Effect of late-life weight change on dementia incidence: a 10-year cohort study using claim data in Korea

Association of changes in predicted body composition with subsequent risk of dementia

OBJECTIVE

The effect of body composition change on the risk of dementia is not clear. This study analyzed the associations of changes in predicted lean body mass index (pLBMI), predicted appendicular skeletal muscle mass index (pASMI), and predicted body fat mass index (pBFMI) with the risk of dementia.

METHODS

In this nationwide cohort study, data were obtained from the Korean National Health Insurance Service database. The exposure was defined as changes in pLBMI, pASMI, and pBFMI derived from validated prediction equations. The outcome was dementia, defined based on the dementia diagnosis with prescription of anti-dementia medication. Cox proportional hazards regression analyses were performed to obtain the hazard ratio with a 95% confidence interval for risk of dementia according to changes in predicted body composition.

RESULTS

A total of 13,215,208 individuals with no prior record of dementia who underwent health screenings twice between 2009-2010 and 2011-2012 were included. A 1-kg/m2 increase in pLBMI and pASMI had an association with reduced risk of dementia (aHR: 0.85, 95% CI 0.84-0.87; aHR: 0.70, 95% CI 0.69-0.72, respectively for men, and aHR: 0.69, 95% CI 0.67-0.71; aHR: 0.59, 95% CI 0.57-0.61, respectively for women). A 1-kg/m2 increase in pBFMI had an association with a raised risk of dementia (aHR: 1.19, 95% CI 1.17-1.21 for men and aHR: 1.53, 95% CI 1.48-1.57 for women). These results remained consistent regardless of sex or weight change.

INTERPRETATION

Increase in pLBMI or pASMI, or reduction in pBFMI was linked to lower risk of dementia.

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.

Increased risk of ischemic stroke associated with elevated gamma-glutamyl transferase level in adult cancer survivors: a population-based cohort study

Adult cancer survivors may have an increased risk of developing ischemic stroke, potentially influenced by cancer treatment-related factors and shared risk factors with stroke. However, the association between gamma-glutamyl transferase (GGT) levels and the risk of ischemic stroke in this population remains understudied. Therefore, our study aimed to examine the relationship between GGT levels and the risk of ischemic stroke using a population-based cohort of adult cancer survivors. A population-based cohort of adult cancer survivors was derived from the National Health Insurance Service-Health Screening Cohort between 2003 and 2005 who survived after diagnosis of primary cancer and participated in the biennial national health screening program between 2009 and 2010. Cox proportional hazards model adjusted for sociodemographic factors, health status and behavior, and clinical characteristics was used to investigate the association between GGT level and ischemic stroke in adult cancer survivors. Among 3095 adult cancer survivors, 80 (2.58%) incident cases of ischemic stroke occurred over a mean follow-up of 8.2 years. Compared to the lowest GGT quartile, the hazard ratios (HRs) for ischemic stroke were 1.56 (95% CI 0.75-3.26), 2.36 (95% CI 1.12-4.99), and 2.40 (95% CI 1.05-5.46) for the second, third, and fourth sex-specific quartiles, respectively (Ptrend = 0.013). No significant effect modification was observed by sex, insurance premium, and alcohol consumption. High GGT level is associated with an increased risk of ischemic stroke in adult cancer survivors independent of sex, insurance premium, and alcohol consumption.

Body mass index, weight change in midlife, and dementia incidence: the Japan Public Health Center-based Prospective Study

INTRODUCTION

Insufficient evidence exists on the sex-specific associations of body mass index (BMI) and weight change through midlife with dementia incidence, especially in Asian populations.

METHODS

For 37,414 Japanese residents aged 40 to 59 years, BMIs at baseline (year 1990 or 1993) and 10-year follow-ups were obtained. Weight changes between baseline and 10-year follow-ups were determined. Disabling dementia incidence from 2006 to 2016 was ascertained using long-term care insurance (LTCI) certifications. Hazard ratios (HRs) were computed.

RESULTS

Increased dementia risk was observed with obesity at baseline and with underweight at 10-year follow-ups. Weight loss after baseline was at greater risk than weight gain. No sex difference was observed.

