Evidence map›Paper›PMID 32542849›Full record

ArticleBiometrical journal. Biometrische Zeitschrift2020

Impact of adolescent obesity on middle-age health of women given data MAR.

Yongyun Shin, Shumei Sun, Dipankar Bandyopadhyay

Abstract read
In one paragraph

Article in Biometrical journal. Biometrische Zeitschrift, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

3 authors.

Yongyun ShinDepartment of Biostatistics, Virginia Commonwealth University, Richmond, VA, USA.ORCID 0000-0003-0654-2620
Shumei SunDepartment of Biostatistics, Virginia Commonwealth University, Richmond, VA, USA.
Dipankar BandyopadhyayDepartment of Biostatistics, Virginia Commonwealth University, Richmond, VA, USA.

Funding

Research Supplement to Promote Diversity in Health Related ResearchUL1TR002649 · NCATS · VIRGINIA COMMONWEALTH UNIVERSITY · PI MOELLER, FREDERICK GERARD · 2018 to 2022
$19.1M
Juvenile Protective Factors and Their Effects on AgingR01AG048801 · NIA · VIRGINIA COMMONWEALTH UNIVERSITY · PI SUN, SHUMEI S · 2016 to 2019
$1.5M
Institute of Education Sciences R305D130033NCATS NIH HHS UL1 TR002649NIA NIH HHS R01 AG048801NIH HHS UL1TR002649VCU Presidential Research Quest Fund
6 · The paper itself

Abstract

We analyze adolescent BMI and middle-age systolic blood pressure (SBP) repeatedly measured on women enrolled in the Fels Longitudinal Study (FLS) between 1929 and 2010 to address three questions: Do adolescent-specific growth rates in body mass index (BMI) and menarche affect middle-age SBP? Do they moderate the aging effect on middle-age SBP? Have the effects changed over historical time? To address the questions, we propose analyzing a growth curve model (GCM) that controls for age, birth-year cohort, and historical time. However, several complications in the data make the GCM analysis nonstandard. First, the person-specific adolescent BMI and middle-age SBP trajectories are unobservable. Second, missing data are substantial on BMI, SBP, and menarche. Finally, modeling the latent trajectories for BMI and SBP, repeatedly measured on two distinct sets of unbalanced time points, are computationally intensive. We adopt a bivariate GCM for BMI and SBP with correlated random coefficients. To efficiently handle missing values of BMI, SBP, and menarche assumed missing at random, we estimate their joint distribution by maximum likelihood via the EM algorithm where the correlated random coefficients and menarche are multivariate normal. The estimated distribution will be transformed to the desired GCM for SBP that includes the random coefficients of BMI and menarche as covariates. We demonstrate unbiased estimation by simulation. We find that adolescent growth rates in BMI and menarche are positively associated with, and moderate, the aging effect on SBP in middle age, controlling for age, cohort, and historical time, but the effect sizes are at most modest. The aging effect is significant on SBP, controlling for cohort and historical time, but not vice versa.

Indexed as

AgingHealth StatusPediatric ObesityAdolescentBlood PressureBody Mass IndexFemaleHumansLongitudinal StudiesMenarcheMiddle Agedgrowth curve modelhierarchical modellongitudinal datamaximum likelihoodmixed model

Identifiers

PMID32542849
PMCPMC7641917

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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.