Associations of delay discounting and drinking trajectories from ages 14 to 22

The IMAGEN Consortium

doi:10.1111/acer.14799

Associations of delay discounting and drinking trajectories from ages 14 to 22

The IMAGEN Consortium

Research output: Contribution to journal › Article › peer-review

6 Citations (Scopus)

Abstract

Background: While drinking alcohol, one must choose between the immediate rewarding effects and the delayed reward of a healthier lifestyle. Individuals differ in their devaluation of a delayed reward based on the time required to receive it, i.e., delay discounting (DD). Previous studies have shown that adolescents discount more steeply than adults and that steeper DD is associated with heavier alcohol use in both groups. Methods: In a large-scale longitudinal study, we investigated whether higher rates of DD are an antecedent or a consequence of alcohol use during adolescent development. As part of the IMAGEN project, 2220 adolescents completed the Monetary Choice Questionnaire as a DD measure, the Alcohol Use Disorders Identification Test, and the Timeline Follow Back interview at ages 14, 16, 18, and 22. Bivariate latent growth curve models were applied to investigate the relationship between DD and drinking. To explore the consequences of drinking, we computed the cumulative alcohol consumption and correlated it with the development of discounting. A subsample of 221 participants completed an intertemporal choice task (iTeCh) during functional magnetic resonance imaging at ages 14, 16, and 18. Repeated-measures ANOVA was used to differentiate between high-risk and low-risk drinkers on the development of neural processing during intertemporal choices. Results: Overall, high rates of DD at age 14 predicted a greater increase in drinking over 8 years. In contrast, on average, moderate alcohol use did not affect DD from ages 14 to 22. Of note, we found indicators for less brain activity in top-down control areas during intertemporal choices in the participants who drank more. Conclusions: Steep DD was shown to be a predictor rather than a consequence of alcohol use in low-level drinking adolescents. Important considerations for future longitudinal studies are the sampling strategies to be used and the reliability of the assessments.

Original language	English
Pages (from-to)	667-681
Number of pages	15
Journal	Alcoholism: Clinical and Experimental Research
Volume	46
Issue number	4
DOIs	https://doi.org/10.1111/acer.14799
Publication status	Published - Apr 2022

Keywords

adolescence
alcohol
delay discounting
latent growth curve modeling
longitudinal fMRI

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

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10.1111/acer.14799

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@article{853049be54f04d219ef41365fc54c465,

title = "Associations of delay discounting and drinking trajectories from ages 14 to 22",

abstract = "Background: While drinking alcohol, one must choose between the immediate rewarding effects and the delayed reward of a healthier lifestyle. Individuals differ in their devaluation of a delayed reward based on the time required to receive it, i.e., delay discounting (DD). Previous studies have shown that adolescents discount more steeply than adults and that steeper DD is associated with heavier alcohol use in both groups. Methods: In a large-scale longitudinal study, we investigated whether higher rates of DD are an antecedent or a consequence of alcohol use during adolescent development. As part of the IMAGEN project, 2220 adolescents completed the Monetary Choice Questionnaire as a DD measure, the Alcohol Use Disorders Identification Test, and the Timeline Follow Back interview at ages 14, 16, 18, and 22. Bivariate latent growth curve models were applied to investigate the relationship between DD and drinking. To explore the consequences of drinking, we computed the cumulative alcohol consumption and correlated it with the development of discounting. A subsample of 221 participants completed an intertemporal choice task (iTeCh) during functional magnetic resonance imaging at ages 14, 16, and 18. Repeated-measures ANOVA was used to differentiate between high-risk and low-risk drinkers on the development of neural processing during intertemporal choices. Results: Overall, high rates of DD at age 14 predicted a greater increase in drinking over 8 years. In contrast, on average, moderate alcohol use did not affect DD from ages 14 to 22. Of note, we found indicators for less brain activity in top-down control areas during intertemporal choices in the participants who drank more. Conclusions: Steep DD was shown to be a predictor rather than a consequence of alcohol use in low-level drinking adolescents. Important considerations for future longitudinal studies are the sampling strategies to be used and the reliability of the assessments.",

