[Obstetric care and severe pregnancy complications in Latin America and the Caribbean: an analysis of information from demographic health surveys].

OBJECTIVE

To compile, consolidate, and analyze information obtained in surveys conducted by the MEASURE DHS [Demographic and Health Surveys] program, concerning obstetric care and pregnancy complications for women in Latin America and the Caribbean, in the five years before the survey.

METHODS

This exploratory study utilized data from demographic surveys carried out in the 1990s in seven countries of Latin America: Bolivia, Brazil, Colombia, the Dominican Republic, Guatemala, Nicaragua, and Peru. The study describes the characteristics of the women who were interviewed and of the obstetric care that they received in the five years before the respective survey, and it also estimates the occurrence of prolonged labor and of hemorrhagic, hypertensive, and infectious complications in those five years.

RESULTS

The median number of prenatal consultations ranged from 4.7 in Bolivia to 6.6 in the Dominican Republic. More than 40% of deliveries in Guatemala, Peru, and Bolivia were attended by traditional midwives, relatives, or other persons without formal training. The highest rates of deliveries performed in health care facilities (> 90%) were in the Dominican Republic and Brazil. In Guatemala, Peru, and Bolivia more than 45% of deliveries were at home. The highest rate of cesarean delivery was in Brazil (36.4%), and the lowest rates (< 12%) were in Peru and Guatemala. The rate of pregnancy complications reported by the women surveyed was 16.7% in Brazil, 17.9% in Guatemala, 42.1% in Colombia, 42.5% in Nicaragua, 43.0% in the Dominican Republic, 51.7% in Bolivia, and 51.8% in Peru.

CONCLUSION

The reported occurrence of severe pregnancy complications in the surveys we examined was well above the 15% rate reported in other scientific literature, suggesting that these complications may have been overestimated in the MEASURE DHS surveys. Prior validation of the questionnaires used for data collection is extremely important in the generation of high-quality data.