiency
of knowledge about the complications of CSs, the fear of NVD, and the reduced role
of midwives in maternity hospitals, have led to an increased inclination by part of
the mothers to undergo a CS.[14 ] Furthermore, other factors, such as maternal age, progress in surgical techniques,
social and economic factors, health insurance coverage, and lack of proper training
during the pregnancy, have led to a decreased willingness to undergo a NVD.[15 ]
The analysis of more than 5,400 deliveries (60% of all the deliveries in 2016) in
2 tertiary care maternity hospitals in Dubai showed that groups 5, 8 and 9 of Robson
10-group classification system were the largest contributors to the overall CS rate
and accounted for 30% of the total CS rate ([Table 2 ]). The average global CS rate shows the lowest CS rates in Africa (7.3%), and the
highest CS rates in Latin America and in the Caribbean (40.5%), while Asia is in the
middle, with a CS rate of 19.2%.[15 ] The results of the present study show that the CS rate in the UAE is higher than
the global average CS rate, as well as than the average CS rate in Asia, which highlights
the need for more education of pregnant women and of their physicians to promote NVD.
Several resource-rich countries have responded to the public health concern posed
by high CS rates by implementing policies designed to increase the NVD rates.[16 ]
[17 ] Reducing a relatively high CS rate is a long-term achievement, which requires a
stringent plan over several years, involving several staff categories. However, the
decrease in the CS rate might have some negative consequences, such as an increase
in the number of forceps deliveries and of obstetric anal sphincter injuries, as well
as in the number of newborn babies with low Apgar scores.[18 ]
The results of the present study show that we need to propose and evaluate interventions
for the improvement of labor management in women with multiple pregnancies, as well
as in those with a single pregnancy with a transverse or oblique lie, and to promote
vaginal delivery after previous cesarean section to mitigate further increases in
the future. Several studies showed that the main reason of CS is the previous cesarean
section.[19 ] The scientific, public health, and medical communities have raised concern about
this global epidemic, while the search for ideas and interventions to reduce unnecessary
CSs is ongoing.[10 ]
[20 ] Hence, a proper planning is needed to reduce the number of CSs in nulliparous women
in order to prevent repeated CSs in the future. Fear of NVD, the age of the mother
and the recommendation of the physician are the most influential factors that encourage
mothers to undergo a CS. Therefore, holding consultation sessions before and during
the pregnancy could help mothers to choose the best method of delivery.[21 ] Furthermore, familiarity with the delivery room, staff, equipment, analgesia, presence
of visitors, and making the delivery room pleasant[22 ] are factors that reduce maternal anxiety and aid the mother in choosing the best
method of delivery.
However, the reasonable and responsible reduction of unnecessary CSs is not a trivial
task, and it will take considerable time and effort. Monitoring both the CS rates
and outcomes is essential to ensure that policies, practices, and actions for the
optimization of the utilization of CS lead to improved maternal and infant outcomes.
Nonetheless, the present article is an observational retrospective study, based on
routinely collected data with an explorative character, and it does not allow for
causal explanations. The strength of the present study, given the fact that data were
abstracted for > 5,000 women who presented to tertiary care hospitals in Dubai, far
outweighs its limitation. It is anticipated that the results of our study will encourage
healthcare providers, policy makers, and decision makers to establish a more decisive
policy to encourage NVD in comparison to CS.
