Comparison of cesarean section rates with those of other countries and regions, combined with reference cesarean section rates, to illustrate that t

Discussion Focus:

Comparison of cesarean section rates with those of other countries and regions, combined with reference cesarean section rates, to illustrate that the cesarean section rate in China remains high and there is significant room for reduction.The cesarean section rate in China is significantly higher compared to the WHO model's ideal cesarean section rate. Effective measures need to be taken to reduce the cesarean section rate.

Comparison of cesarean section rates among primiparous women with those of other countries and regions, combined with the trend of increasing cesarean section rates among primiparous women this year, indicating a possible further upward trend in cesarean section rates in the future, necessitating vigilance.The rising trend of cesarean sections requires increased attention.

Identification of the main risk factors for cesarean section and differences from the risk factors for cesarean section in other countries and cesarean section guidelines. For example, breech presentation and macrosomia are indications for cesarean section that can reduce infant mortality, whereas diabetes, advanced maternal age, higher education level, and fetal sex should not be indications for cesarean section. Therefore, it is necessary to focus on discussing the modifiable risk factors that should be the focus of future work. Examples include: (1) reducing the impact of advanced maternal age on cesarean section rates by strengthening obstetric quality control and paying attention to the indications for cesarean section. (2) Reducing the impact of gestational diabetes mellitus (GDM) on cesarean section rates through nutrition clinic construction and health education, as well as enhancing obstetric quality control. (3) Addressing higher education level as a risk factor for cesarean section by improving health education to raise awareness of the adverse health effects of cesarean section and improving access to painless delivery. (4) Addressing male fetal sex as a risk factor for cesarean section by addressing societal preferences for male offspring and avoiding prenatal sex determination. (5) High-level tertiary hospitals have higher cesarean section rates due to the concentration of high-risk pregnancies, so efforts should be made to control cesarean section rates in these hospitals.

Introduction

When compared to spontaneous labor with an expected vaginal birth, the risk of potentially fatal newborn morbidity was lower in women who opted for a Caesarean section before labor at full term. Having a Caesarean section would not have helped the 63% of women who went into spontaneous labor and gave birth vaginally. The higher newborn risk was linked to surgical vaginal delivery and intrapartum CS, but not spontaneous vaginal birth, according to a subgroup analysis of the SL group by mode of delivery(1) ADDIN EN.CITE <EndNote><Cite><Author>Dahlgren</Author><Year>2019</Year><RecNum>82</RecNum><DisplayText>(Dahlgren et al., 2019)</DisplayText><record><rec-number>82</rec-number><foreign-keys><key app="EN" db-id="2fzd0wr2p29fsoes9da5v9fptrd2rdfx5efs" timestamp="1709585016">82</key></foreign-keys><ref-type name="Journal Article">17</ref-type><contributors><authors><author>Dahlgren, Leanne S</author><author>von Dadelszen, Peter</author><author>Christilaw, Jan</author><author>Janssen, Patricia A</author><author>Lisonkova, Sarka</author><author>Marquette, Gerald P</author><author>Liston, Robert M</author></authors></contributors><titles><title>Caesarean section on maternal request: risks and benefits in healthy nulliparous women and their infants</title><secondary-title>Journal of Obstetrics and Gynaecology Canada</secondary-title></titles><periodical><full-title>Journal of Obstetrics and Gynaecology Canada</full-title></periodical><pages>808-817</pages><volume>31</volume><number>9</number><dates><year>2019</year></dates><isbn>1701-2163</isbn><urls></urls></record></Cite></EndNote>. Maternal and newborn health may be impacted by the rise in Caesarian section right over the past few decades. A cesarean section, also referred to as c-section, has emerged as the primary alternative method of delivery for pregnancies with severe complications that pose a risk to the mother's life. The choice to undergo a cesarean section should be made when vaginal delivery is not possible or carries greater risks, and should only be done when there are specific medical reasons related to the mother or the fetus(2).

A study(3) findings shows that worldwide, 21.1% of births were caesarean sections, with rates ranging from 5% in sub-Saharan Africa to 42.8% in Latin America and the Caribbean, according to the most recent statistics available (2010-2018) from 154 nations accounting for 94.5% of live births. Every region has seen an increase in CS since 1990. Eastern Asia, Western Asia, and Northern Africa had the highest percentage increases (44.9, 34.7, and 31.5 percent, respectively), whilst sub-Saharan Africa and Northern America had the lowest percentage increases (3.6 and 9.5 percent, respectively). Worldwide, projections indicate that 28.5% of births will be caesarean sections, with a range of 7.1% in sub-Saharan Africa and 63.4% in Eastern Asia. This equates to 38 million cesarean sections every year, with 33.5 million of them occurring in low- and middle-income countries(3).

Since 1970s, the Chinese government has imposed the one-child policy to manage the sharp expansion of the population. In response to the growing issue of an aging population, the population policy has transitioned to the two-child policy. This policy, which encourages the birth of a second child, was introduced in 2011 and has been completely imposed since 2016(4). China is expected to experience a substantial rise in fertility rate as a result of this new population policy, leading to a considerable increase in the proportion of women with advanced maternal age (AMA), both primiparous and multiparous women with advanced maternal age (AMA) experienced an preeminent risk of developing gestational diabetes and hypertensive disorders of pregnancy. A study(5,6) demonstrated that caesarean section was chosen by 48.44% of the participants in this study. There was a significant difference in the mean scores of fears of pain between the C-section and vaginal delivery groups, with the former having 39.98 8.21 and the latter 36 8.62. Increased tendency to C-section was directly associated with husband's level of education, income, fear of labor pain, history of C-section, and improved attitude toward C-section. On the other hand, women's tendency to C-section was indirectly associated with female fetus gender, increased BMI, and improved attitude toward vaginal delivery(6).

