[Skip to Content]
[Skip to Content Landing]
Figure.
Hazard Ratios for Midlife Weight Quartiles by the Rate of Weight Change per Decade
Hazard Ratios for Midlife Weight Quartiles by the Rate of Weight Change per Decade

The estimates are based on a model adjusted for sex, years of education, APOE*E4, and weight at study entry, with age as the time scale. The mean (SD) maximum weight measurements in midlife were 62.0 (5.1) kg for the first quartile (Q1), 75.9 (3.6) kg for the second quartile (Q2), 86.8 (2.9) kg for the third quartile (Q3), and 103.7 (11.8) kg for the fourth quartile (Q4). The observed median (fifth and 95th percentile) rates of weight change from midlife to study entry for the 4 weight quartiles were −0.4 (−6.5 to 5.2) kg per decade for Q1, −1.0 (−8.2 to 5.2) kg per decade for Q2, −1.7 (−9.4 to 6.0) kg per decade for Q3, and −2.3 (−14.4 to 7.7) kg per decade for Q4. We provided the fifth and 95th percentiles to give a broader sense of the distribution of weight change for each midlife weight quartile.

Table 1.  
Summary of Participants’ Characteristics by Sex
Summary of Participants’ Characteristics by Sex
Table 2.  
Summary of Participants’ Characteristics by Incident MCI
Summary of Participants’ Characteristics by Incident MCI
Table 3.  
Association of Weight Measurements With Incident Mild Cognitive Impairment Overall and by Sex
Association of Weight Measurements With Incident Mild Cognitive Impairment Overall and by Sex
Table 4.  
Association of Weight Measurements With Incident MCI Subtypesa
Association of Weight Measurements With Incident MCI Subtypesa
1.
Roberts  R, Knopman  DS.  Classification and epidemiology of MCI.  Clin Geriatr Med. 2013;29(4):753-772.PubMedGoogle ScholarCrossref
2.
Mitchell  AJ, Shiri-Feshki  M.  Rate of progression of mild cognitive impairment to dementia—meta-analysis of 41 robust inception cohort studies.  Acta Psychiatr Scand. 2009;119(4):252-265.PubMedGoogle ScholarCrossref
3.
Nourhashémi  F, Deschamps  V, Larrieu  S, Letenneur  L, Dartigues  JF, Barberger-Gateau  P; PAQUID study. Personnes Agées Quid.  Body mass index and incidence of dementia: the PAQUID study.  Neurology. 2003;60(1):117-119.PubMedGoogle ScholarCrossref
4.
Atti  AR, Palmer  K, Volpato  S, Winblad  B, De Ronchi  D, Fratiglioni  L.  Late-life body mass index and dementia incidence: nine-year follow-up data from the Kungsholmen Project.  J Am Geriatr Soc. 2008;56(1):111-116.PubMedGoogle ScholarCrossref
5.
Buchman  AS, Wilson  RS, Bienias  JL, Shah  RC, Evans  DA, Bennett  DA.  Change in body mass index and risk of incident Alzheimer disease.  Neurology. 2005;65(6):892-897.PubMedGoogle ScholarCrossref
6.
Fitzpatrick  AL, Kuller  LH, Lopez  OL,  et al.  Midlife and late-life obesity and the risk of dementia: cardiovascular health study.  Arch Neurol. 2009;66(3):336-342.PubMedGoogle ScholarCrossref
7.
Stewart  R, Masaki  K, Xue  QL,  et al.  A 32-year prospective study of change in body weight and incident dementia: the Honolulu-Asia Aging Study.  Arch Neurol. 2005;62(1):55-60.PubMedGoogle ScholarCrossref
8.
Gustafson  D, Rothenberg  E, Blennow  K, Steen  B, Skoog  I.  An 18-year follow-up of overweight and risk of Alzheimer disease.  Arch Intern Med. 2003;163(13):1524-1528.PubMedGoogle ScholarCrossref
9.
Whitmer  RA, Gustafson  DR, Barrett-Connor  E, Haan  MN, Gunderson  EP, Yaffe  K.  Central obesity and increased risk of dementia more than three decades later.  Neurology. 2008;71(14):1057-1064.PubMedGoogle ScholarCrossref
10.
Kivipelto  M, Ngandu  T, Fratiglioni  L,  et al.  Obesity and vascular risk factors at midlife and the risk of dementia and Alzheimer disease.  Arch Neurol. 2005;62(10):1556-1560.PubMedGoogle ScholarCrossref
11.
Xu  WL, Atti  AR, Gatz  M, Pedersen  NL, Johansson  B, Fratiglioni  L.  Midlife overweight and obesity increase late-life dementia risk: a population-based twin study.  Neurology. 2011;76(18):1568-1574.PubMedGoogle ScholarCrossref
12.
Chiang  CJ, Yip  PK, Wu  SC,  et al.  Midlife risk factors for subtypes of dementia: a nested case-control study in Taiwan.  Am J Geriatr Psychiatry. 2007;15(9):762-771. PubMedGoogle ScholarCrossref
13.
Qizilbash  N, Gregson  J, Johnson  ME,  et al.  BMI and risk of dementia in two million people over two decades: a retrospective cohort study.  Lancet Diabetes Endocrinol. 2015;3(6):431-436.PubMedGoogle ScholarCrossref
14.
Sturman  MT, de Leon  CF, Bienias  JL, Morris  MC, Wilson  RS, Evans  DA.  Body mass index and cognitive decline in a biracial community population.  Neurology. 2008;70(5):360-367.PubMedGoogle ScholarCrossref
15.
Cronk  BB, Johnson  DK, Burns  JM; Alzheimer’s Disease Neuroimaging Initiative.  Body mass index and cognitive decline in mild cognitive impairment.  Alzheimer Dis Assoc Disord. 2010;24(2):126-130.PubMedGoogle ScholarCrossref
16.
Gao  S, Nguyen  JT, Hendrie  HC,  et al.  Accelerated weight loss and incident dementia in an elderly African-American cohort.  J Am Geriatr Soc. 2011;59(1):18-25.PubMedGoogle ScholarCrossref
17.
St Sauver  JL, Grossardt  BR, Yawn  BP,  et al.  Data resource profile: the Rochester Epidemiology Project (REP) medical records–linkage system.  Int J Epidemiol. 2012;41(6):1614-1624.PubMedGoogle ScholarCrossref
18.
Roberts  RO, Geda  YE, Knopman  DS,  et al.  The Mayo Clinic Study of Aging: design and sampling, participation, baseline measures and sample characteristics.  Neuroepidemiology. 2008;30(1):58-69.PubMedGoogle ScholarCrossref
19.
Petersen  RC, Roberts  RO, Knopman  DS,  et al; The Mayo Clinic Study of Aging.  Prevalence of mild cognitive impairment is higher in men.  Neurology. 2010;75(10):889-897.PubMedGoogle ScholarCrossref
20.
Morris  JC.  The Clinical Dementia Rating (CDR): current version and scoring rules.  Neurology. 1993;43(11):2412-2414.PubMedGoogle ScholarCrossref
21.
Pfeffer  RI, Kurosaki  TT, Harrah  CH  Jr, Chance  JM, Filos  S.  Measurement of functional activities in older adults in the community.  J Gerontol. 1982;37(3):323-329.PubMedGoogle ScholarCrossref
22.
Smith  GE, Malec  JF, Ivnik  RJ.  Validity of the construct of nonverbal memory: a factor-analytic study in a normal elderly sample.  J Clin Exp Neuropsychol. 1992;14(2):211-221.PubMedGoogle ScholarCrossref
23.
