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Conflicting results have been reported concerning possible adverse effects on the cognitive function of offspring of mothers with type 1 diabetes (O-mT1D). Previous studies have included offspring of parents from the background population (O-BP), but not offspring of fathers with type 1 diabetes (O-fT1D) as the unexposed reference group. This is a population-based retrospective cohort study from 2010 to 2016. Nationally standardized school test scores (range, 1 to 100) were obtained for public school grades 2, 3, 4, 6, and 8 in O-mT1D and compared with those in O-fT1D and O-BP. Of the 622,073 included children, 2,144 were O-mT1D, and 3,474 were O-fT1D. Multiple linear regression models were used to compare outcomes, including the covariates offspring with type 1 diabetes, parity, number of siblings, offspring sex, smoking during pregnancy, parental age, and socioeconomic factors. Mean test scores were 54.2 (standard deviation, SD 24.8) in O-mT1D, 54.4 (SD 24.8) in O-fT1D, and 56.4 (SD 24.7) in O-BP. In adjusted analyses, the mean differences in test scores were -1.59 (95% CI -2.48 to -0.71, p < 0.001) between O-mT1D and O-BP and -0.78 (95% CI -1.48 to -0.08, p = 0.03) between O-fT1D and O-BP. No significant difference in the adjusted mean test scores was found between O-mT1D and O-fT1D (p = 0.16). The study's limitation was no access to measures of glycemic control during pregnancy. O-mT1D achieved lower test scores than O-BP but similar test scores compared with O-fT1D. Glycemic control during pregnancy is essential to prevent various adverse pregnancy outcomes in women with type 1 diabetes. However, the present study reduces previous concerns regarding adverse effects of in utero hyperglycemia on offspring cognitive function.

Objective: The study examined cross-sectional associations of personality with BMI and obesity among men and women in a large late midlife community sample. Methods: The sample comprised 5,286 Danish individuals aged 49-63 years from the Copenhagen Ageing and Midlife Biobank (CAMB) with complete information on measured BMI, personality assessed by the NEO Five Factor Inventory (NEO FFI), and sociodemographic factors including sex, age and educational length. Analysis of variance and logistic regression models were used to investigate associations between personality and BMI as well as obesity. Personality traits were analyzed separately and combined in the same model. Results: All personality traits except for neuroticism were significantly associated with BMI, with extraversion (p value ranged from <0.001 to 0.012) and agreeableness (p value ranged from 0.001 to 0.002) being the most consistent predictors of BMI among men and women, respectively. Furthermore, extraversion among men (high scores) (p = 0.016) and agreeableness among women (low scores) (p = 0.026) were the only personality traits significantly associated with obesity when adjusting for duration of education. Conclusion: Personality was significantly associated with BMI and to a lesser extent with obesity, and these associations differed between men and women. Also, it was suggested that the interrelations of the five personality traits should be considered in future research of personality and health outcomes.

The prevalence of post-traumatic stress disorder (PTSD) is estimated to be as high as 30% among refugees. The coexistence of prevalent chronic pain is believed to maintain symptoms of PTSD and add complexity to the condition. Despite this, little evidence exists on how to treat PTSD and comorbid conditions best in trauma-affected refugees. The aim of the present study was to investigate if adding either BBAT or mixed physical activity to the treatment as usual (TAU) for trauma-affected refugees with PTSD would increase the treatment effect compared to TAU alone. Randomised controlled trial, 3-armed parallel group superiority study, conducted at Competence Centre for Transcultural Psychiatry, Denmark. Participants were adult trauma-affected refugees with PTSD. Allocation ratio was 1:1:1, stratified for PTSD severity and gender. An open-label design was applied due to the nature of the intervention. Participants were randomised to receive either individual basic body awareness therapy (group B) or individual mixed physical activity (group M) one hour/week for 20 weeks plus TAU, or TAU only (group C). The primary outcome was PTSD severity measured by Harvard Trauma Questionnaire (HTQ). Trial registration: ClinicalTrials.gov, NCT01955538. Of the 338 patients included (C/B/M = 110/114/114), 318 patients were eligible for intention-to-treat analysis (C/B/M = 104/105/109). On the primary outcome, intention-to-treat as well as per-protocol analyses showed small but significant improvement on scores from pre- to post-treatment in all three groups but with no significant difference in improvement between groups. The findings do not provide evidence that either BBAT or mixed physical activity as add-on treatment bring significantly larger improvement on symptoms of PTSD compared to TAU alone for adult, trauma-affected refugees. There is a need for studies on potential subpopulations of trauma-affected refugees who could benefit from physical activity as a part of their treatment.

