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DOI 10.1212/WNL.0b013e3182190d09
2011;76;1568Neurology
W.L. Xu, A.R. Atti, M. Gatz, et al.
population-based twin study
Midlife overweight and obesity increase late-life dementia risk : A
June 8, 2011This information is current as of
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rights reserved. Print ISSN: 0028-3878. Online ISSN: 1526-632X. Allsince 1951, it is now a weekly with 48 issues per year. Copyright © 2011 by AAN Enterprises, Inc.
® is the official journal of the American Academy of Neurology. Published continuouslyNeurology
by GUILLERMO GARCIA-RAMOS on June 8, 2011www.neurology.orgDownloaded from
Midlife overweight and obesity increase
late-life dementia risk
A population-based twin study
W.L. Xu, MD, PhD
A.R. Atti, MD, PhD
M. Gatz, PhD
N.L. Pedersen, PhD
B. Johansson, PhD
L. Fratiglioni, MD, PhD
ABSTRACT
Objective: The relation of overweight to dementia is controversial. We aimed to examine the asso-
ciation of midlife overweight and obesity with dementia, Alzheimer disease (AD), and vascular
dementia (VaD) in late life, and to verify the hypothesis that genetic and early-life environmental
factors contribute to the observed association.
Methods: From the Swedish Twin Registry, 8,534 twin individuals aged ⱖ65 (mean age 74.4)
were assessed to detect dementia cases (DSM-IV criteria). Height and weight at midlife (mean
age 43.4) were available in the Registry. Data were analyzed as follows: 1) unmatched case-
control analysis for all twins using generalized estimating equation (GEE) models and 2) cotwin
matched case-control approach for dementia-discordant twin pairs by conditional logistic regres-
sion taking into account lifespan vascular disorders and diabetes.
Results: Among all participants, dementia was diagnosed in 350 subjects, and 114 persons had
questionable dementia. Overweight (body mass index [BMI] ⬎25–30) and obesity (BMI ⬎30) at
midlife were present in 2,541 (29.8%) individuals. In fully adjusted GEE models, compared with
normal BMI (20–25), overweight and obesity at midlife were related to dementia with odds ratios
(ORs) (95% CIs) of 1.71 (1.30–2.25) and 3.88 (2.12–7.11), respectively. Conditional logistic
regression analysis in 137 dementia-discordant twin pairs led to an attenuated midlife BMI-
dementia association. The difference in ORs from the GEE and the matched case-control analysis
was statistically significant (p⫽0.019).
Conclusions: Both overweight and obesity at midlife independently increase the risk of dementia,
AD, and VaD. Genetic and early-life environmental factors may contribute to the midlife high
adiposity–dementia association. Neurology
®
2011;76:1568–1574
GLOSSARY
AD ⫽Alzheimer disease; BMI ⫽body mass index; CERAD ⫽Consortium to Establish a Registry for Alzheimer’s Disease; CI ⫽
confidence interval; DSM-IV ⫽Diagnostic and Statistical Manual of Mental Disorders, 4th edition; DZ ⫽dizygotic; GEE ⫽
generalized estimating equation; ICD ⫽International Classification of Diseases; IDR ⫽Inpatient Discharge Registry;
MMSE ⫽Mini-Mental State Examination; MZ ⫽monozygotic; OR ⫽odds ratio; VaD ⫽vascular dementia.
Body mass index (BMI) provides an indirect measure of adiposity, and is strongly correlated with
total body fat tissue.
1
Adiposity may influence or be influenced by brain structures and functions,
which may be involved in dementing processes.
2
In the last decade, many population-based longi-
tudinal studies have evaluated the relationship between adiposity and dementia. Several reports have
shown that midlife obesity increases the risk of dementia in late life
3-10
; however, the effect of midlife
overweight on dementia is controversial.
3,5,7,9
Currently, the prevalence of overweight and obesity is
over 50% among adults in the United States and Europe.
11
Although adiposity may be linked to dementia through several biologically plausible path-
ways,
12
our understanding of the mechanisms for such an association is still limited. Both
From the Aging Research Center (W.L.X., A.R.A., L.F.), Department of Neurobiology, Care Sciences and Society, Karolinska Institutet and
Stockholm University, Stockholm, Sweden; Department of Epidemiology (W.L.X.), Tianjin Medical University, Tianjin, China; Psychiatry Institute
Paolo Ottonello (A.R.A.), Bologna University, Bologna, Italy; Department of Psychology (M.G., N.L.P.), University of Southern California, Los
Angeles; Department of Medical Epidemiology and Biostatistics (M.G., N.L.P.), Karolinska Institutet, Stockholm; Department of Psychology (B.J.),
University of Gothenburg, Gothenburg; and Stockholm Gerontology Research Center (L.F.), Stockholm, Sweden.
