Parents’ age and total fertility rate in selected high-income countries from Europe and North America, 1990–2020
Bibliographic record
Abstract
OBJECTIVE: To provide a comprehensive picture of trends in parents' age and total fertility rate in selected most populous high-income countries from Europe and North America. STUDY DESIGN: Data were retrieved from official statistics published by the United Nations, the World Bank, the European Union (EU), and by national health statistics offices. RESULTS: Mean maternal age at birth showed increasing trends in all considered countries; in 2020, the highest mean age was observed in Italy (32.2) and Spain (32.3), and the lowest one in the USA (28.8). Mean maternal age at first birth also showed upward trends. In the 1990s, mean age at first birth ranged from 25.5 to 26.9 years, except for the USA where it was below 25 years. The countries with the highest average maternal age at first birth were Italy and Spain, reaching 31 years over the most recent years. Data on mean paternal age at birth were scant. In Germany (2019) it was 34.6 and in the USA (2014) 27.9 years. In Italy, mean paternal age increased from 34.2 in 2000 to 35.5 in 2018, in the UK from 30.7 in 1990 to 33.4 in 2017, and in Canada, a decrease was observed from 29.1 in 2006 to 28.3 in 2011. Finally, Sweden and the USA had the highest fertility rates, around two children in some years, while Italy and Spain had the lowest ones, with less than 1.5 children over the whole period. CONCLUSIONS: Monitoring of trends in reproductive factors is crucial to gain insight into society from a cultural and sociological point of view and to analyze the impact of these changes on reproductive health and related conditions.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".