Measuring disability across

cultures and health

conditions Geneva

December 2012

Prof. Martin Prince

Centre for Global Mental Health

King’s College London

martin.prince@kcl.ac.uk

The 10/66 Dementia Research Group

• Pilot studies in 24 centres (dementia diagnosis, care

arrangements) (1999-2002)

• Population-based catchment area surveys in seven Latin

American countries, India and China (2003-2007)

• 3-5 year incidence phase (2008-2010)

Measuring disability – key 10/66 publications

1. Sousa RM et al. Contribution of chronic diseases to disability in elderly

people in countries with low and middle incomes: a 10/66 Dementia

Research Group population-based survey. Lancet. 2009 Nov

28;374(9704):1821-30.

2. Sousa RM et al. The contribution of chronic diseases to the prevalence

of dependence among older people in Latin America, China and India: a

10/66 Dementia Research Group population-based survey. BMC

Geriatrics. 2010 Aug 6;10:53

3. Sousa RM et al. Measuring disability across cultures; the psychometric

properties of the WHODAS II in older people from seven low- and

middle-income countries. The 10/66 Dementia Research Group

population-based survey. Int J Methods Psychiatr Res. 2010 Jan 26.

4. Prince M et al. Measuring disability across physical, mental and

cognitive disorders. In “The Conceptual Evolution of DSM-V” ed Regier

DA et al, American Psychopathological Association 2010

Disability (ICF)

• “the negative aspects of the interaction between an

individual (with a health condition) and that individual’s

contextual factors (personal and environmental)”

• Interactions include

– impairments (affecting the body),

– activity limitations (affecting actions or behaviour)

– participation restrictions (affecting experience of life)

Approaches to disability assessment

• Self-identification as disabled e.g. “Do you have a limiting disability?”

• Lists of chronic disease diagnoses and/ or impairments

• Activities of daily living assessments – core tasks essential to daily

life

• Instrumental activities of daily living

• Performance measures

• Health status scales (e.g. HoNoS and SF-36/12) – symptoms,

impairments, general health, physical activity limitations, role

limitations, and participation restriction

• WHODAS 2.0

Understanding/

communicating

Self - care

Getting around Getting on with

people

Life activities

Participation

Global disability

WHODAS II Model

SF-36® WHODAS 2.0

Ownership Quality Metric Inc. WHO

Conceptual basis Weak - Empirical Strong - Theory

driven (ICF), CAR

Model Cartesian ‘Global disability’

Dimensional structure Multidimensional Unidimensional

Scale development Classical scale

theory

IRT (12 item

version)

Documentation Extensive Recent

Use 12191 references 92 references

Status World leader Growing

Comparing two measurement approaches

Dependence

• “the need for frequent human help or care beyond that

habitually required by a healthy adult” (Harwood, WHO Bull 2004)

• Less often studied than disability

• Measurement issues not resolved

– Frequently inferred from ADL disability, or even chronic diseases

– Direct assessment of co-resident potential carers (e.g. 10/66)

– Critical time dependence

Why do needs for care matter?

• Neglected public health topic

• Prevalence 3-16% (slightly

lower than in HIC)

• Associated with

– comorbidity

– socioeconomic disadvantage

– high health and societal costs

• 4 x increase among older

people in LMIC forecast to

2050

• Social protection not

assured

WHODAS 2.0 disability, and needs for care

Understanding/

communicating

Self - care

Getting around Getting on with

people

Health condition

Interrelationships

Disability

Dependence

Brain and mind disorders make the largest contribution

to disability and dependence (10/66 studies)

Health condition/ impairment DEPENDENCE

Mean PAPF %

DISABILITY

Mean PAPF %

1. Dementia 36.0% 25.1%

2. Limb paralysis/ weakness 11.9% 10.5%

3. Stroke 8.7% 11.4%

4. Depression 6.5% 8.3%

5. Visual impairment 5.4% 6.8%

6. Arthritis 2.6% 9.9%

Sousa et al, Lancet, 2009; BMC Geriatrics 2010

Questions regarding the measurement of

disability

– Is the WHODAS II a unidimensional scale?

– Is it a hierarchical scale conforming to IRT

principles?

– Does it measure the same thing in the same

way (measurement invariance)….

• across countries and cultures?

• across health conditions?

Evidence from 10/66 studies

• Cronbach’s alpha ranges from 0.90 to 0.97 by site

• PCA generated a one factor solution in 7/11 sites –

2 factor solution in Cuba, Dominican Republic (DR),

rural India, rural China with some cross-loading

• CFA suggested that the DR two factor solution fitted

better than the one factor solution in nearly all sites

• However,

– factor loadings exceeded 0.40 for the one factor solution

in all sites

– Second factor comprised ‘getting along with people’ and

‘self-care’, the two ‘high difficulty’ domains

Mokken IRT analysis – Monotone Homogeneity Model

Loevinger’s H scalability coefficient

Cuba 0.64

DR 0.52

Peru (urban) 0.66

Peru (rural) 0.55

Venezuela 0.63

Mexico (urban) 0.60

Mexico (rural) 0.65

China (urban) 0.81

China (rural) 0.69

India (urban) 0.64

India (rural) 0.72

Only 2/132 item x site

combinations

showed small

monotonicity

violations

Sousa et al, Int. J Meth

Psych Res, 2010

Does the WHODAS II show measurement

invariance across cultures?

