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Int. J. Environ. Res. Public Health 2018, 15(4), 671; https://doi.org/10.3390/ijerph15040671

An Ecological Study on the Spatially Varying Relationship between County-Level Suicide Rates and Altitude in the United States

1,*
and
2
1
Department of Sociology, Anthropology and Geography, Auburn University at Montgomery, 7041 Senators Drive, Montgomery, AL 36117, USA
2
Department of Geology and Geography, Georgia Southern University, P.O. Box 8149, Statesboro, GA 30460, USA
*
Author to whom correspondence should be addressed.
Received: 8 February 2018 / Revised: 28 March 2018 / Accepted: 1 April 2018 / Published: 4 April 2018
(This article belongs to the Special Issue Frontiers in Mental Health and the Environment)
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Abstract

Suicide is a serious but preventable public health issue. Several previous studies have revealed a positive association between altitude and suicide rates at the county level in the contiguous United States. We assessed the association between suicide rates and altitude using a cross-county ecological study design. Data on suicide rates were obtained from a Web-based Injury Statistics Query and Reporting System (WISQARS), maintained by the U.S. National Center for Injury Prevention and Control (NCIPC). Altitude data were collected from the United States Geological Survey (USGS). We employed an ordinary least square (OLS) regression to model the association between altitude and suicide rates in 3064 counties in the contiguous U.S. We conducted a geographically weighted regression (GWR) to examine the spatially varying relationship between suicide rates and altitude after controlling for several well-established covariates. A significant positive association between altitude and suicide rates (average county rates between 2008 and 2014) was found in the dataset in the OLS model (R2 = 0.483, p < 0.001). Our GWR model fitted the data better, as indicated by an improved R2 (average: 0.62; range: 0.21–0.64) and a lower Akaike Information Criteria (AIC) value (13,593.68 vs. 14,432.14 in the OLS model). The GWR model also significantly reduced the spatial autocorrelation, as indicated by Moran’s I test statistic (Moran’s I = 0.171; z = 33.656; p < 0.001 vs. Moran’s I = 0.323; z = 63.526; p < 0.001 in the OLS model). In addition, a stronger positive relationship was detected in areas of the northern regions, northern plain regions, and southeastern regions in the U.S. Our study confirmed a varying overall positive relationship between altitude and suicide. Future research may consider controlling more predictor variables in regression models, such as firearm ownership, religion, and access to mental health services. View Full-Text
Keywords: altitude; suicide rates; geographically weighted regression; health geography altitude; suicide rates; geographically weighted regression; health geography
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Ha, H.; Tu, W. An Ecological Study on the Spatially Varying Relationship between County-Level Suicide Rates and Altitude in the United States. Int. J. Environ. Res. Public Health 2018, 15, 671.

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