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Type 2 diabetes (T2D) is a prevalent disease and has been associated with an increased fracture risk despite normal or even higher areal BMD. The aim of this study was to estimate the association between glucose metabolism status (GMS) and measurements of glycemic control with HRpQCT parameters of bone microarchitecture and strength. Participants of the Maastricht study who underwent an HRpQCT scan at the distal radius and tibia were included. GMS was determined by use of an oral glucose tolerance test and grouped into a normal glucose metabolism (NGM), prediabetes, or T2D. Linear regression models were used, stratified by sex with multiple adjustments. This study incorporated cross-sectional data from 1400 (796 [56.9%] NGM, 228 [16.3%] prediabetes, and 376 [26.9%] T2D) men and 1415 (1014 [71.7%] NGM, 211 [14.9%] prediabetes, and 190 [13.4%] T2D) women. The mean age was 59.8 ± 8.6 and 57.6 ± 9.0 yr for men and women, respectively. After adjustment, T2D was associated with a higher total BMD measured by HRpQCT and cortical thickness, and a smaller total and trabecular area in men and women compared with NGM. In women, T2D was additionally associated with a higher stiffness and failure load at the radius. Results were more pronounced at the distal radius than at the distal tibia. To conclude, these findings suggest that in this cohort of Maastricht study participants, total and trabecular bone area are smaller, but bone microarchitecture, density, and bone strength assessed by HRpQCT are not impaired in individuals with T2D.
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OBJECTIVE: We aimed to estimate the association of age, education, and sex/gender with semantic fluency performance as measured by the standard total number of words as well as novel item-level metrics and to descriptively compare associations across cohorts with different recruitment strategies and sample compositions. METHOD: Cross-sectional data from 2,391 individuals from three cohorts were used: Washington Heights/Inwood Columbia Aging Project, a community-based cohort; Second Manifestations of ARTerial disease-Magnetic Resonance, a clinic-based cohort; and African American Alzheimer's Disease Genetics Study, a volunteer-based cohort. Total number of correct words and six item-level semantic fluency metrics were included as main outcomes: average cluster size, number of cluster switches, lexical/Zipf frequency, age of acquisition, and lexical decision response time. General linear models were run separately in each cohort to model the association between sociodemographic variables and semantic fluency metrics. RESULTS: Across cohorts, older age was associated with a lower total score and fewer cluster switches. Higher level of education was associated with naming more words, performing more cluster switches, and naming words with a longer lexical decision response time, lower frequency of occurrence, or later age of acquisition. Being female compared to male was associated with naming fewer words, smaller cluster sizes, naming words with a longer lexical decision response time, and lower age of acquisition. The effects varied in strength but were in a similar direction across cohorts. CONCLUSIONS: Item-level semantic fluency metrics-similar to the standard total score-are sensitive to the effects of age, education, and sex/gender. The results suggest geographical, cultural, and cross-linguistic generalizability of these sociodemographic effects on semantic fluency performance. (PsycInfo Database Record (c) 2024 APA, all rights reserved).
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BACKGROUND: Socioeconomic inequalities in cognitive impairment may partly act through structural brain damage and reduced connectivity. This study investigated the extent to which the association of early-life socioeconomic position (SEP) with later-life cognitive functioning is mediated by later-life SEP, and whether the associations of SEP with later-life cognitive functioning can be explained by structural brain damage and connectivity. METHODS: We used cross-sectional data from the Dutch population-based Maastricht Study (n = 4,839; mean age 59.2 ± 8.7 years, 49.8% women). Early-life SEP was assessed by self-reported poverty during childhood and parental education. Later-life SEP included education, occupation, and current household income. Participants underwent cognitive testing and 3-T magnetic resonance imaging to measure volumes of white matter hyperintensities, grey matter, white matter, cerebrospinal fluid, and structural connectivity. Multiple linear regression analyses tested the associations between SEP, markers of structural brain damage and connectivity, and cognitive functioning. Mediation was tested using structural equation modeling. RESULTS: Although there were direct associations between both indicators of SEP and later-life cognitive functioning, a large part of the association between early-life SEP and later-life cognitive functioning was explained by later-life SEP (72.2%). The extent to which structural brain damage or connectivity acted as mediators between SEP and cognitive functioning was small (up to 5.9%). CONCLUSIONS: We observed substantial SEP differences in later-life cognitive functioning. Associations of structural brain damage and connectivity with cognitive functioning were relatively small, and only marginally explained the SEP gradients in cognitive functioning.
