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See detailThe evolution and social determinants of mental health during the first wave of the COVID-19 outbreak in Luxembourg
Ribeiro, Fabiana UL; Schröder, Valerie UL; Krüger, Rejko UL et al

in Psychiatry Research (2021), 303

Studies have been showing a negative impact of pandemic control measures on mental health. However, few studies assessed these effects longitudinally during the peak of the first wave of the COVID-19 ... [more ▼]

Studies have been showing a negative impact of pandemic control measures on mental health. However, few studies assessed these effects longitudinally during the peak of the first wave of the COVID-19 pandemic. The goals of this study were to explore whether differential effects of COVID-19 restrictions on mental health could be observed by sex and age in a Luxembourgish nationally representative sample during the initial outbreak of COVID-19. Furthermore, we aimed to assess whether there are differences in risk and protective factors longitudinally at two assessment times. A total of 1,756 respondents aged 18 years and older (50.74% women) reported sociodemographic and socio-economic characteristics, depression, anxiety, stress, and loneliness. Women and younger respondents reported higher rates of severe depression and anxiety symptoms, suggesting higher vulnerability to the pandemic control measures. This study contributes to the investigation of mental health consequences of the pandemic and the pandemic control measures, particularly related to shifts in care task responsibilities, gender and socio-economic inequalities, as well as younger groups' uncertainty about the future. [less ▲]

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See detailCode reviewing as a practice in research groups
Leist, Anja UL

Presentation (2021, July)

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See detailInvestigating the associations of trajectories of depressive symptoms and self-perceived health and incident dementia : an unsupervised machine learning approach.
Klee, Matthias UL; Leist, Anja UL

Poster (2021, July)

Background: Risk factors for dementia show inter-individually varying trajectories over the lifespan. However, risk factors have been mainly investigated with one time-point assessments. New research ... [more ▼]

Background: Risk factors for dementia show inter-individually varying trajectories over the lifespan. However, risk factors have been mainly investigated with one time-point assessments. New research suggests that certain risk factor trajectories are associated with increased risk of adverse cognitive outcomes (Demnitz et al., 2020 [https://doi.org/10.1101/2020.05.20.20106963]; Singh-Manoux et al., 2018 [https://doi.org/10.1016/j.jalz.2017.06.2637]). However, it remains unclear how sequential and simultaneous changes of risk factors alter the individual risk for developing dementia. Testing the joint contribution of trajectories of depressive symptoms and self-perceived health on incidence of dementia, we hypothesized that consistently poor as well as deteriorating trajectories increase the risk for incident dementia, and explored possible interactions of the trajectories. Method: A total of 5,326 respondents to the SHARE survey, mean age 73.9 years, and 6 complete follow-ups spanning ~13 years, answered the EURO-D depression scale, self-perceived health (SPH) (t1-t5), and self-reported dementia diagnosis at last follow-up (t6). To investigate the predictive ability of distinct longitudinal trajectories, we applied unsupervised statistical learning methods (K-means cluster modelling). Clusters indicated distinct risk factor trajectories, which were used as exposures in stepwise logistic regressions to predict incident dementia, controlling for age, gender, education, and country. Result: Cluster analysis revealed five distinct trajectories each for SPH and EURO-D, with varying dementia incidence. In stepwise logistic regressions, respondents with trajectories “consistently poor health” and “consistently high depression” showed elevated risk of dementia (OR = 4.02 [1.39, 14.75] and OR = 2.26 [1.03, 4.95], respectively) compared to the combined baseline risk for “consistently low depression” and “consistently good health”. Interactions were not significant. However, respondents with the combination of “consistently high depression” and “consistently poor health” showed increased risk (N = 246; 6.1% dementia). Conclusion: Applying unsupervised machine learning is helpful to incorporate longitudinal information on depressive symptoms and self-perceived health and model these risk factors longitudinally to test their contribution to explain incidence of dementia. The predictive ability of the trajectories of depressive symptoms and self-perceived health for dementia indicates the potential for improving the identification of people at risk for developing dementia in late life by exploiting trajectory information readily accessible through regular medical check-ups in old age. [less ▲]

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See detailLuxembourg
Leist, Anja UL

in Immergut, E.; Anderson, K.; Devitt, C. (Eds.) et al Health politics in Europe: A handbook (2021)

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See detailSymposium: Contextual and life-course determinants of later-life cognitive functioning and dementia
Leist, Anja UL; Muniz-Terrera, Graciela

Scientific Conference (2021, June)

