Evaluating the associations between social variables and nutritional risk in a population cohort of Canadian adults
Notice bibliographique
Résumé
Background: Nutritional risk is a public health concern associated with aging. While nutritional risk has been linked to various individual social factors, an assessment of the relationship between nutritional risk and the overall strength of social environment, through the assessment of multiple social factors in combination, has not been considered in previous research. Objective: To evaluate associations between the strength of social environment and nutritional risk using cross-sectional data from the Canadian Longitudinal Study on Aging (n=20,786). Subgroup analyses were performed among middle-aged (45-64 years, n = 13,060) and older-aged (65 years, n = 7,726) subgroups. Consumption of four major food groups (whole grains, proteins, dairy products, and fruits and vegetables) by social environment group was assessed as a secondary outcome.Methods: Latent class analysis (LCA) was performed to classify participants into social environment groups according to data on network size, social participation, social support, social cohesion, and social isolation. Nutritional risk was assessed with the SCREEN-II-AB questionnaire and consumption of food groups by the Short Dietary Questionnaire. Analysis of covariance was conducted to compare estimated means of the SCREEN-II-AB score by strength of social environment group, adjusted for sociodemographic and lifestyle factors. Three statistical models were performed with increasing adjustment (model 1: adjusted for age, sex, and province; model 2: additionally adjusted for income, education, urban/rural residence, ethnicity and immigration status; model 3: additionally adjusted for smoking status). Models were repeated to compare the mean consumption of food groups (times/day) by social group. Results: LCA identified three distinct social environment groups classified as low, medium, and high social strength (18%, 40%, and 42% of the sample, respectively). Adjusted mean SCREEN-II-AB scores differed significantly between all social environment groups in a dose-response manner for all three statistical models, with the low social strength group consistently having an adjusted mean score indicating high nutritional risk. For the fully adjusted model, Model 3, adjusted mean SCREEN-II-AB scores were as follows; Low: 37.1 (99% confidence interval (CI): 36.8, 37.4); Medium: 39.3 (39.2, 39.5); High: 40.3 (40.2, 40.5), (p<0.0001). Respondents in the low strength of social environment group also reported significantly lower consumption frequency of the proteins, dairy, and fruits and vegetables food groups (including and excluding juices) compared to the medium and high social strength groups with some variation among age subgroups (p<0.002). Responses significantly differed by strength of social environment for all items of the SCREEN-II-AB, with the low social strength group indicating greater frequency of skipping meals, having a poorer appetite, difficulty swallowing food, and cooking their own meals compared to the other social groups. The low strength of social environment group also indicated lower daily servings of fruits and vegetables, cups of fluids, and the consumption of meals with others. Conclusions: These findings suggest that adults with weak social environments are more vulnerable to nutritional risk. Nutritional risk interventions should consider social factors as targets.Keywords: Aging; social environment; nutrition; nutritional risk; food groups; CLSA
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 machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,002 | 0,002 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,003 | 0,004 |
| Études des sciences et des technologies | 0,003 | 0,001 |
| Communication savante | 0,001 | 0,000 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 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 source (Gemma direct ou Codex distillé), 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 ».