Dataset Information

Reconstruction of Birth Histories for the Study of Fertility in the United States, 1830-1910.

ABSTRACT: This paper describes a method to reconstruct complete birth histories for women in the 1900 and 1910 U. S. census IPUMS samples. The method is an extension of an earlier method developed by Luther and Cho (1988). The basic method relies on the number of children ever born, number of children surviving, number of children coresident in the household and age-specific fertility rates for the population to probabilistically assign an "age" to deceased and unmatched children. Modifications include the addition of an iterative Poisson regression model to fine-tune age-specific fertility inputs. The potential of complete birth histories for the study of the U.S. fertility transition is illustrated with a few examples.

SUBMITTER: Hacker JD

PROVIDER: S-EPMC8631723 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

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Reconstruction of Birth Histories for the Study of Fertility in the United States, 1830-1910.

Hacker J David JD

Historical methods 20191009 1

This paper describes a method to reconstruct complete birth histories for women in the 1900 and 1910 U. S. census IPUMS samples. The method is an extension of an earlier method developed by Luther and Cho (1988). The basic method relies on the number of children ever born, number of children surviving, number of children coresident in the household and age-specific fertility rates for the population to probabilistically assign an "age" to deceased and unmatched children. Modifications include th ...[more]

PMID: 34853487

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Project description:BackgroundPreterm birth is serious public health worldwide, and early prediction of preterm birth in pregnant women may provide assistance for timely intervention and reduction of preterm birth. This study aimed to develop a preterm birth prediction model that is readily available and convenient for clinical application.MethodsData used in this case-control study were extracted from the National Vital Statistics System (NVSS) database between 2018 and 2019. Univariate and multivariate logistic regression analyses were utilized to find factors associated with preterm birth. Odds ratio (OR) and 95% confidence interval (CI) were used as effect measures. The area under the curve (AUC), accuracy, sensitivity, and specificity were utilized as model performance evaluation metrics.ResultsData from 3,006,989 pregnant women in 2019 and 3,039,922 pregnant women in 2018 were used for the model establishment and external validation, respectively. Of these 3,006,989 pregnant women, 324,700 (10.8%) had a preterm birth. Higher education level of pregnant women [bachelor (OR = 0.82; 95%CI, 0.81-0.84); master or above (OR = 0.82; 95%CI, 0.81-0.83)], pre-pregnancy overweight (OR = 0.96; 95%CI, 0.95-0.98) and obesity (OR = 0.94; 95%CI, 0.93-0.96), and prenatal care (OR = 0.48; 95%CI, 0.47-0.50) were associated with a reduced risk of preterm birth, while age ≥ 35 years (OR = 1.27; 95%CI, 1.26-1.29), black race (OR = 1.26; 95%CI, 1.23-1.29), pre-pregnancy underweight (OR = 1.26; 95%CI, 1.22-1.30), pregnancy smoking (OR = 1.27; 95%CI, 1.24-1.30), pre-pregnancy diabetes (OR = 2.08; 95%CI, 1.99-2.16), pre-pregnancy hypertension (OR = 2.22; 95%CI, 2.16-2.29), previous preterm birth (OR = 2.95; 95%CI, 2.88-3.01), and plurality (OR = 12.99; 95%CI, 12.73-13.24) were related to an increased risk of preterm birth. The AUC and accuracy of the prediction model in the testing set were 0.688 (95%CI, 0.686-0.689) and 0.762 (95%CI, 0.762-0.763), respectively. In addition, a nomogram based on information on pregnant women and their spouses was established to predict the risk of preterm birth in pregnant women.ConclusionsThe nomogram for predicting the risk of preterm birth in pregnant women had a good performance and the relevant predictors are readily available clinically, which may provide a simple tool for the prediction of preterm birth.

Dataset Information

Reconstruction of Birth Histories for the Study of Fertility in the United States, 1830-1910.

Publications

Reconstruction of Birth Histories for the Study of Fertility in the United States, 1830-1910.

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