Study design
This prospective cohort study used data from birth cohorts - BRISA (Brazilian Birth Cohort Studies) [9], registered between February 2010 and June 2011 (started in prenatal care – 22 to 25 weeks of gestation), at birth and follow-up in 2012/2013. This study used the cohort of the municipality of São Luís, Maranhão, Brazil (Da Silva, 2014).
Study population and sampling
The study population consisted of 1,447 women in the prenatal cohort, of which 1,381 were re-interviewed within 24 h postpartum (Da Silva, 2014). Observations with no response in the exposure (violence), outcome (perinatal outcomes), and mediation (depression) variable were excluded from the sample, thus totaling 1,130 mother/newborn pairs.
Data collection
Data was collected in two moments: prenatal care and birth, by interviews with application of structured questionnaires by properly trained personnel. The women were contacted at ultrasound and prenatal clinics and invited to participate in the study (Da Silva, 2014).
Exposure variable
Violence against women was assessed using the World Health Organization Violence against Women instrument [18, 19], self-applied between the 22nd and 25th weeks of gestation. It consists of 26 questions, asking whether the woman has experienced violence during her current pregnancy and in the 12 months prior to pregnancy, including psychological, physical, and sexual violence.
Our analysis included violence during pregnancy (physical, psychological or sexual), physical violence during pregnancy, and psychological violence during pregnancy, assessed as “Yes” or “No.”
Mediation variable
To identify depressive symptoms during pregnancy, we used the Center for Epidemiologic Studies Depression Scale (CES-D) [20], assessing the frequency of depressive symptoms experienced in the week prior to the interview (0 = Rarely – less than 1 day; 1 = for a short time – 1 or 2 days; 2 = during a moderate time – 3 to 4 days; 3 = during most of the time – from 5 to 7 days). For the analysis, depressive symptoms were considered as a continuous variable (final score ranging from 0 to 60 points).
Outcome variables
Birth weight (BW): birth weight (kg) was obtained from medical records.
Gestational age at birth (GA): was considered as the complete weeks of gestation, calculated from the last normal menstrual period (LNMP) reported by the mother. Day 15 was imputed for all cases with unknown LNMP day. Cases with less than 20 and over 43 weeks were recoded as missing. Cases with missing GA were imputed in a regression model containing birth weight, parity, per capita monthly family income, and newborn sex [21, 22].
Intrauterine growth restriction (IUGR)
IUGR was defined by the birth weight ratio [23], which classifies as having intrauterine growth restriction newborns with values below 0.85. This ratio is calculated by dividing the newborn’s weight by the weight corresponding to the 50th percentile of the weight-for-gestational-age curve.
Complementary variables
For adjustment, we included the following variables: mother’s age (years), number of children (continuous), maternal education (0–4, 5–8, 9–11, and 12 or more years), maternal occupation (manual labor, non-manual labor, does not work), monthly family income in minimum wage (R$ 510.00 in 2010), pregnancy planning (yes/no) and economic classification (A/B, C, D/E [24] – categories A and B having the highest spending power) [24]. To define the socioeconomic classification, the Brazilian Economic Classification Criteria, CEB, was used, which is a standard of socioeconomic classification, based on households. It consists of a way of measuring the purchasing power of the population. Thus, it is possible to segment individuals into classes. The parameter considers aspects such as the physical structure of the residence, consumer goods and education of the head of the family. The categories are classified according to the minimum wage, thus A (above 20 minimum wages), B (10 to 20 wages), C (4 to 10 wages), D (2 to 4 wages) and E (Up to 2 wages).
To describe the study sample, we included the variables: skin color/ethnicity (white, Asian, brown/mixed race, black), marital status (married, domestic partnership, single, separated, widowed), and type of delivery (cesarean, forceps, normal).
Data analysis
The sample was characterized by means of descriptive analyses (absolute and relative frequencies, mean, and standard deviation).
We also performed moderated mediation analysis (conditional process modeling), which occurs when the effect of the exposure on the outcome by a mediating variable changes depending on the levels of the moderating variable. Violence against women during pregnancy was considered as a possible moderator of the mediating relationship between depression during pregnancy and perinatal outcomes (Fig. 1).
To obtain the effects of the conditional process, we estimated three models according to type of violence (violence during pregnancy regardless of type, physical violence during pregnancy, and psychological violence during pregnancy) for each of the perinatal outcomes independently.
Bootstrapped confidence intervals (BCI) of the indirect effect were set at 95%, with a 0.05 confidence level [25]. We estimated the hypothesized conditional process model, specifying the effects of moderated mediation. The conditional process model was estimated using the R program with the interaction and mediation packages.
Ethical aspects
This project met the criteria of the National Health Council Resolution No. 196/1996 and its complementary regulations. It was approved by the Research Ethics Committee of the University Hospital of UFMA under opinion No. 223/2009, protocol: 4771/2008-30. The interviewees were invited to participate in the research. Those who agreed signed the informed consent form (ICF).