ArticleSpatial and spatio-temporal epidemiology2020
Multivariate spatiotemporal modeling of drug- and alcohol-poisoning deaths in New York City, 2009-2014.
Article in Spatial and spatio-temporal epidemiology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers, 2 of them syntheses that pooled it.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
3 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- A systematic review of the association between alcohol-related deaths and area-level socioeconomic deprivation and other geographic characteristics in high-income countries.BMC public health · 2026Pooled it
- A Systematic Review of Joint Spatial and Spatiotemporal Models in Health Research.International journal of environmental research and public health · 2023Pooled it
- Area-Level Social Determinants of Alcohol-Related Mortality: Knowledge Gaps and Implications for Community Health.Alcohol research : current reviews · 2024Review
Corrections and comments
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Authors and funding
5 authors.
Funding
Abstract
Drug- and alcohol-poisoning deaths remain current public health problems. Studies to date have typically focused on individual-level predictors of drug overdose deaths, and there remains a limited understanding of the spatiotemporal patterns and predictors of the joint outcomes. We use a hierarchical Bayesian spatiotemporal multivariate Poisson regression model on data from (N = 167) ZIP-codes between 2009 and 2014 in New York City to examine the spatiotemporal patterns of the joint occurrence of drug (opioids) and alcohol-poisoning deaths, and the covariates associated with each outcome. Results indicate that rates of both outcomes were highly positively correlated across ZIP-codes (cross-correlation: 0.57, 95% credible interval (CrI): 0.29, 0.77). ZIP-codes with a higher prevalence of heavy drinking had higher alcohol-poisoning deaths (relative risk (RR):1.63, 95% CrI: 1.26, 2.05) and drug-poisoning deaths (RR: 1.29, 95% CrI: 1.03, 1.59). These spatial patterns may guide public health planners to target specific areas to address these co-occurring epidemics.
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Registered trials
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