Research News Roundup: February 22, 2024

Journal: JAMA Network Open, 2024, doi:10.1001/jamanetworkopen.2023.55952

Authors: Troy B. Puga, Hongying Daisy Dai, Yingying Wang, & Elijah Theye

Abstract:

Importance: Maternal tobacco use during pregnancy (MTDP) persists across the globe. Longitudinal assessment of the association of MTDP with neurocognitive development of offspring at late childhood is limited.

Objectives: To examine whether MTDP is associated with child neurocognitive development at ages 9 to 12 years.

Design, Setting, and Participants: This cohort study included children aged 9 and 10 years at wave 1 (October 2016 to October 2018) and aged 11 to 12 years at a 2-year follow-up (wave 2, August 2018 to January 2021) across 21 US sites in the Adolescent Brain Cognitive Development (ABCD) Study. Data were analyzed from June 2022 to December 2023.

Exposure: MTDP.

Main Outcomes and Measures: Outcomes of interest were neurocognition, measured by the National Institutes of Health (NIH) Toolbox Cognition Battery, and morphometric brain measures through the region of interest (ROI) analysis from structural magnetic resonance imaging (sMRI).

Results: Among 11 448 children at wave 1 (mean [SD] age, 9.9 [0.6] years; 5990 [52.3%] male), 1607 children were identified with MTDP. In the NIH Toolbox Cognition Battery, children with MTDP (vs no MTDP) exhibited lower scores on the oral reading recognition (mean [SE] B = −1.2 [0.2]; P < .001), picture sequence memory (mean [SE] B = −2.3 [0.6]; P < .001), and picture vocabulary (mean [SE] B = −1.2 [0.3]; P < .001) tests and the crystallized cognition composite score (mean [SE] B = −1.3 [0.3]; P < .001) at wave 1. These differential patterns persisted at wave 2. In sMRI, children with MTDP (vs no MTDP) had smaller cortical areas in precentral (mean [SE] B = −104.2 [30.4] mm2; P = .001), inferior parietal (mean [SE] B = −153.9 [43.4] mm2; P < .001), and entorhinal (mean [SE] B = −25.1 [5.8] mm2; P < .001) regions and lower cortical volumes in precentral (mean [SE] B = −474.4 [98.2] mm3; P < .001), inferior parietal (mean [SE] B = −523.7 [136.7] mm3; P < .001), entorhinal (mean [SE] B = −94.1 [24.5] mm3; P < .001), and parahippocampal (mean [SE] B = −82.6 [18.7] mm3; P < .001) regions at wave 1. Distinct cortical volume patterns continued to be significant at wave 2. Frontal, parietal, and temporal lobes exhibited differential ROI, while there were no notable distinctions in the occipital lobe and insula cortex.

Conclusions and Relevance: In this cohort study, MTDP was associated with enduring deficits in childhood neurocognition. Continued research on the association of MTDP with cognitive performance and brain structure related to language processing skills and episodic memory is needed.

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Journal: Medical Cannabis & Cannabinoids, 2024, doi: 10.1159/000536339

Authors: Charles N. Zawatsky, Sara Mills-Huffnagle, Corinne M. Augusto, Kent E. Vrana, & Jennifer E. Nyland

Abstract:

Background: In this review, we summarize current scientific knowledge on psychoactive cannabinoids synthesized from cannabidiol (CBD) and sold in the semi-legal market established in response to the passage of the US Agriculture Improvement Act of 2018, commonly known as the 2018 Farm Bill. The discussion focuses on recent developments that suggest this unregulated market may be fertile ground for a potential health crisis.

Summary: Current research into CBD-derived cannabinoids is mainly limited to Δ8-tetrahydrocannabinol (Δ8-THC) products, with some recent publications beginning to explore O-acetyl-THC, a term describing the acetate ester of Δ8-THC or Δ9-THC, and its potential pulmonary toxicity. We advance the discussion on the CBD-derived cannabinoid market, shedding light on the introduction and associated dangers of novel cannabinoids, likely produced via fully synthetic routes using sidechain variants of CBD, with purportedly greater agonist activity at the human cannabinoid receptor 1 (as a source of euphorigenic activity) than Δ9-THC. We discuss the expanded incorporation of the acetate ester motif into other THC analogues. We also discuss the lack of regulatory oversight for the production of CBD-derived cannabinoids and the unlabeled presence of under-researched cannabinoids formed as reaction side products in the CBD-derived cannabinoid products being sold. Accordingly, we suggest approaches to monitoring the CBD-derived cannabinoid market and investigating the pharmacology of the cannabinoids being consumed. Finally, important epidemiological findings are discussed and future directions for research are suggested to call investigators to this critically understudied field.