The World Health Organization (WHO) highlighted the need of guaranteeing that women who require it have retrieved to caesarean delivery (CD). The implementation of the two-child policy in China has led to a sizable increase in childbirth among older women, thus rising in a higher need for caesarean sections(7). Though there was a significant reduction in the CD rate that was statistically significant, the total rate however remained at a high level. The rate of vaginal birth was significant among women who had medical indications of CD. There was a clear link between vaginal delivery in women with medical indications of caesarean delivery (CD) and higher rates of negative pregnancy outcomes, such as stillbirth. (1) The slight reduction indicates that more efforts are required to reduce the Caesarean delivery (CD) rate in China; (2) It is prudent to implement comprehensive interventions to enhance the specific CD rate and minimize unnecessary CD procedures, rather than solely focusing on the overall CD rate; and (3) Pregnant women with pre-existing medical conditions and suspected fetal macrosomia should receive personalized counselling regarding the advantages and disadvantages of each delivery method(7). A caesarean section is performed with the purpose of saving the lives of both the mother and the fetus. As per the World Health Organization (WHO), the recommended rate for caesarean sections in various nations is 10% - 15%. However, the actual rate is approximately 72.1%. Believing the significant occurrence of caesarean section documented in the study(8), it is worthwhile to decrease the rate of caesarean section in nulliparous women (group 2) then primiparous and multiparous, and promote vaginal delivery following caesarean section.

The emotions of fear, anxiety, discomfort, and the mother's level of inclination from a previous delivery involvement significantly influence the decision-making process when selecting the method of delivery(9). Consequently, the awareness of labor pain might affect the predisposition and choice of delivery method among expectant mothers, and an amplified unfavorable perception of natural labor pain can substantially reduce the predisposition towards vaginal delivery(10). The ratio of cesarean section deliveries to the overall birth rate is considered as a key indication in any country. A cesarean section is performed with the purpose of saving the lives of both the mother and the fetus. Nevertheless, the current trend of an unnecessary rise in cesarean section procedures has resulted in a significant increase in maternal and fetal morbidity and mortality(11).

Despite a worldwide uptick in the use of cesarean sections, the hospital has seen a particularly alarming trend: an increase in first-time cesarean sections, which in turn has led to a surge in the use of these procedures for subsequent pregnancies(12).

In this study, we are examining cesarean section rates from 2012 to 2021. Because many elements might alter their investigation's conclusions. First, determine the population C-section rate variations. Healthcare practitioners, health authorities and researchers need this data. Therefore, they may better alter their approaches to achieve the best outcomes for the mother and newborn. This information allows it to analyze the ever-changing distribution landscape. This study acknowledges the multifaceted prevalence of cesarean sections by focusing on first-time mothers and women with several children. This will enhance mother health and reduce unnecessary surgeries.

Use of the c-model to estimate the reference C-section rate improves benchmarking precision and provides a consistent measurement to analyze Zhejiang Province's C-section rates. By doing this study, it is feasible to examine and appraise cesarean delivery patterns across the research period with higher precision. This knowledge may help us create more tailored strategies to make giving delivery safer and more natural and reduce the incidence of cesarean procedures.

The population-attributable risk can be used as the final stage to assess the relative importance of each component in explaining surgical section rates. This is done via population-attributable risk. Addressing the reasons of higher C-section rates in Zhejiang Province may enhance mother and the newborn health. This information helps prioritize treatments and allocate resources, as well as achieve this goal.

1.1 Research Aim and Objectives (ROs)The main aim of this study is to explore the prevalence and risk factors of C-section among overall population in Zhejiang Province, China from a period of 2012 to 2021. Therefore, in order to fulfil this aim, the following ROs are proposed:

RO1: To investigate the changes in C-section rates in Zhejiang Province from 2012 to 2021: overall population and primiparous women, also incorporating advanced maternal aged primiparous women with or without complications.

RO2: To use the c-model to calculate the reference C-section rate in Zhejiang Province from 2012 to 2021: overall population, primiparous women, and multiparous women.

RO3: To explore the risk factors associated with caesarean section in overall population, primiparous women, and multiparous women.

RO4: To calculate the population-attributable risk to show the proportion of C-section rates caused by specific exposure factors.

1.2 Research MethodologyThe main aim of this study is to determine the prevalence of C-section among overall population in China. Therefore, in order to fulfil this aim, different ROs are proposed, focusing on the changes in C-section rate among women in China in a period of January 2012 to December 2021, leading to the identification of different risk factors in this regard. These objectives mainly focus on the causal association between the risk factors and C-section rate among primiparous and multiparous women in Zhejiang Province, China, supporting the integration of objectivism. Thus, the positivist philosophy(13) was incorporated in this study to fulfil the proposed objectives. At the same time, the deductive approach was incorporated in which reasoning moves from general characteristics to specific conclusion(14). This helped in identifying the contribution of risk factors in increasing C-section rates among women in China. On the basis of the positivist philosophy and deductive approach, the quantitative method was implemented within this study to attain the required results.

Therefore, for this scientific research, a cohort study was considered for determining the prevalence of C-section among multiparous and primiparous women in Zhejiang Province, China. A cohort study is stated as one of the types of epidemiological studies within which the follow-up of a group, including different individuals with common characteristics(15), is taken into account for a specific period of time in order to determine that how many of these individuals have reached the required health outcomes. Thus, this epidemiological approach was most suitable for current research as it mainly focuses on the prevalence of C-section among overall women population in Zhejiang Province, China, focusing on the associated risk factors and outcomes within a period of January 2012 to December 2021. For this purpose, the data was collected from Chinas National Maternal Near-Miss Surveillance System (NMNMSS) for Zhejiang Province. The exposure variables within this context included demographic, reproductive history, pregnancy complications, and birth outcomes from all the pregnant and postpartum women. Moreover, an important exclusion and inclusion criteria was also developed for selecting the required data in association with the objectives of this study.