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See detailInequality of educational opportunity differentially impacts women’s and men’s later-life cognitive performance
Leist, Anja UL; Bar-Haim; Chauvel, Louis UL

Scientific Conference (2021, June)

Find the published paper here: https://doi.org/10.1016/j.ssmph.2021.100837

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See detailExploring the frequency of anxiety and depression symptoms in a Brazilian sample during the COVID-19 outbreak
Ribeiro, Fabiana UL; Santos, Flávia; Anunciação, Luis et al

in International Journal of Environmental Research and Public Health (2021), 18(9),

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See detailReturns to Educational and Occupational Attainment in Cognitive Performance for Middle-Aged South Korean Men and Women
Ford, Katherine Joy UL; Leist, Anja UL

in Gerontology and Geriatric Medicine (2021), 7

Background: Gender differences in late middle-age cognitive performance may be explained by differences in educational or occupational attainment rates, or gender-patterned returns of similar education ... [more ▼]

Background: Gender differences in late middle-age cognitive performance may be explained by differences in educational or occupational attainment rates, or gender-patterned returns of similar education and occupation to cognitive reserve. We tested these competing hypotheses in the historically highly gender unequal context of South Korea. Methods: Data came from the 2006 wave of the Korean Longitudinal Study of Aging. We included adults aged 45–65 years. Using quantile regression decompositions, we decomposed cognitive performance differences across quantiles into differences due to rates of educational and occupational attainment and differences due to divergent returns to those characteristics. Results: Gender-based cognitive performance differences across deciles were driven by differences in rates of educational and occupational attainment, while the returns to these characteristics were similar for both genders. Conclusions: Findings suggest that educational and occupational characteristics contribute to cognitive performance similarly in men and women, but discordant rates of these characteristics contribute to performance gaps. [less ▲]

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See detailPartnership and cognitive aging in Europe: Mediating factors and social stratification
Bertogg, Ariane; Leist, Anja UL

in Journals of Gerontology. Series B, Psychological Sciences and Social Sciences (2021)

Objectives. Living in a partnership has been shown to benefit later life health in general and decrease the risk of cognitive impairment. Few studies have, however, examined whether different types of ... [more ▼]

Objectives. Living in a partnership has been shown to benefit later life health in general and decrease the risk of cognitive impairment. Few studies have, however, examined whether different types of partnership transitions also differ with respect to their impact on cognitive trajectories, and whether financial resources, health behaviors, cognitive stimulation and social integration can explain these differences. Methods. Data came from six waves of the Survey of Health, Ageing and Retirement in Europe, which is a representative panel for the population aged 50 years or older, and was collected between 2004 and 2017 in 20 European countries. Our sample includes 213,023 valid person-year observations from 81,814 persons. Mean age at baseline is 63.86 years, and individuals were observed on average 2.6 times. Cognitive functioning was assessed with measures of immediate and delayed recall on a memory test, and verbal fluency. Fixed-effects regression models were employed to exploit individual-level variation in partnership and simultaneous cognitive changes. Results. Partnership status was stable in most respondents (around 90%). Compared to remaining partnered and after controlling for socio-demographic factors, transition to divorce was associated with a steeper decline in immediate and delayed recall. Exploring possible mechanisms, both financial resources and social integration explained these differences. Additional analyses suggested that effects were mostly driven by individuals with lower education. Discussion. Partnership transitions remain infrequent events in later life, but our findings indicate that they can induce less favorable cognitive trajectories compared to partnered individuals, particularly for those with lower cognitive reserve. [less ▲]

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See detailMachine learning in the social and health sciences
Leist, Anja UL; Klee, Matthias UL; Kim, Jung Hyun UL et al

E-print/Working paper (2021)

The uptake of machine learning (ML) approaches in the social and health sciences has been rather slow, and research using ML for social and health research questions remains fragmented. This may be due to ... [more ▼]

The uptake of machine learning (ML) approaches in the social and health sciences has been rather slow, and research using ML for social and health research questions remains fragmented. This may be due to the separate development of research in the computational/data versus social and health sciences as well as a lack of accessible overviews and adequate training in ML techniques for non data science researchers. This paper provides a meta-mapping of research questions in the social and health sciences to appropriate ML approaches, by incorporating the necessary requirements to statistical analysis in these disciplines. We map the established classification into description, prediction, and causal inference to common research goals, such as estimating prevalence of adverse health or social outcomes, predicting the risk of an event, and identifying risk factors or causes of adverse outcomes. This meta-mapping aims at overcoming disciplinary barriers and starting a fluid dialogue between researchers from the social and health sciences and methodologically trained researchers. Such mapping may also help to fully exploit the benefits of ML while considering domain-specific aspects relevant to the social and health sciences, and hopefully contribute to the acceleration of the uptake of ML applications to advance both basic and applied social and health sciences research. [less ▲]