keywords = "adolescence, alcohol, delay discounting, latent growth curve modeling, longitudinal fMRI",

author = "{The IMAGEN Consortium} and Fr{\"o}hner, {Juliane H.} and Stephan Ripke and Sarah Jurk and Li, {Shu Chen} and Tobias Banaschewski and Bokde, {Arun L.W.} and Quinlan, {Erin Burke} and Sylvane Desrivi{\`e}res and Herta Flor and Antoine Grigis and Hugh Garavan and Andreas Heinz and R{\"u}diger Br{\"u}hl and Martinot, {Jean Luc} and {Paill{\`e}re Martinot}, {Marie Laure} and Eric Artiges and Frauke Nees and {Papadopoulos Orfanos}, Dimitri and Luise Poustka and Sarah Hohmann and Henrik Walter and Robert Whelan and Gunter Schumann and Smolka, {Michael N.}",

note = "Funding Information: This study was supported by the Deutsche Forschungsgemeinschaft (DFG project numbers 402170461 [TRR 265] and 178833530 [SFB 940] and [NE 1383/14-1]) and the German Ministry of Education and Research (BMBF Grants 01GS08152; 01EV0711; 01EE1406A, 01EE1406B, 01EE1406D [Forschungsnetz AERIAL]; 01GL1745B [Forschungsnetz IMAC-Mind]). JHF received a PhD scholarship from the SFB 940 “Volition and Cognitive Control: mechanisms, modulators and dysfunctions.” Other sources included the European Union-funded FP6 Integrated Project IMAGEN (Reinforcement-related behavior in normal brain function and psychopathology) (LSHM-CT- 2007-037286), the Horizon 2020-funded ERC Advanced Grant “STRATIFY” (Brain network based stratification of reinforcement-related disorders) (695313), Human Brain Project (HBP SGA 2, 785907, and HBP SGA 3, 945539), the Medical Research Council Grant “c-VEDA” (Consortium on Vulnerability to Externalizing Disorders and Addictions) (MR/N000390/1). Funding Information: This study was supported by the Deutsche Forschungsgemeinschaft (DFG project numbers 402170461 [TRR 265] and 178833530 [SFB 940] and [NE 1383/14‐1]) and the German Ministry of Education and Research (BMBF Grants 01GS08152; 01EV0711; 01EE1406A, 01EE1406B, 01EE1406D [Forschungsnetz AERIAL]; 01GL1745B [Forschungsnetz IMAC‐Mind]). JHF received a PhD scholarship from the SFB 940 “Volition and Cognitive Control: mechanisms, modulators and dysfunctions.” Other sources included the European Union‐funded FP6 Integrated Project IMAGEN (Reinforcement‐related behavior in normal brain function and psychopathology) (LSHM‐CT‐ 2007‐037286), the Horizon 2020‐funded ERC Advanced Grant “STRATIFY” (Brain network based stratification of reinforcement‐related disorders) (695313), Human Brain Project (HBP SGA 2, 785907, and HBP SGA 3, 945539), the Medical Research Council Grant “c‐VEDA” (Consortium on Vulnerability to Externalizing Disorders and Addictions) (MR/N000390/1), the National Institute of Health (NIH) (R01DA049238, A decentralized macro and micro gene‐by‐environment interaction analysis of substance use behavior and its brain biomarkers), the National Institute for Health Research (NIHR) Biomedical Research Centre at South London and Maudsley NHS Foundation Trust and King{\textquoteright}s College London, the Medical Research Foundation and Medical Research Council (grants MR/R00465X/1 and MR/S020306/1), and the National Institutes of Health (NIH)‐funded ENIGMA (grants 5U54EB020403‐05 and 1R56AG058854‐01). Further support was provided by grants from the ANR (ANR‐12‐SAMA‐0004, AAPG2019—GeBra), the Eranet Neuron (AF12‐NEUR0008‐01—WM2NA; and ANR‐18‐NEUR00002‐01—ADORe), the Fondation de France (00081242), the Fondation pour la Recherche M{\'e}dicale (DPA20140629802), the Mission Interminist{\'e}rielle de Lutte‐contre‐les‐Drogues‐et‐les‐Conduites‐Addictives (MILDECA), the Assistance‐Publique‐H{\^o}pitaux‐de‐Paris and INSERM (interface grant), Paris Sud University IDEX 2012, the Fondation de l{\textquoteright}Avenir (grant AP‐RM‐17‐013), the F{\'e}d{\'e}ration pour la Recherche sur le Cerveau, and the National Institutes of Health, Science Foundation Ireland (16/ERCD/3797), USA (Axon, Testosterone and Mental Health during Adolescence; RO1 MH085772‐01A1) and by NIH Consortium grant U54 EB020403, supported by a cross‐NIH alliance that funds Big Data to Knowledge Centres of Excellence; ImagenPathways {"}Understanding the Interplay between Cultural, Biological and Subjective Factors in Drug Use Pathways{"} is a collaborative project supported by the European Research Area Network on Illicit Drugs (ERANID). This paper is based on independent research commissioned and funded in England by the National Institute for Health Research (NIHR) Policy Research Programme (project ref. PR‐ST‐0416‐10001). The views expressed in this article are those of the authors and not necessarily those of the national funding agencies or ERANID. We thank the participants for their impressive encouragement and participation over the years. We thank Matthew J. Belanger for language editing of the manuscript. We thank Tara Madhyastha for her help in setting up the neuropointillist analyses. Publisher Copyright: {\textcopyright} 2022 The Authors. Alcoholism: Clinical & Experimental Research published by Wiley Periodicals LLC on behalf of Research Society on Alcoholism.",

