A More Supportive Social Environment May Protect Against Nutritional Risk: A Cross-Sectional Analysis Using Data From the Canadian Longitudinal Study on Aging
Bibliographic record
Abstract
BACKGROUND: Nutritional risk has been linked to individual social factors, but the relationship with the overall social environment has not been assessed. OBJECTIVES: To evaluate associations between different support profiles of the social environment and nutritional risk using cross-sectional data from the Canadian Longitudinal Study on Aging (n = 20,206). Subgroup analyses were performed among middle-aged (range, 45-64 y; n = 12,726) and older-aged (≥65 y, n = 7480) adults. Consumption of major food groups [whole grains, proteins, dairy products, and fruits and vegetables (FV)] by social environment profile was a secondary outcome. METHODS: Latent structure analysis (LSA) classified participants into social environment profiles according to data on network size, social participation, social support, social cohesion, and social isolation. Nutritional risk and food group consumption were assessed with the SCREEN-II-AB and Short Dietary questionnaires, respectively. ANCOVA was conducted to compare SCREEN-II-AB mean scores by social environment profile, adjusted for sociodemographic and lifestyle factors. Models were repeated to compare mean food group consumption (times/day) by social environment profile. RESULTS: LSA identified 3 social environment profiles classified as low, medium, and high support (17%, 40%, and 42% of the sample, respectively). Adjusted mean SCREEN-II-AB scores significantly increased with increasing social environment support, with the low support score indicating high nutritional risk status [low, medium, high support, respectively: 37.1 (99% CI: 36.9, 37.4), 39.3 (39.2, 39.5), 40.3 (40.2, 40.5), all comparisons P < 0.0001]. Results were consistent among age subgroups. The low support social environment profile had lower consumption of protein [low, medium, high support, respectively (mean ± SD): 2.17 ± 0.09, 2.21 ± 0.07, 2.23 ± 0.08, P = 0.004], dairy (2.32 ± 0.23, 2.40 ± 0.20, 2.38 ± 0.21, P = 0.009), and FV (3.65 ± 0.23, 3.94 ± 0.20, 4.08 ± 0.21, P < 0.0001), with some variation among age subgroups. CONCLUSIONS: The low support social environment profile had the poorest nutritional outcomes. Therefore, a more supportive social environment may protect against nutritional risk among middle- and older-aged adults.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".