Measuring cognitive status in older age in lower income countries

Measuring Cognitive Status in Older Age

1

SAGE Working Paper No. 3. November 2012.

Measuring cognitive status in older age in lower income countries: Results from

a pilot of the Study on global AGEing and Adult Health (SAGE).

Brionne Alvord Carroll1, Paul Kowal2, Nirmala Naidoo2, Somnath Chatterji2

1 Department of Pharmacy Practice, University of Washington, Seattle, Washington, USA. 2 Department of Measurement and Health Information Systems, World Health Organization, Geneva, Switzerland. …. Corresponding author: Dr Paul Kowal co-PI SAGE World Health Organization Department of Health Statistics and Information Systems 20 Avenue Appia CH-1211 Geneva 27 Switzerland

Acknowledgements:

We would like to thank Kathleen Brodrick, Federico Campigotto, Monica Ferreira, Barry

Gurland, Sebastiana Kalula and Nadia Minicuci for their assistance in assessing and

measuring cognition across countries and cultures. SAGE is supported by the Division

of Behavioral and Social Research of the US National Institute on Aging through

Interagency Agreements (OGHA 04034785; YA1323-08-CN-0020; Y1-AG-1005-01)

with the World Health Organization.

Word Count (text only): 2233


2

Word Count (abstract): 232

Tables & Figures: 4 tables, 2 figures (if possible); otherwise 2 figures in the Appendix 1

Appendices: 4


3

Abstract

Background. A reliable tool to measure cognition in older persons as part of

household health surveys is needed: in particular, a culture-fair instrument to distinguish

track decline in cognitive function. Additionally, the instrument should be sensitive to

different literacy levels. Currently available tools used to screen for cognitive decline

show substantial variation across different countries, suggesting limitations in accuracy

and reliability.

Methods. Implementing a battery of cognitive tests, verbal fluency, immediate and

delayed verbal recall and digit-span forward and backward, in a household health

survey pilot from the World Health Organization Study on AGEing and adult health

(SAGE) in Ghana, India, and Tanzania. The survey included self-reported health with

anchoring vignettes, plus self-reported and measured function.

Results. A total of 1446 respondents completed the study. Self-reported health differed

by age, sex and education. Verbal recall scores varied slightly by country and sex, with

women consistently scoring lower than men. Lower scores were also associated with

increasing age. The influence of sex was more pronounced in verbal fluency and less

impacted by age. Results varied on digit span by education. Higher education levels

positively impacted scores on all cognitive tests.

Conclusions. The SAGE survey proved to be a culture-sensitive screening tool in a

diverse set of countries. The instruments had face validity in all countries and were

sensitive to age, sex and education levels. This approach can be used for the

assessment of cognition in older age.


4


5

Introduction

Assessing cognition is a complex task even in a relatively homogenous population, but

measuring age-related cognitive decline across countries and in the context of an

ageing world presents significant challenges. With the expected ageing of populations

across the globe over the next 25 years, countries will be faced with larger older

populations, many experiencing cognitive changes. The established association

between increasing age and dementia rates could therefore lead to increased mental

health disease burdens. Dementia, one possible outcome from cognitive change, will

increasingly occur in low and middle income countries as a result of population aging1.

Mild cognitive impairment is often used to define those who might be at risk of

developing dementia and may be a target for early interventions; consequently,

measuring cognition to establish rates and trends would be useful2,3.

Older adults may experience changes in their abilities to name objects or with their

visual, verbal and short-term memory - some of which may be considered a normal

consequence of the ageing process.4,5,6 When these cognitive changes begin impacting

daily functioning or quality of life, the ability to accurately and reliably measure and

differentiate normal changes from disease processes becomes more important for

planning purposes.7,8,9

In recent years, research on cognition has improved the understanding of cognitive

impairment and progression to dementia.3,10 Estimates of cognitive impairment vary by

up to 25% within a given country, depending on the selected definition of


6

impairment.11,12 Adding a measure of function in the form of Instrumental Activities of

Daily Living (IADL), has been shown to improve the accuracy of cognitive assessments

even in populations with different education levels and socioeconomic status. 13 , 14

Lower cognition scores correlated with greater impairments in functioning, suggesting

IADL improves assessment of cognitive decline. 15 Similar to measuring cognitive

impairment rates, rates of various dementias differ between countries, even when using

consistent diagnostic definitions. 16 These discrepancies highlight the difficulty in

ascertaining true cognition levels with existing tools, and differentiating between

"normal" cognitive decline and decline preceding the onset of dementia.

