Transcript Gender differences in the norms of the Minimental State

Gender differences in the norms
of the Minimental State
Examination in Arabic
Amin Abuful, Rivka Inzelberg, Magda
Masarwa, Aziz Mazarib, Edna Schechtman
Rosa Strugatsky & Robert P. Friedland
Hillel Yaffe Medical Center, Technion Rappaport
Faculty of Medicine, Ben Gurion University, Israel &
Case Western University School of Medicine,
Cleveland, Ohio, USA
Background
• The prevalence of Alzheimer's disease is
increasing.
• There is a need for accurate and easily
administered screening instruments.
• The Minimental State Examination
(MMSE) is widely used.
• It has been validated in North America,
Europe and Asia , but not in Arabic
populations.
Aim
• To present gender differences in the
normative data of an Arabic translation of
the MMSE.
Methods
• The present work is part of our
epidemiological study of brain aging
related disorders carried out in Wadi Ara
villages in northern Israel.
Methods – Study population
• Wadi Ara houses a population of 81,400 Arab
inhabitants (51% men) in Northern Israel.
• Most of the population is younger than 45 years.
• Only 9,831 residents (12 %) are older than 45
years.
• The population >=65 years counts 2067
residents (2.5 %) on prevalence day (January
1st 2003), according to the Israel Central
Statistics Bureau.
Methods – Study population
• We systematically approached
consecutive houses in the villages.
• We examined all residents who agreed to
participate in the study.
• Elderly subjects in Wadi Ara live with their
family. None were in an institution.
Study team
• All participants were examined in their
homes by a fluently Arabic speaking native
team
• The team comprised an academic nurse,
a social worker and neurologists.
Methods – Study procedures
• Participants systematically evaluated for:
• Cardiovascular risk factors
• Questionnaires concerning activities of
daily living
• Life style
• Cognitive function
Methods – Study procedures
Clinical assessment
• First visit: All subjects were approached by nurse
• Interview: medical and family history, medications
• History of changes in behavior, cognitive abilities, ADL,
occupational and recreational activities
• Second visit: Neurologist performed complete
neurological examination.
• Consensus conference: Four neurologists reviewed all
subjects’ files.
Definition of cognitively normal
• No complaints about memory impairment
• Or any other cognitive domain
• No evidence of such disturbance
according to surrogates
• No evidence of impairment in ADL
stemming from cognitive disturbances
Methods – Cognitive evaluation
• An Arabic translation of the MMSE
(maximum score=30)
• Brookdale Cognitive Screening Test
(BCST, maximum score=24)
• The BCST test developed in the Brookdale
Institute of Gerontology, Jerusalem
Methods – Cognitive evaluation
BCST
• Orientation in time
and place
• Memory
• Praxis
• Naming
• Stimulus selection
•
•
•
•
•
Abstraction
Calculation
Attention
Left-right orientation
Visuo-spatial
orientation
– No items related to
reading and writing
Methods – Occupation
• Questionnaires about occupation (present
and past)
• Categorized for statistical analysis
• 1=never worked outside the house, or
housewife
• 2=handy work (trader in shop, cook,
carpenter, builder, etc),
• 3=agriculture
• 4=office.
Methods – Statistical analysis
•
•
•
•
Education was stratified:
1=0-4 years, 2=5-8 years, 3=>8 years
Comparison of proportions by chi-square
The comparison of means of MMSE and
BCST by gender and levels of education
by Analysis of Covariance, using age as a
covariate
Results
• 442 subjects approached
• 438 agreed (refusal rate 0.9 %)
• Four were excluded: severe systemic nonneurological disease
Cognitively normal
• The study population consisted of 266
subjects (158 males)
• Mean age (SD) was 72.4 (5.5) years
• Range 65 -91 years
• Mean age:
Males: 72.8 (5.6); females: 71.6 (5.4)
years (p>0.1)
Results
• Mean MMSE entire population = 25 (4)
• Mean BCST entire population = 19 (4)
points
• Highly significant correlation between
MMSE and Brookdale scores in the entire
group (r=0.852, p<0.0001)
• Males r=0.8223, Females r=0.854,
p<0.0001 both
Education levels
90
80
70
60
50
%
within
males
females
40
gender 30
20
10
0
0-4 years
5-8 years
> 8 years
p<0.001
Education years
MMSE by gender & education
M
M
S
E
30
29
28
27
26
25
24
23
22
21
20
19
18
17
16
15
males
females
p<0.05
p<0.0001
0-4 yrs
5-8 yrs
Education years
>8 yrs
BCST by gender & education
B
C
S
T
24
23
22
21
20
19
18
17
16
15
14
13
12
males
females
p<0.05
p<0.0001
0-4 yrs
5-8 yrs
Education years
>8 yrs
Occupation categories
60
50
%
40
within
gender 30
20
10
0
males
females
females
males
no
handy
agricult.
Occupation category
office
p<0.05
Occupation and education within
genders
• For males MMSE and BCST scores were significantly
higher for higher education (p<0.05). Occupation
category had no significant effect.
• For females MMSE and BCST scores were significantly
higher for higher education (p<0.0001). Occupation
category had no significant effect.
• The main effect was due to education and not
occupation.
Conclusions
• We described normative data for an
Arabic translation of the MMSE by gender.
Conclusions
• Mean values of the MMSE scores were
comparable to population-based norms
described in English in the USA at all
correspondent education levels (Crum et
al. JAMA, 1993).
Conclusions
• We found a divergent effect of gender in
different education levels.
• Females with low-schooling (<=4 years)
perform significantly worse than males.
• However, females with higher schooling
(>=5 years) perform significantly better
than males.
Discussion
• We verified whether working in the
community might contribute to the
performance.
• We found that scores are influenced by
education and not by occupation within
genders, when these two factors are
analyzed.
• Influence of social exposure and life-style ?
Brookdale Cognitive Screening
• We found a highly significant correlation
between MMSE and BCST scores in both
genders.
• Despite the fact that BCST does not
include reading or writing items, it is still
influenced by education as much as the
MMSE.
Conclusions
• Different cut-off scores should be used in
different education strata.
• Scores of females at low education levels
should be considered cautiously to prevent
false positive interpretation.
• Information on education is mandatory.
• Still, MMSE may serve for measuring
change over time.
Thank you
•
Rob P. Friedland, Case Western
Reserve University- Lab of
Neurogenetics , USA
•
Lindsay Farrer, Boston UniversityGenetics Program, USA
•
Edna Schechtman, Ben Gurion
University- Dept. Industrial Engineering,
Beer Sheva, Israel
•
Hillel Yaffe Medical Center, Hadera,
Israel
Rivka Inzelberg
Aziz Mazarib
Magda Masarwa
Saif Abo-Mouch
Rosa Strugatsky
Gital Gamliel
•
•
•
•
•
•
Occupation categories by education
levels
80
60
%
within
gender
males
females
40
20
females
males
0
no
handy
agricult.
office
Education 0-4 years
Education 5-8 years
50
40
% within
gender
males
females
30
20
females
males
10
0
no
handy
agricult.
office
Occupation categories
education 0-4 years
80
60
%
within
gender
males
females
40
20
females
males
0
no
handy
agricult.
office
Occupation category
p<0.05
Occupation categories
education 5-8 years
50
40
%
males
females
30
within
20
gender
10
females
males
0
no
handy
agricult.
office
Occupation category
p<0.05