DISCUSSION

In both sexes, obesity in midlife increased the risk of developing dementia with increasing impacts of weight loss after midlife. A healthy body weight throughout adulthood is beneficial for dementia prevention.

Highlights

Obesity in midlife is a risk factor for incident dementia.Weight loss is a bigger risk factor than weight gain in later midlife.Association of BMI and weight change in midlife with dementia does not vary by sex.

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.

Association between Reduction of Muscle Mass and Faster Declines in Global Cognition among Older People: A 4-Year Prospective Cohort Study

OBJECTIVES

A few studies reported that both decrease and increase in body mass index (BMI) were associated with the development of dementia in later life. However, it is unclear what changes in body composition are associated with cognitive decline. This study investigated the longitudinal influences of changes in body composition on cognitive function among community-dwelling adults.

DESIGN, SETTING AND PARTICIPANTS

This longitudinal study included older adults aged ≥60 years without cognitive impairment who participated in National Institute for Longevity Sciences - Longitudinal Study of Aging.

MEASUREMENTS

Cognitive function was assessed using the MMSE. Body composition was measured by a dual-energy X-ray absorptiometry system. Then, BMI, fat mass index (FMI), fat-free mass index (FFMI), and muscle mass index (MMI) were calculated. The changes in body composition over 6 years (second wave to fifth wave) were calculated, and three groups were created: decreased group, decrease of >5%; stable group, change within 5%, and increased group, increase of >5%. In statistical analysis, a linear mixed model was applied by sex to investigate the influences of body composition changes on cognitive function over 4 years (fifth wave to seventh wave).

RESULTS

This study analyzed 515 participants (mean age, 67.05 years; 53.4% men). Men with decreased group in FFMI and MMI exhibited faster declines in MMSE scores than those with stable group (β [95% CI]: FFMI, -0.293 [-0.719 to -0.020]; MMI, -0.472 [-0.884 to -0.059]). In women, there was no significant association between body composition changes and cognitive functions.

CONCLUSIONS

Decrease in fat-free mass and muscle mass is associated with faster cognitive declines in men. These results suggest the importance of continuous monitoring of muscle mass to prevent cognitive decline in later life.

Body Mass Index Trajectories Preceding Incident Mild Cognitive Impairment and Dementia

Importance

Body mass index (BMI) trajectories before the onset of mild cognitive impairment (MCI) and during the progression from MCI to dementia remain unclear.

Objective

To assess the long-term BMI trajectories preceding incident MCI and dementia and explore whether they are associated with brain pathologies.

Design, Setting, and Participants

The Rush Memory and Aging Project (MAP) was an ongoing community-based cohort study. This study included cognitively intact participants aged 60 to 90 years at baseline with annual follow-up from October 1997 to December 2020 (maximum follow-up of 22 years). During the follow-up, participants underwent brain autopsies. Data were analyzed from August 2021 to February 2022 using mixed-effect models.

Exposures

BMI was calculated using height and weight measured at baseline and follow-ups.

Main Outcomes and Measures

Incident MCI and dementia were diagnosed following standard criteria. Neuropathological assessments (including global Alzheimer disease and vascular pathology) were performed for autopsies.

