Umbrella review and Delphi study on modifiable factors for dementia risk reduction

Rosenau, Colin; Köhler, Sebastian; Soons, Lion M.; Anstey, Kaarin J.; Brayne, Carol; Brodaty, Henry; Engedal, Knut; Farina, Francesca R.; Ganguli, Mary; Livingston, Gill; Lyketsos, Constantine G.; Mangialasche, Francesca; Middleton, Laura E.; Rikkert, Marcel G. M. Olde; Peters, Ruth; Sachdev, Perminder S.; Scarmeas, Nikolaos; Salbæk, Geir; van Boxtel, Martin P. J.; Deckers, Kay

doi:10.1002/alz.13577

Cited by 5 publications

(4 citation statements)

References 129 publications

(262 reference statements)

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“…42 Notably, a recent revision suggested the addition of three more factors (hearing impairment, social contact, and sleep) to the LIBRA index, which is currently undergoing validation studies. 43 factor in an index. 45 Social and economic deprivation are drivers of adverse lifestyles for brain health.…”

Section: Discussionmentioning

confidence: 99%

Lifestyle for brain health and cognitive functioning in midlife to early late‐life New Zealanders: Utility of the LIBRA index

Röhr,

Stephens,

Alpass

2024

Int J Geriat Psychiatry

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ObjectivesThere is enormous potential to improve brain health and reduce the risk of cognitive decline and dementia based on modifiable risk factors. The Lifestyle for Brain Health (LIBRA) index was developed to quantify modifiable dementia risk or room for brain health improvement. The objective of the study was to investigate the utility of the LIBRA index in relation to cognitive functioning in a midlife to early late‐life sample of New Zealanders.MethodsA subsample (n = 1001) of the longitudinal New Zealand Health, Work and Retirement (NZHWR) study completed face‐to‐face cognitive assessments using the ‘Kiwi’ Addenbrooke's Cognitive Examination—Revised (ACE‐R) in 2010 and again in 2012, in addition to completing biennial NZHWR surveys on socioeconomic, health and wellbeing aspects. The LIBRA index was calculated incorporating information on 8 out of 12 modifiable health and lifestyle factors for dementia. Unadjusted and adjusted regression models and mixed effects models were used to inspect associations of LIBRA with cognitive functioning, cognitive impairment, and cognitive decline.ResultsThe analytical sample (n = 881 [88.0%], after considering exclusion criteria and missing data) had a mean age of 63.1 (SD = 6.5) years, 53.3% were female, 26.2% were Māori, and 61.7% were highly educated. Higher LIBRA scores (indicating higher modifiable dementia risk) were associated with lower cognitive functioning (B = −0.33, 95% CI = −0.52;−0.15, p < 0.001) and a higher likelihood of cognitive impairment (OR = 1.22, 95% CI = 1.04; 1.42, p = 0.013), but did not predict cognitive decline over 2 years (B = −0.03, 95% CI = −0.22; 0.16, p = 0.766), adjusted for age, age2, gender, education, and ethnicity.ConclusionsThe LIBRA index indicated promising utility for quantifying modifiable dementia risk in midlife and early late‐life New Zealanders. For local use, refinement of the LIBRA index should consider cultural differences in health and lifestyle risk factors, and further investigate its utility with a wider range of modifiable factors over a longer observation period.

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Section: Discussionmentioning

confidence: 99%

Lifestyle for brain health and cognitive functioning in midlife to early late‐life New Zealanders: Utility of the LIBRA index

Röhr,

Stephens,

Alpass

2024

Int J Geriat Psychiatry

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“…29,37 In addition, family history, stroke, psychiatric illness, sleep apnea, and sensory impairments (hearing and vision) were considered. 38 Lifestyle factors included physical activity levels, body mass index (BMI) as a measure of obesity, smoking habits, dietary patterns (including saturated fat intake, adherence to a dementia-preventive diet, and alcohol consumption), cognitive activity, sleep quality, and stress levels. 39 Furthermore, laboratory components, such as C-reactive protein (CRP), cobalamin (vitamin B12), folate, cholesterol, homocysteine, fasting blood sugar (FBS), glycated hemoglobin (HbA1C), and thyroid-stimulating hormone (TSH), were included in the LIBRA framework.…”

