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Record W3134851246 · doi:10.1111/dar.13265

Impact of body mass and alcohol consumption on all‐cause and liver mortality in 240 000 adults in the United States

2021· article· en· W3134851246 on OpenAlexaff
Jayadeep Patra, Charlotte Buckley, William C. Kerr, Alan Brennan, Robin C. Purshouse, Jürgen Rehm

Bibliographic record

VenueDrug and Alcohol Review · 2021
Typearticle
Languageen
FieldMedicine
TopicAlcohol Consumption and Health Effects
Canadian institutionsPublic Health OntarioUniversity of TorontoCentre for Addiction and Mental Health
FundersNational Institute on Alcohol Abuse and Alcoholism
KeywordsMedicineHazard ratioDemographyObesityBody mass indexConfidence intervalCause of deathGerontologyInternal medicineDisease

Abstract

fetched live from OpenAlex

Abstract Introduction Nationally representative studies of the combined impact of drinking and body mass (BMI) on mortality outcomes are unavailable. We investigate whether both act together to elevate risk of all‐cause or liver mortality. Methods We obtained self‐reported histories of drinking and BMI from 129 098 women (mean age 47.2 years) and 102 568 men (mean age 45.6 years) ≥18 years interviewed from 1997 to 2004 in the National Health Interview Survey and related these data to the deaths that occurred by 31 December 2006 (women = 8486; men = 7819 deaths). Death hazards among current drinkers in different BMI groups were adjusted for age, education, race and smoking. Results Obese (≥30 kg m −2 ) adults with consumption of >40 g day −1 (women) or >60 g day −1 (men) pure ethanol were at risk of increased mortality from all‐cause and chronic liver disease (P trend <0.0001). For heavy drinkers with BMI ≥30 kg m −2 , each 5 kg m −2 higher BMI was associated with an elevated all‐cause mortality in men (hazard ratios 1.27, 95% confidence interval [CI]: 1.16–1.40) and women (1.12, [1.02–1.24]). The excess risk due to interaction was more pronounced in men (7.30, [3.60–11.00]) than women (2.90, [0.50–5.30]). Discussion and Conclusions Obesity and excess alcohol are both related to all‐cause and liver mortality—the latter with evidence of a supra‐additive interaction between the risk factors. The presence of both factors in the same population and their impact should inform treatment, public health policies and research.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.306
Threshold uncertainty score0.530

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.133
GPT teacher head0.435
Teacher spread0.302 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations12
Published2021
Admission routes1
Has abstractyes

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