Dispositional optimism and depression risk in older women in the Nurses´ Health Study: a prospective cohort study

Dispositional optimism is a potentially modifiable factor and has been associated with multiple physical health outcomes, but its relationship with depression, especially later in life, remains unclear. In the Nurses´ Health Study (n = 33,483), we examined associations between dispositional optimism and depression risk in women aged 57–85 (mean = 69.9, SD = 6.8), with 4,051 cases of incident depression and 10 years of follow-up (2004–2014). We defined depression as either having a physician/clinician-diagnosed depression, or regularly using antidepressants, or the presence of severe depressive symptoms using validated self-reported scales. Age- and multivariable-adjusted Cox proportional hazards models were used to estimate hazard ratios (HRs) with 95% confidence intervals (95% CIs) across optimism quartiles and for a 1-standard deviation (SD) increment of the optimism score. In sensitivity analyses we explored more restrictive definitions of depression, potential mediators, and moderators. In multivariable-adjusted models, women with greater optimism (top vs. bottom quartile) had a 27% (95%CI = 19–34%) lower risk of depression. Every 1-SD increase in the optimism score was associated with a 15% (95%CI = 12–18%) lower depression risk. When applying a more restrictive definition for clinical depression, the association was considerably attenuated (every 1-SD increase in the optimism score was associated with a 6% (95%CI = 2–10%-) lower depression risk. Stratified analyses by baseline depressive symptoms, age, race, and birth region revealed comparable estimates, while mediators (emotional support, social network size, healthy lifestyle), when combined, explained approximately 10% of the optimism-depression association. As social and behavioral factors only explained a small proportion of the association, future research should investigate other potential pathways, such as coping strategies, that may relate optimism to depression risk.

Protecting against researcher bias in secondary data analysis: challenges and potential solutions

Analysis of secondary data sources (such as cohort studies, survey data, and administrative records) has the potential to provide answers to science and society’s most pressing questions. However, researcher biases can lead to questionable research practices in secondary data analysis, which can distort the evidence base. While pre-registration can help to protect against researcher biases, it presents challenges for secondary data analysis. In this article, we describe these challenges and propose novel solutions and alternative approaches. Proposed solutions include approaches to (1) address bias linked to prior knowledge of the data, (2) enable pre-registration of non-hypothesis-driven research, (3) help ensure that pre-registered analyses will be appropriate for the data, and (4) address difficulties arising from reduced analytic flexibility in pre-registration. For each solution, we provide guidance on implementation for researchers and data guardians. The adoption of these practices can help to protect against researcher bias in secondary data analysis, to improve the robustness of research based on existing data.

Long-term association of pregnancy and maternal brain structure: the Rotterdam Study

The peripartum period is the highest risk interval for the onset or exacerbation of psychiatric illness in women’s lives. Notably, pregnancy and childbirth have been associated with short-term structural and functional changes in the maternal human brain. Yet the long-term effects of pregnancy on maternal brain structure remain unknown. We investigated a large population-based cohort to examine the association between parity and brain structure. In total, 2,835 women (mean age 65.2 years; all free from dementia, stroke, and cortical brain infarcts) from the Rotterdam Study underwent magnetic resonance imaging (1.5 T) between 2005 and 2015. Associations of parity with global and lobar brain tissue volumes, white matter microstructure, and markers of vascular brain disease were examined using regression models. We found that parity was associated with a larger global gray matter volume (β = 0.14, 95% CI = 0.09–0.19), a finding that persisted following adjustment for sociodemographic factors. A non-significant dose-dependent relationship was observed between a higher number of childbirths and larger gray matter volume. The gray matter volume association with parity was globally proportional across lobes. No associations were found regarding white matter volume or integrity, nor with markers of cerebral small vessel disease. The current findings suggest that pregnancy and childbirth are associated with robust long-term changes in brain structure involving a larger global gray matter volume that persists for decades. Future studies are warranted to further investigate the mechanism and physiological relevance of these differences in brain morphology.

The nationwide Finnish anticoagulation in atrial fibrillation (FinACAF): study rationale, design, and patient characteristics

Atrial fibrillation (AF) is a major cause of ischemic stroke and the number of AF patients is increasing. Thus, up-to-date multifaceted data about the characteristics of AF patients, their treatments, and outcomes are urgently needed. The Finnish anticoagulation in atrial fibrillation (FinACAF) study has collected comprehensive data on all Finnish AF patients from 1st January 2004 to 31st December 2018. The aim of this paper is to describe the study rationale, the process of integrating data from the applied resources and to define the study cohort. Using national unique personal identification number, individual patient data is linked from nationwide health care registries (primary, secondary, and tertiary care), drug purchases, education, and socio-economic status as well as places of domicile, incomes, and taxes. Six regional laboratory databases (~ 282,000, 77% of the patients) are also included. The study cohort comprises of a total of 411,000 patients. Since the introduction of the national primary care register in 2012, 9% of all AF patients were identified outside hospital care registers. The prevalence of AF in Finland—4.1% of whole population—is for the first time now established. The FinACAF study allows a unique possibility to investigate the epidemiology and socio-medico-economic impact of AF as well as the cost effectiveness of different AF management strategies in a completely unselected, nationwide population. This article provides the rationale and design of the study together with a summary of the characteristics of the cohort.

Cardiovascular risk factors, living and ageing in Halle: the CARLA study

The CARLA study (Cardiovascular Disease, Living and Ageing in Halle) is a longitudinal population-based cohort study of the general population of the city of Halle (Saale), Germany. The primary aim of the cohort was to investigate risk factors for cardiovascular diseases based on comprehensive cardiological phenotyping of study participants and was extended to study factors associated with healthy ageing. In total, 1779 probands (812 women and 967 men, aged 45–83 years) were examined at baseline (2002–2005), with a first and second follow-up performed 4 and 8 years later. The response proportion at baseline was 64.1% and the reparticipation proportion for the first and second follow-up was 86% and 77% respectively. Sixty-four percent of the study participants were in retirement while 25% were full- or partially-employed and 11% were unemployed at the time of the baseline examination. The currently running third follow-up focuses on the assessment of physical and mental health, with an intensive 4 h examination program, including measurement of cardiovascular, neurocognitive, balance and gait parameters. The data collected in the CARLA Study resulted in answering various research questions in over 80 publications, of which two thirds were pooled analyses with other similar population-based studies. Due to the extensiveness of information on risk factors, subclinical conditions and evident diseases, the biobanking concept for the biosamples, the cohort representativeness of an elderly population, and the high level of quality assurance, the CARLA cohort offers a unique platform for further research on important indicators for healthy ageing.