The extant literature on type 2 diabetes and cognitive decline is based on short cognitive follow-ups and assessments of baseline cognitive ability after diagnosis. The objective was to investigate the influence of type 2 diabetes on cognitive decline over a period of on average 44 years. This cohort study included 5,147 men from the Danish Aging and Cognition cohort consisting of a late mid-life (mean age 64.2 years) follow-up of men with intelligence test scores (IQ) available from statutory conscription board examinations in young adulthood (mean age 20.4 years). Follow-up included re-administration of the conscription board intelligence test and a comprehensive questionnaire. Exposure was self-reported but register-based type 2 diabetes and duration of disease were also calculated. Cognitive decline was defined as both IQ change (baseline-follow-up) and significant IQ decline based on the reliable change index (cut-off: 13.2 IQ-points). Associations were analyzed in linear and logistic regression models. Men having type 2 diabetes had a 1.81 IQ points (95%CI:1.14,2.49) larger decline compared to men without diabetes when adjusting for baseline IQ, years of education, follow-up age, retest interval, depression, and smoking status. Moreover, type 2 diabetes was associated with 1.42 times higher odds of a significant IQ decline and longer duration was associated with a larger, though not statistically significant, decline. The participation rate was 13.4%, and the participants were healthier and more well-educated than non-participants. To account for potential selection bias, inverse probability weights (IPW) were calculated based on baseline characteristics. The analyses applying these weights yielded similar estimates. Type 2 diabetes was associated with modestly greater cognitive decline and higher odds of a statistically significant (>13.2 IQ points) and clinically relevant decline. Finally, the alignment between main and IPW results indicates the findings are robust and likely generalizable.

From 19th to 22nd November 2018, 26 researchers representing nine countries and a variety of academic disciplines met in Snekkersten, Denmark, to reach evidence-based consensus about physical activity and older adults. It was recognised that the term ‘older adults’ represents a highly heterogeneous population. It encompasses those that remain highly active and healthy throughout the life-course with a high intrinsic capacity to the very old and frail with low intrinsic capacity. The consensus is drawn from a wide range of research methodologies within epidemiology, medicine, physiology, neuroscience, psychology and sociology, recognising the strength and limitations of each of the methods. Much of the evidence presented in the statements is based on longitudinal associations from observational and randomised controlled intervention studies, as well as quantitative and qualitative social studies in relatively healthy community-dwelling older adults. Nevertheless, we also considered research with frail older adults and those with age-associated neurodegenerative diseases, such as Alzheimer’s and Parkinson’s disease, and in a few cases molecular and cellular outcome measures from animal studies. The consensus statements distinguish between physical activity and exercise. Physical activity is used as an umbrella term that includes both structured and unstructured forms of leisure, transport, domestic and work-related activities. Physical activity entails body movement that increases energy expenditure relative to rest, and is often characterised in terms of intensity from light, to moderate to vigorous. Exercise is defined as a subset of structured physical activities that are more specifically designed to improve cardiorespiratory fitness, cognitive function, flexibility balance, strength and/or power. This statement presents the consensus on the effects of physical activity on older adults’ fitness, health, cognitive functioning, functional capacity, engagement, motivation, psychological well-being and social inclusion. It also covers the consensus on physical activity implementation strategies. While it is recognised that adverse events can occur during exercise, the risk can be minimised by carefully choosing the type of activity undertaken and by consultation with the individual’s physician when warranted, for example, when the individual is frail, has a number of co-morbidities, or has exercise-related symptoms, such as chest pain, heart arrhythmia or dizziness. The consensus was obtained through an iterative process that began with the presentation of the state-of-the-science in each domain, followed by group and plenary discussions. Ultimately, the participants reached agreement on the 30-item consensus statements.

