Body weight variability in midlife and risk for dementia in old age

Estimating global prevalence of mild cognitive impairment and dementia in elderly with overweight, obesity, and central obesity: A systematic review and meta-analysis

BACKGROUND AND AIM

Previous studies have demonstrated that adiposity, particularly obesity during midlife, may have a detrimental effect on cognitive function. This study aims to estimate the global prevalence of mild cognitive impairment (MCI) and dementia in elderly aged 60 years or above with overweight, obesity, and central obesity.

METHODS

We searched PubMed, Embase, Web of Science, and Cochrane Library from inception to November 2023. DerSimonian-Laird random-effects model with Logit transformation was used. Sensitivity analysis, meta-regression, and subgroup analysis were employed to investigate determinants of the prevalence of MCI and dementia.

RESULTS

A total of 72 studies involving 2,980,947 elderly with distinct adiposity status were included. Pooled prevalence of MCI and dementia in elderly with overweight and obesity was 32.54% and 9.47%, respectively. Univariate meta-regression analysis indicated that the heterogeneity in dementia prevalence was attributable to variations in study size (R2 = 0.01, p < 0.05), while the multivariable analysis underscored that the income of country or area had the most significant predictive importance (60.3% and 90.3%) for both MCI and dementia prevalence. Subgroup analysis revealed regional disparities and diagnostic technique variations contributing to heterogeneity. Based on currently available but inadequate epidemiological data, the pooled prevalence of MCI and dementia in elderly with central obesity was calculated as 10.18% and 9.75%, respectively.

CONCLUSION

Strategies to address adiposity-associated cognitive impairment should consider multifaceted interventions beyond simple weight reduction. Macro-level initiatives such as improvement of income levels and micro-level interventions including the adoption of accurate diagnostic techniques also represent equally pivotal components.

Iron accumulation/overload and Alzheimer's disease risk factors in the precuneus region: A comprehensive narrative review

Alzheimer's disease (AD) is a neurodegenerative disease that is characterized by amyloid plaques, neurofibrillary tangles, and neuronal loss. Early cerebral and body iron dysregulation and accumulation interact with AD pathology, particularly in the precuneus, a crucial functional hub in cognitive functions. Quantitative susceptibility mapping (QSM), a novel post-processing approach, provides insights into tissue iron levels and cerebral oxygen metabolism and reveals abnormal iron accumulation early in AD. Increased iron deposition in the precuneus can lead to oxidative stress, neuroinflammation, and accelerated neurodegeneration. Metabolic disorders (diabetes, non-alcoholic fatty liver disease (NAFLD), and obesity), genetic factors, and small vessel pathology contribute to abnormal iron accumulation in the precuneus. Therefore, in line with the growing body of literature in the precuneus region of patients with AD, QSM as a neuroimaging method could serve as a non-invasive biomarker to track disease progression, complement other imaging modalities, and aid in early AD diagnosis and monitoring.

Abdominal fat depots are related to lower cognitive functioning and brain volumes in middle-aged males at high Alzheimer's risk

OBJECTIVE

High BMI, which poorly represents specific fat depots, is linked to poorer cognition and higher dementia risk, with different associations between sexes. This study examined associations of abdominal fat depots with cognition and brain volumes and whether sex modifies this association.

METHODS

A total of 204 healthy middle-aged offspring of Alzheimer's dementia patients (mean age = 59.44, 60% females) underwent abdominal magnetic resonance imaging to quantify hepatic, pancreatic, visceral, and subcutaneous adipose tissue and to assess cognition and brain volumes.

RESULTS

In the whole sample, higher hepatic fat percentage was associated with lower total gray matter volume (β = -0.17, p < 0.01). Primarily in males, higher pancreatic fat percentage was associated with lower global cognition (males: β = -0.27, p = 0.03; females: β = 0.01, p = 0.93) executive function (males: β = -0.27, p = 0.03; females: β = 0.02, p = 0.87), episodic memory (males: β = -0.28, p = 0.03; females: β = 0.07, p = 0.48), and inferior frontal gyrus volume (males: β = -0.28, p = 0.02; females: β = 0.10, p = 0.33). Visceral and subcutaneous adipose tissue was inversely associated with middle frontal and superior frontal gyrus volumes in males and females.

CONCLUSIONS

In middle-aged males at high Alzheimer's dementia risk, but not in females, higher pancreatic fat was associated with lower cognition and brain volumes. These findings suggest a potential sex-specific link between distinct abdominal fat with brain health.

Association of midlife body-weight variability and cycles with earlier dementia onset: a nationwide cohort study

BACKGROUND

Given the rising awareness of health-related lifestyle modifications, the impact of changes in body weight (BW) on cognitive function and dementia generates significant concern. This study aimed to investigate the association between BW changes and dementia in a middle-aged Korean population.

METHODS

A retrospective, population-based longitudinal study was conducted utilizing data from the National Health Insurance Service (NHIS) database. Participants aged 40 years or older in 2011 who underwent at least five health checkups between 2002 and 2011 were followed-up for dementia until 2020. A total of 3,635,988 dementia-free Korean aged < 65 at baseline were examined. We analyzed the association between BW variability independent of the mean (VIM) with BW cycle, defined as either an upward or a downward direction of BW, and the risk of incident dementia.

RESULTS

The results showed an increased risk of dementia in the highest quartile of VIM quartile (hazard ratio [HR] 1.52, 95% confidence interval [CI] 1.47-1.58) compared to the lowest quartile of VIM. Additionally, the results showed an even higher increased risk of dementia in the highest BW cycle (≥ 2 cycles of 10% BW = HR 2.00, 95% CI 1.74-1.29). Notably, the combined concept of VIM with BW cycle showed an even higher dementia risk (highest quartile of VIM with ≥ 2 cycles of 10% BW = HR 2.37, 95% CI 2.05-2.74) compared to the baseline group (lowest quartile of VIM with < 3% BW cycle).

CONCLUSIONS

The present study highlights the importance of considering BW changes with BW variability along with the BW cycle to assess dementia risk in detail, providing valuable insights for preventive strategies.

Dynamic Features of Body Mass Index in Late Life Predict Cognitive Trajectories and Alzheimer's Disease: A Longitudinal Study

Background

The causal relationships of late-life body mass index (BMI) with Alzheimer's disease (AD) remains debated.

Objective

We aimed to assess the associations of dynamic BMI features (ΔBMIs) with cognitive trajectories, AD biomarkers, and incident AD risk.

Methods

We analyzed an 8-year cohort of 542 non-demented individuals who were aged ≥65 years at baseline and had BMI measurements over the first 4 years. ΔBMIs were defined as changing extent (change ≤ or >5%), variability (standard deviation), and trajectories over the first 4 years measured using latent class trajectory modeling. Linear mixed-effect models were utilized to examine the influence of ΔBMIs on changing rates of AD pathology biomarkers, hippocampus volume, and cognitive functions. Cox proportional hazards models were used to test the associations with AD risk. Stratified analyzes were conducted by the baseline BMI group and age.

Results

Over the 4-year period, compared to those with stable BMI, individuals who experienced BMI decreases demonstrated accelerated declined memory function (p = 0.006) and amyloid-β deposition (p = 0.034) while BMI increases were associated with accelerated hippocampal atrophy (p = 0.036). Three BMI dynamic features, including stable BMI, low BMI variability, and persistently high BMI, were associated with lower risk of incident AD (p < 0.005). The associations were validated over the 8-year period after excluding incident AD over the first 4 years. No stratified effects were revealed by the BMI group and age.

Conclusions

High and stable BMI in late life could predict better cognitive trajectory and lower risk of AD.

The association between regional adiposity, cognitive function, and dementia-related brain changes: a systematic review

Background

Adiposity has been previously associated with cognitive impairment and Alzheimer's disease and related disorders (ADRD). Body mass index (BMI) is the most common measure of global adiposity, but inconsistent results were found since it is a global measurement. BMI does not represent regional fat distribution which differs between sexes, race, and age. Regional fat distribution may contribute differently to cognitive decline and Alzheimer's disease (AD)-related brain changes. Fat-specific targeted therapies could lead to personalized improvement of cognition. The goal of this systematic review is to explore whether regional fat depots, rather than central obesity, should be used to understand the mechanism underlying the association between adiposity and brain.

Methods

This systematic review included 33 studies in the English language, conducted in humans aged 18 years and over with assessment of regional adiposity, cognitive function, dementia, and brain measures. We included only studies that have assessed regional adiposity using imaging technics and excluded studies that were review articles, abstract only or letters to editor. Studies on children and adolescents, animal studies, and studies of patients with gastrointestinal diseases were excluded. PubMed, PsychInfo and web of science were used as electronic databases for literature search until November 2022.

Results

Based on the currently available literature, the findings suggest that different regional fat depots are likely associated with increased risk of cognitive impairment, brain changes and dementia, especially AD. However, different regional fat depots can have different cognitive outcomes and affect the brain differently. Visceral adipose tissue (VAT) was the most studied regional fat, along with liver fat through non-alcoholic fatty liver disease (NAFLD). Pancreatic fat was the least studied regional fat.

Conclusion

Regional adiposity, which is modifiable, may explain discrepancies in associations of global adiposity, brain, and cognition. Specific regional fat depots lead to abnormal secretion of adipose factors which in turn may penetrate the blood brain barrier leading to brain damage and to cognitive decline.

