Social Factors and Nutrition Risk in Community-Living Seniors During the COVID-19 Pandemic
Bibliographic record
Abstract
Pandemic countermeasures (e.g., lockdown, restrictions) enacted to minimize the spread of COVID-19 may put older adults at nutrition risk. This thesis uses an online/telephone survey to investigate factors associated with nutrition risk for community-dwelling older adults living in Hamilton, Ontario, Canada during the COVID-19 pandemic. Data were collected on nutrition risk, loneliness, mental health, assistance with meal preparation and/or delivery, frequency of making phone/video calls and using social media, and more. Subsequent data were collected in waves approximately three months apart. Objectives of this thesis were to understand the prevalence of high nutrition risk and identify the association with social-related variables that could be impacted by COVID-19 during different time points of the pandemic. Research questions were: \n \n1. What is the prevalence of high nutrition risk (SCREEN-8 score <38) in the IMPACT sample? \n \n2. Are participant-reported variables (self-reported mental health, loneliness over the past week, and receiving assistance with meal preparation or delivery) that could be impacted by COVID-19 shelter-in-place public health policy in the first wave of the pandemic, associated with baseline nutrition risk scores (SCREEN-8) in community-dwelling adults over 65 years old in Hamilton, Ontario, when adjusting for meaningful covariates (e.g., sex, age)? \n \n3. Is there a change in median nutrition risk score over nine months in community-dwelling adults over 65 years old in Hamilton, Ontario? \n \n4. Do participants change nutrition risk categorization over this time frame? \n \n5. Are changes in mental health, loneliness, frequency of video/phone calls and use of social media associated with change in nutrition risk scores over time (from baseline to nine months)? \n \nFrom this sample of older adults (n=272, 78±7.3 years old, 70% female), we found that nutrition risk was prevalent among the community-dwelling older adults (64% at high risk). In a multivariable cross-sectional analysis that examined baseline only, loneliness in the past week (β -2.92, 95% CI [-5.51, -0.34]) and resilience (β 1.28, [0.04, 2.52]) were found to be associated with nutrition risk. In a second longitudinal analysis (n=178) based on a subset with a complete nutrition risk questionnaire nine months later, authors also found that frequency of direct social contacts from phone/video calls was associated with less nutrition risk (β -6.84, [-12.9, -0.77]), but people using more social media are more likely to be at high risk (β 6.19, [0.64, 11.75]). \n \nFindings from this thesis may inform public health interventions with respect to social interactions in pandemic circumstances or other challenging situations. This research also implies that it is critical to understand and advocate for healthy social media use to improve nutrition for older adults. Strategies to mitigate the adverse outcomes, such as loneliness and subsequent nutrition risk of future pandemic countermeasures should target this vulnerable group.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| 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".