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Record W2994751512 · doi:10.1016/s2214-109x(19)30458-9

Association between interpregnancy interval and subsequent stillbirth in 58 low-income and middle-income countries: a retrospective analysis using Demographic and Health Surveys

2019· article· en· W2994751512 on OpenAlexafffundabout
Akshay Swaminathan, Deshayne B. Fell, Annette K. Regan, Mark Walker, Daniel J. Corsi

Bibliographic record

VenueThe Lancet Global Health · 2019
Typearticle
Languageen
FieldMedicine
TopicReproductive Health and Contraception
Canadian institutionsOttawa HospitalChildren's Hospital of Eastern OntarioUniversity of Ottawa
FundersCanadian Institutes of Health Research
KeywordsDemographySocioeconomic statusResidenceMedicineConfidence intervalPopulationParity (physics)Live birthFertilityPregnancyEnvironmental health

Abstract

fetched live from OpenAlex

BACKGROUND: About 3 million stillbirths occur each year, 98% of which are in low-income and middle-income countries (LMICs). Interpregnancy interval is a key risk factor of interest, because it is modifiable. We aimed to investigate whether there is a causal relationship between the length of interpregnancy interval and risk of subsequent stillbirth. METHODS: We used Demographic and Health Surveys (2002-18) from 58 LMICs to study reproductive histories of women and to identify livebirths and stillbirths in the preceding 5 years. Countries were selected on the basis of the availability of interpregnancy interval data and other covariates of interest (age, education, urban or rural residence, and wealth) in surveys done since 2002. Exclusion criteria were being nulliparous, having missing parity data, and not having had at least two births (livebirth or stillbirth) in the 5 years before the survey. We combined two analytic approaches: one that analyses intervals between all births and another that analyses intervals within mothers. We report stratified estimates for the first, second, and third intervals, controlling for all past birth outcomes and intervals in a 5-year period, and other socioeconomic covariates. We also explored effect heterogeneity across key cohort subgroups. FINDINGS: Between July, 1997, and April, 2018, we identified 716 478 births from 338 223 women in 123 Demographic and Health Surveys from 58 LMICs, of which 9647 were stillbirths. Intervals of less than 6 months were associated with an increased risk of stillbirth in the between-mother models when considering the first interval (risk difference [RD] 0·0096, 95% CI 0·008-0·011). This association was slightly attenuated when considering only the second interval (RD 0·0054, 95% CI 0·0010 to 0·0099) and substantially attenuated when considering only the third interval (0·0007, -0·037 to 0·039). Within-mother modelling showed a null association with intervals of 24-59 months when considering the first and second (RD 0·007, 95% CI -0·001 to 0·016) and first and third (0·040, -0·422 to 0·501) intervals. INTERPRETATION: Although interpregnancy intervals of less than 12 months were associated with increased risk of stillbirth, these effects were attenuated when considering second and third intervals, suggesting the association in the first interval might not be causal. Future studies should use generalisable cohorts with longitudinal data, and report estimates stratified by birth order. FUNDING: Canadian Institutes of Health Research.

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)0.003
metaresearch head score (Gemma)0.005
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.022
Threshold uncertainty score0.043

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.005
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.003
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0000.001
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 head0.031
GPT teacher head0.348
Teacher spread0.316 · 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
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

Citations37
Published2019
Admission routes3
Has abstractyes

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