The impact of fentanyl on state- and county-level psychostimulant and cocaine overdose death rates by race in Ohio from 2010 to 2020: a time series and spatiotemporal analysis.
The impact of fentanyl on state- and county-level psychostimulant and cocaine overdose death rates by race in Ohio from 2010 to 2020: a time series and spatiotemporal analysis.
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DOI：
10.1186/s12954-024-00936-9
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发表时间：
2024-01-17
影响因子：
4.4
通讯作者：
Kline, David
中科院分区：
文献类型：
--
作者：
Estadt, Angela T.;White, Brian N.;Ricks, JaNelle M.;Lancaster, Kathryn E.;Hepler, Staci;Miller, William C.;Kline, David
在过去的十年中，在美国，与白人相比，黑人中可卡因和阿片类精神兴奋剂的过量服用率增幅最高。芬太尼是否导致俄亥俄州可卡因和精神兴奋剂过量服用的增加尚不清楚。我们试图按俄亥俄州的种族来衡量芬太尼对可卡因和精神兴奋剂过量死亡率的影响。我们使用俄亥俄州公共卫生信息仓库的数据进行了时间序列和时空分析。主要结果是 2010 年至 2020 年州和县级黑人和白人的用药过量死亡率。感兴趣的测量是由四种药物涉及类别组成的过量：（1）所有可卡因过量，（2）不涉及芬太尼的可卡因过量，（3）所有精神兴奋剂过量，以及（4）不涉及芬太尼的精神兴奋剂过量。我们使用贝叶斯广义线性混合模型拟合对数标准化死亡率 (SMR) 的时间序列模型来估计后验中值比率 (RR)。我们通过对县级每种药物类别的 SMR 进行建模来进行时空分析，以描述县级随时间变化的特征。 2020 年，吸毒过量率最高的是黑人（每 10 万人中有 24.8 人死亡）和白人（每 10 万人中有 10.1 人死亡）服用精神兴奋剂。黑人（aRR = 1.71；95% CI（1.43，2.02））和白人（aRR = 1.60，95% CI（1.39，1.80））人群中精神兴奋剂过量的年死亡率最高。对于不涉及芬太尼的可卡因，黑人（aRR = 1.04；95% CI (0.96,1.16)）和白人（aRR = 1.02；95% CI (0.87,1.20））人群的年死亡率比率相似。在每个药物类别中，两个种族群体随时间的变化是相似的。空间模型突出了所有药物类别的县级差异。在没有芬太尼参与的情况下，可卡因过量服用保持不变，而精神兴奋剂过量服用则有所增加。量身定制的减少危害方法，例如分发芬太尼试纸和取消影响联系紧急服务决定的惩罚性法律，是降低俄亥俄州城市人口中芬太尼可卡因过量服用率的第一步。与此同时，有必要采取减少伤害政策来解决精神兴奋剂过量服用的问题。在线版本包含可在 10.1186/s12954-024-00936-9 获取的补充材料。
Over the past decade in the USA, increases in overdose rates of cocaine and psychostimulants with opioids were highest among Black, compared to White, populations. Whether fentanyl has contributed to the rise in cocaine and psychostimulant overdoses in Ohio is unknown. We sought to measure the impact of fentanyl on cocaine and psychostimulant overdose death rates by race in Ohio. We conducted time series and spatiotemporal analyses using data from the Ohio Public Health Information Warehouse. Primary outcomes were state- and county-level overdose death rates from 2010 to 2020 for Black and White populations. Measures of interest were overdoses consisting of four drug involvement classes: (1) all cocaine overdoses, (2) cocaine overdoses not involving fentanyl, (3) all psychostimulant overdoses, and (4) psychostimulant overdoses not involving fentanyl. We fit a time series model of log standardized mortality ratios (SMRs) using a Bayesian generalized linear mixed model to estimate posterior median rate ratios (RR). We conducted a spatiotemporal analysis by modeling the SMR for each drug class at the county level to characterize county-level variation over time. In 2020, the greatest overdose rates involved cocaine among Black (24.8 deaths/100,000 people) and psychostimulants among White (10.1 deaths/100,000 people) populations. Annual mortality rate ratios were highest for psychostimulant-involved overdoses among Black (aRR = 1.71; 95% CI (1.43, 2.02)) and White (aRR = 1.60, 95% CI (1.39, 1.80)) populations. For cocaine not involving fentanyl, annual mortality rate ratios were similar among Black (aRR = 1.04; 95% CI (0.96,1.16)) and White (aRR = 1.02; 95% CI (0.87, 1.20)) populations. Within each drug category, change over time was similar for both racial groups. The spatial models highlighted county-level variation for all drug categories. Without the involvement of fentanyl, cocaine overdoses remained constant while psychostimulant overdoses increased. Tailored harm reduction approaches, such as distribution of fentanyl test strips and the removal of punitive laws that influence decisions to contact emergency services, are the first steps to reduce cocaine overdose rates involving fentanyl among urban populations in Ohio. In parallel, harm reduction policies to address the increase in psychostimulant overdoses are warranted. The online version contains supplementary material available at 10.1186/s12954-024-00936-9.
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影响因子：
13.8
作者：
通讯作者：
--
兴奋剂依赖性的异质性：国家药物滥用治疗临床试验网络研究。
DOI：
10.1080/10550490902787031
发表时间：
2009-05
期刊：
The American journal on addictions
影响因子：
--
作者：
Wu LT;Blazer DG;Patkar AA;Stitzer ML;Wakim PG;Brooner RK
通讯作者：
Brooner RK
影响因子：
12.7
作者：
Lopez, Andrea M.;Thomann, Matthew;Sullivan, Shane
通讯作者：
Sullivan, Shane
影响因子：
4.4
作者：
Kolak, Marynia A.;Chen, Yen-Tyng;Pho, Mai T.
通讯作者：
Pho, Mai T.
影响因子：
4.2
作者：
Jones, A. A.;Shearer, R. D.;Winkelman, T. N. A.
通讯作者：
Winkelman, T. N. A.