Heat stress perception, knowledge levels and health consequences of urban heat in major cities in Bangladesh
Bibliographic record
Abstract
Urban heatwaves are a growing concern, especially in South Asian countries grappling with rapid urbanization and limited resources. While prior studies focused on the biophysical aspects of urban heat islands in this region, there is limited evidence of people’s understanding of urban heat stress and its health consequences. This study aimed to investigate the perceived urban heat risk and associated health impacts in Bangladesh. A cross-sectional study involving 898 participants in eight major cities in Bangladesh were included in the study. A substantial proportion of individuals regularly experienced urban heat stress but have limited awareness of heatwave reduction measures. Moreover, perceived physiological impacts were found to be more severe than psychological impacts. Urban heat also moderately affects daily activities, particularly transportation and sleep/rest. Factors like gender, home cooling systems, and extended outdoor exposure intensified heat's physiological and psychological impacts, while students, highly educated individuals, residents of traditional katcha houses, and those in good health experienced milder effects. Furthermore, individuals over 30 years of age and employed individuals exhibited greater knowledge about heat impact reduction but less affected by psychological impacts. These findings can inform targeted interventions and guidelines for heat mitigation and adaptation in South Asian cities.
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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 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 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".