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In causal inference, parametric models are usually employed to address causal questions estimating the effect of interest. However, parametric models rely on the correct model specification assumption that, if not met, leads to biased effect estimates. Correct model specification is challenging, especially in high-dimensional settings. Incorporating Machine Learning (ML) into causal analyses may reduce the bias arising from model misspecification, since ML methods do not require the specification of a functional form of the relationship between variables. However, when ML predictions are directly plugged in a predefined formula of the effect of interest, there is the risk of introducing a "plug-in bias" in the effect measure. To overcome this problem and to achieve useful asymptotic properties, new estimators that combine the predictive potential of ML and the ability of traditional statistical methods to make inference about population parameters have been proposed. For epidemiologists interested in taking advantage of ML for causal inference investigations, we provide an overview of three estimators that represent the current state-of-art, namely Targeted Maximum Likelihood Estimation (TMLE), Augmented Inverse Probability Weighting (AIPW) and Double/Debiased Machine Learning (DML)., Competing Interests: Declarations Ethics approval Not applicable. Competing interests The authors have no relevant financial or non-financial interests to disclose., (© 2024. The Author(s).)

We examine the causal effect of early retirement on medication use using Danish registry data. A reform in early retirement schemes in 2006 gradually increased eligibility ages from 60 to 64 differentially across birth cohorts. This enables an instrumental variable design that was applied using novel g-estimation methods that alleviate bias in binary outcome IV models. Our data allow studying patterns in the short run (ages 59½-60½) and in the long run (ages 57-63). For those who were eligible already at age 60, retirement did not change overall medication use. However, when investigating medication and population subgroups, we see that painkiller use decreases and hypertension medication as well as mental health medication use increase after retirement in almost all population subgroups. Moreover, males as well as the blue-collar occupation subgroups do show decreases in overall medication use after early retirement. In conclusion, our analyses reveal that retirement can have important heterogeneous health effects across population groups and are potentially informative about the welfare benefits of social insurance more broadly., (© 2024. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

Introduction: Overweight and obesity constitute a major concern among patients treated at forensic psychiatric departments. The present clinical feasibility study aimed at investigating the extent to which glucagon-like peptide 1 receptor agonist (GLP-1RA) treatment with once-daily liraglutide 3.0 mg could be a feasible pharmacological treatment of these conditions in patients with schizophrenia spectrum disorders hospitalised in forensic psychiatry., Methods: The 26-week, open-label feasibility study included participants aged 18-65 years diagnosed with a severe mental illness and hospitalised at a forensic psychiatric department. At the time of inclusion, all participants fulfilled the indication for using liraglutide as a treatment for overweight and obesity. Participants' baseline examinations were followed by a 26-week treatment period with liraglutide injection once daily according to a fixed uptitration schedule of liraglutide, with a target dose of 3.0 mg. Each participant attended seven visits to evaluate the efficacy and adverse events. The primary endpoint was the number of "completers", with adherence defined as >80% injections obtained in the period, weeks 12-26. Determining whether liraglutide is a feasible treatment was pre-defined to a minimum of 75% completers., Results: Twenty-four participants were included in the study. Sex, male = 19 (79.2%). Mean age: 42.3 [25th and 75th percentiles: 39.1; 48.4] years; body mass index (BMI): 35.7 [31.7; 37.5] kg/m 2 ; glycated haemoglobin (HbA1c): 37 [35; 39] mmol/mol. Eleven out of 24 participants (46%) completed the study. For the completers, the median net body weight loss after 26 weeks of participation was -11.4 kg [-15.4; -5.9]. The net difference in HbA1C and BMI was -2.0 mmol/mol [-4; -1] and -3.6 kg/m 2 [-4.7; -1.8], respectively. The weight change and reduction in HbA1c and BMI were all statistically significant from baseline., Conclusion: The study did not confirm our hypothesis that liraglutide is a feasible treatment for a minimum of 75% of the patients initiating treatment with liraglutide while hospitalised in a forensic psychiatric department. The high dropout rate may be due to the non-naturalistic setting of the clinical trial. For the proportion of patients compliant with the medication, liraglutide 3.0 mg was an efficient treatment for overweight., (© 2024 The Authors. Acta Psychiatrica Scandinavica published by John Wiley & Sons Ltd.)

Background: The decline in global child mortality is an important public health achievement, yet child mortality remains disproportionally high in many low-income countries like Guinea-Bissau. The persisting high mortality rates necessitate targeted research to identify vulnerable subgroups of children and formulate effective interventions., Objective: This study aimed to discover subgroups of children at an elevated risk of mortality in the urban setting of Bissau, Guinea-Bissau, West Africa. By identifying these groups, we intend to provide a foundation for developing targeted health interventions and inform public health policy., Methods: We used data from the health and demographic surveillance site, Bandim Health Project, covering 2003 to 2019. We identified baseline variables recorded before children reached the age of 6 weeks. The focus was on determining factors consistently linked with increased mortality up to the age of 3 years. Our multifaceted methodological approach incorporated spatial analysis for visualizing geographical variations in mortality risk, causally adjusted regression analysis to single out specific risk factors, and machine learning techniques for identifying clusters of multifactorial risk factors. To ensure robustness and validity, we divided the data set temporally, assessing the persistence of identified subgroups over different periods. The reassessment of mortality risk used the targeted maximum likelihood estimation (TMLE) method to achieve more robust causal modeling., Results: We analyzed data from 21,005 children. The mortality risk (6 weeks to 3 years of age) was 5.2% (95% CI 4.8%-5.6%) for children born between 2003 and 2011, and 2.9% (95% CI 2.5%-3.3%) for children born between 2012 and 2016. Our findings revealed 3 distinct high-risk subgroups with notably higher mortality rates, children residing in a specific urban area (adjusted mortality risk difference of 3.4%, 95% CI 0.3%-6.5%), children born to mothers with no prenatal consultations (adjusted mortality risk difference of 5.8%, 95% CI 2.6%-8.9%), and children from polygamous families born during the dry season (adjusted mortality risk difference of 1.7%, 95% CI 0.4%-2.9%). These subgroups, though small, showed a consistent pattern of higher mortality risk over time. Common social and economic factors were linked to a larger share of the total child deaths., Conclusions: The study's results underscore the need for targeted interventions to address the specific risks faced by these identified high-risk subgroups. These interventions should be designed to work to complement broader public health strategies, creating a comprehensive approach to reducing child mortality. We suggest future research that focuses on developing, testing, and comparing targeted intervention strategies unraveling the proposed hypotheses found in this study. The ultimate aim is to optimize health outcomes for all children in high-mortality settings, leveraging a strategic mix of targeted and general health interventions to address the varied needs of different child subgroups., (©Andreas Rieckmann, Sebastian Nielsen, Piotr Dworzynski, Heresh Amini, Søren Wengel Mogensen, Isaquel Bartolomeu Silva, Angela Y Chang, Onyebuchi A Arah, Wojciech Samek, Naja Hulvej Rod, Claus Thorn Ekstrøm, Christine Stabell Benn, Peter Aaby, Ane Bærent Fisker. Originally published in JMIR Public Health and Surveillance (https://publichealth.jmir.org), 09.04.2024.)

