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Record W4288491561 · doi:10.3390/women2030020

Early Marriage in Adolescence and Risk of High Blood Pressure and High Blood Glucose in Adulthood: Evidence from India

2022· article· en· W4288491561 on OpenAlexfundno aff
Biplab Datta, Ashwini Tiwari

Bibliographic record

VenueWomen · 2022
Typearticle
Languageen
FieldMedicine
TopicBirth, Development, and Health
Canadian institutionsnot available
FundersInstitute of Population and Public Health
KeywordsBlood pressureMedicineDemographyYoung adultLife course approachOddsEarly adulthoodGerontologyPsychologyDevelopmental psychologyLogistic regressionEndocrinologyInternal medicine

Abstract

fetched live from OpenAlex

Adolescence, the transition phase to adulthood, is a critical period for physical and psychological development. Disruptions during this period, such as getting married, could result in various adverse short- and long-term health outcomes. This study aimed to assess the differential risk of two common chronic conditions—high blood pressure and high blood glucose—in adult women (20–49 years) who were married during different stages of adolescence (10–19 years) compared to women who were married in their youth (20–24 years). Using the most recent nationally representative data from India, we separately assessed the odds in favor of having the two chronic conditions for women who were married during early (10–14 years), middle (15–17 years), and late (18–19 years) adolescence. We found that an earlier age at marriage during adolescence was associated with a higher risk of chronic conditions later in life. Women who were married during early adolescence were respectively 1.29 and 1.23 times more likely (p < 0.001) to have high blood pressure and high blood glucose compared to women who were married in their youth. These findings highlight the importance of preventing underage marriage among adolescent females to address the risk of downstream chronic health consequences as adults.

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 score0.030
Threshold uncertainty score0.892

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 integrity0.0000.001
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 head0.009
GPT teacher head0.234
Teacher spread0.225 · 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

Citations10
Published2022
Admission routes1
Has abstractyes

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