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Record W4411968272 · doi:10.1016/j.cjca.2025.06.072

Effect of Life’s Essential 8 and Exposure to Solid Fuels for Cooking on Cardiovascular Disease Risk

2025· article· en· W4411968272 on OpenAlexvenueno aff
Yanjiao Wang, Fei Mi, Qiao Zhang, Leilei Liu, Zhimiao Yu, Li-Ling Chen, Quzong Deji, Junmin Zhou, Yuemei Feng, Qiong Meng, Jianzhong Yin

Bibliographic record

VenueCanadian Journal of Cardiology · 2025
Typearticle
Languageen
FieldEnvironmental Science
TopicHealth, Environment, Cognitive Aging
Canadian institutionsnot available
FundersCenter for Makroøkologi, Evolution og KlimaSichuan UniversityApplied Basic Research Key Project of YunnanNational Key Research and Development Program of ChinaKunming Medical UniversityGuizhou Medical UniversityNational Natural Science Foundation of China
KeywordsMedicineDiseaseSolid fuelEnvironmental healthIntensive care medicineInternal medicineCombustion

Abstract

fetched live from OpenAlex

BACKGROUND: Few studies have examined the association between Life's Essential 8 (LE8) scores and cardiovascular disease (CVD) risk in less-developed countries. In this study we aimed to assess the relationship between LE8 levels and CVD and evaluate whether LE8 modifies the association between exposure to solid cooking fuels and CVD. METHODS: A cross-sectional analysis was conducted using data extracted from the China Multi-Ethnic Cohort. Cardiovascular health was scored using LE8 and categorized as low, moderate, and high. Exposure to solid fuels for cooking was classified as no exposure, intermediate exposure, and heavy exposure. RESULTS: Among 89,772 participants, 4444 (5.0%) had CVD. Higher LE8 scores were associated with lower CVD risk after full covariate adjustment. The adjusted odds ratios (95% confidence intervals [CIs]) for the moderate and high LE8 groups were 0.82 (0.74-0.89) and 0.73 (0.66-0.81), respectively (P for trend < 0.001). Compared with no exposure, heavy exposure to solid fuels was associated with a higher CVD risk (odds ratio, 1.21 [95% CI, 1.06-1.40]; P = 0.004). A significant interaction was observed between the LE8 score and solid fuel exposure (P for interaction = 0.01). The inverse association between LE8 and CVD was the strongest among those with no exposure to solid fuels (odds ratio, 0.80 [95% CI, 0.71-0.91]). CONCLUSIONS: High LE8 scores are associated with reduced CVD risk, particularly among participants with no exposure to solid fuels for cooking.

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)0.002
metaresearch head score (Gemma)0.001
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 score0.231
Threshold uncertainty score0.490

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
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 head0.006
GPT teacher head0.237
Teacher spread0.231 · 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

Citations0
Published2025
Admission routes1
Has abstractyes

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