Myopia Prevalence in Chinese‐Canadian Children in an Optometric Practice
Bibliographic record
Abstract
PURPOSE: The high prevalence of myopia in Chinese children living in urban East Asian countries such as Hong Kong, Taiwan, and China has been well documented. However, it is not clear whether the prevalence of myopia would be similarly high for this group of children if they were living in a Western country. This study aims to determine the prevalence and progression of myopia in ethnic Chinese children living in Canada. METHODS: Right eye refraction data of Chinese-Canadian children aged 6 to 12 years were collated from the 2003 clinical records of an optometric practice in Mississauga, Ontario, Canada. Myopia was defined as a spherical equivalent refraction (SER) equal or less than -0.50 D. The prevalence of myopia and refractive error distribution in children of different ages and the magnitude of refractive error shifts over the preceding 8 years were determined. Data were adjusted for potential biases in the clinic sample. A questionnaire was administered to 300 Chinese and 300 Caucasian children randomly selected from the clinic records to study lifestyle issues that may impact on myopia development. RESULTS: Optometric records of 1468 children were analyzed (729 boys and 739 girls). The clinic bias adjusted prevalence of myopia increased from 22.4% at age 6 to 64.1% at age 12 and concurrently the portion of the children that were emmetropic (refraction between -0.25 and +0.75 D) decreased (68.6% at 6 years to 27.2% at 12 years). The highest incidence of myopia for both girls ( approximately 35%) and boys ( approximately 25%) occurred at 9 and 10 years of age. The average annual refractive shift for all children was -0.52+/-0.42 D and -0.90+/-0.40 D for just myopic children. The questionnaire revealed that these Chinese-Canadian children spent a greater amount of time performing near work and less time outdoors than did Caucasian-Canadian children. CONCLUSIONS: Ethnic Chinese children living in Canada develop myopia comparable in prevalence and magnitude to those living in urban East Asian countries. Recent migration of the children and their families to Canada does not appear to lower their myopia risk.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.003 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".