A reliable tool to measure cognition in older persons as part of household health

surveys is needed: in particular, a culture-fair instrument to distinguish normal cognition

from pathological decline.17,18,19 Additionally, the instrument should be sensitive to

different literacy levels. Currently available tools used to screen for cognitive decline

show substantial variation across different countries, suggesting limitations in accuracy

and reliability.20,21,22, 23

The battery of tests in this study originated from the World Health Organization's World

Health Survey (WHS) programme, which has used self-reported and measured

cognition in over 70 countries.24 The three cognitive tests selected as part of the Study

on AGEing and adult health's (SAGE) pilot test - word list recall, verbal fluency and digit

span - accurately measure the cognitive domains most impacted by age, impairment

and the early stages of dementia. The selected tasks are also brief compared to other


7

neuropsychological tests, allowing for a culture-fair screening tool within a household

health survey that combines subjective and objective measures of cognition and

physical function. Lastly, it can be implemented by trained lay interviewers.8 We

present the initial results from a pilot study of the World Health Organization's SAGE

instrument.

Methods

The SAGE survey was piloted in Ghana, India and Tanzania from April to July 2005.

Face-to-face interviews were conducted in respondent's dwellings. Translation and

back-translation methods based on the WHS protocol were used (WHO, 2003). Data

collected included household and housing characteristics, income, expenditures and

transfers, self-reported health in 12 domains, and measured cognitive and physical

function.

India and Ghana used a convenience sample to obtain the desired sample size of

N=500 persons aged 50 years and older, with an emphasis on enlisting similar numbers

of men and women across the older age ranges. Respondents in Tanzania were

randomly selected from household listings within a demographic surveillance site in the

north-eastern region of the country. India included a small sample of respondents

younger than 50 years as a comparator group. Training sessions for survey

methodologies and instruments were provided in each country.


8

Self-reported cognition was assessed through two questions, one about concentration

and the other about learning. In addition, measures of functioning - were assessed

through the WHO Disability Assessment Scale, Version 2.0 (WHODAS) along with

additional questions about Activities of Daily Living (ADLs) and Instrumental Activities of

Daily Living (IADL).25

Performance tests:

Three domains were selected to objectively measure cognition: assessment of memory

and learning (using the word-list learning task); working memory (using digit span

forward and backward); and, verbal fluency (using the category fluency test).26,27,28 All

three performance tests were scored according to standard practices for each test.

Verbal recall, measured with a 10-word learning task, was estimated by summing the

four trials, three immediate recall and one delayed by 10 to 15 minutes.2612 Scoring for

digit span forward and backward involved tabulations based on first or second try

correct recitation of each number series - two points or one point per row, with eight

rows in total for each of the two tests. The final task, verbal fluency, was measured as

the sum of all admissible words regarding the category of animals. STATA version 9.2

was used for all analyses.

Results

A total of 1446 respondents completed the survey. Fifty-four percent of respondents

were women (see Table 1). The mean age was 59 years in India, 61 years in Ghana

and 65 years in Tanzania. The sample in Ghana was primarily urban, Tanzania


9

primarily rural and the India sample a mixture between rural and urban. It was possible

in Ghana to collect follow-up data on 119 respondents from the baseline World Health

Survey conducted in 2003. Levels of education varied by country, but women

consistently had lower levels of education than men across all countries.

[Table 1 about here]

The pattern of self-reported cognition, memory and learning, were significantly different

by sex and age (p<0.05), with women and older adults reporting more difficulty with

memory and learning (see also Figures 1 and 2).

[Figures 1 and 2 about here or if in Appendix – add “in appendix” after “see also Fig 1 &

2”]

Results of the cognition tests differed by country, sex, age, and education level (see

Table 2). The mean verbal recall (VR) scores were lower in India, but the difference

was small compared to Ghana and Tanzania. Women scored lower than men in the

word-list learning task (p < 0.006) and mean scores decreased with increasing age.

The difference was most evident when comparing the 80+ age group (mean score of

13.7) to the youngest age group in India (23.7). The impact of years of education on

memory was clear: for every unit increase in years of education the average VR score

increased by 1.123 (p < 0.001) In Ghana, scores ranged from 19.7 with no formal

education to 29.3 in respondents who completed a post-graduate education.


10

[Table 2 about here: Mean VR, VF scores by country, sex, age and education level]

Verbal fluency results were comparable in Ghana, India, and Tanzania: the mean

number of animals named in one minute was 10.8, 11.5 and 9.5, respectively. The

influence of sex was more pronounced in verbal fluency than verbal recall, with larger

differences between mean scores of women and men than with verbal recall. Verbal

fluency was less influenced by age until respondents reached the 80 year and older

group. Mean verbal fluency scores increased with higher levels of education. Each

additional year of education completed resulted in almost one additional animal named

(0.928, p < 0.001). Respondents in India, for example, who completed college degrees

or further education named a third more animals than those with no formal education.