Study funding: Funded by The National Institute on Aging (R01-AG08724), the Swedish Research Councils (FAS-09-0632), and the Swedish Brain
Power. Also supported in part by funds from the Gamla Tja¨narinnor, the Bertil Stohnes Foundation, the Demensfonden, the Loo and Hans
Ostermans Foundation, and the Foundation for Geriatric Diseases at Karolinska Institutet.
Disclosure: Author disclosures are provided at the end of the article.
Address correspondence and
reprint requests to Dr. Weili Xu,
Aging Research Center,
Karolinska Institutet, Ga¨vlegatan
16, S-113 30 Stockholm, Sweden
weili.xu@ki.se
1568 Copyright © 2011 by AAN Enterprises, Inc.
by GUILLERMO GARCIA-RAMOS on June 8, 2011www.neurology.orgDownloaded from
obesity and dementia are complex genetic and
lifestyle-related disorders. Evidence has shown
that early-life environments (such as child-
hood socioeconomic situation) may affect the
development of obesity and dementia.
13,14
The life course development of the adiposity-
dementia association has been suggested,
15
but the contribution of genetics and early life
environments to the relationship has not been
investigated. In the present study, we sought
to 1) verify the long-term effect of midlife
overweight and obesity measured by BMI on
the risk of dementia, Alzheimer disease (AD),
and vascular dementia (VaD) taking into ac-
count diabetes and lifespan vascular disorders
using unmatched case-control analysis; and 2)
explore whether genetic and early-life envi-
ronments could explain the observed associa-
tion between midlife adiposity and dementia
by cotwin matched case-control approach us-
ing data from the Swedish Twin Registry.
METHODS Participants and data collection. Partici-
pants were drawn from the nationwide Swedish Twin Registry.16
In 1998–2001, all living twins in the registry who were born in
1935 and earlier (aged ⱖ65 years) were invited to participate in a
telephone interview screening for most common diseases, which
included a brief cognitive assessment.17 In brief, a total of 20,206
individuals in the registry were eligible for screening. Of them,
13,693 twins completed the cognitive screening module, result-
ing in a participation rate of 67.8%. Information concerning
demographic factors, education, current height and weight,
health status and behavior, current and past diseases, and use of
medications was also obtained during the interview. In addition,
self-report information on height and weight at midlife (mean
age 43.4) was collected for all like-sexed twin pairs by the Regis-
try in 1967, i.e., on average 30 years preceding the screening
phase. Out of the 13,693 twins, 8,534 had data on height and
weight at midlife available for the current analysis (figure 1).
Screening phase. The screening test included the TELE ques-
tionnaire for participants18,19 and the Blessed Dementia Rating
Scale for informants when participants performed poorly on the
TELE.19,20 The TELE and BDRS were combined into an ordinal
scale with scores ranging from 0 (cognitively intact) to 3 (cogni-
tive dysfunction). Participants who screened positive (i.e., scored
3) and their cotwins were invited to a clinical examination (n ⫽
1,450).
Clinical phase and diagnosis. The full clinical workup
consisted of a visit by an assessment team composed of a nurse
and a physician using a protocol that generally followed the
Consortium to Establish a Registry for Alzheimer’s Disease
(CERAD). The protocol included physical and neurologic
examination, a review of medical history, informant interview,
and a neuropsychological assessment. The neuropsychological bat-
tery included the Mini-Mental State Examination (MMSE),
CERAD word list immediate and delayed recall, verbal flu-
ency, block design, figure copying, judgment, information,
symbol-digit, and prospective memory, as well as the Memory
in Reality test.
The assessment team made an initial diagnosis of dementia
and dementia subtypes following the DSM-IV criteria.21 All pro-
tocols were reviewed by a diagnostic board, consisting of a neu-
rologist and a neuropsychologist, who were blind to the
assessment team’s preliminary diagnosis, and verified the prelim-
inary diagnosis. More details of the clinical examination and di-
agnostic procedure have been reported previously.17 The cases
completely fulfilling the DSM-IV criteria were diagnosed as “de-
mentia,” in contrast with a category of “questionable dementia,”
which was used for individuals who did not fulfill one of the first
3DSM-IV diagnostic criteria, but did exhibit cognitive impair-
ment or functional disability. Participants were first classified as
no dementia, questionable, or dementia. A differential diagnosis
Figure 1 Flow chart of the study population
BMI ⫽body mass index.
