Measuring urbanicity as a risk factor for childhood wheeze in a transitional area of coastal ecuador: a cross-sectional analysis
Bibliographic record
Abstract
BACKGROUND: The urbanisation process has been associated with increases in asthma prevalence, an observation supported largely by studies comparing urban with rural populations. The nature of this association remains poorly understood, likely because of the limitations of the urban-rural approach to understand what a multidimensional process is. OBJECTIVE: This study explored the relationship between the urbanisation process and asthma prevalence using a multidimensional and quantitative measure of urbanicity. METHODS: A cross-sectional analysis was conducted in 1843 children living in areas with diverse levels of urbanisation in the district of Quinindé, Ecuador in 2013-2015. Categorical principal components analysis was used to generate an urbanicity score derived from 18 indicators measured at census ward level based on data from the national census in 2010. Indicators represent demographic, socioeconomic, built environment and geographical dimensions of the urbanisation process. Geographical information system analysis was used to allocate observations and urban characteristics to census wards. Logistic random effects regression models were used to identify associations between urbanicity score, urban indicators and three widely used definitions for asthma. RESULTS: The prevalence of wheeze ever, current wheeze and doctor diagnosis of asthma was 33.3%, 13% and 6.9%, respectively. The urbanicity score ranged 0-10. Positive significant associations were observed between the urbanicity score and wheeze ever (adjusted OR=1.033, 95% CI 1.01 to 1.07, p=0.05) and doctor diagnosis (adjusted OR=1.06, 95% CI 1.02 to 1.1, p=0.001). For each point of increase in urbanicity score, the prevalence of wheeze ever and doctor diagnosis of asthma increased by 3.3% and 6%, respectively. Variables related to socioeconomic and geographical dimensions of the urbanisation process were associated with greater prevalence of wheeze/asthma outcomes. CONCLUSIONS: Even small increases in urbanicity are associated with a higher prevalence of asthma in an area undergoing the urban transition. The use of a multidimensional urbanicity indicator has greater explanatory power than the widely used urban-rural dichotomy to improve our understanding of how the process of urbanisation affects the risk of asthma.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".