Glycated haemoglobin (HbA1c ), diabetes and neuropsychological performance in community-dwelling older adults

Identifying comorbidity patterns of mental health disorders in community-dwelling older adults: a cluster analysis

As global life expectancy increases, understanding mental health patterns and their associated risk factors in older adults becomes increasingly critical. Using data from the cross-sectional Trinity Ulster Department of Agriculture study (TUDA, 2008-2012; n = 5186 ; mean age 74.0 years) and a subset of participants followed-up longitudinally (TUDA 5+, 2014-2018; n = 953 ), we perform a multi-view co-clustering analysis to identify distinct mental health profiles and their relationships with potential risk factors. The TUDA multi-view dataset consists of five views: (1) mental health, measured with Center for Epidemiologic Studies Depression Scale [CES-D] and Hospital Anxiety and Depression Scale [HADS], (2) cognitive and neuropsychological function, (3) illness diagnoses and medical prescription history, (4) lifestyle and nutritional attainment, and (5) physical well-being. That is, each participant is described by five distinct sets of features. The mental health view serves as the target feature set, while the other four views are analyzed as potential contributors to mental health risks. Under the multi-view co-clustering framework, for each view data, the participants (rows) are partitioned into different row-clusters, and the features (columns) are partitioned into different column-clusters. Each row-cluster is most effectively explained by the features in one or two column-clusters. Notably, the row-clusterings across views are dependent. By analyzing the associations between row clusters in the mental health view and those in each of the other four views, we can identify which risk factors co-occur and contribute to an increased risk of poor mental health. We identify five distinct row-clusters in the mental-health view data, characterized by varying levels of depression and anxiety: Group 1, mild depressive symptoms and no symptoms of anxiety; Group 2, acute depression and anxiety; Group 3, less severe but persistent depression and anxiety symptoms; Group 4, symptoms of anxiety with no depressive symptoms; and Group 5, no symptoms of either depression or anxiety. Cross-view association analysis revealed the following key insights: Participants in Group 3 exhibit lower neuropsychological function, are older, more likely to live alone, come from more deprived regions, and have reduced physical independence. Contrasting Group 3, participants in Group 2 show better neuropsychological function, greater physical independence, and higher socioeconomic status. Participants in Group 5 report fewer medical diagnoses and prescriptions, more affluent backgrounds, less solitary living, and stronger physical independence. A significant portion of this group aligns with cognitive health row-clusters 1 and 3, suggesting a strong link between cognitive and mental health in older age. Participants with only depressive (Group 1) or anxiety symptoms (Group 4) exhibit notable differences. Those with anxiety symptoms are associated with healthier clusters across other views. The co-clustering methodology also categorizes the questions in the CES-D and HADS scales into meaningful clusters, providing valuable insights into the underlying dimensions of mental health assessment. In the CES-D scale, the questions are divided into four clusters: those related to loneliness and energy, those addressing feelings of insecurity, worthlessness, and fear, those concerning concentration and effort, and those focused on sleep disturbances. Similarly, the HADS questions are grouped into clusters that reflect themes such as a strong sense of impending doom, nervousness or unease, and feelings of tension or restlessness. By organizing the questions from both scales into these smaller groups, the methodology highlights distinct symptom patterns and their varying severity among participants. This approach could be leveraged to develop abridged versions of the assessment scales, enabling faster and more efficient triage in clinical practice.

Discrete Relationships between Spatiotemporal Gait Characteristics and Domain-Specific Neuropsychological Performance in Midlife

Midlife risk factors such as type 2 diabetes mellitus (T2DM) confer a significantly increased risk of cognitive impairment in later life with executive function, memory, and attention domains often affected first. Spatiotemporal gait characteristics are emerging as important integrative biomarkers of neurocognitive function and of later dementia risk. We examined 24 spatiotemporal gait parameters across five domains of gait previously linked to cognitive function on usual-pace, maximal-pace, and cognitive dual-task gait conditions in 102 middle-aged adults with (57.5 ± 8.0 years; 40% female) and without (57.0 ± 8.3 years; 62.1% female) T2DM. Neurocognitive function was measured using a neuropsychological assessment battery. T2DM was associated with significant changes in gait phases and rhythm domains at usual pace, and greater gait variability observed during maximal pace and dual tasks. In the overall cohort, both the gait pace and rhythm domains were associated with memory and executive function during usual pace. At maximal pace, gait pace parameters were associated with reaction time and delayed memory. During the cognitive dual task, associations between gait variability and both delayed memory/executive function were observed. Associations persisted following covariate adjustment and did not differ by T2DM status. Principal components analysis identified a consistent association of slower gait pace (step/stride length) and increased gait variability during maximal-pace walking with poorer memory and executive function performance. These data support the use of spatiotemporal gait as an integrative biomarker of neurocognitive function in otherwise healthy middle-aged individuals and reveal discrete associations between both differing gait tasks and gait domains with domain-specific neuropsychological performance. Employing both maximal-pace and dual-task paradigms may be important in cognitively unimpaired populations with risk factors for later cognitive decline-with the aim of identifying individuals who may benefit from potential preventative interventions.

Low-Grade systemic inflammation is associated with domain-specific cognitive performance and cognitive decline in older adults: Data from the TUDA study

Studies examining the relationships between chronic inflammation, cognitive function and cognitive decline in older adults have yielded conflicting results. In a large cohort of older adults free from established dementia (n = 3270; 73.1 ± 7.9 years; 68.4% female), we evaluated the cross-sectional and longitudinal relationships between serum cytokines (IL-6, IL-10, TNF-α) and both global and domain-specific cognitive performance (Repeatable Battery for Assessment of Neuropsychological Status [RBANS]). Higher IL-6 (OR: 1.33; 1.06, 1.66, p = 0.01), TNF-α (OR: 1.35; 1.09, 1.67, p = 0.01) and IL-6:IL-10 Ratio (OR: 1.43; 1.17, 1.74, p = 0.001) were cross-sectionally associated with impaired global RBANS performance. For specific cognitive domains, greatest effect sizes were observed between higher TNF-α levels and poorer visual-spatial and attention performance. In a subset of participants (n = 725; 69.8 ± 5.5 years; 67.0% female) with repeat assessment performed at a median of 5.4 years, only higher baseline IL-6:IL-10 ratio was associated with impaired incident overall, immediate memory and visual-spatial performance. Associations were stronger in females, but not modified by age or APOE genotype.