Subject(s)
Magnetic Resonance Imaging , Humans , Female , Male , Middle Aged , Cross-Sectional Studies , Netherlands , Aged , Cognition/physiology , Social Class , Brain/diagnostic imaging , Cognitive Dysfunction , Socioeconomic Factors , Brain Injuries/complications , Brain Injuries/psychologyABSTRACT
The role of the social environment can facilitate positive health outcomes through active community engagement, normalization of healthy behaviors, and stress buffering. We aim to examine the associations of neighborhood social cohesion with changes in BMI over time. A total of 7641 participants from The Maastricht Study between the ages of 40 and 75 years were analyzed. Weight and height were measured at baseline, and weight was self-reported annually up to 10 years of follow-up (median = 4.7 years). Perceived social cohesion was obtained by questionnaire. Home addresses for each participant were linked to geographic information system data from the Geoscience and Health Cohort Consortium to create neighborhood exposure variables including area level social cohesion, neighborhood walkability, and food environment within a 1000 m Euclidian buffer. Linear regression analyses were performed with BMI adjusted for socioeconomic variables. A mixed model analysis was carried out to examine changes in BMI. Living in the highest quartile area of individually perceived social cohesion was associated with lower BMI (Q4 B: -.53; 95% CI = -.79, -.28) compared to the lowest quartile. Similar findings were discovered using the area level measure (Q4 B: -.97; 95% CI = -1.29, -.65). There was no longitudinal association between social cohesion and BMI. Neighborhood social cohesion was associated with lower BMI classifying it as an obesogenic area characteristic that influences weight, independent of conventional built environment features.
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Life-course exposure to risk and protective factors impacts brain macro- and micro-structure, which in turn affects cognition. The concept of brain-age gap assesses brain health by comparing an individual's neuroimaging-based predicted age with their calendar age. A higher BAG implies accelerated brain ageing and is expected to be associated with worse cognition. In this study, we comprehensively modelled mutual associations between brain health and lifestyle factors, brain age and cognition in a large, middle-aged population. For this study, cognitive test scores, lifestyle and 3T MRI data for n = 4881 participants [mean age (± SD) = 59.2 (±8.6), 50.1% male] were available from The Maastricht Study, a population-based cohort study with extensive phenotyping. Whole-brain volumes (grey matter, cerebrospinal fluid and white matter hyperintensity), cerebral microbleeds and structural white matter connectivity were calculated. Lifestyle factors were combined into an adapted LIfestyle for BRAin health weighted sum score, with higher score indicating greater dementia risk. Cognition was calculated by averaging z-scores across three cognitive domains (memory, information processing speed and executive function and attention). Brain-age gap was calculated by comparing calendar age to predictions from a neuroimaging-based multivariable regression model. Paths between LIfestyle for BRAin health tertiles, brain-age gap and cognitive function were tested using linear regression and structural equation modelling, adjusting for sociodemographic and clinical confounders. The results show that cerebrospinal fluid, grey matter, white matter hyperintensity and cerebral microbleeds best predicted brain-age gap (R 2 = 0.455, root mean squared error = 6.44). In regression analysis, higher LIfestyle for BRAin health scores (greater dementia risk) were associated with higher brain-age gap (standardized regression coefficient ß = 0.126, P < 0.001) and worse cognition (ß = -0.046, P = 0.013), while higher brain-age gap was associated with worse cognition (ß=-0.163, P < 0.001). In mediation analysis, 24.7% of the total difference in cognition between the highest and lowest LIfestyle for BRAin health tertile was mediated by brain-age gap (ß indirect = -0.049, P < 0.001; ß total = -0.198, P < 0.001) and an additional 3.8% was mediated via connectivity (ß indirect = -0.006, P < 0.001; ß total = -0.150, P < 0.001). Findings suggest that associations between health- and lifestyle-based risk/protective factors (LIfestyle for BRAin health) and cognition can be partially explained by structural brain health markers (brain-age gap) and white matter connectivity markers. Lifestyle interventions targeted at high-risk individuals in mid-to-late life may be effective in promoting and preserving cognitive function in the general public.
