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Record W2052443822 · doi:10.1097/psy.0b013e3181647e30

Early Socioeconomic Status is Associated With Adult Nighttime Blood Pressure Dipping

2008· article· en· W2052443822 on OpenAlexaff
Tavis S. Campbell, Brenda L. Key, Alana Ireland, Simon Bacon, Blaine Ditto

Bibliographic record

VenuePsychosomatic Medicine · 2008
Typearticle
Languageen
FieldNeuroscience
TopicStress Responses and Cortisol
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsSocioeconomic statusMedicineBlood pressureBody mass indexAmbulatory blood pressureDemographyStepwise regressionAnalysis of varianceDiastoleAmbulatoryInternal medicineEnvironmental healthPopulation

Abstract

fetched live from OpenAlex

OBJECTIVE: To examine the prognostic significance of early socioeconomic status (SES) on 24-hour blood pressure (BP) during early adulthood. Low SES has been related to poor health outcomes, in particular, cardiovascular morbidity and mortality. Recent cross-sectional research has also linked low levels of SES with several cardiovascular risk factors including poor nighttime BP dipping. METHODS: A total of 174 undergraduate university students whose childhood SES was assessed by highest level of education completed by their parents underwent 24-hour ambulatory BP monitoring. RESULTS: Initial correlation analyses revealed positive associations between childhood SES and BP dipping, indicating that lower levels of childhood SES were associated with less systolic BP (SBP) (r = .29, p < .01) and diastolic BP (DBP) dipping (r = .38, p < .01). A stepwise multiple regression analyses indicated that childhood SES explained 6.9% of the variance in SBP dipping and 11.5% of the variance in DBP dipping above and beyond other lifestyle-related factors including daytime BP, body mass index, alcohol use, smoking, and current SES. CONCLUSIONS: These findings suggest that irrespective of adult achievement, childhood SES may have lasting health implications.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.156
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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)0.0010.000

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 head0.023
GPT teacher head0.263
Teacher spread0.240 · 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.

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

Citations20
Published2008
Admission routes1
Has abstractyes

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