Pre-term associated factors en Campina Grande/PB, Brazil: a case control study

Abstract

Pre-term births are one of the main causes of perinatal mortality and morbidity in both developed and underdeveloped countries, and an important risk-factor for problems in infancy and latter years. The factors that have been identified as being part of the pre-term birth causal chain are related to biological and mothers reproductive history, social and economic conditions, pre-natal care, fetus characteristics and delivery care. Today, emphasis is on the comprehension of the complex multifactorial processes. Pre-term births have been increasing in the last decades in many countries, and in spite of research, the reasons for this are not at all clear. Besides the important reproductive population changes an important factor may be changes in obstetric pratices. In poor countries infectious diseases (HIV, malaria, tbc) and malnutrition may be acting as factors.In brazil, pre-term births proportions follow global tendencies. Two population based studies indicate an increase of 7,2% to 13,3% between 1979 and 1994 in Ribeirão Preto (SP) and 6,3% to 14,7% in Pelotas (RS). In the Northeast area, population based study in 1997/98 indicated a proportion of 12,7% pre-term births. Studies based on Birth Registration health information system (SINASC) obtained much lower values. There are few national studies on pre-term risk factors, predominating studies in the more affluent South and Southeast regions. This research project proposes the same methodology of a research project in Londrina (PR), financed by FAPESP in 2005-2007. In this way, it will be possible to compare context and pre-term risk factors in two very distinct realities, two cities in the South and Northeast region. The study is based on a case-control epidemiological design. Based on the statistical results of the initial project, 394 pre-term newborns, cases, will be studied, and 394, controls, will be sampled from the term births (>37 weeks gestation). This sample size will allow ORs as low as 1,7 to be estimated for exposure variables with a prevalence of 15% in controls. Data for maternal, biological, socio-economic, reproductive, emotional and health care variables will be obtained with a validated questionnaire and mother's interview in hospital. Data will also be collected from hospital clinical files. A data base will be developed and after data validating procedures, multivariate statistical analysis will be applied with a hierarchical model based on a theoretical causal model. (AU)