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Record W1998652838 · doi:10.5539/gjhs.v7n3p90

Interaction of Lifestyle and Work Ability Index in Blue Collar Workers

2014· article· en· W1998652838 on OpenAlexvenueno aff
Saber Mohammadi, Mostafa Ghaffari, Alireza Abdi, Baharak Bahadori, Elham Mirzamohammadi, Mirsaeed Attarchi

Bibliographic record

VenueGlobal Journal of Health Science · 2014
Typearticle
Languageen
FieldHealth Professions
TopicWorkplace Health and Well-being
Canadian institutionsnot available
FundersIran University of Medical Sciences
KeywordsBody mass indexConfoundingLogistic regressionBlue collarMedicineIndex (typography)Cigarette smokingWork (physics)Physical activityGerontologyEnvironmental healthDemographyPhysical therapyEngineering

Abstract

fetched live from OpenAlex

BACKGROUND: Early labor force exit is one of the major problems worldwide. The present study investigates the relationship between work ability and lifestyle. METHODS: This study was conducted at a manufacturing plant in Tehran in 2012. All 851 male workers in this plant were included into the study and their work ability was assessed using the Work Ability Index (WAI). Based on the obtained scores, the participants were then classified into four work ability groups (poor, moderate, good, or excellent). Moreover, the participants' lifestyles were studied in three areas, including physical activity, cigarette smoking, and Body Mass Index (BMI). RESULTS: The average work ability index score was 42.07, ranging from 7-48. Among the participants, 6.4% (43), 6.5% (44), 38.3% (259), and 48.8% (330) were in the groups with poor, moderate, good, and excellent work ability, respectively. The results of logistic regression analysis showed that there is a significant relationship between work ability and lifestyle (cigarette smoking, BMI, and physical activity) even after adjustment for confounding variables (P<0.05). CONCLUSIONS: According to the results of the present study, there might be a relationship between work ability and lifestyle (physical activity, BMI, cigarette smoking). Therefore, it is recommended to implement a lifestyle quality enhancement program to improve work ability in working environments.

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)0.012
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.014
Threshold uncertainty score0.517

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0120.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.021
GPT teacher head0.398
Teacher spread0.377 · 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

Citations18
Published2014
Admission routes1
Has abstractyes

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