What has geography got to do with it? Using GWR to explore place-specific associations with prenatal care utilization

Abstract

We use a geographically weighted regression (GWR) approach to examine how the relationships between a set of predictors and prenatal care vary across the continental US. At its most fundamental, GWR is an exploratory technique that can facilitate the identification of areas with low prenatal care utilization and help better understand which predictors are associated with prenatal care at specific locations. Our work complements existing prenatal care research in providing an ecological, place-sensitive analysis. We found that the percent of the population who was uninsured was positively associated with the percent of women receiving late or no prenatal care in the global model. The GWR map not only confirmed, but also demonstrated the spatial varying association. Additionally, we found that the number of Ob-Gyn doctors per 100,000 females of childbearing age in a county was associated with the percentage of women receiving late or no prenatal care, and that a higher value of female disadvantage is associated with higher percentages of late or no prenatal care. GWR offers a more nuanced examination of prenatal care and provides empirical evidence in support of locally tailored health policy formation and program implementation, which may improve program effectiveness.

Mapping the results of local statistics

“…In Figure 3 the significant positive parameters estimates are represented by shades of blue, while the significant negative parameter estimates are shades of green. We have used this map design in two prior papers (Chen et al, 2012; Shoff, Yang, and Matthews, forthcoming). …”

“…As an exploratory technique GWR provides a great richness in the results obtained for any spatial data set and should be useful across all disciplines in which spatial data are utilized. Indeed, applications of GWR include studies in a wide variety of demographic fields including but not limited to the analysis of health and disease (Goovaerts, 2005; Nakaya et al, 2005; Yang et al, 2009; Chen et al, 2010), health care delivery (Shoff, Yang, and Matthews, forthcoming), environmental equity (Mennis and Jordan, 2005), housing markets (Fotheringham, Brunsdon, and Charlton, 2002; Yu, Wei, and Wu, 2007), population density and housing (Mennis, 2006), US poverty (Partridge and Rickman, 2005), poverty mapping in Malawi (Benson, Chamberlin, and Rhinehart, 2005), urban poverty (Longley and Tobon, 2004), demography and religion (Jordan, 2006), regional industrialization and development (Huang and Leung, 2002; Yu, 2006), traffic models (Zhao and Park, 2004), the Irish famine (Gregory and Ell, 2005), voting (Calvo and Escolar, 2003) as well as environmental conditions (Foody, 2003). …”

Examining the Spatially Non- Stationary Associations Between the Second Demographic Transition and Infant Mortality: A Poisson GWR Approach

“…GWR is a powerful tool that can be used to investigate spatial non-stationarity and has been proven to also handle spatial dependence inherent to ecological data (Fotheringham et al 2002). GWR has been increasingly used in health studies to unveil the place-specific associations (Chen et al 2010; Edwards et al 2010; Shoff, Yang and Matthews 2011) and we will use this approach to test this final hypothesis.…”

When homogeneity meets heterogeneity: the geographically weighted regression with spatial lag approach to prenatal care utilisation

“…Specifically, we employ an analytic framework where a spatially lagged (SL) effect of the dependent variable is incorporated into the GWR model, which is called GWR-SL. Using this innovative framework, we found evidence to argue that spatial homogeneity is neglected in the study by Shoff et al (2012) and the results are changed after considering the spatially lagged effect of prenatal care utilization. The GWR-SL approach allows us to gain a place-specific understanding of prenatal care utilization in US counties.…”

“… Using geographically weighted regression (GWR), a recent study by Shoff and colleagues (2012) investigated the place-specific risk factors for prenatal care utilization in the US and found that most of the relationships between late or not prenatal care and its determinants are spatially heterogeneous. However, the GWR approach may be subject to the confounding effect of spatial homogeneity.…”