Measuring Therapeutic Landscapes: Associations between socio-environmental deprivation and cancer survival.

Authors: Daniel Wiese*, Temple University, Department of Geography, Kevin A. Henry, Temple University, Department of Geography, Victor Hugo Gutierrez-Velez, Temple University, Department of Geography, Shannon M. Lynch, Fox Chase Cancer Center
Topics: Medical and Health Geography, Geography and Urban Health, Geographic Information Science and Systems
Keywords: Cancer Survival, Therapeutic Landscape, Socioeconomic Disparities, Geographic Disparities, New Jersey
Session Type: Paper
Presentation File: No File Uploaded


Beyond individual level factors, studies have reported that cancer survival is also influenced by neighborhood-based factors, which can capture social, physical and economic conditions of the environment in which a person lives.

The concept of therapeutic landscapes demonstrates that social and spatial are interconnected, and modification of place can have various effects on human health. This assumes that different types of land cover, their proportion and use could be influential on place perception and emotions.

Combining physical environmental and socio-economic variables may prove useful for quantifying neighborhood quality and measure socio-environmental deprivation. However, with exception of few studies, insufficient attention has been given to integration of socio-environmental perspectives on cancer outcomes. Landscape metrics are common in landscape architecture, are used for urban aesthetics evaluation and were found to be associated with human health outcomes.

The goal of this research was to develop a new neighborhood measure, which includes socioeconomic and environmental characteristics, and to examine its association with cancer survival.

Landscape metrics were derived using the national land cover data set. Census 2010 was used for the extraction of socioeconomic variables. The study population included all New Jersey residents diagnosed with NHL or Colon cancer between 2006 and 2015. Principal component analysis was used for the definition of the socio-environmental deprivation index. Bayesian spatial models were applied to estimate hazard rates, and to examine geospatial disparities before and after adjustment for individual factors (sex, age) and socio-environmental deprivation.

Abstract Information

This abstract is already part of a session. View the session here.

To access contact information login