The third performance test included reciting a digit-span forward and backward. In each

country, fewer respondents completed this task in comparison to the other performance

tests. Tanzanian respondents consistently scored lower in the forward and backward

tests compared to the other countries (see Table 3). Respondents in Ghana scored 1.2

points higher than those in India for digits forward, while mean scores in India were 2.4

points higher than in Ghana for digits backward. The influence of sex and age were

inconsistent across countries for digit span. As with the previous two tests, higher

educational levels resulted in higher mean scores.



11

Since cognitive function is an intrinsic component of ADLs,158 we included WHODAS to

measure function associated with cognition, plus additional ADL/IADL type questions.

The WHODAS contains many of the most commonly asked ADL and IADL questions -

plus the WHODAS approach also assesses severity of disability. Tanzanians reported

less disability than either Ghana or India. Forty percent of the respondents in

Tanzania reported no problems with ADLs (see Table 4), and correspondingly had the

lowest disability assessment score of 18.5. Comparatively, between 26 and 28% of

respondents in Ghana and India stated no difficulties with ADLs.

Across all three countries, substantially more women reported problems with

ADL/IADLs. In Ghana, 51% of women reported difficulties in at least two activities of

daily living compared to 35% of men. Additionally, women had higher mean WHODAS

scores, with even a third higher score in India than for men. Older age groups reported

higher WHODAS scores. Seventy-one percent of respondents in India, ages 18-49 had

no difficulty with ADLs compared to 25% at the ages 50-59, and almost 12% in

respondents aged 80 years and older. Those with less education, particularly no formal

education, reported substantially more disability than the respondents who had at

minimum completed high school or the equivalent. In Tanzania, mean WHODAS

scores declined from 22.9 in respondents with no formal education, to 5.6 in

respondents who have completed college or university.



12

As an objective measure of mobility, the mean time to complete a 4 meter walk at usual

pace was longest in Ghana at 6.2 seconds, followed by Tanzania at 5.8 seconds and

4.5 seconds in India. Mean times were longer for women in each country, and

increased with increasing age. The differences in mobility as measured by the timed

walk and WHODAS scores across countries reflect the multidimensionality of the

WHODAS tool and both followed recognizable age and sex trends.

Discussion

Currently, an estimated 24 million persons worldwide live with dementia, a number

expected to reach 81 million by 2040. 29 Accurately measuring cognition and

determining global prevalence of dementia will continue to be a problem due to the

inconsistency of available data across countries. Previous attempts to reconcile

differences in cross-cultural observations of dementia found that less than half of

dementia cases across countries were consistently diagnosed correctly.30 Even among

developed regions with sound epidemiological studies, a large proportion of variability

exists in reported dementia rates. 31 , 32 Yet it is in developing countries where the

majority of persons with dementia reside, but where little is known about prevalence.

An estimated 60% of those with dementia currently live in developing countries and this

is projected to climb to nearly three-fourths of the population with dementia by 2040.2915

Attempting to measure cognition within a household health survey requires additional

considerations in regards to interview time, complexity and selection of cognition


13

domains. Mild cognitive impairment and early stages of dementia particularly impact

memory, attention, learning, and language. 33 , 34 Episodic, semantic, and working

memory decline early in disease progression.35,36 Testing these elements of memory

may therefore be ideal for screening patients for dementia prior to diagnosis.

Another challenge is the reliability and comparability of answers to questions that use

ordered categorical response scales like those used for self-reported cognition.37 One

method to address this comparability problem is the anchoring vignettes approach.38

The vignettes use a concrete level of cognition and respondents are asked to rate the

vignettes using the same questions and response categories that they use to describe

their own cognition. Vignettes fix the level of cognitive ability so that variation in

categorical responses is attributable to variation in response category cutpoints.

Objective cognition tests are employed as one step to establish the validity this

methodology. Vignette adjusted results for this SAGE pilot will be presented elsewhere.

