Does the Gender Inequality Index Explain the Variation in State Prevalence Rates of Physical Teen Dating Violence Victimization?

Purpose: When the prevalence of physical teen dating violence (TDV) victimization is examined at the state level, significant variation exists; the prevalence ranges from 7.4% in Oklahoma and Vermont to 17.8% in Louisiana. Using U.S. states as the unit of analysis, this study sought to determine whe...

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Main Author: Gressard, Lindsay A.
Format: Others
Published: ScholarWorks @ Georgia State University 2012
Subjects:
Online Access:http://scholarworks.gsu.edu/iph_theses/211
http://scholarworks.gsu.edu/cgi/viewcontent.cgi?article=1224&context=iph_theses
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spelling ndltd-GEORGIA-oai-scholarworks.gsu.edu-iph_theses-12242015-03-17T03:37:08Z Does the Gender Inequality Index Explain the Variation in State Prevalence Rates of Physical Teen Dating Violence Victimization? Gressard, Lindsay A. Purpose: When the prevalence of physical teen dating violence (TDV) victimization is examined at the state level, significant variation exists; the prevalence ranges from 7.4% in Oklahoma and Vermont to 17.8% in Louisiana. Using U.S. states as the unit of analysis, this study sought to determine whether gender inequality is a societal level risk factor for TDV victimization. Method: Data measuring physical TDV victimization were obtained from the 2009 YRBS. To measure the level of gender inequality in each state, the Gender Inequality Index (GII) was calculated using the procedure described in the United Nations’ Human Development Report. Pearson’s correlation coefficients were calculated to determine the association between TDV victimization, the GII, and the indicators of the GII. Results: Of the 40 states included in analyses, the GII was significantly associated with the state prevalence of both total TDV victimization (r=.323, p=.042) and female TDV victimization (r=.353, p=.026). Subsequent to removal of the outlying case of Oklahoma, the GII was also significantly associated with male TDV victimization (r=.366, p=.022). Several individual GII indicators were significantly associated with TDV victimization after removing the outlying case. Ordinary least squares regression was used to create a model for TDV victimization and gender inequality. Conclusion: This is the first study to examine societal level gender inequality as a risk factor for state level TDV victimization using nationally representative data on school youth. As policy-makers implement TDV prevention policy at the state level, further research understanding potential macro-level risk factors is particularly important. 2012-05-11T07:00:00Z text application/pdf http://scholarworks.gsu.edu/iph_theses/211 http://scholarworks.gsu.edu/cgi/viewcontent.cgi?article=1224&context=iph_theses Public Health Theses ScholarWorks @ Georgia State University adolescent dating violence gender inequality risk factor
collection NDLTD
format Others
sources NDLTD
topic adolescent
dating violence
gender inequality
risk factor
spellingShingle adolescent
dating violence
gender inequality
risk factor
Gressard, Lindsay A.
Does the Gender Inequality Index Explain the Variation in State Prevalence Rates of Physical Teen Dating Violence Victimization?
description Purpose: When the prevalence of physical teen dating violence (TDV) victimization is examined at the state level, significant variation exists; the prevalence ranges from 7.4% in Oklahoma and Vermont to 17.8% in Louisiana. Using U.S. states as the unit of analysis, this study sought to determine whether gender inequality is a societal level risk factor for TDV victimization. Method: Data measuring physical TDV victimization were obtained from the 2009 YRBS. To measure the level of gender inequality in each state, the Gender Inequality Index (GII) was calculated using the procedure described in the United Nations’ Human Development Report. Pearson’s correlation coefficients were calculated to determine the association between TDV victimization, the GII, and the indicators of the GII. Results: Of the 40 states included in analyses, the GII was significantly associated with the state prevalence of both total TDV victimization (r=.323, p=.042) and female TDV victimization (r=.353, p=.026). Subsequent to removal of the outlying case of Oklahoma, the GII was also significantly associated with male TDV victimization (r=.366, p=.022). Several individual GII indicators were significantly associated with TDV victimization after removing the outlying case. Ordinary least squares regression was used to create a model for TDV victimization and gender inequality. Conclusion: This is the first study to examine societal level gender inequality as a risk factor for state level TDV victimization using nationally representative data on school youth. As policy-makers implement TDV prevention policy at the state level, further research understanding potential macro-level risk factors is particularly important.
author Gressard, Lindsay A.
author_facet Gressard, Lindsay A.
author_sort Gressard, Lindsay A.
title Does the Gender Inequality Index Explain the Variation in State Prevalence Rates of Physical Teen Dating Violence Victimization?
title_short Does the Gender Inequality Index Explain the Variation in State Prevalence Rates of Physical Teen Dating Violence Victimization?
title_full Does the Gender Inequality Index Explain the Variation in State Prevalence Rates of Physical Teen Dating Violence Victimization?
title_fullStr Does the Gender Inequality Index Explain the Variation in State Prevalence Rates of Physical Teen Dating Violence Victimization?
title_full_unstemmed Does the Gender Inequality Index Explain the Variation in State Prevalence Rates of Physical Teen Dating Violence Victimization?
title_sort does the gender inequality index explain the variation in state prevalence rates of physical teen dating violence victimization?
publisher ScholarWorks @ Georgia State University
publishDate 2012
url http://scholarworks.gsu.edu/iph_theses/211
http://scholarworks.gsu.edu/cgi/viewcontent.cgi?article=1224&context=iph_theses
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