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Original Contribution |

Central Obesity and the Aging Brain FREE

William Jagust, MD; Danielle Harvey, PhD; Dan Mungas, PhD; Mary Haan, DrPH
[+] Author Affiliations

Author Affiliations: School of Public Health and Helen Wills Neuroscience Institute, University of California at Berkeley (Dr Jagust); Division of Biostatistics, Department of Public Health Sciences, School of Medicine, University of California at Davis (Dr Harvey); Department of Neurology, School of Medicine, University of California at Davis, Sacramento (Dr Mungas); and Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor (Dr Haan).


Arch Neurol. 2005;62(10):1545-1548. doi:10.1001/archneur.62.10.1545.
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Published online

Background  Central adiposity as an indicator of visceral fat is linked to vascular and metabolic factors that in turn are related to cognitive decline and dementia.

Objective  To determine whether larger waist-hip ratio (WHR) is associated with structural brain changes that underlie cognitive decline and dementia.

Design  Cross-sectional analysis of an epidemiologic cohort study of cognitive and functional decline (Sacramento Area Latino Study on Aging).

Setting  California Central Valley.

Participants  A total of 112 individuals selected from an ongoing cohort study of 1789 older Latino individuals. Baseline anthropomorphic measures (WHR) and measurements of fasting blood glucose, cholesterol, and insulin levels and blood pressure were obtained.

Main Outcome Measures  Baseline magnetic resonance images were analyzed quantitatively to determine the hippocampal volumes in the right and left hemispheres and rated for the percentage of white matter hyperintensities.

Results  Greater WHR (P = .02) and older age (P<.001) were negatively related to hippocampal volumes. The WHR and age were positively related to white matter hyperintensities (P = .02 and P = .001, respectively). A 1-SD increase in WHR was associated with a 0.2-SD decrease in hippocampal volume and a 27% increase in white matter hyperintensities. These relationships were not affected by adjustment for body mass index, total cholesterol, fasting blood glucose, and insulin levels or systolic blood pressure in the models.

Conclusion  A larger WHR may be related to neurodegenerative, vascular, or metabolic processes that affect brain structures underlying cognitive decline and dementia.

Figures in this Article

Increasing rates of obesity in the United States have led to widespread public concerns about an epidemic with profound negative health consequences.1 Although obesity is defined as a body mass index (BMI) of 30 or greater, the greatest association with vascular and metabolic disease involves abdominal obesity, measured as waist-hip ratio (WHR) or waist circumference, which is also increasing.2 The factors of abdominal obesity, hyperlipidemia, hypertension, and glucose intolerance frequently coexist and constitute the metabolic syndrome, an important risk factor for diabetes mellitus and cardiovascular disease. The metabolic syndrome is also prevalent in the United States, with some of the highest rates in Mexican American individuals.3

Obesity has recently been linked to both Alzheimer disease and alterations in brain structure seen with computed tomography.46 A host of potential factors may mediate these associations, including diabetes,7 hypertension,8 and vascular disease.9

Based on associations among obesity, metabolic and vascular disease, and dementia, it seems reasonable to further investigate changes in brain structure that may underlie these relationships. Magnetic resonance imaging (MRI) measures that have been linked to cognitive impairment and dementia are hippocampal volume (HV) and white matter hyperintensities (WMHs). Although it is also seen in other conditions, HV is highly associated with Alzheimer disease.10,11 Although also not entirely specific, WMHs are associated with cerebrovascular risk factors and cognitive decline.12,13 We recently reported that HV and WMHs both contribute independently to the risk of dementia in an epidemiologic cohort.14 Therefore, we sought to evaluate how WHR, considered a predictor of cardiovascular disease and a component of the metabolic syndrome, might be associated with changes in brain structure in this cohort.

SUBJECTS

Subjects were recruited for neuroimaging from a sample of community-dwelling Latino individuals 60 years and older who were residing in the Sacramento, Calif, area. Detailed information about sampling, screening, evaluation, and dementia ascertainment has been previously described.15 A subgroup of 122 subjects was selected for an imaging substudy from the larger cohort of 1789 individuals.14 Of the MRI subgroup, 112 individuals had complete data available for analysis for this report. The study was approved by the institutional review boards of participating institutions.

