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Record W7084132694 · doi:10.22442/jlumhs.2025.01335

Relationship between Body Mass Index and Occupation with Low Back Pain

2025· article· en· W7084132694 on OpenAlexaboutno aff

Bibliographic record

VenueDOAJ (DOAJ: Directory of Open Access Journals) · 2025
Typearticle
Languageen
FieldComputer Science
TopicImage Processing and 3D Reconstruction
Canadian institutionsnot available
Fundersnot available
KeywordsLow back painBody mass indexIncidence (geometry)PopulationSports medicineCross-sectional studyAnthropometry

Abstract

fetched live from OpenAlex

OBJECTIVE: This study aimed to identify the relationship between body mass index (BMI) and occupation with low back pain (LBP) incidence in Zainoel Abidin Hospital. METHODOLOGY: This cross-sectional study used convenience sampling to include 237 patients with LBP selected from a population of 618 at the Neurology Polyclinic, Zainoel Abidin Hospital. Data were collected using the Short Form McGill Pain Questionnaire (SFMPQ) and analyzed descriptively to assess pain characteristics and intensity among participants. The chi-square test was used to identify correlations between key variables. RESULTS: Comprehensive results were obtained. 58.7% of the samples had a thin/normal BMI, 57.4% had an occupation background of self-employed/retired/housewives, and 87.8% experienced mild pain. This study showed a relationship between BMI and LBP (p = 0.009) and no relationship between occupation and LBP (p = 0.129). CONCLUSION: The findings indicate a significant relationship between BMI and the incidence of LBP, while no significant association was found between occupation type and LBP among patients at Zainoel Abidin Hospital. Workers are encouraged to maintain a healthy BMI and practice proper workplace ergonomics to reduce LBP risk, especially for physically demanding roles.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScholarly communication
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.699
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0020.004
Open science0.0010.000
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 head0.123
GPT teacher head0.483
Teacher spread0.359 · 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.

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

Citations0
Published2025
Admission routes1
Has abstractyes

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