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Record W4382931404 · doi:10.1097/opx.0000000000002035

Is There Any Association between Nutrition and Myopia? A Systematic Review

2023· review· en· W4382931404 on OpenAlexaboutno aff
Sruthi Chamarty, Satish Gupta, Rohit Dhakal, Pavan K. Verkicharla

Bibliographic record

VenueOptometry and Vision Science · 2023
Typereview
Languageen
FieldMedicine
TopicOphthalmology and Visual Impairment Studies
Canadian institutionsnot available
Fundersnot available
KeywordsOdds ratioMedicineOddsMeta-analysisMEDLINEAssociation (psychology)Systematic reviewCohort studyRandomized controlled trialInternal medicineLogistic regressionPsychologyBiology

Abstract

fetched live from OpenAlex

SIGNIFICANCE: This systematic review highlights the possible role of nutrition in myopia based on qualitative analysis of vast and diverse literature that investigated this association. PURPOSE: We systematically reviewed the outcomes of the studies that previously investigated the association between nutrition and myopia. METHODS: EMBASE, MEDLINE, and PubMed were searched by two independent authors to identify cross-sectional, cohort, retrospective, or interventional studies that assessed the association of nutrition with myopia from inception to the year 2021. Furthermore, the reference list of the included articles was screened. The data from the included studies were extracted, and qualitative analysis was performed. Quality assessment for noninterventional studies and interventional trials was performed using the Newcastle-Ottawa Scale and Cochrane RoB 2, respectively. RESULTS: Twenty-seven articles were included in the review. Most of the nutrients and dietary elements investigated in noninterventional studies showed inconsistencies in their association with myopia, with the majority indicating no association. Nine studies showed a significant association of diverse nutrients and dietary elements with either an increase (odds ratio, 1.07) or a decrease (odds ratio, 0.5 to 0.96) in the risk of myopia development. However, a majority of these studies have minimal odds ratios with wider or overlapping confidence intervals, implicating weaker associations. All three nutrients and dietary elements assessed in the interventional trial had implications for myopia control, with two trials indicating a clinically minimal effect. CONCLUSIONS: This review implies that there is some evidence to indicate a potential influence of specific nutrients and dietary elements in myopia development, which are supported by several theories. However, given the vast, diverse, and complex nature of nutrition, more systematic investigation is warranted to comprehend the extent to which these specific nutrients and dietary elements are associated with myopia through longitudinal studies by subduing the limitations in the existing literature.

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

Direct model labels (unvalidated)

Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.

Model armCategoriesStudy designConfidence
gemmano category
Domain: not available · Genre: Review
About the Canadian research system: no · About a Canadian topic: no
Systematic reviewlow
gptno category
Domain: not available · Genre: Review
About the Canadian research system: no · About a Canadian topic: no
Systematic reviewhigh
models agreeAgreement compares identical category sets and study designs across arms.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.020
Threshold uncertainty score0.675

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0000.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.103
GPT teacher head0.551
Teacher spread0.448 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Labeled directly by 2 models reading the full record.

The models applied no category: nothing in the taxonomy fit this work.
Study designSystematic review
Domainnot available
GenreReview

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".

Quick stats

Citations13
Published2023
Admission routes1
Has abstractyes

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