The verbal recall word-list test involves short- and long-term memory, plus learning a

new task.2612 This verbal recall test, along with a verbal fluency test, rank among the

best discriminating tests for cognitive impairment and the most sensitive for patients

with Alzheimer's disease.3521, 3622, 39 Verbal fluency tests both language and semantic

memory. Cognitive impairment impacts category fluency over letter fluency.40 Among

categories, animal fluency performs as a better marker for dementia than listing words

beginning with a certain letter.41 Category fluency maintains as high as 100% sensitivity

for dementia.42 Digit span, the third in our battery of tests, assesses short-term and


14

working memory as well as attention and concentration with a high degree of

reliability.2713, 3622 Cognitively impaired patients scored lower than normal respondents,

particularly on the reverse span.43

The results of this study across the three countries indicated strong face validity for the

self-reported questions and performance tests. Women, persons of older age, and

those with less education scored lower on both the self-reported and administered

cognitive tests. These results support the battery of tests presented in this study as a

culture-fair measure of cognition as well as a comprehensive tool in its assessment of

both self-report and performance-based measures of function. One recognized

limitation was initiating the digit span performance task with too complex a series,

evidenced in the results by the small number of respondents able to complete even the

first row correctly. This task has been altered in the recent survey to a series of three

digits for digit forward and two digits for digit backwards to facilitate greater accuracy.

This pilot data covered relatively smaller populations from three different countries.

These pilot results has informed the implementation of the full survey and further

develop a culture-fair cognitive screening tool for use in household health surveys.

Data from an anticipated six countries will help to improve the assessment of cognition

worldwide.


15

TABLES AND FIGURE

Table 1. Sociodemographic characteristics by sex and country.

Ghana India Tanzania

Male Female Total Male Female Total Male Female Total

Age

18-49 na* na na 14.8 6 10.4 na na na

50-59 50.9 44.1 47.2 32.2 37.3 34.8 40.9 37.5 39.0

60-69 24.8 30.4 27.9 34.7 30.5 32.6 28.8 35.1 32.4

70-79 16.4 17.1 16.8 16.1 20.6 18.3 20 15.4 17.4

80+ 6.5 6.5 6.5 2.1 5.2 3.6 10.2 11.9 11.2

Missing 1.4 1.9 1.7 0 0.4 0.2 0 0 0

Residence

Urban 90.7 89.4 89.9 53.8 54.9 54.4 1.4 0.7 1.0

Rural 9.3 10.6 10.1 46.2 45.1 45.6 98.6 99.3 99.0

Marital Status

Never 2.3 0.4 1.3 5.5 0.4 3 0.5 0 0.2

Currently 79.0 36.5 55.6 87.7 58.8 73.4 80.5 28.8 51.0

Separated/Divorced 7.9 25.1 17.4 0 1.3 0.6 8.8 22.5 16.6

Widowed 10.3 37.6 25.4 6.8 39.1 22.8 10.2 47.0 31.2

Co-habiting 0 0.4 0.2 0 0 0 0 1.8 1.0

Missing 0.5 0 0.2 0 0.4 0.2 0 0 0

Education No formal education 17.3 49.4 35 31.8 71.2 51.4 33.5 80.7 60.4

Less than Primary 9.3 12.5 11.1 14.4 4.7 9.6 37.2 14.4 24.2

Primary 32.2 24.3 27.9 19.1 11.6 15.4 23.3 4.6 12.6

Secondary 20.6 8.0 13.6 11.9 4.3 8.1 4.7 0 2.0

High School 12.1 4.6 8.0 8.1 2.1 5.1 0 0.4 0.2

College/University 6.1 1.1 3.4 8.9 4.7 6.8 1.4 0 0.6

Post Graduate 1.9 0 0.8 5.9 0.9 3.4 0 0 0

Missing 0.5 0 0.2 0 0.4 0.2 0 0 0

Income quintile

1 (lowest) 13.6 24.0 19.3 20.3 17.2 18.8 8.8 28.1 19.8

2 19.6 18.3 18.9 17.8 19.7 18.8 19.1 20.4 19.8

3 21.5 17.5 19.3 14.4 23.2 18.8 19.1 20.7 20.0

4 20.1 18.6 19.3 20.3 20.2 20.3 23.7 17.2 20.0

5 (highest) 22.9 16.0 19.1 25.4 19.3 22.4 28.4 13.0 19.6

Missing 2.3 5.7 4.2 1.7 0.4 1.1 0.9 0.7 0.8

Total 100 100 100 100 100 100 100 100 100

Number 214 263 477 236 233 469 215 285 500

*na = not applicable


16

Table 2. Mean verbal recall (VR), verbal fluency (VF) scores by country, sex, age and education level.*