Neurology 76 May 3, 2011 1569
by GUILLERMO GARCIA-RAMOS on June 8, 2011www.neurology.orgDownloaded from
was then given for dementia subtype according to the National
Institute of Neurological and Communicative Disorders and
Stroke–Alzheimer’s Disease and Related Disorders Association
criteria for AD22 and the National Institute of Neurological Dis-
orders and Stroke–Association Internationale pour la Recherche
et l’Enseignement en Neurosciences criteria for VaD.23 Through
the clinical workup, dementia was diagnosed in 350 subjects
including 232 AD and 74 VaD cases, and 114 had questionable
dementia. Among all participants, 8,070 did not have dementia.
Data on history of diabetes and vascular diseases obtained at
the screening interview were integrated with data from the Inpa-
tient Discharge Registry (IDR), which encompasses all hospital
discharges in Sweden since 1969. All discharge diagnoses for
participants who were hospitalized during 1969–2001 were ob-
tained. Each record in the IDR included up to 8 discharge diag-
noses according to the International Classification of Diseases,
8th revision (ICD-8) between 1969 and 1986 and 9th revision
(ICD-9) since 1987. Medical conditions derived from the inpa-
tient register database included diabetes (ICD-8, 9 code 250),
hypertension (ICD-8 codes 400–404; ICD-9 codes 401–405),
ischemic heart disease (ICD-8, 9 codes 410–414), cardiac dys-
rhythmia, heart failure or other myocardial insufficiency
(ICD-8, 9 codes 427 and 428), and stroke (ICD-8, 9 codes
430–438). Diabetes and vascular diseases were deemed present
if reported by self or informant, or if recorded in the inpatient
registry. Survival status from midlife to the screening phase was
obtained from the Cause of Death Register.
Validation of self-reported height and weight. A previ-
ous study indicated that the correlations between self-reported
and measured height and weight were 0.97 for height and 0.95
for weight.24 The mean differences (⫾SD) between self-reported
and measured values were 1.2 ⫾2.4 cm for height and 0.8 ⫾4.0
kg for weight. In the present study, the correlation between self-
reported height and weight at the screening phase and measured
height and weight at the clinical phase were 0.91 ( p⬍0.001)
and 0.93 ( p⬍0.001, n ⫽864), respectively. Pearson correla-
tion coefficients were 0.87 ( p⬍0.001, n ⫽931) for the corre-
lation between the height at midlife recorded in the twin registry
and measured height at the clinical examination.
Standard protocol approvals. Informed consents were re-
quired from all participants during the telephone interview and
again in the clinical phase. The data collection procedures were
reviewed and approved by the Swedish Data Inspection Board,
Stockholm Sweden, the Regional Ethics Committee at Karolin-
ska Institutet, Stockholm, and the Institutional Review Board of
the University of Southern California.
Statistical analysis. BMI was calculated as self-reported
weight in kilograms divided by self-reported height in meters
squared, and categorized into 4 groups: underweight (⬍20),
normal weight (20–25), overweight (⬎25–30), and obese
(⬎30).25 Midlife BMI was used as both continuous and categor-
ical variables in the analysis.
The characteristics of participants in different groups were
compared using
2
tests for categorical variables, one-way analy-
sis of variance for continuous variables. Multinomial logistic re-
gression was first performed to estimate the odds ratios (OR) and
95% confidence intervals (CI) of dementia (350 dementia cases
vs 8,070 controls) and questionable dementia (114 questionable
dementia cases vs 8,070 controls) separately in relation to BMI.