Results

A total of 1390 participants (mean [SD] age, 78.4 [6.5] years; 1063 female [76.5%]) were included in the study. In the analysis of BMI trajectories before MCI (n = 939), during the follow-up (median [IQR] duration, 6 [3-9] years), 371 participants (39.5%) developed MCI, of whom 88 (23.7%) progressed to dementia. Those who developed MCI were older (mean [SD] age, 79.6 [5.9] years vs 76.9 [6.6] years), consumed less alcohol (median [IQR] consumption, 0 [0-5.8] g/day vs 1.1 [0-6.9] g/day), had a lower BMI (mean [SD], 27.2 [4.9] vs 28.2 [5.9]), and were more likely to be apolipoprotein E (APOE) ε4 carriers (89 of 371 [24.0%] vs 98 of 568 [17.3%]) compared with those who remained cognitively intact over follow-up. Those who developed dementia were older (mean [SD] age, 81.0 [5.2] years vs 79.1 [6.0] years), had a lower level of physical activity (median [IQR] activity, 1.0 [0-2.5] h/week vs 1.8 [0.2-3.8] h/week), and were more likely to be APOE ε4 carriers than those who were dementia-free (33 of 88 [37.5%] vs 56 of 283 [19.8%]). Compared with participants who remained cognitively intact, in those with incident MCI, BMI tended to decline earlier and faster. From 7 years before diagnosis, people with incident MCI had an associated significantly lower BMI (mean difference, -0.96; 95% CI, -1.85 to -0.07) than those who were cognitively intact. Among people with incident MCI, the slopes of BMI decline did not differ significantly between those who did and did not develop dementia (β, -0.03; 95% CI, -0.21 to 0.15). In the analysis of BMI trajectories before autopsy (n = 358), BMI was associated with a faster declination among participants with a high burden of global Alzheimer disease pathology (β for pathology × time highest vs lowest tertile, -0.14; 95% CI, -0.26 to -0.02) or vascular pathology (β for pathology × time2 highest vs lowest tertile, 0.02; 95% CI, 0-0.05).

Conclusions and Relevance

Results of this cohort study suggest that among cognitively intact people, significantly lower BMI occurs beginning approximately 7 years before MCI diagnosis. After MCI diagnosis, BMI declines at the same pace in people who develop dementia and those who do not. High brain pathologies may underly the BMI decline preceding dementing disorders.

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.

Weight loss in a cardiovascular trial population identifies people at future risk of dementia

Introduction

Populations at increased risk of dementia need to be identified for well-powered trials of preventive interventions. Weight loss, which often occurs in pre-clinical dementia, could identify a population at sufficiently high dementia risk.

Methods

In 12,975 survivors in the Heart Protection Study statin trial of people with, or at high risk of, cardiovascular disease, the association of weight change over 5 years during the trial with post-trial dementia recorded in electronic hospital admission and death records (n = 784) was assessed, after adjustment for age, sex, treatment allocation, and deprivation measures.

Results

Among the 60% without substantial weight gain (≤2 kg weight gain), each 1 kg weight loss was associated with a risk ratio for dementia of 1.04 (95% confidence interval, 1.02-1.07). Weight loss ≥4 kg and cognitive function below the mean identified participants aged ≥67 years with a 13% 10-year dementia risk.

Discussion

The combination of weight loss and high vascular risk identified individuals at high risk of dementia who could be recruited to dementia prevention trials.

Association Between Late-Life Weight Change and Dementia: A Population-based Cohort Study

BACKGROUND

The impact of late-life weight changes on incident dementia is unclear. We aimed to investigate the associations of body mass index (BMI) and weight changes with dementia and to explore the role of APOE ɛ4 in these associations.

METHODS

A total of 1 673 dementia-free participants aged ≥60 and older were followed for an initial 6 years to detect changes in BMI/weight and then for an additional 6 years to detect incident dementia. BMI change ([BMIfirst 6-year follow-up - BMIbaseline]/BMIbaseline) was categorized as stable (≤5%), and moderate (5%-10%) or large (>10%) gain or loss. Weight change (weightfirst 6-year follow-up - weightbaseline) was categorized as stable (≤2.5 kg), and moderate (2.5-7.5 kg) or large (>7.5 kg) gain or loss. Dementia was diagnosed following standard criteria. Data were analyzed using Cox regression models.

RESULTS

Over the second 6-year follow-up period, 102 incident dementia cases were identified. Compared with stable BMI, the hazard ratios (95% CI) of dementia were 2.61 (1.09-5.54) and 2.93 (1.72-4.91) for BMI gain or loss >10%, respectively. The risk of dementia was higher among APOE ɛ4 carriers experiencing a large BMI gain (9.93 [3.49-24.6]) or loss (6.66 [2.83-14.4]) than APOE ɛ4 noncarriers with stable BMI. Similar results were observed for weight change and dementia associations.

CONCLUSIONS

BMI and weight changes showed U-shaped associations with dementia risk. Large bodyweight gain and loss alike are associated with an almost 3-fold higher risk of dementia, which may be amplified by APOE ɛ4.