year = "2022",

month = apr,

doi = "10.1111/acer.14799",

language = "English",

volume = "46",

pages = "667--681",

journal = "Alcoholism: Clinical and Experimental Research",

issn = "0145-6008",

publisher = "Wiley-Blackwell",

number = "4",

}

TY - JOUR

T1 - Associations of delay discounting and drinking trajectories from ages 14 to 22

AU - The IMAGEN Consortium

AU - Fröhner, Juliane H.

AU - Ripke, Stephan

AU - Jurk, Sarah

AU - Li, Shu Chen

AU - Banaschewski, Tobias

AU - Bokde, Arun L.W.

AU - Quinlan, Erin Burke

AU - Desrivières, Sylvane

AU - Flor, Herta

AU - Grigis, Antoine

AU - Garavan, Hugh

AU - Heinz, Andreas

AU - Brühl, Rüdiger

AU - Martinot, Jean Luc

AU - Paillère Martinot, Marie Laure

AU - Artiges, Eric

AU - Nees, Frauke

AU - Papadopoulos Orfanos, Dimitri

AU - Poustka, Luise

AU - Hohmann, Sarah

AU - Walter, Henrik

AU - Whelan, Robert

AU - Schumann, Gunter

AU - Smolka, Michael N.

N1 - Funding Information: This study was supported by the Deutsche Forschungsgemeinschaft (DFG project numbers 402170461 [TRR 265] and 178833530 [SFB 940] and [NE 1383/14-1]) and the German Ministry of Education and Research (BMBF Grants 01GS08152; 01EV0711; 01EE1406A, 01EE1406B, 01EE1406D [Forschungsnetz AERIAL]; 01GL1745B [Forschungsnetz IMAC-Mind]). JHF received a PhD scholarship from the SFB 940 “Volition and Cognitive Control: mechanisms, modulators and dysfunctions.” Other sources included the European Union-funded FP6 Integrated Project IMAGEN (Reinforcement-related behavior in normal brain function and psychopathology) (LSHM-CT- 2007-037286), the Horizon 2020-funded ERC Advanced Grant “STRATIFY” (Brain network based stratification of reinforcement-related disorders) (695313), Human Brain Project (HBP SGA 2, 785907, and HBP SGA 3, 945539), the Medical Research Council Grant “c-VEDA” (Consortium on Vulnerability to Externalizing Disorders and Addictions) (MR/N000390/1). Funding Information: This study was supported by the Deutsche Forschungsgemeinschaft (DFG project numbers 402170461 [TRR 265] and 178833530 [SFB 940] and [NE 1383/14‐1]) and the German Ministry of Education and Research (BMBF Grants 01GS08152; 01EV0711; 01EE1406A, 01EE1406B, 01EE1406D [Forschungsnetz AERIAL]; 01GL1745B [Forschungsnetz IMAC‐Mind]). JHF received a PhD scholarship from the SFB 940 “Volition and Cognitive Control: mechanisms, modulators and dysfunctions.” Other sources included the European Union‐funded FP6 Integrated Project IMAGEN (Reinforcement‐related behavior in normal brain function and psychopathology) (LSHM‐CT‐ 2007‐037286), the Horizon 2020‐funded ERC Advanced Grant “STRATIFY” (Brain network based stratification of reinforcement‐related disorders) (695313), Human Brain Project (HBP SGA 2, 785907, and HBP SGA 3, 945539), the Medical Research Council Grant “c‐VEDA” (Consortium on Vulnerability to Externalizing Disorders and Addictions) (MR/N000390/1), the National Institute of Health (NIH) (R01DA049238, A decentralized macro and micro gene‐by‐environment interaction analysis of substance use behavior and its brain biomarkers), the National Institute for Health Research (NIHR) Biomedical Research Centre at South London and Maudsley NHS Foundation Trust and King’s College London, the Medical Research Foundation and Medical Research Council (grants MR/R00465X/1 and MR/S020306/1), and the National Institutes of Health (NIH)‐funded ENIGMA (grants 5U54EB020403‐05 and 1R56AG058854‐01). Further support was provided by grants from the ANR (ANR‐12‐SAMA‐0004, AAPG2019—GeBra), the Eranet Neuron (AF12‐NEUR0008‐01—WM2NA; and ANR‐18‐NEUR00002‐01—ADORe), the Fondation de France (00081242), the Fondation pour la Recherche Médicale (DPA20140629802), the Mission Interministérielle de Lutte‐contre‐les‐Drogues‐et‐les‐Conduites‐Addictives (MILDECA), the Assistance‐Publique‐Hôpitaux‐de‐Paris and INSERM (interface grant), Paris Sud University IDEX 2012, the Fondation de l’Avenir (grant AP‐RM‐17‐013), the Fédération pour la Recherche sur le Cerveau, and the National Institutes of Health, Science Foundation Ireland (16/ERCD/3797), USA (Axon, Testosterone and Mental Health during Adolescence; RO1 MH085772‐01A1) and by NIH Consortium grant U54 EB020403, supported by a cross‐NIH alliance that funds Big Data to Knowledge Centres of Excellence; ImagenPathways "Understanding the Interplay between Cultural, Biological and Subjective Factors in Drug Use Pathways" is a collaborative project supported by the European Research Area Network on Illicit Drugs (ERANID). This paper is based on independent research commissioned and funded in England by the National Institute for Health Research (NIHR) Policy Research Programme (project ref. PR‐ST‐0416‐10001). The views expressed in this article are those of the authors and not necessarily those of the national funding agencies or ERANID. We thank the participants for their impressive encouragement and participation over the years. We thank Matthew J. Belanger for language editing of the manuscript. We thank Tara Madhyastha for her help in setting up the neuropointillist analyses. Publisher Copyright: © 2022 The Authors. Alcoholism: Clinical & Experimental Research published by Wiley Periodicals LLC on behalf of Research Society on Alcoholism.