High body weight variability is associated with increased risk of depression: a nationwide cohort study in South Korea

BACKGROUND

Body weight variability (BWV) negatively affects the incidence and outcomes of various diseases, but the nature of the association between BWV and depression remains unclear. In this study, we aimed to test the hypothesis that BWV is associated with the risk of new-onset depression.

METHODS

Data from a nationwide population-based cohort in the Korean National Health Insurance Service database were analyzed for 6 598 570 adults with no history of depression and reports of at least three health examinations. BWV was estimated using variability independent of the mean indices and divided into quartiles (Q1 lowest, Q4 highest BWV). Cox proportional hazard models were applied to assess the risk of depression according to the quartile of BWV.

RESULTS

The incident rate for depression from Q1 to Q4 of BWV was 20.7, 20.3, 20.8, and 22.2 per 1000 person-years, respectively. BWV, especially high BWV, was associated with an increased risk of depression after adjusting for age, sex, smoking, alcohol consumption, physical activity, income, diabetes mellitus, hypertension, and dyslipidemia. The hazard ratio (HR) of new-onset depression was highest in Q4 relative to Q1 in the total population (HR 1.12, p < 0.0001) and was higher in women than in men (HR 1.72 v. 1.16, p < 0.0001). In stratified analyses, regardless of obesity or weight change status at baseline, the risk of depression was increased when bodyweight fluctuated highly during follow-up.

CONCLUSIONS

High BWV was associated with an increased risk of depression. Further studies need to evaluate the role of high BWV with respect to the onset of depression.

Longitudinal body weight dynamics in relation to cognitive decline over two decades: A prospective cohort study

OBJECTIVE

The aim of this study was to investigate the associations of body weight change (BWC) and body weight variability (BWV) with changes in cognitive function.

METHODS

In 10,340 Health and Retirement Study participants (mean age: 68.0 years), body weight was reported biennially from 1993/1994 to 2016, and cognitive function was measured biennially from 1998 to 2016. We calculated BWC and BWV as the slope and root-mean-square error by regressing body weight on time for each individual. BWC was categorized by quintiles (Q): stable weight (Q2 to Q4), weight loss (Q1), and weight gain (Q5). BWV was categorized by tertiles. We used linear mixed regression models to assess associations with cognitive change.

RESULTS

Compared with stable weight (median: 0 kg/y), weight loss (median: -1.3 kg/y) predicted faster cognitive decline as demonstrated by mean difference of -0.023 (95% CI: -0.027 to -0.019) in cognitive change z score per year, whereas weight gain (median: 1 kg/y) was related to slower cognitive decline (β = 0.006; 95% CI: 0.003 to 0.009). Larger BWV was also associated with faster cognitive decline (β comparing the top with bottom tertile = -0.003; 95% CI: -0.006 to -0.0002). Similar associations were observed for episodic and working memory.

CONCLUSIONS

Weight loss and large BWV over a long time independently predicted faster cognitive decline in middle-aged and older adults, underscoring the importance of long-term dynamic body weight monitoring.

Relationship Between Weight-Change Patterns and Cognitive Function: A Retrospective Study

BACKGROUND

Obesity has been linked to cognitive impairment. However, how changes in body mass index (BMI) over the life course influence cognitive function remains unclear.

OBJECTIVE

The influence of distinct weight-change patterns from young adulthood to midlife and late adulthood on cognitive function in older adults was explored.

METHODS

A total of 5,809 individuals aged≥60 years were included and categorized into four groups on the basis of BMI change patterns. Cognitive function was assessed using four cognition tests in the baseline survey. The relationship between the weight-change patterns and cognition was evaluated using regression models.

RESULTS

In comparison with participants who remained at non-obese, those moving from the non-obese to obese weight-change pattern from young (25 years of age) to middle adulthood showed lower Digit Symbol Substitution Test (DSST) scores (β= -1.28; 95% confidence interval [CI]: -2.24 to -0.32). A non-obese to obese change pattern from age 25 years of age to 10 years before baseline was associated with a higher risk of DSST impairment (odds ratio = 1.40; 95% CI: 1.09 to 1.79). In comparison with participants whose heaviest weight was recorded after 60 years of age, those with the heaviest weight between 18 and 40 years of age had lower DSST scores (β= -1.46; 95% CI: -2.77 to -1.52).

CONCLUSION

Our results suggest that the transition from the non-obese to obese category in early adulthood and appearance of the heaviest weight between 18 and 40 years of age are associated with lower cognitive function in later life.

Association of Early Weight Change With Cognitive Decline in Patients With Parkinson Disease

BACKGROUND AND OBJECTIVE

To examine whether early weight change is associated with subsequent deterioration in cognitive function, including overall performance and specific domains, in Parkinson disease (PD).

METHODS

This observational study used data from the Parkinson Progression Markers Initiative cohort. The patients underwent annual nonmotor assessments covering neuropsychiatric, sleep-related, and autonomic symptoms for up to 8 years of follow-up. Cognitive function was measured using the Montreal Cognitive Assessment (MoCA) and detailed neuropsychological testing. Linear mixed-effects models were applied to investigate the association of early weight change with longitudinal evolution of cognitive and other nonmotor symptoms.

RESULTS

A total of 358 patients with early PD were classified into weight loss (decrease of >3% body weight during the first year; n = 98), weight maintenance (within ±3%; n = 201), and weight gain (increase of >3%; n = 59) groups. The weight loss group showed a significantly faster decline in MoCA scores than the weight maintenance group (β = -0.19, 95% CI -0.28 to -0.10). With respect to specific cognitive domains, the weight loss group showed a steeper decline in sematic fluency test scores (β = -0.37, 95% CI -0.66 to -0.08) and MoCA phonemic fluency scores (β = -0.18, 95% CI -0.31 to -0.05) and, to a lesser extent, Letter-Number Sequencing scores (β = -0.07, 95% CI -0.14 to 0.01) compared with the weight maintenance group. Conversely, the weight gain group showed a slower decline in the Symbol Digit Modalities Test scores (β = 0.34, 95% CI 0.05 to 0.63), although no association was found with longitudinal changes in MoCA scores. We did not find any significant effects of weight change on the progression of other nonmotor symptoms.

DISCUSSION

Early weight loss was associated with a faster progression of decline in global cognitive function and executive function in patients with PD, whereas early weight gain was associated with a slower progression of decline in processing speed and attention. The impact of early weight change on nonmotor symptoms seemed to be specific to cognition.

Weight loss, visit-to-visit body weight variability and cognitive function in older individuals

OBJECTIVE

to investigate the association between variability and loss of body weight with subsequent cognitive performance and activities of daily living in older individuals.

DESIGN

cross-sectional cohort study.

SETTING

PROspective Study of Pravastatin in the Elderly at Risk, multicentre trial with participants from Scotland, Ireland and the Netherlands.

SUBJECTS

4,309 participants without severe cognitive dysfunction (mean age 75.1 years, standard deviation (SD) = 3.3), at higher risk for cardiovascular disease (CVD).

METHODS

body weight was measured every 3 months for 2.5 years. Weight loss was defined as an average slope across all weight measurements and as ≥5% decrease in baseline body weight during follow-up. Visit-to-visit variability was defined as the SD of weight measurements (kg) between visits. Four tests of cognitive function were examined: Stroop test, letter-digit coding test (LDCT), immediate and delayed picture-word learning tests. Two measures of daily living activities: Barthel Index (BI) and instrumental activities of daily living (IADL). All tests were examined at month 30.

RESULTS

both larger body weight variability and loss of ≥5% of baseline weight were independently associated with worse scores on all cognitive tests, but minimally with BI and IADL. Compared with participants with stable weight, participants with significant weight loss performed 5.83 seconds (95% CI 3.74; 7.92) slower on the Stroop test, coded 1.72 digits less (95% CI -2.21; -1.13) on the LDCT and remembered 0.71 pictures less (95% CI -0.93; -0.48) on the delayed picture-word learning test.

CONCLUSION

in older people at higher risk for CVD, weight loss and variability are independent risk-factors for worse cognitive function.

Recent Updates on Associations among Various Obesity Metrics and Cognitive Impairment: from Body Mass Index to Sarcopenic Obesity

Obesity and obesity-associated morbidity continues to be a major public health issue worldwide. Dementia is also a major health concern in aging societies and its prevalence has increased rapidly. Many epidemiologic studies have shown an association between obesity and cognitive impairment, but this relationship is not as well established as other comorbidities. Conflicting results related to the age and sex of participants, and the methodology used to define obesity and dementia may account for the uncertainty in whether obesity is a modifiable risk factor for dementia. More recently, sarcopenia and sarcopenic obesity have been reported to be associated with cognitive impairment. In addition, new mediators such as the muscle-myokine-brain axis and gut-microbiota-brain axis have been suggested and are attracting interest. In this review, we summarize recent evidence on the link between obesity and cognitive impairment, especially dementia. In particular, we focus on various metrics of obesity, from body mass index to sarcopenia and sarcopenic obesity.

Stability in BMI over time is associated with a better cognitive trajectory in older adults

OBJECTIVE

Evidence on simultaneous changes in body mass index (BMI) and cognitive decline, which better reflect the natural course of both health phenomena, is limited.

