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Understanding Geographic and Neighborhood Variations in Overdose Death Rates

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Abstract

The current opioid epidemic continues to challenge us in new and potentially troubling ways. For example, research today finds more overdose deaths occurring in rural, rather than urban, geographic areas. Yet, studies have often ignored heterogeneities within these spaces and the neighborhood variations therein. Using geodemographic classification, we investigate neighborhood differences in overdose death rates by geographical areas to further understand where and among what groups the problem might be most concentrated. For deaths between 2013 and 2016, we find significant variation in rates among neighborhoods, defined by their socio-economic and demographic characteristics. For example, overdose death rates vary up to 13-fold among neighborhoods within geographic areas. Our results overall show that while the rural or urban classification of a geographic area is important in understanding the current overdose problem, a more segmented analysis by neighborhood’s socio-economic and demographic makeup is also necessary.

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Notes

  1. Moreover, the approach allows us to address a methodological issue that has complicated neighborhood level research on overdose deaths in the US. Since the American Community Survey (ACS) has replaced the long form of the decennial census, it is the most prominent source for contextual information for geographic areas in the US [28, 34]. However, small scale data on the block group level or census tract level, which most closely align with our understandings of neighborhoods, show high levels of uncertainty [28, 34,35,36]. In geodemographic classification based on ACS data uncertainty for small scale data is reduced by using a composite of multiple variables [28].

  2. The five-year 2011 ACS data conveniently aligns with the beginning of our study period 2013–2016 making the classification valuable for our investigation. Input, output, and validation data of Spielman and Singletons classification are available at https://www.openicpsr.org/openicpsr/project/100235/version/V5/view. R code for cluster analysis and data visualization is available at https://github.com/geoss/acs_demographic_clusters.

  3. Delaware has 218 census tracts, four of these have no civilian population and were excluded from the analysis.

  4. For instance, we found that the neighborhood type shows comparable scores to the wealthy-neighborhood types A and B when defined by a common concentrated disadvantage measure (http://www.amchp.org/programsandtopics/data-assessment/Documents/Tip%20Sheet_Concentrated%20Disadvantage_LC-06_Final.pdf) and fall into the same income quartile.

  5. There were 851 overdose deaths among Delaware residents in the study period from 2013 to 2016. 64% of the decedents were male, 84% were white and the median age of the decedents was 43 years.

  6. Person-years are calculated as four times the 2010 census population for the respective geographic areas or neighborhood types.

  7. Neighborhood type A (Wealthy, Nuclear Families) was chosen as the reference category for the presentation of the rate ratios since the type is present in all geographic areas and allows for a quick estimate how a neighborhood fares compared to one of the most economically advantaged neighborhood type.

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Acknowledgements

This study was supported by Bureau of Justice Assistance (Grant No. 2014-BM-PX-0002) and National Institute of Justice (Grant No. 2017-IJ-CX-0016). The results and discussion presented here do not necessarily reflect the views of our funders. We are grateful to our colleagues for feedback on earlier versions of this paper.

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Authors and Affiliations

  1. University of Delaware, Newark, DE, USA

    Jascha Wagner, Logan Neitzke-Spruill, Daniel O’Connell, James Highberger, Steven S. Martin & Tammy L. Anderson

  2. Delaware Division of Forensic Science, Wilmington, DE, USA

    Rebecca Walker

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  1. Jascha Wagner
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Correspondence to Tammy L. Anderson.

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Wagner, J., Neitzke-Spruill, L., O’Connell, D. et al. Understanding Geographic and Neighborhood Variations in Overdose Death Rates. J Community Health 44, 272–283 (2019). https://doi.org/10.1007/s10900-018-0583-0

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