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See detailInequality of educational opportunity at time of schooling predicts cognitive functioning in later adulthood
Leist, Anja UL; Bar-Haim, Eyal; Chauvel, Louis UL

in SSM - Population Health (2021), 15

Objectives. Our understanding of how societal conditions and educational policies influence cognitive development across the life course is improving. We tested the extent to which inequality of ... [more ▼]

Objectives. Our understanding of how societal conditions and educational policies influence cognitive development across the life course is improving. We tested the extent to which inequality of educational opportunity (IEO), the country- and cohort-specific correlation of parents' and their offspring's length of schooling, offers systematically different opportunities to contribute to cognitive development, which in turn influences cognitive abilities up to older ages. Methods. A total of 46,972 individuals of three cohorts born 1940–63 from 16 European countries and Israel provided up to six cognitive assessments and information on covariates in the SHARE survey 2004–2017. Individual-level data were linked to indicators of IEO at time of schooling, and economic, health, and human development, provided by World Bank, WHO, and the UN. Results. In multilevel (mixed-effects) models with random individual and country-cohort effects and adjusted for a large set of confounders, higher IEO was associated with lower levels of cognitive functioning in men and women. Interaction analyses suggested lower cognitive levels particularly of women who were schooled in higher IEO contexts and had lower educational attainment. Associations with rate of change in cognitive functioning were present only in women, however there was little clinically relevant cognitive decline across the window of observation. Result patterns were mostly consistent after including additional contextual indicators, and in a subsample with childhood information. Discussion. Findings suggest that IEO is able to substantially influence cognitive development with long-lasting impacts. Lower-educated women of the cohorts under investigation may have been particularly vulnerable to high-inequality educational contexts. [less ▲]

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See detailSocioeconomic and behavioural factors associated with access to and use of Personal Health Records
Paccoud, Ivana UL; Baumann, Michèle UL; Le Bihan, Etienne UL et al

in BMC Medical Informatics and Decision Making (2021), 21

Background: Access to and use of digital technology are more common among people of higher socioeconomic status. These differences might be due to lack of interest, not having physical access or having ... [more ▼]

Background: Access to and use of digital technology are more common among people of higher socioeconomic status. These differences might be due to lack of interest, not having physical access or having lower intentions to use this technology. By integrating the digital divide approach and the User Acceptance of Information Technology (UTAUT) model, this study aims to further our understanding of socioeconomic factors and the mechanisms linked to different stages in the use of Personal Health Records (PHR): desire, intentions and physical access to PHR. Methods: A cross-sectional online and in-person survey was undertaken in the areas of Lorraine (France), Luxembourg, Rhineland-Palatinate and Saarland (Germany), and Wallonia (Belgium). Exploratory factor analysis was performed to group items derived from the UTAUT model. We applied linear and logistic regressions controlling for country-level heterogeneity, health and demographic factors. Results: A total of 829 individuals aged over 18 completed the questionnaire. Socioeconomic inequalities were present in the access to and use of PHR. Education and income played a significant role in individuals' desire to access their PHR. Being older than 65 years, and migrant, were negatively associated with desire to access PHR. An income gradient was found in having a physical access to PHR, while for the subgroup of respondents who expressed desire to have access, higher educational level was positively associated with intentions to regularly use PHR. In fully adjusted model testing the contribution of UTAUT-derived factors, individuals who perceived PHRs to be useful and had the necessary digital skills were more inclined to use their PHR regularly. Social influence, support and lack of anxiety in using technology were strong predictors of regular PHR use. Conclusion: The findings highlight the importance of considering all stages in PHR use: desire to access, physical access and intention to regularly use PHRs, while paying special attention to migrants and people with lower socioeconomic backgrounds who may feel financial constraints and are not able to exploit the potential of PHRs. As PHR use is expected to come with health benefits, facilitating access and regular use for those less inclined could reduce health inequalities and advance health equity. [less ▲]

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See detailDetecting the ‘Black Hole’ of age-period excess mortality in 25 countries: Age-period-cohort residual analysis
Chauvel, Louis UL; Leist, Anja UL; Smith, Herbert L.

in Bell, Andrew (Ed.) Age, Period, and Cohort Effects (2021)

