Association between late-life body mass index and dementia: The Kame Project

The Association Between Physical Activity, Obesity, and Cognition in Middle-Aged and Older Adults

As rates of obesity continue to rise, so does the impact of obesity on cognitive function. Engaging in physical activity is one pathway through which individuals can help maintain cognitive function. This study examined whether any link between exercise and cognitive function was associated with weight characteristics. Data from 6,012 participants in the Health and Retirement Study were used. The association between participation in light or moderate physical activity and better cognitive function was particularly strong for overweight or obese adults and less so for those who were normal weight. Overall, the findings suggested that while being physically active is associated with better cognitive function regardless of weight, the associations were stronger for individuals who were overweight/obese compared with those who were normal weight. Given the results were particularly pronounced for waist circumference (relative to body mass index), further research should be conducted to examine if individuals with greater abdominal adiposity may benefit most from staying active in terms of their cognitive function.

Obesity pharmacotherapy in older adults: a narrative review of evidence

The prevalence of obesity in older adults (people aged >60 years) is increasing in line with the demographic shift in global populations. Despite knowledge of obesity-related complications in younger adults (increased risk of type 2 diabetes, liver and cardiovascular disease and malignancy), these considerations may be outweighed, in older adults, by concerns regarding weight-loss induced reduction in skeletal muscle and bone mass, and the awareness of the 'obesity paradox'. Obesity in the elderly contributes to various obesity-related complications from cardiometabolic disease and cancer, to functional decline, worsening cognition, and quality of life, that will have already suffered an age-related decline. Lifestyle interventions remain the cornerstone of obesity management in older adults, with emphasis on resistance training for muscle strength and bone mineral density preservation. However, in older adults with obesity refractory to lifestyle strategies, pharmacotherapy, using anti-obesity medicines (AOMs), can be a useful adjunct. Recent evidence suggests that intentional weight loss in older adults with overweight and obesity is effective and safe, hence a diminishing reluctance to use AOMs in this more vulnerable population. Despite nine AOMs being currently approved for the treatment of obesity, limited clinical trial evidence in older adults predominantly focuses on incretin therapy with glucagon-like peptide-1 receptor agonists (liraglutide, semaglutide, and tirzepatide). AOMs enhance weight loss and reduce cardiometabolic events, while maintaining muscle mass. Future randomised controlled trials should specifically evaluate the effectiveness of novel AOMs for long-term weight management in older adults with obesity, carefully considering the impact on body composition and functional ability, as well as health economics.

Childhood obesity and risk of Alzheimer's disease: a Mendelian randomization study

BACKGROUND

Midlife obesity is a modifiable risk factor for Alzheimer's disease. However, the association between childhood obesity and Alzheimer's disease remains largely unknown. Therefore, we conducted a mendelian randomization analysis (MR) to assess the causal link between childhood obesity and Alzheimer's disease.

METHODS

Using summary statistics from publicly available genome-wide association studies (GWAS) database, we explored the genetic link between childhood obesity and Alzheimer's disease through a two-sample MR. The primary analysis employed the inverse-variance weighted (IVW) method. To complement our findings, we also employed MR-Egger, weighted median, simple model, and weighted model methods for MR estimates. Furthermore, we conducted Cochrane's Q-statistic test, Egger intercept test, and a leave-one-out sensitivity test to ensure the robustness and reliability of our results.

RESULTS

The IVW analysis yielded non-significant results, indicating no significant genetic association between childhood obesity and Alzheimer's disease (OR = 0.958, 95% CI = 0.910-1.008, p = 0.095). Consistent with this, the results from MR-Egger, the weighted median, simple model, and weighted model approaches all supported these findings. Furthermore, we did not detect any signs of heterogeneity or pleiotropy, and our leave-one-out analysis confirmed that no single nucleotide polymorphisms had a substantial impact on the reliability of our results.

CONCLUSIONS

The evidence from our MR analyses suggests that there is no causal effect of childhood obesity on the risk of Alzheimer's disease.

Liver integrity and the risk of Alzheimer's disease and related dementias

INTRODUCTION

We examined midlife (1990-1992, mean age 57) and late-life (2011-2013, mean age 75) nonalcoholic fatty liver disease (NAFLD) and aminotransferase with incident dementia risk through 2019 in the Atherosclerosis Risk in Communities (ARIC) Study.

METHODS

We characterized NAFLD using the fatty liver index and fibrosis-4, and we categorized aminotransferase using the optimal equal-hazard ratio (HR) approach. We estimated HRs for incident dementia ascertained from multiple data sources.

RESULTS

Adjusted for demographics, alcohol consumption, and kidney function, individuals with low, intermediate, and high liver fibrosis in midlife (HRs: 1.45, 1.40, and 2.25, respectively), but not at older age, had higher dementia risks than individuals without fatty liver. A U-shaped association was observed for alanine aminotransferase with dementia risk, which was more pronounced in late-life assessment.

DISCUSSION

Our findings highlight dementia burden in high-prevalent NAFLD and the important feature of late-life aminotransaminase as a surrogate biomarker linking liver hypometabolism to dementia. Highlights Although evidence of liver involvement in dementia development has been documented in animal studies, the evidence in humans is limited. Midlife NAFLD raised dementia risk proportionate to severity. Late-life NAFLD was not associated with a high risk of dementia. Low alanine aminotransferase was associated with an elevated dementia risk, especially when measured in late life.

Inflammatory Pathways in Overweight and Obese Persons as a Potential Mechanism for Cognitive Impairment and Earlier Onset Alzeihmer's Dementia in the General Population: A Narrative Review

The overweight status or obesity can be confirmed through classical methods such as the body mass index (BMI) and the waist-to-hip ratio (WHR). Apart from metabolic issues such as atherosclerosis, liver steatosis, or diabetes mellitus, long-term obesity or overweight status can pose a risk for cardiovascular and neurovascular complications. While some acute adverse events like coronary syndromes of strokes are well-documented to be linked to an increased body mass, there are also chronic processes that, due to their silent onset and evolution, are underdiagnosed and not as thoroughly studied. Through this review, we aimed to collect all relevant data with regard to the long-term impact of obesity on cognitive function in all ages and its correlation with an earlier onset of dementia such as Alzheimer's disease (AD). The exact mechanisms through which a decline in cognitive functions occurs in overweight or obese persons are still being discussed. A combination of factors has been acknowledged as potential triggers, such as a sedentary lifestyle and stress, as well as a genetic predisposition, for example, the apolipoprotein E (ApoE) alleles in AD. Most research highlights the impact of vascular dysfunction and systemic inflammation on the nervous system in patients with obesity and the subsequent neurological changes. Obesity during the early to mid-ages leads to an earlier onset of cognitive dysfunction in various forms. Also, lifestyle intervention can reverse cognitive dysfunction, especially dieting, to encourage weight loss.

Weight loss and risk of dementia in individuals with versus without obesity

INTRODUCTION

Using nationwide cohort data, we aimed to elucidate whether baseline obesity altered the relationship between loss in body mass index (BMI) or waist circumference (WC) and risk of dementia.

METHODS

Among 9689 participants whose BMIs and WCs were repeatedly measured over 1 year, 1:1 propensity score matching was conducted between participants with and without obesity (n = 2976 per group, mean age 70.9). For each group, we explored the association between loss in BMI, or WC, and incidence of dementia during an approximately 4-year follow-up period.

RESULTS

BMI loss was associated with an increased risk of all-cause dementia and Alzheimer's disease in participants without obesity; however, this association was absent in participants with obesity. WC loss was associated with decreased Alzheimer's disease risk only in participants with obesity.

DISCUSSION

Only unfavorable loss (loss from non-obese state) in BMI, not WC, can be a metabolic biomarker of prodromal dementia.

The complex relationship between obesity and neurodegenerative diseases: an updated review

Obesity is a global epidemic, affecting roughly 30% of the world's population and predicted to rise. This disease results from genetic, behavioral, societal, and environmental factors, leading to excessive fat accumulation, due to insufficient energy expenditure. The adipose tissue, once seen as a simple storage depot, is now recognized as a complex organ with various functions, including hormone regulation and modulation of metabolism, inflammation, and homeostasis. Obesity is associated with a low-grade inflammatory state and has been linked to neurodegenerative diseases like multiple sclerosis (MS), Alzheimer's (AD), and Parkinson's (PD). Mechanistically, reduced adipose expandability leads to hypertrophic adipocytes, triggering inflammation, insulin and leptin resistance, blood-brain barrier disruption, altered brain metabolism, neuronal inflammation, brain atrophy, and cognitive decline. Obesity impacts neurodegenerative disorders through shared underlying mechanisms, underscoring its potential as a modifiable risk factor for these diseases. Nevertheless, further research is needed to fully grasp the intricate connections between obesity and neurodegeneration. Collaborative efforts in this field hold promise for innovative strategies to address this complex relationship and develop effective prevention and treatment methods, which also includes specific diets and physical activities, ultimately improving quality of life and health.

