Evaluating the associations between social variables and nutritional risk in a population cohort of Canadian adults
Bibliographic record
Abstract
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
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".