Agreement between methods for quantitative measurements are typically assessed by computing limits of agreement between pairs of methods and/or by illustration through Bland-Altman plots. We consider the situation where the observed measurement methods are considered a random sample from a population of possible methods, and discuss how the underlying linear mixed effects model can be extended to this situation. This is relevant when, for example, the methods represent raters/judges that are used to score specific individuals or items. In the case of random methods, we are not interested in estimates pertaining to the specific methods, but are instead interested in quantifying the variation between the methods actually involved making measurements, and accommodating this as an extra source of variation when generalizing to the clinical performance of a method. In the model we allow raters to have individual precision/skill and permit linked replicates ( i.e. , when the numbering, labeling or ordering of the replicates within items is important). Applications involving estimation of the limits of agreement for two datasets are shown: A dataset of spatial perception among a group of students as well as a dataset on consumer preference of French chocolate. The models are implemented in the MethComp package for R [Carstensen B, Gurrin L, Ekstrøm CT, Figurski M. MethComp: functions for analysis of agreement in method comparison studies; 2013. R package version 1.22, R Core Team. R: a language and environment for statistical computing. Vienna, Austria: R Foundation for Statistical Computing; 2012]., (© 2024 Walter de Gruyter GmbH, Berlin/Boston.)

Ethnic disparities in stillbirth exist in Europe and suboptimal care due to miscommunication is one contributing cause. The MAMAACT intervention aimed to reduce ethnic disparity in stillbirth and newborns' health through improved management of pregnancy complications. The intervention encompassed training of antenatal care midwives in cultural competencies and intercultural communication combined with health education materials for the expecting parents about symptoms of pregnancy complications. The evaluation consisted of a qualitative in-depth implementation analysis and a process evaluation embedded in a cluster randomized trial including 19 of 20 maternity wards in Denmark. In this article, the findings from the different evaluation perspectives are integrated. The integration follows the principles of realist evaluation by analyzing to what extent the MAMAACT activities were generating mechanisms of change in interaction with the context. The integration analysis shows that the health education materials in the MAMAACT intervention contributed to heightened health literacy concerning pregnancy complications among pregnant women. Additionally, the training of midwives in cultural competency and intercultural communication raised awareness among midwives. Nonetheless, the exclusive emphasis on midwives and the inflexibility in care provision hindered them from changing their communication practices. To enhance the cultural competence in maternity care, it is essential to implement more comprehensive initiatives involving healthcare professionals in maternity care at all levels, from pregraduate to postgraduate. Adequate interpreter services and management support should also be ensured. Currently, the Danish antenatal care system faces challenges including inadequate information transfer between healthcare sectors, insufficient differentiation of care, and inflexibility in midwife scheduling. This results in a lack of responsiveness to the individual needs of women with immigrant backgrounds, potentially reproducing health inequities., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (© 2024 Villadsen, Johnsen, Damsted Rasmussen, Ekstrøm, Sørensen, Azria, Rich-Edwards, Essén, Christensen, Smith Jervelund and Nybo Andersen.)

Motivation: Polygenic scores (PGSs) are widely available and employed in genomic data analyses for predicting and understanding genetic architectures. Existing approaches either require information on SNP level, do not infer clusters of traits sharing genetic characteristic, or do not have any immediate predictive properties., Results: Here, we present geneJAM, which is a novel clustering and estimation method using PGSs for inferring a genetic relationship among multiple, simultaneously measured and potentially correlated traits in a multivariate GWAS.Using graphical lasso, we estimate a sparse covariance matrix of the PGSs and obtain clusters of traits sharing genetic characteristics. We use the clusters to specify the structure of the error covariance matrix of a generalized least squares (GLS) model and use the feasible GLS estimator for estimating a linear regression model with a certain unknown degree of correlation between the residuals.The method suits many biology studies well with traits embedded in some genetic functioning groups and facilitates development of the PGS research. We compare the method with fully parametric techniques on simulated data and illustrate the utility of the methods by examining a heterogeneous stock mouse data set from the Wellcome Trust Centre for Human Genetics. We demonstrate that the method successfully identifies clusters of traits and increases precision, power, and computational efficiency., Availability and Implementation: GeneJAM is implemented in R and available at: https://github.com/abuchardt/geneJAM., Competing Interests: None declared., (© The Author(s) 2024. Published by Oxford University Press.)

Life-course epidemiology relies on specifying complex (causal) models that describe how variables interplay over time. Traditionally, such models have been constructed by perusing existing theory and previous studies. By comparing data-driven and theory-driven models, we investigated whether data-driven causal discovery algorithms can help in this process. We focused on a longitudinal data set on a cohort of Danish men (the Metropolit Study, 1953-2017). The theory-driven models were constructed by 2 subject-field experts. The data-driven models were constructed by use of the temporal Peter-Clark (TPC) algorithm. The TPC algorithm utilizes the temporal information embedded in life-course data. We found that the data-driven models recovered some, but not all, causal relationships included in the theory-driven expert models. The data-driven method was especially good at identifying direct causal relationships that the experts had high confidence in. Moreover, in a post hoc assessment, we found that most of the direct causal relationships proposed by the data-driven model but not included in the theory-driven model were plausible. Thus, the data-driven model may propose additional meaningful causal hypotheses that are new or have been overlooked by the experts. In conclusion, data-driven methods can aid causal model construction in life-course epidemiology, and combining both data-driven and theory-driven methods can lead to even stronger models., (© The Author(s) 2023. Published by Oxford University Press on behalf of the Johns Hopkins Bloomberg School of Public Health. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)

The obesity epidemic, evolving in many countries since the 1970s, has been attributed to the widespread contemporary so-called obesogenic transformation of the societies, but what preceded the epidemic? Using quantile regression, we studied the trends by year of birth in the percentile distribution of body mass index (BMI = weight/height 2 ) of 320,962 Danish school children, born from 1930 to 1976, and of 205,153 Danish young conscripts, born from 1939 to 1959. The overall trend of the percentiles of the BMI distributions were found to be linear across the years of birth. While the percentiles below the 75th were almost stable, those above showed a steadily steeper rise the more extreme the percentile among both school children and young men is. These changes, indicating the emergence of the obesity epidemic, preceded the presumed obesogenic transformation of the society by several decades and imply that other, so far unknown, factors have been involved.

Background: Chronic subdural hematoma (CSDH) pathophysiology has undergone a paradigm shift from being regarded as solely traumatic to be driven mainly by inflammation. Human leucocyte antigen (HLA) is a gene complex involved in antigen processing and presentation to T lymphocytes, thereby mediating the adaptive immune responses. As specific HLA profiles are associated with inflammatory diseases, patients with a specific HLA profile may have a lower threshold for subdural inflammation, and therefore are predisposed for CSDH development. We hypothesized that (1) CSDH patients have a specific HLA profile compared to a Danish background population, and (2) patients with recurrent CSDH have a specific HLA profile compared to CSDH patients without recurrent CSDH., Methods: Three specific HLA class II haplotypes known to drive inflammatory-mediated diseases were determined in 68 patients with CSDH. The distribution of these three haplotypes in our CSDH population was compared to a Danish population of blood donors using Monte Carlo Pearson's chi-square test. Furthermore, the distribution of the haplotypes was compared between CSDH patients with and without recurrent CSDH., Results: We found no significant association between either of the haplotypes and the risk of CSDH, and neither of the haplotypes were associated with increased risk of CSDH recurrence., Conclusion: This study did not show an association between selected HLA class II haplotypes and the risk of CSDH or recurrence of CSDH compared with a healthy background population., (© 2023. The Author(s), under exclusive licence to Springer-Verlag GmbH Austria, part of Springer Nature.)

