Intimate Partner Violence and Maternal Mental health: An Analysis of the Georgia 2016-2020 PRAMS Data
Abstract
As a public health concern, intimate partner violence (IPV) negatively impacts women and their children. The persistence of this phenomenon before and during pregnancy results in several adverse events related to maternal mortality. Maternal mental health (MMH) conditions are common, manageable complications that can happen at any point during pregnancy, childbirth, or in the first year following delivery, with 1 in 5 women affected particularly prevalent among low-income minority women. Perinatal depression affects one in seven women. Unfortunately, 75% of women who experience MMH symptoms are left untreated and while these women face different MMH conditions, 3 in 5 women of color are more vulnerable. These maternal health issues affect over 30,000 Georgian women annually. Research shows that women who experience IPV before and during pregnancy are more likely to have maternal anxiety, maternal depression, or intrusive thoughts. The absence of healthcare providers and services for mental health treatment in Georgia poses serious dangers. This study aims at examining the association between IPV and MMH, how abuse before or during pregnancy, and adequacy of care results in mental health issues.
Research questions are, in Georgia, (a) is there a relationship between IPV and MMH (b)is the Kotel chuck index a significant predictor of mental illness in pregnant women controlling for age, IPV, race, marital status, employment, and education, and (c) does abuse before and during pregnancy result in an increased rate of MMH problems. The 2016-2020 Pregnancy Risk Assessment Monitoring System (PRAMS) secondary data for Georgia from the CDC will be used to design a cross-sectional study to examine the intersection between IPV and MMH.
We intend to use a descriptive/bivariate analysis of the variables, multivariate analyses with binomial logistic regression analysis, and OLS regression on mental health to understand pregnant women’s level of care.
Keywords
Intimate Partner Violence, Maternal Mental Health, Georgia, Maternal Health
Intimate Partner Violence and Maternal Mental health: An Analysis of the Georgia 2016-2020 PRAMS Data
As a public health concern, intimate partner violence (IPV) negatively impacts women and their children. The persistence of this phenomenon before and during pregnancy results in several adverse events related to maternal mortality. Maternal mental health (MMH) conditions are common, manageable complications that can happen at any point during pregnancy, childbirth, or in the first year following delivery, with 1 in 5 women affected particularly prevalent among low-income minority women. Perinatal depression affects one in seven women. Unfortunately, 75% of women who experience MMH symptoms are left untreated and while these women face different MMH conditions, 3 in 5 women of color are more vulnerable. These maternal health issues affect over 30,000 Georgian women annually. Research shows that women who experience IPV before and during pregnancy are more likely to have maternal anxiety, maternal depression, or intrusive thoughts. The absence of healthcare providers and services for mental health treatment in Georgia poses serious dangers. This study aims at examining the association between IPV and MMH, how abuse before or during pregnancy, and adequacy of care results in mental health issues.
Research questions are, in Georgia, (a) is there a relationship between IPV and MMH (b)is the Kotel chuck index a significant predictor of mental illness in pregnant women controlling for age, IPV, race, marital status, employment, and education, and (c) does abuse before and during pregnancy result in an increased rate of MMH problems. The 2016-2020 Pregnancy Risk Assessment Monitoring System (PRAMS) secondary data for Georgia from the CDC will be used to design a cross-sectional study to examine the intersection between IPV and MMH.
We intend to use a descriptive/bivariate analysis of the variables, multivariate analyses with binomial logistic regression analysis, and OLS regression on mental health to understand pregnant women’s level of care.
