Cesarean Delivery in Uganda: A Mixed Methods Study

Recent data indicate that 1 in 5 women worldwide undergo Caesarean sections (CS) and in most regions CS rates are increasing. Sub-Saharan Africa has the lowest CS rate at 3.5%, compared to a global average of 19.1%. However, there is emerging evidence for a double burden in low-income countries, with low national CS rates masking both overuse and underuse. While national CS rates may remain stagnant, disaggregation by wealth, location, and education level reveal disparities in rate.

The purpose of this study is to understand the Caesarean delivery in Uganda by examining CS rates, factors associated with CS and maternal and neonatal outcomes across institutions using the Robson classification.

Caesarean sections (CS) are an essential component of obstetric care and the most common surgical procedures performed in women. At the population level, the ideal CS rate is challenging to determine, however, in the past the World Health Organization has recommended a national population level rate of 10-15% and more recently updated its recommendation to state that no benefit is seen in maternal and neonatal mortality above this population level rate.

Recent data indicate that 1 in 5 women worldwide undergo CS and in most regions worldwide CS rates are increasing. However, stark disparities exist globally with national rates ranging from as low as 1.4% in Niger to as high as 56.4% in the Dominican Republic. At the regional level, sub-Saharan Africa (SSA) has the lowest CS rate at 3.5% (compared to a global average of 19.1%) and over the last two decades demonstrated the least increases in this rate.

There is, however, emerging evidence for a double burden in low income countries, with low national CS rates masking both overuse and underuse. While national CS rates may remain stagnant, disaggregation by wealth, location, and education level reveal disparities in rate. In Uganda, for example, national CS rates remain low with a national rate of 6% in 2016, up from 3% in 2006, indicating that at the national level there is likely a lack of access to CS for many women in need of this procedure. However, disaggregation by wealth reveals rates of 3% in the in the poorest fifth of the population in compared to 15 % in the richest fifth; 5% in rural vs 11% in urban and 3-8% among less educated compared to 22% in more educated women. There is also striking variation in CS rates in hospitals of the same cadre. For example, Nsambya Hospital has a CS rate of 50.3% compared to Gulu regional referral hospital with a CS rate of 12.3%. Moreover, strikingly higher rates of CS are seen in some private institutions. In recent newspaper publications, some national newspaper reports, some private institutions are cited as having CS rates as high as 70%.

Benchmarking of CS rates between facilities and across time can help demonstrate where CS rates may not be optimal (either underuse or overuse) and provide the basis to motivate change. The Robson Classification has been recommended by both the WHO and the International Federation of Gynaecology and Obstetrics (FIGO) as a global standard for assessing, monitoring, and comparing c-section rates within heath care facilities, over time and between facilities. In this system, deliveries are categorized into 10 groups based on obstetric history, onset of labour, fetal presentation, number of neonates and gestational age. This system benefits from parameters that are prospective, mutually exclusive, and totally inclusive. There are a few studies using the Robson Classification to understand facility-based rates in SSA, however to date, none have been in Uganda.

In this study, our goal is to examine CS rates using the Robson classification through a cross-Sectional Clinical Record Review of women delivering at regional referral hospitals (RRHs) and large private non-profit hospitals (PNFPs) in Uganda.

Eligibility Criteria:
Inclusion Criteria:

* Delivery at a regional referral hospital or private not for profit hospital participating in the study

Exclusion Criteria:

* none