Objective: To evaluate whether MAMAACT, an antenatal care (ANC) intervention, aimed at reducing ethnic and social disparities in perinatal mortality, affected perinatal health outcomes., Design: Cluster randomised controlled trial., Setting: Nineteen of 20 maternity wards in Denmark., Population: All newborn children within a pre-implementation period (2014-2017) or an implementation period (2018-2019) (n = 188 658)., Intervention: A 6-h training session for midwives in intercultural communication and cultural competence, two follow-up dialogue meetings, and health education materials for pregnant women on warning signs of pregnancy complications in six languages., Methods: Nationwide register-based analysis of the MAMAACT cluster randomised controlled trial. Mixed-effects logistic regression models were used to estimate the change in outcomes from pre- to post-implementation in the intervention group relative to the control group. Results were obtained for the overall study population and for children born to immigrants from low- to middle-income countries, separately. Models were adjusted for confounders selected a priori., Main Outcome Measures: A composite perinatal mortality and morbidity outcome, including stillbirths, neonatal deaths, Apgar score <7, umbilical arterial pH < 7.0, admissions to a neonatal intensive care unit (NICU) >48 h, and NICU admissions for mechanical ventilation. Additional outcomes were the individual measures., Results: The intervention increased the risk of the composite outcome (adjusted odds ratio [aOR] 1.16, 95% confidence interval [CI] 0.99-1.34), mainly driven by differences in NICU admission risk (composite outcome excluding NICU, aOR 0.98, 95% CI 0.84-1.14). The intervention slightly increased the risk of low Apgar score and decreased the risk of low arterial pH, reflecting, however, small differences in absolute numbers. Other outcomes were unchanged., Conclusions: Overall, the MAMAACT intervention did not improve the composite perinatal mortality and morbidity outcome (when excluding NICU admissions). The lack of effects may be due to contextual factors including organisational barriers in ANC hindering the midwives from changing practices., (© 2023 The Authors. BJOG: An International Journal of Obstetrics and Gynaecology published by John Wiley & Sons Ltd.)

Linkage between drug claims data and clinical outcome allows a data-driven experimental approach to drug repurposing. We develop an estimation procedure based on generalized random forests for estimation of time-point specific average treatment effects in a time-to-event setting with competing risks. To handle right-censoring, we propose a two-step procedure for estimation, applying inverse probability weighting to construct time-point specific weighted outcomes as input for the generalized random forest. The generalized random forests adaptively handle covariate effects on the treatment assignment by applying a splitting rule that targets a causal parameter. Using simulated data we demonstrate that the method is effective for a causal search through a list of treatments to be ranked according to the magnitude of their effect on clinical outcome. We illustrate the method using the Danish national health registries where it is of interest to discover drugs with an unexpected protective effect against relapse of severe depression., (© 2023 John Wiley & Sons Ltd.)

Objectives: This study aimed to analyze mortality, risk factors, and causes of death among people with tuberculosis (TB)., Methods: This is a population-based cohort study with patients with TB ≥18 years notified from 1990 to 2018 in Denmark, compared with sex- and age-matched controls. Mortality was assessed in Kaplan-Meier models and risk factors for death were estimated in Cox proportional hazards models., Results: Overall mortality was twofold higher among people with TB compared with controls up to 15 years after TB diagnosis (hazard ratio [HR]: 2.18, 95% confidence interval [CI]: 2.06-2.29, P <0.0001). Danes with TB were three times more likely to die than migrants (adjusted HR: 3.13, 95% CI: 2.84-3.45, P <0.0001). Risk factors for death included living alone, being unemployed, having low income, and comorbidities such as mental illness with substance abuse, lung diseases, hepatitis, and HIV. TB was the most common cause of death (21%), followed by chronic obstructive pulmonary disease (7%), lung cancer (6%), alcoholic liver disease (5%), and mental illness with substance abuse (4%)., Conclusion: People with TB had substantially inferior survival up to 15 years after TB diagnosis, in particular, socially disadvantaged Danes with TB with specific comorbidities. This may reflect unmet needs for enhanced treatment of other medical/social conditions during TB treatment., Competing Interests: Declaration of competing interest The authors have no competing interests to declare., (Copyright © 2023 The Author(s). Published by Elsevier Ltd.. All rights reserved.)

Background: Breastmilk is the ideal nutrition for infants, and breastfeeding protects infants and mothers from a range of adverse health outcomes. In Denmark, most mothers initiate breastfeeding but many cease within the first months resulting in just 14% reaching the World Health Organization recommendation of six months of exclusive breastfeeding. Furthermore, the low breastfeeding proportion at six months is characterised by a marked social inequality. A previous intervention tested in a hospital setting succeeded in increasing the proportion of mothers breastfeeding exclusively at six months. However, most breastfeeding support is provided within the Danish municipality-based health visiting programme. Therefore, the intervention was adapted to fit the health visiting programme and implemented in 21 Danish municipalities. This article reports the study protocol, which will be used to evaluate the adapted intervention., Methods: The intervention is tested in a cluster-randomised trial at the municipal level. A comprehensive evaluation approach is taken. The effectiveness of the intervention will be evaluated using survey and register data. Primary outcomes are the proportion of women who breastfeed exclusively at four months postpartum and duration of exclusive breastfeeding measured as a continuous outcome. A process evaluation will be completed to evaluate the implementation of the intervention; a realist evaluation will provide an understanding of the mechanisms of change characterising the intervention. Finally, a health economic evaluation will assess the cost-effectiveness and cost-utility of this complex intervention., Discussion: This study protocol reports on the design and evaluation of the Breastfeeding Trial - a cluster-randomised trial implemented within the Danish Municipal Health Visiting Programme from April 2022 to October 2023. The purpose of the programme is to streamline breastfeeding support provided across healthcare sectors. The evaluation approach is comprehensive using a multitude of data to analyse the effect of the intervention and inform future efforts to improve breastfeeding for all., Trial Registration: Prospectively registered with Clinical Trials NCT05311631 https://clinicaltrials.gov/ct2/show/NCT05311631., (© 2023. The Author(s).)

Preterm birth is associated with smaller body dimensions at birth. The impact on body size in later life, measured by body mass index (BMI) and height, remains unclear. A prospective register-based cohort study with 62,625 singletons from the Danish National Birth Cohort born 1996-2003 for whom information on gestational age (GA) at birth, length or weight at birth, and at least two growth measurements scheduled at the ages of 5 and 12 months, and 7, 11 and 18 years were available. Linear mixed effects with splines, stratified by sex, and adjusted for confounders were used to estimate standardised BMI and height. GA was positively associated with BMI in infancy, but differences between preterm and term children declined with age. By age 7, preterm children had slightly lower BMI than term children, whereas no difference was observed by adolescence (mean difference in BMI z-score - 0.28 to 0.15). GA was strongly associated with height in infancy, but mean differences between individuals born preterm and term declined during childhood. By adolescence, the most preterm individuals remained shorter than their term peers (mean difference in height z-score from - 1.00 to - 0.28). The lower BMI in preterm infants relative to term infants equalizes during childhood, such that by adolescence there is no clear difference. Height is strongly positively associated with GA in early childhood, whilst by end of adolescence individuals born preterm remain slightly shorter than term peers., (© 2023. The Author(s).)

