ArticleMaternal and child health journal2026
Comparing Approaches to Measuring Prospective Fertility Desires in the United States: A Population-based Study.
Article in Maternal and child health journal, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
objectivesFertility desires are central to reproductive health, yet researchers lack consensus on how to best measure them. We compared participants' responses to three individual questions - Timing ("How do you feel about having a child now or sometime in the future?"), Importance ("How important is it to you to avoid becoming pregnant now?"), and Wantedness ("Do you want to become pregnant in the next year?") - to responses to the 14-item Desire to Avoid Pregnancy (DAP) scale, a psychometrically valid measure of pregnancy preferences.
methodsWe analyzed data from the Surveys of Women, population-based longitudinal studies of reproductive-aged females in nine US states. We used multinomial logistic regression to generate predicted responses to each individual question by DAP score, and logistic regression to estimate annual incident pregnancy for each approach.
resultsWhile responses to individual fertility desire questions aligned with DAP scores, the approaches yielded substantially different categorizations. The lowest and highest categories of Timing, Importance, and Wantedness largely captured individuals with low and high DAP scores, respectively. However, the highest categories also included large proportions of individuals with a moderate preference to avoid pregnancy (Timing: 45% of those with mid-range DAP scores, Importance: 43%, Wantedness: 70%). Similarly, the non-polar categories of the individual fertility desire questions included individuals across wide ranges of DAP scores. CONCLUSIONS FOR PRACTICE: Asking about wanting pregnancy can identify those most open to pregnancy but does not differentiate fertility preferences among individuals not explicitly desiring pregnancy, which is most people. While single questions are efficient, lack of measurement precision or evidence that they accurately categorize respondents is a compelling drawback to their use.
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