Further, 2 analytical strategies were applied to address the fol-
lowing aims: 1) unmatched case-control analyses was performed
in all subjects (464 dementia and questionable dementia cases vs
8,070 controls) using generalized estimating equations (GEE)
models, which are conceptually equivalent to logistic regression
for the analysis of classic case-control design, but control for the
clustering of twins within a pair; and 2) cotwin matched case-
control analyses was carried out using conditional logistic regres-
sion models among the 137 dementia-discordant twin pairs after
exclusion of 3,476 single twins, and 2,357 both no dementia and
35 both dementia twin pairs. The latter strategy allows matching
for unmeasured familial factors, which could reflect genetic
background or early life environment. Cases and controls are
comparable with respect to genetic and early life environmental
history (such as prenatal and postnatal nutritional status, and
childhood socioeconomic status). If the association found in
GEE analyses becomes attenuated in cotwin matched case-
control analyses, genetic factors or familial environments or both
are likely to contribute to the association. In contrast, if a signif-
icant association remains when using cotwin matched pairs, the
influences of genetic or early environmental factors on the asso-
ciation are likely to be marginal.
Logistic regression was used to test the difference in ORs
from GEE model and conditional logistic regression by examin-
ing the difference of overweight and obesity at midlife among
unmatched vs cotwin controls. Age, sex, education, zygosity, di-
abetes, and vascular diseases were considered as confounders in
all models. The statistical analyses were performed using SAS
statistical software version 9.1 and Stata SE 10.
RESULTS Population characteristics. Among the
8,534 participants, 350 (4.1%) were dementia cases
including 232 AD and 74 VaD, and 114 (1.3%)
were diagnosed with questionable dementia. Among
those included in the analysis, 6.0% of the females
and 4.6% of the males had dementia or questionable
dementia (
2
⫽7.82, p⫽0.005).
Compared to participants without dementia,
twins with dementia or questionable dementia were
older, had a lower level of education and current
BMI, had higher midlife BMI, and were more likely
to have diabetes, stroke, and heart disease. A total of
2,541 twins (29.8%) were overweight or obese at
midlife (table 1).
BMI in relation to questionable dementia and demen-
tia. In the multinomial logistic analysis of the entire
sample, midlife BMI as a continuous variable was
significantly associated with an increased risk of de-
mentia (OR 1.08, 95% CI 1.03–1.14) as well as
questionable dementia (OR 1.07, 95% CI 1.04–
1.11) after adjustment for potential confounders.
Figure 2 shows the multi-adjusted ORs of dementia
and questionable dementia related to BMI as cate-
gorical variable. As the midlife BMI-related ORs for
dementia and questionable dementia were similar,
these 2 categories were combined as an outcome of
dementia in subsequent analyses.
Unmatched analysis. In GEE models, higher midlife
BMI was associated with greater risk of all dementia,
AD, and VaD using BMI as a continuous variable.
1570 Neurology 76 May 3, 2011 by GUILLERMO GARCIA-RAMOS on June 8, 2011www.neurology.orgDownloaded from
When BMI was analyzed as a categorical variable,
compared with normal weight, overweight was asso-
ciated with an increased risk of dementia and AD,
while obesity increased the risk of dementia, AD, and
VaD controlling for age, sex, and education. Further,
the association was not attenuated by additional ad-
justing for diabetes and vascular diseases (table 2).
However, the statistical power was limited for the
BMI-VaD association due to the few VaD cases.
Matched analysis. Among the 137 dementia discor-
dant twin pairs, 44 were monozygotic (MZ), 90
were dizygotic (DZ), and 3 were unknown zygos-
ity. In the cotwin matched case-control analyses,
the association of midlife overweight and obesity
(BMI ⬎25) with dementia was attenuated, and no
longer significant (table 3).
The difference between the ORs of dementia re-
lated to BMI ⬎25 (overweight and obesity) from
GEE model based on the entire sample (age- and
sex-adjusted OR 1.56 [95% CI 1.28–1.91]) and
from conditional logistic model based on dementia-
discordant pairs (sex-adjusted OR 0.88 [95% CI
0.64–1.21]) was tested by comparing high BMI
(⬎25) among the unmatched and matched controls.
The difference was statistically significant (OR 1.62
[95% CI 1.12–2.66 p⫽0.019]), indicating that ge-
netic and family environmental factors may contrib-
ute to the high adiposity-dementia association.
Supplementary analyses. The dropout rate in the
screening phase of this study was 32.2% (6,531/
20,206) mainly due to refusal (74.8%) and to
death (4.6%). Multivariable GEE model showed
that being a dropout was associated with ORs of
1.05 (95% CI 1.02–1.06) for old age, 1.06 (95%
CI 0.86–1.39) for female gender, 0.77 (95% CI
0.72–0.81) for education (per 1-year increase),
1.05 (95% CI 0.81–1.35) for stroke, 0.95 (95%
CI 0.72–1.27) for diabetes, 0.79 (95% CI 0.63–
1.03) for heart disease, and 0.98 (95% CI 0.74–
1.29) for hypertension.