The potential association between level of education and age-related cognitive decline remains an open question, partly because of a lack of studies including large subsamples with low education and follow-up intervals covering a substantial part of the adult lifespan. To examine cognitive decline assessed by a comprehensive clinical test of intelligence over a 35-year period of follow-up from ages 50 to 85 and to analyze the effect of education on trajectories of cognitive decline, including the effects of selective attrition. A longitudinal cohort study with a 35-year follow-up of community dwelling members of the Glostrup 1914 cohort. The study sample comprised 697 men and women at the 50-year baseline assessment and additional participants recruited at later follow-ups. Verbal, Performance, and Full Scale IQs were assessed using the Wechsler Adult Intelligence Scale at ages 50, 60, 70, 80, and 85. To be able to track cognitive changes between successive WAIS assessments, all IQs were based on the Danish 50-year norms. Information on school education was self-reported. The association between education and cognitive decline over time was examined in growth curve models. Selective attrition was investigated in subsamples of participants who dropped out at early or later follow-ups. The trajectories for Verbal, Performance, and Full Scale IQ showed higher initial cognitive performance, but also revealed steeper decline among participants with a formal school exam compared to participants without a formal exam. Verbal IQ showed the largest difference in level between the two educational groups, whereas the interaction between education and age was stronger for Performance IQ than for Verbal IQ. In spite of the difference in trajectories, higher mean IQ was observed among participants with a formal school exam compared to those without across all ages, including the 85-year follow-up. Further analyses revealed that early dropout was associated with steeper decline, but that this effect was unrelated to education. Comprehensive cognitive assessment over a 35-year period suggests that higher education is associated with steeper decline in IQ, but also higher mean IQ at all follow-ups. These findings are unlikely to reflect regression towards the mean, other characteristics of the employed test battery or associations between educational level and study dropout.

Previous studies have found paternal occupation, childhood intelligence, and educational attainment to be important predictors of socioeconomic status (SES) later in life. However, these factors only explain part of the variance in SES and thus, it is important to identify other predictors of SES and trajectories of influence from early childhood to adulthood. To analyze predictors of SES attainment during the life course from early childhood to midlife with special emphasis on identifying direct and indirect effects on midlife SES of early childhood, late childhood and young adult characteristics. This study uses questionnaire and national registry data, including data on parental social background, intelligence, education, and midlife SES for 6,294 members of the Metropolit 1953 Danish Male Birth Cohort. The study sample included cohort members with information on intelligence at age 12 who were living in Denmark at age 50. Using structural equation modelling, direct and indirect mediated effects on midlife SES were estimated for early childhood, late childhood, and young adult characteristics. Educational attainment, intelligence, parental education, and father's occupational class had the strongest influences on midlife SES. A prediction model only including education and intelligence could only be slightly improved by the inclusion of other predictors, from 53.5% to 54.1% explained variance in midlife SES. Educational attainment was a particularly strong predictor of status attainment. Other early and late childhood factors had relatively weak direct effects, but significant indirect effects. Thus, it was possible to identify trajectories of influence from early childhood to midlife. Young adult education and intelligence were the strongest predictors of midlife SES. Early and late childhood factors influence young adult characteristics, but over the life course the direct effects of early life variables tend to decrease, and the effects on midlife SES become mediated and indirect.

Previous studies have reported an association between circadian disturbances and age-related cognitive impairment. The aim was to study the 24-hour profiles of melatonin and cortisol in relation to cognitive function in middle-aged male subjects. Fifty healthy middle-aged males born in 1953 were recruited from a population-based cohort based on previous cognitive assessments in young adulthood and late midlife. The sample included 24 cognitively high-functioning and 26 cognitively impaired participants. Saliva samples were collected every 4 hours over a 24-hour period and analyzed for cortisol and melatonin levels by immunoassay. All participants exhibited clear circadian rhythms of salivary melatonin and cortisol. Salivary melatonin concentrations had a nocturnal peak at approximately 4 am. The median nocturnal melatonin response at 4 am was significantly lower in the cognitively impaired group than in the high-functioning group (-4.6 pg/mL, 95% CI: -7.84, -1.36, P=0.006). The 24-hour mean melatonin concentration (high-functioning group: 4.80±0.70 pg/mL, vs cognitively impaired group: 4.81±0.76 pg/mL; P>0.05) (or the area under the curve, AUC) was not significantly different between the two groups. Cortisol levels were low during the night, and peaked at approximately 8 am. Median cortisol concentrations were similar at all times, as were the 24-hour mean cortisol concentrations and AUC. To the best of our knowledge, ours is the first study to assess circadian measures (ie, melatonin and cortisol) in healthy middle-aged men with different cognitive trajectories in midlife. We found evidence of altered circadian rhythms with a reduced nocturnal melatonin response at 4 am in men with cognitive impairment. The 24-hour concentration and AUC of melatonin and cortisol were similar in the cognitively high-functioning group and in the cognitively impaired.

