Link to the University of Pittsburgh Homepage
Link to the University Library System Homepage Link to the Contact Us Form

Maternal sources of stress within her combined individual and neighborhood environment and the risk of preeclampsia

Blum, Ethan (2016) Maternal sources of stress within her combined individual and neighborhood environment and the risk of preeclampsia. Master's Thesis, University of Pittsburgh. (Unpublished)

Submitted Version

Download (722kB)


Preeclampsia is one of the leading contributors to morbidity and mortality for both the mother and fetus. Risk factors include African-American ancestry, obesity, and high levels of allostatic load. Low socioeconomic status is associated with high allostatic load. We assessed the relationship between socioeconomic status and race in efforts to obtain an accurate estimation of the African-American risk of preeclampsia. This study is significant to public health because it may identify reasons behind the differences in preeclampsia risk of preeclampsia between African-American women and Caucasian women to reveal points of intervention to reduce this risk. Nulliparous Pittsburgh women who delivered singleton births at UPMC Magee Women 19s Hospital between Jan 1st 2007-Dec 31st 2014 were randomly sampled. Women with preexisting hypertension, diabetes, and thyroid disorder were excluded. Our final sample consisted of 527 cases and 1713 controls. We created multi-level regression models to assess the risk of preeclampsia. We included neighborhood level information provided by the 2009-2013 American Community Survey, 2000, Decennial Census, and other Pittsburgh-wide organizations. UPMC Magee-Women 19s Hospital Obstetrical Maternal and Infant database provided individual level indicators. The neighborhood indicators included; percentage of households on SNAP, poverty rate, unemployment, median household income, percent greenery, crime rate, and economic and demographic growth between 2000-2009. Together these multi-level models could potentially illuminate the driving forces behind both neighborhood characteristics and individual qualities on the observed racial disparities in preeclampsia. Univariate analysis showed that African-Americans were more likely to have preeclampsia than Caucasians. When applying a multi-level model, the African-Americans odds decreased 16%. Under conditional regressions where neighborhoods were matched on similar quartiles of SNAP, poverty status, unemployment, and median household income, African-Americans odds of preeclampsia declined by 39-41%. The matched analysis explained more of the variability in risk of preeclampsia that was independent of race. Analysis of African-Americans compared to Caucasians indicated disparities among several neighborhood-level indicators. We discovered that the inclusion of the neighborhood environment explained some of the African-American risk of preeclampsia. We also noticed neighborhood-level disparities between Caucasians and African-Americans in Pittsburgh. We speculate the frequency of preeclampsia in African-Americans may be reduced by lowering these economic disparities.


Social Networking:
Share |


Item Type: University of Pittsburgh ETD
Status: Unpublished
CreatorsEmailPitt UsernameORCID
Blum, Ethanesb32@pitt.eduESB32
ETD Committee:
TitleMemberEmail AddressPitt UsernameORCID
Committee ChairAdibi, Jenniferadibij@pitt.eduADIBIJ
Committee MemberMendez, Daraddm11@pitt.eduDDM11
Committee MemberRoberts, Jamesjroberts@mwri.magee.eduJROBERTS
Date: 29 June 2016
Date Type: Publication
Defense Date: 11 April 2016
Approval Date: 29 June 2016
Submission Date: 27 April 2016
Access Restriction: 2 year -- Restrict access to University of Pittsburgh for a period of 2 years.
Number of Pages: 53
Institution: University of Pittsburgh
Schools and Programs: School of Public Health > Epidemiology
Degree: MS - Master of Science
Thesis Type: Master's Thesis
Refereed: Yes
Uncontrolled Keywords: multi-level model, socioeconomic status, SES, preeclampisa, disparity, African-American
Date Deposited: 29 Jun 2016 17:54
Last Modified: 01 May 2018 05:15


Monthly Views for the past 3 years

Plum Analytics

Actions (login required)

View Item View Item