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

DEVELOPING COMPOSITE AREA-LEVEL INDICATORS OF SOCIOECONOMIC POSITION FOR PITTSBURGH, PENNSYLVANIA

Doebler, Donna Charissa Almario (2009) DEVELOPING COMPOSITE AREA-LEVEL INDICATORS OF SOCIOECONOMIC POSITION FOR PITTSBURGH, PENNSYLVANIA. Master's Thesis, University of Pittsburgh. (Unpublished)

[img]
Preview
PDF
Primary Text

Download (6MB) | Preview

Abstract

Objective: To develop a process to construct composite area-level indicators of socioeconomic position (SEP) from existing SEP measures and examine how well they predict the proportion of low birth weight (LBW) infants in Pittsburgh, Pennsylvania. Methodology: Twelve existing measures of SEP were derived from U.S. Census 2000 and constructed at block group (BG) and neighborhood (NB) levels. Geocoded individual-level LBW data were obtained from Allegheny County Birth Registry (2003-2006) and aggregated to BG level for Pittsburgh. The indicator development process included multilevel data exploration (boxplots, variance decomposition, mapping, and examining correlations), exploratory multilevel factor analysis (MFA), and model selection. Multilevel linear regression (MLR) and diagnostic tests were used to examine whether indicators of SEP predicted LBW. Results: MFA identified two BG-level factors: "material and economic deprivation" (MEDij, mean=29.8, variance=184.8), representing percentage of individuals or households not owning a car, renting their residence, in poverty, receiving public assistance, and earning low income; and "concentrated disadvantage" (CDij, mean=15.7, variance=164.4), representing percentage of Blacks, single-headed families, having family members under 18 years old, and receiving public assistance. At NB level, all 12 SEP measures were captured in one factor, "overall neighborhood deprivation" (ONDj, mean=29.3, variance =115.9). MLR identified significant associations between both ONDj and MEDij and LBW: a unit increase in ONDj was associated with 0.003 increase in LBW infants (p<0.001), and a unit increase in MEDij was associated with 0.0018 increase (p<0.01). The association between CDij and LBW was moderated by ONDj (p=0.017): in NBs with high ONDj, LBW increased as CDij increased, while in NBs with low ONDj, LBW decreased as CDij increased. This result suggests that lower levels of ONDj may ameliorate the effects of high CDij at the BG level in Pittsburgh. Conclusion: The study outlines a novel approach to examining area-level associations between SEP and health by utilizing MFA to develop BG and NB composite SEP measures; this approach has not been reported in previous neighborhood research. An important public health implication is that these methods facilitate a closer examination of the mechanisms by which SEP at different area-levels could impact health.


Share

Citation/Export:
Social Networking:
Share |

Details

Item Type: University of Pittsburgh ETD
Status: Unpublished
Creators/Authors:
CreatorsEmailPitt UsernameORCID
Doebler, Donna Charissa Almariodoalmario@gmail.com
ETD Committee:
TitleMemberEmail AddressPitt UsernameORCID
Committee ChairStone, Roslyn AROSLYN@pitt.eduROSLYN
Committee MemberKim, Kevin Hkhkim@pitt.eduKHKIM
Committee MemberSharma, Ravi Kks1946@pitt.eduKS1946
Committee MemberThomas, Stephen Bsbthomas@pitt.eduSBTHOMAS
Date: 29 September 2009
Date Type: Completion
Defense Date: 17 July 2009
Approval Date: 29 September 2009
Submission Date: 1 August 2009
Access Restriction: No restriction; Release the ETD for access worldwide immediately.
Institution: University of Pittsburgh
Schools and Programs: Graduate School of Public Health > Biostatistics
Degree: MS - Master of Science
Thesis Type: Master's Thesis
Refereed: Yes
Uncontrolled Keywords: ADVERSE BIRTH OUTCOMES; CONTEXTUAL FACTORS; MULTIVARIATE STATISTICAL ANALYSIS
Other ID: http://etd.library.pitt.edu/ETD/available/etd-08012009-221605/, etd-08012009-221605
Date Deposited: 10 Nov 2011 19:56
Last Modified: 15 Nov 2016 13:47
URI: http://d-scholarship.pitt.edu/id/eprint/8808

Metrics

Monthly Views for the past 3 years

Plum Analytics


Actions (login required)

View Item View Item