Literature DB >> 23973178

Multivariate Bayesian spatial model of preterm birth and cardiovascular disease among Georgia women: Evidence for life course social determinants of health.

Michael R Kramer1, Rebecca Williamson.   

Abstract

BACKGROUND: There is epidemiologic evidence that women who experience preterm birth (PTB) are at elevated risk for cardiovascular disease (CVD) later in life. Each outcome independently has noted spatial and socioeconomic gradients; we test for spatial structure in the population correlation of the two.
METHODS: Exploratory spatial data analysis and multivariate Bayesian spatial models were fit to describe the spatial correlation of PTB with CVD among women in Georgia counties from 2002 to 2006.
RESULTS: Global Moran's I and local-indicators of spatial association statistics suggest significant co-occurrence of CVD and PTB. Bayesian posterior estimates for multivariate correlation of these outcomes range from r=0.11-0.34 for CVD and PTB. Significant spatial correlation persists with control for county covariates among whites but not blacks.
CONCLUSION: Modest evidence for spatial structure of the ecologic correlation of PTB and women's CVD is consistent with a lifecourse perspective on socially clustered determinants of health.
Copyright © 2013 Elsevier Ltd. All rights reserved.

Entities:  

Keywords:  Bayesian spatial model; CVD; Cardiovascular disease; DIC; Health disparities; LISA; MCAR; PTB; Preterm birth; Social determinants of health; VPTB; cardiovascular disease; deviance information criteria; local indicator of spatial association; multivariate conditional auto-regressive; preterm birth; very preterm birth

Mesh:

Year:  2013        PMID: 23973178     DOI: 10.1016/j.sste.2013.05.002

Source DB:  PubMed          Journal:  Spat Spatiotemporal Epidemiol        ISSN: 1877-5845


  2 in total

Review 1.  The role of social determinants in explaining racial/ethnic disparities in perinatal outcomes.

Authors:  Scott A Lorch; Elizabeth Enlow
Journal:  Pediatr Res       Date:  2015-10-14       Impact factor: 3.756

2.  The bivariate combined model for spatial data analysis.

Authors:  Thomas Neyens; Andrew B Lawson; Russell S Kirby; Christel Faes
Journal:  Stat Med       Date:  2016-02-29       Impact factor: 2.373

  2 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.