METHODS

We capitalized on longitudinal data from 15,977 initially non-demented elderly from the Alzheimer's Disease Centers followed for 5 years on average. Changes in BMI were defined as (1) last minus first BMI, (2) mean of all follow-up BMIs minus first BMI, and (3) standard deviation of BMI change from baseline and all follow-up visits (representing variability).

RESULTS

Participants with significant changes in BMI (increase or decrease of ≥5%), or who had greater variability in BMI, had faster cognitive decline. This pattern was consistent irrespective of normal (BMI < 25; N = 5747), overweight (25 ≤ BMI < 30; N = 6302), or obese (BMI ≥ 30; N = 3928) BMI at baseline.

CONCLUSIONS

Stability in BMI predicts better cognitive trajectories suggesting clinical value in tracking BMI change, which is simple to measure, and may point to individuals whose cognition is declining.

Association of Long-Term Body Weight Variability With Dementia: A Prospective Study

BACKGROUND

Body weight variability (BWV) refers to intraindividual weight loss and gain over a period. The association of long-term BWV with dementia remains unclear and whether this association is beyond body weight change is undetermined.

METHODS

In the Health and Retirement Study, a total of 5 547 dementia-free participants (56.7% women; mean [SD] age, 71.1 [3.2] years) at baseline (2008) were followed up to 8 years (mean = 6.8 years) to detect incident dementia. Body weight was self-reported biennially from 1992 to 2008. BWV was measured as the coefficient of variation utilizing the body weight reported 9 times across 16 years before baseline. Cox-proportional hazard model was used to estimate the hazard ratio (HR) and 95% confidence interval (CI).

RESULTS

Among the 5 547 participants, a total of 427 incident dementia cases were identified during follow-up. Greater long-term BWV was significantly associated with a higher risk of dementia (HR comparing extreme quartiles: 2.01, 95% CI: 1.48-2.72; HR of each SD increment: 1.21, 95% CI: 1.10-1.32; p-trend < .001) independent of mean body weight and body weight change. This significant association was even observed for BWV estimated approximately 15 years preceding dementia diagnosis (HR of each SD increment: 1.13, 95% CI: 1.03-1.23) and was more pronounced for that closer to diagnosis.

CONCLUSION

Our prospective study suggested that greater BWV may be a novel risk factor for dementia.

Body weight variability and the risk of dementia in patients with type 2 diabetes mellitus: A nationwide cohort study in Korea

AIMS

This study aimed to examine the association between body weight variability and dementia risk using a large-scale cohort data of Korean patients with type 2 diabetes mellitus (T2DM).

METHODS

A population-based cohort of 1,206,764 individuals with T2DM aged ≥ 40 years who underwent ≥ 3 Korean national health screenings were followed up until the end of 2019. Body weight variability was assessed using variability independent of the mean (VIM). A multivariate Cox proportional hazard regression was performed with calculating hazard ratios (HRs) with 95 % confidence intervals (CIs) of dementia incidence.

RESULTS

During a median follow-up of 7.9 years, 162,615 (13.4 %) individuals developed dementia. Individuals with greater body weight variability tended to be associated with higher risk of all types of dementia (P for trend < 0.001). Individuals in the highest quartile of VIM showed 26 % (HR: 1.26, 95 % CI: 1.24-1.28), 33 % (HR: 1.33, 95 % CI: 1.30-1.36) and 28 % (HR: 1.28, 95 % CI: 1.23-1.33) higher risk for all-cause dementia, Alzheimer's disease, and vascular dementia, compared with those in the lowest quartile. These associations persisted in all body mass index categories (P for trend < 0.001).

CONCLUSIONS

Maintaining an appropriate body weight may help mitigate dementia risk in patients with T2DM.

Variability in Cardiometabolic and Inflammatory Parameters and Cognitive Decline

INTRODUCTION

The relationship between variability in cardiometabolic and inflammatory parameters and cognitive changes is unknown. This study investigates the association of visit-to-visit variability in BMI, mean arterial pressure, total cholesterol, triglycerides, HbA1c, high-sensitivity C-reactive protein, ferritin, and fibrinogen with cognitive decline.

METHODS

This population-based cohort study included 2,260 individuals (mean age=63.0 [SD=7.5] years) free of cognitive diseases who underwent ≥3 clinical measurements from 2004 to 2019. Variability was expressed as variability independent of the mean across visits. Participants were divided on the basis of quartiles of variability score, a scoring system generated to explore the composite effect of parameter variability (range=0-24), where 0 points were assigned for Quartile 1, 1 point was assigned for Quartile 2, 2 points were assigned for Quartile 3, and 3 points were assigned for Quartile 4, each for the variability of 8 parameters measured as variability independent of the mean. Linear mixed models evaluated the longitudinal associations with cognitive decline in memory and verbal fluency. All analyses were conducted in 2020-2021.

RESULTS

Higher BMI, mean arterial pressure, total cholesterol, HbA1c, and ferritin variability were linearly associated with cognitive decline irrespective of their mean values. In addition, participants in the highest quartile of variability score had a significantly worse cognitive decline rate in memory (-0.0224 points/year, 95% CI= -0.0319, -0.0129) and verbal fluency (-0.0088 points/year, 95% CI= -0.0168, -0.0008) than those in the lowest quartile.

CONCLUSIONS

A higher variability in cardiometabolic and inflammatory parameters was significantly associated with cognitive decline. Stabilizing these parameters may serve as a target to preserve cognitive functioning.

Association between Variations in Body Mass Index and Cognitive Function in Older Korean Adults

Background

Although several studies have assessed obesity and cognitive impairment, most of these studies focus on body mass index (BMI) and cognitive impairment. Therefore to better understand the importance of weight maintenance with aging, this study investigated the relationship between variations in weight and cognitive impairment using the Korean version of the Mini-Mental State Examination (K-MMSE) in individuals aged 45 years or older in Korea.

Methods

Data on 3,477 adults with normal cognitive function (K-MMSE ≥24) at baseline were acquired from the Korean Longitudinal Study of Aging (KLoSA) 2006-2016. The association between weight variability and risk of cognitive impairment was assessed using multiple logistic regression models. We also assessed weight variability and change in cognitive function over the 6-year follow-up using multiple linear regression.

Results

Overall, higher variations in BMI were associated with cognitive impairment. Patients in the quintile with the highest variation (Q5) in BMI (mean of BMI changes, 2.69) showed the greatest degree of cognitive impairments (adjusted odds ratio, 1.52; 95% confidence interval [CI], 1.08-2.14; P for trend=0.016). Furthermore, a higher frequency in the number of times (3 times) the patient’s body weight changed was associated with a lower cognitive function (adjusted odds ratio, 3.42; 95% CI, 1.67-7.03; P for trend<0.001).

Conclusion

In this nationally representative study, weight variability was associated with a higher risk of cognitive decline during mid- and late-life stages.

Longitudinal Body Weight Change, Visit-To-Visit Body Weight Fluctuation, and Cognitive Decline Among Older Adults

BACKGROUND

The evidence regarding dementia and late-life weight change is inconsistent, and data on body weight fluctuation and dementia are limited.

OBJECTIVE

To test the hypothesis that weight loss and substantial weight fluctuation predict cognitive decline independent of body weight and traditional risk factors of dementia.

METHODS

This study utilized longitudinal data from the National Alzheimer's Coordinating Center for 10,639 stroke- and dementia-free older adults (60.9%female, mean age 71.6 years, median follow-up 5.5 years). Trends in weight change and weight fluctuation were estimated for each individual by regressing repeated body weight measurements on time. Cognitive decline was examined as diagnostic progression from normal to mild cognitive impairment (MCI) or dementia and from MCI to dementia.

RESULTS

Compared to participants with stable weight, those with weight loss had increased odds of diagnostic progression (adjusted OR = 1.35, 95%CI [1.21, 1.51]). Also, large weight fluctuation was associated with increased odds of diagnostic progression (OR comparing the extreme quartiles = 1.20, 95%CI [1.04, 1.39]) after adjusting for traditional risk factors for dementia and body weight change. The magnitude of the association appeared larger among those older than 80 and those with 3 or more cardiometabolic risk factors at baseline (both p for interaction < 0.05).

CONCLUSION

Weight loss and substantial weight fluctuation during late-life were associated with increased odds of cognitive decline independent of body weight and traditional risk factors of dementia. Our results suggested the linkage between late-life body weight instability and cognitive decline especially among those with greater age or higher cardiometabolic risk.

Association between body weight variability and incidence of Parkinson disease: A nationwide, population-based cohort study

BACKGROUND AND PURPOSE

Although body weight variability has been associated with mortality, cardiovascular disease, and dementia, the relationship between body weight variability and Parkinson disease (PD) has rarely been studied. We aimed to investigate the longitudinal association between body weight variability and PD incidence.

METHODS

A nationwide population-based, cohort study was conducted using the database from the Health Insurance Review and Assessment Service of the whole Korean population. We analyzed 2,815,135 participants (≥40 years old, mean age = 51.7 ± 8.6 years, 66.8% men) without a previous PD diagnosis. We determined individual body weight variability from baseline weight and follow-up visits. We used Cox proportional hazards regression models.

