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    Male-female fertility differentials across 17 high-income countries: insights from a new data resource
    (European Journal of Population, 2021-01-20) Dudel, Christian; Klüsener, Sebastian
    Obtaining cross-country comparative perspectives on male fertility has long been difficult, as male fertility is usually less well registered than female fertility. Recent methodological advancements in imputing missing paternal ages at childbirth enable us to provide a new database on male fertility. This new resource covers more than 330 million live births and is based on a consistent and well-tested set of methods. These methods allow us to handle missing information on the paternal age, which is missing for roughly 10% of births. The data resource is made available in the Human Fertility Collection and allows for the first time a comparative perspective on male fertility in high-income countries using high-quality birth register data. We analyze trends in male–female fertility quantum and tempo differentials across 17 high-income countries, dating as back as far as the late 1960s for some countries, and with data available for the majority of countries from the 1980s onward. Using descriptive and counterfactual analysis methods, we find substantial variation both across countries and over time. Related to the quantum we demonstrate that disparities between male and female period fertility rates are driven to a large degree by the interplay of parental age and cohort size differences. For parental age differences at childbirth, we observe a development toward smaller disparities, except in Eastern Europe. This observation fits with expectations based on gender theories. However, variation across countries also seems to be driven by factors other than gender equality.
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    Estimation of genetic parameters for female fertility traits in the Polish Holstein-Friesian population
    (Animals, 2022-06-08) Otwinowska-Mindur, Agnieszka; Ptak, Ewa; Jagusiak, Wojciech; Zarnecki, Andrzej
    The objective of this study was to estimate genetic parameters for the analyzed fertility traits of Polish Holstein-Friesian primiparous and multiparous cows, as a step toward the incorporation of new traits into routine genetic evaluation. Lactation records of 116,836 Polish Holstein-Friesian cows were studied. The records cover the first three lactations of all cows. The cows, daughters of 2884 sires, were calved from 2006 to 2020. The conception rate for heifers (CRh) and for cows in the second (CR2) and third parity (CR3), the interval from first calving to first insemination (CTFI), the days open (DO), and the interval from first to successful insemination for heifers (FSh) and for cows in second (FS2) and third (FS3) parity were analyzed. The BLUPf90 package and a Bayesian method via Gibbs sampling were used to estimate (co)variance components. In general, all heritabilities were low and ranged from 0.013 (CTFI) to 0.038 (FS2). The heritability of conception rate and interval from first to successful insemination was slightly lower for heifers than for cows. Genetic correlations were moderate to high with two exceptions: correlation of CTFI with CRh (0.033) and with FSh (−0.051). The results indicate that a few analyzed traits could be used in genetic evaluation of Polish Holstein-Friesian cows. It is suggested to complement the selection index with traits for both heifers and cows, such as the interval from first to successful insemination (i.e., FSh, FS2 and FS3), in order to enable effective improvement of female fertility scores in the Polish Holstein-Friesian population.
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    Association between body mass index and female infertility in the United States: data from national health and nutrition examination survey 2013–2018
    (International Journal of General Medicine, 2022-02-19) Zhu, Lei; Zhou, Bin; Zhu, Xi; Cheng, Feng; Pan, Ying; Zhou, Yi; Wu, Yong; Xu, Qingna
    Purpose: This study aimed to investigate the effects of body mass index (BMI) on infertility in women of childbearing age. Patients and Methods: We performed a cross-sectional study using data from 3624 participants from the National Health and Nutrition Examination Survey (NHANES). We used BMI and fertility status in the survey as independent and dependent variables, respectively. We evaluated their relationship and used smoothed curve fitting and multivariate logistic regression analysis as well as a generalized additive model (GAM) to determine the effect of BMI. Results: Logistic regression model analysis linked BMI and infertility after adjusting for potential confounders OR 1.03, 95%Cl: 1.02–1.05). There was a non-linear relationship between BMI and infertility, with each unit increase in BMI reducing the risk of infertility by 33% when BMI was <19.5 kg/m2. In contrast, when BMI ≥19.5 kg/m2, each unit increase in BMI predicted a 3% increase in the risk of infertility. Conclusion: The relationship between infertility and BMI presented a U-shaped curve. Therefore, a BMI that lay at the extremes of the spectrum tended to predict infertility. We believe that this study will support the maintenance of suitable BMI levels in women preparing for pregnancy.