Changes in chronic disease risk factors and current exercise habits among Canadian adults living with and without a child during the COVID-19 pandemic
Bibliographic record
Abstract
Background: Canadians have been gravely impacted by the COVID-19 pandemic, and adults living with children may have been disproportionately impacted. The objective of this study was to describe changes in chronic disease risk factors and current exercise habits among adults living with and without a child younger than 18 years old. Data and Methods: A repeated cross-sectional study was conducted using data collected from Canadians aged 15 and older via the Canadian Perspective Survey Series (CPSS) in late March (CPSS1, N=4,383), early May (CPSS2, N=4,367) and mid-July 2020 (CPSS4, N=4,050). This analysis included participants aged 25 and older. At three points during 2020, participants reported whether they increased, decreased, or had not changed their consumption of alcohol, tobacco and junk food or sweets, their screen use, and whether they currently exercised indoors or outdoors. Behaviours were compared for adults living with and without a child, and unadjusted odds ratios (OR) and 95% confidence intervals (CI) were estimated using logistic regression. Results: The presence of a child in the household was associated with higher odds of increased (compared with decreased or no change) alcohol consumption at all three time points, consumption of junk food and sweets at CPSS1 (OR: 1.69, 95% CI: 1.09-2.60), and time on the Internet at CPSS1 (OR: 1.59, 95% CI: 1.05-2.41) and CPSS4 (OR: 1.56, 95% CI: 1.05-2.29). Compared with older adults (aged 55 and older), younger adults (aged 25 to 54) were more likely to exhibit increases in chronic disease risk factors regardless of the presence of a child in the household. Interpretation: A substantial proportion of Canadian adults reported increased chronic disease risk factors during the pandemic, with greater increases noted among adults living with a child, compared with those living without a child. Public health interventions are urgently needed to mitigate the long-term impact of the pandemic on population health.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 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".