RESULTS

The highest quartile group was associated with increased PD incidence compared with the lowest quartile group after adjustment for confounding factors (hazard ratio [HR] = 1.18, 95% confidence interval [CI] = 1.08-1.29). In contrast, baseline body mass index, baseline waist circumference, and waist circumference variability were not associated with increased PD incidence. In the body weight loss group, individuals within the quartile of the highest variation in body weight showed a higher HR of PD risk than those within other quartiles (HR = 1.41, 95% CI = 1.18-1.68).

CONCLUSIONS

Body weight variability, especially weight loss, was associated with higher PD incidence. This finding has important implications for clinicians and supports the need for preventative measures and surveillance for PD in individuals with fluctuating body weight.

Predictors of change in BMI over 10 years among midlife and older adults: Associations with gender, CVD risk status, depressive symptoms, and social support

RATIONALE

Change in BMI is recognized as a key health indicator among midlife and older adults, though predictors of BMI change in this group have received little attention.

OBJECTIVE

The aim of this study was to examine relations between hypothesized predictors (i.e., gender, cardiovascular disease [CVD] risk status, depressive symptoms, social support) and BMI change over 10 years, among midlife and older adults.

METHODS

Participants were adults ages 50-74 at baseline (N = 5,688, 64% women) who completed four assessments over 10 years. Gender, CVD risk status (i.e., diagnosis of hypertension, type 2 diabetes, or both), depressive symptoms, and perceived social support were assessed at baseline, and BMI was calculated from height and weight reports at all assessments. Multilevel models tested for concurrent and prospective relations between predictors and BMI change (effect size estimates as semipartial correlation coefficients, sr), as well as whether observed relations were further moderated by baseline BMI category (underweight, healthy weight, overweight, or obese).

RESULTS

Baseline BMI was higher among those with (vs. without) CVD risk, higher (vs. lower) depressive symptoms, and lower (vs. higher) social support; all of these relations were moderated by gender (ps < 0.05, srs 0.03-0.32). Moreover, BMI showed significant change over 10 years, and BMI variability during this time was higher among women (vs. men) and those with (vs. without) CVD risk (ps < 0.0001). BMI change also differed by CVD risk status, and this relation was moderated by gender, baseline depressive symptoms, and baseline BMI category (ps < 0.05, srs 0.03-0.08).

CONCLUSIONS

Although the predictors of interest were not associated with steady BMI decreases (which are associated with long term health risks for older adults), findings reveal unique patterns of change in BMI among subgroups of midlife and older adults, and may allow for early identification of those with noteworthy BMI changes after age 50.

The relationship of obesity predicting decline in executive functioning is attenuated with greater leisure activities in old age

Objectives: We investigated the longitudinal relationship between obesity and subsequent decline in executive functioning over six years as measured through performance changes in the Trail Making Test (TMT). We also examined whether this longitudinal relationship differed by key markers of cognitive reserve (education, occupation, and leisure activities), taking into account age, sex, and chronic diseases as covariates.Method: We used latent change score modeling based on longitudinal data from 897 older adults tested on TMT parts A and B in two waves six years apart. Mean age in the first wave was 74.33 years. Participants reported their weight and height (to calculate BMI), education, occupation, leisure activities, and chronic diseases.Results: There was a significant interaction of obesity in the first wave of data collection with leisure activities in the first wave on subsequent latent change. Specifically, obesity in the first wave significantly predicted a steeper subsequent decline in executive functioning over six years in individuals with a low frequency of leisure activities in the first wave. In contrast, in individuals with a high frequency of leisure activities in the first wave, this longitudinal relationship between obesity and subsequent decline in executive functioning was not significant.Conclusion: The longitudinal relationship between obesity and subsequent decline in executive functioning may be attenuated in individuals who have accumulated greater cognitive reserve through an engaged lifestyle in old age. Implications for current cognitive reserve and gerontological research are discussed.

Body mass index trajectories and the risk for Alzheimer's disease among older adults

The effect of body mass index (BMI) changes and variability on the risk for Alzheimer’s disease (AD) remains unclear. We analyzed 45,076 participants, whose BMI were measured on phase 1 (2002–2003), phase 2 (2004–2005), and phase 3 (2006–2007), of the Korean National Health Insurance Service-Health Screening Cohort. We evaluated the effect of 2- and 4-year BMI changes and BMI variability on the risk of AD using Cox regression models. In men, association between 2-year BMI changes, BMI variability, and the risk of AD was not significant. Risk of AD was higher in men whose BMI had decreased 10.1–15.0% over 4 years. In women, aHRs and 95% CIs for AD were 1.14 (1.02–1.29), 1.44 (1.17–1.79), and 1.51 (1.09–2.09) when 2-year BMI loss was 5.1–10.0%, 10.1–15.0%, and > 15.0%. The HRs for AD in women significantly increased when 4-year BMI loss was > 5.0%. The aHR and 95% CI for AD was 1.31 (1.17–1.46) in the 4th quartile of average successive variability (ASV) compared with the 1st quartile of ASV in women. BMI loss over 2- and 4-year period was associated with increased risk for AD, and risk increased in women with higher BMI variability. Appropriate body weight management is recommended to prevent AD.

Association between Long-term Weight Change since Midlife and Risk of Incident Disabling Dementia among Elderly Japanese: the Ohsaki Cohort 2006 Study

Background

Both weight loss and cognitive impairment are common in late-life, but it remains unknown whether weight change is associated with risk of incident dementia among elderly Japanese. Our study aimed to investigate the association between long-term weight change since midlife and risk of incident disabling dementia using a community-based cohort study of elderly Japanese.

Methods

In 2006, we conducted a cohort study of 6,672 disability-free Japanese adults aged ≥65 years. In both 1994 and 2006, the participants reported their weight using a self-reported questionnaire. Based on weight obtained at these two time points, participants were classified into: stable weight (−1.4 to +1.4 kg), weight gain (≥+1.5 kg), and weight loss of −2.4 to −1.5 kg, −3.4 to −2.5 kg, −4.4 to −3.5 kg, −5.4 to −4.5 kg, and ≥−5.5 kg. Incident disabling dementia was retrieved from the public Long-term Care Insurance database. Participants were followed-up for 5.7 years (between April 2007 and November 2012). Cox proportional hazards model was used to estimate multivariable-adjusted hazard ratios (HRs) and 95% confidence intervals (CIs) for incident disabling dementia.

Results

During 32,865 person-years of follow-up, 564 participants were ascertained as having incident disabling dementia. Compared with stable weight, the multivariable-adjusted HRs were 0.97 (95% CI, 0.70–1.34) for weight loss of −2.4 to −1.5 kg, 0.98 (95% CI, 0.70–1.38) for −3.4 to −2.5 kg, 1.28 (95% CI, 0.91–1.81) for −4.4 to −3.5 kg, 1.27 (95% CI, 0.92–1.77) for −5.4 to −4.5 kg, and 1.64 (95% CI, 1.29–2.09) for ≥−5.5 kg.

Conclusion

Our study suggested that a ≥−3.5 kg weight loss over 12 years might be associated with higher risk of incident disabling dementia among elderly Japanese.

Variability in body weight precedes diagnosis in dementia: A nationwide cohort study

BACKGROUND

While there have been disagreements concerning whether obesity and increase in body weight elevate the risk of dementia, variability in body weight has been recently recognized as a new biometric associated with a high risk for a number of diseases. This nationwide, population-based cohort study examined the association between body weight variability and dementia.

METHODS

A total of 2,812,245 adults (mean age, 51.7 years; standard deviation, 8.6) without a history of dementia who underwent at least three health examinations between 2005 and 2012 in a nationwide cohort were followed-up until the date of dementia diagnosis (based on prescribed drugs and disease code) or until 2016 (median follow-up duration, 5.38 years; interquartile range, 5.16-5.61). Cox regression models were used to evaluate the risk of Alzheimer's disease and vascular dementia according to body weight variability.

RESULTS

The hazard ratios (95% confidence intervals) of the highest quartiles of variability were 1.42 (1.35-1.49) for Alzheimer's disease and 1.47 (1.32-1.63) for vascular dementia compared to the lowest quartile group as a reference. This association was consistent in various subgroup analyses and sensitivity analyses.

CONCLUSIONS

Body weight variability could predict Alzheimer's disease and vascular dementia, which may provide new insights into the prevention and management of dementia.

Midlife Modifiable Risk Factors for Dementia: A Systematic Review and Meta-analysis of 34 Prospective Cohort Studies

OBJECTIVE

The aim of this study is to assess the association between midlife risk factors and dementia.

METHODS

PubMed and Cochrane library were systematically searched on May 24, 2018, to retrieve prospective cohort studies. The summary Relative Risk (RR) and 95% Confidence Interval (CI) were calculated by the random-effect model to explore the association between midlife risk factors and dementia. Sensitivity analysis and meta-regression were conducted to explore the source of heterogeneity. Publication bias was examined using Begg's and Egger's tests.

