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Record W2488469559 · doi:10.1177/1010539516660374

Anemia Status in Relation to Body Mass Index Among Women of Childbearing Age in Bangladesh

2016· article· en· W2488469559 on OpenAlexaff
Ghose Bishwajit, Sanni Yaya, Shangfeng Tang

Bibliographic record

VenueAsia Pacific Journal of Public Health · 2016
Typearticle
Languageen
FieldNursing
TopicChild Nutrition and Water Access
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsBody mass indexMedicineAnemiaDemographyIndex (typography)Environmental healthObstetricsInternal medicine

Abstract

fetched live from OpenAlex

Undernutrition and micronutrient deficiency disorders together constitute a major public health concern in Bangladesh. Among many vitamin and mineral deficiency diseases, iron-deficiency anemia remains the most persistent and has been shown to contribute to high maternal and child morbidity and mortality in the country. In parallel with micronutrient malnutrition, the country is also experiencing a rising epidemic of overweight and obesity due to changing pattern in dietary behavior and body mass index status. Previous empirical studies have demonstrated a strong correlation between body weight and anemia status. However, results remain inconclusive and for Bangladesh such evidence is nonexistent. To this end, we conducted this study using Bangladesh Demographic and Health Survey 2011 data with an aim to explore the association between body mass index and anemia status among adult women in Bangladesh. According to the findings, age between 15 and 29 years ( P < .001, OR = 1.30, 95% CI = 1.12-1.49), experiencing first birth before reaching the age of 18 years ( P < .001, OR = 1.31, 95% CI = 1.15-1.50), lack of access to potable water ( P = .013, OR = 1.467, 95%CI = 1.085- 1.982), being underweight ( P < .001, 95% CI = 1.208-1.570) and normal weight ( P < .001, 95% CI = 1.819-2.516) were significantly associated with anemia status.

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)0.003
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 score0.020
Threshold uncertainty score0.437

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.021
GPT teacher head0.284
Teacher spread0.263 · 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

Citations49
Published2016
Admission routes1
Has abstractyes

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