Body mass index and two-year change of in vivo Alzheimer's disease pathologies in cognitively normal older adults

BACKGROUND

Low body mass index (BMI) or underweight status in late life is associated with an increased risk of dementia or Alzheimer's disease (AD). However, the relationship between late-life BMI and prospective longitudinal changes of in-vivo AD pathology has not been investigated.

METHODS

This prospective longitudinal study was conducted as part of the Korean Brain Aging Study for Early Diagnosis and Prediction of Alzheimer's Disease (KBASE). A total of 194 cognitive normal older adults were included in the analysis. BMI at baseline was measured, and two-year changes in brain Aβ and tau deposition on PET imaging were used as the main outcomes. Linear mixed-effects (LME) models were used to examine the relationships between late-life BMI and longitudinal change in AD neuropathological biomarkers.

RESULTS

A lower BMI at baseline was significantly associated with a greater increase in tau deposition in AD-signature region over 2 years (β, -0.018; 95% CI, -0.028 to -0.004; p = .008), In contrast, BMI was not related to two-year changes in global Aβ deposition (β, 0.0002; 95% CI, -0.003 to 0.002, p = .671). An additional exploratory analysis for each sex showed lower baseline BMI was associated with greater increases in tau deposition in males (β, -0.027; 95% CI, -0.046 to -0.009; p = 0.007), but not in females.

DISCUSSION

The findings suggest that lower BMI in late-life may predict or contribute to the progression of tau pathology over the subsequent years in cognitively unimpaired older adults.

Body Mass Index and Cognition: Associations Across Mid- to Late Life and Gender Differences

BACKGROUND

Higher mid-life body mass index (BMI) is associated with lower late-life cognition. Associations between later-life BMI and cognition are less consistent; evidence suggests reverse causation may play a role. We aimed to characterize associations between BMI and cognition across a wide age range during mid- to late life (55-85 years) and examine whether associations vary by gender.

METHODS

We used data from the Health and Retirement Study (HRS) (N = 39,153) to examine the association between BMI and 3 cognitive outcomes: cognitive level, cognitive decline, and cognitive impairment. We used a series of linear regression, mixed effects regression, and logistic regression models, adjusting for potential confounders.

RESULTS

Higher BMI before age 65 (midlife) was associated with lower cognitive performance, faster rates of cognitive decline, and higher odds of cognitive impairment in late life. Averaging across analyses assessing associations between BMI measured before age 60 and late-life cognition, a 5-unit higher level of BMI was associated with a 0.26 point lower cognitive score. Beyond age 65, associations flipped, and higher BMI was associated with better late-life cognitive outcomes. Associations in both directions were stronger in women. Excluding those with BMI loss attenuated findings among women in older ages, supporting the reverse causation hypothesis.

CONCLUSIONS

In this sample, age 65 represented a critical turning point between mid- and late life for the association between BMI and cognition, which has important implications for recruitment strategies for studies focused on risk factors for late-life cognitive outcomes. Evidence of gender differences raises the need to further investigate plausible mechanisms.

Nonalcoholic fatty liver disease and cognitive impairment: A prospective cohort study

BACKGROUND & AIMS

Nonalcoholic fatty liver disease (NAFLD) is prevalent and may affect cognitive function. We studied associations of NAFLD with risk of cognitive impairment. Secondarily we evaluated liver biomarkers (alanine aminotransferase (ALT), aspartate aminotransferase (AST), their ratio, and gamma-glutamyl transpeptidase).

METHODS

In a prospective cohort study, the REasons for Geographic and Racial Differences in Stroke, among 30,239 black and white adults aged ≥45,495 cases of incident cognitive impairment were identified over 3.4 years follow up. Cognitive impairment was identified as new impairment in two of three cognitive tests administered every two years during follow up; word list learning and recall, and verbal fluency. 587 controls were selected from an age, race, sex-stratified sample of the cohort. The fatty liver index was used to define baseline NAFLD. Liver biomarkers were measured using baseline blood samples.

RESULTS

NAFLD at baseline was associated with a 2.01-fold increased risk of incident cognitive impairment in a minimally adjusted model (95% CI 1.42, 2.85). The association was largest in those aged 45-65 (p interaction by age = 0.03), with the risk 2.95-fold increased (95% CI 1.05, 8.34) adjusting for cardiovascular, stroke and metabolic risk factors. Liver biomarkers were not associated with cognitive impairment, except AST/ALT >2, with an adjusted OR 1.86 (95% CI 0.81, 4.25) that did not differ by age.

CONCLUSIONS

A laboratory-based estimate of NAFLD was associated with development of cognitive impairment, particularly in mid-life, with a tripling in risk. Given its high prevalence, NAFLD may be a major reversible determinant of cognitive health.

Metabolically Healthy Overweight and Obesity, Transition to Metabolically Unhealthy Status and Cognitive Function: Results from the Framingham Offspring Study

AIMS

To evaluate the association between metabolically healthy overweight/obesity (MHO) status and longitudinal cognitive function while also considering the stability of the condition.

METHODS

In total, 2892 participants (mean age 60.7 (9.4) years) from Framingham Offspring Study completed health assessments every four years since 1971. Neuropsychological testing was repeated every four years starting from 1999 (Exam 7) to 2014 (Exam 9) (mean follow-up: 12.9 (3.5) years). Standardized neuropsychological tests were constructed into three factor scores (general cognitive performance, memory, processing speed/executive function). Healthy metabolic status was defined as the absence of all NCEP ATP III (2005) criteria (excluding waist circumference). MHO participants who scored positively for one or more of NCEP ATPIII parameters in the follow-up period were defined as unresilient MHO.

RESULTS

No significant difference on the change in cognitive function over time was observed between MHO and metabolically healthy normal weight (MHN) individuals (all p > 0.05). However, a lower processing speed/executive functioning scale score was observed in unresilient MHO participants compared to resilient MHO participants (β = -0.76; 95% CI = -1.44, -0.08; p = 0.030).

CONCLUSIONS

Retaining a healthy metabolic status over time represents a more important discriminant in shaping cognitive function compared to body weight alone.

Obesity-Induced Brain Neuroinflammatory and Mitochondrial Changes

Obesity is defined as abnormal and excessive fat accumulation, and it is a risk factor for developing metabolic and neurodegenerative diseases and cognitive deficits. Obesity is caused by an imbalance in energy homeostasis resulting from increased caloric intake associated with a sedentary lifestyle. However, the entire physiopathology linking obesity with neurodegeneration and cognitive decline has not yet been elucidated. During the progression of obesity, adipose tissue undergoes immune, metabolic, and functional changes that induce chronic low-grade inflammation. It has been proposed that inflammatory processes may participate in both the peripheral disorders and brain disorders associated with obesity, including the development of cognitive deficits. In addition, mitochondrial dysfunction is related to inflammation and oxidative stress, causing cellular oxidative damage. Preclinical and clinical studies of obesity and metabolic disorders have demonstrated mitochondrial brain dysfunction. Since neuronal cells have a high energy demand and mitochondria play an important role in maintaining a constant energy supply, impairments in mitochondrial activity lead to neuronal damage and dysfunction and, consequently, to neurotoxicity. In this review, we highlight the effect of obesity and high-fat diet consumption on brain neuroinflammation and mitochondrial changes as a link between metabolic dysfunction and cognitive decline.

Poor Cognitive Agility Conservation in Obese Aging People

Life expectancy has been boosted in recent decades at expenses of increasing the age-associated diseases. Dementia, for its incidence, stands out among the pathologies associated with aging. The exacerbated cognitive deterioration disables people from carrying out their daily lives autonomously and this incidence increases exponentially after 65 years of age. The etiology of dementia is a miscellaneous combination of risk factors that restrain the quality of life of our elderly. In this sense, it has been established that some metabolic pathologies such as obesity and diabetes act as a risk factor for dementia development. In contrast, a high educational level, as well as moderate physical activity, have been shown to be protective factors against cognitive impairment and the development of dementia. In the present study, we have evaluated the metabolic composition of a population between 60-90 years old, mentally healthy and with high academic degrees. After assessing agility in mental state, we have established relationships between their cognitive abilities and their body composition. Our data support that excess body fat is associated with poorer maintenance of cognition, while higher percentages of muscle mass are associated with the best results in the cognitive tests.

