Evidence map›Paper›PMID 34629252›Full record

ArticleNutrition, metabolism, and cardiovascular diseases : NMCD2021

Longitudinal association between adiposity measures and regression of prediabetes/diabetes.

Ashwinkumar Modi, Rajendra Gadhavi, Cynthia M Pérez, Kaumudi Joshipura

Open access · greenAbstract read
In one paragraph

Article in Nutrition, metabolism, and cardiovascular diseases : NMCD, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed, 1 pooled it
0.9field-weighted citation impact, top 25% 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

4 citing papers in PubMed, 1 synthesis or guideline pooled it, 9 citations in OpenAlex.

  1. Pooled it
  2. Article
  3. Article
  4. 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

4 authors at 3 institutions in 3 countries.

Ashwinkumar ModiCenter for Clinical Research and Health Promotion, University of Puerto Rico, Medical Sciences Campus, San Juan, Puerto Rico, USA.
Rajendra GadhaviB. J. Medical College, Gujarat, India.
Cynthia M PérezGraduate School of Public Health, University of Puerto Rico, Medical Sciences Campus, San Juan, Puerto Rico, USA.
Kaumudi JoshipuraCenter for Clinical Research and Health Promotion, University of Puerto Rico, Medical Sciences Campus, San Juan, Puerto Rico, USA; Department of Epidemiology, Harvard T. H. Chan School of Public Health, Boston, MA, USA. Electronic address: kaumudi.joshipura@upr.edu.
University of Puerto Rico, Medical Sciences Campus · PRB.J. Medical College · INHarvard University · US

Funding

TECHNOLOGIES AND RESOURCES FOR CORE LABORATORIESU54MD007587 · NIMHD · UNIVERSITY OF PUERTO RICO MED SCIENCES · PI LUCIANO, CARLOS A., WOJNA, VALERIE · 2012 to 2018
$23.2M
Tracking and Evaluation CoreU54GM133807 · NIGMS · UNIVERSITY OF PUERTO RICO MED SCIENCES · PI LUCIANO, CARLOS A., MOROU-BERMUDEZ, EVANGELIA · 2020 to 2024
$17.7M
Periodontitis and pre-clinical diabetesR01DE020111 · NIDCR · UNIVERSITY OF PUERTO RICO MED SCIENCES · PI JOSHIPURA, KAUMUDI J, PEREZ, CYNTHIA MADELINE · 2010 to 2015
$3.1M
NIDCR NIH HHS R01 DE020111NIGMS NIH HHS U54 GM133807NIMHD NIH HHS U54 MD007587
6 · The paper itself

Abstract

BACKGROUND AND

aimsThe recent COVID-19 pandemic has further increased the importance of reducing obesity and prediabetes/diabetes. We aimed to evaluate the association between adiposity and regression of prediabetes/diabetes. METHODS AND

resultsThe San Juan Overweight Adults Longitudinal Study (SOALS) included 1351 individuals with overweight/obesity, aged 40-65, free of major cardiovascular diseases and physician diagnosed diabetes. From the 1012 participants with baseline prediabetes/diabetes, 598 who completed the follow-up were included. Over the follow-up, 25% regressed from prediabetes to normoglycemia or from diabetes to prediabetes or normoglycemia. Poisson regression with robust standard error was used to estimate the relative risk (RR) adjusting for major confounders. Higher neck circumference (NC) was associated with regression of prediabetes/diabetes (RR = 0.45 comparing extreme tertiles; 95% CI:0.30-0.66); RR was 0.49 (95% CI:0.34-0.73) for waist circumference (WC) and 0.64 (95% CI:0.44-0.92) for BMI. Significant associations were found using median cut-offs or continuous measures for weight and BMI. Greater reduction in BMI (comparing extreme tertiles) was significantly associated with regression of prediabetes/diabetes (RR = 1.44; 95% CI:1.02-2.02). Continuous measures of change in adiposity (except for NC) were also associated with regression of prediabetes/diabetes for BMI and weight. Participants who reduced BMI (>5%) increased prediabetes/diabetes regression (RR = 1.61; 95% CI:1.15-2.25) compared to those who did not; similarly for weight (RR = 1.55; 95% CI: 1.10-2.19). Additional analysis for body fat percentage showing slightly weaker results than BMI/weight further supported our findings.

conclusionLower baseline adiposity and higher reduction in adiposity were associated with regression of prediabetes/diabetes among individuals with overweight/obesity.

Indexed as

AdiposityAdultAgedBody Mass IndexCOVID-19Diabetes Mellitus, Type 2FemaleHumansLongitudinal StudiesMaleMiddle AgedObesityOverweightPoisson DistributionPrediabetic StateRisk FactorsBody mass indexDiabetesNeck circumferenceObesityPre-diabetesRegressionWaist circumferenceWeight loss

Identifiers

PMID34629252
PMCPMC8650404
OpenAlexW3193041195

What OpenQuestion holds

Textmetadata
LicenceTDM
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.