Background: Preterm birth is the leading cause of perinatal morbidity and mortality and is associated with adverse developmental and long-term health outcomes, including several cardiometabolic risk factors and outcomes. However, evidence about the association of preterm birth with later body size derives mainly from studies using birth weight as a proxy of prematurity rather than an actual length of gestation. We investigated the association of gestational age (GA) at birth with body size from infancy through adolescence., Methods and Findings: We conducted a two-stage individual participant data (IPD) meta-analysis using data from 253,810 mother-child dyads from 16 general population-based cohort studies in Europe (Denmark, Finland, France, Italy, Norway, Portugal, Spain, the Netherlands, United Kingdom), North America (Canada), and Australasia (Australia) to estimate the association of GA with body mass index (BMI) and overweight (including obesity) adjusted for the following maternal characteristics as potential confounders: education, height, prepregnancy BMI, ethnic background, parity, smoking during pregnancy, age at child's birth, gestational diabetes and hypertension, and preeclampsia. Pregnancy and birth cohort studies from the LifeCycle and the EUCAN-Connect projects were invited and were eligible for inclusion if they had information on GA and minimum one measurement of BMI between infancy and adolescence. Using a federated analytical tool (DataSHIELD), we fitted linear and logistic regression models in each cohort separately with a complete-case approach and combined the regression estimates and standard errors through random-effects study-level meta-analysis providing an overall effect estimate at early infancy (>0.0 to 0.5 years), late infancy (>0.5 to 2.0 years), early childhood (>2.0 to 5.0 years), mid-childhood (>5.0 to 9.0 years), late childhood (>9.0 to 14.0 years), and adolescence (>14.0 to 19.0 years). GA was positively associated with BMI in the first decade of life, with the greatest increase in mean BMI z-score during early infancy (0.02, 95% confidence interval (CI): 0.00; 0.05, p < 0.05) per week of increase in GA, while in adolescence, preterm individuals reached similar levels of BMI (0.00, 95% CI: -0.01; 0.01, p 0.9) as term counterparts. The association between GA and overweight revealed a similar pattern of association with an increase in odds ratio (OR) of overweight from late infancy through mid-childhood (OR 1.01 to 1.02) per week increase in GA. By adolescence, however, GA was slightly negatively associated with the risk of overweight (OR 0.98 [95% CI: 0.97; 1.00], p 0.1) per week of increase in GA. Although based on only four cohorts (n = 32,089) that reached the age of adolescence, data suggest that individuals born very preterm may be at increased odds of overweight (OR 1.46 [95% CI: 1.03; 2.08], p < 0.05) compared with term counterparts. Findings were consistent across cohorts and sensitivity analyses despite considerable heterogeneity in cohort characteristics. However, residual confounding may be a limitation in this study, while findings may be less generalisable to settings in low- and middle-income countries., Conclusions: This study based on data from infancy through adolescence from 16 cohort studies found that GA may be important for body size in infancy, but the strength of association attenuates consistently with age. By adolescence, preterm individuals have on average a similar mean BMI to peers born at term., Competing Interests: I have read the journal’s policy and the authors of this manuscript have the following competing interests: DAL has received support from Roche Diagnostics and Medtronic in relation to biomarker research that is not related to the research presented in this paper. The other authors have declared that no competing interests exist., (Copyright: © 2023 Vinther et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Health care expenditure in the last year of life makes up a high proportion of medical spending across the world. This is often framed as waste, but this framing is only meaningful if it is known at the time of treatment who will go on to die. We analyze the distribution of health care spending by predicted mortality for the Danish population over age 65 over the year 2016, with one-year mortality predicted by a machine learning model based on sociodemographics and use of health care services for the two years before entry into follow-up. While a reasonably good model can be built, extremely few individuals have high ex-ante probability of dying, and those with a predicted mortality of more than 50% account for only 2.8% of total health care expenditure. Decedents outspent survivors by a factor of more than ten, but compared to survivors with similar predicted mortality they spent only 2.5 times as much. Our results suggest that while spending in the last year of life is indeed high, this is nearly all spent in situations where there is a reasonable expectation that the patient can survive., (© 2023. The Author(s).)

Many popular sports involve matches between two teams or players where each team have the possibility of scoring points throughout the match. While the overall match winner and result is interesting, it conveys little information about the underlying scoring trends throughout the match. Modeling approaches that accommodate a finer granularity of the score difference throughout the match is needed to evaluate in-game strategies, discuss scoring streaks, teams strengths, and other aspects of the game. We propose a latent Gaussian process to model the score difference between two teams and introduce the Trend Direction Index as an easily interpretable probabilistic measure of the current trend in the match as well as a measure of post-game trend evaluation. In addition we propose the Excitement Trend Index-the expected number of monotonicity changes in the running score difference-as a measure of overall game excitement. Our proposed methodology is applied to all 1143 matches from the 2019-2020 National Basketball Association season. We show how the trends can be interpreted in individual games and how the excitement score can be used to cluster teams according to how exciting they are to watch., Supplementary Information: The online version contains supplementary material available at 10.1007/s10182-022-00452-w., Competing Interests: Conflict of interestThe authors declare that they have no conflict of interest., (© Springer-Verlag GmbH Germany, part of Springer Nature 2022.)

Background: Randomised clinical trials in critical care are prone to inconclusiveness owing, in part, to undue optimism about effect sizes and suboptimal accounting for heterogeneous treatment effects. Planned predictive enrichment based on secondary critical care data (often very rich with respect to both data types and temporal granularity) and causal inference methods may help overcome these challenges, but no overview exists about their use to this end., Methods: We will conduct a scoping review to assess the extent and nature of the use of causal inference from secondary data for planned predictive enrichment of randomised clinical trials in critical care. We will systematically search 10 general and specialty journals for reports published on or after 1 January 2018, of randomised clinical trials enrolling adult critically ill patients. We will collect trial metadata (e.g., recruitment period and phase) and, when available, information pertaining to the focus of the review (predictive enrichment based on causal inference estimates from secondary data): causal inference methods, estimation techniques and software used; types of patient populations; data provenance, types and models; and the availability of the data (public or not). The results will be reported in a descriptive manner., Discussion: The outlined scoping review aims to assess the use of causal inference methods and secondary data for planned predictive enrichment in randomised critical care trials. This will help guide methodological improvements to increase the utility, and facilitate the use, of causal inference estimates when planning such trials in the future., (© 2022 The Authors. Acta Anaesthesiologica Scandinavica published by John Wiley & Sons Ltd on behalf of Acta Anaesthesiologica Scandinavica Foundation.)

Introduction: Alcohol use disorder is a difficult-to-treat psychiatric disorder and a major burden on public health. Existing treatment efficacy is moderate, and relapse rates are high. Preliminary findings suggest that psilocybin, a psychedelic compound, can safely and reliably occasion highly meaningful experiences that may spur a positive change in drinking behaviour when administered in a therapeutic context. However, the efficacy of a single psilocybin administration and its potential neurobiological underpinnings still remain unknown., Methods and Analysis: To establish efficacy, we will investigate the effects of psilocybin-assisted therapy versus placebo in a randomised, double-blinded, placebo-controlled 12-week clinical trial. Ninety treatment-seeking patients, aged 20-70 years, diagnosed with alcohol use disorder will be recruited from the community via advertisement and referrals from general practitioners or specialised treatment units. The psilocybin or placebo will be administered in accordance with a protocol for psychological support before, during and after the dosing. Outcome assessments will be carried out 1, 4, 8 and 12 weeks postdosing. The primary outcome is reduction in the percentage of heavy drinking days from baseline to follow-up at 12 weeks. Key secondary outcomes are as follows: (1) total alcohol consumption, (2) phosphatidyl-ethanol, an objective biomarker for alcohol, (3) plasma psilocin, the active metabolite, to establish a possible therapeutic range, (4) the acute subjective drug experience as a possible predictor of treatment outcome and (5) neuronal response to alcohol cues and cognitive flexibility within corticostriatal pathways by use of functional MR brain imaging 1-week postdosing., Ethics and Dissemination: Ethical approval has been obtained from the Committee on Health Research Ethics of the Capital Region of Denmark (H-20043832). All patients will be provided oral and written information about the trial before screening. The study results will be disseminated by peer-review publications and conference presentations., Trial Registration Number: EudraCT 2020-000829-55 and NCT05416229., Competing Interests: Competing interests: None declared., (© Author(s) (or their employer(s)) 2022. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.)

