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Record W4404754589 · doi:10.2196/59545

Vientiane Multigenerational Birth Cohort Project in Lao People’s Democratic Republic: Protocol for Establishing a Longitudinal Multigenerational Birth Cohort to Promote Population Health

2024· article· en· W4404754589 on OpenAlexvenueno aff
Jordyn T. Wallenborn, Miley Sinantha-Hu, Vattahanaphone Ouipoulikoune, Sengchanh Kounnavong, Latsamy Siengsounthone, Nicole Probst‐Hensch, Peter Odermatt, Somphou Sayasone, Günther Fink

Bibliographic record

VenueJMIR Research Protocols · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicHealth disparities and outcomes
Canadian institutionsnot available
FundersSchweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung
KeywordsPopulationMedicineGrandparentCohortContext (archaeology)Public healthDemographyEnvironmental healthGerontologyGeographyPsychology

Abstract

fetched live from OpenAlex

BACKGROUND: Rapid global population growth and urbanization have led to an increase in urban populations in low- and middle-income countries. Although these urban areas have generally better health outcomes than lower-income rural areas, many environmental, social, and health challenges remain. Vientiane, the capital of Lao People's Democratic Republic (Lao PDR), has approximately 1.5 of the 7.5 million Laotian population (2022) and provides a unique opportunity to examine health outcomes among socioeconomically diverse populations in the rapidly urbanizing context of the country. OBJECTIVE: The aim of the Vientiane multigenerational birth cohort (VITERBI) project is to (1) establish a multigenerational birth cohort in Vientiane capital, Lao PDR, which is representative of the local population, (2) serve as the basis for additional observational (ie, cross-sectional) and intervention studies that promote population health in Vientiane province, and (3) investigate the social, epidemiological, and medical problems of public health importance to Lao PDR. METHODS: VITERBI is a prospective multigenerational birth cohort. The study population is structured around children born between July 1, 2022, and June 30, 2023, who reside in Chanthabuly, Sikhottabong, Sangthong, or Mayparkngum districts of Vientiane. Whenever possible, children and their mothers are enrolled during pregnancy; nonreported pregnancies are enrolled after birth. The cohort plans to enroll 3000 pregnant women and their children and the infants' fathers, grandparents, and great-grandparents for a total study population of approximately 13,000 individuals. Participants will be followed throughout the life course with a range of data collected, including demographics, behavior, diet, physical activity, physiology, neurodevelopment, health history, quality of life, environmental exposures, depression, anxiety, stress, resilience, household characteristics, obstetric history, birth outcomes, and various living and dementia scales for older adults. Biomarkers collected include height, weight, blood pressure, and hemoglobin levels. Currently, no statistical analyses are planned. RESULTS: As of April 2024, this study has enrolled 3500 pregnant women and 4579 family members. Study participation is ongoing until May 2025 at minimum, with the goal to extend follow-up until 2050. CONCLUSIONS: The study cohort will be used as a basis for further observational (cross-sectional, longitudinal) and intervention studies. It also serves as a tool to investigate social, epidemiological, and medical problems of public health importance to Lao PDR, which will contribute to broader understanding of regional and international contexts. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/59545.

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)0.021
metaresearch head score (Gemma)0.019
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: none
GenreCandidate signal: Protocol · Consensus signal: Protocol
Teacher disagreement score0.037
Threshold uncertainty score0.122

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0210.019
Meta-epidemiology (narrow)0.0020.002
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.002
Science and technology studies0.0040.001
Scholarly communication0.0020.002
Open science0.0030.002
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0370.007

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 head0.258
GPT teacher head0.589
Teacher spread0.331 · 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
GenreProtocol

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

Citations4
Published2024
Admission routes1
Has abstractyes

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