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Record W2893315559 · doi:10.1093/hropen/hoy015

Changing seasonal variation in births by sociodemographic factors: a population-based register study

2018· article· en· W2893315559 on OpenAlexaboutno aff
Johan Dahlberg

Bibliographic record

VenueHuman Reproduction Open · 2018
Typearticle
Languageen
FieldMedicine
TopicMaternal and Perinatal Health Interventions
Canadian institutionsnot available
FundersVetenskapsrådet
KeywordsDemographySeasonalityBirth rateParity (physics)FertilityChildbirthPopulationQuarter (Canadian coin)Variation (astronomy)Season of birthGeographyMultinomial logistic regressionPregnancyBiologyStatisticsEcology

Abstract

fetched live from OpenAlex

STUDY QUESTION: Have seasonal variations in births by factors related to maternal education, age, parity and re-partnering changed over a 72-year period? SUMMARY ANSWER: Seasonal variation in births has been reduced overall but also changed its pattern over the last seven decades. WHAT IS KNOWN ALREADY: The number of births varies markedly by season, but the causes of this variation are not fully understood. Seasonality of births is, in some populations, strongly influenced by sociodemographic factors. STUDY DESIGN SIZE DURATION: A longitudinal study design was used by analysing the seasonal variation in live births between 1940 and 2012, and relating it to mothers' sociodemographic characteristics at the time of childbirth (maternal education, age, parity and re-partnering). PARTICIPANTS/MATERIALS SETTING METHODS: Register data on 6 768 810 live births in Sweden between 1940 and 2012 were used. Information on biological parents are available for more than 95% of all births. Multinomial logistic regressions were used to calculate predicted probabilities of giving birth for each calendar month. MAIN RESULTS AND THE ROLE OF CHANCE: Between 1940 and 1999, Swedish birth rates showed the typical seasonal variation with high numbers of births during the spring, and low numbers of births during the last quarter of the year. However, during the 21st century, the seasonal variation in fertility declined so that only minor variation in birth rates between February and September now remains. Still, the pattern of low birth rates at the end of the year remains and has even become more pronounced from the 1980s onwards. The characteristic 'Christmas effect' that used to be visible in September has vanished over the last 30 years. The roles in seasonal variation of maternal education, the mother's age, parity and instances where the mother has re-partnered between subsequent births changed during the second half of the 20th century. From 1980s onwards, the decline in birth rates during the last quarter of the year became particularly pronounced among highly educated mothers. Over the 72 years studied, the seasonal variation among first-time mothers declined steadily and has almost disappeared at the end of the study period. Using data that cover ~180 000 births in each month, all meaningful results are statistically significant. LIMITATIONS REASONS FOR CAUTION: The study uses data from one Nordic country only, making it difficult to draw conclusions that may hold for other countries. WIDER IMPLICATIONS OF THE FINDINGS: The typical seasonal variation reported for Sweden between 1940 and 1999, with high numbers of births during the spring and low numbers of births during the last quarter of the year, is in line with results from most other European countries during the same time period. However, the significant decline in seasonal variation in the early 21st century is a novel development. The study underlines that in a society with low fertility and efficient birth control, active choices and behaviours associated with an individual's sociodemographic characteristics tend to matter more for the seasonal timing of childbearing than environmental factors related to the physiological ability to reproduce and cultural-behavioural factors related to the frequency of intercourse. STUDY FUNDING/COMPETING INTERESTS: The study was funded by the Swedish Research Council (Vetenskapsrådet) via the Swedish Initiative for Research on Microdata in the Social and Medical Sciences (SIMSAM): Stockholm University SIMSAM Node for Demographic Research (grant registration number 340-2013-5164). The authors declare no conflicts of interest. TRIAL REGISTRATION NUMBER: Not applicable.

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)0.002
metaresearch head score (Gemma)0.006
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 score0.020
Threshold uncertainty score0.039

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.006
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.004
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.078
GPT teacher head0.396
Teacher spread0.317 · 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

Citations39
Published2018
Admission routes1
Has abstractyes

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