In a time of worldwide availability of annual age-specific mortality data, we lack basic tools for detecting and graphing, from a comparative perspective, fine-grained deviations from mortality trends. We ... [more ▼]

In a time of worldwide availability of annual age-specific mortality data, we lack basic tools for detecting and graphing, from a comparative perspective, fine-grained deviations from mortality trends. We provide a new age-period-cohort-based methodology, combining information from age-period (AP) and APC-Detrended (APCD) analyses to detect all-cause mortality increases. Plotting the resulting AP coefficients and APCD residuals in equilateral Lexis diagrams, mortality patterns can easily be distinguished as age, period, or cohort trends and fluctuations. We highlight abnormalities as interactions of age and period (‘Black Holes’). We then investigate the ‘Black Holes’ of mortality of young-adult cohorts in the early 1990s in Spain, other southern European countries, and the U.S., in emphasizing their simultaneously occurring mortality crises. Additional analyses with WHO mortality data and epidemiological evidence from other studies show that these mortality increases likely result from lack of treatment and inadequate public health responses to the beginnings of the HIV/AIDS epidemic. We discuss other possible applications of the new method. [less ▲]

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See detailDementia prevention “for all”: Between enthusiasm and prudence
Leist, Anja UL

Article for general public (2021)

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See detailChanges in Neighborhood-Level Socioeconomic Disadvantage and Older Americans’ Cognitive Functioning
Settels, Jason UL; Leist, Anja UL

in Health and Place (2021)

Background: While associations of neighborhood conditions with cognitive functioning at older ages have been established, few studies have investigated with a dynamic perspective if changing neighborhood ... [more ▼]

Background: While associations of neighborhood conditions with cognitive functioning at older ages have been established, few studies have investigated with a dynamic perspective if changing neighborhood socioeconomic conditions affect older residents’ cognitive declines, and which putative factors mediate this relationship. Method: Using data from waves 2 (2010–2011) and 3 (2015–2016) of the National Social Life, Health, and Aging Project (NSHAP) survey (n = 1837), ordinary least squares regressions and mediation analyses were conducted, adjusting for multiple confounders and testing eight putative mediators. Results: Worsening neighborhood socioeconomic circumstances were associated with cognitive declines. Changes in depressive symptoms, sizes of close social networks, and physical activity substantially mediated this relationship. Discussion: While 18.10% of the total effect occurred through these mechanisms, further pathways may work through contextual- and individual-level variables not assessed in the NSHAP. [less ▲]

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See detailWho is going to pay the price of Covid-19? Reflections about an unequal Brazil
Ribeiro, Fabiana UL; Leist, Anja UL

in International Journal for Equity in Health (2020), 19

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See detailProgramme Démence Prévention (pdp ): A Nation-Wide Programme for Dementia Prevention in Luxembourg
Schröder, Valerie UL; Kaysen, Anne UL; Fritz, Joëlle UL et al

Poster (2020, April)

Objectives: To implement a multi-year nation-wide programme, by the means of a personalised lifestyle intervention, to prevent or to delay cognitive decline that can contribute to development of dementia ... [more ▼]

Objectives: To implement a multi-year nation-wide programme, by the means of a personalised lifestyle intervention, to prevent or to delay cognitive decline that can contribute to development of dementia in Luxembourg. Methods: Participants with mild cognitive impairment, referred to the programme by their treating physician, undergo an extensive cognitive evaluation by a neuropsychologist on relevant neuropsychological domains as well as a structured dementia risk factor assessment. Based on these assessments, individualised lifestyle interventions are offered by diverse national partners involved in the programme, thus filling a gap of not yet reimbursed services in the Luxemburgish healthcare system. After the personalised lifestyle interventions, each participant will undergo a neuropsychological follow-up in order to re-evaluate his/her health status in terms of cognition. Results: We established a participant-centred national network by presenting the programme on many outreach events and efficient stakeholder communication. The network raises the awareness of dementia prevention in the Luxembourgish population, fosters interdisciplinary communication between individual medical and non-medical healthcare professionals and allows for a successful recruitment of the target population. Moreover, we collect information about adherence to the suggested lifestyle changes, as well as the effectiveness of our interventions in reducing risk factors contributing to the onset of dementia. Conclusions: We provide evidence for the feasibility of the implementation of a nation-wide dementia prevention programme including diverse partners offering personalised lifestyle interventions, which are easily transferrable to other countries. Future results from this programme may also help to integrate prevention interventions into the regular healthcare system. [less ▲]

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