Lifestyle Characteristics and Gastroesophageal Reflux Disease: A Population-Based Study in Albania
Bibliographic record
Abstract
Aim. We aimed to assess the prevalence and lifestyle correlates of gastroesophageal reflux disease (GERD) in the adult population of Albania, a Mediterranean country in Southeast Europe which has experienced major behavioral changes in the past two decades. Methods. A cross-sectional study, conducted in 2012, included a population-representative sample of 845 individuals (≥18 years) residing in Tirana (345 men, mean age: 51.3 ± 18.5; 500 women, mean age: 49.7 ± 18.8; response rate: 84.5%). Assessment of GERD was based on Montreal definition. Covariates included socioeconomic characteristics, lifestyle factors, and body mass index. Logistic regression was used to assess the association of socioeconomic characteristics and lifestyle factors with GERD. Results. The overall prevalence of GERD was 11.9%. There were no significant sex differences, but a higher prevalence among the older participants. In fully adjusted models, there was a positive relationship of GERD with smoking, physical inactivity, fried food consumption, and obesity, but not so for alcohol intake and meat consumption. Conclusion. We obtained important evidence on the prevalence and lifestyle correlates of GERD in a Western Balkans' country. Smoking, physical inactivity, and obesity were strong "predictors" of GERD in this population. Findings from this study should be replicated in prospective studies in Albania and other transitional settings.
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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 | 0.001 | 0.001 |
| 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".