1.2.1 Study Population and SettingsStudy population is usually selected on the basis of developed ROs. Therefore, the most suitable study population for this study includes the primiparous and multiparous women in Zhejiang Province, China. Thus, for current cohort epidemiological research, the data was obtained from Chinas National Maternal Near-Miss Surveillance System (NMNMSS) for Zhejiang Province. The NMNMSS was established in October 2010, and covered 326 urban districts and rural counties across China. Hospitals with more than 1000 deliveries per year were eligible to be surveillance sites. However, it was inconvenient for the researcher to collect the data from such a larger population due to time constraints and limited resources, emphasizing the implementation of an effective sampling technique. Thus, for the current research, all of the eligible hospitals were selected via stratified random sampling to ensure proportional representation of urban and rural populations across all three regions in China (eastern, central, and western). This approach was also found to be effective in preventing research bias within the context of selection of the sample size for this research.

Therefore, in Zhejiang Province 18 out of 85 eligible hospitals were randomly sampled. These consisted of 11 tertiary hospitals and 7 secondary hospitals (12 county level, 4 municipal level, 2 provincial level). Trained doctors and nurses filled out a questionnaire consisting of information about demographic, reproductive history, pregnancy complications, and birth outcomes from all the pregnant and postpartum women in the 18 surveillance sites by referring to the medical record and entered the data into a web-based data management system. Local staff of NMNMSS were responsible for verifying the quality of data. County-level, municipal, and provincial staffs of NMNMSS in Zhejiang Province visited all of the 18 surveillance sites at least once a year to check the accuracy of monitoring information by cross-checking with medical records. The National Office for Maternal and Child Health Surveillance also visited a random sample of six to eight hospitals in each province once a year to ensure the quality assurance. Detailed information about the data collection and quality control process has been reported elsewhere.

1.2.2 Inclusion and Exclusion Criteria

Important exclusion and inclusion criteria has been defined for this study, in order to collect the data from an appropriate population to fulfil the proposed objectives.

Inclusion Criteria

This study focuses on the prevalence of C-section among primiparous and multiparous women in Zhejiang Province, China. Therefore, for data collection, 18 hospitals (11 tertiary hospitals and 7 secondary hospitals) in Zhejiang Province, were selected randomly. Thus, the C-section cases of such women conducted in these hospitals were selected for this study.

The cases of C-section within the context of primiparous and multiparous women recorded in the selected 18 hospitals, from a period of January 2012 to December 2021, were selected for this study.

Women who terminated their pregnancies in these sectors within the provided period were selected.

Cases of women with singleton pregnancy were also selected.

C-section cases in which the age of woman was greater than 18 years, were selected.

Exclusion Criteria

Cases of women, with incomplete data were excluded.

Cases of women with singleton pregnancy, who had miscarriages.

Cases of women, who had gestational age which was less than 28 weeks or over 43 weeks.

Cases with incorrect data on maternal age (age < 13 years, or > 50 years) of women.

1.2.3 Data Collection

Data collection procedure is stated to be an integral part of a research study. As a result, important focus was given in implementing an effective data collection process for this study, in order to ensure the credibility as well as integrity of the collected data. For this study, the period of January 2012 to December 2021, was considered for data collection. However, for the current research, focus was given on the changes in C-section rate among women in Zhejiang Province, China. For this purpose, it was determined that how many primiparous and multiparous women underwent C-section within the selected period. At the same time, the risk factors associated with C-section in these women were also analyzed by focusing on the database of the selected hospitals for this study. Moreover, the contribution of different risk factors to the C-section rate among the multiparous and primiparous women within the selected hospitals, was also considered.

However, for the selection of a proper sample size of the women who underwent C-section in China, within the context of current research; the formulated inclusion and exclusion criteria was considered. Therefore, the on basis of collected data, it was observed that between January 2012 to December 2021, about 865,208 cases were carried out in which women terminated a pregnancy in the selected 18 surveillance sites of Zhejiang Province. Based on the inclusion and exclusion criteria of this study, about 392,855 cases, including women with incomplete data, were excluded from this study. At the same time, cases in which, women who had incorrect (number of parities > number of gravidity) (n = 0) or missing data on parity (n = 23), were also excluded, leading to selection of about 472,330 C-section cases. Later on, after careful evaluation of the collected data, 11,821 cases in which women had multiple miscarriages in the past, were also excluded from this study and a sample of 460,509 cases of women with C-section, was selected. Moreover, out of these 460,509 cases of women, 19,763 of the women had miscarriages, while 1,878 women had gestational age which was less than 28 weeks or over 43 weeks. These women were also excluded from the sample of the study. Additionally, cases of 43 women who had incorrect data on maternal age (age < 13 years, or > 50 years) and 1,101 who did not terminate the pregnancy in the surveillance sites, were also excluded for the final analysis. The remaining 437,356 mothers and birth pairs were included in the analysis.

Figure 1. Data collection, based on inclusion and exclusion criteria.

1.2.4 Assessment of Study VariablesIn order to assess the variables of this study, their definitions were considered. For instance, within the context of this study, advanced maternal age was defined as women older than 35 years old. However, for the diagnosis of uterine rupture, placenta previa, placental abruption, hypertensive disorder, diabetes, heart disease, liver disease and lung disease among the women, the collected data from medical records, was considered. However, for fetal presentation, physician diagnosis was considered. Within this context, the pregnant women with chronic hypertension, hypertension during pregnancy, preeclampsia, eclampsia, and HELLP syndromes were defined as hypertensive disorder, while pregnant women with chronic diabetes and gestational diabetes were diagnosed as diabetes. Maternal near miss (MNM) was defined according to WHO criteria which states that MNM, includes a woman who has survived a severe complication at the time of pregnancy or has nearly died during this process(16). Moreover, in regard to current study, macrosomia was defined as newborns with gestational weight above 4000g.

