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Measuring socioeconomic adversity in early life.


ABSTRACT: AIM:Early life adversity leads to enduring effects on physical and mental health, school performance and other outcomes. We sought to identify potentially modifiable factors associated with socioeconomic adversity in early life. METHODS:We enrolled 1503 pregnant women aged 16-40 years, without pregnancy complications or pre-existing conditions from Shelby County, Tennessee. Social, familial and economic variables were analysed using principal components (PCs) analyses to generate the Socioeconomic Adversity Index (SAI). This was replicated using the National Survey of Children's Health (NSCH). Health and social outcomes were compared across the quintile groups defined by SAI values at the county, state and national levels. RESULTS:Significant differences occurred across the SAI Quintile-1 to Quintile-5 groups in marital status, household structure, annual income, education and health insurance. Significantly worse health and social outcomes occurred in the lower versus higher SAI quintiles, including maternal depression, parental incarceration, child's birthweight and potential for child abuse. Maternal age and race also differed significantly across the SAI quintiles. CONCLUSION:Modifiable factors contributing to socioeconomic adversity in early life included marital status, household structure, annual income, education and health insurance. Those exposed to greater socioeconomic adversity as defined by SAI values had significantly worse maternal and child outcomes.

SUBMITTER: Anand KJS 

PROVIDER: S-EPMC6584079 | biostudies-literature | 2019 Jul

REPOSITORIES: biostudies-literature

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<h4>Aim</h4>Early life adversity leads to enduring effects on physical and mental health, school performance and other outcomes. We sought to identify potentially modifiable factors associated with socioeconomic adversity in early life.<h4>Methods</h4>We enrolled 1503 pregnant women aged 16-40 years, without pregnancy complications or pre-existing conditions from Shelby County, Tennessee. Social, familial and economic variables were analysed using principal components (PCs) analyses to generate  ...[more]

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