Ivnik  RJ, Smith  GE, Cerhan  JH, Boeve  BF, Tangalos  EG, Petersen  RC.  Understanding the diagnostic capabilities of cognitive tests.  Clin Neuropsychol. 2001;15(1):114-124.PubMedGoogle ScholarCrossref
24.
Petersen  RC.  Mild cognitive impairment as a diagnostic entity.  J Intern Med. 2004;256(3):183-194.PubMedGoogle ScholarCrossref
25.
American Psychiatric Association.  Diagnostic and Statistical Manual of Mental Disorders. 4th ed. Washington, DC: American Psychiatric Association; 1994.
26.
Petersen  RC.  Clinical practice: mild cognitive impairment.  N Engl J Med. 2011;364(23):2227-2234.PubMedGoogle ScholarCrossref
27.
Johnson  DK, Wilkins  CH, Morris  JC.  Accelerated weight loss may precede diagnosis in Alzheimer disease.  Arch Neurol. 2006;63(9):1312-1317.PubMedGoogle ScholarCrossref
28.
Barrett-Connor  E, Edelstein  SL, Corey-Bloom  J, Wiederholt  WC.  Weight loss precedes dementia in community-dwelling older adults.  J Am Geriatr Soc. 1996;44(10):1147-1152.PubMedGoogle ScholarCrossref
29.
Sobów  T, Fendler  W, Magierski  R.  Body mass index and mild cognitive impairment-to-dementia progression in 24 months: a prospective study.  Eur J Clin Nutr. 2014;68(11):1216-1219. PubMedGoogle ScholarCrossref
30.
Tolppanen  AM, Ngandu  T, Kåreholt  I,  et al.  Midlife and late-life body mass index and late-life dementia: results from a prospective population-based cohort.  J Alzheimers Dis. 2014;38(1):201-209.PubMedGoogle Scholar
31.
Knopman  DS, Edland  SD, Cha  RH, Petersen  RC, Rocca  WA.  Incident dementia in women is preceded by weight loss by at least a decade.  Neurology. 2007;69(8):739-746.PubMedGoogle ScholarCrossref
32.
Albanese  E, Davis  B, Jonsson  PV,  et al.  Overweight and obesity in midlife and brain structure and dementia 26 years later: the AGES-Reykjavik Study.  Am J Epidemiol. 2015;181(9):672-679.PubMedGoogle ScholarCrossref
33.
Geda  YE, Roberts  RO, Mielke  MM,  et al.  Baseline neuropsychiatric symptoms and the risk of incident mild cognitive impairment: a population-based study.  Am J Psychiatry. 2014;171(5):572-581.PubMedGoogle ScholarCrossref
34.
Brodaty  H, Heffernan  M, Draper  B,  et al.  Neuropsychiatric symptoms in older people with and without cognitive impairment.  J Alzheimers Dis. 2012;31(2):411-420.PubMedGoogle Scholar
35.
Rosenberg  PB, Mielke  MM, Appleby  BS, Oh  ES, Geda  YE, Lyketsos  CG.  The association of neuropsychiatric symptoms in MCI with incident dementia and Alzheimer disease.  Am J Geriatr Psychiatry. 2013;21(7):685-695.PubMedGoogle ScholarCrossref
36.
Albers  MW, Gilmore  GC, Kaye  J,  et al.  At the interface of sensory and motor dysfunctions and Alzheimer’s disease.  Alzheimers Dement. 2015;11(1):70-98.PubMedGoogle ScholarCrossref
37.
Doty  RL.  Olfaction in Parkinson’s disease and related disorders.  Neurobiol Dis. 2012;46(3):527-552.PubMedGoogle ScholarCrossref
38.
Kovács  T, Cairns  NJ, Lantos  PL.  Olfactory centres in Alzheimer’s disease: olfactory bulb is involved in early Braak’s stages.  Neuroreport. 2001;12(2):285-288.PubMedGoogle ScholarCrossref
39.
Devanand  DP, Lee  S, Manly  J,  et al.  Olfactory deficits predict cognitive decline and Alzheimer dementia in an urban community.  Neurology. 2015;84(2):182-189.PubMedGoogle ScholarCrossref
40.
Wilson  RS, Schneider  JA, Arnold  SE, Tang  Y, Boyle  PA, Bennett  DA.  Olfactory identification and incidence of mild cognitive impairment in older age.  Arch Gen Psychiatry. 2007;64(7):802-808.PubMedGoogle ScholarCrossref
41.
Nguyen  JC, Killcross  AS, Jenkins  TA.  Obesity and cognitive decline: role of inflammation and vascular changes.  Front Neurosci. 2014;8:375.PubMedGoogle ScholarCrossref
42.
Gorelick  PB, Scuteri  A, Black  SE,  et al; American Heart Association Stroke Council; Council on Epidemiology and Prevention; Council on Cardiovascular Nursing; Council on Cardiovascular Radiology and Intervention; Council on Cardiovascular Surgery and Anesthesia.  Vascular contributions to cognitive impairment and dementia: a statement for healthcare professionals from the American Heart Association/American Stroke Association.  Stroke. 2011;42(9):2672-2713.PubMedGoogle ScholarCrossref
43.
Taki  Y, Kinomura  S, Sato  K,  et al.  Relationship between body mass index and gray matter volume in 1,428 healthy individuals.  Obesity (Silver Spring). 2008;16(1):119-124.PubMedGoogle ScholarCrossref
44.
Lee  YH, Martin  JM, Maple  RL, Tharp  WG, Pratley  RE.  Plasma amyloid-beta peptide levels correlate with adipocyte amyloid precursor protein gene expression in obese individuals.  Neuroendocrinology. 2009;90(4):383-390.PubMedGoogle ScholarCrossref
45.
Koga  S, Kojima  A, Kuwabara  S, Yoshiyama  Y.  Immunohistochemical analysis of tau phosphorylation and astroglial activation with enhanced leptin receptor expression in diet-induced obesity mouse hippocampus.  Neurosci Lett. 2014;571:11-16.PubMedGoogle ScholarCrossref
46.
Banks  WA, Burney  BO, Robinson  SM.  Effects of triglycerides, obesity, and starvation on ghrelin transport across the blood-brain barrier.  Peptides. 2008;29(11):2061-2065.PubMedGoogle ScholarCrossref
47.
Sumarac-Dumanovic  M, Stevanovic  D, Ljubic  A,  et al.  Increased activity of interleukin-23/interleukin-17 proinflammatory axis in obese women.  Int J Obes (Lond). 2009;33(1):151-156.PubMedGoogle ScholarCrossref
48.
Gemma  C, Bickford  PC.  Interleukin-1beta and caspase-1: players in the regulation of age-related cognitive dysfunction.  Rev Neurosci. 2007;18(2):137-148.PubMedGoogle ScholarCrossref
49.
André  C, Dinel  AL, Ferreira  G, Layé  S, Castanon  N.  Diet-induced obesity progressively alters cognition, anxiety-like behavior and lipopolysaccharide-induced depressive-like behavior: focus on brain indoleamine 2,3-dioxygenase activation.  Brain Behav Immun. 2014;41:10-21.PubMedGoogle ScholarCrossref
50.
Erion  JR, Wosiski-Kuhn  M, Dey  A,  et al.  Obesity elicits interleukin 1-mediated deficits in hippocampal synaptic plasticity.  J Neurosci. 2014;34(7):2618-2631.PubMedGoogle ScholarCrossref
51.
Cano  V, Valladolid-Acebes  I, Hernández-Nuño  F,  et al.  Morphological changes in glial fibrillary acidic protein immunopositive astrocytes in the hippocampus of dietary-induced obese mice [Published online June 6, 2014].  Neuroreport. doi:10.1097/WNR.0000000000000180.PubMedGoogle Scholar
Original Investigation
April 2016

