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Record W2967860139 · doi:10.3389/fnut.2019.00138

Nutritional Strategies to Combat Type 2 Diabetes in Aging Adults: The Importance of Protein

2019· review· en· W2967860139 on OpenAlexaff
Kayleigh M. Beaudry, Michaela C. Devries

Bibliographic record

VenueFrontiers in Nutrition · 2019
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMuscle metabolism and nutrition
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsSarcopeniaLean body massType 2 diabetesMedicineWeight lossDiabetes mellitusObesityGlycemicEndocrinologyGerontologyAgeingInternal medicinePhysiologyBody weight

Abstract

fetched live from OpenAlex

The prevalence of pre-diabetes (PD) and type II diabetes (T2D) has risen dramatically in recent years affecting an estimated 422 million adults worldwide. The risk of T2D increases with age, with the sharpest rise in diagnosis occurring after age 40. With age, there is also a progressive decline in muscle mass starting after the age of 30. The decline in muscle mass and function due to aging is termed sarcopenia and immediately precedes the sharp rise in T2D. The purpose of the current review is to discuss the role of protein to attenuate declines in muscle mass and insulin sensitivity to prevent T2D and sarcopenia in aging adults. The current recommended dietary allowance for protein consumption is set at 0.8 g/kg/day and is based on dated studies on young healthy men and may not be sufficient for older adults. Protein consumption upwards of 1.0-1.5 g/kg/day in older adults is able to induce improvements in glycemic control and muscle mass. Obesity, particularly central or visceral obesity is a major risk factor in the development of PD and T2D. However, the tissue composition of weight loss in older adults includes both lean body mass and fat mass and therefore may have adverse metabolic consequences in older adults who are already at a high risk of lean body mass loss. High protein diets have the ability to increase weight loss while preserving lean body mass therefore inducing "high-quality weight loss," which provides favorable metabolic changes in older adults. High protein diets also induce beneficial outcomes on glycemic markers due to satiety, lowered post-prandial glucose response, increased thermogenesis, and the ability to decrease rates of muscle protein breakdown (MPB). The consumption of dairy specific protein consumption has also been shown to improve insulin sensitivity by improving body composition, enhancing insulin release, accelerating fat oxidation, and stimulating rates of muscle protein synthesis (MPS) in older adults. Exercise, specifically resistance training, also works synergistically to attenuate the progression of PD and T2D by further stimulating rates of MPS thereby increasing muscle mass and inducing favorable changes in glycemic control independent of lean body mass increases.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.903
Threshold uncertainty score0.890

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
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 head0.014
GPT teacher head0.273
Teacher spread0.259 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations42
Published2019
Admission routes1
Has abstractyes

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