RESULTS

Thirty-four prospective cohort studies were included, among which 24 were eligible for metaanalysis. A total of 159,594 non-demented adults were enrolled at baseline before 65 years and 13,540 people were diagnosed with dementia after follow-up. The pooled results revealed that five factors could significantly increase the dementia risk by 41 to 78%, including obesity (RR, 1.78; 95% CI: 1.31-2.41), diabetes mellitus (RR, 1.69; 95% CI: 1.38-2.07), current smoking (RR, 1.61; 95%, CI: 1.32-1.95), hypercholesterolemia (RR, 1.57; 95% CI: 1.19-2.07), and hypertension (borderline blood pressure RR, 1.41; 95% CI: 1.23-1.62 and high Systolic Blood Pressure (SBP) RR, 1.72; 95% CI: 1.25-2.37). However, the sensitivity analyses found that the results of hypercholesterolemia and high SBP were not reliable, which need to be confirmed by more high-quality studies. No influences due to publication bias were revealed. In the systematic review, another three factors (hyperhomocysteinemia, psychological stress, and heavy drinking) were found to be associated with elevated dementia risk. In addition, physical exercise, a healthy diet, and hormone therapy in middle age were associated with the reduction of dementia risk.

CONCLUSIONS

Middle-aged people with obesity, diabetes, hypertension, or hypercholesterolemia, and current smokers in midlife are at higher risk of developing dementia later in life.

Long-term trajectories of BMI predict carotid stiffness and plaque volume in type 2 diabetes older adults: a cohort study

BACKGROUND

High body mass index (BMI) is a risk factor for type 2 diabetes and cardiovascular disease. However, its relationships with indices of carotid stiffness and plaque volume are unclear. We investigated associations of long-term measurements of BMI with indices of carotid stiffness and atherosclerosis among non-demented diabetes patients from the Israel Diabetes and Cognitive Decline (IDCD) study.

METHODS

Carotid ultrasound indices [carotid intima media thickness (cIMT), distensibility, elastography and plaque volume] were assessed in N = 471 participants. Mean BMI across all MHS diabetes registry measurements and trajectories of BMI were calculated. BMI was categorized into three trajectory groups representing: a relatively stable normal weight (n = 185, 44%), overweight trajectory (n = 188, 44.8%) and a trajectory of obesity (n = 47, 11.2%). Linear and logistic regressions estimated associations of carotid indices with mean BMI and BMI trajectories.

RESULTS

Compared to the normal weight trajectory, an obesity trajectory was associated with carotid distensibility (β = - 3.078, p = 0.037), cIMT (β = 0.095, p = 0.004), and carotid elastography (β = 0.181, p = 0.004) but not with plaque volume (β = 0.066, p = 0.858). Compared with the normal weight trajectory, an obesity trajectory was associated with increased odds for impaired carotid distensibility (OR = 2.790, p = 0.033), impaired cIMT (OR = 5.277, p = 0.001) and large carotid plaque volume (OR = 8.456, p = 0.013) but not with carotid elastography (OR = 1.956, p = 0.140). Mean BMI was linearly associated with Distensibility (β = - 0.275, p = 0.005) and cIMT (β = 0.005, p = 0.026).

CONCLUSIONS

Long-term measurements of adiposity are associated with indices of carotid stiffness and plaque volume among older type 2 diabetes adults.

Cardiovascular Risk Factors: It's Time to Focus on Variability!

Atherosclerotic heart disease remains a leading cause of morbidity and mortality worldwide. While extensive research supports cardiovascular risk factor reduction in the form of achieving evidence-based blood pressure, lipid, glucose, and body weight targets as a means to improve cardiovascular outcomes, residual risk remains. Emerging data have demonstrated that the intraindividual variability of these risk factor targets potentially contribute to this residual risk. It may therefore be time to define risk factor by not only its magnitude and duration as done traditionally, but perhaps also by the variability of that particular risk factor over time.

Association of body mass index with risk of cognitive impairment and dementia: A systematic review and meta-analysis of prospective studies

Controversies persist about the associations of body mass index (BMI) with risk of cognitive impairment and dementia. This study aimed to evaluate these associations from various aspects, in which Embase, PubMed and Cochrane databases were searched to identify prospective studies up to May 2019. Random-effects meta-analyses and dose-response meta-analysis were conducted, involving twenty-nine of 20,083 identified literatures. Meta-analysis showed that midlife underweight, obesity and late-life underweight conferred 1.39-, 1.31- and 1.64-fold excess risk for cognitive impairment and dementia, while late-life overweight and obesity conferred 21% and 25% reduced risk. In dose-response meta-analysis, all cause dementia (ACD), Alzheimer's disease (AD) and vascular dementia (VaD) risk in midlife was significantly elevated when BMI surpassed 29, 30 and 32 kg/m2. AD risk in late-life was decreased when BMI was under 27 kg/m2, while this protection for VaD was absent when BMI surpassed 39 kg/m2. Higher BMI produced opposite exerted opposite effects on dementia in mid- and late-age population. Firstly reported, a dose-response relationship further supports the guideline from the standpoint of dementia prevention.

Risk Factor Variability and Cardiovascular Outcome: JACC Review Topic of the Week

Until recently, intraindividual visit-to-visit variability of cardiovascular risk factors has been dismissed as random fluctuation. This simplistic concept was challenged by demonstrating that visit-to-visit blood pressure variability, independent of average blood pressure, was a powerful risk factor for stroke. Subsequently, variability of other cardiovascular risk factors such as cholesterol, glycemia, and body weight was documented to increase risk independent of their absolute values. Variability of these risk factors has been demonstrated to be a powerful predictor for all-cause and cardiovascular mortality, stroke, coronary artery disease, heart failure, end-stage renal disease, and dementia. With the notable exception of heart rate, cardiovascular risk factors must now be defined by 2 components: the magnitude and duration of sustained risk factor elevation and, equally important, the variability of the same risk factor over time.

Computerized Cognitive Training for Older Adults at Higher Dementia Risk due to Diabetes: Findings From a Randomized Controlled Trial

BACKGROUND

To evaluate the effects of adaptive and tailored computerized cognitive training on cognition and disease self-management in older adults with diabetes.

METHODS

This was a single-blind trial. Eighty-four community-dwelling older adults with diabetes were randomized into a tailored and adaptive computerized cognitive training or a generic, non-tailored or adaptive computerized cognitive training condition. Both groups trained for 8 weeks on the commercially available CogniFit program and were supported by a range of behavior change techniques. Participants in each condition were further randomized into a global or cognition-specific self-efficacy intervention, or to a no self-efficacy condition. The primary outcome was global cognition immediately following the intervention. Secondary outcomes included diabetes self-management, meta-memory, mood, and self-efficacy. Assessments were conducted at baseline, immediately after the training, and at a 6-month follow-up.

RESULTS

Adherence and retention were lower in the generic computerized cognitive training condition, but the self-efficacy intervention was not associated with adherence. Moderate improvements in performance on a global cognitive composite at the posttreatment assessments were observed in both cognitive training conditions, with further small improvement observed at the 6-month follow-up. Results for diabetes self-management showed a modest improvement on self-rated diabetes care for both intervention conditions following the treatment, which was maintained at the 6-month follow-up.

CONCLUSIONS

Our findings suggest that older adults at higher dementia risk due to diabetes can show improvements in both cognition and disease self-management following home-based multidomain computerized cognitive training. These findings also suggest that adaptive difficulty and individual task tailoring may not be critical components of such interventions.

TRIAL REGISTRATION

NCT02709629.

Gamma-Glutamyl Transferase Variability and Risk of Dementia in Diabetes Mellitus: A Nationwide Population-Based Study

CONTEXT

Gamma-glutamyl transferase (GGT) has been associated with oxidative stress and inflammatory reactions. Variability in various biomarkers has emerged as a new clinical indicator for diseases including neurodegenerative disorders.

OBJECTIVE

We investigated the association between GGT variability and dementia risk in patients with diabetes mellitus (DM).

DESIGN, PARTICIPANTS, AND METHODS

We used the Korean National Health Insurance Service datasets of Claims and Health Check-ups from 2004 to 2016. The risk of incident dementia (all-cause dementia, Alzheimer disease, vascular dementia) was analyzed by quartiles of GGT variability in ≥ 40-year-old DM individuals without baseline dementia.

RESULTS

During 6.12 years of follow-up, 37, 983 cases of dementia developed. In the fully adjusted model, the group with the highest quartile of GGT variability had a 19% increased risk of all-cause dementia when compared with the lowest quartile group (hazard ratio; 95% confidence interval): 1.19; 1.16-1.22, with a small effect size (Cohen d's = 0.14). Compared with the group with low baseline GGT level and the lowest quartiles of its variability, the group with high baseline GGT level and the highest quartile of its variability increased 27% of all-cause dementia. A 1 SD increment in the GGT variability was associated with a 3% increased risk of all-cause dementia. Subgroup analysis showed a more prominent association between increased GGT variability and dementia risk in men and < 60-year-old individuals (P for interaction ≤ .001).

CONCLUSIONS

In subjects with DM, high variability of GGT increased the risk of dementia independently of other factors, including baseline GGT levels.

Adiposity, Weight Change, and Risk of Cognitive Impairment: The Singapore Chinese Health Study

BACKGROUND

Few prospective studies with long duration of follow-up have assessed the relations of body mass index (BMI) and weight change with cognitive function, especially in Asian populations.

OBJECTIVE

To investigate whether BMI and weight change in midlife are associated with cognitive impairment in old age.