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BACKGROUND: Establishing collaborations between cohort studies has been fundamental for progress in health research. However, such collaborations are hampered by heterogeneous data representations across cohorts and legal constraints to data sharing. The first arises from a lack of consensus in standards of data collection and representation across cohort studies and is usually tackled by applying data harmonization processes. The second is increasingly important due to raised awareness for privacy protection and stricter regulations, such as the GDPR. Federated learning has emerged as a privacy-preserving alternative to transferring data between institutions through analyzing data in a decentralized manner. METHODS: In this study, we set up a federated learning infrastructure for a consortium of nine Dutch cohorts with appropriate data available to the etiology of dementia, including an extract, transform, and load (ETL) pipeline for data harmonization. Additionally, we assessed the challenges of transforming and standardizing cohort data using the Observational Medical Outcomes Partnership (OMOP) common data model (CDM) and evaluated our tool in one of the cohorts employing federated algorithms. RESULTS: We successfully applied our ETL tool and observed a complete coverage of the cohorts' data by the OMOP CDM. The OMOP CDM facilitated the data representation and standardization, but we identified limitations for cohort-specific data fields and in the scope of the vocabularies available. Specific challenges arise in a multi-cohort federated collaboration due to technical constraints in local environments, data heterogeneity, and lack of direct access to the data. CONCLUSION: In this article, we describe the solutions to these challenges and limitations encountered in our study. Our study shows the potential of federated learning as a privacy-preserving solution for multi-cohort studies that enhance reproducibility and reuse of both data and analyses.
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Dementia , Humans , Netherlands , Cohort Studies , Algorithms , Information Dissemination/methods , Biomedical ResearchABSTRACT
INTRO: We aim to investigate the relationship between social cohesion and sedentary behavior (SB), total physical activity (PA), moderate-to-vigorous PA (MVPA), and dietary quality. Additionally, we assess whether these associations are independent of neighborhood walkability and the food environment. METHODS: A total of 7641 participants from The Maastricht Study in the Netherlands between the ages of 40 and 75 years were analyzed. Neighborhood social cohesion was obtained by participant questionnaire completed at baseline and measured by the Dutch Livability meter. Home addresses were linked to geographic information system (GIS) data from the Geoscience and Health Cohort Consortium (GECCO) to create neighborhood exposures of walkability and food environment. A thigh worn accelerometer collected data to measure sedentary time, total daily PA, and MVPA. Dietary quality was measured with a food frequency questionnaire. Multivariate linear regression analyses were adjusted for age, sex, socioeconomic position, neighborhood walkability, and food environment. RESULTS: Those living in the highest quartile area of perceived social cohesion had statistically significant lower levels of SB (Q4 B: -13.04; 95% CI = -20.23, -5.85), higher total PA (Q4 B: 4.39; 95% CI = 1.69, 7.10), and higher MVPA (Q4 B: 2.57; 95% CI = 0.83, 4.31) and better diet quality (Q4 B: 1.12; 95% CI = 0.24, 2.01) compared to the lowest quartile independent of walkability and food environment. Similar results were found using the Livability meter. CONCLUSION: We discovered neighborhood social cohesion as an important obesogenic determinant that should be considered in policymaking to encourage higher levels of PA and higher diet quality.
Subject(s)
Diet , Exercise , Residence Characteristics , Sedentary Behavior , Humans , Female , Male , Netherlands , Middle Aged , Residence Characteristics/statistics & numerical data , Adult , Surveys and Questionnaires , Aged , Walking/statistics & numerical data , AccelerometryABSTRACT
BACKGROUND: Cerebral microvascular dysfunction may contribute to depression via disruption of brain structures involved in mood regulation, but evidence is limited. We investigated the association of retinal microvascular function, a proxy for microvascular function in the brain, with incidence and trajectories of clinically relevant depressive symptoms. METHODS: Longitudinal data are from The Maastricht Study of 5952 participants (59.9 ± 8.5 years/49.7% women) without clinically relevant depressive symptoms at baseline (2010-2017). Central retinal arteriolar equivalent and central retinal venular equivalent (CRAE and CRVE) and a composite score of flicker light-induced retinal arteriolar and venular dilation were assessed at baseline. We assessed incidence and trajectories of clinically relevant depressive symptoms (9-item Patient Health Questionnaire score ⩾10). Trajectories included continuously low prevalence (low, n = 5225 [87.8%]); early increasing, then chronic high prevalence (early-chronic, n = 157 [2.6%]); low, then increasing prevalence (late-increasing, n = 247 [4.2%]); and remitting prevalence (remitting, n = 323 [5.4%]). RESULTS: After a median follow-up of 7.0 years (range 1.0-11.0), 806 (13.5%) individuals had incident clinically relevant depressive symptoms. After full adjustment, a larger CRAE and CRVE were each associated with a lower risk of clinically relevant depressive symptoms (hazard ratios [HRs] per standard deviation [s.d.]: 0.89 [95% confidence interval (CI) 0.83-0.96] and 0.93 [0.86-0.99], respectively), while a lower flicker light-induced retinal dilation was associated with a higher risk of clinically relevant depressive symptoms (HR per s.d.: 1.10 [1.01-1.20]). Compared to the low trajectory, a larger CRAE was associated with lower odds of belonging to the early-chronic trajectory (OR: 0.83 [0.69-0.99]) and a lower flicker light-induced retinal dilation was associated with higher odds of belonging to the remitting trajectory (OR: 1.23 [1.07-1.43]). CONCLUSIONS: These findings support the hypothesis that cerebral microvascular dysfunction contributes to the development of depressive symptoms.
