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Record W2802800015 · doi:10.3233/nha-180042

Relationships between the inflammatory potential of the diet, aging and anthropometric measurements in a cross-sectional study in Pakistan

2018· article· en· W2802800015 on OpenAlexaff
Iftikhar Alam, Nitin Shivappa, James R. Hébert, Graham Pawelec, Anis Larbi

Bibliographic record

VenueNutrition and Healthy Aging · 2018
Typearticle
Languageen
FieldMedicine
TopicNutritional Studies and Diet
Canadian institutionsHealth Sciences North
FundersKing Saud University
KeywordsAnthropometryBody mass indexMedicineObesityWaistCross-sectional studyWaist–hip ratioInternal medicineEndocrinologyPhysiologyDemographyPathology

Abstract

fetched live from OpenAlex

BACKGROUND: Little is known about associations between dietary inflammation, age and anthropometric measurements. OBJECTIVE: In this regard, we examine how DII is related to age, anthropometrics [weight, Body mass index (BMI), waist to hip ratio (WHR)] and other parameters of nutrition (energy, protein, fats and cholesterol intake, Net Endogenous Acid Production (NEAP) and Phytochemical Index (PI)) in a cross-sectional study in Pakistan. DESIGN: Only men ( n = 651, age 54–95 years) participated in the study. Anthropometric data were collected using standard methods. DII was calculated from nutrients derived from 24-hr Dietary Recall questionnaires. NEAP and PI were calculated by established algorithms using information on nutrient intake. RESULTS: The results show that with increasing age, there was a significant increase in the DII score ( p < 0.05). Similarly significant positive correlations were found between DII score and weight, BMI, WHR and % BF ( p, for all trends < 0.05). DII score significantly positively correlated with the dietary factors studied i.e. energy, protein, and fats ( p, for all trends < 0.0001) but non-significantly with cholesterol ( p > 0.05). Similarly, a significant positive correlation with NEAP ( p < 0.0001) was found, but negative with PI ( p < 0.0001). CONCLUSION: In conclusion, the present study shows direct positive correlations between the DII, age and indices of obesity, and thus supports the hypothesis that diet may have a role in the development of obesity through inflammatory modulation mechanisms in elderly.

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)0.001
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 score0.006
Threshold uncertainty score0.416

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
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 head0.104
GPT teacher head0.399
Teacher spread0.295 · 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

Citations35
Published2018
Admission routes1
Has abstractyes

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