1.2.5 C-Section (CS) Rate Calculation

For this study, a mathematical model, known as C-model (proposed by WHO in the year 2015) was utilized for calculating the CS rate. This model takes into account obstetric factors, complications and demographic characteristics, leading to the generation of an appropriate CS rate locally for the population under study. this model was constructed, by using data from about 22 nations, validating with the data attained from 43 nations. C-model has been used for demonstrating discriminatory capacity within an AUC which ranges from 0.832 to 0.844. For this study, the models complete version (v1.3) was taken into account and the following formula was used for calculating CS rate:

Logit=-4.015252-0.77531parity+2.922222previous CD+1.834027multiple pregnancy+2.634921provider initiated childbirth+2.985162fetal presentation+0.71104maternal age+0.661417organ dysfunction or ICU admission+3.796513placenta previa+2.741255abruption placenta+0.561991chronic hypertension+0.98718pre-eclampsia+1.301346renal disease+1.310211HIV1.2.6 Statistical AnalysisFor this research study, statistical analysis was conducted to fulfil the developed ROs. For this purpose, monthly average cesarean section was charted to visualize the characteristics of temporal distribution. Categorical and numerical variables were expressed as number (percentage) and meanstandard deviation (SD), respectively. Differences in proportions and means between cesarean section and vaginal delivery were tested by 2 test or the analysis of variance. At the same time, logistic regression models were also used to investigate the risk factors of cesarean section among women. The unadjusted model was used to summarize the crude odds ratios without adjustment of any covariates. In the adjusted model, hospital type, education, advanced maternal age, gravidity, uterine rupture, placenta previa, placental abruption, hypertensive disorder, diabetes, heart disease, liver disease, lung disease, fetal presentation, maternal near miss, newborn sex, and macrosomia, were included. Population-attributable risk was calculated based on logistic model, to show the proportion of the cesarean section rate that is attributable to a given exposure. All analyses were conducted by R software (version 3.2.2; https://www.r-project.org/). Statistical significance was determined using a two-side probability set at p < 0.05.

The current research mainly incorporates a cohort epidemiology study, in which the data was collected from 18 selected hospitals, present in Zhejiang Province. For this purpose, the database of National Maternal Near-Miss Surveillance System (NMNMSS) was considered for selecting the associated cases of women for this study. An important inclusion as well as exclusion criteria was formulated for this study and a final sample of 437,356 mothers and birth pairs were included. Statistical analysis was conducted for this study.

Results and AnalysisThis section mainly includes the results of the study, focusing on the changes in the reference cesarean section rate And Cesarean section rate using the c-model in Zhejiang Province from 2012 to 2021, risk factors for cesarean section and population-attributable.

2.1 Changes in the Reference Cesarean Section Rate and Cesarean Section Rate Using the C-Model

In order to fulfil the RO1 of the study, we observed the changes in the reference cesarean section rate using the c-model.

2.1.1 Changes in the Reference Cesarean Section Rate and Cesarean Section Rate

among the Overall Population of Zhejiang ProvinceFigure 2.1 shows the C-section rate among overall population in Zhejiang Province, China from a period of 2012 to 2014, it has relatively remained stable, with in an average around 41% whereas, the reference C-section rate has slightly decreased an average of 11% within this period among the overall population. Contrarily, C-section rates decreased from a period of 2015 to 2019 among overall population within the context of Zhejiang Province while the reference C-section rates decreased from 2015 to 2017. Finally, the C-section rates increased from 2020 among overall population and reference C-section also increased from 2018.

Figure 2.1. Trends in Reference C-section Rate in Overall Population of Zhejiang Province (2012 to 2021)

2.1.2 Changes in the Reference Cesarean Section Rate and Cesarean Section Rate

Among Primiparous and Multiparous Women in Zhejiang ProvinceFigure 2.2 shows changes in the reference cesarean section rate among primiparous and multiparous women in Zhejiang Province. It has been observed that the C-section rates increased among primiparous women in Zhejiang Province, China from a period of 2012 to 2014, whereas these rates decreased from 2015 to 2019 among primiparous women in Zhejiang Province, China and later increased in 2020. Within the context of primiparous women, reference C-section rates decreased from 2012 to 2017 and later increased from 2017 to 2021. Moreover, figure 2.2 also shows that C-section rates increased from 2012 to 2015 among multiparous women in Zhejiang Province, China, while these rates decreased among such women in 2016 and again increased from 2017 to 2021. However, the reference C-section rates within the context of multiparous women increased from a period of 2012 to 2014, whereas these rates decreased from 2015 to 2019 and later increased in 2020.

Figure 2.2 Trends in Reference C-section Rate in Primiparous and Multiparous Women in Zhejiang Province (2012 to 2021)

2.3 Risk Factor Analysis

In order to fulfil RO2, risk factor analysis was also conducted, Within this context, the risk factors of C-section among the selected women were divided into four important groups which are (a) risk factors for C-section in overall population of Zhejiang Province, (b) risk factors for C-section among high-risk/low-risk populations in Zhejiang Province, (c) risk factors for C-section among primiparous and multiparous women in Zhejiang Province and (d) risk factors for C-section among women with and without a history of C-section.

2.3.1 Risk Factors for C-section in Overall Population of Zhejiang ProvinceDifferent risk factors for C-section in overall population of Zhejiang Province were also observed as shown in table 2.3. Within the context of unadjusted model, different factors including tertiary hospital, high school, college or above, primipara, advanced maternal age, gravidity, cesarean section history, breech presentation, shoulder presentation, mixed presentation, male infant, macrosomia, uterine rupture, placenta previa and placental abruption contributed to increased risks during C-section as value of p was found to be < 0.001 for all these factors. At the same time, other factors including hypertensive disorder, heart disease, liver disease, gestational diabetes, lung disease and maternal near miss also contribute to increased risks within the context of C-section in overall population of Zhejiang Province (p < 0.001). These factors were also found to lead to increased risks in C-section within the context of adjusted model (p < 0.05).