Background: The global vision is a world free of tuberculosis (TB). Even in resource-rich TB low-incidence settings, we need more focus on the role of social risk factors to end the TB epidemic., Methods: Nationwide, retrospective register-based, case-control study from 1990 to 2018, including all TB patients in Denmark ≥18 years old (n = 9581) matched 1:3 on sex and age with population controls. TB risk factors were assessed in logistic regression models and estimated by odds ratio (OR)., Results: All TB patients had considerably lower socio-economic status compared with controls (P < 0.0001). Among ethnic Danes, TB was mostly found among males, persons between 35 and 65 years, those living alone, those with low educational level, persons on social welfare benefits and those with low income. Conversely, for migrants, being younger, sex and living alone were less important, whereas having children was protective. In an adjusted multivariable regression model among Danes, key risk factors for TB were being on disability pension (OR = 2.7) and cash benefits (OR = 4.7). For migrants, fewer social risk factors increased TB risk, although low income and cash benefits did (OR = 3.1)., Conclusion: Even today in a resourceful setting, socio-economic status drives disparities in health. In our study, multifactorial social deprivation was highly associated with TB. Especially household structure, education, employment and income were important risk factors that should be addressed in the future to accelerate TB control and end the TB epidemic., (© The Author(s) 2022; all rights reserved. Published by Oxford University Press on behalf of the International Epidemiological Association.)

Nearly all diseases are caused by different combinations of exposures. Yet, most epidemiological studies focus on estimating the effect of a single exposure on a health outcome. We present the Causes of Outcome Learning approach (CoOL), which seeks to discover combinations of exposures that lead to an increased risk of a specific outcome in parts of the population. The approach allows for exposures acting alone and in synergy with others. The road map of CoOL involves (i) a pre-computational phase used to define a causal model; (ii) a computational phase with three steps, namely (a) fitting a non-negative model on an additive scale, (b) decomposing risk contributions and (c) clustering individuals based on the risk contributions into subgroups; and (iii) a post-computational phase on hypothesis development, validation and triangulation using new data before eventually updating the causal model. The computational phase uses a tailored neural network for the non-negative model on an additive scale and layer-wise relevance propagation for the risk decomposition through this model. We demonstrate the approach on simulated and real-life data using the R package 'CoOL'. The presentation focuses on binary exposures and outcomes but can also be extended to other measurement types. This approach encourages and enables researchers to identify combinations of exposures as potential causes of the health outcome of interest. Expanding our ability to discover complex causes could eventually result in more effective, targeted and informed interventions prioritized for their public health impact., (© The Author(s) 2022; all rights reserved. Published by Oxford University Press on behalf of the International Epidemiological Association.)

BackgroundAlcohol use disorder (AUD) is a chronic, relapsing brain disorder that accounts for 5% of deaths annually, and there is an urgent need to develop new targets for therapeutic intervention. The glucagon-like peptide-1 (GLP-1) receptor agonist exenatide reduces alcohol consumption in rodents and nonhuman primates, but its efficacy in patients with AUD is unknown.MethodsIn a randomized, double-blinded, placebo-controlled clinical trial, treatment-seeking AUD patients were assigned to receive exenatide (2 mg subcutaneously) or placebo once weekly for 26 weeks, in addition to standard cognitive-behavioral therapy. The primary outcome was reduction in number of heavy drinking days. A subgroup also completed functional MRI (fMRI) and single-photon emission CT (SPECT) brain scans.ResultsA total of 127 patients were enrolled. Our data revealed that although exenatide did not significantly reduce the number of heavy drinking days compared with placebo, it significantly attenuated fMRI alcohol cue reactivity in the ventral striatum and septal area, which are crucial brain areas for drug reward and addiction. In addition, dopamine transporter availability was lower in the exenatide group compared with the placebo group. Exploratory analyses revealed that exenatide significantly reduced heavy drinking days and total alcohol intake in a subgroup of obese patients (BMI > 30 kg/m2). Adverse events were mainly gastrointestinal.ConclusionThis randomized controlled trial on the effects of a GLP-1 receptor agonist in AUD patients provides new important knowledge on the effects of GLP-1 receptor agonists as a novel treatment target in addiction.Trial registrationEudraCT: 2016-003343-11. ClinicalTrials.gov (NCT03232112).FundingNovavi Foundation; Research Foundation, Mental Health Services, Capital Region of Denmark; Research Foundation, Capital Region of Denmark; Ivan Nielsen Foundation; A.P. Moeller Foundation; Augustinus Foundation; Woerzner Foundation; Grosserer L.F. Foghts Foundation; Hartmann Foundation; Aase and Ejnar Danielsen Foundation; P.A. Messerschmidt and Wife Foundation; and Lundbeck Foundation.

Aims: Communication barriers in healthcare encounters contribute to ethnic inequality in health outcomes. This study aimed to examine, in a large national Danish sample of women, whether ethnicity was associated with pregnant women's Active engagement with healthcare providers. Methods: A cross-sectional survey of 1898 pregnant women attending 19 Danish maternity wards. The key variable of interest was maternal ethnicity among ethnic Danish, European, African and Asian immigrant women and their descendants. Syrian immigrant women were studied as a subgroup. The outcome was the health literacy questionnaire domain Ability to engage actively with healthcare providers (five-item domain scored from 'cannot do/always difficult' (1) to 'always easy' (5)) which is a reflection of a respondent's lived experiences of engaging with healthcare providers. Adjusted mixed effect multivariate linear regression was used to compare Active engagement across groups expressed as the mean difference (95% confidence interval). Results: Lower means of Active engagement were reported for immigrant women compared to ethnic Danish women in all models. When adjusting for age, parity, complications and occupation, the difference between ethnic Danish women's Active engagement and other groups was smallest among European -0.15 (-0.26 to -0.05), slightly larger in African -0.19 (-0.40 to 0.02), and largest in Asian immigrant women -0.31 (-0.41 to -0.21). Syrian immigrant women had the largest difference -0.42 (-0.58 to -0.27). Conclusions: Pregnant immigrant women reported lower means of Active engagement than ethnic Danish women did. Increased health literacy responsiveness in maternity care is required to mitigate the potential for differential care and health inequity.

