The association of early IQ and education with mortality: 65 year longitudinal study in Malmö, Sweden

Objectives To establish whether differences in early IQ explain why people with longer education live longer, or whether differences in father’s or own educational attainment explain why people with higher early IQ live longer

Food abundance in men before puberty predicts a range of cancers in grandsons

Nutritional conditions early in human life may influence phenotypic characteristics in later generations. A male-line transgenerational pathway, triggered by the early environment, has been postulated with support from animal and a small number of human studies. Here we analyse individuals born in Uppsala Sweden 1915–29 with linked data from their children and parents, which enables us to explore the hypothesis that pre-pubertal food abundance may trigger a transgenerational effect on cancer events. We used cancer registry and cause-of-death data to analyse 3422 cancer events in grandchildren (G2) by grandparental (G0) food access. We show that variation in harvests and food access in G0 predicts cancer occurrence in G2 in a specific way: abundance among paternal grandfathers, but not any other grandparent, predicts cancer occurrence in grandsons but not in granddaughters. This male-line response is observed for several groups of cancers, suggesting a general susceptibility, possibly acquired in early embryonic development. We observed no transgenerational influence in the middle generation

Machine Learning of Public Sentiments toward Wind Energy in Norway

Across Europe negative public opinion has and may continue to limit the deployment of renewable energy infrastructure required for the transition to net-zero energy systems. Understanding public sentiment and its spatio-temporal variations is as such important for decision-making and socially accepted energy systems. In this study, we apply a sentiment classification model based on a machine learning framework for natural language processing, NorBERT, on data collected from Twitter between 2006 and 2022 to analyse the case of wind power opposition in Norway. From the 68828 tweets with geospatial information, we show how discussions about wind power intensified in 2018/2019 together with a trend of more negative tweets up until 2020, both on a regional level and for Norway as a whole. Furthermore, we find weak geographical clustering in our data, indicating that discussions are country wide and not dominated by specific regional events or developments. Twitter data allows for detailed insight into the temporal nature of public sentiments and extending this research to additional case studies of technologies, countries and sources of data (e.g. newspapers, other social media) may prove important to complement traditional survey research and the understanding of public sentiment.Comment: 31 pages, 36 figures, 2 table

Approaches to sample size calculation for clinical trials in rare diseases

We discuss 3 alternative approaches to sample size calculation: traditional sample size calculation based on power to show a statistically significant effect, sample size calculation based on assurance, and sample size based on a decision-theoretic approach. These approaches are compared head-to-head for clinical trial situations in rare diseases. Specifically, we consider 3 case studies of rare diseases (Lyell disease, adult-onset Still disease, and cystic fibrosis) with the aim to plan the sample size for an upcoming clinical trial. We outline in detail the reasonable choice of parameters for these approaches for each of the 3 case studies and calculate sample sizes. We stress that the influence of the input parameters needs to be investigated in all approaches and recommend investigating different sample size approaches before deciding finally on the trial size. Highly influencing for the sample size are choice of treatment effect parameter in all approaches and the parameter for the additional cost of the new treatment in the decision-theoretic approach. These should therefore be discussed extensively

Childhood IQ and marriage by mid-life: the Scottish Mental Survey 1932 and the Midspan Studies

The study examined the influence of IQ at age 11 years on marital status by mid-adulthood. The combined databases of the Scottish Mental Survey 1932 and the Midspan studies provided data from 883 subjects. With regard to IQ at age 11, there was an interaction between sex and marital status by mid-adulthood (p = 0.0001). Women who had ever-married achieved mean lower childhood IQ scores than women who had never-married (p < 0.001). Conversely, there was a trend for men who had ever-married to achieve higher childhood IQ scores than men who had never-married (p = 0.07). In men, the odds ratio of ever marrying was 1.35 (95% CI 0.98–1.86&#59; p = 0.07) for each standard deviation increase in childhood IQ. Among women, the odds ratio of ever marrying by mid-life was 0.42 (95% CI 0.27–0.64; p = 0.0001) for each standard deviation increase in childhood IQ. Mid-life social class had a similar association with marriage, with women in more professional jobs and men in more manual jobs being less likely to have ever-married by mid-life. Adjustment for the effects of mid-life social class and height on the association between childhood IQ and later marriage, and vice versa, attenuated the effects somewhat, but suggested that IQ, height and social class acted partly independently