The WHR was measured twice and averaged by field staff in the subjects’ homes. The waist measurement was taken at the midpoint between the iliac crest and lower rib using an insertion tape and measured at the end of a normal expiration. Hip circumference was the maximum circumference over the buttocks below the iliac crest. The WHR was calculated as the ratio of waist circumference to hip circumference. The BMI was calculated as weight in kilograms (measured with a portable digital scale) divided by the square of height in meters (measured with a portable stadiometer). Brachial and ankle blood pressures were measured with a handheld Doppler probe. Morning fasting blood samples were taken for measurement of total cholesterol, glucose, and insulin levels.

MRI ACQUISITION AND ANALYSIS

Subjects underwent MRI (GE Signa system; General Electric, Milwaukee, Wis) using a sagittal fast spin-echo T2 sequence, an axial oblique spin-echo T2-weighted/proton density sequence, and a T1-weighted, coronal 3-dimensional spoiled gradient recalled echo inversion recovery prepped sequence.14 Measurement of HV and WMHs has previously been described.14 The HV measurements on the T1 images included CA1 through CA3, dentate gyrus, and subiculum. The WMHs were rated using a semiquantitative rating scale in which a rater evaluated uniformly formatted axial proton-density images with respect to a series of image standards that had quantitated magnetic resonance WMHs.

DATA ANALYSIS

Strategy for data analysis used linear regression with model building that was the same across analyses. The WMHs were not normally distributed and so were increased by 1 (to shift the lowest value from 0 to 1) and log transformed. The HV and WHR were transformed into z scores for all analyses for ease of interpretation. Subsequent analyses included multiple regression models accounting for potential confounders.

We performed unadjusted linear regressions to assess the relationship between measures of interest. Since our primary hypothesis concerned the relationship between WHR and MRI variables, we constructed models with WHR and age as the independent variables and HV or WMHs as the dependent variables. Subsequently, the models were adjusted for the effects of a group of covariates that largely reflected metabolic and vascular disease.

Characteristics of the sample are given in Table 1>. A total of 25% of the group was obese, with BMIs of 30 or greater. Ten percent of subjects were cognitively impaired but did not have dementia, an additional 21% had dementia, and the rest were cognitively healthy. Values for WMHs, HV, and cognitive function were previously reported to differ among these groups.14 However, these groups did not differ by WHR (P = .19 for a group by WHR analysis of variance). The high mean fasting glucose level reflects the 39% prevalence of type 2 diabetes mellitus as identified by either a medical history of the disease or prescription of hypoglycemic agents.

The results of multiple regression modeling for the average of the right and left HVs are presented in Table 2>. The WHR and age together accounted for 25% of the variability in HV, whereas WHR alone accounted for 4%. A 1-SD increase in age was associated with a 0.5-SD decrease in HV, whereas a 1-SD increase in WHR was associated with a 0.2-SD decrease in HV. Relationships between covariates and HV were evaluated and none, including sex, BMI, cholesterol level, systolic blood pressure, ankle-arm blood pressure index, fasting blood glucose level, or insulin level, were associated with HV. The strongest associations were seen with blood glucose level (partial R2 = 0.02, P = .10) and systolic blood pressure (partial R2 = 0.02, P = .15). When these covariates were added to the model with WHR and age, they did not significantly affect the results. Results using the individual values for right and left hemisphere HVs were similar to those for the average of the right and left. The regression for WHR and HV, controlling for the effects of age, is shown in Figure 1.

Place holder to copy figure label and caption
Figure 1.

Plot of waist-hip ratio vs age-adjusted hippocampal volume. There is a significant association between the 2 variables ( = 0.2, P = .02).

Graphic Jump Location
Table Graphic Jump LocationTable 2.  Multiple Regression Models for Hippocampal Volume and White Matter Hyperintensities

The results of the multiple regression model for WMHs are presented in Table 2>. Both WHR and age accounted for 13.5% of the variability in WMHs, and WHR alone accounted for 4.7% of the variability. Both variables were significantly associated with WMHs. A 1-SD increase in age was associated with a 42% increase in WMHs, whereas a 1-SD increase in WHR was associated with a 27% increase. Among the covariates, including sex, BMI, cholesterol level, systolic blood pressure, ankle-arm blood pressure index, and glucose and insulin levels, we found that the fasting glucose level and systolic blood pressure were significantly associated with WMHs (for glucose, partial R2 = 0.05, P = .01; and for systolic blood pressure, partial R2 = 0.14, P<.001). The only other variables that came close to a significant association were sex (partial R2 = 0.03, P = .07) and cholesterol level (partial R2 = 0.02, P = .15). When these confounders were included in the multivariate model, however, the relationship between WHR and WMHs did not change (the estimate was 0.29, partial R2 = 0.05, P = .05). Figure 2 shows the relationship between WHR and WMHs after controlling for the effects of age.

