Predicting Fertility Intentions Among Young Adults Using Machine Learning: The Relative Importance of Family Expectations, Housing Insecurity, Gender Ideology, Career Uncertainty, Relationship Quality, and Cultural Values
Keywords:
fertility intentions, machine learning, relationship quality, housing insecurity, gender ideology, career uncertainty, cultural values, GermanyAbstract
Objective: This study aimed to predict positive fertility intentions among young adults in Germany and determine the relative importance of family expectations, housing insecurity, gender ideology, career uncertainty, relationship quality, and cultural values.
Methods and Materials: A cross-sectional predictive study was conducted with 1,284 adults aged 18–35 years residing in Germany. Participants completed measures of fertility intentions, family expectations, housing insecurity, gender ideology, career uncertainty, relationship quality, and cultural values. The dataset was divided into an 80% training set and a 20% independent test set. Logistic regression, elastic-net regression, random forest, extreme gradient boosting, support vector machine, and multilayer perceptron models were developed using nested stratified cross-validation. Model performance was evaluated through the area under the receiver operating characteristic curve, precision–recall area, balanced accuracy, sensitivity, specificity, F1 score, and Brier score. Predictor importance was assessed using permutation importance and Shapley additive explanation values.
Findings: Extreme gradient boosting produced the strongest predictive performance, with an area under the receiver operating characteristic curve of .846, precision–recall area of .799, balanced accuracy of .784, sensitivity of .764, specificity of .803, F1 score of .753, and Brier score of .159. Its discrimination was significantly greater than that of standard logistic regression and elastic-net regression. Relationship quality was the most influential predictor domain, accounting for 24.8% of total SHAP importance, followed by housing insecurity at 21.6%, cultural values at 18.9%, career uncertainty at 15.7%, family expectations at 11.6%, and gender ideology at 7.4%. Severe housing and career uncertainty reduced the probability of positive fertility intentions, whereas high relationship quality and family-centered cultural values increased it. Family expectations showed a nonlinear pattern, and gender ideology was more influential when combined with supportive relationships and expectations of shared caregiving.
Conclusion: Fertility intentions among young adults in Germany are best predicted through an integrated assessment of relational, residential, cultural, and occupational conditions, with relationship quality and housing security representing the most influential domains.
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