Are there gender based differences in participation and time spent in physical activity in Albania? Evidence from 2017-18 demographic and health survey
Bibliographic record
Abstract
BACKGROUND: Since 1990, Albania has embraced the market economy and globalization. Prosperity and modernization have also brought significant lifestyle changes toward unhealthy behaviours, doubling the mortality from non-communicable diseases (NCDs). While Physical Activity (PA) can mitigate the NCDs burden, participation is low in Albania. To date, research on PA determinants that could meaningfully inform policy is lacking. To fill this gap, this study examines the PA behaviour among Albanian adults. Specifically, we assess the decisions to participate, and the time spent in PA. METHODS: Using the 2017-2018 Albania Demographic and Health Survey data and a double-hurdle regression model, we simultaneously assess the influence of demographic, socioeconomic and lifestyle factors on the likelihood of participating (extensive margin) and the time spent (intensive margin) in PA. To understand gender differences regarding PA decisions, we run separate models for men and women. RESULTS: Results show significant variations in the likelihood of participation and the time spent in PA, by household economic status, administrative regions, occupation, and education. We find that likelihood of participation in PA increases with household wealth, but conditional on participation, affluent Albanians spent less time in PA. Education and employment status also have opposite effects on participation and time spent margins. Results show notable gender-based differences in PA behaviour (either for participation or time spent) related to education, age, family structure (marital status and the number of young children), regions, occupation, and lifestyle factors. CONCLUSIONS: Insights in understanding the PA behaviour of Albanian adults allow policymakers to identify socio-demographic groups most in need of intervention effort. To effectively support PA among Albanians, policymakers should target males and females differently and address gender-specific needs accordingly.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".