Home > Publications . Search All . Browse All . Country . Browse PSC Pubs . PSC Report Series

PSC In The News

RSS Feed icon

Miller et al. find benefits of Medicaid for pregnant mothers in 1980s carry over two generations

Starr's findings account for some of the 19% black-white gap in federal sentencing

Frey says suburbs are aging, cities draw millennials

More News

Highlights

Bailey et al. find higher income among children whose parents had access to federal family planning programs in the 1960s and 70s

U-M's campus climate survey results discussed in CHE story

U-M honors James Jackson's groundbreaking work on how race impacts the health of black Americans

U-M is the only public and non-coastal university on Forbes' top-10 list for billionaire production

More Highlights

Next Brown Bag

Mon, Jan 22, 2018, noon: Narayan Sastry

A Review of Spatial Methods in Epidemiology, 2000-2010

Archived Abstract of Former PSC Researcher

Auchincloss, A., S. Gebreab, C. Mair, and Ana V. Diez Roux. 2012. "A Review of Spatial Methods in Epidemiology, 2000-2010." Annual Review of Public Health, 33: 107-122.

Understanding the impact of place on health is a key element of epidemiologic investigation, and numerous tools are being employed for analysis of spatial health-related data. This review documents the huge growth in spatial epidemiology, summarizes the tools that have been employed, and provides in-depth discussion of several methods. Relevant research articles for 2000-2010 from seven epidemiology journals were included if the study utilized a spatial analysis method in primary analysis (n = 207). Results summarized frequency of spatial methods and substantive focus; graphs explored trends over time. The most common spatial methods were distance calculations, spatial aggregation, clustering, spatial smoothing and interpolation, and spatial regression. Proximity measures were predominant and were applied primarily to air quality and climate science and resource access studies. The review concludes by noting emerging areas that are likely to be important to future spatial analysis in public health.

DOI:10.1146/annurev-publhealth-031811-124655 (Full Text)

Browse | Search : All Pubs | Next