Evidence map›Paper›PMID 31618988›Full record

ArticleNutrients2019

Day-Time Patterns of Carbohydrate Intake in Adults by Non-Parametric Multi-Level Latent Class Analysis-Results from the UK National Diet and Nutrition Survey (2008/09-2015/16).

Chaochen Wang, Suzana Almoosawi, Luigi Palla

Abstract readComparative Study
In one paragraph

Article in Nutrients, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed, 1 pooled it
–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

5 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
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  3. Review
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  5. Review
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

3 authors.

Chaochen WangDepartment of Public Health, Aichi Medical University, Nagakute, Aichi, 480-1195, Japan. chaochen@wangcc.me.
Suzana AlmoosawiNNEdPro Global Centre for Nutrition and Health, Cambridge, CB4 0WS, UK. suzana.almoosawi@gmail.com.
Luigi PallaDepartment of Medical Statistics, London School of Hygiene & Tropical Medicine, London, WC1E 7HT, UK. Luigi.Palla@lshtm.ac.uk.

Funding

Japan Society for the Promotion of Science 19K20199
6 · The paper itself

Abstract

This study aims at combining time and quantity of carbohydrate (CH) intake in the definition of eating patterns in UK adults and investigating the association of the derived patterns with type 2 diabetes (T2D). The National Diet and Nutrition Survey (NDNS) Rolling Program included 6155 adults in the UK. Time of the day was categorized into 7 pre-defined time slots: 6-9 am, 9-12 noon, 12-2 pm, 2-5 pm, 5-8 pm, 8-10 pm, and 10 pm-6 am. Responses for CH intake were categorized into: no energy intake, CH <50% or ≥50% of total energy. Non-parametric multilevel latent class analysis (MLCA) was applied to identify eating patterns of CH consumption across day-time, as a novel method accounting for the repeated measurements of intake over 3-4 days nested within individuals. Survey-designed multivariable regression was used to assess the associations of CH eating patterns with T2D. Three CH eating day patterns (low, high CH percentage and frequent CH intake day) emerged from 24,483 observation days; based on which three classes of CH eaters were identified and characterized as: low (28.1%), moderate (28.8%) and high (43.1%) CH eaters. On average, low-CH eaters consumed the highest amount of total energy intake (7985.8 kJ) and had higher percentages of energy contributed by fat and alcohol, especially after 8 pm. Moderate-CH eaters consumed the lowest amount of total energy (7341.8 kJ) while they tended to have their meals later in the day. High-CH eaters consumed most of their carbohydrates and energy earlier in the day and within the time slots of 6-9 am, 12-2 pm and 5-8 pm, which correspond to traditional mealtimes. The high-CH eaters profile had the highest daily intake of CH and fiber and the lowest intake of protein and fat. Low-CH eaters had greater odds than high-CH eaters of having T2D in self-reported but not in previously undiagnosed diabetics. Further research using prospective longitudinal studies is warranted to ascertain the direction of causality in the association of CH patterns with type 2 diabetes.

Indexed as

Feeding BehaviorMealsAdultBiomarkersBlood GlucoseCross-Sectional StudiesDiabetes Mellitus, Type 2Dietary CarbohydratesEnergy IntakeFemaleGlycated HemoglobinHumansMaleMiddle AgedNutritional StatusNutrition SurveysBiomarkersBlood GlucoseDietary CarbohydratesGlycated Hemoglobinhemoglobin A1c protein, humanchrononutritiondiurnal patterns of eatingmultilevel latent class analysisNDNS RPnutritional epidemiology

Identifiers

PMID31618988
PMCPMC6835827

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.