Decline in Weight and Incident Mild Cognitive Impairment: Mayo Clinic Study of Aging

Author Affiliations
  • 1Mayo Clinic Graduate School of Medicine, Rochester, Minnesota
  • 2Department of Neurology, Mayo Clinic, Rochester, Minnesota
  • 3Division of Epidemiology, Department of Health Sciences Research, Mayo Clinic, Rochester, Minnesota
  • 4Division of Biomedical Statistics and Informatics, Department of Health Sciences Research, Mayo Clinic, Rochester, Minnesota
  • 5Department of Psychiatry and Psychology, Mayo Clinic, Rochester, Minnesota
  • 6Departments of Psychiatry and Psychology and of Neurology, Mayo Clinic, Scottsdale, Arizona
JAMA Neurol. 2016;73(4):439-446. doi:10.1001/jamaneurol.2015.4756
Abstract

Importance  Unintentional weight loss has been associated with risk of dementia. Because mild cognitive impairment (MCI) is a prodromal stage for dementia, we sought to evaluate whether changes in weight and body mass index (BMI) may predict incident MCI.

Objective  To investigate the association of change in weight and BMI with risk of MCI.

Design, Setting, and Participants  A population-based, prospective study of participants 70 years of age or older from the Mayo Clinic Study of Aging, which was initiated on October 1, 2004. Maximum weight and height in midlife (40-65 years of age) were retrospectively ascertained from the medical records of participants using a medical records–linkage system. The statistical analyses were performed between January and November 2015.

Main Outcomes and Measures  Participants were evaluated for cognitive outcomes of normal cognition, MCI, or dementia at baseline and prospectively assessed for incident events at each 15-month evaluation. The association of rate of change in weight and BMI with risk of MCI was investigated using proportional hazards models.

Results  Over a mean follow-up of 4.4 years, 524 of 1895 cognitively normal participants developed incident MCI (50.3% were men; mean age, 78.5 years). The mean (SD) rate of weight change per decade from midlife to study entry was greater for participants who developed incident MCI vs those who remained cognitively normal (−2.0 [5.1] vs −1.2 [4.9] kg; P = .006). A greater decline in weight per decade was associated with an increased risk of incident MCI (hazard ratio [HR], 1.04 [95% CI, 1.02-1.06]; P < .001) after adjusting for sex, education, and apolipoprotein E (APOE) ε4 allele. A weight loss of 5 kg per decade corresponds to a 24% increase in risk of MCI (HR, 1.24). A higher decrease in BMI per decade was also associated with incident MCI (HR, 1.08 [95% CI, 1.03-1.13]; P = .003).

Conclusions and Relevance  These findings suggest that increasing weight loss per decade from midlife to late life is a marker for MCI and may help identify persons at increased risk for MCI.

Introduction

Mild cognitive impairment (MCI) is a prodromal stage of dementia that provides us with the opportunity to study risk factors for dementia and to identify persons at increased risk of dementia. Approximately 5% to 15% of persons with MCI will progress to dementia per year.1,2 Therefore, the delay or prevention of MCI could also reduce the public health impact of dementia. Several modifiable risk factors are associated with an increased risk of MCI, including education, vascular risk factors, and related outcomes.1

Changes in body mass index (BMI, calculated as weight in kilograms divided by height in meters squared) and weight are also associated with increased risk of dementia, but, overall, the findings of different studies have been inconclusive. Some studies have reported associations of lower late-life BMI and faster decline in weight or BMI in late life with increased risk of dementia3-7; others suggest that being overweight at older ages,8 central obesity in midlife,9 or higher midlife BMI10,11 increase the risk of dementia and Alzheimer dementia. In contrast, one study12 found that being underweight or overweight in midlife may increase the risk of dementia in late life. Furthermore, other investigators have reported that obesity in midlife is associated with a decreased risk of cognitive decline and dementia,13 or they have not observed a predictive role of high BMI in late life for cognitive decline.14 The association of BMI with MCI is even less certain. Few investigators have observed a decline in BMI prior to a diagnosis of MCI.15,16 The association of declining weight and BMI with MCI may have implications for preventive strategies for MCI. The objective of our study was to examine associations of longitudinal changes in weight and BMI with incident MCI among participants in the Mayo Clinic Study of Aging.

