Evidence map›Paper›PMID 35745274›Full record

ArticleNutrients2022

Comparison of Quality of Carbohydrate Metrics Related to Fasting Insulin, Glycosylated Hemoglobin and HOMA-IR in Brazilian Adolescents.

Camilla Medeiros Macedo da Rocha, Vanessa Proêza Maciel Gama, Amanda de Moura Souza, Edna Massae Yokoo, Eliseu Verly Junior, Katia Vergetti Bloch, Rosely Sichieri

Open access · goldAbstract readComparative Study
In one paragraph

Article in Nutrients, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.4field-weighted citation impact, top 36% of its field
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

2 citing papers in PubMed, 3 citations in OpenAlex.

  1. Article
  2. 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 at 3 institutions in 1 country.

Camilla Medeiros Macedo da RochaInstituto de Alimentação e Nutrição, Centro Mutidisciplinar UFRJ-Macaé, Universidade Federal do Rio de Janeiro, Av. Aluizio da Silva Gomes 50, Novo Cavaleiros, Macaé 27930-560, RJ, Brazil.ORCID 0000-0003-1720-3560
Vanessa Proêza Maciel GamaInstituto Federal de Educação, Ciência e Tecnologia Fluminense, Av. Souza Mota 350, Parque Fundão, Campos dos Goytacazes 28060-010, RJ, Brazil.ORCID 0000-0001-9261-4250
Amanda de Moura SouzaInstituto de Estudos em Saúde Coletiva, Universidade Federal do Rio de Janeiro, Avenida Horácio Macedo s/n, Ilha do Fundão, Rio de Janeiro 21941-598, RJ, Brazil.
Edna Massae YokooDepartamento de Epidemiologia e Bioestatística, Universidade Federal Fluminense, Rua Marques de Paraná 303, 3º Andar, Centro, Niterói 24030-210, RJ, Brazil.ORCID 0000-0002-3513-2084
Eliseu Verly JuniorInstituto de Medicina Social, Universidade do Estado do Rio de Janeiro, Rua São Francisco Xavier 524, Pavilhão João Lyra Filho, 7º Andar, Rio de Janeiro 20550-900, RJ, Brazil.ORCID 0000-0002-1101-8746
Katia Vergetti BlochInstituto de Estudos em Saúde Coletiva, Universidade Federal do Rio de Janeiro, Avenida Horácio Macedo s/n, Ilha do Fundão, Rio de Janeiro 21941-598, RJ, Brazil.
Rosely SichieriInstituto de Medicina Social, Universidade do Estado do Rio de Janeiro, Rua São Francisco Xavier 524, Pavilhão João Lyra Filho, 7º Andar, Rio de Janeiro 20550-900, RJ, Brazil.
Universidade Federal do Rio de Janeiro · BRUniversidade do Estado do Rio de Janeiro · BRUniversidade Federal Fluminense · BR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Low glycemic index (GI) and glycemic load (GL) diets are effective for glycemic control (GC) associated with a carbohydrate-controlled meal plan. However, whether GI and GL peaks are related to GC is unknown. Objective: To compare the daily GI (DGI)/GL (DGL) and average GI (AvGI)/GL (AvGL) of meals (accounting for peaks) related to GC markers (GCM) in Brazilian adolescents. Methods: A representative national school-based (public/private) sample of students without diabetes, 12−17 years of age, was evaluated. Food intake was based on a 24 h recall. The models for complex cluster sampling were adjusted (sex, sexual maturation, age, and physical activity). Results: Of 35,737 students, 74% were from public schools, 60% girls, 17% overweight, and 8% obese. The minimum DGI and DGL were observed at lunch, with higher values at night. Fasting insulin was 1.5 times higher in overweight/obese (OW) girls, and 1.7 times higher in OW boys than in normal-weight (NW) girls. The same trend was observed for the homeostatic model assessment for insulin resistance (HOMA-IR) (OW = 2.82 vs. NW = 1.84 in girls; OW = 2.66 vs. NW = 1.54 in boys; p < 0.05). The daily and average metrics were greater for NW adolescents. Glycosylated hemoglobin was not associated with these metrics, except for AvGL. Insulin and HOMA-IR were associated with all metrics in NW adolescents, with greater coefficients associated with AvGL. Among overweight/obese adolescents, only GI metrics were associated (β = 0.23; AvGI and insulin) and appeared to have the best association with GCM. Conclusions: Among NW adolescents, GL is a better measure of carbohydrate quality, but for those with overweight/obesity, carbohydrate consumption is more associated with GC, probably because they eat/report small amounts of carbohydrates.

Indexed as

Insulin ResistanceAdolescentBlood GlucoseBrazilChildDietary CarbohydratesFastingFemaleGlycated HemoglobinGlycemic IndexHumansInsulinMaleObesityOverweightBlood GlucoseDietary CarbohydratesGlycated HemoglobinInsulinadolescentsglycemic controlglycemic indexglycemic loadintake

Identifiers

PMID35745274
PMCPMC9227805
OpenAlexW4283119110

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.