Evidence map›Paper›PMID 39287642›Full record

ArticleEuropean journal of nutrition2024

Dietary patterns derived by reduced rank regression, macronutrients as response variables, and variation by economic status: NHANES 1999-2018.

Samuel C Coxall, Frances Em Albers, Sherly X Li, Zumin Shi, Allison M Hodge, Brigid M Lynch, Yohannes Adama Melaku

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PubMed Full text at PMC Publisher
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Article in European journal of nutrition, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

Samuel C CoxallCancer Epidemiology Division, Cancer Council Victoria, Level 8, 200 Victoria Parade, East Melbourne, Melbourne, VIC, 3002, Australia.ORCID http://orcid.org/0009-0009-9522-0762
Frances Em AlbersCancer Epidemiology Division, Cancer Council Victoria, Level 8, 200 Victoria Parade, East Melbourne, Melbourne, VIC, 3002, Australia.ORCID http://orcid.org/0000-0002-7319-5182
Sherly X LiCancer Epidemiology Division, Cancer Council Victoria, Level 8, 200 Victoria Parade, East Melbourne, Melbourne, VIC, 3002, Australia.ORCID http://orcid.org/0000-0002-7840-4051
Zumin ShiHuman Nutrition Department, College of Health Sciences, QU Health, Qatar University, Doha, Qatar.ORCID http://orcid.org/0000-0002-3099-3299
Allison M HodgeCancer Epidemiology Division, Cancer Council Victoria, Level 8, 200 Victoria Parade, East Melbourne, Melbourne, VIC, 3002, Australia.ORCID http://orcid.org/0000-0001-5464-2197
Brigid M LynchCancer Epidemiology Division, Cancer Council Victoria, Level 8, 200 Victoria Parade, East Melbourne, Melbourne, VIC, 3002, Australia. Brigid.Lynch@cancervic.org.au.ORCID http://orcid.org/0000-0001-8060-547X
Yohannes Adama MelakuCancer Epidemiology Division, Cancer Council Victoria, Level 8, 200 Victoria Parade, East Melbourne, Melbourne, VIC, 3002, Australia.ORCID http://orcid.org/0000-0002-3051-7313

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeMacronutrient intakes vary across people and economic status, leading to a disparity in diet-related metabolic diseases. This study aimed to provide insight into this by: (1) identifying dietary patterns in adults using reduced rank regression (RRR), with macronutrients as response variables, and (2) investigating the associations between economic status and macronutrient based dietary patterns, and between dietary patterns with central obesity (waist circumference) and systemic inflammation (C-reactive protein [CRP]).

methods41,849 US participants from the National Health and Nutrition Examination Survey (NHANES), 1999-2018 were included. The percentages of energy from protein, carbohydrates, saturated fats, and unsaturated fats were used as response variables in RRR. Multivariable generalized linear models with Gaussian distribution were employed to investigate the associations.

resultsFour dietary patterns were identified. Economic status was positively associated with both the high fat, low carbohydrate [β

conclusionMacronutrient dietary patterns, which varied by economic status and were associated with metabolic health markers, may explain associations between economic status and health.

Indexed as

DietNutrientsNutrition SurveysAdultC-Reactive ProteinCross-Sectional StudiesFeeding BehaviorFemaleHumansInflammationMaleMiddle AgedRegression AnalysisSocioeconomic FactorsUnited StatesWaist CircumferenceC-Reactive ProteinNutrientsDietary patternsEconomic statusInflammationMacronutrientsObesityReduced rank regression

Identifiers

PMID39287642
PMCPMC11519099

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