Relationship Between Cognitive Performance, Physical Activity, and Socio-Demographic/Individual Characteristics Among Aging Americans

BACKGROUND

Physical activity (PA) has emerged as a promising approach to delay Alzheimer's disease and related dementias, but the optimal intensity of PA to improve cognitive health remains unknown.

OBJECTIVE

To evaluate the association between duration and intensity of PA and cognitive domains (executive function, processing speed, and memory) in aging Americans.

METHODS

Linear regressions in hierarchical blocks for variable adjustment and the size of effect (η2) were analyzed by using the data of 2,377 adults (age = 69.3±6.7 years) from the NHANES 2011-2014.

RESULTS

Participants with 3-6 h/week of vigorous- and > 1 h/week of moderate-intensity PA scored significantly higher in executive function and processing speed domains of cognition compared to inactive peers (η2 = 0.005 & 0.007 respectively, p < 0.05). After adjustment, the beneficial effects of 1-3 h /week of vigorous-intensity PA became trivial for delayed recall memory domain test scores (β= 0.33; 95% CI: -0.01,0.67; η2 = 0.002; p = 0.56). There was no linear dose-response relationship between the cognitive test scores and weekly moderate-intensity of PA. Interestingly, higher handgrip strength and higher late-life body mass index were associated with a higher performance across all cognitive domains.

CONCLUSION

Our study supports habitual PA with superior cognition health in some but not all domains among older adults. Furthermore, increased muscle strength and higher late-life adiposity may also impact cognition.

Obesity in Late-Life as a Protective Factor Against Dementia and Dementia-Related Mortality

OBJECTIVE

We estimated the conversion from cognitively normal to mild cognitive impairment (MCI) to probable dementia and death for underweight, normal, overweight, and obese older adults, where the timing of examinations is associated with the severity of dementia.

METHODS

We analyzed six waves of the National Health and Aging Trends Study (NHATS). Body mass (BMI) was computed from height and weight. Multi-state survival models (MSMs) examined misclassification probability, time-to-event ratios, and cognitive decline.

RESULTS

Participants (n = 6078) were 77 years old, 62% had overweight and/or obese BMI. After adjusting for the effects of cardiometabolic factors, age, sex, and race, obesity was protective against developing dementia (aHR=.44; 95%CI [.29-.67]) and dementia-related mortality (aHR=.63; 95%CI [.42-.95]).

DISCUSSION

We found a negative relationship between obesity and dementia and dementia-related mortality, a finding that has been underreported in the literature. The continuing obesity epidemic might complicate the diagnosis and treatment of dementia.

[Diagnosis and treatment of obesity disease in older adults]

In Japan, the proportion of older adults with obesity is rising, highlighting the need for specialized medical care for older adults with obesity. The Japan Society for the Study of Obesity (JASSO) defines 'obesity' as excessive fat storage in adipose tissue with body mass index (BMI) ≥ 25 kg/m2, and "Obesity Disease" as a condition with health disorders associated with obesity and/or visceral fat accumulation.The term 'high-degree obesity' applies to those with BMI≥ 35 kg/m2, and "Obesity Disease" with high-degree obesity is defined as "high-degree Obesity Disease".While the diagnostic criteria for "Obesity Disease" are same regardless of age group, older adults have unique problems. For example, BMI may not accurately reflect fat mass due to age-related height changes and other factors like edema. There's also an 'obesity paradox' in the older adults, where higher BMI may correlate with reduced mortality, though visceral fat is a risk factor.Weight reduction goal is 3% or more of body weight in 3-6 months for "Obesity Disease" and 5-10% or more for "high-degree Obesity Disease" . Management may include calorie-controlled diets and resistance exercises to prevent bone and muscle loss. Advanced treatment options like bariatric/metabolic surgery are also available for "high-degree Obesity Disease" .Recent guidelines from the Japan Geriatrics Society and JASSO provide insights into managing "Obesity Disease" among older adults, considering specific issues like dementia and functional decline. Future therapy need to evolve and provide individualized approaches to manage obesity for older adults.

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.

Dynamic functional connectivity patterns associated with dementia risk

Background

This study assesses the relationships between dynamic functional network connectivity (DFNC) and dementia risk.

Methods

DFNC of the default mode (DMN), salience (SN), and executive control networks was assessed in 127 cognitively unimpaired older adults. Stepwise regressions were performed with dementia risk and protective factors and biomarkers as predictors of DFNC.

Results

Associations were found between times spent in (i) a “weakly connected” state and lower self-reported engagement in early- and mid-life cognitive activity and higher LDL cholesterol; (ii) a “SN-negatively connected” state and higher blood pressure, higher depression score, and lower body mass index (BMI); (iii) a “strongly connected” state and higher self-reported engagement in early-life cognitive activity, Preclinical Alzheimer’s cognitive composite-5 score, and BMI; and (iv) a “DMN-negatively connected” state and higher self-reported engagement in early- and mid-life stimulating activities and lower LDL cholesterol and blood pressure. The lower number of state transitions was associated with lower brain perfusion.

Conclusion

DFNC states are differentially associated with dementia risk and could underlie reserve.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13195-022-01006-7.

Adiposity in the older population and the risk of dementia: The Rotterdam Study

INTRODUCTION

We determined associations of total and regional adiposity with incident dementia among older adults.

METHODS

Within the population-based Rotterdam Study, adiposity was measured as total, android, and gynoid fat mass using dual-energy X-ray absorptiometry in 3408 men and 4563 women, every 3 to 6 years between 2002 and 2016. Incident dementia was recorded until 2020.

RESULTS

Higher adiposity measures were associated with a decreased risk of dementia in both sexes. After excluding the first 5 years of follow-up, only the association of gynoid fat among women remained significant (hazard ratio 0.85 [95% confidence interval 0.75-0.97] per standard deviation increase). No major differences in trajectories of adiposity measures were observed between dementia cases and dementia-free controls.

DISCUSSION

Higher total and regional fat mass related to a decreased risk of dementia. These results may be explained by reverse causality, although a protective effect of adiposity cannot be excluded.

HIGHLIGHTS

Total and regional adiposity were assessed using dual-energy X-ray absorptiometry scans in 7971 older adults. All adiposity measures were associated with a decreased risk of dementia. The results suggest a beneficial effect of gynoid fat on the risk of dementia in women. Reverse causation and competing risk may explain these inverse associations.

Association of late-life body mass index with the risk of Alzheimer disease: a 10-year nationwide population-based cohort study

Existing data for the association between late-life body mass index (BMI) and the risk of Alzheimer’s disease (AD) in the underweight population are limited with conflicting results. A large population-based cohort study of 148,534 individuals aged ≥ 65 years who participated in the national health screening program from 2002 to 2005 was performed using the Korean National Health Insurance Service-Senior cohort database 2006–2015. The risk of AD according to BMI category (kg/m²) in Asians was evaluated using a multivariable Cox regression model, after adjustments for age, sex, lifestyle, low-income status, and comorbidities. To evaluate the association between BMI and AD risk, the underweight population was further subdivided according to the degree of thinness. During the 10-year follow-up period, 22,279 individuals developed AD. Relative to the normal-weight population, the estimated adjusted hazard ratio (HR) for incident AD in the underweight, overweight, and obese populations was 1.17 (95% confidence interval [CI], 1.09–1.24), 0.90 (0.87–0.93), and 0.83 (0.80–0.85), respectively. In the underweight population, AD risk increased as the degree of thinness increased (p for the trend, < .001). Late-life BMI showed a significant inverse relationship with AD risk, especially in the underweight population. Public health strategies to screen for AD more actively in the underweight population and improve their weight status may help reduce the burden of AD.