Place holder to copy figure label and caption
Figure 2.

Plot of waist-hip ratio vs age-adjusted log of white matter hyperintensities (WMHs). There is a significant association between the 2 variables (r = 0.22, P = .02).

Graphic Jump Location

We found that distribution and amount of body fat accounted for a small, but significant, proportion of variance in the size of the hippocampus and the amount of WMHs in this cohort of individuals with a high prevalence of obesity and glucose intolerance. Adjustment for covariates that included both generalized obesity (BMI) and a variety of cardiovascular variables did not affect these relationships. Although the strength of the associations is small, the estimates indicate moderate effects of increases in WHR on HV and WMHs. These effects are likely to be behaviorally relevant, since we have previously reported significant effects of both WMHs and HV on cognition in this cohort.14

Considerable evidence exists to support the idea that the MRI variables we chose for analysis are intimately related to metabolic and vascular disease. Smaller HVs have been reported in association with diabetes mellitus and poor glucose tolerance.16,17 Similarly, changes in brain white matter are well known to be associated with a variety of vascular factors, including hypertension and diabetes.12,13

Nevertheless, changes in glucose metabolism and vascular risk factors do not entirely explain the relationship between these changes in brain structure and WHR because inclusion of these variables in the regression models did not affect the associations. A number of other potential mechanisms might mediate these associations. Such possibilities include inflammatory mechanisms, mediated by proinflammatory cytokines such as interleukin 6 and tumor necrosis factor α, which are produced by adipose tissue.18,19 In addition, central adiposity has been suggested as an outcome related to chronic stress or allostatic load.20 Although chronic stress effects on the brain are poorly understood, cumulative effects have been proposed to exert deleterious adaptation of the hypothalamic-pituitary-adrenal axis that in turn produces hippocampal dysfunction.21 Although relationships between central obesity and such physiologic and anatomical changes are highly speculative, evidence exists that relates stress and hypothalamic-pituitary-adrenal axis dysfunction to hippocampal atrophy.22,23 Increased cortisol levels in aging are also associated with poor performance on memory tests and smaller HVs.24

The strength of the associations are small and could potentially be explained by residual confounding or comorbid illnesses. Nevertheless, standard measures of vascular and metabolic disease and cognitive status do not appear to account for the results.

These results are consistent with a growing body of evidence that links obesity, vascular disease, and inflammation to cognitive decline and dementia and provide additional evidence of the brain mechanisms that may mediate these associations. Vascular risk factors are well known to increase the risk of dementia, cognitive decline, and Alzheimer disease.12,15,25 Women, but not men, who develop dementia between the ages of 79 and 88 years had a higher BMI an average of 18 years earlier.5 In the same cohort, higher BMI (but not WHR) was associated with greater temporal lobe atrophy by visual rating of computed tomographic scans.6 These findings were not accounted for by vascular factors. In another cohort, variables that reflect the metabolic syndrome, including BMI, increased dementia risk independently of one another and were not simply reflective of cardiovascular disease or atherosclerosis.4 Our findings extend these observations by defining brain regions and potential pathophysiologic processes that may mediate these associations.

The findings reported herein are thus congruent with a wealth of data that indicate negative effects of obesity on cognitive function and also with data that implicate diabetes,26 inflammation,27 and stress28 as factors related to cognitive decline. Evidence that suggests that physical exercise may reduce the risk of dementia29 is also consistent with these results, since it can affect weight, insulin function, and potentially stress and is associated with diminished loss of brain tissue with age.30 The finding that a greater WHR is associated with both smaller hippocampi and more WMH demonstrates evidence of structural brain damage that should be at least partially modifiable by lifestyle changes.

Correspondence: William Jagust, MD, Helen Wills Neuroscience Institute, 132 Barker Hall, MC 3190, University of California, Berkeley, CA 94720 (jagust@berkeley.edu).

Accepted for Publication: March 4, 2004.

Author Contributions:Study concept and design: Jagust and Haan. Acquisition of data: Jagust, Mungas, and Haan. Analysis and interpretation of data: Jagust, Harvey, Haan, and Mungas. Drafting of the manuscript: Jagust. Critical revision of the manuscript for important intellectual content: Harvey, Mungas, and Haan. Statistical analysis: Harvey. Obtained funding: Haan. Administrative, technical, and material support: Jagust and Haan. Study supervision: Haan.