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BACKGROUND: Microvascular dysfunction is involved in the development of various cerebral disorders. It may contribute to these disorders by disrupting white matter tracts and altering brain connectivity, but evidence is scarce. We investigated the association between multiple biomarkers of microvascular function and whole-brain white matter connectivity. METHODS AND RESULTS: Cross-sectional data from The Maastricht Study, a Dutch population-based cohort (n=4326; age, 59.4±8.6 years; 49.7% women). Measures of microvascular function included urinary albumin excretion, central retinal arteriolar and venular calibers, composite scores of flicker light-induced retinal arteriolar and venular dilation, and plasma biomarkers of endothelial dysfunction (intercellular adhesion molecule-1, vascular cell adhesion molecule-1, E-selectin, and von Willebrand factor). White matter connectivity was calculated from 3T diffusion magnetic resonance imaging to quantify the number (average node degree) and organization (characteristic path length, global efficiency, clustering coefficient, and local efficiency) of white matter connections. A higher plasma biomarkers of endothelial dysfunction composite score was associated with a longer characteristic path length (ß per SD, 0.066 [95% CI, 0.017-0.114]) after adjustment for sociodemographic, lifestyle, and cardiovascular factors but not with any of the other white matter connectivity measures. After multiple comparison correction, this association was nonsignificant. None of the other microvascular function measures were associated with any of the connectivity measures. CONCLUSIONS: These findings suggest that microvascular dysfunction as measured by indirect markers is not associated with whole-brain white matter connectivity.
Subject(s)
White Matter , Humans , Female , Middle Aged , Aged , Male , White Matter/pathology , Cross-Sectional Studies , Brain/diagnostic imaging , Brain/pathology , Diffusion Magnetic Resonance Imaging , BiomarkersABSTRACT
BACKGROUND: Type 2 diabetes mellitus (T2DM) is a common chronic disease that disproportionally affects disadvantaged groups. People with a low socioeconomic position (SEP) have increased risk of T2DM and people with a low SEP and T2DM have higher HbA1c-levels compared to people with T2DM and high SEP. The aim of this study is to analyze longitudinal socioeconomic differences in health-related functioning in people with T2DM. METHODS: Longitudinal data from 1,537 participants of The Maastricht Study with T2DM were used (32.6% female, mean (SD) age 62.9 (7.7) years). SEP was determined by baseline measures of education, occupation and income. Health-related functioning (physical, mental and social) was measured with the Short-Form Health Survey and the Impact on Participation and Autonomy survey (all scored from 0 to 100). Associations of SEP and health-related functioning were studied annually over a 10-year period (median (IQR) 7.0 (5.0) years, baseline 2010-2018) using linear mixed methods adjusting for demographics, HbA1c-levels and lifestyle factors. RESULTS: Participants with a low SEP had significantly worse health-related functioning compared to those with a high SEP. For example, participants with low income had lower scores for physical (-4.49[CI -5.77;-3.21]), mental (-2.61[-3.78,-1.44]) and social functioning (-9.76[-12.30;-7.23]) compared to participants with high income on a scale from 0 to 100. In addition, participants with a low education significantly declined more over time in mental (score for interaction education with time - 0.23[-0.37;-0.09]) and social functioning (-0.44[-0.77;-0.11]) compared to participants with high education. Participants with low and intermediate incomes significantly declined more over time in physical functioning (-0.17 [-0.34, -0.01 and - 0.18 [-0.36, 0.00]) compared to participants with high income. CONCLUSIONS: Among people with T2DM, those with a lower SEP had worse health-related functioning in general than people with a higher SEP. Additionally, people with T2DM and low education developed poorer mental and social functioning over time compared to people with T2DM and high education. People with T2DM and low or intermediate income declined more in physical functioning over time than those with high incomes. In addition to HbA1c-levels and lifestyle patterns, more attention is needed for socioeconomic differences in health-related functioning for people living with T2DM.
