Evidence map›Paper›PMID 37090902›Full record

ArticleInternational journal of alcohol and drug research2022

Improved estimates for individual and population-level alcohol use in the United States, 1984-2020.

Charlotte Buckley, Alan Brennan, William C Kerr, Charlotte Probst, Klajdi Puka, Robin C Purshouse, Jürgen Rehm

Abstract read
In one paragraph

Article in International journal of alcohol and drug research, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

  1. Article
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

Charlotte BuckleyDepartment of Automatic Control and Systems Engineering, University of Sheffield, Sheffield, UK, S1 3JD.
Alan BrennanSchool of Health and Related Research, University of Sheffield, Regent Court, 30 Regent Street, Sheffield, UK, S1 4DT.
William C KerrAlcohol Research Group, 6001 Shellmound St, Suite 450, Emeryville, CA 94608, USA.
Charlotte ProbstInstitute for Mental Health Policy Research, Centre for Addiction and Mental Health, 33 Ursula Franklin Street, Toronto, Ontario, Canada, M5S 2S1.
Klajdi PukaInstitute for Mental Health Policy Research, Centre for Addiction and Mental Health, 33 Ursula Franklin Street, Toronto, Ontario, Canada, M5S 2S1.
Robin C PurshouseDepartment of Automatic Control and Systems Engineering, University of Sheffield, Sheffield, UK, S1 3JD.
Jürgen RehmInstitute for Mental Health Policy Research, Centre for Addiction and Mental Health, 33 Ursula Franklin Street, Toronto, Ontario, Canada, M5S 2S1.

Funding

TREND &STRUCTURE OF ALCOHOL DEPENDENCE--GENERAL POPULATION 1990 SURVEY DATAP50AA005595 · NIAAA · WESTERN CONSORTIUM FOR PUBLIC HEALTH · PI MARTINEZ, PRISCILLA · 1985 to 2025
$34.1M
Supplement to a microsimulation of alcohol control interventions to advance health equity and reverse the current decrease in life expectancy in the USR01AA028009 · NIAAA · CENTRE FOR ADDICTION AND MENTAL HEALTH · PI PROBST, CHARLOTTE · 2020 to 2024
$2.4M
Calibrated Agent Simulations for Combined Analysis of Drinking Etiologies (CASCADE)R01AA024443 · NIAAA · UNIVERSITY OF SHEFFIELD · PI PURSHOUSE, ROBIN · 2016 to 2020
$2.3M
NIAAA NIH HHS P50 AA005595NIAAA NIH HHS R01 AA024443NIAAA NIH HHS R01 AA028009
6 · The paper itself

Abstract

Aims: While nationally representative alcohol surveys are a mainstay of public health monitoring, they underestimate consumption at the population level. This paper demonstrates how to adjust individual-level survey data using aggregated alcohol per capita (APC) data for improved individual- and population-level consumption estimates. Design and Methods: For the period 1984-2020, data on self-reported alcohol consumption in the past 30 days were taken from the Behavioral Risk Factor Surveillance System (BRFSS) involving participants (18+ years) in the United States (US). Monthly abstainers were reallocated into lifetime abstainers, former drinkers, and 12-month drinkers using the 2005 National Alcohol Survey data. To correct for under-coverage of alcohol use, we triangulated APC and survey data by upshifting quantity (average grams/day) and frequency (drinking days/week) of alcohol use based on national- and state-level APC data. Results were provided for the US as a whole and for selected states to represent different drinking patterns. Findings: The corrections described above resulted in improved correspondence between survey and APC data. Following our procedure, national estimates of alcohol quantity increased from 45% to 77% of APC estimates. Both quantity and frequency of alcohol use were upshifted; by upshifting to 90% of APC, we were able to fit trends and distributions in APC patterns for individual states and the US. Conclusions: An individual-level dataset which more accurately reflects the alcohol use of US citizens was achieved. This dataset will be invaluable as a research tool and for the planning and evaluation of alcohol control policies for the US. The methodology described can also be used to adjust individual-level alcohol survey data in other geographical settings.

Indexed as

Alcohol drinkingEpidemiologyPopulation healthSurvey dataSynthetic populations

Identifiers

PMID37090902
PMCPMC10117538

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.