Study design
This study was designed as a retrospective cross-sectional study linking data collected as part of a prospective cohort study to geocoded administrative data on violent crime.
Study Setting
This study was conducted in São Paulo, Brazil. Like other LMICs, Brazil has experienced a rapid and mostly unmanaged urbanization process in the past decades, accompanied by large increases in social and economic inequality [31,32]. The rates of homicides in Brazil have been rising steadily over the past years, reaching a record level of 31.6 homicides per 100,000 inhabitants in 2017 [33]. With 10.3 homicides per 100,000 inhabitants, São Paulo municipality had one of the lowest homicide rates in Brazil in 2017 overall, but very high rates in areas of low socioeconomic development [33]. In the Western Region of São Paulo, where this study was conducted, homicide rates ranged in its neighborhoods between 5 and 20 homicides per 100,000 inhabitants [34].
Study Population
The Western Region Birth Cohort (Região Oeste Coorte – ROC-Cohort) enrolled all locally resident infants born at the University Hospital of the School of Medicine of the University of São Paulo between April 1, 2012, and March 31, 2014. A total of 6,207 mother-child pairs were enrolled in the cohort. The cohort is still active, with children currently under the 72 months follow-up.
Data
Hospital electronic birth records were available for all children in the cohort. The electronic medical registry includes birth characteristics such as type of delivery, gestational length, weight at birth, and others. During the postpartum hospital stay, trained interviewers administrated structured questionnaires to collect information on socio-demographic characteristics and health during pregnancy to a subset of mothers. The questionnaire can be found in the Supplementary file 1.
Outcomes
The analysis focused on three adverse birth outcomes: low birth weight (LBW), preterm delivery (PT), and small-for-gestational-age (SGA). Birth weight and length were measured by the Hospital’s neonatology team immediately after birth using standard hospital equipment. Gestational length in weeks was estimated using the New Ballard Score [35]. LBW was defined as birth weight < 2,500 grams, and SGA was defined as weight-for-gestational age < 10th percentile based on the Intergrowth-21th growth reference tables [36].
Exposure – violence in the neighborhood
Data on violence is routinely collected and made publicly available by the Secretariat of Public Safety of the State of São Paulo (www.ssp.sp.gov.br). The system collects detailed information about willful murder, femicide, robbery followed by death, bodily injury followed by death, death resulting from police intervention, suspicious death, fatal vehicle accidents, and mobile theft. Each reported incident record contains the date, time, and address of the crime. Following most of the external violence literature, we focused on violent crime in our analysis, which includes willful murder, robbery followed by death, bodily injury followed by death and death resulting from police intervention, but excludes other crimes such as robberies without injuries.
We extracted data on violent crimes between 2011 and 2014 to cover the pregnancy period of all ROC-Cohort children. The address of each reported crime was geocoded with latitude and longitude coordinates using the ggmap package [37], and a point-layer for each time point (month-year) was generated using R map tools [38]. The maternal residential address was collected at birth and geocoded as an additional point-layer. Each residential address was treated as a centroid point. We then computed the number of crimes within a 1-kilometer spatial buffer by day, month and year. Exposure to violence during pregnancy was estimated as the sum of violent crimes in the first two trimesters of pregnancy. Violence in the third trimester was not considered because total exposure to violence after week 24 of gestation directly depends on gestational length (the outcome variable). Violence exposure during the first two trimesters was then divided into five equally sized quintiles for analysis.
Statistical analyses
We first compute the average number of crimes for each of the exposure quintiles. Next, we tested crude associations of exposure to violence quintiles with each outcome (LBW, SGA, and PT birth). In the fully adjusted multivariable models, we included all covariates highlighted in the extant literature as risk factors for adverse birth outcomes, including maternal age (<20, >=35), educational level, alcohol consumption, diabetes and hypertension during pregnancy, and socioeconomic (SES) index. The construction of a socioeconomic (SES) index was based on the approach proposed by Vyas and Kumaranayake [39], which relies on the use of principal component analysis (PCA) to the selected variables. The SES index variable describes the SES status based on questions about ownership of durables, income, and house characteristics. The resulting SES index was then divided into quintiles - low, medium-low, medium, medium-high, and high SES status. Age was measured as a continuous variable but categorized in the adjusted model to take into account the risks of pregnancy in different ages range (adolescence, adulthood, and after 35 years old).
Given that the postpartum questionnaire was only available for a subsample of children, we initially screened the dataset for missing data and patterns of non-responsiveness in the postpartum questionnaire using t-test and chi-square to test if the assumptions of missing at random (MAR) were met. We implemented multiple imputations by chained equations (MICE) with a fully conditional specification of prediction equations using variables that potentially predicted non-response or the outcome. The MICE method accounts for statistical uncertainty in the imputations, resulting in more plausible imputes, and hence more reliable inferences in complex settings. Further details on these imputations are provided in the Table S1 (Supplementary file 2). All analyses were performed using Stata version 14 [40] and R version 3.6.1 [38].