Role of toxic metal exposure in the association of functional limitation and cardiovascular diseases among US adults
Notice bibliographique
Résumé
Functional limitations are common among US adults and are established predictors of cardiovascular disease (CVD). However, it is unclear whether exposure to toxic metals modifies the association between functional limitations and CVD risk. This study evaluates whether blood concentrations of toxic metals modify the association between functional limitations and CVD in US adults. This cross-sectional study included 3097 adults aged 18 years or older who participated in the National Health and Nutrition Examination Survey (NHANES) 2021–2023. Exposure Functional Limitation status was assessed across three domains including cognition, mobility, and vision. Blood concentrations of lead, cadmium, mercury, manganese, and selenium were categorized as high (≥ 90th percentile) vs. low. The primary outcome was self-reported CVD, defined as any history of heart failure, coronary heart disease, angina, myocardial infarction, or stroke. Survey-weighted descriptive statistics, cross-tabulations, survey-weighted logistic regression models (adjusted for age, sex, race/ethnicity, marital status, and hypertension) were used to estimate the main and interaction effects. Among 3097 participants (mean age 47.9 [95% CI: 46.7–49.2] years, 49.9% male), the prevalence of any cognitive, mobility, and visual difficulty was 43.2% (40.1–46.3), 21.5%, (19.6–23.4) and 34.4% (32.4–36.5), respectively. In survey-weighted analyses, high blood cadmium was consistently associated with greater prevalence of functional impairment across all domains (for cognition: 8.2% [6.2–10.2] vs. 5.0% [3.6–6.4], p = 0.013; for mobility: 10.7% [7.8–13.7] vs. 5.2% [4.1–6.3], p < 0.001; for vision: 9.3% [7.0–11.5] vs. 4.9% [4.0–5.8], p < 0.001). In multivariable-adjusted logistic regression, high blood cadmium was associated with higher odds of cognitive (OR = 1.71, 95% CI: 1.07–2.73, p = 0.036) and mobility difficulty (OR = 1.99, 1.12–3.55, p = 0.032); similar associations were observed for high blood lead (cognitive: OR = 1.73, 1.07–2.79, p = 0.036; mobility: OR = 2.04, 1.14–3.65, p = 0.030). High blood mercury (OR = 1.70, 95% CI: 1.04–2.77, p = 0.041), manganese (OR = 1.75, 1.06–2.87, p = 0.037), and selenium (OR = 1.72, 1.06–2.79, p = 0.038) were each associated with increased odds of cognitive difficulty in adjusted models; similar patterns were observed for mobility, but no significant associations were found for visual difficulty. No significant interaction effects were detected in any model. Functional limitation in cognition and mobility was independently associated with higher CVD prevalence among US adults. Concurrent high exposure to toxic metals and functional limitation was associated with the highest observed CVD burden; however, toxic metal exposure did not statistically modify the association between functional limitation and CVD risk.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».