Figure 2 Odds ratio (OR) and 95% confidence interval (CI) of dementia and questionable dementia related
to midlife body mass index (BMI), after adjustment for age, sex, education, zygosity, diabetes,
stroke, hypertension, and heart disease (results from Multinomial Logistic Regression)
Table 1 Characteristics of the study participants (n ⴝ8,435) by
dementia diagnosis
a
Characteristics
No dementia
(n ⴝ8,070)
Questionable
dementia
(n ⴝ114)
Dementia
(n ⴝ350) pValue
Age, y, mean (SD) 74.0 (6.7) 80.5 (7.1) 82.3 (6.5) ⬍0.001
Female sex 4,669 (57.9) 58 (50.9) 241 (68.9) ⬍0.001
Education, y, mean (SD)b12.5 (62.3) 8.2 (2.9) 7.3 (2.5) ⬍0.001
Zygotic status
Monozygotic 2,892 (35.8) 44 (38.6) 133 (38.0)
Dizygotic 5,041 (62.5) 70 (61.4) 204 (58.3)
Unknown 137 (1.7) 0 13 (3.7) ⬍0.001
Midlife BMI, mean (SD) 23.7 (2.9) 24.9 (4.9) 25.0 (3.1) ⬍0.001
Underweight (<20) 610 (7.5) 6 (5.3) 11 (3.1)
Normal (20–25) 5,126 (63.5) 61 (53.5) 179 (51.1)
Overweight (25–30) 2,120 (26.3) 41 (36.0) 136 (38.9)
Obese (>30) 214 (2.7) 6 (5.3) 24 (6.9) ⬍0.001
Current BMI, mean (SD) 25.1 (3.7) 24.4 (3.6) 23.9 (4.7) ⬍0.001
Diabetes 805 (10.0) 22 (19.3) 84 (24.0) ⬍0.001
Stroke 621 (7.7) 35 (30.7) 103 (29.4) ⬍0.001
Heart disease 1,111 (13.8) 48 (42.1) 245 (70.0) ⬍0.001
Hypertension 2,727 (33.8) 42 (36.8) 126 (36.0) ⬎0.05
Abbreviation: BMI ⫽body mass index.
a
Values are n (%) of participants unless indicated otherwise.
b
A total of 32 participants had missing value for education.
Neurology 76 May 3, 2011 1571
by GUILLERMO GARCIA-RAMOS on June 8, 2011www.neurology.orgDownloaded from
Further, we repeated the analysis of the BMI–
dementia association leaving out the twins who
scored 3 at cognitive screening but were diagnosed
as no dementia or not referred to clinical workup
(n ⫽655). This produced results similar to those
from the initial analysis. Finally, we examined the
effect of BMI ⬎25 on mortality from midlife to
late life (the screening phase). Among all like-
sexed twins born before 1936, 4,825 died before
the screening phase. In the GEE model, BMI ⬎25
(overweight and obesity) at midlife was related to
elevated risk of death with multiadjusted OR of
1.30 (95% CI 1.19–1.42).
DISCUSSION In this nationwide Swedish twin
study, overweight and obesity at midlife increase the
risk of all dementia, AD, and VaD, independently of
lifespan diabetes and vascular diseases. Findings from
the cotwin matched analyses suggest that familial fac-
tors (genetic factors and early life environments) con-
tribute to the association between midlife high
adiposity and dementia in late life.
A growing body of evidence suggests that a high
level of adiposity is associated with cognitive decline
and dementia
10,26,27
; however, the relation between
BMI and dementia among people aged over 65 is
controversial.
28-30
Several population-based studies
have reported an effect of obesity at middle age on
dementia risk.
3,4,7,9
Only one study reported an in-
creased dementia risk in people with overweight.
5
Despite the fact that high adiposity is associated with
dementia, there remains a debate whether this con-
cerns only AD or also VaD. Some prospective studies
did find an association between obesity and increased
risk of VaD,
7,29,31
while others did not.
9,32-34
In this
Swedish twin cohort, we found that having dementia
or AD was associated with more than a 70% higher
odds of being overweight at midlife, while the odds
of being obese at midlife were higher for those with
AD as well as those with VaD. Although the effect of
midlife overweight on dementia is not as substantial
as that of obesity, its impact on public health and
clinical practice is significant due to the fact that
there are 1.6 billion overweight adults worldwide.