Pathogenesis, Murine Models, and Clinical Implications of Metabolically Healthy Obesity

Although obesity is commonly associated with numerous cardiometabolic pathologies, some people with obesity are resistant to detrimental effects of excess body fat, which constitutes a condition called “metabolically healthy obesity” (MHO). Metabolic features of MHO that distinguish it from metabolically unhealthy obesity (MUO) include differences in the fat distribution, adipokine types, and levels of chronic inflammation. Murine models are available that mimic the phenotype of human MHO, with increased adiposity but preserved insulin sensitivity. Clinically, there is no established definition of MHO yet. Despite the lack of a uniform definition, most studies describe MHO as a particular case of obesity with no or only one metabolic syndrome components and lower levels of insulin resistance or inflammatory markers. Another clinical viewpoint is the dynamic and changing nature of MHO, which substantially impacts the clinical outcome. In this review, we explore the pathophysiology and some murine models of MHO. The definition, variability, and clinical implications of the MHO phenotype are also discussed. Understanding the characteristics that differentiate people with MHO from those with MUO can lead to new insights into the mechanisms behind obesity-related metabolic derangements and diseases.

Organized Registration for the Assessment of Dementia by the Nationwide General Consortium Toward Effective Treatment (ORANGE) Registry: Current Status and Perspectives of Mild Cognitive Impairment

Background: With increasingly aging societies, a comprehensive strategy for dementia research is important. The Organized Registration for the Assessment of dementia by the Nationwide General consortium toward Effective treatment (ORANGE) Registry is the first longitudinal multicenter prospective trial-ready cohort in Japan. Objective: To establish a large cohort for use in clinical trials and research in Japan. Methods: This registry, based on communities, hospitals, and nursing homes, covers three dementia stages (preclinical, mild cognitive impairment [MCI], and advanced dementia), and includes more than 30 hospitals. We analyzed enrollment and 1-year follow-up data for disease progression. Results: There were 1450 registered patients (649 men, 801 women; mean age, 77.92±6.70 years; mean Mini-Mental State Examination [MMSE] score, 25.19±2.76). The conversion rates from MCI to dementia and MCI to normal were 14.3% and 1.1%, respectively. High Clinical Dementia Rating score (odds ratio [OR] = 11.085, 95% confidence interval [CI]:1.619–75.913, p = 0.014), low MMSE score (OR = 0.835, 95% CI: 0.761–0.917, p <  0.001), high Geriatric Depression Scale score (OR = 1.093, 95% CI: 1.005–1.189, p = 0.038), and low body mass index (OR = 0.895, 95% CI: 0.829–0.967, p = 0.005) at enrollment were significant factors for conversion. Conclusion: The ORANGE MCI Registry is an established registry that facilitates creation of trial-ready cohorts to accelerate promotion of clinical trials with low reversion rates as it originates from a hospital. One-year follow-up analysis suggested assessing various factors for conversion risk. Further analyses will be possible in future with registry expansion. We will continue to refine this registry, including how it can be used more efficiently.

Sex-Differential Associations Between Body Mass Index and the Incidence of Dementia

BACKGROUND

Little is known about the sex differences in the association between body mass index (BMI) and dementia in late life.

OBJECTIVE

Therefore, this retrospective cohort study aimed to analyze associations between BMI and dementia in older women and men separately in general practices in Germany.

METHODS

This study included patients followed in one of 832 general practices in Germany between 2006 and 2019 (index date: first visit date). Study variables included dementia (dependent variable), BMI (independent variable), age, sex, and comorbidities (control variables). Kaplan-Meier curves and adjusted Cox regression analyses were conducted to analyze associations between BMI and the 10-year incidence of dementia in women and men, separately.

RESULTS

There were 296,767 patients included in this study (mean [standard deviation] age 70.2 [5.9] years; 54.3% women). The proportion of underweight, normal weight, overweight, and obesity was 0.9%, 25.5%, 41.5%, and 32.1%, respectively. The 10-year incidence of dementia significantly decreased with increasing BMI, from 11.5% in women with underweight to 9.1% in those with obesity (log-rank p <  0.001). Respective figures in men were 12.0% and 8.2% (log-rank p <  0.001). In women, only overweight (versus normal weight) was significantly associated with dementia (HR = 0.93, 95% CI = 0.88-0.97). In contrast, in men, the only BMI category significantly associated with the incidence of dementia was underweight (HR = 1.58, 95% CI = 1.11-2.25).

CONCLUSION

In this study conducted in Germany, overweight was negatively associated with dementia in women, whereas there was a positive underweight-dementia relationship in men. More data are needed to confirm or refute these findings in other settings.

Sex Differences in Cognition Across Aging

Sex and gender differences are seen in cognitive disturbances in a variety of neurological and psychiatry diseases. Men are more likely to have cognitive symptoms in schizophrenia whereas women are more likely to have more severe cognitive symptoms with major depressive disorder and Alzheimer's disease. Thus, it is important to understand sex and gender differences in underlying cognitive abilities with and without disease. Sex differences are noted in performance across various cognitive domains - with males typically outperforming females in spatial tasks and females typically outperforming males in verbal tasks. Furthermore, there are striking sex differences in brain networks that are activated during cognitive tasks and in learning strategies. Although rarely studied, there are also sex differences in the trajectory of cognitive aging. It is important to pay attention to these sex differences as they inform researchers of potential differences in resilience to age-related cognitive decline and underlying mechanisms for both healthy and pathological cognitive aging, depending on sex. We review literature on the progressive neurodegenerative disorder, Alzheimer's disease, as an example of pathological cognitive aging in which human females show greater lifetime risk, neuropathology, and cognitive impairment, compared to human males. Not surprisingly, the relationships between sex and cognition, cognitive aging, and Alzheimer's disease are nuanced and multifaceted. As such, this chapter will end with a discussion of lifestyle factors, like education and diet, as modifiable factors that can alter cognitive aging by sex. Understanding how cognition changes across age and contributing factors, like sex differences, will be essential to improving care for older adults.

Influence of Weight Loss on Cognitive Functions: A Pilot Study of a Multidisciplinary Intervention Program for Obesity Treatment

There is a relationship between obesity and cognitive functioning. Our aim was to assess weight loss influence on global cognition and executive functioning (EF) in adults with obesity under a multidisciplinary weight loss program. In this six-month longitudinal study, we assessed 81 adults (age < 50 years) with body mass index (BMI) ≥ 30. EF and global cognitive performance were evaluated with the Montreal Cognitive Assessment (MoCA), Neuropsychological Battery of Executive Functions (BANFE-2) and Trail Making Test-Part B (TMT-B). Median age was 40.0 years (IQR: 31.5−47, 61% women), and the median BMI was 41.4 (IQR: 36.7−45.9). At a six-month follow-up, the mean weight loss was 2.67% (29.6% of patients achieved ≥5% weight loss). There was an improvement in EF evaluated with BANFE (p = 0.0024) and global cognition with MoCA (p = 0.0024). Women experienced more remarkable change, especially in EF. Weight loss did not correlate with cognitive performance, except for TMT-B (r-0.258, p = 0.026). In the regression analysis, only years of education predicted the MoCA score. This study showed that patients improved cognitive performance during the follow-up; nevertheless, the magnitude of weight loss did not correlate with cognitive improvement. Future studies are warranted to demonstrate if patients achieving ≥5% weight loss can improve cognition, secondary to weight loss.

Body Mass Index, Waist Circumference, and Cognitive Decline Among Chinese Older Adults: A Nationwide Retrospective Cohort Study

Background

The reported associations between body mass index (BMI), waist circumference (WC), and cognitive decline are not consistent, especially in older adults.

Objective

This study aims to investigate the longitudinal associations of BMI, WC, and their change values with cognitive decline among Chinese adults aged 60 years and older and to examine the potential moderating effect of sex on these relationships.

Methods

The participants in this study were from waves one to four (2011–2018) of the China Health and Retirement Longitudinal Study (CHARLS). Cognition function, BMI, and WC were measured at four examinations over 7 years. The interview-based cognitive assessments of memory, orientation and attention, and visuospatial ability were recorded. Standardized global cognitive scores were generated. BMI and WC were objectively measured. Mixed-effects models were performed to evaluate the associations.

Results

A final sample of 3,035 Chinese older adults [mean (SD) age, 66.94 (5.43) years; 40.16% (n = 1,219) women] were included. Higher BMI (estimate = 0.0107; SE = 0.0024; p < 0.0001) and WC (estimate = 0.0019; SE = 0.0006; p = 0.0037) were associated with slower cognition score decline over a 7-year follow-up, while greater BMI variability (estimate = −0.0365; SE = 0.0116; p = 0.0017) was related to faster cognition score decline. The results were not modified by sex. BMI-defined overweight (estimate = 0.0094; SE = 0.0043; p = 0.0298) was associated with a slower cognition score decline, and both large weight gain (estimate = −0.0266; SE = 0.0074; p = 0.0003) and large WC loss (estimate = −0.0668; SE = 0.0329; p = 0.0426) were associated with faster cognition score decline.

