Background Population-based studies analyzing neonatal deaths in middle-income countries may contribute to design interventions to achieve the Sustainable Development Goals, established by United Nations. This study goal is to analyze the annual trend of neonatal mortality in São Paulo State, Brazil, over a 10-year period and its underlying causes and to identify maternal and neonatal characteristics at birth associated with neonatal mortality. Method A population-based study of births and deaths from 0 to 27 days between 2004 and 2013 in São Paulo State, Brazil, was performed. The annual trend of neonatal mortality rate according to gestational age was analyzed by Poisson or by Negative Binomial Regression models. Basic causes of neonatal death were classified according to ICD-10. Association of maternal demographic variables (block 1), prenatal and delivery care variables (block 2), and neonatal characteristics at birth (block 3) with neonatal mortality was evaluated by Poisson regression analysis adjusted by year of birth. Results Among 6,056,883 live births in São Paulo State during the study period, 48,309 died from 0 to 27 days (neonatal mortality rate: 8.0/1,000 live births). For the whole group and for infants with gestational age 22–27, 28–31, 32–36, 37–41 and ≥ 42 weeks, reduction of neonatal mortality rate was, respectively, 18 %, 15 %, 38 %, 53 %, 31 %, and 58 %. Median time until 50 % of deaths occurred was 3 days. Main basic causes of death were respiratory disorders (25 %), malformations (20 %), infections (17 %), and perinatal asphyxia (7 %). Variables independently associated with neonatal deaths were maternal schooling, prenatal care, parity, newborn sex, 1st minute Apgar, and malformations. Cesarean delivery, compared to vaginal, was protective against neonatal mortality for infants at 22–31 weeks, but it was a risk factor for those with 32–41 weeks. Conclusions Despite the significant decrease in neonatal mortality rate over the 10-year period in São Paulo State, improved access to qualified health care is needed in order to avoid preventable neonatal deaths and increase survival of infants that need more complex levels of assistance.

Background Prematurity and respiratory distress syndrome (RDS) are strongly associated. RDS continues to be an important contributor to neonatal mortality in low- and middle-income countries. This study aimed to identify clusters of preterm live births and RDS-associated neonatal deaths, and their cooccurrence pattern in São Paulo State, Brazil, between 2004 and 2015.  Methods Population-based study of all live births with gestational age ≥ 22 weeks, birthweight ≥ 400 g, without congenital anomalies from mothers living in São Paulo State, Brazil, during 2004–2015. RDS-associated neonatal mortality was defined as deaths < 28 days with ICD-10 codes P22.0 or P28.0. RDS-associated neonatal mortality and preterm live births rates per municipality were submitted to first- and second-order spatial analysis before and after smoothing using local Bayes estimates. Spearman test was applied to identify the correlation pattern between both rates. Results Six hundred forty-five thousand two hundred seventy-six preterm live births and 11,078 RDS-associated neonatal deaths in São Paulo State, Brazil, during the study period were analyzed. After smoothing, a non-random spatial distribution of preterm live births rate (I = 0.78; p = 0.001) and RDS-associated neonatal mortality rate (I = 0.73; p = 0.001) was identified. LISA maps confirmed clusters for both, with a negative correlation (r = -0.24; p = 0.0000). Clusters of high RDS-associated neonatal mortality rates overlapping with clusters of low preterm live births rates were detected. Conclusions Asymmetric cluster distribution of preterm live births and RDS-associated neonatal deaths may be helpful to indicate areas for perinatal healthcare improvement.

