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Record W2308465823 · doi:10.1017/thg.2016.11

Twin's Birth-Order Differences in Height and Body Mass Index From Birth to Old Age: A Pooled Study of 26 Twin Cohorts Participating in the CODATwins Project

2016· article· en· W2308465823 on OpenAlexafffund
Yoshie Yokoyama, Aline Jelenkovic, Reijo Sund, Joohon Sung, John L. Hopper, Syuichi Ooki, Kauko Heikkilä, Sari Aaltonen, Ádám Domonkos Tárnoki, Dávid László Tárnoki, Gonneke Willemsen, Meike Bartels, Kimberly J. Saudino, Tessa L. Cutler, Tracy L. Nelson, Keith E. Whitfield, Jane Wardle, Clare Llewellyn, Abigail Fisher, Mingguang He, Xiaohu Ding, Morten Bjerregaard-Andersen, Henning Beck‐Nielsen, Morten Sodemann, Yun‐Mi Song, Sarah Yang, Kayoung Lee, Hoe-Uk Jeong, Ariel Knafo‐Noam, David Mankuta, Lior Abramson, S. Alexandra Burt, Kelly L. Klump, Juan R. Ordoñana, Juan F. Sánchez-Romera, Lucía Colodro‐Conde, Jennifer R. Harris, Ingunn Brandt, Thomas Sevenius Nilsen, Jeffrey M. Craig, Richard Saffery, Fuling Ji, Feng Ning, Zengchang Pang, Lise Dubois, Michel Boivin, Mara Brendgen, Ginette Dionne, Frank Vitaro, Nicholas G. Martin, Sarah E. Medland, Grant W. Montgomery, Patrik K. E. Magnusson, Nancy L. Pedersen, Anna K. Dahl Aslan, Per Tynelius, Claire M. A. Haworth, Robert Plomin, Esther Rebato, Richard J. Rose, Jack Goldberg, Finn Rasmussen, Yoon-Mi Hur, Thorkild I. A. Sørensen, Dorret I. Boomsma, Jaakko Kaprio, Karri Silventoinen

Bibliographic record

VenueTwin Research and Human Genetics · 2016
Typearticle
Languageen
FieldMedicine
TopicBirth, Development, and Health
Canadian institutionsUniversité du Québec à MontréalUniversité de MontréalOttawa Public HealthUniversité LavalUniversity of Ottawa
FundersFP7 HealthEunice Kennedy Shriver National Institute of Child Health and Human DevelopmentNational Institute on AgingBiotechnology and Biological Sciences Research CouncilCanadian Institutes of Health ResearchMedical Research CouncilNational Institutes of HealthDirectorate for Biological SciencesJapan Society for the Promotion of ScienceCancer Research UKNational Health and Medical Research CouncilNational Institute of Mental HealthState Government of VictoriaNational Research Foundation of KoreaNational Institute on Alcohol Abuse and AlcoholismNational Research FoundationMinisterio de Ciencia e Innovación
KeywordsZygosityBirth orderBirth weightBody mass indexDemographyMedicineMass indexPregnancyPopulationBiologyEndocrinology

Abstract

fetched live from OpenAlex

We analyzed birth order differences in means and variances of height and body mass index (BMI) in monozygotic (MZ) and dizygotic (DZ) twins from infancy to old age. The data were derived from the international CODATwins database. The total number of height and BMI measures from 0.5 to 79.5 years of age was 397,466. As expected, first-born twins had greater birth weight than second-born twins. With respect to height, first-born twins were slightly taller than second-born twins in childhood. After adjusting the results for birth weight, the birth order differences decreased and were no longer statistically significant. First-born twins had greater BMI than the second-born twins over childhood and adolescence. After adjusting the results for birth weight, birth order was still associated with BMI until 12 years of age. No interaction effect between birth order and zygosity was found. Only limited evidence was found that birth order influenced variances of height or BMI. The results were similar among boys and girls and also in MZ and DZ twins. Overall, the differences in height and BMI between first- and second-born twins were modest even in early childhood, while adjustment for birth weight reduced the birth order differences but did not remove them for BMI.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.007
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.016
Threshold uncertainty score0.032

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.007
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.129
GPT teacher head0.406
Teacher spread0.277 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations21
Published2016
Admission routes2
Has abstractyes

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