Objectives: Ethnic differences in perinatal morbidity and mortality are starting points for social inequality in health. Increased incidence and severity of some pregnancy complications are found among immigrant women compared to ethnic majority women in high-income settings. However, little is known about immigrant women's assessment and management of warning signs. We aimed to assess women's knowledge about how to manage warning signs of pregnancy complications among immigrants and their descendants compared to women of Danish origin., Methods: A cross-sectional study including phone-based interviews with 1899 women. Women were interviewed during gestational week 30-37 in one of six languages. Maternal ethnicity was categorized as; immigrants, their descendants and ethnic Danes. The outcomes were yes or no to; do you know what to do if you experience 1) sudden swelling, redness, and heat in one leg 2) severe headache and 3) vaginal bleeding., Results: Immigrant women had lower levels of knowledge about how to manage all three types of warning signs of pregnancy complications compared to women of Danish origin. Adjusted OR for vaginal bleeding for women of European (4.33, 95% CI: 2.24-8.37), Asian (9.26, 95% CI: 5.10-16.83) and African (8.66, 95% CI: 3.26-23.05) origin., Conclusions for Practice: Immigrant women had lower levels of knowledge about how to manage warning signs of pregnancy complications compared to women of Danish origin. Improved needs-based health education in pregnancy complications and body symptoms during antenatal care is needed to address delays in the management of complications and could potentially improve the health of women and children., (© 2021. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.)

Metagenomics is increasingly used to describe microbial communities in biological specimens. Ideally, the steps involved in the processing of the biological specimens should not change the microbiome composition in a way that it could lead to false interpretations of inferred microbial community composition. Common steps in sample preparation include sample collection, storage, DNA isolation, library preparation, and DNA sequencing. Here, we assess the effect of three library preparation kits and two DNA sequencing platforms. Of the library preparation kits, one involved a PCR step (Nextera), and two were PCR free (NEXTflex and KAPA). We sequenced the libraries on Illumina HiSeq and NextSeq platforms. As example microbiomes, two pig fecal samples and two sewage samples of which aliquots were stored at different storage conditions (immediate processing and storage at -80°C) were assessed. All DNA isolations were performed in duplicate, totaling 80 samples, excluding controls. We found that both library preparation and sequencing platform had systematic effects on the inferred microbial community composition. The different sequencing platforms introduced more variation than library preparation and freezing the samples. The results highlight that all sample processing steps need to be considered when comparing studies. Standardization of sample processing is key to generating comparable data within a study, and comparisons of differently generated data, such as in a meta-analysis, should be performed cautiously. IMPORTANCE Previous research has reported effects of sample storage conditions and DNA isolation procedures on metagenomics-based microbiome composition; however, the effect of library preparation and DNA sequencing in metagenomics has not been thoroughly assessed. Here, we provide evidence that library preparation and sequencing platform introduce systematic biases in the metagenomic-based characterization of microbial communities. These findings suggest that library preparation and sequencing are important parameters to keep consistent when aiming to detect small changes in microbiome community structure. Overall, we recommend that all samples in a microbiome study are processed in the same way to limit unwanted variations that could lead to false conclusions. Furthermore, if we are to obtain a more holistic insight from microbiome data generated around the world, we will need to provide more detailed sample metadata, including information about the different sample processing procedures, together with the DNA sequencing data at the public repositories.

BackgroundPregnancy increases the risk of tuberculosis (TB), however, data on TB epidemiology in pregnant women are limited.AimTo guide possible interventions, we analysed risk factors for TB in pregnant and post-partum women.MethodsWe conducted a nationwide retrospective register-based case-control study from January 1990 to December 2018 in Denmark. Cases were women diagnosed with TB during their pregnancy or in the post-partum period. We selected two control groups: pregnant or post-partum women without TB, and non-pregnant women with TB. Differences were assessed by chi-squared or Fisher's exact test. Risk factors for TB were identified through logistic regression and estimated by odds ratio (OR).ResultsWe identified 392 cases, including 286 pregnant and 106 post-partum women. Most were migrants (n = 366; 93%) with a shorter median time spent in Denmark (2.74 years; interquartile range (IQR): 1.52-4.64) than non-pregnant TB controls (3.98 years; IQR: 1.43-8.51). Cases less likely had a Charlson comorbidity index ≥ 2compared with non-pregnant TB controls (p < 0.0001), and had no increased risk of severe disease (p = 0.847). Migrants from other World Health Organization regions than Europe, especially Africa (OR: 187; 95%CI: 125-281) had persistently higher odds of TB.ConclusionsIn Denmark, the risk of TB in pregnant and post-partum women is increased in migrant women who have stayed in the country a median time of approximately 3 years. We recommend increased focus on TB risk during pregnancy and suggest evaluating targeted TB screening of selected at-risk pregnant women to promote early case finding and prevent TB among mothers and their newborn children.

Patients with severe mental illness (SMI) i.e. schizophrenia, schizoaffective disorder, and bipolar disorder are at increased risk of severe outcomes if infected with coronavirus disease 2019 (COVID-19). Whether patients with SMI are at increased risk of COVID-19 is, however, sparsely investigated. This important issue must be addressed as the current pandemic could have the potential to increase the existing gap in lifetime mortality between this group of patients and the background population. The objective of this study was to determine whether a diagnosis of schizophrenia, schizoaffective disorder, or bipolar disorder is associated with an increased risk of COVID-19. A cross-sectional study was performed between January 18th and February 25th, 2021. Of 7071 eligible patients with schizophrenia, schizoaffective disorder, or bipolar disorder, 1355 patients from seven psychiatric centres in the Capital Region of Denmark were screened for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) antibodies. A total of 1258 unvaccinated patients were included in the analysis. The mean age was 40.5 years (SD 14.6), 54.3% were female. Fifty-nine of the 1258 participants had a positive SARS-CoV-2 antibody test, corresponding to a adjusted seroprevalence of 4.96% (95% CI 3.87-6.35). No significant difference in SARS-CoV-2-risk was found between female and male participants (RR = 1.32; 95% CI 0.79-2.20; p = .290). No significant differences in seroprevalences between schizophrenia and bipolar disease were found (RR = 1.12; 95% CI 0.67-1.87; p = .667). Seroprevalence among 6088 unvaccinated blood donors from the same region and period was 12.24% (95% CI 11.41-13.11). SARS-CoV-2 seroprevalence among included patients with SMI was significantly lower than among blood donors (RR = 0.41; 95% CI 0.31-0.52; p < .001). Differences in seroprevalences remained significant when adjusting for gender and age, except for those aged 60 years or above. The study is registered at ClinicalTrails.gov (NCT04775407). https://clinicaltrials.gov/ct2/show/NCT04775407?term=NCT04775407&draw=2&rank=1., Competing Interests: The authors have declared that no competing interests exist.

Background: Adults born preterm (<37 weeks) have lower educational attainment than those born term. Whether this relationship is modified by family factors such as socioeconomic background is, however, less well known. We investigated whether the relationship between gestational age and educational attainment in adulthood differed according to parents' educational level in 4 Nordic countries., Methods: This register-based cohort study included singletons born alive from 1987 up to 1992 in Denmark, Finland, Norway, and Sweden. In each study population, we investigated effect modification by parents' educational level (low, intermediate, high) on the association between gestational age at birth (25-44 completed weeks) and low educational attainment at 25 years (not having completed upper secondary education) using general estimation equations logistic regressions., Results: A total of 4.3%, 4.0%, 4.8%, and 5.0% singletons were born preterm in the Danish (n = 331 448), Finnish (n = 220 095), Norwegian (n = 292 840), and Swedish (n = 513 975) populations, respectively. In all countries, both lower gestational age and lower parental educational level contributed additively to low educational attainment. For example, in Denmark, the relative risk of low educational attainment was 1.84 (95% confidence interval 1.44 to 2.26) in adults born at 28 to 31 weeks whose parents had high educational level and 5.25 (95% confidence interval 4.53 to 6.02) in adults born at 28 to 31 weeks whose parents had low educational level, compared with a reference group born at 39 to 41 weeks with high parental educational level., Conclusions: Although higher parental education level was associated with higher educational attainment for all gestational ages, parental education did not mitigate the educational disadvantages of shorter gestational age., Competing Interests: FINANCIAL DISCLOSURE: The authors have indicated that they have no financial relationships relevant to this article to disclose., (Copyright © 2021 by the American Academy of Pediatrics.)