Box Section Ref ID

Key Points

  • Question: Is there a loss of weight prior to the diagnosis of mild cognitive impairment (MCI) as observed with Alzheimer dementia?

  • Findings: In a prospective, population-based, cohort study of 1895 cognitively normal persons 70 years of age or older at enrollment, a greater loss of weight per decade from midlife to late life was significantly associated with an increased risk of incident MCI.

  • Meaning: Increasing weight loss per decade from midlife to late life is a marker for MCI and may help identify persons at increased risk for MCI.

Methods
Study Participants

The study design and method have been previously published17-19 and are only briefly described herein. Participants were enrolled in the population-based Mayo Clinic Study of Aging established in Olmsted County, Minnesota. At the initiation of the study, a sampling frame of Olmsted County residents who were 70 to 89 years of age on October 1, 2004 (with a total population of 9953), was constructed using the medical records–linkage system of the Rochester Epidemiology Project.17 Participants were randomly selected from this sampling frame, and those who were eligible (ie, without dementia or in hospice care) were recruited to the study. Recruitment is ongoing to maintain the sample size, and participants are seen every 15 months. The present study includes participants who were cognitively normal at the baseline evaluation, had at least 1 follow-up evaluation, and had data on maximum weight and height in midlife (40-65 years of age; mean age, 58.6). Our study was approved by the institutional review boards of the Mayo Clinic and the Olmsted Medical Center. Written informed consent was obtained from each participant prior to participation.

Participant Evaluation

Participants were evaluated by a nurse or a study coordinator who assessed their memory and administered the Clinical Dementia Rating scale20 and the Functional Activities Questionnaire21 to the participant’s informant. Each participant underwent neuropsychological testing using 9 tests to assess performance in 4 cognitive domains: memory, executive function, language, and visuospatial skills.18,19,22,23 Participants also underwent a neurological evaluation by a physician.

Identification of MCI/Dementia

The nurse or the study coordinator, the physician who evaluated the participant, and a neuropsychologist reviewed all data collected for each participant. A diagnosis of MCI, dementia, or normal cognition was made by consensus.18 Participants were classified as cognitively normal if they performed in the normative range and did not meet criteria for MCI24 or for dementia.25 Incident MCI cases were classified as amnestic MCI if the memory domain was impaired or nonamnestic MCI if the memory domain was not impaired.26

Assessment of Weight, Height, and BMI at Baseline and Follow-up Evaluations

Weight and height were measured at each evaluation, and BMI was computed. The maximum weight and height in midlife (mean age, 58.6 years) were ascertained from the medical record of each participant by trained nurse abstractors using the medical records–linkage system of the Rochester Epidemiology Project.

Assortment of Other Covariates

Demographic variables (including age, sex, and education) were obtained at the baseline visit for each participant. A history of type 2 diabetes, hypertension, coronary heart disease, and stroke were abstracted from the medical records at baseline and during follow-up. Depressive symptoms were assessed with the Beck Depression Inventory. History of cigarette smoking (never, former, or current) and diagnosed alcohol problems were assessed from self-report. Current medications were assessed from the medication bottles at each evaluation. Genotyping was performed to determine apolipoprotein E ε4 (APOE*E4) carrier status at baseline.

Statistical Analysis

All cognitively normal participants at baseline were considered at risk for incident MCI. Onset of MCI was assigned at the midpoint between the last assessment as cognitively normal and the first-ever assessment as having MCI. Persons who developed dementia without an intervening MCI diagnosis were presumed to have had an undetected MCI phase. We computed the follow-up duration from baseline to MCI onset for incident cases and through the date of the last follow-up for participants who remained cognitively normal. Participants who refused to participate, who could not be contacted, or who died during follow-up were censored at their last evaluation.

We computed the rate of weight change (kilograms per decade) from the maximum weight in midlife through follow-up, including late-life weight measurements as a time-dependent variable. We investigated the association of weight change with incident MCI using the Cox proportional hazards model and reported hazard ratios (HRs) and 95% CIs; in separate models, we included maximum weight in midlife or late-life weight. We examined confounding by APOE*E4, diabetes, hypertension, stroke, and cigarette smoking, with each variable added separately, and effect modification by age, sex, and APOE*E4 by including interaction terms of these covariates with rate of weight change.

The multivariable models were as follows: Model 1 included sex (where applicable), education, and APOE*E4 genotype (APOE*E4 carrier vs noncarrier), and model 2 included the model 1 variables and the following potential confounders: alcohol problem (yes vs no), depressive symptoms (Beck Depression Inventory score of ≥16), use of statins, diabetes, hypertension, coronary heart disease, cigarette smoking (never vs former or current), and stroke.

We also examined the effect of including height in the models. In a separate model, we included both maximum weight in midlife and late-life weight, but not weight change, in the same model and examined the associations with MCI. We repeated the analyses using rate of change in BMI (unit/decade). All hypothesis testing was conducted assuming an α = .05 significance level and a 2-sided alternative hypothesis. All statistical analyses were performed using SAS, version 9.3 (SAS Institute).

Results

The characteristics of the 1895 cognitively normal participants at baseline (50.3% men; mean age, 78.5 years) are summarized by sex in Table 1. Men had a higher frequency of former or current smoking (61.2% vs 36.0%; P < .001), diabetes (20.4% vs 14.3%; P = .001), and coronary artery disease (49.2% vs 29.1%; P < .001) than women. Women had a nonsignificantly greater mean rate of weight change per decade from midlife to study entry compared with men, but a lower mean maximum weight and a lower mean BMI in midlife compared with men.

Over a mean (SD) follow-up of 4.4 (2.4) years, 524 participants developed incident MCI (Table 2). Participants who developed incident MCI were older, more likely to be carriers of APOE*E4, and more likely to have diabetes, hypertension, stroke, or coronary artery disease compared with participants who remained cognitively normal. The mean (SD) weight change was greater for participants who developed incident MCI than for those who remained cognitively normal (−2.0 [5.1] vs −1.2 [4.9] kg; P = .006). The mean (SD) loss of weight per decade was greater in men who developed incident MCI than in men who did not (−2.1 [5.3] vs −1.0 [4.6] kg; P = .02) but was similar for women who developed incident MCI and women who did not (−1.9 [4.8] vs −1.5 [5.3]; P = .12).

