Factors associated with preventable infant death: a multiple logistic regression

Abstract

OBJECTIVETo identify and analyze factors associated with preventable child deaths.METHODSThis analytical cross-sectional study had preventable child mortality as dependent variable. From a population of 34,284 live births, we have selected a systematic sample of 4,402 children who did not die compared to 272 children who died from preventable causes during the period studied. The independent variables were analyzed in four hierarchical blocks: sociodemographic factors, the characteristics of the mother, prenatal and delivery care, and health conditions of the patient and neonatal care. We performed a descriptive statistical analysis and estimated multiple hierarchical logistic regression models.RESULTSApproximatelly 35.3% of the deaths could have been prevented with the early diagnosis and treatment of diseases during pregnancy and 26.8% of them could have been prevented with better care conditions for pregnant women.CONCLUSIONSThe following characteristics of the mother are determinant for the higher mortality of children before the first year of life: living in neighborhoods with an average family income lower than four minimum wages, being aged ≤ 19 years, having one or more alive children, having a child with low APGAR level at the fifth minute of life, and having a child with low birth weight.

Spatial analysis of inequalities in fetal and infant mortality due to avoidable causes

“…Additional intersectoral actions could also contribute to health promotion and positive outcomes in maternal and child health (33) . Moreover, issues regarding educational level, family income, access to healthcare services, basic sanitation and living conditions also influence outcomes (17,34) . These determinant factors reflect the greater vulnerability of these mothers to situations of risk and influence fetus and infant survival (17,25,34) .…”

“…Moreover, issues regarding educational level, family income, access to healthcare services, basic sanitation and living conditions also influence outcomes (17,34) . These determinant factors reflect the greater vulnerability of these mothers to situations of risk and influence fetus and infant survival (17,25,34) . In Nigeria, the results of a study analyzing socioeconomic inequalities in infant mortality among groups defined by wealth, maternal educational level and maternal age clearly showed that a significant proportion of infant deaths could have been avoided if socioeconomic inequalities in rates of infant mortality had been eliminated/reduced by appropriate policies (35) .…”

“…Like in other regions, the infant mortality rate found in the study showed a reduction between the analyzed periods. Although the coefficient of infant mortality has decreased in many regions, inequalities persist (34,40) . In Egypt, the analysis of socioeconomic inequalities in infant mortality showed an inverse association between infant mortality rates and standard measures of life, and the poor have the highest preterm infant mortality (40) .…”

Determinants of Infant Mortality in Bhutan: Evidence from the 2012 National Health Survey Data

“…A range of proximal (e.g., health-related factors), intermediate (e.g., water and sanitation), and distal (e.g., education and income) determinants are thought to predict infant and child mortality (Mosley & Chen, 2003). These determinants include breastfeeding (Iram & Butt, 2008;Lamichhane et al, 2017;Reno & Hyder, 2018), baby's birth size and weight (Lamichhane et al, 2017;Memiah et al, 2020;Vidal e Silva et al, 2018), and place and type of delivery (Iram & Butt, 2008;Lamichhane et al, 2017;Memiah et al, 2020). Poor health of newborn (Vidal e Silva et al, 2018), prenatal and postnatal care (Iram & Butt, 2008;Reno & Hyder, 2018), multiple births (Dwomoh et al, 2019;Vidal e Silva et al, 2018), and birth interval (Dwomoh et al, 2019;Lamichhane et al, 2017;Reno & Hyder, 2018) are also found to be associated with infant mortality.…”

“…These determinants include breastfeeding (Iram & Butt, 2008;Lamichhane et al, 2017;Reno & Hyder, 2018), baby's birth size and weight (Lamichhane et al, 2017;Memiah et al, 2020;Vidal e Silva et al, 2018), and place and type of delivery (Iram & Butt, 2008;Lamichhane et al, 2017;Memiah et al, 2020). Poor health of newborn (Vidal e Silva et al, 2018), prenatal and postnatal care (Iram & Butt, 2008;Reno & Hyder, 2018), multiple births (Dwomoh et al, 2019;Vidal e Silva et al, 2018), and birth interval (Dwomoh et al, 2019;Lamichhane et al, 2017;Reno & Hyder, 2018) are also found to be associated with infant mortality. Maternal age and health (Iram & Butt, 2008;Reno & Hyder, 2018;Vidal e Silva et al, 2018), maternal substance use (Reno & Hyder, 2018), education (Andriano & Monden, 2019;Dutta et al, 2020;Iram & Butt, 2008;Reno & Hyder, 2018), poor socioeconomic status (Ezeh et al, 2015;Iram & Butt, 2008;Reno & Hyder, 2018), rural residence and region (Ezeh et al, 2015;Lamichhane et al, 2017), area disadvantage (Reno & Hyder, 2018;Vidal e Silva et al, 2018), and female labor participation or employment (Akinyemi et al, 2018;Scharber, 2014) also predicted child and infant mortality.…”