Subject(s)
Diabetes Mellitus, Type 2 , Humans , Female , Middle Aged , Male , Diabetes Mellitus, Type 2/epidemiology , Diabetes Mellitus, Type 2/etiology , Income , Educational Status , Occupations , Socioeconomic Factors , Social ClassABSTRACT
In population-based cohort studies, magnetic resonance imaging (MRI) is vital for examining brain structure and function. Advanced MRI techniques, such as diffusion-weighted MRI (dMRI) and resting-state functional MRI (rs-fMRI), provide insights into brain connectivity. However, biases in MRI data acquisition and processing can impact brain connectivity measures and their associations with demographic and clinical variables. This study, conducted with 5110 participants from The Maastricht Study, explored the relationship between brain connectivity and various image quality metrics (e.g., signal-to-noise ratio, head motion, and atlas-template mismatches) that were obtained from dMRI and rs-fMRI scans. Results revealed that in particular increased head motion (R2 up to 0.169, p < 0.001) and reduced signal-to-noise ratio (R2 up to 0.013, p < 0.001) negatively impacted structural and functional brain connectivity, respectively. These image quality metrics significantly affected associations of overall brain connectivity with age (up to -59%), sex (up to -25%), and body mass index (BMI) (up to +14%). Associations with diabetes status, educational level, history of cardiovascular disease, and white matter hyperintensities were generally less affected. This emphasizes the potential confounding effects of image quality in large population-based neuroimaging studies on brain connectivity and underscores the importance of accounting for it.
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INTRODUCTION: Hyperglycemia constitutes a likely pathway linking diabetes and depressive symptoms; lowering glycemic levels may help reduce diabetes-comorbid depressive symptoms. Since randomized controlled trials can help understand temporal associations, we systematically reviewed the evidence regarding the potential association of hemoglobin HbA1c lowering interventions with depressive symptoms. METHODS: PubMed, PsycINFO, CINAHL, and EMBASE databases were searched for randomized controlled trials evaluating HbA1c-lowering interventions and including assessment of depressive symptoms published between 01/2000-09/2020. Study quality was evaluated using the Cochrane Risk of Bias tool. PROSPERO registration: CRD42020215541. RESULTS: We retrieved 1,642 studies of which twelve met our inclusion criteria. Nine studies had high and three unclear risks of bias. Baseline depressive symptom scores suggest elevated depressive symptoms in five studies. Baseline HbA1c was <8.0% (<64 mmol/mol) in two, 8.0-9.0% (64-75 mmol/mol) in eight, and ≥10.0% (≥86 mmol/mol) in two studies. Five studies found greater HbA1c reduction in the treatment group; three of these found greater depressive symptom reduction in the treatment group. Of four studies analyzing whether the change in HbA1c was associated with the change in depressive symptoms, none found a significant association. The main limitation of these studies was relatively low levels of depressive symptoms at baseline, limiting the ability to show a lowering in depressive symptoms after HbA1c reduction. CONCLUSIONS: We found insufficient available data to estimate the association between HbA1c reduction and depressive symptom change following glucose-lowering treatment. Our findings point to an important gap in the diabetes treatment literature. Future clinical trials testing interventions to improve glycemic outcomes might consider measuring depressive symptoms as an outcome to enable analyses of this association.
