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Over the last decades, ovarian cancer mortality in Europe has been decreasing, but disparities in trends were observed. In this paper, we analysed ovarian cancer mortality trends in Europe over the period 1990–2020 and predicted the number of deaths and rates by 2025. We extracted population and death certification data from ovarian cancer in women for 31 European countries, between 1990 and 2020 from the World Health Organization database. We computed age-standardised mortality rates (ASMR) per 100,000 women-years, based on the world standard population. We also obtained predictions for 2025 using a joinpoint regression model and calculated the number of avoided deaths over the period 1994–2025. Over the observed period, mortality from ovarian cancer showed a favourable pattern in most countries. In the EU-27, rates declined by 5.9% from 2010–2014 to 2015–2019, reaching an ASMR of 4.66/100,000. During the same period, the decline in ovarian cancer mortality was more pronounced in the EU-14 countries (−7.0%) compared to Transitional countries (−2.1%). Declines were also observed in the United Kingdom, to reach an ASMR of 5.29. Decreases in mortality from ovarian cancer are predicted until 2025, to 4.17/100,000 for the EU-27. Favourable trends in ovarian cancer mortality are expected to persist in Europe and can be mainly attributed to the increased use of oral contraceptives in subsequent generations of European women. Decreased use of menopausal Hormone Replacement Therapy and improved diagnosis and management may also have played a role. • Ovarian cancer mortality decreased over the last decade in most European countries. • Favourable trends will continue in the next 5 years. • Less favourable epidemiological situation was observed in Transitional countries. • The largest decrease of mortality in 2025 is predicted to be in Germany. • Until 2025 nearly 131,000 deaths from ovarian cancer would be avoided in EU. [ABSTRACT FROM AUTHOR]

Socioeconomic inequalities in childhood Body Mass Index (BMI) are becoming increasingly more pronounced across the world. Although countries differ in the direction and strength of these inequalities, cross-national comparative research on this topic is rare. This paper draws on harmonized longitudinal cohort data from four wealthy countries—Germany, the Netherlands, the United Kingdom (UK), and the United States (US)—to 1) map cross-country differences in the magnitude of socioeconomic inequalities in childhood BMI, and 2) to examine cross-country differences in the role of three energy-balance-related behaviors—physical activity, screen time, and breakfast consumption—in explaining these inequalities. Children were aged 5–7 at our first timepoint and were followed up at age 8–11. We used data from the German National Educational Panel Study, the Dutch Generation R study, the UK Millennium Cohort Study and the US Early Childhood Longitudinal-Kindergarten Study. All countries revealed significant inequalities in childhood BMI. The US stood out in having the largest inequalities. Overall, inequalities between children with low versus medium educated parents were smaller than those between children with high versus medium educated parents. The role of energy-balance-related behaviors in explaining inequalities in BMI was surprisingly consistent. Across countries, physical activity did not, while screen time and breakfast consumption did play a role. The only exception was that breakfast consumption did not play a role in the US. Cross-country differences emerged in the relative contribution of each behavior in explaining inequalities in BMI: Breakfast consumption was most important in the UK, screen time explained most in Germany and the US, and breakfast consumption and screen time were equally important in the Netherlands. Our findings suggest that what constitutes the most effective policy intervention differs across countries and that these should target both children from medium as well as low educated families. • All countries showed substantial socioeconomic inequalities in childhood BMI. • In all countries, inequalities in BMI steepen over course of primary school. • Protective factors among the most advantaged seem to mainly drive inequalities. • Across most countries, underlying mechanisms for inequalities in BMI are similar. • The relative contribution of each mechanism to BMI inequalities differs per country. [ABSTRACT FROM AUTHOR]