Table 2.3 Risk Factors for C-section in Overall Population of Zhejiang Province

var_nameodd_unadjustedp_valueodd_adjustedp_valueTertiary hospital 1.32 [1.31,1.34] < 0.001 1.2 [1.18,1.22] < 0.001

High shcool1.08 [1.06,1.09] < 0.001 1.03 [1.01,1.05] 0.0018

College or above 0.92 [0.91,0.93] < 0.001 0.97 [0.96,0.99] 0.0023

Primipara0.6 [0.59,0.6] < 0.001 4.08 [4.01,4.16] < 0.001

Advanced maternal age 2.55 [2.51,2.58] < 0.001 2.44 [2.39,2.5] < 0.001

Gravidity 1.71 [1.7,1.73] < 0.001 1.31 [1.29,1.33] < 0.001

Cesarean_section_history54.24 [52.78,55.74] < 0.001 145.17 [140.46,150.03] < 0.001

Breech presentation 23.35 [22.15,24.61] < 0.001 41.76 [39.28,44.39] < 0.001

Shoulder presentation 16.43 [13.9,19.42] < 0.001 16.28 [13.41,19.76] < 0.001

Mixed presentation 14.87 [10.99,20.11] < 0.001 24.32 [16.89,35.01] < 0.001

Male infant 1.09 [1.08,1.1] < 0.001 1.13 [1.11,1.14] < 0.001

Macrosomia 1.96 [1.92,2] < 0.001 3.02 [2.94,3.1] < 0.001

Uterine rupture 41.01 [30.04,55.97] < 0.001 5.57 [3.67,8.48] < 0.001

Placenta previa 28.16 [25.79,30.73] < 0.001 37.73 [34.18,41.65] < 0.001

Placental abruption 2.36 [2.25,2.49] < 0.001 2.95 [2.77,3.15] < 0.001

Hypertensive disorder 2.88 [2.81,2.94] < 0.001 3.36 [3.27,3.46] < 0.001

Heart disease 3.17 [2.94,3.41] < 0.001 3.44 [3.13,3.78] < 0.001

Liver disease 1.56 [1.51,1.62] < 0.001 1.58 [1.5,1.66] < 0.001

Gestational diabetes 1.52 [1.5,1.55] < 0.001 1.16 [1.13,1.18] < 0.001

Lung disease 3.83 [2.99,4.92] < 0.001 3.15 [2.28,4.35] < 0.001

Maternal near miss 2.66 [2.5,2.82] < 0.001 2.53 [2.28,2.8] < 0.001

2.3.2 Risk Factors for C-section among Advanced maternal age and Non-advanced maternal age Populations in Zhejiang Province.

Women with advanced maternal age (> 35 years) were considered to be high-risk population within the context of this study, while the women with non-advanced maternal age were considered to be low-risk population. Table 2.4 shows that different factors integrating tertiary hospital, high school, college or above, primipara, advanced maternal age, gravidity, cesarean section history, breech presentation, shoulder presentation, mixed presentation, male infant, macrosomia, uterine rupture, placenta previa and placental abruption are significant risk factors for C-section among high-risk population (p < 0.001) as well as among low-risk population (p < 0.001). In addition, other associated risk factors including hypertensive disorder, heart disease, liver disease, gestational diabetes, lung disease and maternal near miss, were also found to have a significant impact within the context of both high-risk and low-risk populations (p < 0.001).

Table 2.4. Risk Factors for C-section among advanced maternal age/Non-advanced maternal age Population

var_nameAdvanced maternal age Non-advanced maternal age

odd_adjustedp_valueodd_adjustedp_valueTertiary hospital 1.2 [1.14,1.26] < 0.001 1.2 [1.18,1.22] < 0.001

High shcool0.83 [0.78,0.88] < 0.001 1.07 [1.05,1.1] < 0.001

College or above 0.65 [0.62,0.69] < 0.001 1.03 [1.01,1.04] 0.0046

Primipara6.11 [5.73,6.52] < 0.001 3.95 [3.87,4.04] < 0.001

Advanced maternal age - - - -

Gravidity 1.33 [1.22,1.44] < 0.001 1.3 [1.28,1.32] < 0.001

Cesarean_section_history86.4 [80.44,92.81] < 0.001 161.03 [155.18,167.09] < 0.001