Subject(s)
Diabetes Mellitus , Hyperglycemia , Adult , Humans , Glycated Hemoglobin , Depression/drug therapy , Depression/etiology , Glucose , Hyperglycemia/drug therapyABSTRACT
INTRODUCTION: The retina may provide non-invasive, scalable biomarkers for monitoring cerebral neurodegeneration. METHODS: We used cross-sectional data from The Maastricht study (n = 3436; mean age 59.3 years; 48% men; and 21% with type 2 diabetes [the latter oversampled by design]). We evaluated associations of retinal nerve fiber layer, ganglion cell layer, and inner plexiform layer thicknesses with cognitive performance and magnetic resonance imaging indices (global grey and white matter volume, hippocampal volume, whole brain node degree, global efficiency, clustering coefficient, and local efficiency). RESULTS: After adjustment, lower thicknesses of most inner retinal layers were significantly associated with worse cognitive performance, lower grey and white matter volume, lower hippocampal volume, and worse brain white matter network structure assessed from lower whole brain node degree, lower global efficiency, higher clustering coefficient, and higher local efficiency. DISCUSSION: The retina may provide biomarkers that are informative of cerebral neurodegenerative changes in the pathobiology of dementia.
Subject(s)
Diabetes Mellitus, Type 2 , White Matter , Male , Humans , Middle Aged , Female , White Matter/diagnostic imaging , White Matter/pathology , Cross-Sectional Studies , Retina/diagnostic imaging , Brain/diagnostic imaging , Brain/pathology , Biomarkers , CognitionABSTRACT
BACKGROUND: Late-life depression has been associated with volume changes of the hippocampus. However, little is known about its association with specific hippocampal subfields over time. AIMS: We investigated whether hippocampal subfield volumes were associated with prevalence, course and incidence of depressive symptoms. METHOD: We extracted 12 hippocampal subfield volumes per hemisphere with FreeSurfer v6.0 using T1-weighted and fluid-attenuated inversion recovery 3T magnetic resonance images. Depressive symptoms were assessed at baseline and annually over 7 years of follow-up (9-item Patient Health Questionnaire). We used negative binominal, logistic, and Cox regression analyses, corrected for multiple comparisons, and adjusted for demographic, cardiovascular and lifestyle factors. RESULTS: A total of n = 4174 participants were included (mean age 60.0 years, s.d. = 8.6, 51.8% female). Larger right hippocampal fissure volume was associated with prevalent depressive symptoms (odds ratio (OR) = 1.26, 95% CI 1.08-1.48). Larger bilateral hippocampal fissure (OR = 1.37-1.40, 95% CI 1.14-1.71), larger right molecular layer (OR = 1.51, 95% CI 1.14-2.00) and smaller right cornu ammonis (CA)3 volumes (OR = 0.61, 95% CI 0.48-0.79) were associated with prevalent depressive symptoms with a chronic course. No associations of hippocampal subfield volumes with incident depressive symptoms were found. Yet, lower left hippocampal amygdala transition area (HATA) volume was associated with incident depressive symptoms with chronic course (hazard ratio = 0.70, 95% CI 0.55-0.89). CONCLUSIONS: Differences in hippocampal fissure, molecular layer and CA volumes might co-occur or follow the onset of depressive symptoms, in particular with a chronic course. Smaller HATA was associated with an increased risk of incident (chronic) depression. Our results could capture a biological foundation for the development of chronic depressive symptoms, and stresses the need to discriminate subtypes of depression to unravel its biological underpinnings.
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Depression , Hippocampus , Humans , Female , Middle Aged , Male , Incidence , Prevalence , Hippocampus/pathology , Temporal Lobe , Magnetic Resonance Imaging/methods , Organ SizeABSTRACT
BACKGROUND: High cognitive activity possibly reduces the risk of cognitive decline and dementia. AIMS: To investigate associations between an individual's need to engage in cognitively stimulating activities (need for cognition, NFC) and structural brain damage and cognitive functioning in the Dutch general population with and without existing cognitive impairment. METHOD: Cross-sectional data were used from the population-based cohort of the Maastricht Study. NFC was measured using the Need For Cognition Scale. Cognitive functioning was tested in three domains: verbal memory, information processing speed, and executive functioning and attention. Values 1.5 s.d. below the mean were defined as cognitive impairment. Standardised volumes of white matter hyperintensities (WMH), cerebrospinal fluid (CSF) and presence of cerebral small vessel disease (CSVD) were derived from 3T magnetic resonance imaging. Multiple linear and binary logistic regression analyses were used adjusted for demographic, somatic and lifestyle factors. RESULTS: Participants (n = 4209; mean age 59.06 years, s.d. = 8.58; 50.1% women) with higher NFC scores had higher overall cognition scores (B = 0.21, 95% CI 0.17-0.26, P < 0.001) and lower odds for CSVD (OR = 0.74, 95% CI 0.60-0.91, P = 0.005) and cognitive impairment (OR = 0.60, 95% CI 0.48-0.76, P < 0.001) after adjustment for demographic, somatic and lifestyle factors. The association between NFC score and cognitive functioning was similar for individuals with and without prevalent cognitive impairment. We found no significant association between NFC and WMH or CSF volumes. CONCLUSIONS: A high need to engage in cognitively stimulating activities is associated with better cognitive functioning and less presence of CSVD and cognitive impairment. This suggests that, in middle-aged individuals, motivation to engage in cognitively stimulating activities may be an opportunity to improve brain health.