Ghana India Tanzania

VR VF VR VF VR VF

Sex

Male 21.2 11.7 19.1 12.6 19.2 11.2

Female 20.2 10.2 17.5 10.3 19.1 8.2

Total 20.6 10.8 18.3 11.4 19.2 9.5

Age group

18-49 23.7 14

50-59 21.8 11.4 19.4 11.7 20.2 9.9

60-69 20.9 10.8 17.6 11.3 19.1 9.5

70-79 19.1 10.4 15.6 10.1 19 9.4

80+ 15 8.7 13.7 9.5 16 8.1

Total 20.7 10.9 18.4 11.4 19.2 9.5

Education

No formal 19.7 9.9 16.0 9.9 18.8 8.6

Less than primary 19.1 10.8 19.2 11.8 20.1 10.6

Primary completed 20.6 10.8 20.2 12.8 18.5 11.1

Secondary completed 21.7 12.2 20.7 12.3 22.2 12.9

High school 22.7 11.7 20 12.8 25 1

College/university completed 24.3 12.6 24.1 15.6 14 11

Post-graduate degree completed 29.3 13.5 22.8 15.3 Total 20.7 10.8 18.4 11.4 19.2 9.5

*See Appendix 2 for the word-list (VR) and category fluency (VF) performance tests.


17

Table 3. Number (N) of respondents completing the digit span tests and mean scores for forward (DF) and backward (DB) by country, sex, age and education level.* Ghana India Tanzania

DF DB DF DB DF DB

N Mean N Mean N Mean N Mean N Mean N Mean

Sex

Male 182 3.9 63 2.3 39 2.4 11 3.6 68 1.5 17 1.4

Female 174 3.0 56 2.7 16 2.3 3 9.7 43 1.7 14 2.4

Total 356 3.5 119 2.5 55 2.3 14 4.9 111 1.6 31 1.8

Age group

18-49 0 0 0 0 16 2.3 7 3.3 0 0 0 0

50-59 186 3.8 67 2.5 19 2.5 1 13 58 1.6 16 1.4

60-69 99 3.4 34 2.7 16 2.1 2 2 36 1.6 10 2.7

70-79 48 3.0 12 2.2 4 3.0 4 7.3 15 1.5 5 1.4

80+ 18 2.3 1 1.0 0 0 0 0 2 1.5 0 0

Total 351 3.5 114 2.5 55 2.3 14 4.9 111 1.6 31 1.8

Education

No formal 84 2.1 23 2.7 6 1.7 2 8.5 36 1.3 7 2.7

Less than 38 2.8 14 2.4 4 1.5 1 8 36 1.6 11 1.4

Primary 113 3.6 30 2.3 7 2.1 0 0 29 1.7 9 1.9

Secondary 64 4.6 30 2.7 7 2.9 2 7 8 1.8 2 1

High school 37 4.5 13 1.8 4 2.5 1 2 1 7 1 3

College/university

completed

16 4.3 6 3.2 19 2.4 3 1.7 1 1 1 1

Post-graduate

degree

4 5.3 3 2.7 8 2.8 5 4.6 0 0 0 0

Total 356 3.5 119 2.5 55 2.3 14 4.9 111 1.6 31 1.8

*See Appendix 2 for the digit span forward and backward performance tests.


18

Table 4. ADL deficiencies (%) and mean WHODAS score by country, sex, age and education level.* Ghana India Tanzania

ADL Mean

DAS

ADL MeanDA

S

ADL MeanDA

S Non

e One

2+ Non

e One

2+ Non

e One

2+

Sex

Male 38.3

26.6

35 17.8 37.7 22.

5 39.

8 17 51.2

23.3

25.6

12.5

Female 16

33.1

51 27.4 18.5 20.

2 61.

4 29.3 32.6

24.6

42.8

23.1

Total 26

30.2

43.8

23.1 28.1 21.

3 50.

5 23.1 40.6 24

35.4

18.5

Age group

18-49 0 0 0 0 71.4

12.2

16.3

8.7 0 0 0 0

50-59 35.1 32

32.9

15.9 25.2 27 47.

9 20.2 57.4 20

22.6

11.7

60-69 24.1

28.6

47.4

24.7 27.5 22.

2 50.

3 23 38.3 29

32.7

18

70-79 10

31.3

58.8

33 12.8 17.

4 69.

8 33.1 19.5

29.9

50.6

26.7

80+ 0

25.8

74.2

45.3 11.8 5.9 82.

4 45.1 21.4

14.3

64.3

31

Total 26

30.2

43.8

23.3 28.1 21.

3 50.

5 23.2 40.6 24

35.4

18.5

Education

No formal 14.4

40.1

45.5

26.9 19.5 17.

8 62.

7 30.1 32.8

23.8

43.4

22.9

Less than primary

18.9 28.

3 52.

8 28.5 31.1 20

48.9

18.3 47.9 28.