Section: Methodsmentioning

confidence: 99%

Multimodal dementia identification using lifestyle and brain lesions, a machine learning approach

Akbarifar,

Maghsoudpour,

Mohammadian

et al. 2024

AIP Advances

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Dementia diagnosis often relies on expensive and invasive neuroimaging techniques that limit access to early screening. This study proposes an innovative approach for facilitating early dementia screening by estimating diffusion tensor imaging (DTI) measures using accessible lifestyle and brain imaging factors. Conventional DTI analysis, though effective, is often hindered by high costs and limited accessibility. To address this challenge, fuzzy subtractive clustering identified 14 influential variables from the Lifestyle for Brain Health and Brain Atrophy and Lesion Index frameworks, encompassing demographics, medical conditions, lifestyle factors, and structural brain markers. A multilayer perceptron (MLP) neural network was developed using these selected variables to predict fractional anisotropy (FA), a DTI metric reflecting white matter integrity and cognitive function. The MLP model achieved promising results, with a mean squared error of 0.000 878 on the test set for FA prediction, demonstrating its potential for accurate DTI estimation without costly neuroimaging techniques. The FA values in the dataset ranged from 0 to 1, with higher values indicating greater white matter integrity. Thus, a mean squared error of 0.000 878 suggests that the model’s predictions were highly accurate compared to the observed FA values. This multifactorial approach aligns with the current understanding of dementia’s complex etiology influenced by various biological, environmental, and lifestyle factors. By integrating readily available data into a predictive model, this method enables widespread, cost-effective screening for early dementia risk assessment. The proposed accessible screening tool could facilitate timely interventions, preventive strategies, and efficient resource allocation in public health programs, ultimately improving patient outcomes and caregiver burden.

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“…Social isolation is one of the risk factors that contributes 3.5% of the overall 39.7% of the population attributable fraction of dementia worldwide ( 1 ). Social isolation is characterized by an individual’s lack of meaningful interactions ( 2 ), and is related to other risk factors for dementia, such as depression ( 1 ). This indicates that social isolation and other risk factors can exacerbate each other, which stresses its importance.…”

Section: Introductionmentioning

confidence: 99%

Social activities in multidomain dementia prevention interventions: insights from practice and a blueprint for the future

Bruinsma,

Visser,

Abaci

et al. 2024

Front. Psychiatry

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IntroductionSocial activities are important for health and act as a driver of cognitive reserve during aging. In this perspective paper, we describe challenges and outline future (research) endeavors to establish better operationalization of social activities in multidomain interventions to prevent dementia.BodyWe first address the lack of conceptual clarity, which makes it difficult to measure engagement in social activities. Second, drawing from our experience with the Finnish Geriatric Intervention Study to Prevent Cognitive Impairment and Disability (FINGER), we discuss social activities in multidomain dementia prevention interventions. Using qualitative data from the Multimodal Preventive Trial for Alzheimer’s Disease (MIND-ADmini), we reflect on participant experiences with social activities. Third, we address the potential and challenges of digital solutions in promoting social activities in interventions for dementia prevention. Finally, we share insights from a workshop on digital technology, where we consulted with individuals with and without cognitive impairment who have been involved in three European projects (i.e., EU-FINGERS, Multi-MeMo, and LETHE).DiscussionBased on these insights, we advocate for research that strengthens and accelerates the integration of social activities into multidomain interventions for dementia prevention. We propose several ways to achieve this: (a) by conducting mixed methods research to formulate a broadly accepted definition and instructions to measure social activities; (b) by focusing on promoting engagement in social activities beyond the intervention setting; and (c) by exploring the needs and preferences of older adults towards digitally-supported interventions and co-design of new technologies that enrich in-person social activities.

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Umbrella review and Delphi study on modifiable factors for dementia risk reduction

Cited by 5 publications

References 129 publications

Lifestyle for brain health and cognitive functioning in midlife to early late‐life New Zealanders: Utility of the LIBRA index

Lifestyle for brain health and cognitive functioning in midlife to early late‐life New Zealanders: Utility of the LIBRA index

Multimodal dementia identification using lifestyle and brain lesions, a machine learning approach

Social activities in multidomain dementia prevention interventions: insights from practice and a blueprint for the future

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