Background: Individuals born preterm may experience difficulties beyond the neonatal period, such as poorer school outcomes. However, whether these outcomes are modified by family factors is less well-known., Objectives: To investigate whether parental educational level modify the relationship of gestational age with completion of final examinations and grade point average in compulsory education., Methods: This nationwide register-based cohort study included singletons born in Denmark during 1995-2001. We investigated the differences in the associations between gestational age (24-44 weeks) and two school outcomes at 16 years according to parental educational level (lower (≤10 years), intermediate (11-13 years), and higher (>13 years)). Mixed-effect logistic regression and mixed-effect linear regression were used to model completion of final examination and grade point average, respectively., Results: Of the 425 101 singletons, 4.7% were born before 37 weeks. The risk of not completing final examination increased with shorter gestational age and lower parental educational level. For instance, among adolescents whose parents had a lower educational level, the risk increased from 23.9% (95% CI, 23.1, 24.6) for those born in week 40 to 36.6% (95% CI, 31.5, 42.1) for those born in week 28. For adolescents whose parents had a higher educational level, the corresponding risk increase was 5.9% (95% CI, 5.7, 6.1) to 10.5% (95% CI, 8.6, 12.8), respectively. Grade point average decreased with shorter gestational age in adolescents born before 30 weeks and with lower parental educational level. The associations between gestational age and grade point average were similar across parental educational levels. For completions of final examination, the associations with gestational age were weaker with higher parental educational level., Conclusions: Shorter gestational age and lower parental educational level were associated with poorer school outcomes. Our findings suggest that parental educational level mitigates the adverse effects of shorter gestational age on some school outcomes., (© 2021 The Authors. Paediatric and Perinatal Epidemiology published by John Wiley & Sons Ltd.)

Life-course epidemiology is useful for describing and analyzing complex etiological mechanisms for disease development, but existing statistical methods are essentially confirmatory, because they rely on a priori model specification. This limits the scope of causal inquiries that can be made, because these methods are suited mostly to examine well-known hypotheses that do not question our established view of health, which could lead to confirmation bias. We propose an exploratory alternative. Instead of specifying a life-course model prior to data analysis, our method infers the life-course model directly from the data. Our proposed method extends the well-known Peter-Clark (PC) algorithm (named after its authors) for causal discovery, and it facilitates including temporal information for inferring a model from observational data. The extended algorithm is called temporal PC. The obtained life-course model can afterward be perused for interesting causal hypotheses. Our method complements classical confirmatory methods and guides researchers in expanding their models in new directions. We showcase the method using a data set encompassing almost 3,000 Danish men followed from birth until age 65 years. Using this data set, we inferred life-course models for the role of socioeconomic and health-related factors on development of depression., (© The Author(s) 2021. Published by Oxford University Press on behalf of the Johns Hopkins Bloomberg School of Public Health. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)

News media often report that the trend of some public health outcome has changed. These statements are frequently based on longitudinal data, and the change in trend is typically found to have occurred at the most recent data collection time point-if no change had occurred the story is less likely to be reported. Such claims may potentially influence public health decisions on a national level. We propose two measures for quantifying the trendiness of trends. Assuming that reality evolves in continuous time, we define what constitutes a trend and a change in trend, and introduce a probabilistic Trend Direction Index. This index has the interpretation of the probability that a latent characteristic has changed monotonicity at any given time conditional on observed data. We also define an index of Expected Trend Instability quantifying the expected number of changes in trend on an interval. Using a latent Gaussian process model, we show how the Trend Direction Index and the Expected Trend Instability can be estimated in a Bayesian framework, and use the methods to analyse the proportion of smokers in Denmark during the last 20 years and the development of new COVID-19 cases in Italy from 24 February onwards., (© 2021 The Royal Statistical Society and John Wiley & Sons Ltd.)

Objective: Diabetes is associated with an increased risk of depression. Some antidiabetes agents, specifically metformin and pioglitazone, have been suggested to have beneficial effects on depression, but associations between antidiabetes drugs and depression have not been systematically investigated., Research Design and Methods: We combined four Danish population-based registers to investigate whether the 20 most widely used orally administered antidiabetes drugs were associated with an altered risk of incident depression. Analyses of insulin were included for comparisons. All persons in Denmark in 2005 were included in the study and followed until 2015. Two different outcome measures of incident depression were included: 1 ) a diagnosis of depressive disorder at a psychiatric hospital as an inpatient or outpatient and 2 ) a combined measure of a diagnosis of depression or use of antidepressants. Data were analyzed using Cox regression models., Results: A total of 360,205 individuals using orally administered antidiabetes drugs and 64,582 using insulin at any time during the study period were included in the analyses. Continued use of metformin and combinations of drugs including metformin were associated with decreased rates of incident depression. Pioglitazone was not associated with a decreased rate of incident depression. No other antidiabetes drugs or insulin showed significant associations with depression., Conclusions: Real-life population-based data suggest a positive effect of metformin on depression rates. This evidence should be used in guiding prescriptions for patients with type 2 diabetes who are at risk for developing depression, including those with prior depression or anxiety and patients with a family history of depression., (© 2020 by the American Diabetes Association.)

Hypertension, cardiovascular diseases, and cerebrovascular diseases are associated with an increased risk of depression, but it remains unclear whether treatment with antihypertensive agents decreases or increases this risk. The effects of individual drugs are also unknown. We used Danish population-based registers to systematically investigate whether the 41 most used individual antihypertensive drugs were associated with an altered risk of incident depression. Analyses of diuretics were included for comparisons. Participants were included in the study in January 2005 and followed until December 2015. Two different outcome measures were included: (1) a diagnosis of depressive disorder at a psychiatric hospital as an inpatient or outpatient and (2) a combined measure of a diagnosis of depression or use of antidepressants. Continued use of classes of angiotensin agents, calcium antagonists, and β-blockers was associated with significantly decreased rates of depression, whereas diuretic use was not. Individual drugs associated with decreased depression included 2 of 16 angiotensin agents: enalapril and ramipril; 3 of 10 calcium antagonists: amlodipine, verapamil, and verapamil combinations; and 4 of 15 β-blockers: propranolol, atenolol, bisoprolol, and carvedilol. No drug was associated with an increased risk of depression. In conclusion, real-life population-based data suggest a positive effect of continued use of 9 individual antihypertensive agents. This evidence should be used in guiding prescriptions for patients at risk of developing depression including those with prior depression or anxiety and patients with a family history of depression.