In vivo brain iron concentration in healthy individuals at 3.0 T magnetic resonance imaging: a prospective cross-sectional study

OBJECTIVE

To quantify iron deposits in the basal ganglia and to evaluate its relation to age, sex, body mass index and brain laterality.

METHODS

Prospective observational study. Data were collected from the patients' electronic medical records. The concentration of iron deposits in the brain was assessed using whole-brain MRI at 3.0 Tesla.

RESULTS

138 participants were selected, 69.6% were female and the mean age was 47 ± 19 years. The κ coefficient was very strong (k = 0.92, p < 0.001). Age showed a moderate correlation between iron deposits in the caudate and putamen nuclei, on both right and left sides. In overall and right-handed individuals, a significantly higher iron concentration was observed on the left side for the caudate nucleus, putamen, thalamus, globus pallidus, and centrum semiovale, and for left-handed individuals, it was also observed in the left side-for the putamen and centrum semiovale. A weak correlation was shown between body mass index and left and right substantia nigra, left caudate nuclei, left putamen and right globus pallidus.

CONCLUSION

Our results showed a significantly higher iron deposit on the left side in most brain regions. In addition, the body mass index may also be related to iron overload, especially in the caudate nucleus.

ADVANCES IN KNOWLEDGE

Brain iron deposits may be normal, owing to aging, or be pathological, such as neurodegeneration. Thus, it is important to know how much is expected of iron deposition in the brain of healthy populations.

Apolipoprotein E Isoform-Dependent Effects on Human Amyloid Precursor Protein/Aβ-Induced Behavioral Alterations and Cognitive Impairments and Insoluble Cortical Aβ42 Levels

Mice expressing human amyloid precursor protein (APP) containing the dominant Swedish and Iberian mutations (AppNL-F ) or also Arctic mutation (AppNL-G-F ) show neuropathology and hippocampus-dependent cognitive impairments pertinent to Alzheimer's disease (AD) in mouse models at 18 and 6 months of age, respectively. Apolipoprotein E, involved in cholesterol metabolism, plays an important role in maintaining the brain. There are three human apolipoprotein E isoforms: E2, E3, and E4. Compared to E3, E4 increases while E2 protects against AD risk. At 6 months of age, prior to the onset of plaque pathology, E3, but not E4, protected against hAPP/Aβ-induced impairments in spatial memory retention in the Morris water maze. However, these earlier studies were limited as hapoE was not expressed outside the brain and E3 or E4 was not expressed under control of an apoE promotor, E2 was often not included, hAPP was transgenically overexpressed and both mouse and hAPP were present. Therefore, to determine whether apoE has isoform-dependent effects on hAPP/Aβ-induced behavioral alterations and cognitive impairments in adult female and male mice at 6 and 18 months of age, we crossed AppNL-G-F and AppNL-F mice with E2, E3, and E4 mice. To distinguish whether genotype differences seen at either time point were due to main effects of hAPP, hapoE, or hAPP × hapoE genetic interactions, we also behavioral and cognitively tested E2, E3, and E4 female and male mice at 6 and 18 months of age. We also compared behavioral and cognitive performance of 18-month-old AppNL-G-F and AppNL-F female and male mice on a murine apoE background along with that of age-and sex-matched C57BL/6J wild-type mice. For many behavioral measures at both time points there were APP × APOE interactions, supporting that apoE has isoform-dependent effects on hAPP/Aβ-induced behavioral and cognitive performance. NL-G-F/E3, but not NL-G-F/E2, mice had lower cortical insoluble Aβ42 levels than NL-G-F/E4 mice. NL-F/E3 and NL-F/E2 mice had lower cortical insoluble Aβ42 levels than NL-F/E4 mice. These results demonstrate that there are apoE isoform-dependent effects on hAPP/Aβ-induced behavioral alterations and cognitive impairments and cortical insoluble Aβ42 levels in mouse models containing only human APP and apoE.

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.