35
Several potential biological mechanisms may ex-
plain the association between adiposity and demen-
tia. First, higher BMI is associated with diabetes and
vascular diseases, which are related to dementia
risk.
12
Nonetheless, in our study, the association be-
tween midlife high BMI and dementia remained sig-
nificant after controlling for lifespan vascular
diseases, suggesting that nonvascular pathways might
play an important role in the adiposity-dementia as-
sociation. Second, higher adiposity at midlife may
reflect a lifetime exposure to an altered metabolic and
inflammatory state. Adiposity is one component of
the metabolic syndrome which has been related to
cognitive decline.
36
Further, adipose tissue is the larg-
est endocrine organ and secretes inflammatory cyto-
kines and growth hormones; some of them (such as
Table 2 Adjusted odds ratio (OR) and 95% confidence interval (CI) of dementia, Alzheimer disease, and vascular dementia related to
midlife BMI (results from generalized estimating equation models)
Midlife
BMI No. of twins
All dementia Alzheimer disease Vascular dementia
No. OR (95% CI)aOR (95% CI)bNo. OR (95% CI)aOR (95% CI)bNo. OR (95% CI)aOR (95% CI)b
Continuous 8,534 464 1.09 (1.06–1.12) 1.06 (1.03–1.10) 232 1.09 (1.04–1.13) 1.06 (1.01–1.10) 74 1.14 (1.08–1.21) 1.11 (1.04–1.19)
Categorical
<20 627 17 0.74 (0.44–1.25) 0.79 (0.45–1.38) 8 0.89 (0.64–1.23) 0.66 (0.31–1.41) 0 — —
20–25 5,366 240 1 (Reference) 1 (Reference) 120 1 (Reference) 1 (Reference) 36 1 (Reference) 1 (Reference)
>25 2,541 207 1.50 (1.22–1.84) 1.80 (1.37–2.35) 104 1.52 (1.15–2.02) 1.98 (1.36–2.88) 38 1.62 (1.01–2.59) 1.35 (0.81–2.24)
25–30 2,297 177 1.37 (1.11–1.70) 1.71 (1.30–2.25) 90 1.41 (1.05–1.89) 1.91 (1.30–2.80) 31 1.39 (0.85–2.29) 1.17 (0.69–2.00)
>30 244 30 3.01 (1.95–4.64) 3.88 (2.12–7.11) 14 2.87 (1.57–5.26) 3.43 (1.49–7.90) 7 4.38 (1.89–10.14) 3.50 (1.36–8.99)
Abbreviations: BMI ⫽body mass index; CI ⫽confidence interval; OR ⫽odds ratio.
a
Adjusted for age, sex, and education.
b
Adjusted for age, sex, education, diabetes, hypertension, stroke, and heart disease.
Table 3 Midlife BMI in relation to dementia in dementia-discordant twin pairs
(n ⴝ137) (results from conditional logistic regression models)
Midlife BMI No. of twins Pairs
All dementia (n ⴝ137)
OR (95% CI)aOR (95% CI)b
Continuous 274 137 1.07 (0.97–1.21) 1.09 (0.95–1.26)
Categorical
<20 15 8 1.19 (0.40–3.56) 1.07 (0.23–4.96)
20–25 154 73 1 (Reference) 1 (Reference)
>25 105 56 1.26 (0.77–2.67) 1.24 (0.71–2.87)
25–30 92 47 1.14 (0.71–2.32) 1.10 (0.68–3.30)
>30 13 9 2.24 (0.77–6.72) 1.62 (0.65–6.94)
Abbreviations: BMI ⫽body mass index; CI ⫽confidence interval; OR ⫽odds ratio.
a
Adjusted for sex and education.
b
Adjusted for sex, education, diabetes, stroke, heart disease, and hypertension.
1572 Neurology 76 May 3, 2011 by GUILLERMO GARCIA-RAMOS on June 8, 2011www.neurology.orgDownloaded from
leptin, interleukin-6, and C-reactive protein) may af-
fect cognitive functioning. Leptin is involved in de-
position of amyloid

-42, and plays a role in
neurodegenerative process.