Conclusion

Among Chinese older adults, higher BMI, higher WC, and overweight are related to slower cognitive decline, while greater BMI variability, large weight gain, and large WC loss are associated with faster cognitive decline.

Targeting hypercoagulation to alleviate Alzheimer's disease progression in metabolic syndrome

INTRODUCTION

Metabolic Syndrome (MetS) constitutes an important risk factor for Alzheimer's disease (AD); however, the mechanism linking these two disorders has not been completely elucidated. Hence, hypercoagulation may account for the missing hallmark connecting MetS and AD. The present review proposes how hemostatic imbalance triggered in MetS advances in the context of AD. MetS causes interruption of insulin signaling and inflammation, inciting insulin resistance in the brain. Subsequently, neuroinflammation and brain endothelial dysfunction are prompted that further intensify the exorbitant infiltration of circulating lipids and platelet aggregation, thereby causing hypercoagulable state, impairing fibrinolysis and eventually inducing prothrombic state in the brain leading to neurodegeneration.

OBJECTIVE

This study aims to understand the role of hypercoagulation in triggering the progression of neurodegeneration in MetS. It also offers a few interventions to prevent the progression of AD in MetS targeting hypercoagulation.

METHODS

Literature studies based on MetS related neurodegeneration, the impact of coagulation on aggravating obesity and AD via the mechanisms of BBB disruption, neuroinflammation, and hypofibrinolysis.

CONCLUSION

The present paper proposes the hypothesis that hypercoagulation might amplify MetS associated insulin resistance, neuroinflammation, BBB disruption, and amyloid beta accumulation which eventually leads to AD.

Mid- to Late-Life Body Mass Index and Dementia Risk: 38 Years of Follow-up of the Framingham Study

Growing evidence relates body mass index (BMI) to poorer health outcomes; however, results across studies associating BMI and dementia are conflicting. A total of 3,632 Framingham Offspring participants aged 20 to 60 years at their second health examination (1979-1983) were included in this study, with 190 cases of incident dementia identified by 2017. Cox proportional hazards regression models were fitted to investigate the association of BMI at each of their 8 exams as a baseline for dementia risk and the associations between obesity and dementia across age groups. Spline models were fitted to investigate nonlinear associations between BMI and dementia. Each 1-unit increase in BMI at ages 40-49 years was associated with higher risk of dementia, but with lower risk after age 70 years. Obesity at ages 40-49 years was associated with higher risk of dementia. Overall, the relationship between BMI and dementia risk was heterogeneous across the adult age range. Monitoring BMI at different ages might mediate risk for dementia across an individual's lifetime.

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.

A Multimodal Risk Network Predicts Executive Function Trajectories in Non-demented Aging

Background: Multiple modalities of Alzheimer's disease (AD) risk factors may operate through interacting networks to predict differential cognitive trajectories in asymptomatic aging. We test such a network in a series of three analytic steps. First, we test independent associations between three risk scores (functional-health, lifestyle-reserve, and a combined multimodal risk score) and cognitive [executive function (EF)] trajectories. Second, we test whether all three associations are moderated by the most penetrant AD genetic risk [Apolipoprotein E (APOE) ε4+ allele]. Third, we test whether a non-APOE AD genetic risk score further moderates these APOE × multimodal risk score associations. Methods: We assembled a longitudinal data set (spanning a 40-year band of aging, 53-95 years) with non-demented older adults (baseline n = 602; Mage = 70.63(8.70) years; 66% female) from the Victoria Longitudinal Study (VLS). The measures included for each modifiable risk score were: (1) functional-health [pulse pressure (PP), grip strength, and body mass index], (2) lifestyle-reserve (physical, social, cognitive-integrative, cognitive-novel activities, and education), and (3) the combination of functional-health and lifestyle-reserve risk scores. Two AD genetic risk markers included (1) APOE and (2) a combined AD-genetic risk score (AD-GRS) comprised of three single nucleotide polymorphisms (SNPs; Clusterin[rs11136000], Complement receptor 1[rs6656401], Phosphatidylinositol binding clathrin assembly protein[rs3851179]). The analytics included confirmatory factor analysis (CFA), longitudinal invariance testing, and latent growth curve modeling. Structural path analyses were deployed to test and compare prediction models for EF performance and change. Results: First, separate analyses showed that higher functional-health risk scores, lifestyle-reserve risk scores, and the combined score, predicted poorer EF performance and steeper decline. Second, APOE and AD-GRS moderated the association between functional-health risk score and the combined risk score, on EF performance and change. Specifically, only older adults in the APOEε4- group showed steeper EF decline with high risk scores on both functional-health and combined risk score. Both associations were further magnified for adults with high AD-GRS. Conclusion: The present multimodal AD risk network approach incorporated both modifiable and genetic risk scores to predict EF trajectories. The results add an additional degree of precision to risk profile calculations for asymptomatic aging populations.

Association between Visceral Fat and Brain Structural Changes or Cognitive Function

Visceral fat accumulation is an independent risk factor for cardiovascular disease and mortality. Visceral fat is a causal risk factor for hypertension and type 2 diabetes, which was reported as one of the risk factors for dementia. Visceral fat areas (VFA) might be clinically important to prevent dementia; however, the association between VFA and cognitive function in the elderly remains unknown. We aimed to evaluate the association between brain structural abnormalities using magnetic resonance imaging (MRI) and VFA, and the association between cognitive function and VFA, in the elderly. A total of 2364 healthy individuals were enrolled, and we excluded those diagnosed with dementia. Participants were divided into a high-VFA and a low-VFA group based on median VFA. The high-VFA group had significantly lower cognitive function than the low-VFA group (p = 0.025), after adjustment for related factors using a linear regression model. Regarding brain structure in MRI, VFA remained significantly associated with white matter lesions (odds ratio (OR), 1.90; 95% confidence interval (1.33-2.70); adjusted p < 0.001) and perivascular space (OR, 1.28; 95% confidence interval (1.02-1.61); adjusted p = 0.033). Further follow-up studies are needed, but reducing visceral fat might be important, not only to prevent cardiovascular disease but also to prevent dementia.

The risk of Alzheimer's disease according to dynamic changes in metabolic health and obesity: a nationwide population-based cohort study

We evaluated the association of metabolic health and obesity phenotypes with the risk of Alzheimer's disease (AD). This study enrolled 136,847 elderly participants aged 60 or above from the Korean National Health Insurance System. At baseline examinations in 2009 and 2010, subjects were categorized into four groups: the metabolically healthy non-obese (MHNO), metabolically healthy obese (MHO), metabolically unhealthy non-obese (MUNO), and metabolically unhealthy obese (MUO) groups. Based on the phenotypic transition after 2 years, the subjects were further categorized into 16 subgroups. They were followed from 2009 to 2015 to monitor for AD development. The MHO phenotype protected subjects from AD, relative to the MHNO phenotype (HR, 0.73; 95% CI, 0.65-0.81). Among subjects initially classified as MHO, 41.8% remained MHO, with a significantly lower risk of AD compared with the stable MHNO group (HR, 0.62; 95% CI, 0.50-0.77). Among MUO subjects at baseline, those who changed phenotype to MUNO were at higher risk of AD (HR, 1.47; 95% CI, 1.28-1.70), and the transition to the MHO phenotype protected subjects from AD (HR, 0.62; 95% CI, 0.50-0.78). The MHO phenotype conferred a decreased risk of AD. Maintenance or recovery of metabolic health might mitigate AD risk among obese individuals.

Weight Loss and the Risk of Dementia: A Meta-analysis of Cohort Studies

BACKGROUND

Weight loss is a common phenomenon among the elderly and is identified as an important indicator of health status. Many epidemiology studies have investigated the association between weight loss and dementia, but the results were inconsistent.

OBJECTIVE

To examine and determine the association between weight loss and the risk of dementia.

METHODS

Eligible cohort studies involving weight loss and dementia were searched from PubMed, Embase, and Ovid databases through October 2018. Pooled relative risks (RRs) with its 95% confidence intervals (CIs) were used to estimate the effects of weight loss on the risk of dementia. Subgroup and sensitivity analyses were performed to explore the potential sources of heterogeneity. The Begg's test and Egger's test were used to assess the publication bias.