Funding/Support: This study was supported by National Institutes of Health grants AG12975, DK60753, and AG10220.

Flegal  KMCarroll  MDOgden  CLJohnson  CL Prevalence and trends in obesity among US adults 1999-2000. JAMA 2002;2881723- 1727
PubMed
Ford  ESMokdad  AHGiles  WH Trends in waist circumference among U.S. adults. Obes Res 2003;111223- 1231
PubMed
Ford  ESGiles  WHDietz  WH Prevalence of the metabolic syndrome among US adults: findings from the third national health and nutrition examination survey. JAMA 2002;287356- 359
PubMed
Kalmijn  SFoley  DWhite  L  et al.  Metabolic cardiovascular syndrome and risk of dementia in Japanese-American elderly men: the Honolulu-Asia aging study. Arterioscler Thromb Vasc Biol 2000;202255- 2260
PubMed
Gustafson  DRothenberg  EBlennow  KSteen  BSkoog  I An 18-year follow-up of overweight and risk of Alzheimer disease. Arch Intern Med 2003;1631524- 1528
PubMed
Gustafson  DLissner  LBengtsson  CBjorkelund  CSkoog  I A 24-year follow-up of body mass index and cerebral atrophy. Neurology 2004;631876- 1881
PubMed
Wu  JHHaan  MNLiang  JGhosh  DGonzalez  HMHerman  WH Impact of diabetes on cognitive function among older Latinos: a population-based cohort study. J Clin Epidemiol 2003;56686- 693
PubMed
Peila  RWhite  LRPetrovich  H  et al.  Joint effect of the APOE gene and midlife systolic blood pressure on late-life cognitive impairment: the Honolulu-Asia aging study. Stroke 2001;322882- 2889
PubMed
Hofman  AOtt  ABreteler  MM  et al.  Atherosclerosis, apolipoprotein E, and prevalence of dementia and Alzheimer's disease in the Rotterdam study. Lancet 1997;349151- 154
PubMed
Seab  JPJagust  WJWong  STSRoos  MSReed  BRBudinger  TF Quantitative NMR measurements of hippocampal atrophy in Alzheimer's disease. Magn Reson Med 1988;8200- 208
PubMed
Jack  CRDickson  DWParisi  JE  et al.  Antemortem MRI findings correlate with hippocampal neuropathology in typical aging and dementia. Neurology 2002;58750- 757
PubMed
Breteler  MMBvan Swieten  JCBots  ML  et al.  Cerebral white matter lesions, vascular risk factors, and cognitive function in a population-based study: the Rotterdam study. Neurology 1994;441246- 1252
PubMed
Longstreth  WTManolio  TAArnold  A  et al.  Clinical correlates of white matter findings on cranial magnetic resonance imaging of 3301 elderly people: The Cardiovascular Health Study. Stroke 1996;271274- 1282
PubMed
Wu  CCMungas  DPetkov  CI  et al.  Brain structure and cognition in a community sample of elderly Latinos. Neurology 2002;59383- 391
PubMed
Haan  MNMungas  DMGonzalez  HMOrtiz  TAAcharya  AJagust  WJ Prevalence of dementia in older Latinos: the influence of type 2 diabetes mellitus, stroke and genetic factors. J Am Geriatr Soc 2003;51169- 177
PubMed
den Heijer  TVermeer  SEVan Dijk  EJ  et al.  Type 2 diabetes and atrophy of medial temporal lobe structures on brain MRI. Diabetologia 2003;461604- 1610
PubMed
Convit  AWolf  OTTarshish  Cde Leon  MJ Reduced glucose tolerance is associated with poor memory performance and hippocampal atrophy among normal elderly. Proc Natl Acad Sci U S A 2003;1002019- 2022
PubMed
Hotamisligil  GSArner  PCaro  JFAtkinson  RLSpiegelman  BM Increased adipose tissue expression of tumor necrosis factor-alpha in human obesity and insulin resistance. J Clin Invest 1995;952409- 2415
PubMed
Kern  PASaghizadeh  MOng  JMBosch  RJDeem  RSimsolo  RB The expression of tumor necrosis factor in human adipose tissue: regulation by obesity, weight loss, and relationship to lipoprotein lipase. J Clin Invest 1995;952111- 2119
PubMed
McEwen  BS Sex, stress and the hippocampus: allostasis, allostatic load and the aging process. Neurobiol Aging 2002;23921- 939
PubMed
McEwen  BS Protective and damaging effects of stress mediators. N Engl J Med 1998;338171- 179
PubMed
Starkman  MNGebarski  SSBerent  SSchteingart  DE Hippocampal formation volume, memory dysfunction, and cortisol levels in patients with Cushing's syndrome. Biol Psychiatry 1992;32756- 765
PubMed
Sapolsky  R Glucocorticoids and hippocampal atrophy in neuropsychiatric disorders. Arch Gen Psychiatry 2000;57925- 935
PubMed
Lupien  SJde Leon  Mde Santi  S  et al.  Cortisol levels during human aging predict hippocampal atrophy and memory deficits. Nat Neurosci 1998;169- 73
PubMed
Haan  MShemanski  LJagust  WJKuller  LManolio  TBryan  N The role of APOE ε4 in modulating effects of other risk factors for cognitive decline in elderly persons. JAMA 1999;28240- 46
PubMed
Biessels  GJvan der Heide  LPKamal  ABleys  RLGispen  WH Ageing and diabetes: implications for brain function. Eur J Pharmacol 2002;4411- 14
PubMed
Yaffe  KKanaya  ALindquist  K  et al.  The metabolic syndrome, inflammation, and risk of cognitive decline. JAMA 2004;2922237- 2242
PubMed
Seeman  TEMcEwen  BSSinger  BHAlbert  MSRowe  JW Increase in urinary cortisol excretion and memory declines: MacArthur studies of successful aging. J Clin Endocrinol Metab 1997;822458- 2465
PubMed
Laurin  DVerreault  RLindsay  JMacPherson  KRockwood  K Physical activity and risk of cognitive impairment and dementia in elderly persons. Arch Neurol 2001;58498- 504
PubMed
Colcombe  SJErickson  KIRaz  N  et al.  Aerobic fitness reduces brain tissue loss in aging humans. J Gerontol A Biol Sci Med Sci 2003;58176- 180
PubMed