METHODS

We used data from 14,691 participants in the Singapore Chinese Health Study and computed weight change as the difference between weight reported at baseline (1993-1998) at mean age of 53.0 years and follow-up 1 (1999-2004) at mean age of 58.6 years. Cognitive impairment was determined using education-specific cut-offs of the Singapore Modified Mini-Mental State Examination at follow-up 3 (2014-2016) at mean age of 72.9 years. We used multivariable logistic regression models to estimate the odds ratios (ORs) and 95% confidence intervals (CIs) for the associations.

RESULTS

Obesity (as defined BMI ≥27.5 kg/m2) was associated with a higher risk of cognitive impairment at baseline (OR 1.33, 95% CI 1.12-1.58) and follow-up 1 (OR 1.30, 95% CI 1.10-1.54) compared to BMI of 18.5-22.9 kg/m2. Underweight (BMI <18.5 kg/m2) was not associated with a significant risk either at baseline (OR 0.91, 95% CI 0.73-1.13) or follow-up 1 (OR 1.05, 95% CI 0.85-1.28). Compared to participants with <5% weight change, the ORs (95% CIs) of cognitive impairment were 1.20 (1.03-1.41) for those with 5-9.9% weight loss, 1.53 (1.29-1.81) for ≥10% weight loss, 1.00 (0.85-1.17) for 5-9.9% weight gain, and 1.50 (1.28-1.75) for ≥10% weight gain.

CONCLUSION

Obesity, weight loss, and excessive weight gain at midlife were associated with an increased risk of cognitive impairment at old age.

Body Weight Variability Increases Dementia Risk Among Older Adults: A Nationwide Population-Based Cohort Study

Background: Recent growing evidences suggest that body weight (Bwt) variability, a repeated loss and regain of weight within a specific period, causes metabolic disturbances and can be a marker for poor homeostasis. Although there have been many studies about the association between Bwt variability and various health status, its association with the incidence of dementia among elderly people has not been examined. Methods: We performed a retrospective elderly cohort study from 19,987 participants with mean age 73 years old in the Korean National Health Insurance Service. We examined the risk of incident dementia, including Alzheimer's dementia and vascular dementia, according to the quartile of Bwt variability, represented as coefficient of variation (Bwt-CV), SD (Bwt-SD), and variability independent of the mean (Bwt-VIM). Results: In fully adjusted model, the group with the highest Bwt variability (Bwt-VIM Q4) showed an increased risk of all-cause dementia (hazard ratio [HR] 1.39, 95% confidence interval [CI] 1.206-1.603) and Alzheimer's dementia (HR 1.46, CI 1.240-1.724) compared to the lowest quartile (Bwt-VIM Q1). We also found that subjects with the highest Bwt variability (Q4) and underweight BMI had a significantly increased risk of developing dementia (HR 1.994, 95% CI 1.302-3.054), while subjects with low Bwt variability (Q1 and Q2) and obese BMI had decreased risk of dementia (HR 0.664, 95% CI 0.505-0.872 and HR 0.648, 95% CI 0.493-0.852, respectively) compared to reference group (lowest Bwt variability (Q1) with normal baseline BMI). The effect of Bwt variability on the incidence of dementia was more prominent in subjects <75 years old and abnormal BMI groups (P for interaction < 0.05). Conclusion: The present study revealed that high Bwt variability was associated with an increased risk of dementia in the elderly.

Cox Proportional Hazard Regression Versus a Deep Learning Algorithm in the Prediction of Dementia: An Analysis Based on Periodic Health Examination

Background

With the increase in the world’s aging population, there is a growing need to prevent and predict dementia among the general population. The availability of national time-series health examination data in South Korea provides an opportunity to use deep learning algorithm, an artificial intelligence technology, to expedite the analysis of mass and sequential data.

Objective

This study aimed to compare the discriminative accuracy between a time-series deep learning algorithm and conventional statistical methods to predict all-cause dementia and Alzheimer dementia using periodic health examination data.

Methods

Diagnostic codes in medical claims data from a South Korean national health examination cohort were used to identify individuals who developed dementia or Alzheimer dementia over a 10-year period. As a result, 479,845 and 465,081 individuals, who were aged 40 to 79 years and without all-cause dementia and Alzheimer dementia, respectively, were identified at baseline. The performance of the following 3 models was compared with predictions of which individuals would develop either type of dementia: Cox proportional hazards model using only baseline data (HR-B), Cox proportional hazards model using repeated measurements (HR-R), and deep learning model using repeated measurements (DL-R).

Results

The discrimination indices (95% CI) for the HR-B, HR-R, and DL-R models to predict all-cause dementia were 0.84 (0.83-0.85), 0.87 (0.86-0.88), and 0.90 (0.90-0.90), respectively, and those to predict Alzheimer dementia were 0.87 (0.86-0.88), 0.90 (0.88-0.91), and 0.91 (0.91-0.91), respectively. The DL-R model showed the best performance, followed by the HR-R model, in predicting both types of dementia. The DL-R model was superior to the HR-R model in all validation groups tested.

Conclusions

A deep learning algorithm using time-series data can be an accurate and cost-effective method to predict dementia. A combination of deep learning and proportional hazards models might help to enhance prevention strategies for dementia.

Who is informed and who uninformed? Addressing the legal barriers to progress in dementia research and care

Conduct of research is an essential tool for the evaluation and improvement of health services. In Israel, research on persons with dementia is very limited, with the largest portion of such research involving a few surveys and examining risk factors for dementia. Very few studies describe clinical research, and those that do either include participants at early stages of dementia, or rely completely on caregivers' perceptions and experiences, often without reference to any individual with dementia. This dearth of research is due, to a substantial extent, to Ministry of Health regulations which do not permit family proxy consent for research involving persons with dementia. Alternative models for regulation of consent for research exist in other countries, including the U.S., and these allow for proxy consent under certain conditions. This paper presents such a model and its underlying ethical principles. It contends that the current state of affairs, which stands in the way of clinical research concerning persons with advanced dementia, is contrary to the interests of such persons, their caregivers, and Israeli society. Therefore, this paper calls for a change in the present regulations and/or law in the cause of advancing knowledge and improving care for persons with dementia.

Variability in metabolic parameters and risk of dementia: a nationwide population-based study

Background

Variability in biological parameters has been reported to be associated with adverse health outcomes. We aimed to investigate the composite effect of the visit-to-visit variability in blood pressure, glucose, cholesterol, and body mass index on the risk of dementia.

Methods

A population-based cohort study including 2,930,816 subjects without a history of dementia, hypertension, diabetes mellitus, and dyslipidemia who underwent ≥ 3 health examinations was performed. The coefficient of variation (CV), standard deviation, and variability independent of the mean were calculated as variability indices. High variability was defined as having values in the highest quartile for each parameter.

Results

A total of 32,901 (1.12%) participants developed dementia, of which 74.4% and 11.0% were attributable to Alzheimer’s disease and vascular dementia, respectively, during the median follow-up of 5.5 years. Individuals with higher variability of each parameter were at higher risk of future dementia. In the multivariable adjusted model, the hazard ratios and 95% confidence intervals of all-cause dementia were 1.22 (1.19–1.26) for one parameter, 1.39 (1.35–1.43) for two parameters, 1.54 (1.48–1.60) for three parameters, and 1.73 (1.60–1.88) for four parameters compared with subjects having no parameters of high variability measured as the CV. Consistent results were noted for Alzheimer’s disease and vascular dementia, using other indices of variability and in various sensitivity and subgroup analyses.

Conclusions

There was a linear association between the number of high variability parameters and risk of dementia. Reducing variability of metabolic parameters would be a target to preserve cognitive reserve in the general population.

Electronic supplementary material

The online version of this article (10.1186/s13195-018-0442-3) contains supplementary material, which is available to authorized users.

Chest width, waist circumference, and thigh circumference are predictors of dementia

OBJECTIVE

Few studies have investigated the relationship between specific body measures and dementia.

METHODS

Three-dimensional anthropometric body surface scanning data containing 38 body measures were collected from 6831 participants from the health examination department of a medical center in Taiwan during 2000 to 2008, and 236 dementia cases were identified during the 10-year follow-up. A multiple Cox regression analysis was performed.

RESULTS

Specific body measures, namely chest width (hazard ratio [HR] = 0.90; 95% confidence interval [CI] = 0.83-0.98), and right thigh circumference (HR = 0.93; 95% CI = 0.90-0.96), were protective predictors to dementia occurrence. Waist circumference (HR = 1.03; 95% CI = 1.02-1.05) was a risk factor in dementia occurrence. Among the combinations, dementia risk was higher in participants with a larger waist circumference and a smaller right thigh circumference, with the highest HR of 2.49 (95% CI = 1.54-4.03).

CONCLUSION

The body measures provide clues for future applications and scientific merits in both clinical and preventive medicine.

Body Mass Index, Height and Socioeconomic Position in Adolescence, Their Trajectories into Adulthood, and Cognitive Function in Midlife

BACKGROUND

Whether life course anthropometric indices relate to cognitive function in midlife remains insufficiently explored. Rarely was socioeconomic position (SEP) adequately accounted for.

OBJECTIVE

To examine the association of the cumulative life course burden of high-ranked body mass index (BMI), its trajectory, and stature with cognitive function in midlife.