Most previous studies of effects of smoking on age-related cognitive decline have compared cognitive decline in current smokers, former smokers, and never smokers rather than investigating the effects of pack-years. The aim of the present study was to analyze the association between smoking and age-related cognitive decline in a sample of men administered the same intelligence test in young adulthood and late midlife, using pack-years between the two assessments as the primary measure of exposure to smoking. In 5052 men, scores on a military intelligence test (BPP, Børge Priens Prøve) were available from young adulthood and a late midlife follow-up assessment including the same intelligence test and a comprehensive questionnaire on socio-demographic factors, lifestyle, and health. Information on smoking was self-reported at follow up for eight age periods, and pack-years were calculated from age 19 based on information on daily smoking and the duration of each age period. The differences in cognitive decline between adult-life smokers and non-smokers and the differences between light, moderate, and heavy smokers defined by pack-years were analyzed in linear regression models. All smoking variables were only weakly associated with cognitive decline. Comparison of adult-life smokers and non-smokers showed less cognitive decline among smokers (1.12 IQ points, p <  0.001). Among smokers, analyses of pack-years suggested a weak dose-response relationship with more decline in heavy smokers than in light smokers (1.33 IQ points, p =  0.001). Independent of pack-years, current smoking was associated with larger cognitive decline than former smoking (1.73 IQ points, p <  0.001). Smoking explained negligible fractions of the variance in cognitive decline, and thus our results did not indicate that smoking is a strong predictor of cognitive decline. The effects of pack-years suggest a relatively weak, possibly cumulative effect of smoking across the adult lifespan. The difference in decline between smokers and non-smokers may reflect participation bias and selective attrition at follow-up while the effects of current smoking may reflect either temporary effects of smoking or individual and life-style characteristics associated with continuation of smoking into late midlife.

Given the high prevalence of trauma-related mental health problems in a growing population of refugees, identifying robust predictors of treatment outcome can optimize treatment strategies and resource allocation. The current study aimed to examine the robustness of predictors from seven previous predictor studies at the Competence Centre for Transcultural Psychiatry (CTP). We studied if predictors from previous studies could be replicated in a sample of 219 refugees with PTSD who participated in a new distinct study conducted at CTP. We included all variables previously found to be significantly related to treatment response, as measured via the Harvard Trauma Questionnaire (HTQ) and the Hamilton Depression Scale (HAM-D). We categorised the variables as sociodemographic factors, CTP predictor index items, and baseline assessment scores. We performed regression analyses with one exposure variable at a time, controlling for baseline assessment scores corresponding to the dependent variable. We also conducted multiple linear regression analyses to examine the variance explained in total by the identified significant predictor variables. The study successfully replicated several predictors of treatment response for PTSD and depression, including a high understanding of therapy concepts, acceptability of psychological treatment, ability to reflect, motivation for active participation and cognitive resources, as well as low baseline pain levels. The findings replicated a U-shaped relationship between age and treatment response for depression, indicating better outcomes for younger participants and those over 60. Multiple regression analyses explained 28% and 39% of the variance in the PTSD (HTQ) and depression (HAM-D) treatment responses, respectively. This study contributes to the understanding of treatment response predictors in trauma-affected refugees by replicating findings from previous research in a new sample. It highlights the importance of modifiable factors, such as psychotherapy readiness, and underscores the necessity for tailored interventions to enhance treatment efficacy. As the global refugee crisis grows, the insights from this research can inform mental health strategies, ultimately improving care for this vulnerable population. Future research should continue to investigate modifiable predictors to further enhance treatment outcomes. ClinicalTrials.gov NCT02761161.