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A Multilevel Analysis of Neighborhood Socioeconomic Effect on Preterm Births in Georgia, USA

This study estimates the neighborhood socioeconomic status (SES) effect on the risk of preterm birth (PTB) using multilevel regression (MLR) models. Birth data retrieved from year 2000 and 2010 Georgia Vital Records were linked to their respective census tracts. Principle component analysis (PCA) wa...

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Autores principales: Tu, Wei, Tu, Jun, Tedders, Stuart
Formato: Online Artículo Texto
Lenguaje:English
Publicado: AIMS Press 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5690432/
https://www.ncbi.nlm.nih.gov/pubmed/29546128
http://dx.doi.org/10.3934/publichealth.2015.4.638
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author Tu, Wei
Tu, Jun
Tedders, Stuart
author_facet Tu, Wei
Tu, Jun
Tedders, Stuart
author_sort Tu, Wei
collection PubMed
description This study estimates the neighborhood socioeconomic status (SES) effect on the risk of preterm birth (PTB) using multilevel regression (MLR) models. Birth data retrieved from year 2000 and 2010 Georgia Vital Records were linked to their respective census tracts. Principle component analysis (PCA) was performed on nine selected census variables and the first two principal components (Fac1 and Fac2) were used to represent the neighborhood-level SES in the MLR models. Two-level random intercept MLR models were specified using 122,744 and 112,578 live and singleton births at the individual level and 1613 and 1952 census tracts at the neighborhood level, for 2000 and 2010, respectively. After adjustment for individual level factors, Fac1, which represents disadvantaged SES, respectively generated an Odds Ratio of 1.056 (95% CI: 1.031–1.081) and 1.080 (95% CI: 1.056–1.105) for these two years, showing a modest but statistically significant effect on PTB. After adjusting for individual level factors and the census tract level factors, Intra-class correlation (ICC) was 1.2% and 1.4%, for year 2000 and 2010, respectively. The two IOR-80% intervals, 0.73–1.52 (year 2000) and 0.73–1.59 (year 2010) suggest large unexplained between census tract variation. The Median Odds Ratio (MOR) value of 1.21(year 2000) and 1.23 (year 2010) revealed that the un-modeled neighborhood effect was smaller than two individual-level predictor variables, race, and tobacco use but larger than the fixed effect of census tract-level predicting variable, Fac1 and all the other individual level factors. Overall, better census tract level SES was found to have a modest protective effect for PTB risk and the effects of the two examined years were similar. Large unexplained between census tract heterogeneity warrants more sophisticated MLR models to further investigate the PTB risk factors and their interactions at both individual and neighborhood levels.
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spelling pubmed-56904322018-03-15 A Multilevel Analysis of Neighborhood Socioeconomic Effect on Preterm Births in Georgia, USA Tu, Wei Tu, Jun Tedders, Stuart AIMS Public Health Research Article This study estimates the neighborhood socioeconomic status (SES) effect on the risk of preterm birth (PTB) using multilevel regression (MLR) models. Birth data retrieved from year 2000 and 2010 Georgia Vital Records were linked to their respective census tracts. Principle component analysis (PCA) was performed on nine selected census variables and the first two principal components (Fac1 and Fac2) were used to represent the neighborhood-level SES in the MLR models. Two-level random intercept MLR models were specified using 122,744 and 112,578 live and singleton births at the individual level and 1613 and 1952 census tracts at the neighborhood level, for 2000 and 2010, respectively. After adjustment for individual level factors, Fac1, which represents disadvantaged SES, respectively generated an Odds Ratio of 1.056 (95% CI: 1.031–1.081) and 1.080 (95% CI: 1.056–1.105) for these two years, showing a modest but statistically significant effect on PTB. After adjusting for individual level factors and the census tract level factors, Intra-class correlation (ICC) was 1.2% and 1.4%, for year 2000 and 2010, respectively. The two IOR-80% intervals, 0.73–1.52 (year 2000) and 0.73–1.59 (year 2010) suggest large unexplained between census tract variation. The Median Odds Ratio (MOR) value of 1.21(year 2000) and 1.23 (year 2010) revealed that the un-modeled neighborhood effect was smaller than two individual-level predictor variables, race, and tobacco use but larger than the fixed effect of census tract-level predicting variable, Fac1 and all the other individual level factors. Overall, better census tract level SES was found to have a modest protective effect for PTB risk and the effects of the two examined years were similar. Large unexplained between census tract heterogeneity warrants more sophisticated MLR models to further investigate the PTB risk factors and their interactions at both individual and neighborhood levels. AIMS Press 2015-09-22 /pmc/articles/PMC5690432/ /pubmed/29546128 http://dx.doi.org/10.3934/publichealth.2015.4.638 Text en © 2015 Wei Tu, Jun Tu, and Stuart Tedders, licensee AIMS Press This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0)
spellingShingle Research Article
Tu, Wei
Tu, Jun
Tedders, Stuart
A Multilevel Analysis of Neighborhood Socioeconomic Effect on Preterm Births in Georgia, USA
title A Multilevel Analysis of Neighborhood Socioeconomic Effect on Preterm Births in Georgia, USA
title_full A Multilevel Analysis of Neighborhood Socioeconomic Effect on Preterm Births in Georgia, USA
title_fullStr A Multilevel Analysis of Neighborhood Socioeconomic Effect on Preterm Births in Georgia, USA
title_full_unstemmed A Multilevel Analysis of Neighborhood Socioeconomic Effect on Preterm Births in Georgia, USA
title_short A Multilevel Analysis of Neighborhood Socioeconomic Effect on Preterm Births in Georgia, USA
title_sort multilevel analysis of neighborhood socioeconomic effect on preterm births in georgia, usa
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5690432/
https://www.ncbi.nlm.nih.gov/pubmed/29546128
http://dx.doi.org/10.3934/publichealth.2015.4.638
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