Subject(s)
Cognitive Dysfunction , Magnetic Resonance Imaging , Humans , Female , Male , Cross-Sectional Studies , Middle Aged , Cognitive Dysfunction/epidemiology , Aged , Netherlands/epidemiology , Cerebral Small Vessel Diseases , Cognition , White Matter/diagnostic imaging , White Matter/pathology , Neuropsychological TestsABSTRACT
The objective of this study was to examine the associations between personality, general and diabetes-specific well-being and self-efficacy, and weight management indicators, among adults with type 2 diabetes. In addition, to examine whether personality provides incremental explanation of variance in weight management indicators. Australian adults with type 2 diabetes (N = 270; 56% women; age: 61±12 years) were recruited via the national diabetes registry. An online survey included measures of: personality (HEXACO-PI-R), weight management indicators (physical activity, healthy diet, body mass index [BMI]), general well-being (WHO-5), general self-efficacy (GSE), diabetes distress (DDS) and diabetes self-efficacy (DMSES). Analyses included bivariate correlations and linear regression, adjusted for demographic, clinical, and psychological variables. All six personality domains showed significant correlation with at least one weight management indicator: physical activity with extraversion (r = .28), conscientiousness (r = .18) and openness (r = .19); healthy diet with honesty-humility (r = .19), extraversion (r = .24), and agreeableness (r = .14); and BMI with emotionality (r = .20) and extraversion (r = -.20). The strongest associations with general and diabetes-specific well-being and self-efficacy were apparent for extraversion, emotionality and conscientiousness (range: r = -.47-.66). Beyond covariates, personality domains explained additional variance for physical activity (Adjusted R2 = .31, R2 difference = .03, p = .03; openness: ß = .16, p = .02, emotionality: ß = .15, p = .04) and healthy diet (Adjusted R2 = .19, R2 difference = .03, p = .02; honesty-humility: ß = .20, p = .002, extraversion: ß = .19, p = .04) but not BMI. This study shows that personality is associated with weight management indicators and psychological factors among adults with type 2 diabetes. Further research is needed, including objective measurement of weight management indictors, to examine how personality influences the experience of type 2 diabetes.
Subject(s)
Diabetes Mellitus, Type 2 , Humans , Adult , Female , Middle Aged , Aged , Male , Cross-Sectional Studies , Diabetes Mellitus, Type 2/therapy , Self Efficacy , Australia , Personality , Surveys and QuestionnairesABSTRACT
Introduction: There is an urgent need for biomarkers identifying individuals at risk of early-stage cognitive impairment. Using cross-sectional data from The Maastricht Study, this study included 197 individuals with mild cognitive impairment (MCI) and 200 cognitively unimpaired individuals aged 40 to 75, matched by age, sex, and educational level. Methods: We assessed the association of plasma sphingolipid and ceramide transfer protein (CERT) levels with MCI and adjusted for potentially confounding risk factors. Furthermore, the relationship of plasma sphingolipids and CERTs with magnetic resonance imaging brain volumes was assessed and age- and sex-stratified analyses were performed. Results: Associations of plasma ceramide species C18:0 and C24:1 and combined plasma ceramide chain lengths (ceramide risk score) with MCI were moderated by sex, but not by age, and higher levels were associated with MCI in men. No associations were found among women. In addition, higher levels of ceramide C20:0, C22:0, and C24:1, but not the ceramide risk score, were associated with larger volume of the hippocampus after controlling for covariates, independent of MCI. Although higher plasma ceramide C18:0 was related to higher plasma CERT levels, no association of CERT levels was found with MCI or brain volumes. Discussion: Our results warrant further analysis of plasma ceramides as potential markers for MCI in middle-aged men. In contrast to previous studies, no associations of plasma sphingolipids with MCI or brain volumes were found in women, independent of age. These results highlight the importance of accounting for sex- and age-related factors when examining sphingolipid and CERT metabolism related to cognitive function.