RESULTS

A total of 20 cohort studies with 38,141 participants were included in this meta-analysis. Weight loss was significantly associated with the risk of dementia (RR=1.26, 95% CI=1.15-1.38). BMI decline ≥0.8 units (RR=1.31, 95% CI=1.10-1.56) and ≥4% (RR=1.19, 95% CI=1.03-1.38) could increase the risk of dementia. The risk of all-cause dementia for people with weight loss increased by 31% (RR=1.31, 95% CI=1.15-1.49), and 25% higher for incident Alzheimer's disease (RR=1.25, 95% CI=1.07-1.46). Weight loss in participants with normal weight had a similar dementia risk (RR=1.21, 95% CI=1.06-1.38) with the overweight individuals (RR=1.22, 95% CI=1.11-1.34).

CONCLUSION

Weight loss may be associated with an increased risk of dementia, especially for Alzheimer's disease. Maintaining weight stability may help prevent dementia.

The Association of Osteoarthritis and Related Pain Burden to Incident Alzheimer's Disease and Related Dementias: A Retrospective Cohort Study of U.S. Medicare Beneficiaries

BACKGROUND

Emerging evidence suggests osteoarthritis (OA) and related symptom burden may increase risk for Alzheimer's disease and related dementias (ADRD). However, longitudinal studies are sparse, and none have examined the potential mediating effects of mood or sleep disorders.

OBJECTIVE

To determine the association of OA and related pain to incident ADRD in U.S. elders.

METHODS

In this retrospective cohort study, we used baseline and two-year follow-up data from linked Medicare claims and Medicare Current Beneficiary Survey files (11 pooled cohorts, 2001-2013). The study sample comprised 16,934 community-dwelling adults≥65 years, ADRD-free at baseline and enrolled in fee-for-service Medicare. Logistic regression was used to assess the association of OA and related pain (back, neck, joint, neuropathic) to incident ADRD, explore the mediating inlfuence of mood and insomnia-related sleep disorders, and (sensitivity analyses) account for potential survival bias.

RESULTS

Overall, 25.5% of beneficiaries had OA at baseline (21.0% with OA and pain); 1149 elders (5.7%) were subsequently diagnosed with ADRD. Compared to beneficiaries without OA, those with OA were significantly more likely to receive a diagnosis of incident ADRD after adjustment for sociodemographics, lifestyle characteristics, comorbidities, and medications (adjusted odds ratio (AOR) = 1.23 (95% confidence interval (CI) 1.06, 1.42). Elders with OA and pain at baseline were significantly more likely to be diagnosed with incident ADRD than were those without OA or pain (AOR = 1.31, CI 1.08, 1.58). Sensitivity analyses yielded similar findings. Inclusion of depression/anxiety, but not sleep disorders, substantially attenuated these associations.

CONCLUSION

Findings of this study suggest that: OA is associated with elevated ADRD risk, this association is particularly pronounced in those with OA and pain, and mood disorders may partially mediate this relationship.

Associations between body composition and cognitive function in an elderly Korean population: A cohort-based cross-sectional study

The prevalence of obesity as well as cognitive impairment increases with age. Previous studies showed that obesity is associated with an increased risk of cognitive impairment and dementia. Body composition changes occur as part of the aging process; therefore, the assessment of obesity in elderly populations should include body composition as well as body weight. This study investigated the relationship between body mass index (BMI), body composition, and cognitive function in a community-dwelling elderly Korean population.This cohort-based cross-sectional analysis included 2386 elderly participants aged between 70 and 84 years from the Korean Frailty and Aging Cohort Study for 2016 to 2017. To investigate the relationship between body composition and cognitive function in community-dwelling individuals, BMI and body composition, including total and trunk fat mass and fat-free mass, were measured by dual-energy X-ray absorptiometry. Fat mass index (FMI), trunk fat mass index (TFMI), and fat-free mass index (FFMI) were used to represent the body composition. A short form of the Korean version of the Consortium to Establish a Registry for Alzheimer disease was used to assess cognitive function. To evaluate the relationship between variables, simple and fully adjusted multivariable analyses were performed using generalized linear regression models.The mean ages were 76.8 years for males and 76.1 years for females. The BMI of male participants was significantly lower than that of females (23.9 ± 2.89 vs 24.7 ± 3.02 kg/m2, P < .001). Among body composition parameters, the differences in FMI (6.44 ± 1.97 vs 9.29 ± 2.3 kg/m2), TFMI (3.68 ± 1.33 vs 5.03 ± 1.43 kg/m2), and FFMI (17.4 ± 1.64 vs 15.3 ± 1.39 kg/m2) were statistically significant. In linear regression analyses, BMI, FMI, and TFMI showed significant positive correlations with mini-mental state examination in the Korean version of the CERAD assessment packet; wordlist memory, recall, and recognition; and frontal assessment battery only in males. The significant positive correlations persisted even after fully adjusting for age, education periods, location of residence, depression, marriage, annual income, presence of diabetes mellitus, dyslipidemia, and hypertension. However, no significant correlations in either sex were observed between FFMI and cognitive functions in the fully adjusted models.In this study, BMI, and fat mass-related indexes including FMI and TFMI showed a positive linear correlation with cognitive functions but not FFMI. Moreover, the findings were significant only in men. Besides the difference between sexes, the results of this study showed a more apparent correlation in fat mass than in fat-free mass that comprises body weight.

Metabolically healthy obesity and lipids may be protective factors for pathological changes of alzheimer's disease in cognitively normal adults

The associations between obesity and Alzheimer's disease (AD) at different ages have been debated. Recent evidence implied the protective effects of metabolically healthy obesity on AD. We hypothesized that obesity and lipids could mitigate the detrimental impacts of AD pathological changes among metabolically healthy individuals in late life. In this study, a total of 604 metabolically healthy participants with normal cognition were included from the Chinese Alzheimer's Biomarker and LifestylE (CABLE) database. Multiple linear regression models were used to test the associations of body mass index (BMI) or lipids with cerebrospinal fluid (CSF) biomarkers after adjustment for age, gender, education, and Apolipoprotein E-ɛ4 (APOE-ɛ4). The results showed the lower CSF levels of total tau protein (t-tau: p = .0048) and phosphorylated tau protein (p-tau: p = .0035) in obese participants than in non-obese participants, even after correcting for covariates. Moreover in late life, higher BMI was associated with decreased CSF t-tau (β: -0.15, p = .0145) and p-tau (β: -0.17, p = .0052). As for lipids, higher levels of total cholesterol (TC) and low-density lipoprotein cholesterol (LDL-C) were associated with decreased CSF t-tau (TC: β: -0.16, p = .0115; LDL-C: β: -0.16, p = .0082) and p-tau (TC: β: -0.15, p = .0177; LDL-C: β: -0.14, p = .0225) in obese participants. Furthermore, these associations were only significant in participants with late-life obesity and APOE-ɛ4 non-carriers. Overall, in a cognitively normal population, we found metabolically healthy obesity and lipids in late life might be protective factors for neurodegenerative changes.

Sex differences in association between body composition and frailty or physical performance in community-dwelling older adults

Frailty is a common geriatric condition due to aging, defined as a decrease in the functional reserve to maintain the homeostasis. As part of the aging process, body composition changes occur. This study investigated the relationship between body composition and frailty in a community-dwelling elderly Korean population.This cross-sectional cohort study analyzed data of 2,385 elderly participants (aged 70-84 years, 1131 males and 1254 females) of the Korean Frailty and Aging Cohort Study from 2016 to 2017. Body composition, including total and trunk fat masses and fat-free mass, were measured with dual-energy X-ray absorptiometry. Fat mass index (FMI), trunk fat mass index, and fat-free mass index (FFMI) represented total fat mass, trunk fat mass, and fat-free mass according to height. Based on the frailty index developed by Fried, we compared the frail and non-frail groups. Poor physical performance assessed with the short physical performance battery score of < 9 is considered frailty. To evaluate the relationship between the variables, simple and fully adjusted multivariable logistic regression analyses were performed according to sex.Among the participants, 462 (19.3%) were defined as the frail group, with a significantly high mean age of 77.9 ± 4.0 years. In the logistic regression analysis of frailty based on body mass index (BMI) categories, underweight (BMI < 18 kg/m2) participants showed a high incidence of frailty in both sexes. BMI showed an association with frailty only in males. Lower FFMI was associated with a higher incidence of frailty in both sexes, which was statistically significant in the fully adjusted models. In the female, fat-related indexes including body fat percentage, FMI, and trunk fat mass index showed a significant association with poor physical performance. In contrast, males with low FFMI only showed a significant association with poor physical performance.Frailty was closely correlated with lower FFMI in both sexes. The poor physical performance associated with frailty correlated with fat-related body composition in females and fat-free mass in males, owing to the difference in body composition between the sexes. In the assessment of frailty, body composition and sex-related differences should be analyzed.