A loss of weight from midlife was associated with an increased risk of incident MCI after adjustment for sex, education, and APOE*E4 (Table 3, model 1). Based on our proportional hazards models, a weight loss of 5 kg/decade corresponds to a 24% increase in risk of MCI (HR, 1.24). Table 3 also describes the effects of adjusting for maximum midlife weight and weight in late life, separately or simultaneously, in models with or without weight change.

When maximum midlife weight and late-life weight were included in the same model as weight change, neither was significantly associated with MCI, but weight change remained significantly associated with MCI. However, when both maximum midlife weight and late-life weight, but not weight change, were included in the same model, a higher maximum midlife weight and a low late-life weight were associated with an increased risk of MCI. Consistent with results for weight change, a greater decrease in BMI per decade (ie, unit decrease) was associated with an increased risk of MCI (HR, 1.08 [95% CI, 1.03-1.13]; P = .003), but the model fit was better using weight change.

When we simultaneously adjusted for potential confounders, the associations of weight change with MCI persisted (Table 3, model 2). However, simultaneously adjusting for these variables in a multivariable model with weight change could result in overcontrolling because these conditions are in the causal pathway from obesity to cognitive impairment.

There was no significant interaction of sex with weight change; however, given the higher risk of MCI in men than women in our cohort, we have reported results by sex (Table 3). The effect sizes were greater in men than in women. There was a significant interaction between age and maximum midlife weight with regard to MCI risk (P = .02 for interaction). The associations of a 5-kg difference in maximum midlife weight with MCI were stronger for persons older at baseline (HR, 1.05 [95% CI, 1.01-1.10] for those 70-74 years of age [P = .03]; HR, 1.07 [95% CI, 1.03-1.12] for those 75-79 years of age [P = .001]; HR, 1.08 [95% CI, 1.04-1.12] for those 80-84 years of age [P < .001]; and HR, 1.09 [95% CI, 1.04-1.14] for those ≥85 years of age [P < .001]). There was no interaction of vascular risk factors with weight change (data are not presented).

The Figure illustrates interrelationships of midlife weight, weight change, and MCI risk. There is no association of midlife weight with MCI after weight change is taken into account. The Figure demonstrates that the slopes for the 4 quartiles of midlife weight do not significantly differ. For persons in the upper midlife weight quartile (ie, the fourth quartile), the risk of MCI increased by 39% (HR, 1.39 [95% CI, 1.02-1.82]) for a weight change of −10 kg/decade. For persons in the lowest quartile (ie, the first quartile), the risk of MCI increased by 78% (HR, 1.78 [95% CI, 0.99-3.21]) for a decrease of −10 kg/decade. The corresponding increases in risk of MCI per −10 kg/decade were 69% (HR, 1.69 [95% CI, 1.04-2.74]) for the second quartile and 61% (HR, 1.61 [95% CI, 1.08-2.38]) for the third quartile. Thus, there is no significant interaction between midlife weight and weight change in determining the risk of MCI (P = .80). Similarly, there was no significant difference in the intercepts of the 4 lines based on the general test comparing the 4 groups (P = .47); that is, after taking into account the rate of weight change, we found that there was no significant contribution of midlife weight to incident MCI. The specific test directly comparing the slopes in the upper and lower quartiles was not significant (P = .43). When we studied the association of weight change with MCI subtypes separately, we found that weight change was significantly associated with amnestic MCI but not with nonamnestic MCI (Table 4), which suggests that loss of weight may involve Alzheimer dementia–related mechanisms.

Discussion

The results of this population-based elderly cohort study demonstrate that a higher rate of weight loss from midlife to late life and a lower weight in late life are markers of risk for MCI. A greater rate of weight loss or decrease in BMI from midlife to late life was associated with an increased risk of MCI. After taking into account rate of weight change, we found that midlife weight and late-life weight do not contribute to risk of MCI. However, without accounting for rate of change in weight, we found that a higher maximum weight in midlife is associated with an increased risk of MCI and that lower weight in late life is also associated with an increased risk of MCI.

The association of greater weight loss with MCI suggests that weight loss may be a marker for risk of MCI. While weight loss may not be causally related to MCI, we hypothesize that weight loss may represent a prodromal stage or an early manifestation of MCI. Consistent with this, there was no interaction of weight loss with midlife weight; even among persons who were of normal weight in midlife, a greater weight loss was associated with an increased risk of MCI in late life.

An important strength of our study is the ability to assess maximum midlife weight from the medical records of participants and from direct measurements in late life. From these measurements, we demonstrated that the age at which weight is assessed is important when investigating the association of weight with risk of MCI. Specifically, when we simultaneously considered maximum midlife and late-life weight in the same model, a higher maximum midlife weight and lower weight in late life were both associated with incident MCI. However, our findings suggest that weight loss is the key weight-related marker of incident MCI in the elderly. The association of weight loss per decade with incident MCI was stronger than estimates for maximum midlife weight or for low weight in late life when these latter variables were simultaneously considered.

Our findings for MCI are consistent with the findings of other prospective studies that correlated weight loss with the increased risk of dementia. In a study of controls for a dementia cohort, greater weight loss preceded the diagnosis of Alzheimer dementia.27 In a community-dwelling elderly cohort, men and women who developed probable or possible Alzheimer dementia experienced significant weight loss preceding the diagnosis compared with persons who remained cognitively normal.28 In a small study of participants with MCI,29 a low initial BMI and weight loss during follow-up were associated with a significantly greater risk of developing dementia. In a population-based cohort, a higher midlife BMI was related to a higher risk of dementia and Alzheimer dementia, independent of obesity-related risk factors and comorbidities.30 In an elderly African American cohort, participants who developed MCI had a greater rate of weight loss (revealed by repeated BMI measurements) compared with elderly participants who remained cognitively normal.16 Similarly, in a case-control study in Olmsted County, weight loss was associated with a greater risk of dementia in women but not in men.31 In the prospective Honolulu Aging Study, weight loss preceded onset of dementia in a cohort of men who were followed up for 26 years.7,27,31

Contrary to our findings, a higher BMI in both midlife and late life was associated with decreased risk of dementia in a large population-based retrospective study.13 Potential issues that may account for those findings13 include lack of clarity on age at assessment of weight, BMI, and onset of dementia. These may have implications for the findings of this study13 if there is a mix of timings of age at assessment of weight and BMI, with the majority of people being assessed at older ages. In another large population-based prospective study,32 being overweight or obese in midlife was not associated with increased risk of dementia.

