Evidence map›Paper›PMID 38069621›Full record

ArticleAmerican journal of human biology : the official journal of the Human Biology Council2024

Harmonization of four biomarkers across nine nationally representative studies of older persons.

Peifeng Hu, Eileen M Crimmins, Jung Ki Kim, Alan Potter, Jake Cofferen, Sharon Merkin, Heather McCreath, Teresa Seeman

Open access · hybridAbstract read
In one paragraph

Article in American journal of human biology : the official journal of the Human Biology Council, 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
0.6field-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

1 citing paper in PubMed, 2 citations in OpenAlex.

  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

8 authors at 3 institutions in 1 country.

Peifeng HuDivision of Geriatrics, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, California, USA.
Eileen M CrimminsDavis School of Gerontology, University of Southern California, Los Angeles, California, USA.ORCID 0000-0001-5459-5239
Jung Ki KimDavis School of Gerontology, University of Southern California, Los Angeles, California, USA.ORCID 0000-0002-4842-0579
Alan PotterDepartment of Laboratory Medicine and Pathology, University of Washington School of Medicine, Seattle, WA, USA.
Jake CofferenDepartment of Laboratory Medicine and Pathology, University of Washington School of Medicine, Seattle, WA, USA.
Sharon MerkinDivision of Geriatrics, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, California, USA.
Heather McCreathDivision of Geriatrics, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, California, USA.
Teresa SeemanDivision of Geriatrics, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, California, USA.
University of California, Los Angeles · USUniversity of Southern California · USUniversity of Washington · US

Funding

HRS Yrs29-34: Y33 SSA CoFundingU01AG009740 · NIA · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI Jessica Faul, KENNETH M LANGA · 1990 to 2026
$555.8M
Project-001R01AG017644 · NIA · UNIVERSITY OF LONDON INST OF NEUROLOGY · PI Andrew Steptoe · 2000 to 2026
$56.2M
Leveraging a natural experiment to estimate the causal impact of blood sugar on dementia and cognition in IndiaR01AG051125 · NIA · UNIVERSITY OF SOUTHERN CALIFORNIA · PI Jinkook Lee · 2015 to 2026
$26.8M
USC/UCLA Center on Biodemography &Population HealthP30AG017265 · NIA · UNIVERSITY OF SOUTHERN CALIFORNIA · PI JENNIFER A AILSHIRE, HIRAM BELTRAN-SANCHEZ · 1999 to 2026
$17.9M
China Health and Retirement Longitudinal StudyR01AG037031 · NIA · PEKING UNIVERSITY · PI STRAUSS, JOHN A, WANG, YAFENG · 2010 to 2024
$15.1M
Modifiable Protective and Risk Factors of Late-Life Cognitive Health and DementiaRF1AG055273 · NIA · UNIVERSITY OF SOUTHERN CALIFORNIA · PI LANGA, KENNETH M, LEE, JINKOOK · 2017 to 2017
$4.0M
Dynamics of Family Well Being in Indonesia After 20 YearsR01HD050764 · NICHD · RAND CORPORATION · PI STRAUSS, JOHN A · 2006 to 2018
$3.5M
Twenty Years On The Fifth Indonesia Family Survey of AgingR01AG026676 · NIA · RAND CORPORATION · PI STRAUSS, JOHN A · 2006 to 2016
$3.3M
Biomarker Cross-Calibration to Investigate International Health InequalitiesR01AG049020 · NIA · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI CRIMMINS, EILEEN M, SEEMAN, TERESA E · 2015 to 2019
$2.6M
NIA NIH HHS P30 AG017265NIA NIH HHS R01 AG017644NIA NIH HHS R01 AG026676NIA NIH HHS R01 AG037031NIA NIH HHS R01 AG049020NIA NIH HHS R01 AG051125NIA NIH HHS RF1 AG055273NIA NIH HHS U01 AG009740NICHD NIH HHS R01 HD050764Wellcome Trust
6 · The paper itself

Abstract

introductionA growing number of international population surveys have included measurement of biomarkers, but differ in the type of specimens collected, sample processing procedures, shipment protocols, and laboratory assay platforms. The purpose of this study is to harmonize biomarker data from nine nationally representative studies of people 50 years of age and over by adjusting for assay platforms and type of specimens for total cholesterol (total-C), high-density lipoprotein cholesterol (HDL-C), glycosylated hemoglobin (HbA1c), and C-reactive protein (CRP).

methodsSets of 24 identical serum, plasma, whole blood, and dried blood spot harmonization samples with known analyte levels were generated at a reference laboratory, shipped at -80°C to the respective study laboratories, and subsequently assayed following the study laboratory's protocol. Both original and harmonized study data were used to calculate mean values and at-risk prevalence.

resultsThe correlation coefficients between the biomarker values of the harmonization samples obtained by the study laboratories and the reference laboratory were 0.99 or above for all analytes and laboratories, indicating the high quality of assays at all laboratories. However, using the harmonized data from each study, there were significant differences in the mean values and country ranking of the prevalence of at-risk levels of these four biomarkers.

conclusionsWhile the biomarker data from the different study laboratories were highly correlated, indicating very high correlation of rank order of specimens, absolute values did vary significantly. This can have a major impact on assessment of international differences in estimates of risks for chronic morbidity and mortality.

Indexed as

BiomarkersC-Reactive ProteinGlycated HemoglobinAgedAged, 80 and overCholesterolCholesterol, HDLFemaleHumansMaleMiddle AgedBiomarkersCholesterolCholesterol, HDLC-Reactive ProteinGlycated Hemoglobin

Identifiers

PMID38069621
PMCPMC11062831
OpenAlexW4389507120

What OpenQuestion holds

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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.