37
Twin studies involving a life-course approach
may help to identify genetic and environmental in-
fluences on the development of chronic diseases, as
twins provide naturally matched pairs, in which con-
founding effects of a large number of potentially
causal factors (e.g., genetics and childhood environ-
ments) may be removed when comparisons are made
within twin pairs. In cotwin control analyses, the as-
sociation between higher midlife BMI and dementia
was significantly attenuated, and thus may be attrib-
uted in part to genetic and early environmental fac-
tors such as childhood socioeconomic situation.
However, twins may also experience similar expo-
sures even at midlife and late life. Studies have re-
ported that early life exposure to an imbalanced
nutrition and disadvantaged economic status are re-
lated to a greater risk of obesity in adult life
38
and
dementia in late life.
39
Our findings suggest that
early-life environmental and genetic factors contrib-
ute to the link between adiposity and dementia.
Some limitations of the study should be men-
tioned. First, the use of prevalent dementia cases may
have introduced some confounding effect due to dif-
ferential survival among cases and controls. In addi-
tion, midlife obesity is associated with elevated
mortality in our study, which would probably lead to
an underestimation of the strength of the observed
association. Second, compared to participants, the
nonresponders were older, less educated, and more
likely to be women, but did not differ from partici-
pants in terms of vascular risk factors. As old age, low
education, and female sex are risk factors for demen-
tia, possible selection bias could arise if the preva-
lence of dementia in this cohort differs from that in
the general population. However, the prevalence of
dementia in this study was comparable with several
studies of dementia prevalence in Europe and the
United States.
17
Third, midlife height and weight re-
lied on self-reported information, which, however,
were validated by a previous study. In addition, BMI
alone might not be an ideal representation of body
composition, although BMI has been widely used in
population-based studies. Additional anthropomet-
ric measures, such as waist circumference, would be
useful. Finally, both obesity and AD are genetically
influenced disorders with substantial concordance in
twins. Thus, the matched pairs could be regarded as
overmatched, as twin pairs are similar on many as-
pects. Nevertheless, the comparison of the results
from the entire sample and from matched pairs pro-
vides information about the potential role of genetic
and familial influences in the observed association.
Finally, in the matched analysis, both MZ and DZ
twins were included due to limited number of
dementia-discordant MZ twin pairs. Hence, genetic
effects were not perfectly controlled for.
Our results provide further support for the im-
portant role of high adiposity at midlife in the devel-
opment of dementia, and highlight the need to
control body weight as early as midlife for prevention
of dementia in late life. These findings have relevant
implications for public health, as the risk of dementia
could be reduced by midlife weight loss.
40
Genetic
and early-life environmental factors may contribute
to the link of overweight and obesity to dementia,
suggesting that the high adiposity-dementia associa-
tion might develop across the lifespan.
AUTHOR CONTRIBUTIONS
Study concept and design: W.L.X., L.F., M.G., N.L.P.; analysis and inter-
pretation of the study: W.L.X., L.F., M.G., N.L.P.; drafting the manu-
script: W.L.X.; critical revision of the manuscript: L.F., M.G., N.L.P.,
A.R.A., B.J. Statistical analysis was conducted by Weili Xu.
ACKNOWLEDGMENT
The authors thank the members of the HARMONY study group for data
collection and management.
DISCLOSURE
Dr. Xu and Dr. Atti report no disclosures. Dr. Gatz received a medical
education grant from Forest Laboratories, Inc.; serves on the editorial
board of the Journal of Community Psychology; receives publishing royalties
for Handbook of the Psychology of Aging, Fifth Edition (Academic Press,
2001) and Assessing and Treating Late-life Depression: A Casebook and Re-
source Guide (Basic Books, 2002); and has received research support from
Forest Laboratories, Inc. and the NIH. Dr. Pedersen serves as an Associate
Editor of International Journal of Molecular Epidemiology and Genetics. Dr.
Johansson serves on scientific advisory boards for Aging Research Center,
Stockholm, Danish Aging Research Center, Denmark, and Kavli Re-
search Center for Ageing and Dementia, Norway; and serves on editorial
advisory boards for Aging and Mental Health,European Journal of Ageing,
Journal of Gerontopsychology and Geriatric Psychiatry, the Journal of Aging
Research, and the Journal of European Psychology Students. Dr. Fratiglioni
reports no disclosures.
Received June 22, 2010. Accepted in final form January 28, 2011.
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DOI 10.1212/WNL.0b013e3182190d09
2011;76;1568Neurology
W.L. Xu, A.R. Atti, M. Gatz, et al.
population-based twin study
Midlife overweight and obesity increase late-life dementia risk : A
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