Breech presentation 23.13 [19.44,27.53] < 0.001 44.61 [41.79,47.62] < 0.001

Shoulder presentation 17.63 [10.26,30.28] < 0.001 16.06 [13.05,19.77] < 0.001

Mixed presentation 22.11 [7.78,62.84] < 0.001 24.71 [16.75,36.46] < 0.001

Male infant 1.06 [1.01,1.1] 0.0091 1.13 [1.12,1.15] < 0.001

Macrosomia 2.17 [2,2.35] < 0.001 3.14 [3.05,3.23] < 0.001

Uterine rupture 4.72 [2.09,10.65] < 0.001 5.85 [3.59,9.52] < 0.001

Placenta previa 30.86 [24.43,38.97] < 0.001 39.28 [35.23,43.81] < 0.001

Placental abruption 1.89 [1.59,2.25] < 0.001 3.18 [2.97,3.41] < 0.001

Hypertensive disorder 3.08 [2.86,3.31] < 0.001 3.4 [3.29,3.51] < 0.001

Heart disease 2.97 [2.16,4.08] < 0.001 3.49 [3.16,3.86] < 0.001

Liver disease 1.33 [1.14,1.55] < 0.001 1.61 [1.53,1.7] < 0.001

Gestational diabetes 1.11 [1.05,1.17] < 0.001 1.17 [1.14,1.19] < 0.001

Lung disease 6.07 [1.96,18.86] 0.0018 2.95 [2.1,4.14] < 0.001

Maternal near miss 1.89 [1.43,2.5] < 0.001 2.66 [2.38,2.97] < 0.001

2.3.3 Risk Factors for C-section among Primiparous and Multiparous Women in Zhejiang Province

Table 2.5 shows risk factors for C-section among primiparous and multiparous women in Zhejiang province, China. The results obtained show that different factors including tertiary hospital, high school, college or above, advanced maternal age, cesarean section history, breech presentation, shoulder presentation, mixed presentation, male infant, macrosomia, uterine rupture, placenta previa, placental abruption, hypertensive disorder, heart disease, liver disease, gestational diabetes, lung disease and maternal near miss, are common risk factors of C-section in both population of primiparous and multiparous women. However, within the context of primiparous women, different factors including tertiary hospital, high school, college or above, advanced maternal age, gravidity, breech presentation, shoulder presentation, mixed presentation, male infant, macrosomia, placenta previa, placental abruption, hypertensive disorder, heart disease, liver disease, gestational diabetes, lung disease and maternal near miss show significant outcomes (p < 0.001), while value of p for uterine rupture was 0.0629, showing insignificant outcome. In addition, multiparous women have also specific risk factors including, C-section History, gravidity, advanced maternal age.

Table 2.5. Risk Factors for C-section among Primiparous and Multiparous Women

var_namemultipara First-time mothers

odd_adjustedp_valueodd_adjustedp_valueTertiary hospital 1.32 [1.28,1.35] < 0.001 1.15 [1.13,1.17] < 0.001

High shcool0.92 [0.89,0.95] < 0.001 1.1 [1.08,1.13] < 0.001

College or above 0.85 [0.82,0.87] < 0.001 1.05 [1.02,1.07] < 0.001

Primipara- - - -

Advanced maternal age 2.12 [2.06,2.18] < 0.001 3.21 [3.08,3.35] < 0.001

Gravidity - - 1.3 [1.28,1.32] < 0.001

Cesarean_section_history139.4 [134.85,144.1] < 0.001 - -

Breech presentation 36.58 [33.52,39.93] < 0.001 45.78 [42,49.89] < 0.001

Shoulder presentation 38.93 [27.99,54.15] < 0.001 7.41 [5.86,9.36] < 0.001

Mixed presentation 35.08 [18.95,64.95] < 0.001 18.89 [12.14,29.4] < 0.001

Male infant 1.07 [1.05,1.1] < 0.001 1.15 [1.13,1.16] < 0.001

Macrosomia 2.09 [2,2.19] < 0.001 3.74 [3.61,3.86] < 0.001

Uterine rupture 7.13 [4.35,11.7] < 0.001 2.21 [0.96,5.09] 0.0629

Placenta previa 41.71 [36.59,47.54] < 0.001 30.72 [26.49,35.62] < 0.001

Placental abruption 3.09 [2.76,3.45] < 0.001 2.87 [2.66,3.11] < 0.001

Hypertensive disorder 3.57 [3.39,3.76] < 0.001 3.28 [3.17,3.4] < 0.001

Heart disease 3.36 [2.78,4.06] < 0.001 3.47 [3.11,3.87] < 0.001

Liver disease 1.55 [1.41,1.7] < 0.001 1.59 [1.5,1.69] < 0.001

Gestational diabetes 1.2 [1.15,1.24] < 0.001 1.14 [1.11,1.17] < 0.001

Lung disease 4.1 [2.43,6.94] < 0.001 2.66 [1.79,3.96] < 0.001

Maternal near miss 2.65 [2.21,3.17] < 0.001 2.47 [2.18,2.8] < 0.001

2.3.4 Risk Factors for C-section among Women with and without a History of C-section

Table 2.6 shows different risks factors for C-section among women with and without a history of C-section. within the context of women without a history of C-section, different factors including tertiary hospital, college or above, primipara, advanced maternal age, gravidity, breech presentation, shoulder presentation, male infant, macrosomia, placenta previa, placental abruption, hypertensive disorder and heart disease, show significant associated (p < 0.05). Moreover, in regard to women with the history of C-section, factors including high school, breech presentation, advanced maternal age, macrosomia, uterine rupture, placenta previa, placental abruption, hypertensive disorder, heart disease, liver disease showed significant association (p < 0.05). moreover, advanced maternal age, macrosomia, hypertensive disorders. Heart disease, placental previa have shown risk factor of a C-section in both groups.

Table 2.6. Risk Factors for C-section among Women with and without a History of C-section

var_nameWomen with a history of cesarean section Women with no history of cesarean section

odd_adjustedp_valueodd_adjustedp_valueTertiary hospital 0.97 [0.91,1.04] 0.3753 1.21 [1.19,1.23] < 0.001

