Forskningsartikler

Abstract:

The aim of this study was to assess the diagnostic validity of a deep learning-based method estimating brain age based on magnetic resonance imaging (MRI) and to compare it with volumetrics obtained using NeuroQuant (NQ) in a clinical cohort. Brain age prediction was performed on minimally processed MRI data using deep convolutional neural networks and an independent training set. The brain age gap (difference between chronological and biological age) was calculated, and volumetrics were performed in 110 patients with dementia (Alzheimer’s disease, frontotemporal dementia (FTD), and dementia with Lewy bodies), and 122 with non-dementia (subjective and mild cognitive impairment). Area-under-the-curve (AUC) based on receiver operating characteristics and logistic regression analyses were performed. The mean age was 67.1 (9.5) years and 48.7% (113) were females. The dementia versus non-dementia sensitivity and specificity of the volumetric measures exceeded 80% and yielded higher AUCs compared to BAG. The explained variance of the prediction of diagnostic stage increased when BAG was added to the volumetrics. Further, BAG separated patients with FTD from other dementia etiologies with > 80% sensitivity and specificity. NQ volumetrics outperformed BAG in terms of diagnostic discriminatory power but the two methods provided complementary information, and BAG discriminated FTD from other dementia etiologies.

Karin Persson, Esten H Leonardsen, Trine Holt Edwin, Anne-Brita Knapskog, Gro Gujord Tangen, Geir Selbæk, Thomas Wolfers, Lars T Westlye, Knut Engedal

Background: Malnutrition is common in older adults and is associated with increased morbidity and mortality rates.

Aim: The aim of the study is to describe the prevalence of malnutrition based on low BMI, involuntary weight loss, and reduced food intake, in a Norwegian population of community-dwelling older adults and older adults living in nursing homes.

Methods: This population-based study is part of the fourth wave of the Trøndelag Health Study (HUNT4) and includes participants ≥70 years from the HUNT4 70+ cohort. The HUNT4 70+ cohort consist of 9 930 (response rate 51.2 %) participants. In the current study 8 127 older people had complete dataset for inclusion in the analyses. Participants completed a self-report questionnaire and standardised interviews and clinical assessments at field stations, in participants’ homes or at nursing homes. Malnutrition was defined using the following criteria: low BMI, involuntary weight loss and severely reduced food intake. The standardised prevalence of malnutrition was estimated using inverse probability weighting (IPW) with weights for sex, age and education of the total population in the catchment area of HUNT.

Results: Of the 8 127 included participants, 7 671 (94.4 %) met at field stations, 356 (4.4 %) were examined in their home, and 100 (1.2 %) in nursing homes. In total, 14.3 % of the population were malnourished based on either low BMI, weight loss, or reduced food intake, of which low BMI was the most frequently fulfilled criterion. The prevalence of malnutrition was less common among men than among women (10.1 vs 18.0 %, p < 0.001), also after adjustment for age (OR 0.53, 95 % confidence interval (CI) 0.46-0.60). The prevalence increased gradually with increasing age and the regression analysis adjusted for sex showed that for each year increase in age the prevalence of malnutrition increased with 4.0 % (OR 1.04, 95 % CI 1.03-1.05). The prevalence was higher both among older adults examined in their homes (26.4%) and residents in nursing home (23.6%), as compared to community-dwelling older adults who met at field stations (13.5%).

Conclusion: The prevalence of malnutrition is high in the older population. Special attention on prevention and treatment of malnutrition should be given to older women, the oldest age groups, and care-dependent community-dwelling older adults and nursing home residents.

Marit Kolberg, Ingvild Paur, Yi-Qian Sun, Linda Gjøra, Håvard Kjesbu Skjellegrind, Pernille Thingstad, Bjørn Heine Strand, Geir Selbæk, Tone Natland Fagerhaug & Lene Thoresen

Abstract

The aging population and increasing evidence of the detrimental health impacts of loneliness emphasize the importance of studying and predicting changes in loneliness prevalence among older adults. To understand and project changes in loneliness over time, we examined 35-year trends in adults aged 70 and older, considering factors such as sex, age, and living situation. Cross-sectional data from 27,032 home-dwelling adults aged 70 years and older who participated in at least one of the four Norwegian HUNT surveys from 1984 to 2019, and Norwegian population data from Statistics Norway were used for the analyses. Loneliness was self-reported, and the prevalence of loneliness was standardized to the Norwegian population at the survey year by age and sex. The results showed that the prevalence of loneliness significantly decreased between each survey. The higher categories of loneliness (a good amount, very much) decreased, from 11.4% (1995-97), 6.7% (2006-08), and 5.8% (2017-19). Across surveys, loneliness was significantly more common among women, the oldest, and those living alone. The prevalence of loneliness among the oldest adults living alone increased from 2006 to 2019. The gradual decline in loneliness observed from 1995 to 2019 coincided with notable societal changes in Norway. We estimated that the number of older adults experiencing loneliness in Norway could rise from 184,000 in 2020 to 286,000 in 2035, and potentially reach 380,000 in 2050.

Ragnhild Holmberg Aunsmo, Ellen Melbye Langballe, Thomas Hansen, Geir Selbæk & Bjørn Heine Strand