Why do those out of work because of sickness or disability have a high mortality risk? Evidence from a Scottish cohort

<b>Background:</b> Existing evidence on the association between being out of work because of sickness or disability and high mortality risk suggests that most of the association cannot be explained by controlling for health, health behaviour or socio-economic position. However, studies are often based on administrative data that lack explanatory factors. Here, we investigate this high mortality risk using detailed information from a cohort study.<p></p> <b>Methods:</b> Data from the West of Scotland Twenty-07 prospective cohort study were used to follow those (average age 56 years) employed, unemployed and out of work in 1988 to death or end of follow-up in 2011. Using a parametric survival model, mean survival was calculated for each employment group after adjustment for health behaviours, health and socio-economic position.<p></p> <b>Results:</b> The difference in survival between those sick or disabled (30% survival at end of follow-up), and those unemployed (49%) or employed (61%) was mostly accounted for by adjusting for the higher levels of poor heath at baseline in the former group (49, 46 and 56%, respectively, after adjustment). After controlling for all variables, the difference between those sick or disabled (51%) and those employed (56%) was further attenuated slightly.<p></p> <b>Conclusion:</b> Our results suggest that the present health of those out of work and sick or disabled should be taken seriously, as their long-term survival prospects are considerably poorer than other employment groups.<p></p&gt

Why do those out of work because of sickness or disability have a high mortality risk? Evidence from a Scottish cohort

<b>Background:</b> Existing evidence on the association between being out of work because of sickness or disability and high mortality risk suggests that most of the association cannot be explained by controlling for health, health behaviour or socio-economic position. However, studies are often based on administrative data that lack explanatory factors. Here, we investigate this high mortality risk using detailed information from a cohort study.<p></p> <b>Methods:</b> Data from the West of Scotland Twenty-07 prospective cohort study were used to follow those (average age 56 years) employed, unemployed and out of work in 1988 to death or end of follow-up in 2011. Using a parametric survival model, mean survival was calculated for each employment group after adjustment for health behaviours, health and socio-economic position.<p></p> <b>Results:</b> The difference in survival between those sick or disabled (30% survival at end of follow-up), and those unemployed (49%) or employed (61%) was mostly accounted for by adjusting for the higher levels of poor heath at baseline in the former group (49, 46 and 56%, respectively, after adjustment). After controlling for all variables, the difference between those sick or disabled (51%) and those employed (56%) was further attenuated slightly.<p></p> <b>Conclusion:</b> Our results suggest that the present health of those out of work and sick or disabled should be taken seriously, as their long-term survival prospects are considerably poorer than other employment groups.<p></p&gt

Using relative and absolute measures for monitoring health inequalities: experiences from cross-national analyses on maternal and child health

Background. As reducing socio-economic inequalities in health is an important public health objective, monitoring of these inequalities is an important public health task. The specific inequality measure used can influence the conclusions drawn, and there is no consensus on which measure is most meaningful. The key issue raising most debate is whether to use relative or absolute inequality measures. Our paper aims to inform this debate and develop recommendations for monitoring health inequalities on the basis of empirical analyses for a broad range of developing countries. Methods. Wealth-group specific data on under-5 mortality, immunisation coverage, antenatal and delivery care for 43 countries were obtained from the Demographic and Health Surveys. These data were used to describe the association between the overall level of these outcomes on the one hand, and relative and absolute poor-rich inequalities in these outcomes on the other. Results. We demonstrate that the values that the absolute and relative inequality measures can take are bound by mathematical ceilings. Yet, even where these ceilings do not play a role, the magnitude of inequality is correlated with the overall level of the outcome. The observed tendencies are, however, not necessities. There are countries with low mortality levels and low relative inequalities. Also absolute inequalities showed variation at most overall levels. Conclusion. Our study shows that both absolute and relative inequality measures can be meaningful for monitoring inequalities, provided that the overall level of the outcome is taken into account. Suggestions are given on how to do this. In addition, our paper presents data that can be used for benchmarking of inequalities in the field of maternal and child health in low and middle-income countries