Five-Year Change in Body Mass Index Predicts Conversion to Mild Cognitive Impairment or Dementia Only in APOE ɛ4 Allele Carriers

BACKGROUND

Body mass index (BMI) has been identified as an important modifiable lifestyle risk factor for dementia, but less is known about how BMI might interact with Apolipoprotein E ɛ4 (APOE ɛ4) carrier status to predict conversion to mild cognitive impairment (MCI) and dementia.

OBJECTIVE

The aim of this study was to investigate the interaction between APOE ɛ4 status and baseline (bBMI) and five-year BMI change (ΔBMI) on conversion to MCI or dementia in initially cognitively healthy older adults.

METHODS

The associations between bBMI, ΔBMI, APOE ɛ4 status, and conversion to MCI or dementia were investigated among 1,289 cognitively healthy elders from the National Alzheimer's Coordinating Center (NACC) database.

RESULTS

After five years, significantly more carriers (30.6%) converted to MCI or dementia than noncarriers (17.6%), p < 0.001, OR = 2.06. Neither bBMI (OR = 0.99, 95%CI = 0.96-1.02) nor the bBMI by APOE interaction (OR = 1.02, 95%CI = 0.96-1.08) predicted conversion. Although ΔBMI also did not significantly predict conversion (OR = 0.90, 95%CI = 0.78-1.04), the interaction between ΔBMI and carrier status was significant (OR = 0.72, 95%CI = 0.53-0.98). For carriers only, each one-unit decline in BMI over five years was associated with a 27%increase in the odds of conversion (OR = 0.73, 95%CI = 0.57-0.94).

CONCLUSION

A decline in BMI over five years, but not bBMI, was strongly associated with conversion to MCI or dementia only for APOE ɛ4 carriers. Interventions and behaviors aimed at maintaining body mass may be important for long term cognitive health in older adults at genetic risk for AD.

Association Between Childhood Neighborhood Quality and the Risk of Cognitive Dysfunction in Chinese Middle-Aged and Elderly Population: The Moderation Effect of Body Mass Index

Background: Identification of early modifiable factors is crucial to delay or prevent the development of cognitive impairment and reduce the social and economic burden. Objective: This study aimed to examine the longitudinal associations of childhood neighborhood quality (CNQ) with the risk of later-life cognitive dysfunction and the role of body mass index (BMI) in this association. Methods: A total of 8,289 community-dwelling middle-aged and elderly population from wave 2011, wave 2013, and wave 2015 of the China Health and Retirement Longitudinal Study (CHARLS) were included. Cognitive function and CNQ were measured by standardized questionnaires. Multilevel linear regression models were used to estimate the associations of CNQ and cognitive function. The interactions of BMI with CNQ in the progress of cognitive function were also estimated. Results: The participants with higher CNQ had a significantly low risk of cognitive impairment than those with lower CNQ score (β = 0.067, 95% CI: 0.031, 0.103), and the results remained similar (β = 0.039, 95% CI: 0.004, 0.075) after controlling other confounding variables. Furthermore, there was an interaction between BMI with CNQ score (P < 0.001) for the risk of cognitive impairment. In BMI-stratified analysis, we found that the association of CNQ and cognitive function was not statistically significant in overweight or obese population (β = 0.019, 95% CI: -0.032, 0.070), but was statistically significant in people with lower BMI (β = 0.059, 95% CI: 0.010, 0.107). Conclusions: Higher CNQ score is significantly associated with the lower risk of cognitive dysfunction in adulthood. BMI may moderate the associations of CNQ with the risk of cognitive function.

Eating Behavior in Aging and Dementia: The Need for a Comprehensive Assessment

Eating behavior can change during aging due to physiological, psychological, and social changes. Modifications can occur at different levels: (1) in food choice, (2) in eating habits, and (3) in dietary intake. A good dietary behavior, like the Mediterranean dietary pattern, can be a protective factor for some aging related pathologies, such as dementia, while a worse eating behavior can lead to pathological conditions such as malnutrition. Changes in eating behavior can also be linked to the onset of dementia: for some types of dementia, such as frontotemporal dementia, dietary changes are one of the key clinical diagnostic feature, for others, like Alzheimer's disease, weight loss is a clinical reported feature. For these reasons, it is important to be able to assess eating behavior in a proper way, considering that there are normal age-related changes. An adequate assessment of dietary behavior can help to plan preventive intervention strategies for heathy aging or can help to identify abnormal behaviors that underline aging related-diseases. In this review, we have analyzed normal age-related and dementia-related changes and the tools that can be used to assess eating behavior. Thus, we make recommendations to screening and monitoring eating behavior in aging and dementia, and to adopt these tools in clinical practice.

Sex differences in underweight and body mass index in Chinese early de novo patients with Parkinson's disease

OBJECTIVE

There have been studies investigating sex differences in clinical manifestation of Parkinson's disease (PD). However, sex differences in underweight and body mass index (BMI) in de novo PD patients lacked systematic study. We aimed to compare sex differences in clinical features and related factors of underweight and BMI in Chinese de novo PD patients.

MATERIALS AND METHODS

A total of 253 untreated PD inpatients and 218 controls were recruited from Ningbo. BMI, demographics, Montreal Cognitive Assessment (MoCA), supine and upright blood pressure, Hamilton Anxiety Scale (HAMA), Hamilton Depression Scale (HAMD), homocysteine (HCY), uric acid, glycated hemoglobin, and lipid parameters were examined. Patients were assessed using the Unified Parkinson's Disease Rating Scale (UPDRS) motor scores and Hoehn and Yahr (HY) Rating Scale.

RESULTS

Female patients had a significantly lower incidence of underweight and higher BMI than male patients, and there were sex differences in serum lipids, HCY levels, and depression severity. Binary regression analysis showed that only in male patients was underweight associated with the UPDRS motor score and lower ΔSBP and ΔDBP values (all p < .05). Further multiple regression analysis indicated, in addition to the correlations between BMI and ΔSBP and ΔDBP values in both sexes (all p < .001), BMI was also associated with MoCA and lower UPDRS motor scores in male patients and lower HAMD scores in female patients.

CONCLUSION

Our study suggests that there are significant sex differences in the prevalence of underweight, BMI, and factors associated with underweight and BMI among de novo PD patients.

Long-term Change in Physiological Markers and Cognitive Performance in Type 2 Diabetes: The Look AHEAD Study

CONTEXT

The effects of physiological improvements on cognitive function among persons with type 2 diabetes mellitus (T2DM) are not fully understood.

OBJECTIVE

To determine whether improvements in physiological markers (body weight, blood sugar control, and physical activity) during intensive lifestyle intervention (ILI) are associated with enhancements in cognitive function in older adults with T2DM.

DESIGN

Multisite randomized controlled trial.

SETTING

Academic research centers.

PATIENTS OR OTHER PARTICIPANTS

Participants were aged 45-76 years, with T2DM.

INTERVENTION

The Action for Health in Diabetes (Look AHEAD) study, a randomized, controlled clinical trial of ILI.

MAIN OUTCOME MEASURE

Two to 3 cognitive assessments were collected from 1089 participants, the first and last occurring a mean (standard deviation) of 8.6 (1.0) and 11.5 (0.7) years after enrollment.

RESULTS

Greater improvement in blood sugar control was associated with better cognitive scores (fasting glucose and Rey Auditory Verbal Learning Test [AVLT]: P = 0.0148; fasting glucose and Digit Symbol Coding (DSC): P = 0.0360; HbA1C and DSC: P = 0.0477); but weight loss had mixed associations with cognitive scores (greater body mass index [BMI] reduction and worse AVLT overall: P = 0.0053; and greater BMI reduction and better DSC scores among those overweight but not obese at baseline: P = 0.010). Associations were strongest among those who were overweight (not obese) at baseline, and among those with a history of cardiovascular disease (CVD) at baseline.

