Annual and state-level data on U.S. total fertility rates, 1931–present

IF 1.4 Q3 MULTIDISCIPLINARY SCIENCES Data in Brief Pub Date : 2025-04-01 Epub Date: 2025-02-11 DOI:10.1016/j.dib.2025.111386
Gregori Galofré-Vilà, María Gómez-León
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Abstract

This data paper presents a comprehensive reconstruction of U.S. fertility trends, offering state-level Total Fertility Rates (TFR) from 1931 to the present on an annual basis. The dataset computes TFR based on the tabulations of birth counts by maternal age category, sourced from the “Vital Statistics of the United States” published by the U.S. Department of Health and Human Services. Additionally, historical TFR are provided by race, with separate categories for white and non-white populations. TFR were further calculated using the number of women aged 14-49, derived from U.S. census data. This is the first time that TFR is being displayed at the state-year level and captures significant variations in fertility trends across states, during the rapid increase in fertility rates in the 1940s and 1950s, subsequent declines in the mid-1960s, and more recent fluctuations influenced by socio-economic factors, policies, and cultural shifts. By providing detailed, state-level data variation, this new resource offers valuable insights for public health researchers, policymakers, and demographers studying the determinants of fertility trends and their implications for social and economic planning.
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美国总生育率的年度和州一级数据,1931年至今
这篇数据论文展示了美国生育趋势的全面重建,提供了从1931年到现在每年的州一级总生育率(TFR)。该数据集根据来自美国卫生与公众服务部出版的《美国人口动态统计》的按产妇年龄分类的出生计数表计算总生育率。此外,历史总生育率是由种族提供的,分为白人和非白人人群。根据美国人口普查数据,研究人员进一步计算了14-49岁女性的总生育率。这是第一次在州-年水平上显示总生育率,并捕捉了在20世纪40年代和50年代生育率快速增长期间各州生育率趋势的显著变化,随后在60年代中期下降,以及最近受社会经济因素、政策和文化转变影响的波动。通过提供详细的国家级数据变化,这一新资源为研究生育率趋势决定因素及其对社会和经济规划的影响的公共卫生研究人员、政策制定者和人口统计学家提供了宝贵的见解。
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来源期刊
Data in Brief
Data in Brief MULTIDISCIPLINARY SCIENCES-
CiteScore
3.10
自引率
0.00%
发文量
996
审稿时长
70 days
期刊介绍: Data in Brief provides a way for researchers to easily share and reuse each other''s datasets by publishing data articles that: -Thoroughly describe your data, facilitating reproducibility. -Make your data, which is often buried in supplementary material, easier to find. -Increase traffic towards associated research articles and data, leading to more citations. -Open up doors for new collaborations. Because you never know what data will be useful to someone else, Data in Brief welcomes submissions that describe data from all research areas.
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