Evidence map›Paper›PMID 31275083›Full record

ReviewContrast media & molecular imaging2019

Assessment of Body Composition in Health and Disease Using Bioelectrical Impedance Analysis (BIA) and Dual Energy X-Ray Absorptiometry (DXA): A Critical Overview.

Maurizio Marra, Rosa Sammarco, Antonino De Lorenzo, Ferdinando Iellamo, Mario Siervo, Angelo Pietrobelli, Lorenzo Maria Donini, Lidia Santarpia, Mauro Cataldi, Fabrizio Pasanisi and 1 more

Open access · hybridAbstract readReview
In one paragraph

Review in Contrast media & molecular imaging, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 228 papers, 5 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
228citing papers in PubMed, 5 pooled it
18.9field-weighted citation impact, top 1% 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

228 citing papers in PubMed, 5 syntheses or guidelines pooled it, 362 citations in OpenAlex.

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  17. Indexing for body surface area when assessing kidney function.Nephrology, dialysis, transplantation : official publication of the European Dialysis and Transplant Association - European Renal Association · 2026
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168 more citing papers are in PubMed but not listed here.

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

11 authors at 6 institutions in 2 countries.

Maurizio MarraDepartment of Clinical Medicine and Surgery, University Federico II, Naples, Italy.
Rosa SammarcoDepartment of Clinical Medicine and Surgery, University Federico II, Naples, Italy.
Antonino De LorenzoDepartment of Biomedicine and Prevention, Division of Clinical Nutrition and Nutrigenomic, University of Rome "Tor Vergata", Italy.ORCID 0000-0001-6524-4493
Ferdinando IellamoDepartment of Clinical Science and Translational Medicine and School of Sports Medicine, University Tor Vergata, Rome, Italy.
Mario SiervoHuman Nutrition Research Centre, Institute of Cellular Medicine and Newcastle University Institute for Ageing, Newcastle University, Biomedical Research Building, Campus for Ageing and Vitality, Newcastle on Tyne, UK.
Angelo PietrobelliPediatric Unit, Verona University Medical School, Verona, Italy.
Lorenzo Maria DoniniSapienza University of Rome, Experimental Medicine Department, Medical Pathophysiology, Food Science and Endocrinology Section, Food Science and Human Nutrition Research Unit, Rome, Italy.ORCID 0000-0003-4692-4754
Lidia SantarpiaDepartment of Clinical Medicine and Surgery, University Federico II, Naples, Italy.
Mauro CataldiDivision of Pharmacology, Department of Neuroscience, Reproductive and Odontostomatologic Sciences, Federico II University of Naples, Naples, Italy.
Fabrizio PasanisiDepartment of Clinical Medicine and Surgery, University Federico II, Naples, Italy.
Franco ContaldoDepartment of Clinical Medicine and Surgery, University Federico II, Naples, Italy.
Federico II University Hospital · ITUniversity of Rome Tor Vergata · ITNewcastle University · GBSapienza University of Rome · ITUniversity of Naples Federico II · ITUniversity of Verona · IT

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The measurement of body composition (BC) represents a valuable tool to assess nutritional status in health and disease. The most used methods to evaluate BC in the clinical practice are based on bicompartment models and measure, directly or indirectly, fat mass (FM) and fat-free mass (FFM). Bioelectrical impedance analysis (BIA) and dual energy X-ray absorptiometry (DXA) (nowadays considered as the reference technique in clinical practice) are extensively used in epidemiological (mainly BIA) and clinical (mainly DXA) settings to evaluate BC. DXA is primarily used for the measurements of bone mineral content (BMC) and density to assess bone health and diagnose osteoporosis in defined anatomical regions (femur and spine). However, total body DXA scans are used to derive a three-compartment BC model, including BMC, FM, and FFM. Both these methods feature some limitations: the accuracy of BIA measurements is reduced when specific predictive equations and standardized measurement protocols are not utilized whereas the limitations of DXA are the safety of repeated measurements (no more than two body scans per year are currently advised), cost, and technical expertise. This review aims to provide useful insights mostly into the use of BC methods in prevention and clinical practice (ambulatory or bedridden patients). We believe that it will stimulate a discussion on the topic and reinvigorate the crucial role of BC evaluation in diagnostic and clinical investigation protocols.

Indexed as

Electric ImpedanceAbsorptiometry, PhotonAdipose TissueBody CompositionBone DensityHumansNutritional StatusOsteoporosis

Identifiers

PMID31275083
PMCPMC6560329
OpenAlexW2947625911

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.