Background: In Brazil, secondary data for epidemiology are largely available. However, they are insufficiently prepared for use in research, even when it comes to structured data since they were often designed for other purposes. To date, few publications focus on the process of preparing secondary data. The present findings can help in orienting future research projects that are based on secondary data.Objective: Describe the steps in the process of ensuring the adequacy of a secondary data set for a specific use and to identify the challenges of this process.Methods: The present study is qualitative and reports methodological issues about secondary data use. The study material was comprised of 6,059,454 live births and 73,735 infant death records from 2004 to 2013 of children whose mothers resided in the State of São Paulo - Brazil. The challenges and description of the procedures to ensure data adequacy were undertaken in 6 steps: (1) problem understanding, (2) resource planning, (3) data understanding, (4) data preparation, (5) data validation and (6) data distribution. For each step, procedures, and challenges encountered, and the actions to cope with them and partial results were described. To identify the most labor-intensive tasks in this process, the steps were assessed by adding the number of procedures, challenges, and coping actions. The highest values were assumed to indicate the most critical steps.Results: In total, 22 procedures and 23 actions were needed to deal with the 27 challenges encountered along the process of ensuring the adequacy of the study material for the intended use. The final product was an organized database for a historical cohort study suitable for the intended use. Data understanding and data preparation were identified as the most critical steps, accounting for about 70% of the challenges observed for data using.Conclusion: Significant challenges were encountered in the process of ensuring the adequacy of secondary health data for research use, mainly in the data understanding and data preparation steps. The use of the described steps to approach structured secondary data and the knowledge of the potential challenges along the process may contribute to planning health research.

Background Infant mortality rate is a measure of population health and neonatal mortality account for great proportion of these deaths. Underdevelopment might be associated to higher neonatal mortality risk due to assistant related factors. Spatial and temporal distribution of mortality help identifying and developing strategies for interventions. Objective To investigate the cluster areas of asphyxia-associated neonatal mortality and to explore its association with per capita gross domestic product (GDP) in São Paulo State (SP), Brazil. Methods Ecological study including live births residents in SP from 2004–2013. Neonatal deaths (0–27 days) with perinatal asphyxia were defined as intrauterine hypoxia, birth asphyxia or meconium aspiration syndrome written in any line of the Death Certificate. Geoprocessing analytical approach included detection of first order effects through quintiles and spatial moving average maps, followed by second order effects by global and local spatial autocorrelation (Moran and LISA, respectively) before and after smoothing with local Bayesian estimates. Finally, Spearman correlation was applied between asphyxia-associated neonatal mortality and mean per capita GDP rates for the municipalities with significant LISA. Results There were 6,713 asphyxia-associated neonatal deaths among 5,949,267 live births (rate: 1.13/1000) in SP. Spatial moving average maps showed a non-random distribution among municipalities, with presence of clusters (I = 0.048; p = 0.023). LISA map identified clusters of asphyxia-associated neonatal mortality in the south, southeast and northwest. After applying local Bayes estimates, clusters were more pronounced (I = 0.589; p = 0.001). There was a partial overlap of the areas of higher asphyxia-associated neonatal mortality and lower mean per capita GDP. Conclusions Spatial analysis identified cluster areas of high asphyxia-associated neonatal mortality and low per capita GDP rates, with a significant negative correlation. This optimized, structured, and hierarchical approach to identify high-risk areas of cause-specific neonatal mortality may be helpful for guiding public health efforts to decrease neonatal mortality.

Moderate and late preterm newborns comprise around 85% of live births < 37 weeks gestation. Data on their neonatal mortality in middle-income countries is limited. This study aims to analyze the temporal trend, causes and timing of neonatal mortality of infants with 320/7–366/7 weeks gestation without congenital anomalies from 2004–2015 in the population of São Paulo State, Brazil. A database was built by deterministic linkage of birth and death certificates. Causes of death were classified by ICD-10 codes. Among 7,317,611 live births in the period, there were 545,606 infants with 320/7–366/7 weeks gestation without congenital anomalies, and 5782 of them died between 0 and 27 days. The neonatal mortality rate decreased from 16.4 in 2004 to 7.6 per thousand live births in 2015 (7.47% annual decrease by Prais–Winsten model). Perinatal asphyxia, respiratory disorders and infections were responsible, respectively, for 14%, 27% and 44% of the 5782 deaths. Median time to death was 24, 53 and 168 h, respectively, for perinatal asphyxia, respiratory disorders, and infections. Bottlenecks in perinatal health care are probably associated with the results that indicate the need for policies to reduce preventable neonatal deaths of moderate and late preterm infants in the most developed state of Brazil.