Figures

Place holder to copy figure label and caption
Figure 1.

Plot of waist-hip ratio vs age-adjusted hippocampal volume. There is a significant association between the 2 variables ( = 0.2, P = .02).

Graphic Jump Location
Place holder to copy figure label and caption
Figure 2.

Plot of waist-hip ratio vs age-adjusted log of white matter hyperintensities (WMHs). There is a significant association between the 2 variables (r = 0.22, P = .02).

Graphic Jump Location

Tables

Table Graphic Jump LocationTable 2.  Multiple Regression Models for Hippocampal Volume and White Matter Hyperintensities

References

Flegal  KMCarroll  MDOgden  CLJohnson  CL Prevalence and trends in obesity among US adults 1999-2000. JAMA 2002;2881723- 1727
PubMed
Ford  ESMokdad  AHGiles  WH Trends in waist circumference among U.S. adults. Obes Res 2003;111223- 1231
PubMed
Ford  ESGiles  WHDietz  WH Prevalence of the metabolic syndrome among US adults: findings from the third national health and nutrition examination survey. JAMA 2002;287356- 359
PubMed
Kalmijn  SFoley  DWhite  L  et al.  Metabolic cardiovascular syndrome and risk of dementia in Japanese-American elderly men: the Honolulu-Asia aging study. Arterioscler Thromb Vasc Biol 2000;202255- 2260
PubMed
Gustafson  DRothenberg  EBlennow  KSteen  BSkoog  I An 18-year follow-up of overweight and risk of Alzheimer disease. Arch Intern Med 2003;1631524- 1528
PubMed
Gustafson  DLissner  LBengtsson  CBjorkelund  CSkoog  I A 24-year follow-up of body mass index and cerebral atrophy. Neurology 2004;631876- 1881
PubMed
Wu  JHHaan  MNLiang  JGhosh  DGonzalez  HMHerman  WH Impact of diabetes on cognitive function among older Latinos: a population-based cohort study. J Clin Epidemiol 2003;56686- 693
PubMed
Peila  RWhite  LRPetrovich  H  et al.  Joint effect of the APOE gene and midlife systolic blood pressure on late-life cognitive impairment: the Honolulu-Asia aging study. Stroke 2001;322882- 2889
PubMed
Hofman  AOtt  ABreteler  MM  et al.  Atherosclerosis, apolipoprotein E, and prevalence of dementia and Alzheimer's disease in the Rotterdam study. Lancet 1997;349151- 154
PubMed
Seab  JPJagust  WJWong  STSRoos  MSReed  BRBudinger  TF Quantitative NMR measurements of hippocampal atrophy in Alzheimer's disease. Magn Reson Med 1988;8200- 208
PubMed
Jack  CRDickson  DWParisi  JE  et al.  Antemortem MRI findings correlate with hippocampal neuropathology in typical aging and dementia. Neurology 2002;58750- 757
PubMed
Breteler  MMBvan Swieten  JCBots  ML  et al.  Cerebral white matter lesions, vascular risk factors, and cognitive function in a population-based study: the Rotterdam study. Neurology 1994;441246- 1252
PubMed
Longstreth  WTManolio  TAArnold  A  et al.  Clinical correlates of white matter findings on cranial magnetic resonance imaging of 3301 elderly people: The Cardiovascular Health Study. Stroke 1996;271274- 1282
PubMed
