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Towards Systematic Methods in an Era of Big Data: Neighborhood Wide Association Studies

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Geospatial Approaches to Energy Balance and Breast Cancer

Part of the book series: Energy Balance and Cancer ((EBAC,volume 15))

Abstract

Methodologic challenges related to variable selection exist in neighborhood studies. In the era of “Big Data”, this variable selection issue will only continue to grow as neighborhood data become increasingly more complex and integrated with multilevel data. To allow for consistency and comparability of neighborhood variables across studies, systematic approaches for variable selection are needed. Borrowing concepts from empiric methods in biology, a novel neighborhood-wide association study (NWAS) and a neighborhood-environment wide association study (NE-WAS) were recently developed. This chapter introduces key concepts of the NWAS/NE-WAS designs, provides criteria for evaluating these systematic approaches, and discusses the potential impact these empiric methods have on future multilevel interventions.

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Author information

Authors and Affiliations

  1. Fox Chase Cancer Center, Philadelphia, PA, USA

    Shannon M. Lynch Ph.D., M.P.H.

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  1. Shannon M. Lynch Ph.D., M.P.H.
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Correspondence to Shannon M. Lynch Ph.D., M.P.H. .

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Editors and Affiliations

  1. Division of Cancer Control and Population Sciences, National Cancer Institute, Bethesda, MD, USA

    David Berrigan

  2. Center for Science, Health and Society Case Comprehensive Cancer Center, Case Western Reserve University, Cleveland, OH, USA

    Nathan A. Berger

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Lynch, S.M. (2019). Towards Systematic Methods in an Era of Big Data: Neighborhood Wide Association Studies. In: Berrigan, D., Berger, N. (eds) Geospatial Approaches to Energy Balance and Breast Cancer. Energy Balance and Cancer, vol 15. Springer, Cham. https://doi.org/10.1007/978-3-030-18408-7_5

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  • DOI: https://doi.org/10.1007/978-3-030-18408-7_5

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