Weight loss prior to MCI or dementia may be a component of the predementia syndrome. If weight loss is a prodromal stage of dementia, we would expect the association between weight loss and MCI to be similar across midlife weight classes. Indeed, the associations between weight loss and MCI did not differ across midlife weight quartiles, suggesting that the hypothesis of weight loss as a prodromal predementia stage is likely.

The association of weight loss with cognitive impairment may involve direct causal mechanisms or may be due to reverse causality or a shared etiology. With regard to causal mechanisms, weight loss prior to cognitive impairment may be related to what has been termed anorexia of aging. While the direct cause of this anorexia is not clear, we speculate that the dysfunctional production of certain hormones (cholecystokinin, leptin, cytokines, dynorphin, neuropeptide Y, and serotonin) on dietary intakes and energy metabolism may lead to reduced dietary intakes that affect MCI risk. With regard to reverse causality, neuropsychiatric symptoms such as depression and apathy, which are prodromal and predictors of MCI and dementia, may contribute to decreased appetite and weight loss prior to the diagnosis of these conditions.33-35 Finally, with regard to a shared etiology, protein deposits including Lewy bodies, tau, or amyloid have been identified in the olfactory bulb and central olfactory pathways prior to the onset of dementia, and olfactory dysfunction is a marker for cognitive impairment and dementia.36-40 Thus, impairment in smell with related changes in taste may contribute to decreased appetite, reduced dietary intake, and the weight loss observed with MCI, Alzheimer dementia, and other neurodegenerative conditions.

The association of high midlife weight with MCI may involve effects of obesity on the brain through cerebrovascular disease and metabolic abnormalities (eg, glucose metabolism and insulin signaling).41 Obesity-related brain pathology likely includes hypoperfusion,42 neuronal injury and death,42 brain atrophy,43 cerebrovascular dysfunction,42 increased levels of β-amyloid precursor protein,44 increased tau expression,45 blood-brain barrier dysfunction,46 systemic47,48 and central49 inflammation-related pathologies, and dysfunction of microglia and astrocytes.50,51

A potential limitation of our study is that it was not possible to determine whether weight loss was intentional or unintentional. Given the consistency of the association of weight loss with incident MCI across all midlife weight quartiles, it is most likely unintentional weight loss. Despite the limited ethnic diversity of the study cohort, our findings are consistent with the findings from an African American cohort.16

Additional strengths of our study include the large cohort and population-based design. Participants were clinically assessed for risk of MCI or dementia. Furthermore, information on clinical conditions was abstracted from the medical record rather than from self-report.

Conclusions

In summary, our findings suggest that an increasing rate of weight loss from midlife to late life is a marker for MCI and may help identify persons at increased risk of MCI.

Back to top
Article Information

Corresponding Author: Rosebud O. Roberts, MB, ChB, Department of Health Sciences Research, Mayo Clinic, 200 First St SW, Rochester, MN 55905 (roberts.rosebud@mayo.edu).

Accepted for Publication: December 9, 2015.

Correction: This article was corrected on January 23, 2017, to fix the misspelling of an author’s surname.

Published Online: February 1, 2016. doi:10.1001/jamaneurol.2015.4756

Author Contributions: Dr Roberts had full access to all of the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis.

Study concept and design: Petersen, Roberts.

Acquisition, analysis, or interpretation of data: All authors.

Drafting of the manuscript: Alhurani, Vassilaki, Roberts.

Critical revision of the manuscript for important intellectual content: Vassilaki, Aakre, Mielke, Kremers, Machulda, Geda, Knopman, Petersen, Roberts.

Statistical analysis: Aakre, Kremers.

Obtained funding: Mielke, Knopman, Petersen, Roberts.

Administrative, technical, or material support: Petersen, Roberts.

Study supervision: Kremers, Roberts.

Conflict of Interest Disclosures: Dr Roberts receives funding from the National Institutes of Health. Dr Knopman serves as deputy editor for Neurology; serves on a data safety monitoring board for Lundbeck Pharmaceuticals and for the Dominantly Inherited Alzheimer Network study; is an investigator in clinical trials sponsored by TauRX Pharmaceuticals, Lilly Pharmaceuticals, and the Alzheimer’s Disease Cooperative Study; and receives research support from the National Institutes of Health. Dr Mielke receives research grants from the National Institutes of Health/National Institute on Aging, the Alzheimer Drug Discovery Foundation, and the Lewy Body Association. Dr Petersen serves on data monitoring committees for Pfizer and Janssen Alzheimer Immunotherapy; is a consultant for Roche, Merck, Genentech, Biogen, and Eli Lilly; and receives publishing royalties from Mild Cognitive Impairment (Oxford University Press, 2003) and research support from the National Institute of Health. No other disclosures are reported.

Funding/Support: The study was supported by the National Institutes of Health (grants U01 AG006786, K01 AG028573, P50 AG016574, and K01 MH068351), the Mayo Foundation for Medical Education and Research, the Robert H. and Clarice Smith and Abigail van Buren Alzheimer’s Disease Research Program, the Clinical and Translational Science Award (grant UL1 TR000135), which supports the Mayo Clinic Center for Clinical and Translational Science, and the National Center for Advancing Translational Sciences, a component of the National Institutes of Health, and was made possible by the Rochester Epidemiology Project (grant R01AG034676).

Role of the Funder/Sponsor: The funders had no role in the design and conduct of study; collection, management, analysis, or interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication.

Additional Contributions: We thank Sondra Buehler, AA, Division of Epidemiology, Department of Health Sciences Research, for administrative support; Mary Dugdale, RN, and Connie Fortner, RN, Division of Epidemiology, Department of Health Sciences Research, for abstraction of medical record data; and the Mayo Clinic Study of Aging participants and staff of the Mayo Clinic Alzheimer’s Disease Patient Registry.