The identification of established modifiable mid-life risk factors for cardiovascular disease which contribute to cognitive decline: Korean Longitudinal Study of Aging (KLoSA)

INTRODUCTION

We explored how different chronic diseases, risk factors, and protective factors highly associated with cardiovascular diseases (CVD) are associated with dementia or Mild Cognitive Impairment (MCI) in Korean elders, with a focus on those that manifest in mid-life.

METHODS

A CVD-free cohort (n = 4289) from the Korean Longitudinal Study of Aging was selected to perform Cox mixed-effects proportional hazard regressions. Eighteen control variables with strong associations to CVD were chosen as explanatory variables, and Mini-Mental State Examination (MMSE) score cut-off for dementia and MCI were used as outcome variables.

RESULTS

The statistically significant (P < 0.05) adverse factors that contribute in developing dementia were age (aHR 1.07, 1.05-1.09), Centre for Epidemiological Studies Depression Scale (CESD-10) (aHR 1.17, 1.12-1.23), diagnosis with cerebrovascular disease (aHR 3.73, 1.81-7.66), living with diabetes (aHR 2.30, 1.22-4.35), and living with high blood pressure (HBP) (aHR 2.05, 1.09-3.87). In contrast, the statistically significant protective factors against developing dementia were current alcohol consumption (aHR 0.67, 0.46-0.99), higher educational attainment (aHR 0.36, 0.26-0.56), and regular exercise (aHR 0.37, 0.26-0.51). The factors with a statistically significant adverse association with progression to MCI were age (aHR 1.02, 1.01-1.03) and CESD-10 (aHR 1.17, 1.14-1.19). In contrast, the statistically significant protective factors against developing MCI were BMI (aHR 0.96, 0.94-0.98), higher educational attainment (aHR 0.33, 0.26-0.43), and regular exercise (aHR 0.83, 0.74-0.92).

CONCLUSION

In lieu of the protective factor of MCI and dementia, implementing regular exercise routine well before mid-life and cognitive decline is significant, with adjustments made for those suffering from health conditions, so they can continue exercising despite their morbidity. Further attention in diabetes care and management is needed for patients who already show decline in cognitive ability as it is likely that their MCI impacts their ability to manage their existing chronic conditions, which may adversely affect their cognitive ability furthermore.

Early mortality and cardiovascular disease, varied association with body mass index and its changes in insulin-treated diabetes: a nationwide study

BACKGROUND/OBJECTIVES

We investigated the hazards of cardiovascular diseases (CVDs) and all-cause death during follow-up according to baseline body mass index (BMI) and percent change in BMI among adults with insulin-treated diabetes.

SUBJECTS/METHODS

Using the Korean National Health Insurance Service datasets (2002-2017), the hazards of myocardial infarction (MI), stroke, and all-cause mortality during follow-up were analyzed according to baseline BMI and percent change in BMI among adults with insulin-treated diabetes and without baseline CVD and/or malignancy (N = 44,055).

RESULTS

At baseline, 67.3% of total subjects were either obese or overweight. During a mean 3.8 years, 1,081 MI and 1,562 stroke cases developed; 2,847 deaths occurred over a mean 3.9 years. Compared with normal weight, overweight and obesity were associated with lower hazards of outcomes [hazard ratio (95% CI): 0.836 (0.712-0.981), 0.794 (0.687-0.917) for MI; 0.829 (0.726-0.946), 0.772 (0.684-0.870) for stroke; 0.740 (0.672-0.816), 0.666 (0.609-0.728) for death, respectively]. Underweight was associated with a higher hazard of all-cause death during follow-up [hazard ratio (95% CI): 2.035 (1.695-2.443)]. When the group with minimum absolute value for percent change in BMI was set as a reference, the relative reduction in BMI was associated with increased hazards of MI, stroke, and all-cause death, and relative increase in BMI was associated with increased hazards of stroke and all-cause death during follow-up.

CONCLUSIONS

Among adults with insulin-treated diabetes, a high prevalence of overweight and obesity was observed, and baseline BMI category was inversely associated with CVD incidence and all-cause death during follow-up. Both weight loss and gain were associated with increased CVD incidence and all-cause death during follow-up, showing a U-shaped relationship between weight change and outcome. Stable body weight might be a predictor of a lower risk of CVDs and premature death among individuals with insulin-treated diabetes.