PY - 2022/4

Y1 - 2022/4

N2 - Background: While drinking alcohol, one must choose between the immediate rewarding effects and the delayed reward of a healthier lifestyle. Individuals differ in their devaluation of a delayed reward based on the time required to receive it, i.e., delay discounting (DD). Previous studies have shown that adolescents discount more steeply than adults and that steeper DD is associated with heavier alcohol use in both groups. Methods: In a large-scale longitudinal study, we investigated whether higher rates of DD are an antecedent or a consequence of alcohol use during adolescent development. As part of the IMAGEN project, 2220 adolescents completed the Monetary Choice Questionnaire as a DD measure, the Alcohol Use Disorders Identification Test, and the Timeline Follow Back interview at ages 14, 16, 18, and 22. Bivariate latent growth curve models were applied to investigate the relationship between DD and drinking. To explore the consequences of drinking, we computed the cumulative alcohol consumption and correlated it with the development of discounting. A subsample of 221 participants completed an intertemporal choice task (iTeCh) during functional magnetic resonance imaging at ages 14, 16, and 18. Repeated-measures ANOVA was used to differentiate between high-risk and low-risk drinkers on the development of neural processing during intertemporal choices. Results: Overall, high rates of DD at age 14 predicted a greater increase in drinking over 8 years. In contrast, on average, moderate alcohol use did not affect DD from ages 14 to 22. Of note, we found indicators for less brain activity in top-down control areas during intertemporal choices in the participants who drank more. Conclusions: Steep DD was shown to be a predictor rather than a consequence of alcohol use in low-level drinking adolescents. Important considerations for future longitudinal studies are the sampling strategies to be used and the reliability of the assessments.

AB - Background: While drinking alcohol, one must choose between the immediate rewarding effects and the delayed reward of a healthier lifestyle. Individuals differ in their devaluation of a delayed reward based on the time required to receive it, i.e., delay discounting (DD). Previous studies have shown that adolescents discount more steeply than adults and that steeper DD is associated with heavier alcohol use in both groups. Methods: In a large-scale longitudinal study, we investigated whether higher rates of DD are an antecedent or a consequence of alcohol use during adolescent development. As part of the IMAGEN project, 2220 adolescents completed the Monetary Choice Questionnaire as a DD measure, the Alcohol Use Disorders Identification Test, and the Timeline Follow Back interview at ages 14, 16, 18, and 22. Bivariate latent growth curve models were applied to investigate the relationship between DD and drinking. To explore the consequences of drinking, we computed the cumulative alcohol consumption and correlated it with the development of discounting. A subsample of 221 participants completed an intertemporal choice task (iTeCh) during functional magnetic resonance imaging at ages 14, 16, and 18. Repeated-measures ANOVA was used to differentiate between high-risk and low-risk drinkers on the development of neural processing during intertemporal choices. Results: Overall, high rates of DD at age 14 predicted a greater increase in drinking over 8 years. In contrast, on average, moderate alcohol use did not affect DD from ages 14 to 22. Of note, we found indicators for less brain activity in top-down control areas during intertemporal choices in the participants who drank more. Conclusions: Steep DD was shown to be a predictor rather than a consequence of alcohol use in low-level drinking adolescents. Important considerations for future longitudinal studies are the sampling strategies to be used and the reliability of the assessments.

KW - adolescence

KW - alcohol

KW - delay discounting

KW - latent growth curve modeling

KW - longitudinal fMRI

UR - http://www.scopus.com/inward/record.url?scp=85133569896&partnerID=8YFLogxK

U2 - 10.1111/acer.14799

DO - 10.1111/acer.14799

M3 - Article

C2 - 35257381

AN - SCOPUS:85133569896

SN - 0145-6008

VL - 46

SP - 667

EP - 681

JO - Alcoholism: Clinical and Experimental Research

JF - Alcoholism: Clinical and Experimental Research

IS - 4

ER -

Associations of delay discounting and drinking trajectories from ages 14 to 22

Abstract

Keywords

UN SDGs

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