Maternal factors regulating preterm infants' responses to pain and stress while in maternal kangaroo care

The relationship between maternal factors and the response of preterm infants to pain and stress experienced during heel puncture while in maternal kangaroo care was investigated. This descriptive study included 42 mothers and their preterm infants cared for in a neonatal unit. Data were collected in the baseline, procedure, and recovery phases. We measured the neonates' facial actions, sleep and wake states, crying, salivary cortisol levels, and heart rate, in addition to the mothers' behavior, salivary cortisol levels, and mental condition. The influence of the maternal explanatory variables on the neonatal response variables were verified through bivariate analysis, ANOVA, and multiple regression. The mothers' behavior and depression and/or anxiety did not affect the neonates' responses to pain and stress, though the mothers' levels of salivary cortisol before the procedure explained the variance in the neonates' levels of salivary cortisol after the procedure (p=0.036). Additionally, the mothers' baseline levels of salivary cortisol along with the neonates' age explained the variance in the neonates' heart rate (p=0.001). The ability of mothers to regulate their own stress contributed to the infants' responses to pain and stress.

Infant mortality in Brazil, 1980-2000: A spatial panel data analysis

Background: Infant mortality is an important measure of human development, related to the level of welfare of a society. In order to inform public policy, various studies have tried to identify the factors that influence, at an aggregated level, infant mortality. The objective of this paper is to analyze the regional pattern of infant mortality in Brazil, evaluating the effect of infrastructure, socio-economic, and demographic variables to understand its distribution across the country. Methods: Regressions including socio-economic and living conditions variables are conducted in a structure of panel data. More specifically, a spatial panel data model with fixed effects and a spatial error autocorrelation structure is used to help to solve spatial dependence problems. The use of a spatial modeling approach takes into account the potential presence of spillovers between neighboring spatial units. The spatial units considered are Minimum Comparable Areas, defined to provide a consistent definition across Census years. Data are drawn from the 1980, 1991 and 2000 Census of Brazil, and from data collected by the Ministry of Health (DATASUS). In order to identify the influence of health care infrastructure, variables related to the number of public and private hospitals are included. Results: The results indicate that the panel model with spatial effects provides the best fit to the data. The analysis confirms that the provision of health care infrastructure and social policy measures (e. g. improving education attainment) are linked to reduced rates of infant mortality. An original finding concerns the role of spatial effects in the analysis of IMR. Spillover effects associated with health infrastructure and water and sanitation facilities imply that there are regional benefits beyond the unit of analysis. Conclusions: A spatial modeling approach is important to produce reliable estimates in the analysis of panel IMR data. Substantively, this paper contributes to our understanding of the physical and social factors that influence IMR in the case of a developing country.