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Record W2044419502 · doi:10.2114/jpa.21.273

Adiposity, Central Body Fat Distribution and Blood Pressure among Young Bengalee Adults of Kolkata, India: Sexual Dimorphism.

2002· article· en· W2044419502 on OpenAlexfundno aff
Mithu Bhadra, Ashish Mukhopadhyay, Kaushık Bose

Bibliographic record

VenueJournal of PHYSIOLOGICAL ANTHROPOLOGY and Applied Human Science · 2002
Typearticle
Languageen
FieldMedicine
TopicBody Composition Measurement Techniques
Canadian institutionsnot available
FundersMcGill University
KeywordsMedicineBlood pressureWaistSexual dimorphismBody mass indexOverweightDemographyAnthropometryFat distributionInternal medicineObesityEndocrinology

Abstract

fetched live from OpenAlex

A cross-sectional study of 174 men and 153 women of Bengalee ethnicity was undertaken to compare levels of adiposity, central body fat distribution and blood pressure. The mean age of both the sexes were similar (men = 20.1 years; women = 20.0 years). Significantly more women (n = 42, 27.5%) were overweight (body mass index, BMI > or = 25.0 kg/m2) as compared with men (19, 10.9%). Men were significantly taller and heavier. They also had significantly greater mean waist (WC) and mid upper arm (MUAC) circumferences compared with women. On the other hand, women had significantly (p < 0.001) greater mean BMI, biceps (BSF), triceps (TSF) and subscapular (SSF) skinfolds. The mean values of systolic (SBP), diastolic (DBP) and mean arterial (MAP) blood pressure were significantly greater among men. These significant differences existed even after controlling for BMI. Regression analyses revealed that sex had significant effect on all these variables even after controlling for BMI. Correlation studies showed that WC was found to be much more strongly correlated than BMI with SBP, DBP and MAP, in both sexes. However, when the effect of WC (along with BMI) was also controlled for, there was no significant sex difference in blood pressure.

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 categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.848
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.005
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 head0.021
GPT teacher head0.273
Teacher spread0.252 · 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 designBench or experimental
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

Citations12
Published2002
Admission routes1
Has abstractyes

Explore more

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