Evidence map›Paper›PMID 40645422›Full record

ArticleAnnals of epidemiology2025

Comparison of two measurement error-correction approaches for assessing the association between choline intake and coronary heart disease prevalence among US community-dwelling adults.

Cuiqiong Huo, Yuanyuan Luan, Roger S Zoh, Nana Gletsu-Miller, Stephen J Carter, Georgia Frey, Hsien-Chang Lin, Aurelian Bidulescu, See Ling Loy, Marwah Abdalla and 1 more

Abstract readComparative Study
In one paragraph

Article in Annals of epidemiology, 2025. 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
–field-weighted citation impact
1 · What the graph read from it

What it found

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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.

  1. Review
4 · The record

Corrections and comments

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5 · Who and what money

Authors and funding

11 authors.

Cuiqiong HuoDepartment of Epidemiology and Biostatistics, Indiana University School of Public Health-Bloomington, 1025 E 7th St, Bloomington, IN 47405, United States. Electronic address: cuiqhuo@iu.edu.
Yuanyuan LuanDepartment of Epidemiology and Biostatistics, Indiana University School of Public Health-Bloomington, 1025 E 7th St, Bloomington, IN 47405, United States. Electronic address: luany@iu.edu.
Roger S ZohDepartment of Epidemiology and Biostatistics, Indiana University School of Public Health-Bloomington, 1025 E 7th St, Bloomington, IN 47405, United States. Electronic address: rszoh@iu.edu.
Nana Gletsu-MillerDepartment of Applied Health Science, Indiana University School of Public Health-Bloomington, 1025 E 7th St, Bloomington, IN 47405, United States. Electronic address: ngletsum@iu.edu.
Stephen J CarterDepartment of Kinesiology, Indiana University School of Public Health-Bloomington, 1025 E 7th St, Bloomington, IN 47405, United States. Electronic address: stjcarte@iu.edu.
Georgia FreyDepartment of Kinesiology, Indiana University School of Public Health-Bloomington, 1025 E 7th St, Bloomington, IN 47405, United States. Electronic address: gfrey@iu.edu.
Hsien-Chang LinDepartment of Child and Family Development, College of Education, San Diego State University, 5500 Campanile Dr, San Diego, CA 92182, United States. Electronic address: hlin6@sdsu.edu.
Aurelian BidulescuDepartment of Epidemiology and Biostatistics, Indiana University School of Public Health-Bloomington, 1025 E 7th St, Bloomington, IN 47405, United States. Electronic address: abidules@iu.edu.
See Ling LoyDepartment of Reproductive Medicine, KK Women's and Children's Hospital, 100 Bukit Timah Rd, Singapore 229899, Singapore. Electronic address: loyseeling@duke-nus.edu.sg.
Marwah AbdallaDepartment of Medicine, Columbia University, 630 W 168th St, New York, NY 10032, United States. Electronic address: ma2947@cumc.columbia.edu.
Carmen D TekweDepartment of Epidemiology and Biostatistics, Indiana University School of Public Health-Bloomington, 1025 E 7th St, Bloomington, IN 47405, United States. Electronic address: ctekwe@iu.edu.

Funding

Automated clinic blood pressure assessment and detection of white coat and masked hypertension study in African AmericansR01HL146636 · NHLBI · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI ABDALLA, MARWAH · 2020 to 2025
$3.8M
Measurement error correction approaches to wearable device-based measures of physical activity and self-reported measures of dietary intake in obesity and type 2 diabetes researchR01DK132385 · NIDDK · TRUSTEES OF INDIANA UNIVERSITY · PI TEKWE, CARMEN D. · 2022 to 2025
$2.3M
Novel Bayesian assessments of device-based physical activity and self-reported dietary intake in joint models of all-cause mortality and type 2 diabetes in a cohort of biracial older US adultsR01DK136994 · NIDDK · TRUSTEES OF INDIANA UNIVERSITY · PI Roger Sai Zoh · 2024 to 2026
$1.8M
NHLBI NIH HHS R01 HL146636NIDDK NIH HHS R01 DK132385NIDDK NIH HHS R01 DK136994
6 · The paper itself

Abstract

purposeThis study compared two measurement error-correction approaches-linear mixed-effects approach to measurement error-correction (MEM) and simulation-extrapolation (SIMEX)-for assessing the association between choline intake and coronary heart disease (CHD) prevalence among United States (US) community-dwelling adults.

methodsSimulations were conducted to evaluate the performances of five estimation approaches: benchmark analysis, 1-day method, average method (AveMethod), MEM, and SIMEX. Data from the National Health and Nutrition Examination Survey (NHANES) were analyzed to determine the relationship between choline intake and CHD prevalence using these methods.

resultsBoth MEM and SIMEX effectively corrected for measurement error-induced biases; MEM generally outperformed SIMEX except when the standard deviation of true exposure (σ

conclusionsMEM and SIMEX mitigated most measurement error-related biases in the simulations, although MEM demonstrated better overall performance. After correction for measurement error, choline intake was not significantly associated with CHD prevalence.

Indexed as

CholineCoronary DiseaseAdultAgedBiasFemaleHumansMaleMiddle AgedNutrition SurveysPrevalenceUnited StatesCholinecholinecoronary heart diseasemeasurement errormixed-effects approach to measurement errorsimulation–extrapolation

Identifiers

PMID40645422
PMCPMC12810691

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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.