Volume 27 - Article 14 | Pages 377–418  

Spatially varying predictors of teenage birth rates among counties in the United States

By Carla Shoff, Tse-Chuan Yang

This article is part of the Special Collection 13 "Spatial Demography"


Background: Limited information is available about teenage pregnancy and childbearing in rural areas, even though approximately 20 percent of the nation’s youth live in rural areas. Identifying whether there are differences in the teenage birth rate (TBR) across metropolitan and nonmetropolitan areas is important because these differences may reflect modifiable ecological-level influences such as education, employment, laws, healthcare infrastructure, and policies that could potentially reduce the TBR.

Objective: The goals of this study are to investigate whether there are spatially varying relationships between the TBR and the independent variables, and if so, whether these associations differ between metropolitan and nonmetropolitan counties.

Methods: We explore the heterogeneity within metropolitan/nonmetropolitan county groups separately using geographically weighted regression (GWR), and investigate the difference between metropolitan/nonmetropolitan counties using spatial regime models with spatial errors. These analyses were applied to county-level data from the National Center for Health Statistics and the US Census Bureau.

Results: GWR results suggested that non-stationarity exists in the associations between TBR and determinants within metropolitan/nonmetropolitan groups. The spatial regime analysis indicated that the effect of socioeconomic disadvantage on TBR significantly varied by the metropolitan status of counties.

Conclusions: While the spatially varying relationships between the TBR and independent variables were found within each metropolitan status of counties, only the magnitude of the impact of the socioeconomic disadvantage index is significantly stronger among metropolitan counties than nonmetropolitan counties. Our findings suggested that place-specific policies for the disadvantaged groups in a county could be implemented to reduce TBR in the US.

Author's Affiliation

Other articles by the same author/authors in Demographic Research

Mapping the results of local statistics: Using geographically weighted regression
Volume 26 - Article 6

Similar articles in Demographic Research

Different places, different stories: A study of the spatial heterogeneity of county-level fertility in China
Volume 37 - Article 16    | Keywords: China, fertility, geographically weighted regression, spatial heterogeneity

Migration signatures across the decades: Net migration by age in U.S. counties, 1950-2010
Volume 32 - Article 38    | Keywords: age, internal migration, net migration, nonmetropolitan, retirement migration, segregation, urbanization

Progress in Spatial Demography
Volume 28 - Article 10    | Keywords: geographically weighted regression, multilevel modeling, pattern analysis, spatial demography, spatial econometrics

Demography, foreclosure, and crime:: Assessing spatial heterogeneity in contemporary models of neighborhood crime rates
Volume 26 - Article 18    | Keywords: criminology, geographically weighted regression

Mapping the results of local statistics: Using geographically weighted regression
Volume 26 - Article 6    | Keywords: geographically weighted regression, local statistics, mapping, nonstationarity