High shcool1.29 [1.19,1.41] < 0.001 1.02 [1,1.04] 0.0553

College or above 1.12 [1.04,1.2] 0.0014 0.97 [0.95,0.98] < 0.001

Primipara- - 4.16 [4.08,4.24] < 0.001

Advanced maternal age 1.31 [1.22,1.42] < 0.001 2.58 [2.52,2.65] < 0.001

Gravidity - - 1.31 [1.29,1.33] < 0.001

Cesarean_section_history- - - -

Breech presentation 1.63 [1.32,2.02] < 0.001 45.92 [43.1,48.93] < 0.001

Shoulder presentation 7.84 [1.95,31.59] 0.0038 16.54 [13.6,20.11] < 0.001

Mixed presentation 0.73 [0.22,2.39] 0.6003 27.16 [18.58,39.7] < 0.001

Male infant 1.07 [1.01,1.13] 0.0287 1.13 [1.11,1.14] < 0.001

Macrosomia 1.48 [1.24,1.75] < 0.001 3.07 [2.99,3.15] < 0.001

Uterine rupture 5.43 [2.7,10.9] < 0.001 5.75 [3.42,9.67] < 0.001

Placenta previa 5.41 [3.57,8.2] < 0.001 40.01 [36.15,44.27] < 0.001

Placental abruption 0.15 [0.13,0.18] < 0.001 3.41 [3.2,3.64] < 0.001

Hypertensive disorder 1.32 [1.13,1.55] < 0.001 3.43 [3.33,3.53] < 0.001

Heart disease 4.05 [1.68,9.8] 0.0019 3.43 [3.12,3.78] < 0.001

Liver disease 1.09 [0.85,1.39] 0.481 1.6 [1.52,1.68] < 0.001

Gestational diabetes 1.03 [0.94,1.13] 0.5368 1.17 [1.14,1.19] < 0.001

Lung disease 28813.56 [0,5.6125948258781e+55] 0.8647 3.09 [2.23,4.28] < 0.001

Maternal near miss 1.07 [0.68,1.69] 0.7559 2.61 [2.36,2.9] < 0.001

2.4 Population-attributable Risk (PAR) Analysis

In order to fulfil RO3, PAR analysis was conducted focusing on PAR for risk factors and PAR in overall population in Zhejiang Province, China.

2.4.1 PAR in Overall Population

Table 2.7 shows PAR% for C-section in overall population of Zhejiang province, focusing on the associated time frames. PAR (%) within the context of tertiary hospital, high school, college or above, primipara, advanced maternal age, gravidity, cesarean section history, breech presentation, shoulder presentation, mixed presentation, male infant, macrosomia, uterine rupture, placenta previa and placental abruption was found to be 10.11, 1.24, 0.87, -7.58, 4.05, 9.25, 3.93, 0.18, 0.07, 2.21, 1.91, 0.18, 1.46, 0.3 and 2.26 for a period of 2012 to 2021. However, PAR (%) within the context of hypertensive disorder, heart disease, liver disease, gestational diabetes, lung disease and maternal near miss, was found to be 0.22, 0.26, 1.03, 0.02, 0.13 and 10.11.

Table 2.7. Population-attributable risk for cesarean section in the overall population of Zhejiang Province

var_name2012-2013/PAR(%) 2014-2015/PAR(%) 2016-2017/PAR(%) 2018-2019/PAR(%) 2020-2021/PAR(%) 2012-2021/PAR(%)

Tertiary hospital 7.38[6.54,8.21] 13.53[12.65,14.4] 10.84[9.9,11.78] 6.4[5.35,7.45] 9.63[8.41,10.86] 10.11[9.68,10.53]

High shcool1.74[1.44,2.05] 1.84[1.56,2.13] 1.18[0.87,1.49] 1.16[0.77,1.54] 0.9[0.46,1.34] 1.24[1.09,1.39]

College or above 7.52[6.88,8.15] 3.79[3.04,4.54] 0.71[-0.15,1.57] -2.05[-3.01,-1.09] -3.58[-4.86,-2.3] 0.87[0.49,1.24]

Primipara-5.9[-6.92,-4.88] -13.9[-14.89,-12.9] -12.19[-13.04,-11.34] -8.52[-9.45,-7.6] -3.91[-4.95,-2.88] -7.58[-8,-7.15]

Advanced maternal age 2.25[2.1,2.41] 3.1[2.91,3.3] 4.77[4.52,5.03] 5.97[5.68,6.27] 6.06[5.73,6.38] 4.05[3.94,4.16]

Gravidity 8.06[7.3,8.82] 9.73[8.75,10.72] 10.7[9.45,11.94] 9.24[7.84,10.63] 7.53[6.17,8.88] 9.25[8.76,9.73]

Cesarean_section_history3.38[3.26,3.49] 4.05[3.92,4.19] 3.51[3.38,3.64] 4.46[4.31,4.62] 4.62[4.45,4.79] 3.93[3.87,3.99]

Breech presentation 0.1[0.08,0.12] 0.15[0.12,0.18] 0.14[0.11,0.16] 0.24[0.21,0.28] 0.33[0.29,0.38] 0.18[0.16,0.19]

Shoulder presentation 0.06[0.05,0.08] 0.07[0.05,0.09] 0.04[0.03,0.06] 0.03[0.02,0.05] 0.13[0.1,0.16] 0.07[0.06,0.07]

Mixed presentation 2.83[2.27,3.4] 2.48[1.88,3.09] 1.42[0.8,2.03] 1.48[0.8,2.16] 2.38[1.65,3.11] 2.21[1.93,2.5]

Male infant 2.02[1.89,2.15] 1.95[1.8,2.1] 1.52[1.37,1.66] 1.89[1.72,2.06] 2.17[1.99,2.35] 1.91[1.84,1.98]

Macrosomia 0.01[0.01,0.02] 0.12[0.1,0.14] 0.25[0.22,0.28] 0.41[0.37,0.45] 0.24[0.2,0.27] 0.18[0.17,0.2]

Uterine rupture 1.16[1.1,1.22] 1.44[1.36,1.51] 1.71[1.63,1.8] 1.51[1.42,1.6] 1.45[1.36,1.55] 1.46[1.42,1.49]

Placenta previa 0.21[0.17,0.25] 0.31[0.26,0.36] 0.33[0.27,0.39] 0.48[0.41,0.55] 0.33[0.24,0.42] 0.3[0.28,0.33]

Placental abruption 2.15[2.04,2.26] 2.29[2.16,2.42] 2.18[2.04,2.31] 2.2[2.04,2.35] 2.72[2.53,2.91] 2.26[2.2,2.32]