CONCLUSIONS

Improvements in glycemic control, but not necessarily weight status, during ILI may be associated with better subsequent cognitive performance. These associations may differ by adiposity and CVD history.

Vascular and metabolic risk factor differences prior to dementia diagnosis: a multidatabase case-control study using European electronic health records

OBJECTIVE

The objective of the study is to compare body mass index (BMI), systolic/diastolic blood pressure (SBP/DBP) and serum total cholesterol levels between dementia cases and controls at multiple time intervals prior to dementia onset, and to test time interval as a modifying factor for these associations.

DESIGN

Case-control study.

SETTING

Six European electronic health records databases.

PARTICIPANTS

291 780 cases at the date of first-recorded dementia diagnosis, compared with 29 170 549 controls randomly selected from the same databases, age matched and sex matched at this index date.

EXPOSURE

The following measures were extracted whenever recorded within each dataset: BMI (kg/m2), SBP and DBP (mm Hg) and serum total cholesterol (mmol/L). Levels for each of these variables were defined within six 2-year time intervals over the 12 years prior to the index date.

MAIN OUTCOMES

Case-control differences in exposures of interest were modelled for each time period and adjusted for demographic and clinical factors (ischaemic/unspecified stroke, type 2 diabetes mellitus, acute myocardial infarction, hypertension diagnosis, antihypertensive medication, cholesterol-lowering medication). Coefficients and interactions with time period were meta-analysed across the six databases.

RESULTS

Mean BMI (coefficient -1.16 kg/m2; 95% CI -1.38 to 0.93) and SBP (-2.83 mm Hg; 95% CI -4.49 to -1.16) were lower in cases at diagnosis, and case-control differences were greater in more recent time periods, as indicated by significant case-x-time interaction and case-x-time-squared interaction terms. Time variations in coefficients for cholesterol levels were less consistent between databases and those for DBP were largely not significant.

CONCLUSION

Routine clinical data show emerging divergence in levels of BMI and SBP prior to the diagnosis of dementia but less evidence for DBP or total cholesterol levels. These divergences should receive at least some consideration in routine dementia risk screening, although underlying mechanisms still require further investigation.

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.

Cardiovascular risk factors and APOE-ε4 status affect memory functioning in aging via changes to temporal stem diffusion

Prior research investigating associations between hypertension, obesity, and apolipoprotein (APOE) genotype status with memory performance among older adults has yielded inconsistent results. This may reflect, in part, a lack of first accounting for the effects these variables have on structural brain changes, that in turn contribute to age-related memory impairment. The current study sought to clarify the relationships between these factors via path modeling. We hypothesized that higher body mass index (BMI), hypertension, and being an APOE-ε4 allele carrier would predict poorer memory scores, with much of these effects accounted for by indirect effects operating via differences in the integrity of temporal stem white matter. Participants included 125 healthy older adults who underwent neuropsychological assessment and diffusion-weighted MRI scanning. Direct effects were found for hypertension and demographic variables including age, sex, and education. Importantly, indirect effects were found for BMI, hypertension, APOE-ε4 status, age, and sex, where these factors predicted memory scores via their impact on temporal stem diffusion measures. There was also a dual effect of sex, with a direct effect indicating that females had better memory performance overall, and an indirect effect indicating that females with greater temporal stem diffusion had poorer memory performance. Results suggest that changes to the integrity of temporal white matter in aging may underpin reduced memory performance. These results highlight that accounting for variables that not only directly impact cognition, but also for those that indirectly impact cognition via structural brain changes, is crucial for understanding the impact of risk factors on cognition.

Impacts of Overweight and Obesity in Older Age on the Risk of Dementia: A Systematic Literature Review and a Meta-Analysis

Background:

It is unclear whether overweight and obesity in older age reduces or increases the risk of incident dementia.

Objective:

To assess the impacts of overweight and obesity in older age on incident dementia.

Methods:

We searched cohort studies reporting body weight measured in older age and dementia through PubMed, Embase, Medline, PyschInfo, and Cochrane library until July 2016. Sixteen articles were identified for the review. We pooled data from them and a new unpublished study from China, to calculate relative risk (RR) of incident dementia in relation to body mass index (BMI) and waist circumference (WC).

Results:

All 16 cohort studies were undertaken in high income countries, with follow-up periods ranging between 3 to 18 years. Thirteen studies showed an inverse association between BMI and dementia, and three studies demonstrated a positive association. Pooled RR of dementia in relation to continuous BMI from 14 studied populations, including the new Chinese data, was 0.97 (95% CI 0.95–1.00); in those followed up <9 years it was 0.95 (0.93–0.96) while in ≥9 years follow-up it was 1.03 (0.96–1.11). In five studied populations examining categorical BMI, RR of dementia in older people classified as overweight and obese was 0.98 (0.54–1.77) and 1.17 (0.65–2.10) respectively, in comparison with other weights. The pooled WC data showed no association between increased WC and reduced risk of dementia.

Conclusion:

The current evidence did not support a paradox on beneficial impacts of overweight and obesity in older age on incident dementia. More studies with long term follow up are needed to clarify the association of body weight in older age with dementia risk.

Higher Body Mass Index Is Associated with Lower Cortical Amyloid-β Burden in Cognitively Normal Individuals in Late-Life

BACKGROUND

Both low and high body mass index (BMI) have been associated with an increased risk of dementia, including that caused by Alzheimer's disease (AD). Specifically, high middle-age BMI or a low late-age BMI has been considered a predictor for the development of AD dementia. Less studied is the relationship between BMI and AD pathology.

OBJECTIVE

We explored the association between BMI and cortical amyloid-β (Aβ) burden in cognitively normal participants that were either in mid-life (45-60 years) or late-life (>60).

METHODS

We analyzed cross-sectional baseline data from the Knight Alzheimer Disease Research Center (ADRC) at Washington University. Aβ pathology was measured in 373 individuals with Aβ PET imaging and was quantified using Centiloid units. We split the cohort into mid- and late-life groups for analyses (n = 96 and n = 277, respectively). We ran general linear regression models to predict Aβ levels from BMI while controlling for age, sex, years of education, and APOE4 status. Analyses were also conducted to test the interaction between BMI and APOE4 genotype and between BMI and sex.

RESULTS

Higher BMI was associated with lower cortical Aβ burden in late-life (β= -0.81, p = 0.0066), but no relationship was found in mid-life (β= 0.04, p > 0.5). The BMI×APOE4+ and BMI×male interaction terms were not significant in the mid-life (β= 0.28, p = 0.41; β= 0.64, p = 0.13) or the late-life (β= 0.17, p > 0.5; β= 0.50, p = 0.43) groups.

CONCLUSION

Higher late-life BMI is associated with lower cortical Aβ burden in cognitively normal individuals.

Association of serum Apolipoprotein B with cerebrospinal fluid biomarkers of Alzheimer's pathology

Objective

To examine whether apolipoprotein B (ApoB), apolipoprotein A‐1 (ApoA1), or their ratio (ApoB/A1) were associated with early changes in cerebrospinal fluid (CSF) biomarkers of Alzheimer’s disease (AD) pathology in elderly adults with subjective cognitive decline (SCD).

Methods

This study included 507 objective cognitive normal participants from the Chinese Alzheimer’s Biomarker and LifestylE (CABLE) database including 288 cognitive normal participants (CN) and 219 SCD. Multiple linear regression models were used to examine the associations of apolipoproteins with CSF AD biomarkers.

Results

Compared with control group, SCD participants with significant AD biological characteristics had lower ApoB levels (P = 0.0461). In total participants, lower level of serum ApoB was associated with decreases in CSF Aβ42 (P = 0.0015) and Aβ42/40 (P = 0.0081) as well as increases in CSF p‐tau/Aβ42 (P < 0.0001) and t‐tau/Aβ42 (P = 0.0013), independent of APOEɛ4 status. In further subgroup analysis, these associations were more significant in SCD participants (ApoB × Diagnose: P < 0.05). In addition, lower levels of ApoB were also found associated with increases in p‐tau in the SCD subgroup (P = 0.0263). Furthermore, these protective associations were more significant in the overweight participants (ApoB × weight: P < 0.05). Results showed no association between ApoA1 and CSF biomarkers.

Interpretation

This study is the first to find protective associations of serum ApoB with CSF AD core biomarkers, especially in SCD individuals. It indicated that ApoB may be a potential biomarker for preclinical AD and may play different roles in different stages of AD.