1 24 12.9

Primary completed

33.1 26.

3 40.

6 22.2 27.8

30.6

41.7

18.1 54 20.

6 25.

4 11.1

Secondary completed

26.2 23.

1 50.

8 19.5 34.2

31.6

34.2

18 80 10 10 6.1

High school completed

39.5 23.

7 36.

8 16.4 50 25 25 12.4 100 0 0 8.3

College/university completed 56.3

18.8 25 11.6 46.9

15.6

37.5 10.8 100 0 0 5.6

Post-graduate degree completed 100 0 0 1.4 62.5

18.8

18.8 9 0 0 0 0

Total 26

30.2

43.8

23.2 28.1 21.

3 50.

5 23.2 40.6 24

35.4

18.5

Response scale: 1=none; 2=mild; 3=moderate; 4=severe; 5=extreme/cannot do.

*See Appendices 3 and 4 for the WHODAS and ADL-scale specific questions.


19

APPENDIX 1. Self-reported Health

Figure 1. Self reported memory by age and sex ("Overall in the last 30 days, how much

difficulty did you have with concentrating or remembering things?").

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

M,18-49 M,50-59 M,60-69 M,70-79 M,80+ F, 18-49 F,50-59 F,60-69 F,70-79 F,80+

None Mild Moderate Severe Extreme

Figure 2. Self reported learning by age and sex ("Overall in the last 30 days, how much difficulty did you have in learning a new task (for example, learning how to get to a new place, learning a new game, learning a new recipe)?").

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

M,18-49 M,50-59 M,60-69 M,70-79 M,80+ F, 18-49 F,50-59 F,60-69 F,70-79 F,80+

None Mild Moderate Severe Extreme


20

APPENDIX 2. Cognitive tests used in SAGE

WORD-LIST RECALL (maximum 40 points) List of words used Arm, Bed, Plane, Dog, Clock, Bike, Ear , Hammer, Chair, Cat Immediate Recall plus learning saturation Number of words recalled correctly Trial 1, 2, 3 Number of words that respondent failed to recall Trial 1, 2, 3 Number of words substituted Trial 1, 2, 3 Delayed Recall Number of words recalled correctly Number of words that respondent failed to recall Number of words substituted

DIGIT SPAN (maximum 16 points for forward and 16 points for backward)

Points Sequence of numbers 0, 1,2 4-7-2-8-1

3-4 8-4-7-2-5-1

5-6 3-9-0-7-1-8-2 7-8 2-6-8-9-0-4-1-5

9-10 8-5-7-3-2-0-1-5-9

11-12 9-6-7-3-9-5-1-6-3-8

13-14 5-1-6-8-9-3-2-0-8-3-1

15-16 3-7-2-9-1-0-5-2-6-4-3-8

CATEGORY FLUENCY

Number of animals named correctly in one minute. Number of errors.

APPENDIX 3. WHO Disability Assessment Scale (WHODAS-12 item)

In the last 30 days, how much difficulty did you have …*

1 … in standing for long periods (such as 30 minutes)?

2 … in taking care of your household responsibilities?

3 … in learning a new task, for example, learning how to get to a new place?

4 … in joining in community activities (for example, festivities, religious or other activities) in the same way as anyone else can?

5 … concentrating on doing something for 10 minutes?

6 … in walking a long distance such as a kilometer (or equivalent)?

7 … in washing your whole body?

8 … in getting dressed (including, for example, putting on your shoes and socks)?

9 … with people you do not know?

10 … in maintaining a friendship?

11 … in your day to day work?

12 In the last 30 days, how much have you been emotionally affected by your health condition(s)?

*Response scale: 1=none; 2=mild; 3=moderate; 4=severe; 5=extreme/cannot do.


21

APPENDIX 4. Activities of Daily Living Scale

In the last 30 days, how much difficulty did you have …*

1 …in standing up from sitting down (such as, getting up from a chair after sitting for long periods)?

2 … in washing your whole body?

3 …in getting dressed (including, for example, putting on your shoes and socks)?

4 … with moving around inside your home (such as walking across a room)?

5 … with eating (including cutting up your food)?

6 … with getting up from lying down (for example, getting in and out of bed)?

7 … with getting to and using the toilet?

*Response scale: 1=none; 2=mild; 3=moderate; 4=severe; 5=extreme/cannot do.