Hypertensive disorder 0.2[0.17,0.24] 0.21[0.17,0.25] 0.25[0.21,0.29] 0.27[0.22,0.32] 0.16[0.11,0.21] 0.22[0.2,0.24]

Heart disease 0.17[0.13,0.22] 0.1[0.03,0.16] 0.45[0.36,0.53] 0.43[0.34,0.52] 0.39[0.3,0.49] 0.26[0.23,0.29]

Liver disease 0.53[0.42,0.65] 1.22[1.06,1.39] 1.54[1.35,1.74] 1.54[1.29,1.78] 1.76[1.46,2.06] 1.03[0.95,1.12]

Gestational diabetes 0.01[0,0.02] 0.02[0,0.03] 0.02[0.01,0.03] 0.02[0.01,0.04] 0.03[0.01,0.05] 0.02[0.01,0.02]

Lung disease 0.12[0.09,0.15] 0.11[0.08,0.15] 0.16[0.12,0.19] 0.14[0.09,0.18] 0.13[0.09,0.18] 0.13[0.11,0.15]

Maternal near miss 7.38[6.54,8.21] 13.53[12.65,14.4] 10.84[9.9,11.78] 6.4[5.35,7.45] 9.63[8.41,10.86] 10.11[9.68,10.53]

2.4.1 Population-attributable Risks (PAR) for Risk FactorsIn order to determine the contributions of risk factors to the C-section rate among women in China (RO3), population-attributable risks (PAR) for risk factors by time period, was evaluated. The results of PAR were shown in Table 2.8, which show that the PAR for C-section among the selected women was -3.7, -4.8, -3.5, -1.4 and -2.6 for the time periods 2012 to 2013, 2014 to 2015, 2016 to 2017, 2018 to 2019 and 2020 to 2021. However, the PAR values for C-section among the associated women were found to be 8.5, 1.8, -2.8, -5.2 and -4.5 for the time periods 2012 to 2013, 2014 to 2015, 2016 to 2017, 2018 to 2019 and 2020 to 2021, within the context of colleges, whereas the total PAR for C-section within the context of high school and middle school was found to be 0.4 and -0.7. Additionally, the PAR for C-section among the selected women for a period of 2012 to 2021 was found to be 2.7 and 6.7 within the context of advanced maternal age and gravidity. However, the PAR for C-section among the selected women, within the context of uterine rupture, placenta previa and placenta abruption was found to be 0.007, 1.5 and 0.6 in a period of 2012 to 2021. Other factors are also found to be responsible for increasing the risks of C-section among the women in China. In this regard, the PAR for C-section among women was found to be 3.3, 0.4 and 0.4 for pregnancy induced hypertension, heart disease and liver disease for a period of 2012 to 2021. At the same time, PAR for C-section among women was found to be 0.03 and 0.4 for lung disease and MNM for a period of 2012 to 2022, while for this period, the PAR for C-section among the selected women was found to be 3.9 within the context of macrosomia.

More than 1 C-section per 100 women could be attributed to factors such as hospital type, advanced maternal age, history of miscarriage and induced labor, placenta previa, hypertensive disorder, diabetes, fetal malpresentation, male fetus, and macrosomia. The proportion of C-section that were the result of advanced maternal age, hypertensive disorder and fetal malpresentation increased over the study period.

Table 2.8. Population-attributable risks (PAR) for risk factors by time period (2012 to 2021)

Characteristics 2012-2013 2014-2015 2016-2017 2018-2019 2020-2021 2012-2021

Hospital type Tertiary hospital Ref Ref Ref Ref Ref Ref

Secondary hospital -3.7 -4.8 -3.5 -1.4 -2.6 -3.3

Education College or above 8.5 1.8 -2.8 -5.2 -4.5 0.8

High school -1.5 0.2 0.8 1.6 1.3 0.4

Middle school or below -3.2 -1 0.2 0.3 0 -0.7

Advanced maternal age No Ref Ref Ref Ref Ref Ref

Yes 1.7 2.3 3.2 3.7 4.3 2.7

Gravidity 1 Ref Ref Ref Ref Ref Ref

2 5.2 6.6 7.9 7.5 6.8 6.7

Uterine rupture No Ref Ref Ref Ref Ref Ref

Yes 0.002 0.002 0.016 0.007 0.014 0.007

Placenta previa No Ref Ref Ref Ref Ref Ref

Yes 1.2 1.5 2 1.6 1.5 1.5

Placental abruption No Ref Ref Ref Ref Ref Ref

Yes 0.3 0.6 0.8 1 0.8 0.6

Pregnancy induced hypertension No Ref Ref Ref Ref Ref Ref

Yes 2.5 3.4 3.7 3.8 4.4 3.3

Heart disease No Ref Ref Ref Ref Ref Ref

Yes 0.3 0.4 0.4 0.5 0.3 0.4

Liver disease No Ref Ref Ref Ref Ref Ref

Yes 0.3 0.2 0.8 0.8 0.6 0.4

Gestational diabetes No Ref Ref Ref Ref Ref Ref

Yes 1.1 2.2 2.7 2.8 2.8 1.9

Lung disease No Ref Ref Ref Ref Ref Ref

Yes 0.014 0.034 0.031 0.034 0.055 0.03

Maternal near miss No Ref Ref Ref Ref Ref Ref

Yes 0.3 0.4 0.5 0.3 0.4 0.4

Foetal presentation 4.1 5.8 6.1 7.5 7 5.7

Sex Male Ref Ref Ref Ref Ref Ref

Female -3.5 -4.7 -3.8 -5 -3.5 -4.1

Macrosomia No Ref Ref Ref Ref Ref Ref

Yes 3.2 4 4.3 4.7 3.9 3.9