Key Messages: The CBD-derived cannabinoid market is growing internationally, and the market has diversified to include potent synthetic cannabinoids. The products sold on this unregulated market are under-researched despite growing availability and consumer interest. Ernest investigation of the pharmacology of these novel cannabinoids and the contents of CBD-derived cannabinoid products is critical for monitoring this potential source of another vaping-related epidemic.

To read the full text of the article, please visit the publisher’s website.

Journal: PLoS One, 2024, doi: 10.1371/journal.pone.0287878

Authors: Alejandro L. Vázquez, Cynthia M. Navarro Flores, Byron H. Garcia, Tyson S. Barrett, & Melanie M. Domenech Rodríguez

Abstract:

E-cigarette use among adolescents is a national health epidemic spreading faster than researchers can amass evidence for risk and protective factors and long-term consequences associated with use. New technologies, such as machine learning, may assist prevention programs in identifying at risk youth and potential targets for intervention before adolescents enter developmental periods where e-cigarette use escalates. The present study utilized machine learning algorithms to explore a wide array of individual and socioecological variables in relation to patterns of lifetime e-cigarette use during early adolescence (i.e., exclusive, or with tobacco cigarettes). Extant data was used from 14,346 middle school students (Mage = 12.5, SD = 1.1; 6th and 8th grades) who participated in the Utah Prevention Needs Assessment. Students self-reported their substance use behaviors and related risk and protective factors. Machine learning algorithms examined 112 individual and socioecological factors as potential classifiers of lifetime e-cigarette use outcomes. The elastic net algorithm achieved outstanding classification for lifetime exclusive (AUC = .926) and dual use (AUC = .944) on a validation test set. Six high value classifiers were identified that varied in importance by outcome: Lifetime alcohol or marijuana use, perception of e-cigarette availability and risk, school suspension(s), and perceived risk of smoking marijuana regularly. Specific classifiers were important for lifetime exclusive (parent’s attitudes regarding student vaping, best friend[s] tried alcohol or marijuana) and dual use (best friend[s] smoked cigarettes, lifetime inhalant use). Our findings provide specific targets for the adaptation of existing substance use prevention programs to address early adolescent e-cigarette use.

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Journal: Harm Reduction Journal, 2024, doi: 10.1186/s12954-024-00952-9

Authors: Lisa de Saxe Zerden, Orrin D. Ware, Brooke N. Lombardi, & Brianna M. Lombardi

Abstract:

Background: Despite recent financial and policy support for harm reduction in the USA, information on the types of workers within organizations who design, implement, and actualize harm reduction services remains nascent. Little is known about how variability in the harm reduction workforce impacts referrals and linkages to other community supports. This exploratory mixed-methods study asked: (1) Who constitutes the harm reduction workforce? (2) Who provides behavioral health services within harm reduction organizations? (3) Are referral services offered and by whom? (4) Do referrals differ by type of harm reduction worker?

Methods: Purposive sampling techniques were used to distribute an electronic survey to U.S.-based harm reduction organizations. Descriptive statistics were conducted. Multivariate binary logistic regression models examined the associations (a) between the odds of the referral processes at harm reduction organizations and (b) between the provision of behavioral health services and distinct types of organizational staff. Qualitative data were analyzed using a hybrid approach of inductive and thematic analysis.

Results: Data from 41 states and Washington, D.C. were collected (N = 168; 48% response rate). Four primary types of workers were identified: community health/peer specialists (87%); medical/nursing staff (55%); behavioral health (49%); and others (34%). About 43% of organizations had a formal referral process; among these, only 32% had follow-up protocols. Qualitative findings highlighted the broad spectrum of behavioral health services offered and a broad behavioral health workforce heavily reliant on peers. Unadjusted results from multivariate models found that harm reduction organizations were more than 5 times more likely (95% CI [1.91, 13.38]) to have a formal referral process and 6 times more likely (95% CI [1.74, 21.52]) to have follow-up processes when behavioral health services were offered. Organizations were more than two times more likely (95% CI [1.09, 4.46]) to have a formal referral process and 2.36 (95% CI [1.11, 5.0]) times more likely to have follow-up processes for referrals when behavioral health providers were included.

Conclusions: The composition of the harm reduction workforce is occupationally diverse. Understanding the types of services offered, as well as the workforce who provides those services, offers valuable insights into staffing and service delivery needs of frontline organizations working to reduce morbidity and mortality among those who use substances. Workforce considerations within U.S.-based harm reduction organizations are increasingly important as harm reduction services continue to expand.

To read the full text of the article, please visit the publisher’s website.