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André J, Diouf M, Martinetti MP, Ortelli O, Gierski F, Fürst F, Pierrefiche O, Naassila M. A new statistical model for binge drinking pattern classification in college-student populations. Front Psychol 2023; 14:1134118. [PMID: 37529316 PMCID: PMC10390312 DOI: 10.3389/fpsyg.2023.1134118] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/29/2022] [Accepted: 05/16/2023] [Indexed: 08/03/2023] Open
Abstract
Background Binge drinking (BD) among students is a frequent alcohol consumption pattern that produces adverse consequences. A widely discussed difficulty in the scientific community is defining and characterizing BD patterns. This study aimed to find homogenous drinking groups and then provide a new tool, based on a model that includes several key factors of BD, to assess the severity of BD regardless of the individual's gender. Methods Using the learning sample (N1 = 1,271), a K-means clustering algorithm and a partial proportional odds model (PPOM) were used to isolate drinking and behavioral key factors, create homogenous groups of drinkers, and estimate the probability of belonging to these groups. Robustness of our findings were evaluated with Two validations samples (N2 = 2,310, N3 = 120) of French university students (aged 18-25 years) were anonymously investigated via demographic and alcohol consumption questionnaires (AUDIT, AUQ, Alcohol Purchase Task for behavioral economic indices). Results The K-means revealed four homogeneous groups, based on drinking profiles: low-risk, hazardous, binge, and high-intensity BD. The PPOM generated the probability of each participant, self-identified as either male or female, to belong to one of these groups. Our results were confirmed in two validation samples, and we observed differences between the 4 drinking groups in terms of consumption consequences and behavioral economic demand indices. Conclusion Our model reveals a progressive severity in the drinking pattern and its consequences and may better characterize binge drinking among university student samples. This model provides a new tool for assessing the severity of binge drinking and illustrates that frequency of drinking behavior and particularly drunkenness are central features of a binge drinking model.
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Affiliation(s)
- Judith André
- INSERM UMR 1247, Groupe de Recherche sur l’alcool et les Pharmacodépendances, GRAP, Université Picardie Jules Verne, Amiens, France
| | - Momar Diouf
- Biostatistics Unit, Clinical Research Department, Amiens-Picardie University Hospital, Amiens, France
| | - Margaret P. Martinetti
- INSERM UMR 1247, Groupe de Recherche sur l’alcool et les Pharmacodépendances, GRAP, Université Picardie Jules Verne, Amiens, France
- Department of Psychology, The College of New Jersey, Ewing, NJ, United States
| | - Olivia Ortelli
- Department of Psychology, The College of New Jersey, Ewing, NJ, United States
| | - Fabien Gierski
- INSERM UMR 1247, Groupe de Recherche sur l’alcool et les Pharmacodépendances, GRAP, Université Picardie Jules Verne, Amiens, France
- Cognition, Health, Society Laboratory (C2S – EA 6291), University of Reims Champagne Ardenne (URCA), Reims, France
- Fédération Hospitalo-Universitaire A2M2P, Améliore le Pronostic des Troubles Addictifs et Mentaux par une Médecine Personnalisée, Paris, France
- GDR CNRS 3557 Psychiatrie-Addictions, Institut de Psychiatrie, Paris, France
| | - Frederic Fürst
- Laboratoire MIS (Modélisation, Information et Système) UR 4290, Université Picardie Jules Verne, Amiens, France
| | - Olivier Pierrefiche
- INSERM UMR 1247, Groupe de Recherche sur l’alcool et les Pharmacodépendances, GRAP, Université Picardie Jules Verne, Amiens, France
| | - Mickael Naassila
- INSERM UMR 1247, Groupe de Recherche sur l’alcool et les Pharmacodépendances, GRAP, Université Picardie Jules Verne, Amiens, France
- Fédération Hospitalo-Universitaire A2M2P, Améliore le Pronostic des Troubles Addictifs et Mentaux par une Médecine Personnalisée, Paris, France
- GDR CNRS 3557 Psychiatrie-Addictions, Institut de Psychiatrie, Paris, France
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Educational Gradients in Drinking Amount and Heavy Episodic Drinking among Working-Age Men and Women in Spain. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2022; 19:ijerph19074371. [PMID: 35410052 PMCID: PMC8998990 DOI: 10.3390/ijerph19074371] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 03/01/2022] [Revised: 04/01/2022] [Accepted: 04/02/2022] [Indexed: 02/04/2023]
Abstract
Alcohol-related harm decreases as socioeconomic position increases, although sometimes the opposite happens with alcohol intake. The objective was to know the educational gradient in monthly measures of drinking amount and heavy episodic drinking (HED) among people aged 25−64 years in Spain from 1997−2017. Such gradient was characterized with the relative percent change (PC) in drinking measures per year of education from generalized linear regression models after adjusting for age, year, region, marital status and immigration status. Among men, the PCs were significantly positive (p < 0.05) for prevalence of <21 g alcohol/day (2.9%) and 1−3 HED days (1.4%), and they were negative for prevalences of 21−40 g/day (−1.1%), >40 g/day (−6.0%) and ≥4 HED days (−3.2%), while among women they ranged from 3.6% to 5.7%. The gradient in prevalences of >40 g/day (men) and >20 g/day (women) was greatly attenuated after additionally adjusting for HED, while that of ≥4 HED days was only slightly attenuated after additionally adjusting for drinking amount. Among women, the gradients, especially in HED measures, seem steeper in 2009−2017 than in 1997−2007. Educational inequality remained after additional adjustment for income and occupation, although it decreased among women. These results can guide preventive interventions and help explain socioeconomic inequalities in alcohol-related harm.
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