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OBJECTIVES: This study examined the cross-sectional association between sleep duration, prediabetes, and type 2 diabetes, and its independence from the traditional lifestyle risk factors diet, physical activity, smoking behavior, and alcohol consumption. METHODS: Cross-sectional data from 5561 people aged 40-75 years recruited into The Maastricht Study between 2010 and 2018 were used (1:1 female:male and mean age: 60.1 years [standard deviation: 8.6]). Sleep duration was operationalized as in-bed time, algorithmically derived from activPAL3 accelerometer data (median 7 nights, IQR 1). Glucose metabolism status was determined with an oral glucose tolerance test. Multinomial logistic regression was used to assess the association of sleep duration as restricted cubic spline with prediabetes and type 2 diabetes. We adjusted for sex, age, educational level, the use of sleep medication or antidepressants, and the following lifestyle risk factors: diet quality, physical activity, smoking behavior, and alcohol consumption. RESULTS: A U-shaped association between sleep duration and type 2 diabetes was found. Compared to those with a sleep duration of 8 hours, participants with a sleep duration of 5 and 12 hours had higher odds of type 2 diabetes (OR: 2.9 [95% CI 1.9 to 4.4] and OR 3.2 [2.0 to 5.2], respectively). This association remained after further adjustment for the lifestyle risk factors (OR: 2.6 [1.7 to 4.1] and OR 1.8 [1.1 to 3.1]). No such association was observed between sleep duration and prediabetes. CONCLUSIONS: Both short and long sleep durations are associated positively and independently of lifestyle and cardiovascular risk factors with type 2 diabetes, but not with prediabetes.
ABSTRACT
AIMS/HYPOTHESIS: To assess the associations between glucose metabolism status and a range of continuous measures of glycaemia with corneal nerve fibre measures, as assessed using corneal confocal microscopy. METHODS: We used population-based observational cross-sectional data from the Maastricht Study of N=3471 participants (mean age 59.4 years, 48.4% men, 14.7% with prediabetes, 21.0% with type 2 diabetes) to study the associations, after adjustment for demographic, cardiovascular risk and lifestyle factors, between glucose metabolism status (prediabetes and type 2 diabetes vs normal glucose metabolism) plus measures of glycaemia (fasting plasma glucose, 2 h post-load glucose, HbA1c, skin autofluorescence [SAF] and duration of diabetes) and composite Z-scores of corneal nerve fibre measures or individual corneal nerve fibre measures (corneal nerve bifurcation density, corneal nerve density, corneal nerve length and fractal dimension). We used linear regression analysis, and, for glucose metabolism status, performed a linear trend analysis. RESULTS: After full adjustment, a more adverse glucose metabolism status was associated with a lower composite Z-score for corneal nerve fibre measures (ß coefficients [95% CI], prediabetes vs normal glucose metabolism -0.08 [-0.17, 0.03], type 2 diabetes vs normal glucose metabolism -0.14 [-0.25, -0.04]; linear trend analysis showed a p value of 0.001), and higher levels of measures of glycaemia (fasting plasma glucose, 2 h post-load glucose, HbA1c, SAF and duration of diabetes) were all significantly associated with a lower composite Z-score for corneal nerve fibre measures (per SD: -0.09 [-0.13, -0.05], -0.07 [-0.11, -0.03], -0.08 [-0.11, -0.04], -0.05 [-0.08, -0.01], -0.09 [-0.17, -0.001], respectively). In general, directionally similar associations were observed for individual corneal nerve fibre measures. CONCLUSIONS/INTERPRETATION: To our knowledge, this is the first population-based study to show that a more adverse glucose metabolism status and higher levels of glycaemic measures were all linearly associated with corneal neurodegeneration after adjustment for an extensive set of potential confounders. Our results indicate that glycaemia-associated corneal neurodegeneration is a continuous process that starts before the onset of type 2 diabetes. Further research is needed to investigate whether early reduction of hyperglycaemia can prevent corneal neurodegeneration.