Objective: To explore ehealth literacy, ability to actively engage with healthcare providers and health system navigation among pregnant immigrant women and their descendants compared with women of Danish origin., Design and Setting: A cross-sectional survey at antenatal clinics in 2016, Denmark., Participants: Pregnant women attending antenatal care (n=405)., Outcome Measures: The eHealth Literacy Questionnaire (eHLQ) and two domains from the Health Literacy Questionnaire (HLQ): ability to actively engage with healthcare providers and health system navigation. Range of response options for eHLQ (1-4) and HLQ (1-5). With mixed-effect linear regressions, eHLQ and HLQ among immigrants and their descendants compared with women of Danish origin were assessed., Results: The response rate was 75%. The overall trend was lower ehealth literacy and HLQ domains among immigrants and their descendants compared with women of Danish origin. For ehealth literacy, the results suggest that challenges related more to digital abilities than motivation, trust and access to technology. The mean ability to engage with digital services was 3.20 (SD 0.44) for women of Danish origin. Non-Western descendants (-0.14, 95% CI -0.31 to 0.02), non-Western (-0.20, 95% CI -0.34 to -0.06) and Western (-0.22, 95% CI -0.39 to -0.06) immigrants had lower adjusted means of this outcome. No differences in motivation to engage with digital services were found for descendants (-0.00, 95% CI -0.17 to 0.17), non-Western (0.03, 95% CI -0.11 to 0.18) or Western (-0.06, 95% CI -0.23 to 0.10) immigrants compared with the mean of the reference (2.85, SD 0.45). Lower ability to engage with healthcare providers was found for non-Western born immigrants (-0.15, CI 95% -0.30 to -0.01) compared with the mean of women with Danish origin (4.15, SD 0.47)., Conclusion: Generally, descendant and immigrant women had lower levels of ehealth literacy and health literacy than women of Danish origin. These differences are potentially antecedents of adverse birth outcomes and could inform structural efforts to mitigate health inequalities., Competing Interests: Competing interests: None declared., (© Author(s) (or their employer(s)) 2020. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.)

Aims/hypothesis: We assessed whether the risk of developing type 2 diabetes and the age of onset varied with the age at diabetes diagnosis of affected family members., Methods: We performed a national register-based open cohort study of individuals living in Denmark between 1995 and 2012. The population under study consisted of all individuals aged 30 years or older without diagnosed diabetes at the start date of the cohort (1 January 1995) and who had information about their parents' identity. Individuals who turned 30 years of age during the observation period and had available parental identity information were also added to the cohort from that date (open cohort design). These criteria restricted the study population mostly to people born between 1960 and 1982. Multivariable Poisson regression models adjusted for current age and highest educational attainment were used to estimate incidence rate ratios (IRRs) of type 2 diabetes., Results: We followed 2,000,552 individuals for a median of 14 years (24,034,059 person-years) and observed 76,633 new cases of type 2 diabetes. Compared with individuals of the same age and sex who did not have a parent or full sibling with diabetes, the highest risk of developing type 2 diabetes was observed in individuals with family members diagnosed at an early age. The IRR was progressively lower with a higher age at diabetes diagnosis in family members: 3.9 vs 1.4 for those with a parental age at diagnosis of 50 or 80 years, respectively; and 3.3 vs 2.0 for those with a full sibling's age at diagnosis of 30 or 60 years, respectively., Conclusions/interpretation: People with a family member diagnosed with diabetes at an earlier age are more likely to develop diabetes and also to develop it at an earlier age than those with a family member diagnosed in later life. This finding highlights the importance of expanding our understanding of the interplay between genetic diabetes determinants and the social, behavioural and environmental diabetes determinants that track in families across generations. Accurate registration of age at diagnosis should form an integral part of recording a diabetes family history, as it provides easily obtainable and highly relevant detail that may improve identification of individuals at increased risk of younger onset of type 2 diabetes. In particular, these individuals may benefit from closer risk factor assessment and follow-up, as well as prevention strategies that may involve the family.

Objectives: Studies suggest that exercise affects the composition and function of the human gut microbiota, yet this has not been investigated in a randomized controlled trial. The primary aim of this study was to assess if exercise alters the diversity, composition and functional potential of the gut microbiota in free-living humans. A secondary aim was to test whether alpha diversity was associated with phenotypical outcomes., Methods: Eighty eight participants with overweight or obesity completed a 6-month randomized controlled trial with 4 arms; habitual living (CON), active commuting by bike (BIKE) and leisure-time exercise of moderate (MOD) or vigorous intensity (VIG). Faecal samples for 16 s rRNA gene amplicon sequencing were collected prior to randomization and again after 3 and 6 months, with simultaneous registration of phenotypical outcomes and diet., Results: Shannon's diversity index increased by 5% in VIG (CI95 1-9%, P = 0.012) at 3 months compared with CON. No associations were observed between alpha diversity and phenotypical outcomes. Beta diversity changed in all exercise groups compared with CON, particularly the participants in VIG showed decreased heterogeneity. No genera changed significantly. The inferred functional potential of the microbiota in the exercise groups was increased, primarily at 3 months and in MOD., Conclusion: Structured exercise induced subtle changes to the human gut microbiota. Cardiorespiratory fitness and fat mass were not associated with alpha diversity.

Aim: To examine whether adding the Community Reinforcement Approach for Seniors (CRA-S) to Motivational Enhancement Therapy (MET) increases the probability of treatment success in people aged ≥ 60 years with alcohol use disorder (AUD)., Design: A single blind multi-centre multi-national randomized (1 : 1) controlled trial., Setting: Out-patient settings (municipal alcohol treatment clinics in Denmark, specialized addiction care facilities in Germany and a primary care clinic in the United States)., Participants: Between January 2014 and May 2016, 693 patients aged 60+ years and fulfilling DSM-5 criteria for AUD participated in comparing MET (n = 351) and MET + CRA-S (n = 342)., Intervention and Comparator: MET (comparator) included four manualized sessions aimed at increasing motivation to change and establishing a change plan. CRA-S (intervention) consisted of up to eight further optional, manualized sessions aimed at helping patients to implement their change plan. CRA-S included a specially designed module on coping with age and age-related problems., Measurements: The primary outcome was either total alcohol abstinence or an expected blood alcohol concentration of ≤ 0.05% during the 30 days preceding the 26 weeks follow-up (defined as success) or blood alcohol concentration of > 0.05% during the follow-up period (defined as failure). This was assessed by self-report using the Form 90 instrument. The main analysis involved complete cases., Findings: The follow-up rate at 26 weeks was 76.2% (76.9% in the MET group and 76.0% in the MET + CRA-S group). The success rate in the MET group was 48.9% [95% confidence interval (CI) = 42.9-54.9%] versus 52.3% (95% CI = 46.2-58.3%) in the MET + CRA-S group. The odds of success in the two conditions did not differ (odds ratio = 1.22. 95% CI = 0.86-1.75, P = 0.26, Bayes factor = 0.10). Sensitivity analyses involving alternative approaches to missing values did not change the results., Conclusions: In older adults with an alcohol use disorder diagnosis, adding the 'community reinforcement approach for seniors' intervention to brief out-patient motivational enhancement therapy treatment did not improve drinking outcome., (© 2019 Society for the Study of Addiction.)

The comparison of alternative rankings of a set of items is a general and common task in applied statistics. Predictor variables are ranked according to magnitude of association with an outcome, prediction models rank subjects according to the personalized risk of an event, and genetic studies rank genes according to their difference in gene expression levels. We propose a sequential rank agreement measure to quantify the rank agreement among two or more ordered lists. This measure has an intuitive interpretation, it can be applied to any number of lists even if some are partially incomplete, and it provides information about the agreement along the lists. The sequential rank agreement can be evaluated analytically or be compared graphically to a permutation based reference set in order to identify changes in the list agreements. The usefulness of this measure is illustrated using gene rankings, and using data from two Danish ovarian cancer studies where we assess the within and between agreement of different statistical classification methods., (© The Author 2018. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)

Competing Interests: Competing interests: We have read and understood BMJ policy on declaration of interests and have no relevant interests to declare.