Geocoding and Measurement of Neighborhood Socioeconomic Position: A U.S. Perspective

By N. Krieger, S. Zierler, Joseph W. Hogan, Pamela Waterman, Jarvis T. Chen, Kerry Lemieux, A. Gjelsvik. 2003

95 citations recorded by the source corpus.

Subfields: General Health Professions, Health, Transportation

View Paper: https://www.semanticscholar.org/paper/89f88b5bbf8c11ebe712790886a80d9c47ff0b72

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In General Health Professions

1. S. Subramanian
2. Jarvis T. Chen
3. Pamela Waterman
4. N. Krieger
5. David H. Rehkopf
6. C. Gravlee
7. K. Pickett
8. R. Wilkinson

In Health

1. R. Tchernis
2. Joseph W. Hogan
3. S. Subramanian
4. Jarvis T. Chen
5. Pamela Waterman
6. N. Krieger
7. David H. Rehkopf
8. C. Gravlee

In Transportation

1. S. Subramanian

Citations in the corpus

• Bayesian Factor Analysis for Spatially Correlated Data, With Application to Summarizing Area-Level Material Deprivation From Census Data (2004, methodology): “Krieger et al. (2001) described a Townsend index derived from U.S. Census variables, which we use for our analyses in Section 4.”
• Race/ethnicity, gender, and monitoring socioeconomic gradients in health: a comparison of area-based socioeconomic measures--the public health disparities geocoding project. (2003, methodology): “problem of absent or limited socioeconomic data in US public health surveillance systems.(6,12,15,16) In this approach, which draws on multilevel frameworks and area-based measures, both cases (numerators) and the catchment population (denominators) are classified by the socioeconomic characteristic”