Low‐to‐Moderate Daytime Physical Activities Predicted Higher‐Quality Sleep Among Habitually Active Agropastoralists
Bibliographic record
Abstract
INTRODUCTION: The positive effects of physical activity (PA) on sleep are widely promoted by public health organizations and supported by abundant empirical evidence. Nonetheless, there remains a dearth of studies investigating the association between daytime PA and nighttime sleep among non-urban and nonindustrial populations that habitually engage in PA as part of their subsistence strategy. METHODS: Here, we examined the bidirectional relationship between PA and sleep. We also looked at age, gender, and occupation-level differences in moderate-to-vigorous-intensity PA (MVPA), low-intensity PA (LPA), and sedentary activity durations among Basotho and Xhoxa agropastoralists residing in rural villages in the Eastern Cape, South Africa. We analyzed activity and sleep data collected from 113 individuals using MotionWatch actigraphy wristwatches across three field seasons (7111 individual days). RESULTS: Percentage daily total MVPA decreased with age, though older participants maintained low activity levels and did not suffer from poorer sleep compared to younger participants. Herders spent more percentage of their day in higher-intensity activity than non-herders. Overall, women had greater daily percentage MVPA and lower percentage sedentary activity than men. Durations of total MVPA and LPA decreased total sleep time (TST) and improved sleep quality (increased sleep efficiency (SE), decreased fragmentation, and decreased percentage wake after sleep onset). Daytime PA measures were not affected by sleep duration or quality from the previous night. CONCLUSIONS: Among this group of habitually active agropastoralists, low-to-moderate-intensity PA durations consistently predicted higher sleep quality. Our findings showed that sleep quality was more strongly affected by PA than sleep duration.
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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 | 0.000 | 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) | 0.003 | 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".