References

1 Ferri CP, Prince M, Brayne C, Brodaty H, et al. Global prevalence of dementia: a Delphi consensus study. Lancet.

2005;366:2112–7. 2 Sosa AL, Albanese E, Stephan BCM, Dewey M, et al. Prevalence, distribution, and impact of mild cognitive

impairment in Latin America, China and India: A 10/66 population-based study. PLoS Med. 2012:9(2):e1001170. 3 Alzheimer’s Disease International. World Alzheimer Report 2011. The benefits of early diagnosis and intervention.

London: Alzeheimer’s Disease International. 2011. www.alz.co.uk/research/WorldAlzheimerReport2011.pdf 4 Levy R. Aging-associated cognitive decline. Working party of the International Psychogeriatric Association in

collaboration with the World Health Organization. Int Psychogeriatr. 1994;6(1):63–8 [review]. 5 Smith GE, Petersen RC, Parisi JE, et al. Definition, course, and outcome of mild cognitive impairment. Aging

Neuropsychol Cogn. 1996;3:141–7. 6 Craik FIM, Salthouse TA (Eds.). Handbook of aging and cognition. Hillsdale, NJ: Lawrence Erlbaum Associates,

1992. 7 Unverzagt FW, Ogunniyi A, Taler V, Gao S, et al. Incidence and risk factors for cognitive impairment no dementia

and mild cognitive impairment in African Americans. Alzheimer Dis Assoc Disord, 25(1):4-10, 2011, PM:20921881. 8 Prince M, Acosta D, Ferri CP, Guerra M, et al. A brief dementia screener suitable for use by non-specialists in

resource poor settings - the cross-cultural derivation and validation of the brief Community Screening Instrument for

Dementia. Int J Geriatr Psychiatry. 2011;26(9):899-907.. 9 Ogunniyi A, Lane KA, Baiyewu O, Gao S, Gureje O, Unverzagt FW, Murrell JR, Smith-Gamble V, Hall KS,

Hendrie HC. Hypertension and incident dementia in community-dwelling elderly Yoruba Nigerians. Acta Neurol

Scand. 2011;124(6):396-402. 10

Unverzagt FW, Gao S, Baiyewu O, et al. Prevalence of cognitive impairment: data from the Indianapolis study of

health and aging. Neurology. 2001;57:1655-62 11

Meguro K, Ishii H, Yamaguchi S, et al. Prevalence and cognitive performance of clinical dementia rating 0.5 and

mild cognitive impairment in Japan. The Tajiri project. Alzheimer Dis Assoc Disord. 2004;18(1):3-10. 12

Pioggiosi PP, Berardi D, Ferrari B, Quartesan R, De Ronchi D. Occurrence of cognitive impairment after age 90:

MCI and other broadly used concepts. Brain Res Bull. 2006;68(4):227-32. 13

Mathuranath PS, George A, Cherian PJ, Mathew R, Sarma PS. Instrumental activities of daily living scale for

dementia screening in elderly people. Int Psychogeriatr. 2005;17(3):461-74. 14

Bruffaerts R, Vilagut G, Demyttenaere K, Alonso J, et al. Role of common mental and physical disorders in

partial disability around the world. Br J Psychiatry. 2012 Apr 26. [Epub ahead of print] 15

Ishizaki T, Yoshida H, Suzuki T, et al. Effects of cognitive function on functional decline among community-

dwelling non-disabled older Japanese. Arch Gerontol Geriatr. 2006;42(1):47-58. 16

Xu G, Meyer JS, Huang Y, Chen G, Chowdhury M, Quach M. Cross-cultural comparison of mild cognitive

impairment between China and the USA. Curr Alzheimer Res. 2004;1(1):55-61. 17

Xu G, Meyer JS, Huang Y, Chen G, et al. Cross-cultural comparison of mild cognitive impairment between China

and USA. Curr Alzheimer Res 2004;1: 55–61.


22

18

Arnaiz E, Almkvist O, Ivnik RJ, Tangalos EG, et al. Mild cognitive impairment: a cross-national comparison. J

Neurol Neurosurg Psych 2004;75:1275–80. 19

Baiyewu O, Unverzagt FW, Ogunniyi A, Smith-Gamble V, et al. Behavioral symptoms in community-dwelling

elderly Nigerians with dementia, mild cognitive impairment, and normal cognition. Int J Geriatr Psychiatry.