METHODS

Weight and height were measured from age 17 across a 33-year follow-up. 507 individuals completed a NeuroTrax computerized cognitive assessment at ages 48-52. Life course SEP was assessed by multiple methods. Using mixed models we calculated the area under the curve (AUC), representing both the life-course burden of BMI (total AUC) and trends in BMI (incremental AUC) from age 17 to midlife. The associations of BMI and height with global cognition and its five component domains were assessed by multiple regression.

RESULTS

Higher BMI in late adolescence and total AUC over the life course were associated with poorer global cognition (Standardized beta (Beta) = -0.111, p = 0.005 and Beta = -0.105, p = 0.018, respectively), adjusted for childhood and adulthood SEP, and demographic characteristics. The associations with higher adolescent and midlife BMI were both restricted to those with low childhood SEP (p < 0.05 for interaction). Short adolescent stature was related to poorer cognition (Beta = 0.115, p = 0.040), whereas late final growth in women was associated with better cognition (Beta = 0.213, p = 0.007).

CONCLUSION

An adverse association of higher BMI with cognitive function began in adolescence and was restricted to low childhood SEP. Taller stature in both sexes and late growth in women were associated with better midlife cognitive performance.

The Relation of Obesity to Performance in Verbal Abilities, Processing Speed, and Cognitive Flexibility in Old Age: The Role of Cognitive Reserve

AIMS

The present study set out to investigate the relation of obesity to performance in verbal abilities, processing speed, and cognitive flexibility and its interplay with key correlates of cognitive reserve in a large sample of older adults.

METHODS

A total of 2,812 older adults served as a sample for the present study. Psychometric tests on verbal abilities, processing speed, and cognitive flexibility were administered. In addition, individuals were interviewed on their weight and height (to calculate body mass index; BMI), educational attainment, occupation, and engaging in different activities throughout adulthood.

RESULTS

Obesity (BMI ≥30) was significantly associated with a lower performance in verbal abilities, processing speed, and cognitive flexibility. Moderation analyses showed that obesity was related to lower processing speed and cognitive flexibility only in individuals with low engagement in activities and low education. Hierarchical regression analyses showed that obesity was not related to any of the three investigated cognitive performance measures when cognitive reserve in early and midlife was taken into account.

CONCLUSION

Present data suggest that cognitive reserve accumulated during the life course may reduce the detrimental influences of obesity on cognitive functioning in old age.

Computerized cognitive training for older diabetic adults at risk of dementia: Study protocol for a randomized controlled trial

Introduction

Older adults with type 2 diabetes are at high risk of cognitive decline and dementia and form an important target group for dementia risk reduction studies. Despite evidence that computerized cognitive training (CCT) may benefit cognitive performance in cognitively healthy older adults and those with mild cognitive impairment, whether CCT may benefit cognitive performance or improve disease self-management in older diabetic adults has not been studied to date. In addition, whether adaptive difficulty levels and tailoring of interventions to individuals' cognitive profile are superior to generic training remains to be established.

Methods

Ninety community-dwelling older (age ≥ 65) diabetic adults are recruited and randomized into a tailored and adaptive computerized cognitive training condition or to a generic, nontailored, or adaptive CCT condition. Both groups complete an 8-week training program using the commercially available CogniFit program. The intervention is augmented by a range of behavior-change techniques, and participants in each condition are further randomized into a global or cognition-specific phone-based self-efficacy (SE) condition, or a no-SE condition. The primary outcome is global cognitive performance immediately after the intervention. Secondary outcomes include diabetes self-management, meta-memory, mood, and SE.

Discussion

This pilot study is the first trial evaluating the potential benefits of home-based tailored and adaptive CCT in relation to cognitive and disease self-management in older diabetic adults. Methodological strengths of this trial include the double-blind design, the clear identification of the proposed active ingredients of the intervention, and the use of evidence-based behavior-change techniques. Results from this study will indicate whether CCT has the potential to lower the risk of diabetes-related cognitive decline. The outcomes of the trial will also advance our understanding of essential intervention parameters required to improve or maintain cognitive function and enhance disease self-management in this at-risk group.

Weight Change in Midlife and Risk of Mortality From Dementia up to 35 Years Later

Background

The relationship between body mass index (BMI) and dementia is complex and controversial. This study investigates the association of weight change during midlife and later dementia-related mortality.

Methods

Two BMI measurements (average of 9.0 years apart) were available for 43,721 participants in the Norwegian Counties Study (NCS), with mean age 42 years at first BMI measurement and 51 at the final measurement. NCS was linked with the Cause of Death Registry until year 2015 (mean follow-up time 25.9 years). Cox regression with a conditional growth model was used.

Results

Our study comprised 1,205 dementia-related deaths. Weight loss was associated with increased dementia-related mortality, irrespectively of baseline BMI and confounders; those with 10% or more loss had hazard ratio (HR) = 1.52 (95% confidence interval [CI]: 1.09, 2.12) compared to those being stable (0%-2.5% BMI gain), and those with 5%-10% loss had HR = 1.38 (95% CI: 1.08, 1.76). Gaining weigh was associated with reduced dementia-related mortality. Associations with BMI change did not vary by baseline BMI.

Conclusions

Weight loss during midlife was associated with increased dementia-related mortality risk more than 3 decades later, while weight gain was associated with reduced risk. These associations held both for low and high baseline BMI. Weight loss was an independent risk factor for dementia-related mortality and more strongly related with dementia-related mortality than stable BMI (stable high or low). Overweight and obesity were associated with an increased risk for nondementia-related mortality, which was far more common than dementia-related mortality.

Body mass index in midlife and dementia: Systematic review and meta-regression analysis of 589,649 men and women followed in longitudinal studies

INTRODUCTION

We conducted a meta-analysis of the conflicting epidemiologic evidence on the association between midlife body mass index (BMI) and dementia.

METHODS

We searched standard databases to identify prospective, population-based studies of dementia risk by midlife underweight, overweight, and obesity. We performed random-effects meta-analyses and meta-regressions of adjusted relative risk (RR) estimates and formally explored between-study heterogeneity.

RESULTS

We included 19 studies on 589,649 participants (2040 incident dementia cases) followed up for up to 42 years. Midlife (age 35 to 65 years) obesity (BMI ≥ 30) (RR, 1.33; 95% confidence interval [CI], 1.08-1.63), but not overweight (25 < BMI < 30) (RR, 1.07; 95% CI, 0.96-1.20), was associated with dementia in late life. The association with midlife underweight (RR, 1.39; 95% CI, 1.13-1.70) was potentially driven by residual confounding (P from meta-regression = .004), selection (P = .046), and information bias (P = .007).

DISCUSSION

Obesity in midlife increases the risk of dementia. The association between underweight and dementia remains controversial.

Effect of a long-term intensive lifestyle intervention on prevalence of cognitive impairment

OBJECTIVE

To assess whether an average of 10 years of lifestyle intervention designed to reduce weight and increase physical activity lowers the prevalence of cognitive impairment among adults at increased risk due to type 2 diabetes and obesity or overweight.

METHODS

Central adjudication of mild cognitive impairment and probable dementia was based on standardized cognitive test battery scores administered to 3,802 individuals who had been randomly assigned, with equal probability, to either the lifestyle intervention or the diabetes support and education control. When scores fell below a prespecified threshold, functional information was obtained through proxy interview.

RESULTS

Compared with control, the intensive lifestyle intervention induced and maintained marked differences in weight loss and self-reported physical activity throughout follow-up. At an average (range) of 11.4 (9.5-13.5) years after enrollment, when participants' mean age was 69.6 (54.9-87.2) years, the prevalence of mild cognitive impairment and probable dementia was 6.4% and 1.8%, respectively, in the intervention group, compared with 6.6% and 1.8%, respectively, in the control group (p = 0.93). The lack of an intervention effect on the prevalence of cognitive impairment was consistent among individuals grouped by cardiovascular disease history, diabetes duration, sex, and APOE ε4 allele status (all p ≥ 0.50). However, there was evidence (p = 0.03) that the intervention effect ranged from benefit to harm across participants ordered from lowest to highest baseline BMI.

CONCLUSIONS

Ten years of behavioral weight loss intervention did not result in an overall difference in the prevalence of cognitive impairment among overweight or obese adults with type 2 diabetes.

CLINICALTRIALSGOV IDENTIFIER

NCT00017953 (Action for Health in Diabetes).

LEVEL OF EVIDENCE

This study provides Class II evidence that for overweight adults with type 2 diabetes, a lifestyle intervention designed to reduce weight and increase physical activity does not lower the risk of cognitive impairment.

Triceps and Subscapular Skinfold in Men Aged 40-65 and Dementia Prevalence 36 Years Later

BACKGROUND

The relationship of obesity with risk for dementia is complex and may change with age.

OBJECTIVE

To analyze the relationship between measures of obesity at age 40-65 and dementia prevalence in survivors 36 years later.

METHODS

Obesity-related measures of triceps and subscapular skinfold thickness were assessed in 1963 in n = 9,760 men aged 40-65 participating in the Israel Ischemic Heart Disease study. Cognitive evaluation and assessment of dementia prevalence were performed in n = 1,643 participants of the original cohort who survived until 1999/2000 (age ≥76 years) and had anthropometric measures in 1963.

