Physical activity during covid-19 lockdown: Relationship with sedentary behaviour, health-related quality of life, loneliness, and sleep quality among a sample of Nigerian adults
Bibliographic record
Abstract
COVID-19 lockdown, targeted at preventing the spread of coronavirus, had deleterious effects on physical and psychosocial health. This study examined the association between physical activity (PA), sedentary behaviour, health-related quality of life (HRQoL), loneliness and quality of sleep of 507 Nigerian adults during the COVID-19 lockdown. Five hundred and seven respondents (aged 18-67 years) from 12 States completed an online survey on RedCap. Questionnaires comprising the Stages of Change scale, Pittsburgh Sleep Quality Index, International Sedentary Assessment Tool, UCLA Loneliness Questionnaire, Short Form-12 Health Survey, and International Physical Activity Questionnaire were used. Respondents were categorised based on exercise behaviour as non-exercisers, non-regular exercisers, or regular exercisers; and based on age into 18-24, 25-34, 35-44 and > 44 years categories. Descriptive and inferential statistics were used to analyse the data. About 33.1% of respondents did not meet moderate-to-vigorous PA levels. The physical component of HRQoL was positively associated with total PA (p = 0.04). Among the non- exercisers, the odds of being regular exercisers during pre-COVID-19 lockdown were significantly higher for the 35-44 (odds ratio [OR] = 3.49; 95% CI = 1.44, 8.48, p = 0.01) and > 44 years age groups (OR = 2.98; 95% CI: 1.16, 7.62, p = 0.02) relative to 18-24 years age category. During COVID-19 lockdown, > 44 (OR = 3.65; 95% CI: 1.47, 9.07, p = 0.005), 35-44 (OR = 6.42; 95% CI 2.75, 14.96, p = 0.001) and 25-34 (OR = 2.35; 95% CI: 1.15, 4.80, p = 0.02) years age categories had significant higher odds of being regular exercisers compared to the 18-24 years age group. There was a high rate of physical inactivity among Nigerian adults during the COVID-19 lockdown, which was directly influenced by the physical components of HRQoL. Older age was an independent predictor of exercise behaviour before and during the COVID-19 lockdown among Nigerian 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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".