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Are neighborhoods causal? Complications arising from the 'stickiness' of ZNA
Journal article   Peer reviewed

Are neighborhoods causal? Complications arising from the 'stickiness' of ZNA

Thomas A. Glass and Usama Bilal
Social science & medicine (1982), v 166, pp 244-253
01 Oct 2016
PMID: 26830654
Featured in Collection :   UN Sustainable Development Goals @ Drexel

Abstract

Biomedical Social Sciences Life Sciences & Biomedicine Public, Environmental & Occupational Health Science & Technology Social Sciences Social Sciences, Biomedical
Are neighborhoods causal? The answer remains elusive. Armed with new multilevel methods, enthusiasm for neighborhoods research surged at the turn of the century. However, a wave of skepticism has arisen based on the difficulty of drawing causal inferences from observational studies in which selection to neighborhoods is non-random. Researchers have sought answers from experimental and quasi experimental studies of movers vs. stayers. We develop two related concepts in this essay in the hopes of shedding light on this problem. First, the inceptive environment into which persons are born (which we term ZNA for Zip code Nativity Area) exerts a potentially powerful causal impact on health. Detecting that causal effect is challenging for reasons similar that obtain in other fields (including genetics). Second, we explicate the problem of neighborhood 'stickiness' in terms of the persistence of neighborhood treatment assignment, and argue that under-appreciation of stickiness has led to systematic bias in causal estimates of neighborhoods proportional to the degree of stickiness. In sticky contexts, failure to account for the lasting influences of ZNA by adjusting for intermediate individual socioeconomic and health variables on the causal pathway can result in neighborhood effects estimates that are biased toward the null. We follow with an example drawn from evidence of neighborhood 'stickiness' and obesity. The stickiness of ZNA cautions us that experimental evidence may be insufficient or misleading as a solution to causal inference problems in neighborhood research. (C) 2016 Elsevier Ltd. All rights reserved.

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UN Sustainable Development Goals (SDGs)

This publication has contributed to the advancement of the following goals:

#10 Reduced Inequalities
#3 Good Health and Well-Being

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Collaboration types
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Web of Science research areas
Public, Environmental & Occupational Health
Social Sciences, Biomedical
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