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.

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 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.

Smoking Cessation, Weight Change, and Risk of Parkinson's Disease: Analysis of National Cohort Data

BACKGROUND AND PURPOSE

To determine whether the postcessation weight gain modifies the protective effect of smoking on the development of Parkinson's disease (PD).

METHODS

This nationwide cohort study included 3,908,687 Korean males aged ≥40 years who underwent at least 2 health checkups biennially between 2009 and 2015. They were grouped into current smokers; quitters with body mass index (BMI) increase, maintenance, and decrease; and never smokers. The occurrence of incident PD was tracked, and Cox proportional-hazard models were used to adjust for potential confounding factors. We also analyzed the impact of weight change regardless of smoking status in the study population.

RESULTS

There were 6,871 incident PD cases observed during the 13,059,208 person-years of follow-up. The overall risk of PD was significantly lower in quitters than in never smokers [hazard ratio (HR)=0.78, 95% confidence interval (CI)=0.70-0.86]. The risk of PD was still lower in quitters with BMI increase (HR=0.80, 95% CI=0.65-0.98) and in those with BMI maintenance (HR=0.77, 95% CI=0.68-0.87). This tendency was also observed in quitters with BMI decrease (HR=0.76, 95% CI=0.55-1.06), although it was not as robust as in the other two groups. With respect to weight change alone, BMI increase (HR=1.10, 95% CI=1.02-1.18) but not BMI decrease (HR=1.06, 95% CI=0.98-1.14) significantly increased the PD risk compared to BMI maintenance.

CONCLUSIONS

Postcessation weight gain in males did not offset the protective impact of smoking on PD development, although overall weight gain predicted an increased risk of PD.

Conducting and Reporting a Clinical Research Using Korean Healthcare Claims Database

An increasing number of studies are using healthcare claims databases to assess healthcare intervention utilization patterns or outcomes in real-world clinical settings. However, methodological issues affecting study design or data analysis can make conducting and reporting these types of studies difficult. This review presents an overview of the types of information contained in claims data, describes some advantages and limitations of using claims data for research purposes, and outlines steps for utilizing the Korea Health Insurance Review and Assessment and National Health Insurance Service databases. The study also reviews epidemiological approaches utilizing healthcare claims databases (including cross-sectional, case-control, case-crossover, and cohort designs) with respect to protocol development, analysis, and reporting of results, and introduces relevant guidelines and checklists, including the Guidelines for Good Pharmacoepidemiology Practices, the Strengthening the Reporting of Observational Studies in Epidemiology checklist, and the Risk of Bias in Nonrandomized Studies of Interventions tool.

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.

Body Weight Variation Patterns as Predictors of Cognitive Decline over a 5 Year Follow-Up among Community-Dwelling Elderly (MAPT Study)

This study aimed to analyze associations between weight variation patterns and changes in cognitive function and hippocampal volume among non-demented, community-dwelling elderly. Sample was formed of 1394 adults >70 years (63.9% female), all volunteers from the Multidomain Alzheimer Preventive Trial (MAPT). Weight loss was defined as ≥5% of body weight decrease in the first year of follow-up; weight gain as ≥5% of weight increase; and stability if <5% weight variation. Cognition was examined by a Z-score combining four tests. Measures were assessed at baseline, 6, 12, 24, 36, 48, and 60 months of follow-up. Hippocampal volume was evaluated with magnetic resonance imaging in 349 subjects in the first year and at 36 months. Mixed models were performed. From the 1394 participants, 5.5% (n = 76) presented weight loss, and 9.0% (n = 125) presented weight gain. Cognitive Z-score decreased among all groups after 5 years, but decline was more pronounced among those who presented weight loss (adjusted between-group mean difference vs. stable: -0.24, 95%CI: -0.41 to -0.07; p = 0.006). After 3 years, hippocampal atrophy was observed among all groups, but no between-group differences were found. In conclusion, weight loss ≥5% in the first year predicted higher cognitive decline over a 5 year follow-up among community-dwelling elderly, independently of body mass index.