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Record W1980834901 · doi:10.1007/s12160-013-9496-4

Childhood Socioeconomic Position and Blood Pressure Dipping in Early Adulthood: a Longitudinal Study

2013· article· en· W1980834901 on OpenAlexafffund
Tavis S. Campbell, Jean R. Séguin, Frank Vitaro, Richard E. Tremblay, Blaine Ditto

Bibliographic record

VenueAnnals of Behavioral Medicine · 2013
Typearticle
Languageen
FieldMedicine
TopicHeart Rate Variability and Autonomic Control
Canadian institutionsMcGill UniversityCentre Hospitalier Universitaire Sainte-JustineUniversité de MontréalUniversity of Calgary
FundersCanadian Institutes of Health ResearchSocial Sciences and Humanities Research Council of CanadaHeart and Stroke Foundation of Canada
KeywordsSocioeconomic statusMedicineBlood pressureBody mass indexHeart rateLongitudinal studyDemographyHealth psychologyPediatricsInternal medicinePublic healthEnvironmental healthPopulation

Abstract

fetched live from OpenAlex

BACKGROUND: The experience of low socioeconomic position in childhood may increase risk for adult cardiovascular disease above and beyond the effects of current socioeconomic position. One limitation of most previous research is that childhood socioeconomic position was assessed retrospectively. METHODS: Measures of ambulatory blood pressure, heart rate, and heart rate variability were obtained from 110 young men (22 years) who were enrolled in a long-term study of child development at age 6. RESULTS: Men who had lower childhood socioeconomic position had smaller decreases in systolic blood pressure (SBP) during sleep independent of current education, daytime SBP, and body mass index (BMI). They also displayed smaller decreases in low-frequency heart rate variability during sleep. Twenty-four-hour SBP was negatively associated with childhood socioeconomic position independent of current education and BMI. CONCLUSIONS: While the mechanisms are unclear, childhood socioeconomic position may influence blood pressure in early adulthood independent of current life circumstances.

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)0.001
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 score0.028
Threshold uncertainty score0.700

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
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 head0.048
GPT teacher head0.340
Teacher spread0.292 · 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

Citations9
Published2013
Admission routes2
Has abstractyes

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