References
1.
Roberts  R, Knopman  DS.  Classification and epidemiology of MCI.  Clin Geriatr Med. 2013;29(4):753-772.PubMedGoogle ScholarCrossref
2.
Mitchell  AJ, Shiri-Feshki  M.  Rate of progression of mild cognitive impairment to dementia—meta-analysis of 41 robust inception cohort studies.  Acta Psychiatr Scand. 2009;119(4):252-265.PubMedGoogle ScholarCrossref
3.
Nourhashémi  F, Deschamps  V, Larrieu  S, Letenneur  L, Dartigues  JF, Barberger-Gateau  P; PAQUID study. Personnes Agées Quid.  Body mass index and incidence of dementia: the PAQUID study.  Neurology. 2003;60(1):117-119.PubMedGoogle ScholarCrossref
4.
Atti  AR, Palmer  K, Volpato  S, Winblad  B, De Ronchi  D, Fratiglioni  L.  Late-life body mass index and dementia incidence: nine-year follow-up data from the Kungsholmen Project.  J Am Geriatr Soc. 2008;56(1):111-116.PubMedGoogle ScholarCrossref
5.
Buchman  AS, Wilson  RS, Bienias  JL, Shah  RC, Evans  DA, Bennett  DA.  Change in body mass index and risk of incident Alzheimer disease.  Neurology. 2005;65(6):892-897.PubMedGoogle ScholarCrossref
6.
Fitzpatrick  AL, Kuller  LH, Lopez  OL,  et al.  Midlife and late-life obesity and the risk of dementia: cardiovascular health study.  Arch Neurol. 2009;66(3):336-342.PubMedGoogle ScholarCrossref
7.
Stewart  R, Masaki  K, Xue  QL,  et al.  A 32-year prospective study of change in body weight and incident dementia: the Honolulu-Asia Aging Study.  Arch Neurol. 2005;62(1):55-60.PubMedGoogle ScholarCrossref
8.
Gustafson  D, Rothenberg  E, Blennow  K, Steen  B, Skoog  I.  An 18-year follow-up of overweight and risk of Alzheimer disease.  Arch Intern Med. 2003;163(13):1524-1528.PubMedGoogle ScholarCrossref
9.
Whitmer  RA, Gustafson  DR, Barrett-Connor  E, Haan  MN, Gunderson  EP, Yaffe  K.  Central obesity and increased risk of dementia more than three decades later.  Neurology. 2008;71(14):1057-1064.PubMedGoogle ScholarCrossref
10.
Kivipelto  M, Ngandu  T, Fratiglioni  L,  et al.  Obesity and vascular risk factors at midlife and the risk of dementia and Alzheimer disease.  Arch Neurol. 2005;62(10):1556-1560.PubMedGoogle ScholarCrossref
11.
Xu  WL, Atti  AR, Gatz  M, Pedersen  NL, Johansson  B, Fratiglioni  L.  Midlife overweight and obesity increase late-life dementia risk: a population-based twin study.  Neurology. 2011;76(18):1568-1574.PubMedGoogle ScholarCrossref
12.
Chiang  CJ, Yip  PK, Wu  SC,  et al.  Midlife risk factors for subtypes of dementia: a nested case-control study in Taiwan.  Am J Geriatr Psychiatry. 2007;15(9):762-771. PubMedGoogle ScholarCrossref
13.
Qizilbash  N, Gregson  J, Johnson  ME,  et al.  BMI and risk of dementia in two million people over two decades: a retrospective cohort study.  Lancet Diabetes Endocrinol. 2015;3(6):431-436.PubMedGoogle ScholarCrossref
14.
Sturman  MT, de Leon  CF, Bienias  JL, Morris  MC, Wilson  RS, Evans  DA.  Body mass index and cognitive decline in a biracial community population.  Neurology. 2008;70(5):360-367.PubMedGoogle ScholarCrossref
15.
Cronk  BB, Johnson  DK, Burns  JM; Alzheimer’s Disease Neuroimaging Initiative.  Body mass index and cognitive decline in mild cognitive impairment.  Alzheimer Dis Assoc Disord. 2010;24(2):126-130.PubMedGoogle ScholarCrossref
16.
Gao  S, Nguyen  JT, Hendrie  HC,  et al.  Accelerated weight loss and incident dementia in an elderly African-American cohort.  J Am Geriatr Soc. 2011;59(1):18-25.PubMedGoogle ScholarCrossref
17.
St Sauver  JL, Grossardt  BR, Yawn  BP,  et al.  Data resource profile: the Rochester Epidemiology Project (REP) medical records–linkage system.  Int J Epidemiol. 2012;41(6):1614-1624.PubMedGoogle ScholarCrossref
18.
Roberts  RO, Geda  YE, Knopman  DS,  et al.  The Mayo Clinic Study of Aging: design and sampling, participation, baseline measures and sample characteristics.  Neuroepidemiology. 2008;30(1):58-69.PubMedGoogle ScholarCrossref
19.
Petersen  RC, Roberts  RO, Knopman  DS,  et al; The Mayo Clinic Study of Aging.  Prevalence of mild cognitive impairment is higher in men.  Neurology. 2010;75(10):889-897.PubMedGoogle ScholarCrossref
20.
Morris  JC.  The Clinical Dementia Rating (CDR): current version and scoring rules.  Neurology. 1993;43(11):2412-2414.PubMedGoogle ScholarCrossref
21.
Pfeffer  RI, Kurosaki  TT, Harrah  CH  Jr, Chance  JM, Filos  S.  Measurement of functional activities in older adults in the community.  J Gerontol. 1982;37(3):323-329.PubMedGoogle ScholarCrossref
22.
Smith  GE, Malec  JF, Ivnik  RJ.  Validity of the construct of nonverbal memory: a factor-analytic study in a normal elderly sample.  J Clin Exp Neuropsychol. 1992;14(2):211-221.PubMedGoogle ScholarCrossref
23.
Ivnik  RJ, Smith  GE, Cerhan  JH, Boeve  BF, Tangalos  EG, Petersen  RC.  Understanding the diagnostic capabilities of cognitive tests.  Clin Neuropsychol. 2001;15(1):114-124.PubMedGoogle ScholarCrossref
24.
Petersen  RC.  Mild cognitive impairment as a diagnostic entity.  J Intern Med. 2004;256(3):183-194.PubMedGoogle ScholarCrossref
25.
American Psychiatric Association.  Diagnostic and Statistical Manual of Mental Disorders. 4th ed. Washington, DC: American Psychiatric Association; 1994.
26.
Petersen  RC.  Clinical practice: mild cognitive impairment.  N Engl J Med. 2011;364(23):2227-2234.PubMedGoogle ScholarCrossref
27.
Johnson  DK, Wilkins  CH, Morris  JC.  Accelerated weight loss may precede diagnosis in Alzheimer disease.  Arch Neurol. 2006;63(9):1312-1317.PubMedGoogle ScholarCrossref
28.
