The geography of post-disaster mental health: spatial patterning of psychological vulnerability and resilience factors in New York City after Hurricane Sandy

Abstract

Background: Only very few studies have investigated the geographic distribution of psychological resilience and associated mental health outcomes after natural or man made disasters. Such information is crucial for location-based interventions that aim to promote recovery in the aftermath of disasters. The purpose of this study therefore was to investigate geographic variability of (1) posttraumatic stress (PTS) and depression in a Hurricane Sandy affected population in NYC and (2) psychological vulnerability and resilience factors among affected areas in NYC boroughs.

Methods: Cross-sectional telephone survey data were collected 13 to 16 months post-disaster from household residents (N = 418 adults) in NYC communities that were most heavily affected by the hurricane. The Posttraumatic Stress Checklist for DSM-5 (PCL-5) was applied for measuring posttraumatic stress and the nine-item Patient Health Questionnaire (PHQ-9) was used for measuring depression. We applied spatial autocorrelation and spatial regimes regression analyses, to test for spatial clusters of mental health outcomes and to explore whether associations between vulnerability and resilience factors and mental health differed among New York City's five boroughs.

Results: Mental health problems clustered predominantly in neighborhoods that are geographically more exposed towards the ocean indicating a spatial variation of risk within and across the boroughs. We further found significant variation in associations between vulnerability and resilience factors and mental health. Race/ethnicity (being Asian or non-Hispanic black) and disaster-related stressors were vulnerability factors for mental health symptoms in Queens, and being employed and married were resilience factors for these symptoms in Manhattan and Staten Island. In addition, parental status was a vulnerability factor in Brooklyn and a resilience factor in the Bronx.

Conclusions: We conclude that explanatory characteristics may manifest as psychological vulnerability and resilience factors differently across different regional contexts. Our spatial epidemiological approach is transferable to other regions around the globe and, in the light of a changing climate, could be used to strengthen the psychosocial resources of demographic groups at greatest risk of adverse outcomes pre-disaster. In the aftermath of a disaster, the approach can be used to identify survivors at greatest risk and to plan for targeted interventions to reach them.

Figure 1

Spatial clusters of PTS. Each dot on the map indicates a respondent’s location. The map indicates significant (p < 0.05) spatial clusters of high (HH) or low (LL) PTS. High values surrounded by low values (HL) and vice versa (LH) indicate outliers. A fixed distance of 9 km was used in the statistics. Note that a geometric shift of approx. 100 m has been introduced for displaying the point data so that single houses may not be identified for privacy reasons.

Figure 2

Spatial clusters of depression. Each dot on the map indicates a respondent’s location. The map indicates significant (p < 0.05) spatial clusters of high (HH) or low (LL) depression. High values surrounded by low values (HL) and vice versa (LH) indicate outliers. A fixed distance of 9 km was used in the statistics. Note that a geometric shift of approx. 100 m has been introduced for displaying the point data so that single houses may not be identified for privacy reasons.

Figure 3

Distribution of respondents within sampling zones across NYC boroughs. Note that a geometric shift of approx. 100 m has been introduced for displaying the point data so that single houses may not be identified for privacy reasons.