Wu  CCMungas  DPetkov  CI  et al.  Brain structure and cognition in a community sample of elderly Latinos. Neurology 2002;59383- 391
PubMed
Haan  MNMungas  DMGonzalez  HMOrtiz  TAAcharya  AJagust  WJ Prevalence of dementia in older Latinos: the influence of type 2 diabetes mellitus, stroke and genetic factors. J Am Geriatr Soc 2003;51169- 177
PubMed
den Heijer  TVermeer  SEVan Dijk  EJ  et al.  Type 2 diabetes and atrophy of medial temporal lobe structures on brain MRI. Diabetologia 2003;461604- 1610
PubMed
Convit  AWolf  OTTarshish  Cde Leon  MJ Reduced glucose tolerance is associated with poor memory performance and hippocampal atrophy among normal elderly. Proc Natl Acad Sci U S A 2003;1002019- 2022
PubMed
Hotamisligil  GSArner  PCaro  JFAtkinson  RLSpiegelman  BM Increased adipose tissue expression of tumor necrosis factor-alpha in human obesity and insulin resistance. J Clin Invest 1995;952409- 2415
PubMed
Kern  PASaghizadeh  MOng  JMBosch  RJDeem  RSimsolo  RB The expression of tumor necrosis factor in human adipose tissue: regulation by obesity, weight loss, and relationship to lipoprotein lipase. J Clin Invest 1995;952111- 2119
PubMed
McEwen  BS Sex, stress and the hippocampus: allostasis, allostatic load and the aging process. Neurobiol Aging 2002;23921- 939
PubMed
McEwen  BS Protective and damaging effects of stress mediators. N Engl J Med 1998;338171- 179
PubMed
Starkman  MNGebarski  SSBerent  SSchteingart  DE Hippocampal formation volume, memory dysfunction, and cortisol levels in patients with Cushing's syndrome. Biol Psychiatry 1992;32756- 765
PubMed
Sapolsky  R Glucocorticoids and hippocampal atrophy in neuropsychiatric disorders. Arch Gen Psychiatry 2000;57925- 935
PubMed
Lupien  SJde Leon  Mde Santi  S  et al.  Cortisol levels during human aging predict hippocampal atrophy and memory deficits. Nat Neurosci 1998;169- 73
PubMed
Haan  MShemanski  LJagust  WJKuller  LManolio  TBryan  N The role of APOE ε4 in modulating effects of other risk factors for cognitive decline in elderly persons. JAMA 1999;28240- 46
PubMed
Biessels  GJvan der Heide  LPKamal  ABleys  RLGispen  WH Ageing and diabetes: implications for brain function. Eur J Pharmacol 2002;4411- 14
PubMed
Yaffe  KKanaya  ALindquist  K  et al.  The metabolic syndrome, inflammation, and risk of cognitive decline. JAMA 2004;2922237- 2242
PubMed
Seeman  TEMcEwen  BSSinger  BHAlbert  MSRowe  JW Increase in urinary cortisol excretion and memory declines: MacArthur studies of successful aging. J Clin Endocrinol Metab 1997;822458- 2465
PubMed
Laurin  DVerreault  RLindsay  JMacPherson  KRockwood  K Physical activity and risk of cognitive impairment and dementia in elderly persons. Arch Neurol 2001;58498- 504
PubMed
Colcombe  SJErickson  KIRaz  N  et al.  Aerobic fitness reduces brain tissue loss in aging humans. J Gerontol A Biol Sci Med Sci 2003;58176- 180
PubMed

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