Neighborhood Change Induced by Natural Hazards

Lee, Dalbyul

doi:10.1177/0885412217696945

Cited by 12 publications

(7 citation statements)

References 93 publications

(120 reference statements)

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“…First, as suggested by ecosocial theory, underlying political, social, and economic neighborhood differences impact health 33 , as well as the probability that a neighborhood will gentrify. Contextual differences include the preexisting spatial and racial inequity in cities, policy efforts underway, the level of affordable housing and community organizing present, speed at which change processes occur, and whether the cause of change is exogenous 91 . In future studies such contextual factors should be considered as potential confounders or effect modifiers of the relationship between neighborhood socioeconomic ascent and health, when testing the relationship across multiple neighborhoods.…”

Section: Author Accepted Manuscriptmentioning

confidence: 99%

Gentrification, Neighborhood Change, and Population Health: a Systematic Review

Schnake-Mahl

Jahn

Subramanian³

et al. 2020

J Urban Health

134

109

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Despite a proliferation of research on neighborhood effects on health, how neighborhood economic development, in the form of gentrification, affects health and well-being in the U.S. is poorly understood, and no systematic assessment of the potential health impacts has been conducted. Further, we know little about whether health impacts differ for residents of neighborhoods undergoing gentrification versus urban development, or other forms of neighborhood socioeconomic ascent. We followed current guidelines for systematic reviews and present data on the study characteristics of the twenty-two empirical articles that met our inclusion criteria and were published on associations between gentrification, and similar but differently termed processes (e.g., urban regeneration, urban development, neighborhood upgrading), and health published between 2000 and 2018. Our results show that impacts on health vary by outcome assessed, exposure measurement, the larger context specific determinants of neighborhood change, and analysis decisions including which reference and treatment groups to examine. Studies of the health impacts of gentrification, urban development, and urban regeneration describe similar processes, and synthesis and comparison of their results helps bridge differing theoretical approaches to this emerging research. Our article helps to inform the debate on the impacts of gentrification and urban development for health and suggests that these neighborhood change processes likely have both detrimental and beneficial effects on health. Given the influence of place on health and the trend of increasing gentrification and urban development in many American cities, we discuss how future research can approach understanding and researching the impacts of these processes for population health.

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Section: Author Accepted Manuscriptmentioning

confidence: 99%

Gentrification, Neighborhood Change, and Population Health: a Systematic Review

Schnake-Mahl

Jahn

Subramanian³

et al. 2020

J Urban Health

134

109

View full text Add to dashboard Cite

show abstract

“…This study examined how a natural disaster can interrupt the trajectory of neighborhood change, focusing on neighborhood poverty rate. Following Lee’s (2017) model of neighborhood change, it applied a methodological approach that accounted for the disaster effect as distinct from the effects of the natural mechanisms of socioeconomic change that constantly take place in neighborhoods. To estimate the impact of natural disasters on these mechanisms, the study examined the trajectory of indicators in pre- and post-disaster periods for disaster events between 1970 and 2000.…”

Section: Discussionmentioning

confidence: 99%

“…Lee (2017) also tried to explain disaster-induced change in the context of neighborhood change dynamics. Neighborhoods naturally undergo gradual change (Schelling 1971), but following a “transient, exogenous shock” (Galster, Cutsinger, and Lim 2007, 167), such as reinvestment/disinvestment (Galster, Cutsinger, and Lim 2007; Newman and Ashton 2004; Smith 2002) or the recovery process following a natural disaster (Cutter et al 2014; Peacock et al 2014; Seidman 2013), they change much more rapidly.…”

Section: Natural Disasters and Neighborhood Changementioning

confidence: 99%

“…This study tests the conceptual model proposed by Lee (2017), which estimates post-disaster neighborhood changes while accounting for patterns in natural historical neighborhood change. It follows a longitudinal data model in which neighborhood poverty rates are utilized to verify the link between neighborhood change and natural disasters.…”

Section: Research Questionsmentioning

confidence: 99%

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The Impact of Natural Disasters on Neighborhood Poverty Rate: A Neighborhood Change Perspective

Lee

2018

Journal of Planning Education and Research

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Neighborhoods change over time through an underlying systematic mechanism. Natural disasters change the socioeconomic characteristics of neighborhoods by causing physical damage, after which outside resources are brought in to support recovery efforts, thereby impacting the natural processes by which neighborhoods change. This study examines the impact of a natural disaster on neighborhood poverty rate and its differential impacts according to neighborhood socioeconomic characteristics. The results show that natural disasters cause a shift in the pattern of the neighborhood poverty rate trajectory and that disasters’ impacts on neighborhood poverty rates are differential across neighborhoods. In particular, natural disasters impact the poverty rates of low-income neighborhoods most adversely.

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“…Despite the growing number of hurricanes and extreme weather events, the academic literature on the patterns of rebuilding and neighborhood change as a result of damage from these events has not kept pace (Fussell et al 2017;Lee 2017). This is a major gap in the literature, as the number, intensity, and cost of natural disasters around the globe is expected to increase in coming decades (NASA 2017).…”

Section: Introductionmentioning

confidence: 99%

Uneven Neighborhood Recovery: Hurricane Damage and Neighborhood Change in the Houston–Galveston Region since 1970

et al. 2019

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Despite the growing number of natural disasters around the globe, limited research exists on post‐disaster patterns of neighborhood change. In this paper, we test two theories of neighborhood change, the “recovery machine” and “rent gap,” which predict opposing effects for low socioeconomic status (SES) neighborhoods following damage from hurricanes, tropical storms, and other natural hazard events. The recovery machine theory posits that after natural hazard events, local communities experience patterns of recovery based on their pre‐disaster SES and access to resources, suggesting that wealthier neighborhoods will recover robustly while lower status neighborhoods languish. In contrast, the rent gap theory suggests that developers will identify a profit opportunity in the depressed values created by damage from natural hazard events, and seek to redevelop low SES areas. We use fixed effects models with census data from 1970 to 2015 to test the impact of damage from natural hazards on neighborhood change. We find substantial recovery and change in low‐income neighborhoods, but not in the high‐income neighborhoods supporting the rent gap theory. We conclude that natural hazard events resulting in damage produce uneven recovery by socioeconomic status of neighborhoods, potentially leading to displacement of low SES groups.

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Neighborhood Change Induced by Natural Hazards

Cited by 12 publications

References 93 publications

Gentrification, Neighborhood Change, and Population Health: a Systematic Review

Gentrification, Neighborhood Change, and Population Health: a Systematic Review

The Impact of Natural Disasters on Neighborhood Poverty Rate: A Neighborhood Change Perspective

Uneven Neighborhood Recovery: Hurricane Damage and Neighborhood Change in the Houston–Galveston Region since 1970

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