Caesarean section rate

Caesarean section rate

Caesarean section rate

The number of women of reproductive age who delivered by caesarean section (CS) in a specified reference period expressed as a percentage of women in the same age range with a delivery in the same period.

A CS is a delivery of a baby through an incision in the woman’s abdomen and womb, rather than the baby passing through the birth canal.

There are two common data sources for this indicator:

  1. Routinely collected administrative data
  2. Population-based household surveys.

Routinely collected administrative data:

Data from routinely collected and compiled administrative data sources will provide information as recorded in medical charts/records or registers and are entered into national and/or subnational health management information systems (HMIS). Data from health information systems may collect information on CS rates among all women who delivered at a health facility.

Routinely collected administrative data and health facility statistics are the preferred data source in settings with a high utilization of health facility services and where data are recorded in a manner that ensures good data quality for both the public and private health sectors. The compiled data in the national HMIS or District Health Information System (DHIS2) should include data from both public and private health sectors, especially when the private sector is a substantial source of service provision to the population. In settings where utilization of health facilities is not high (e.g. settings with a high prevalence of births occurring at home), data may suffer from incompleteness if information about women delivering outside facilities is not captured. In addition, there are often challenges in accurately measuring the numerator and the denominator when routine HMIS data are used to measure this indicator.

Key source of data: Administrative data sources include health facility and health services data abstracted from obstetric medical records, including health services registers. Relevant information is recorded by health personnel within health facilities on paper forms completed by health personnel and/or through an electronic medical record. Data from paper or electronic sources are entered or abstracted into a database or registry and are compiled and analyzed within the national and/or subnational HMIS. The ministry of health (MoH) and/or national statistical offices (NSO) are usually responsible for reporting this indicator.

Indicator definition and calculation: The indicator is calculated as the percentage of deliveries by CS among all deliveries, irrespective of vital status at birth (live birth and stillbirth), in a health facility during a specified reference period. The indicator calculation is as follows:

(Number of CS in a specified time period / Number of total deliveries in the health facility in a specified time period) x 100

Unless specified, the statistic may include any woman regardless of age and includes both live births and stillbirths, as defined by the health facility and/or national or subnational vital statistics offices.

Frequency of measurement: The indicator can be calculated on an annual basis or may be tracked on a more frequent and ongoing basis (e.g. monthly, quarterly), depending on facility, subnational and national processes for data entry, compilation and analysis. As a guide, the recommended frequency of measurement based on reporting level is outlined below:

  • Facility level: Monthly, quarterly, or as needed based on the country and/or facility need
  • Subnational (first and second administrative) level: Monthly or quarterly
  • National level: Annually (data can be aggregated to provide national-level data).

Disaggregation: By level of facility, location of facility (e.g. urban, rural), subnational administrative units (e.g. districts, provinces, regions), and type of health personnel.

Missing values: Missing values are usually not known or not reported.

Population-based household surveys:

The main source of data for this indicator has been through population-based household surveys collected through nationally or subnationally representative and structured questionnaires, such as:

  • Demographic Health Surveys (DHS) (5)
  • Multiple Indicator Cluster Surveys (MICS) (5)
  • Reproductive Health Surveys (RHS)
  • Other household surveys with a similar methodological design.

Population-based household survey data are the preferred data source in settings where utilization of health facility services is not very high (e.g., settings with a high prevalence of deliveries occurring at home) or where private health sector data are excluded from routinely collected administrative data sources.

Key source of data: Eligible women of reproductive age (15–49 years) are identified in the household survey for inclusion and interviewing using an individual women’s questionnaire. Women are considered eligible for survey interview if they are either usual residents or visitors of the household who stayed there the night before the interview.

All eligible and interviewed women (between 15 and 49 years old) who had a live birth at a health facility during a specified reference period, typically 2–5 years prior to the time of interview, are asked about “Was (NAME) delivered by caesarean, that is, did they cut your belly open to take the baby out?”, where “name” refers to the name of the live birth the individual woman had during the same reference period.

The MoH and NSO typically conduct household surveys and compile, analyze and report the results for this indicator in collaboration with the survey program (e.g. DHS, MICS, RHS) and funding agency.

Indicator definition and calculation: Individual women of reproductive age (15–49 years old) are asked if they delivered their baby by CS at a health facility, irrespective of the child’s current living status (dead or alive), and are for the most recent live birth they had during a specified reference period, which is typically 2–5 years before the time of the survey completion. The definition is as follows:

The percentage of interviewed women (aged 15–49 years) with a live birth in the 2–5 years prior to survey completion whose most recent live birth was delivered by CS.

The indicator is calculated as follows:

(Number of interviewed women [15–49 years old] with a live birth in the 2–5 years prior to survey completion whose most recent live birth was delivered by CS / Total number of interviewed women [aged 15–49 years old] with a live birth in the 2–5 years prior to survey completion) x 100

Frequency of measurement: Household surveys are typically conducted every 3–5 years.

Disaggregation at population level: Type of health personnel, place of delivery (private or public health facility, community), place of residence (e.g. urban, rural), subnational administrative units (e.g. districts, provinces, regions), sex of live birth, birth order, socioeconomic status (e.g. education level, household wealth quintile), age of woman at the time of delivery, births attended by skilled health personnel, total number of antenatal care (ANC) visits and timing of first ANC visit, early breastfeeding initiation, and timing
and location of postnatal care health check.

Missing values: Included in the distribution as “don’t know” or “missing”.