Detecting spatio-temporal mortality clusters of European countries by sex and ag

[EN] Background: Mortality decreased in European Union (EU) countries during the last century. Despite these similar trends, there are still considerable differences in the levels of mortality between Eastern and Western European countries. Sub-group analysis of mortality in Europe for different age and sex groups is common, however to our knowledge a spatio-temporal methodology as in this study has not been applied to detect significant spatial dependence and interaction with time. Thus, the objective of this paper is to quantify the dynamics of mortality in Europe and detect significant clusters of mortality between European countries, applying spatio-temporal methodology. In addition, the joint evolution between the mortality of European countries and their neighbours over time was studied. Methods: The spatio-temporal methodology used in this study takes into account two factors: time and the geographical location of countries and, consequently, the neighbourhood relationships between them. This methodology was applied to 26 European countries for the period 1990-2012. Results: Principally, for people older than 64 years two significant clusters were obtained: one of high mortality formed by Eastern European countries and the other of low mortality composed of Western countries. In contrast, for ages below or equal to 64 years only the significant cluster of high mortality formed by Eastern European countries was observed. In addition, the joint evolution between the 26 European countries and their neighbours during the period 1990-2012 was confirmed. For this reason, it can be said that mortality in EU not only depends on differences in the health systems, which are a subject to national discretion, but also on supra-national developments. Conclusions: This paper proposes statistical tools which provide a clear framework for the successful implementation of development public policies to help the UE meet the challenge of rethinking its social model (Social Security and health care) and make it sustainable in the medium term.The authors are grateful for the financial support provided by the Ministry of Economy and Competitiveness, project MTM2013-45381-P. Adina Iftimi gratefully acknowledges financial support from the MECyD (Ministerio de Educacion, Cultura y Deporte, Spain) Grant FPU12/04531. Francisco Montes is grateful for the financial support provided by the Spanish Ministry of Economy and Competitiveness, project MTM2016-78917-R. The research by Patricia Carracedo and Ana Debon has been supported by a grant from the Mapfre Foundation.Carracedo-Garnateo, P.; Debón Aucejo, AM.; Iftimi, A.; Montes-Suay, F. (2018). Detecting spatio-temporal mortality clusters of European countries by sex and ag. 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Contribution of main causes of death to social inequalities in mortality in the whole population of Scania, Sweden

BACKGROUND: To more efficiently reduce social inequalities in mortality, it is important to establish which causes of death contribute the most to socioeconomic mortality differentials. Few studies have investigated which diseases contribute to existing socioeconomic mortality differences in specific age groups and none were in samples of the whole population, where selection bias is minimized. The aim of the present study was to determine which causes of death contribute the most to social inequalities in mortality in each age group in the whole population of Scania, Sweden. METHODS: Data from LOMAS (Longitudinal Multilevel Analysis in Skåne) were used to estimate 12-year follow-up mortality rates across levels of socioeconomic position (SEP) and workforce participation in 975,938 men and women aged 0 to 80 years, during 1991–2002. RESULTS: The results generally showed increasing absolute mortality differences between those holding manual and non-manual occupations with increasing age, while there were inverted u-shaped associations when using relative inequality measures. Cardiovascular diseases (CVD) contributed to 52% of the male socioeconomic difference in overall mortality, cancer to 18%, external causes to 4% and psychiatric disorders to 3%. The corresponding contributions in women were 55%, 21%, 2% and 3%. Additionally, those outside the workforce (i.e., students, housewives, disability pensioners, and the unemployed) showed a strongly increased risk of future mortality in all age groups compared to those inside the workforce. Even though coronary heart disease (CHD) played a major contributing role to the mortality differences seen, stroke and other types of cardiovascular diseases also made substantial contributions. Furthermore, while the most common types of cancers made substantial contributions to the socioeconomic mortality differences, in some age groups more than half of the differences in cancer mortality could be attributed to rarer cancers. CONCLUSION: CHD made a major contribution to the socioeconomic differences in overall mortality. However, there were also important contributions from diseases with less well understood mechanistic links with SEP such as stroke and less-common cancers. Thus, an increased understanding of the mechanisms connecting SEP with more rare causes of disease might be important to be able to more successfully intervene on socioeconomic differences in health