Spatio-temporal patterning of small area low birth weight incidence and its correlates: a latent spatial structure approach

Spat Spatiotemporal Epidemiol. 2011 Dec;2(4):265-71. doi: 10.1016/j.sste.2011.07.011.

Abstract

Low birth weight (LBW) defined as infant weight at birth of less than 2500 g is a useful health outcome for exploring spatio-temporal variation and the role of covariates. LBW is a key measure of population health used by local, national and international health organizations. Yet its spatio-temporal patterns and their dependence structures are poorly understood. In this study we examine the use of flexible latent structure models for the analysis of spatio-temporal variation in LBW. Beyond the explanatory capabilities of well-known predictors, we observe spatio-temporal effects, which are not directly observable using conventional modeling approaches. Our analysis shows that for county-level counts of LBW in Georgia and South Carolina the proportion of black population is a positive risk factor while high-income is a negative risk factor. Two dominant residual temporal components are also estimated. Finally our proposed method provides a better goodness-of-fit to these data than the conventional space–time models.

Keywords: latent structure; low birth weight; small area; socioeconomic; spatial; temporal.

Publication types

  • Research Support, N.I.H., Extramural

MeSH terms

  • Black or African American / statistics & numerical data*
  • Female
  • Georgia / epidemiology
  • Humans
  • Incidence
  • Infant, Low Birth Weight*
  • Infant, Newborn
  • Infant, Premature*
  • Mathematical Computing
  • Poisson Distribution
  • Poverty / statistics & numerical data*
  • Pregnancy
  • Premature Birth / epidemiology*
  • Risk Factors
  • South Carolina / epidemiology
  • Spatio-Temporal Analysis*