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Record W1506781337 · doi:10.1002/ajhb.22547

Age at death and linear enamel hypoplasias: Testing the effects of childhood stress and adult socioeconomic circumstances in premature mortality

2014· article· en· W1506781337 on OpenAlexaff
Alexandra Amoroso, Susana García, Hugo F.V. Cardoso

Bibliographic record

VenueAmerican Journal of Human Biology · 2014
Typearticle
Languageen
FieldMedicine
TopicBone and Dental Protein Studies
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsSocioeconomic statusDemographyStressorConfoundingLogistic regressionMedicineOdds ratioLife expectancyYoung adultGerontologyPopulationEnvironmental healthInternal medicineClinical psychology

Abstract

fetched live from OpenAlex

OBJECTIVE: The aim of this study was to test the association between linear enamel hypolasias and adult socioeconomic circumstances with age at death in a modern skeletal sample of known age. Specifically, this study wishes to test whether there is a relationship between early life stressors, environmental quality in adult life and premature mortality. METHODS: The presence/absence of LEH and the number of LEH episodes were recorded in 113 adult males from the Lisbon identified skeletal collection. The association between LEH and age was quantified using linear regression and binary logistic regression models, calculating crude and adjusted linear regression coefficients and odds ratios. The models were adjusted for year of birth, socioeconomic and migration status, and cause of death. RESULTS: The presence and number of LEH were related to premature mortality. Individuals expressing at least one enamel defect survived 9.0 years less or were 2.5 times more likely to die before 53 years of age compared to individuals with no LEH. However, when controlling for the confounding factors considered, the association between LEH and age became nonsignificant. CONCLUSIONS: The results indicate that although early life stressors, identified as LEH, seem strongly associated with premature mortality, adulthood socioeconomic circumstances accounts for most of the decreased longevity. This suggests that either macroscopically identified LEH in the permanent canine do not measure stressors early in life, or that a cumulative adversity model is a more adequate explanation.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.010
Threshold uncertainty score0.260

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.012
GPT teacher head0.276
Teacher spread0.263 · 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 teacher head, 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

Citations82
Published2014
Admission routes1
Has abstractyes

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