The proportion of CS conducted at the population level is proposed to reflect the accessibility and utilization of services and the functionality of the health system (1). It can serve as a proxy for policy-makers and governments in assessing progress in maternal and infant health and in monitoring emergency obstetric care and resource utilization (2).The appropriate use of a CS leads to a decrease in maternal mortality and morbidity, as well as a decrease in perinatal morbidity and mortality (1–3). However, in large parts of the world CS rates have risen to very high levels and in these settings a large number of CS may not be medically indicated (3).

The CS rate in a geographical area is a measure of access to and use of a common obstetric intervention for averting maternal and neonatal deaths and for preventing complications, such as obstetric fistula (1). Of all the procedures used to treat major obstetric complications, CS is one of the most common, and reporting is relatively reliable. When medically justified, a CS can effectively prevent maternal and perinatal mortality and morbidity (1,2).

While WHO has in the past proposed an “ideal rate” for CS of between 10% and 15% (1,6), more recent recommendations propose that the preferred level set needs to be locally informed by the epidemiological/ demographic pattern in respective countries.

As the proportion of CS increases, the uncertainty between these classifications also increases (1). Rates above 15% suggest overuse of the procedure for non-emergency reasons. However, in many contexts the overuse and underuse of CS coexist, making it difficult – if not impossible – to recommend benchmark levels for optimal CS rates. This is why WHO suggests to review CS rates regularly using the Robson (10-group) classification, where CS can be compared and analyzed within more comparable groups of women (7). The system classifies all women into one of 10 categories based on five basic obstetric characteristics that are routinely collected in all deliveries (parity, number of fetuses, previous CS, onset of labor, gestational age, and fetal presentation) (7).

A CS procedure usually occurs at the end of a complex series of events, possibly including pre-existing and pregnancy-specific medical factors, identification of complications, transportation to health-care facilities, and availability of necessary technology. Excessive use unnecessarily exposes women to anesthesia and surgery with their concomitant risks; moreover, it drains scarce health-care resources (3). When using this indicator, health
program managers and evaluators may also want to employ more in-depth techniques, such as case audits, to investigate what clinical indicators are being used for CS and if the appropriate women are receiving this service. By itself, the indicator reveals nothing about the appropriateness of the procedure.

To reduce the possibility that this indicator will mask inequities in access to and use of CS, evaluators must look closely at their data (1). Rates are often inconsistent and inequities exist between urban and rural environments, public and private sectors, different payment schemes, and/or across administrative areas within a country. Thus, disaggregation of the data is encouraged and national averages need to be interpreted with caution.

Data collected from administrative and other routine data systems:

Administrative data may suffer from poor quality such as irregularities in report generation, data duplication and inconsistencies. Reporting challenges exist at the facility level given data quality issues, including incomplete, inaccurate and lack of timely data due to insufficient capacity in the health system or inadequate system design.

Many HMIS databases or registries are event-based and only include women who delivered a birth at a health facility. In some instances, the denominator may include births delivered by women of an unspecified age range and include both live births and stillbirths. In addition, the definition of a stillbirth varies by country and context, such as differences in inclusion for gestational age (e.g. 20–28 weeks) and birthweight (e.g. ≥ 500 grams). These differences in definitions compromise the ability to compare data between countries.

Administrative data should be interpreted with caution in settings where data quality is poor and the percentage of births at public and private sector health facilities is low, or where data from the private health sector is not compiled within the HMIS reporting.

In settings where routine HMIS data lack information on pregnancies and/or births or deliveries that occur outside the public sector – for example, in private sector facilities, the total number of births in the HMIS should not serve to estimate the denominator for this indicator. Where data on the total numbers of live births for the entire population for the denominator are unavailable, evaluators can calculate total estimated live births using census data for the total population and crude birth rates in a specified area (total expected live births = estimated population x the total crude birth rate).

Data collected through household surveys:

Women may not be able to accurately recall details around childbirth when data are collected through household surveys (4). There is also a time lag as the recall period is up to 2–5 years before the survey data were collected.
The most commonly reported denominator is the number of women with a live birth in the years preceding the survey, which acts as a proxy for the number of pregnant women. This indicator is prone to survivor bias in that only those women who are alive at the time of the interview would be included, and underestimates the total number of deliveries by CS.

For more information on this indicator, see the MoNITOR indication reference sheet developed by the World Health Organization: Who-indicators (

safe motherhood (SM), newborn (NB), emergency, obstetric fistula (OF)

  1. WHO statement on caesarean section rates. Geneva: World Health Organization; 2015 (, accessed 22 October 2020.
  2. Monitoring emergency obstetric care: a handbook. Geneva: World Health Organization; 2009.
  3. Betrán AP, Ye J, Moller AB, Zhang J, Gülmezoglu AM, Torloni MR. The increasing trend in caesarean section rates: global, regional and national estimates: 1990–2014. PLoS One. 2016;11(2):e0148343 (, accessed 22 October 2020.
  4. The DHS Program [website]. Rockville: ICF International; 2020 (, accessed 21 October 2020.
  5. Multiple Indicator Cluster Surveys (MICS) [website]. New York: UNICEF; 2020 (, accessed 21 October 2020.
  6. Caesarean sections should only be performed when medically necessary [news release]. April 9, 2015. In: World Health Organization [website] (, accessed 22 October 2020.
  7. Robson classification: implementation manual. Geneva: World Health Organization; 2017 (, accessed 22 October 2020.

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