Cargando…

Differentiating people who use cannabis heavily through latent class analysis

BACKGROUND: People who use cannabis daily or near-daily vary considerably in their daily dosage and use frequency, impacting both experienced effects and adverse consequences. This study identified heavy cannabis user groups according to consumption patterns and factors associated with class members...

Descripción completa

Detalles Bibliográficos
Autores principales: Alvarez-Roldan, Arturo, García-Muñoz, Teresa, Gamella, Juan F., Parra, Iván, Duaso, Maria J.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10236746/
https://www.ncbi.nlm.nih.gov/pubmed/37264404
http://dx.doi.org/10.1186/s13011-023-00540-3
_version_ 1785053010785730560
author Alvarez-Roldan, Arturo
García-Muñoz, Teresa
Gamella, Juan F.
Parra, Iván
Duaso, Maria J.
author_facet Alvarez-Roldan, Arturo
García-Muñoz, Teresa
Gamella, Juan F.
Parra, Iván
Duaso, Maria J.
author_sort Alvarez-Roldan, Arturo
collection PubMed
description BACKGROUND: People who use cannabis daily or near-daily vary considerably in their daily dosage and use frequency, impacting both experienced effects and adverse consequences. This study identified heavy cannabis user groups according to consumption patterns and factors associated with class membership. METHODS: We conducted a cross-sectional study of 380 Spanish residents (61.8% male; average age = 30.3 years) who had used cannabis ≥ 3 days/week throughout the past year. Participants were recruited through chain referral and cannabis social clubs. We applied latent class analysis (LCA) to cluster participants according to use intensity. LCA indicators included frequency of weekly cannabis use, joints smoked each day, cannabis dosage, and if cannabis was consumed throughout the day or only at specific times. Associations between class membership and socio-demographics, use patterns, motives, supply sources, adverse outcomes, and use of other substances were measured using ANOVA and chi-squared tests. Multinomial regression identified the factors associated with latent class membership. RESULTS: Three latent classes (moderately heavy: 21.8%, heavy: 68.2%, very heavy: 10%) had average weekly cannabis intakes of 2.4, 5.5, and 18.3 g, respectively. Very heavy users were older ([Formula: see text]=17.77, p < 0.01), less educated [Formula: see text]=36.80, p < 0.001), and had used cannabis for longer (F = 4.62, p = 0.01). CAST scores (F = 26.51, p < 0.001) increased across the classes. The prevalence of past-month alcohol use was lower among the heaviest users ([Formula: see text]=5.95, p = 0.05). Cannabis was usually obtained from a club by very heavy users ([Formula: see text]=20.95, p < 0.001). CONCLUSIONS: People who use cannabis heavily present three groups according to frequency and quantity of cannabis consumption. Use intensity is associated with increased cannabis-related problems. Differences among heavy users must be considered in harm reduction interventions in cannabis clubs and indicated prevention.
format Online
Article
Text
id pubmed-10236746
institution National Center for Biotechnology Information
language English
publishDate 2023
publisher BioMed Central
record_format MEDLINE/PubMed
spelling pubmed-102367462023-06-03 Differentiating people who use cannabis heavily through latent class analysis Alvarez-Roldan, Arturo García-Muñoz, Teresa Gamella, Juan F. Parra, Iván Duaso, Maria J. Subst Abuse Treat Prev Policy Research BACKGROUND: People who use cannabis daily or near-daily vary considerably in their daily dosage and use frequency, impacting both experienced effects and adverse consequences. This study identified heavy cannabis user groups according to consumption patterns and factors associated with class membership. METHODS: We conducted a cross-sectional study of 380 Spanish residents (61.8% male; average age = 30.3 years) who had used cannabis ≥ 3 days/week throughout the past year. Participants were recruited through chain referral and cannabis social clubs. We applied latent class analysis (LCA) to cluster participants according to use intensity. LCA indicators included frequency of weekly cannabis use, joints smoked each day, cannabis dosage, and if cannabis was consumed throughout the day or only at specific times. Associations between class membership and socio-demographics, use patterns, motives, supply sources, adverse outcomes, and use of other substances were measured using ANOVA and chi-squared tests. Multinomial regression identified the factors associated with latent class membership. RESULTS: Three latent classes (moderately heavy: 21.8%, heavy: 68.2%, very heavy: 10%) had average weekly cannabis intakes of 2.4, 5.5, and 18.3 g, respectively. Very heavy users were older ([Formula: see text]=17.77, p < 0.01), less educated [Formula: see text]=36.80, p < 0.001), and had used cannabis for longer (F = 4.62, p = 0.01). CAST scores (F = 26.51, p < 0.001) increased across the classes. The prevalence of past-month alcohol use was lower among the heaviest users ([Formula: see text]=5.95, p = 0.05). Cannabis was usually obtained from a club by very heavy users ([Formula: see text]=20.95, p < 0.001). CONCLUSIONS: People who use cannabis heavily present three groups according to frequency and quantity of cannabis consumption. Use intensity is associated with increased cannabis-related problems. Differences among heavy users must be considered in harm reduction interventions in cannabis clubs and indicated prevention. BioMed Central 2023-06-01 /pmc/articles/PMC10236746/ /pubmed/37264404 http://dx.doi.org/10.1186/s13011-023-00540-3 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Research
Alvarez-Roldan, Arturo
García-Muñoz, Teresa
Gamella, Juan F.
Parra, Iván
Duaso, Maria J.
Differentiating people who use cannabis heavily through latent class analysis
title Differentiating people who use cannabis heavily through latent class analysis
title_full Differentiating people who use cannabis heavily through latent class analysis
title_fullStr Differentiating people who use cannabis heavily through latent class analysis
title_full_unstemmed Differentiating people who use cannabis heavily through latent class analysis
title_short Differentiating people who use cannabis heavily through latent class analysis
title_sort differentiating people who use cannabis heavily through latent class analysis
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10236746/
https://www.ncbi.nlm.nih.gov/pubmed/37264404
http://dx.doi.org/10.1186/s13011-023-00540-3
work_keys_str_mv AT alvarezroldanarturo differentiatingpeoplewhousecannabisheavilythroughlatentclassanalysis
AT garciamunozteresa differentiatingpeoplewhousecannabisheavilythroughlatentclassanalysis
AT gamellajuanf differentiatingpeoplewhousecannabisheavilythroughlatentclassanalysis
AT parraivan differentiatingpeoplewhousecannabisheavilythroughlatentclassanalysis
AT duasomariaj differentiatingpeoplewhousecannabisheavilythroughlatentclassanalysis