2012;Mar 2. doi: 10.1002/gps.2804. 20

Stephan BC, Matthews FE, McKeith IG, Bond J, Brayne C. Early cognitive change in the general population: how

do different definitions work? J Am Geriatr Soc 2007;55:1534–40. 21

Palmer K, Backman L, Winblad B, Fratiglioni L. Detection of Alzheimer's disease and dementia in the preclinical

phase: population based cohort study. BMJ 2003;326: 245. 22

Panza F, Capurso C, D'Introno A, Colacicco AM, et al. Heterogeneity of mild cognitive impairment and other

predementia syndromes in progression to dementia. Neurobiol Aging. 2007;28:1631-2. 23

Sosa AL, Albanese E, Prince M, Acosta D, et al. Population normative data for the 10/66 Dementia Research

Group cognitive test battery from Latin America, India and China: a cross-sectional survey. BMC Neurol. 2009;9:48. 24

World Health Organization. World Health Survey. Geneva, Switzerland: World Health Organization, 2006.

www.who.int/healthinfo/survey/whscurrent/en/ 25

Ustün TB, Chatterji S, Kostanjsek N, Rehm J, et al. Developing the World Health Organization Disability

Assessment Schedule 2.0. Bull World Health Organ. 2010;88:815-23. 26

Spreen O, Strauss E. Memory. In: A Compendium of Neuropsychological Tests, 2nd ed. Oxford, England: Oxford

University Press, 1998:260-422. 27

Spreen O, Strauss E. General ability and premorbid intelligence. In: A Compendium of Neuropsychological Tests,

2nd ed. Oxford, England: Oxford University Press, 1998:43-135. 28

Spreen O, Strauss E. Language Tests. In: A Compendium of Neuropsychological Tests, 2nd ed. Oxford, England:

Oxford University Press, 1998:423-480. 29

Ferri CP, Prince M, Brayne C, et al. Global prevalence of dementia: a Delphi consensus study. Lancet.

2005:366:2112-17. 30

Gurland BJ, Wilder DE, Cross P, et al. Screening scales for dementia: toward reconciliation of conflicting cross-

cultural findings. Int J Geriatr Psychiatry. 1992;7:105-113. 31

Ott A, Breteler MM, van Harskamp F, Stijnen T, Hofman A. Incidence and risk of dementia. The Rotterdam

Study. Am J Epidemiol. 1998;147(6):574-80. 32

The Canadian Study of Health and Aging Working Group. The incidence of dementia in Canada. Neurology.

2000;55:66-73. 33

Blennow K, de Leon MF, Zetterberg H. Alzheimer's disease. Lancet. 2006; 368(9533):387-403 [review]. 34

Jacobs DM, Sano M, Dooneief G, Marder K, Bell KL, Stern Y. Neuropsychological detection and

characterization of preclinical Alzheimer's disease. Neurology. 1995;45(5):957-62. 35

Spaan PE, Raaijmakers JG, Jonker C. Early assessment of dementia: the contribution of different memory

components. Neuropsychology. 2005;19(5):629-40. 36

Kalbe E, Kessler J, Calabrese P, et al. DemTect: a new, sensitive cognitive screening test to support the diagnosis

of mild cognitive impairment and early dementia. Int J Geriatr Psychiatry. 2004;19(2):136-43. 37

Salomon JA, Tandon A, Murray CJL. Comparability of self rated health: cross sectional multi-country survey

using anchoring vignettes. BMJ. 2004;328(7434):258. 38

Tandon A, Murray CJL, Salomon JA, King G. Statistical methods to enhance cross-population comparability.

Global Programme on Evidence for Health Policy Discussion Paper No. 42. Geneva, Switzerland: World Health

Organization, 2001. 39

Petersen RC, Smith GE, Waring SC, Ivnik RJ, Tangalos EG, Kokmen E. Mild cognitive impairment: clinical

characterization and outcome. Arch Neurol. 1999;56(3):303-8. 40

Cerhan JH, Ivnik RJ, Smith GE, Tangalos EC, Petersen RC, Boeve BF. Diagnostic utility of letter fluency,

category fluency, and fluency difference scores in Alzheimer's disease. Clin Neuropsychol. 2002;16(1):35-42. 41

Canning SJ, Leach L, Stuss D, Ngo L, Black SF. Diagnostic utility of abbreviated fluency measures in Alzheimer

disease and vascular dementia. Neurology. 2004;62(4):556-62. 42

Monsch AU, Bondi MW, Butters N, Salmon DP, Katzman R, Thal LJ. Comparisons of verbal fluency tasks in the

detection of dementia of the Alzheimer type. Arch Neurol. 1992;49(12):1253-8. 43

Lam LC, Lui VW, Chiu HF, Chan SS, Tam CW. Executive function impairment in community elderly subjects

with questionable dementia. Dement Geriatr Cogn Disord. 2005;19(2-3):86-90.

Date post:	01-Jan-2017
Category:	Documents
Upload:	phungkien
View:	219 times
Download:	0 times

Measuring cognitive status in older age in lower income countries

Documents