Barrett-Connor  E, Edelstein  SL, Corey-Bloom  J, Wiederholt  WC.  Weight loss precedes dementia in community-dwelling older adults.  J Am Geriatr Soc. 1996;44(10):1147-1152.PubMedGoogle ScholarCrossref
29.
Sobów  T, Fendler  W, Magierski  R.  Body mass index and mild cognitive impairment-to-dementia progression in 24 months: a prospective study.  Eur J Clin Nutr. 2014;68(11):1216-1219. PubMedGoogle ScholarCrossref
30.
Tolppanen  AM, Ngandu  T, Kåreholt  I,  et al.  Midlife and late-life body mass index and late-life dementia: results from a prospective population-based cohort.  J Alzheimers Dis. 2014;38(1):201-209.PubMedGoogle Scholar
31.
Knopman  DS, Edland  SD, Cha  RH, Petersen  RC, Rocca  WA.  Incident dementia in women is preceded by weight loss by at least a decade.  Neurology. 2007;69(8):739-746.PubMedGoogle ScholarCrossref
32.
Albanese  E, Davis  B, Jonsson  PV,  et al.  Overweight and obesity in midlife and brain structure and dementia 26 years later: the AGES-Reykjavik Study.  Am J Epidemiol. 2015;181(9):672-679.PubMedGoogle ScholarCrossref
33.
Geda  YE, Roberts  RO, Mielke  MM,  et al.  Baseline neuropsychiatric symptoms and the risk of incident mild cognitive impairment: a population-based study.  Am J Psychiatry. 2014;171(5):572-581.PubMedGoogle ScholarCrossref
34.
Brodaty  H, Heffernan  M, Draper  B,  et al.  Neuropsychiatric symptoms in older people with and without cognitive impairment.  J Alzheimers Dis. 2012;31(2):411-420.PubMedGoogle Scholar
35.
Rosenberg  PB, Mielke  MM, Appleby  BS, Oh  ES, Geda  YE, Lyketsos  CG.  The association of neuropsychiatric symptoms in MCI with incident dementia and Alzheimer disease.  Am J Geriatr Psychiatry. 2013;21(7):685-695.PubMedGoogle ScholarCrossref
36.
Albers  MW, Gilmore  GC, Kaye  J,  et al.  At the interface of sensory and motor dysfunctions and Alzheimer’s disease.  Alzheimers Dement. 2015;11(1):70-98.PubMedGoogle ScholarCrossref
37.
Doty  RL.  Olfaction in Parkinson’s disease and related disorders.  Neurobiol Dis. 2012;46(3):527-552.PubMedGoogle ScholarCrossref
38.
Kovács  T, Cairns  NJ, Lantos  PL.  Olfactory centres in Alzheimer’s disease: olfactory bulb is involved in early Braak’s stages.  Neuroreport. 2001;12(2):285-288.PubMedGoogle ScholarCrossref
39.
Devanand  DP, Lee  S, Manly  J,  et al.  Olfactory deficits predict cognitive decline and Alzheimer dementia in an urban community.  Neurology. 2015;84(2):182-189.PubMedGoogle ScholarCrossref
40.
Wilson  RS, Schneider  JA, Arnold  SE, Tang  Y, Boyle  PA, Bennett  DA.  Olfactory identification and incidence of mild cognitive impairment in older age.  Arch Gen Psychiatry. 2007;64(7):802-808.PubMedGoogle ScholarCrossref
41.
Nguyen  JC, Killcross  AS, Jenkins  TA.  Obesity and cognitive decline: role of inflammation and vascular changes.  Front Neurosci. 2014;8:375.PubMedGoogle ScholarCrossref
42.
Gorelick  PB, Scuteri  A, Black  SE,  et al; American Heart Association Stroke Council; Council on Epidemiology and Prevention; Council on Cardiovascular Nursing; Council on Cardiovascular Radiology and Intervention; Council on Cardiovascular Surgery and Anesthesia.  Vascular contributions to cognitive impairment and dementia: a statement for healthcare professionals from the American Heart Association/American Stroke Association.  Stroke. 2011;42(9):2672-2713.PubMedGoogle ScholarCrossref
43.
Taki  Y, Kinomura  S, Sato  K,  et al.  Relationship between body mass index and gray matter volume in 1,428 healthy individuals.  Obesity (Silver Spring). 2008;16(1):119-124.PubMedGoogle ScholarCrossref
44.
Lee  YH, Martin  JM, Maple  RL, Tharp  WG, Pratley  RE.  Plasma amyloid-beta peptide levels correlate with adipocyte amyloid precursor protein gene expression in obese individuals.  Neuroendocrinology. 2009;90(4):383-390.PubMedGoogle ScholarCrossref
45.
Koga  S, Kojima  A, Kuwabara  S, Yoshiyama  Y.  Immunohistochemical analysis of tau phosphorylation and astroglial activation with enhanced leptin receptor expression in diet-induced obesity mouse hippocampus.  Neurosci Lett. 2014;571:11-16.PubMedGoogle ScholarCrossref
46.
Banks  WA, Burney  BO, Robinson  SM.  Effects of triglycerides, obesity, and starvation on ghrelin transport across the blood-brain barrier.  Peptides. 2008;29(11):2061-2065.PubMedGoogle ScholarCrossref
47.
Sumarac-Dumanovic  M, Stevanovic  D, Ljubic  A,  et al.  Increased activity of interleukin-23/interleukin-17 proinflammatory axis in obese women.  Int J Obes (Lond). 2009;33(1):151-156.PubMedGoogle ScholarCrossref
48.
Gemma  C, Bickford  PC.  Interleukin-1beta and caspase-1: players in the regulation of age-related cognitive dysfunction.  Rev Neurosci. 2007;18(2):137-148.PubMedGoogle ScholarCrossref
49.
André  C, Dinel  AL, Ferreira  G, Layé  S, Castanon  N.  Diet-induced obesity progressively alters cognition, anxiety-like behavior and lipopolysaccharide-induced depressive-like behavior: focus on brain indoleamine 2,3-dioxygenase activation.  Brain Behav Immun. 2014;41:10-21.PubMedGoogle ScholarCrossref
50.
Erion  JR, Wosiski-Kuhn  M, Dey  A,  et al.  Obesity elicits interleukin 1-mediated deficits in hippocampal synaptic plasticity.  J Neurosci. 2014;34(7):2618-2631.PubMedGoogle ScholarCrossref
51.
Cano  V, Valladolid-Acebes  I, Hernández-Nuño  F,  et al.  Morphological changes in glial fibrillary acidic protein immunopositive astrocytes in the hippocampus of dietary-induced obese mice [Published online June 6, 2014].  Neuroreport. doi:10.1097/WNR.0000000000000180.PubMedGoogle Scholar
×