RESULTS

Age-adjusted prevalence of dementia in survivors in 1999/2000 by baseline triceps skinfold quintile was 20.5%, 21.2%, 17.6%, 15.6%, and 14.5%, respectively, from lowest to highest (p = 0.006 in trend test). Using logistic regression, a 6-mm increment of triceps skinfold was associated with an age and BMI-adjusted odds ratio of 0.81 (95% CI, 0.70-0.94) for dementia prevalence among survivors. Age-adjusted risk for dementia by subscapular skinfold quintile demonstrated 20.5%, 17.1%, 15.7%, 19.4%, and 18.1%, respectively, in groups of subjects by subscapular skinfold quintile from lowest to highest (p = 0.6 in trend test).

CONCLUSIONS

Lower triceps skinfold at age 40-65, reflecting diminished peripheral fat, was associated with higher dementia prevalence in late life, potentially suggesting a protective role of peripheral fat to brain health.

Behavioural Risk Factors in Mid-Life Associated with Successful Ageing, Disability, Dementia and Frailty in Later Life: A Rapid Systematic Review

BACKGROUND

Smoking, alcohol consumption, poor diet and low levels of physical activity significantly contribute to the burden of illness in developed countries. Whilst the links between specific and multiple risk behaviours and individual chronic conditions are well documented, the impact of these behaviours in mid-life across a range of later life outcomes has yet to be comprehensively assessed. This review aimed to provide an overview of behavioural risk factors in mid-life that are associated with successful ageing and the primary prevention or delay of disability, dementia, frailty and non-communicable chronic conditions.

METHODS

A literature search was conducted to identify cohort studies published in English since 2000 up to Dec 2014. Multivariate analyses and a minimum follow-up of five years were required for inclusion. Two reviewers screened titles, abstracts and papers independently. Studies were assessed for quality. Evidence was synthesised by mid-life behavioural risk for a range of late life outcomes.

FINDINGS

This search located 10,338 individual references, of which 164 are included in this review. Follow-up data ranged from five years to 36 years. Outcomes include dementia, frailty, disability and cardiovascular disease. There is consistent evidence of beneficial associations between mid-life physical activity, healthy ageing and disease outcomes. Across all populations studied there is consistent evidence that mid-life smoking has a detrimental effect on health. Evidence specific to alcohol consumption was mixed. Limited, but supportive, evidence was available relating specifically to mid-life diet, leisure and social activities or health inequalities.

CONCLUSIONS

There is consistent evidence of associations between mid-life behaviours and a range of late life outcomes. The promotion of physical activity, healthy diet and smoking cessation in all mid-life populations should be encouraged for successful ageing and the prevention of disability and chronic disease.

The risk of overweight/obesity in mid-life and late life for the development of dementia: a systematic review and meta-analysis of longitudinal studies

SCOPE

it has been suggested that overweight/obesity as a risk factor for incident dementia differs between mid-life and later life. We performed a systematic review and meta-analysis of the up-to-date current literature to assess this.

SEARCH METHODS

inclusion criteria included epidemiological longitudinal studies published up to September 2014, in participants without cognitive impairment based on evidence of cognitive assessment and aged 30 or over at baseline assessment with at least 2 years of follow-up. Pubmed, Medline, EMBASE, PsychInfo and the Cochrane Library were searched using combinations of the search terms: Dementia, Alzheimer disease, Vascular Dementia, Multi-Infarct Dementia, Cognitive decline, Cognitive impairment, Mild Cognitive Impairment/Obesity, Overweight, Adiposity, Waist circumference (limits: humans, English language). Handsearching of all papers meeting the inclusion criteria was performed. A random-effects model was used for the meta-analysis.

RESULTS

of the 1,612 abstracts identified and reviewed, 21 completely met the inclusion criteria. Being obese below the age of 65 years had a positive association on incident dementia with a risk ratio (RR) 1.41 (95% confidence interval, CI: 1.20-1.66), but the opposite was seen in those aged 65 and over, RR 0.83 (95% CI: 0.74-0.94).

CONCLUSIONS

this systematic review and meta-analysis suggests a positive association between obesity in mid-life and later dementia but the opposite in late life. Whether weight reduction in mid-life reduces risk is worthy of further study.

Adipocyte-derived factors in age-related dementia and their contribution to vascular and Alzheimer pathology

Age-related dementia is increasingly recognized as having a mixed pathology, with contributions from both cerebrovascular factors and pathogenic factors associated with Alzheimer's disease (AD). Furthermore, there is accumulating evidence that vascular risk factors in midlife, e.g., obesity, diabetes, and hypertension, increase the risk of developing late-life dementia. Since obesity and changes in body weight/adiposity often drive diabetes and hypertension, understanding the relationship between adiposity and age-related dementia may reveal common underlying mechanisms. Here we offer a brief appraisal of how changes in body weight and adiposity are related to both AD and dementia on vascular basis, and examine the involvement of two key adipocyte-derived hormones: leptin and adiponectin. The evidence suggests that in midlife increased body weight/adiposity and subsequent changes in adipocyte-derived hormones may increase the long-term susceptibility to dementia. On the other hand, later in life, decreases in body weight/adiposity and related hormonal changes are early manifestations of disease that precede the onset of dementia and may promote AD and vascular pathology. Understanding the contribution of adiposity to age-related dementia may help identify the underlying pathological mechanisms common to both vascular dementia and AD, and provide new putative targets for early diagnosis and therapy. This article is part of a Special Issue entitled: Vascular Contributions to Cognitive Impairment and Dementia, edited by M. Paul Murphy, Roderick A. Corriveau and Donna M. Wilcock.

The interactive effects of age, education, and BMI on cognitive functioning

We examined the moderating effects of age and cognitive reserve on the relationship between body mass index (BMI) and processing speed, executive function, and working memory based on the literature suggesting that obese individuals perform more poorly on measures of these abilities. Fifty-six healthy, dementia-free community-dwelling older (mean age 65.72 ± 7.40) and younger (mean age 21.10 ± 2.33) adults completed a neuropsychological battery and reported height and weight. Mixed effects models were used to evaluate the interactive effects of age, education (a proxy for cognitive reserve), and BMI on cognitive scores. Higher education was protective for executive deficits in younger, but not older adults. Age differences in executive functions were reduced at higher education levels but increased in individuals with higher BMI. Results suggest the inter-relationships between cognitive reserve - as measured by education - and BMI differ across age, and that obesity may accelerate the cognitive aging process.

BMI and risk of dementia in two million people over two decades: a retrospective cohort study

BACKGROUND

Dementia and obesity are increasingly important public health issues. Obesity in middle age has been proposed to lead to dementia in old age. We investigated the association between BMI and risk of dementia.

METHODS

For this retrospective cohort study, we used a cohort of 1,958,191 individuals derived from the United Kingdom Clinical Practice Research Datalink (CPRD) which included people aged 40 years or older in whom BMI was recorded between 1992 and 2007. Follow-up was until the practice's final data collection date, patient death or transfer out of practice, or first record of dementia (whichever occurred first). People with a previous record of dementia were excluded. We used Poisson regression to calculate incidence rates of dementia for each BMI category.

FINDINGS

Our cohort of 1,958,191 people from UK general practices had a median age at baseline of 55 years (IQR 45-66) and a median follow-up of 9·1 years (IQR 6·3-12·6). Dementia occurred in 45,507 people, at a rate of 2·4 cases per 1000 person-years. Compared with people of a healthy weight, underweight people (BMI <20 kg/m(2)) had a 34% higher (95% CI 29-38) risk of dementia. Furthermore, the incidence of dementia continued to fall for every increasing BMI category, with very obese people (BMI >40 kg/m(2)) having a 29% lower (95% CI 22-36) dementia risk than people of a healthy weight. These patterns persisted throughout two decades of follow-up, after adjustment for potential confounders and allowance for the J-shape association of BMI with mortality.

INTERPRETATION

Being underweight in middle age and old age carries an increased risk of dementia over two decades. Our results contradict the hypothesis that obesity in middle age could increase the risk of dementia in old age. The reasons for and public health consequences of these findings need further investigation.

FUNDING

None.

Reward components of feeding behavior are preserved during mouse aging

Eating behavior depends on associations between the sensory and energetic properties of foods. Healthful balance of these factors is a challenge for industrialized societies that have an abundance of food, food choices and food-related cues. Here, we were interested in whether appetitive conditioning changes as a function of age. Operant and pavlovian conditioning experiments (rewarding stimulus was a palatable food) in male mice (aged 3, 6, and 15 months) showed that implicit (non-declarative) memory remains intact during aging. Two other essential components of eating behavior, motivation and hedonic preference for rewarding foods, were also found not to be altered in aging mice. Specifically, hedonic responding by satiated mice to isocaloric foods of differing sensory properties (sucrose, milk) was similar in all age groups; importantly, however, this paradigm disclosed that older animals adjust their energy intake according to energetic need. Based on the assumption that the mechanisms that control feeding are conserved across species, it would appear that overeating and obesity in humans reflects a mismatch between ancient physiological mechanisms and today's cue-laden environment. The implication of the present results showing that aging does not impair the ability to learn stimulus-food associations is that the risk of overeating in response to food cues is maintained through to old age.