RESUMO
OBJECTIVE: To generate a global reference for caesarean section (CS) rates at health facilities. DESIGN: Cross-sectional study. SETTING: Health facilities from 43 countries. POPULATION/SAMPLE: Thirty eight thousand three hundred and twenty-four women giving birth from 22 countries for model building and 10,045,875 women giving birth from 43 countries for model testing. METHODS: We hypothesised that mathematical models could determine the relationship between clinical-obstetric characteristics and CS. These models generated probabilities of CS that could be compared with the observed CS rates. We devised a three-step approach to generate the global benchmark of CS rates at health facilities: creation of a multi-country reference population, building mathematical models, and testing these models. MAIN OUTCOME MEASURES: Area under the ROC curves, diagnostic odds ratio, expected CS rate, observed CS rate. RESULTS: According to the different versions of the model, areas under the ROC curves suggested a good discriminatory capacity of C-Model, with summary estimates ranging from 0.832 to 0.844. The C-Model was able to generate expected CS rates adjusted for the case-mix of the obstetric population. We have also prepared an e-calculator to facilitate use of C-Model (www.who.int/reproductivehealth/publications/maternal_perinatal_health/c-model/en/). CONCLUSIONS: This article describes the development of a global reference for CS rates. Based on maternal characteristics, this tool was able to generate an individualised expected CS rate for health facilities or groups of health facilities. With C-Model, obstetric teams, health system managers, health facilities, health insurance companies, and governments can produce a customised reference CS rate for assessing use (and overuse) of CS. TWEETABLE ABSTRACT: The C-Model provides a customized benchmark for caesarean section rates in health facilities and systems.
Assuntos
Cesárea/estatística & dados numéricos , Modelos Estatísticos , Adulto , Estudos Transversais , Feminino , Humanos , Internacionalidade , Gravidez , Valores de ReferênciaRESUMO
We conducted a systematic review and meta-analysis of population-based cohort studies of maternal body mass index (BMI) and risk of adverse birth and health outcomes in low- and middle-income countries. PubMed, Embase, CINAHL and the British Nursing Index were searched from inception to February 2014. Forty-two studies were included. Our study found that maternal underweight was significantly associated with higher risk of preterm birth (odds ratio [OR], 1.13; 95% confidence interval [CI], 1.01-1.27), low birthweight (OR, 1.66; 95% CI, 1.50-1.84) and small for gestational age (OR, 1.85; 95% CI, 1.69-2.02). Compared with mothers with normal BMI, overweight or obese mothers were at increased odds of gestational diabetes, pregnancy-induced hypertension, pre-eclampsia, caesarean delivery and post-partum haemorrhage. The population-attributable risk (PAR) indicated that if women were entirely unexposed to overweight or obesity during the pre-pregnancy or early pregnancy period, 14% to 35% fewer women would develop gestational diabetes, pre-eclampsia or pregnancy-induced hypertension in Brazil, China, India, Iran or Thailand. The highest PAR of low birthweight attributable to maternal underweight was found in Iran (20%), followed by India (18%), Thailand (10%) and China (8%). Treatment and prevention of maternal underweight, overweight or obesity may help reduce the burden on maternal and child health in developing countries.