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Record W4408613190 · doi:10.3389/fnut.2025.1519098

Status and factors related to hemoglobin concentration of people with vs. without disability—using nationwide claims check-up database

2025· article· en· W4408613190 on OpenAlexfundno aff
Seyune Lee, Young‐Il Jung, Hyejung Yoon, Se-Youn Jung, Boyoung Jeon, In‐Hwan Oh, Su Jin Jeong

Bibliographic record

VenueFrontiers in Nutrition · 2025
Typearticle
Languageen
FieldMedicine
TopicDown syndrome and intellectual disability research
Canadian institutionsnot available
FundersMinistry of Health, British ColumbiaKorea Health Industry Development Institute
KeywordsWelfarePropensity score matchingMedicineHemoglobinHealth careMatching (statistics)GerontologyEnvironmental healthInternal medicinePathology

Abstract

fetched live from OpenAlex

Background: Blood hemoglobin level is a key indicator of organ function and health status throughout the life course. As hemoglobin-related health problems are gaining attention, many studies on factors related to hemoglobin concentration are being conducted, yet few researches have been conducted targeting persons with disabilities. Furthermore, researches that consider the association between blood hemoglobin and the regional level health welfare resources are rare. This study aimed to explore the factors related to blood hemoglobin concentration among people with and without disability, and to contribute to the development of future nutritional policies and projects for persons with disabilities. Methods: A health insurance claims database with check-ups provided by the National Health Insurance Services (NHIS) was used. One-to-three propensity score matching was conducted between participants with and without disabilities. In addition to the individual clinical and health behavioral aspects based on the claims data, regional-level data of healthcare and social welfare resources was also collected, and multi-level analysis was conducted to identify factors associated with low blood hemoglobin level. Results: A total of 1,697 participants with disability and 5,091 without disabilities were yielded. Disability was significantly associated with lower hemoglobin level, even after propensity score matching. Sex, BMI, health behaviors, and clinical indicators were significantly associated with the blood hemoglobin level. Furthermore, region-level welfare budget was a significant factor among persons with disability. Conclusion: Our findings confirmed the significant association between disability and lower hemoglobin level. Regional health and welfare resources, as well as individual characteristics should be considered in implementation of further nutrition and health policies for persons with disabilities. Further studies are needed to understand of health outcomes of low hemoglobin level.

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 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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.082
Threshold uncertainty score0.446

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.019
GPT teacher head0.318
Teacher spread0.299 · 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

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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

Citations1
Published2025
Admission routes1
Has abstractyes

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