Two approaches……

1. Confirmatory factor analysis

– Do the same items load similarly onto the same underlying latent traits?

– Compare the goodness of fit of two models one in which the loadings are estimated freely and the other in which they are constrained to be equal across sites

2. IRT

– Are the item difficulties in the same rank order, and do they correlate highly between sites?

Measurement Invariance across sites – CFA approach

One Factor Unconstrained Constrained

AIC 23456 25855

TLI 0.72 0.74

RMSEA 0.05 0.05

Two factor

AIC 14946 17645

TLI 0.82 0.82

RMSEA 0.04 0.04

Sousa et al, Int. J Meth

Psych Res, 2010

Measurement invariance – correlations in

item difficulties between sites Cuba Dominican

Republic

Peru

Urban

Peru

Rural

Venezuela Mexico

Urban

Mexico

Rural

China

Urban

China

Rural

India

Urban

India

Rural

Dominican

Republic 0.94 -

Peru

Urban 0.82 0.86 -

Peru

Rural 0.87 0.88 0.90 -

Venezuela 0.95 0.94 0.91 0.92 -

Mexico

Urban 0.94 0.95 0.90 0.91 0.98 -

Mexico

Rural 0.93 0.94 0.85 0.88 0.97 0.99 -

China

Urban 0.85 0.78 0.71 0.72 0.78 0.76 0.73 -

China

Rural 0.50 0.59 0.43 0.48 0.51 0.57 0.61 0.46 -

India

Urban 0.80 0.84 0.78 0.82 0.86 0.88 0.88 0.75 0.62 -

India

Rural 0.92 0.93 0.89 0.88 0.98 0.96 0.96 0.76 0.53 0.82 -

0.5

0.55

0.6

0.65

0.7

0.75

0.8

0.85

0.9

0.95

1

Dealing w

ith people

Maintaining friendship

Getting dressed

Washing

Concentrating

Everyday activities

Com

munity activities

Learning a task

Household responsibilities

Emotionally affected

Walk 1 km

Standing

WHODAS II item

Item

dif

ficu

lty Cuba

DR

Peru U

Peru R

Venezuela

Mexico U

Mexico R

China U

China R

India U

Item difficulty, by site

Does the WHODAS II show measurement

invariance across health conditions?

i l lness free

depression only

dem entia only

physical impairm ent only

com orbid i ty

Health condition

0.00

25.00

50.00

75.00

100.00

full w

ho

das s

co

re (

12 i

tem

)

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

Dealing w

ith people

Maintaining friendship

Getting dressed

Washing

Concentrating

Everyday activities

Com

munity activities

Learning a task

Household responsibilities

Standing

Em

otionally affected

Walk 1 km

WHODAS II item

Item

dif

ficu

lty

Depression

Dementia

Physical impairment

Comorbidity

Whole sample

Item difficulty, by health condition

WHODAS II – Distributional properties, by site

Mean % non-zero Mean WHODAS

WHODAS scores without zeros

Cuba 13.4 (20.0) 62.2% 21.5 (21.7)

DR 16.5 (20.3) 68.6% 24.0 (20.5)

Venezuela 13.0 (20.6) 59.6% 21.9 (22.7)

Peru (urban) 10.4 (14.5) 66.4% 15.7 (15.4)

Peru (rural) 10.7 (16.4) 58.6% 18.3 (17.8)

Mexico (urban) 10.0 (17.3) 51.7% 19.3 (19.9)

Mexico (rural) 11.1 (19.1) 48.7% 22.7 (22.0)

China (urban) 8.1 (20.1) 24.3% 33.2 (28.9)

China (rural) 8.0 (14.5) 43.6% 18.7 (17.2)

India (urban) 10.5 (15.4) 52.3% 16.9 (16.6)

India (rural) 28.3 (18.3) 97.7% 28.9 (17.9)

Sousa et al, Lancet 2009

Negative binomial vs. zero inflated negative binomial regression

(Sousa et al, Lancet 2009) Negative binomial

regression

Zero inflated negative binomial regression

Non-zero observations = 8711

Count (negative binomial) Count (negative binomial) Zero inflation (logit)

‘Well’ 1 (ref) 1 (ref) -

Pure depression 2.62 (2.38-2.90) 1.67 (1.54-1.81) 0.25 (0.20-0.32)

Dementia only 3.55 (3.24-3.89) 2.23 (2.08-2.39) 0.31 (0.27-0.35)

Physical impairment only 2.52 (2.37-2.68) 1.67 (1.59-1.75) 0.06 (0.05-0.08)

Comorbidity 5.60 (5.25-5.97) 2.96 (2.83-3.11) 0.45 (0.37-0.55)

Age (per 5 year increment) 1.25 (1.22-1.28) 1.14 (1.12-1.16) 0.78 (0.75-0.81)

Male gender 0.77 (0.73-0.81) 0.89 (0.85-0.92) 1.49 (1.37-1.61)

Education 0.89 (0.86-0.91) 0.96 (0.94-0.98) 0.19 (0.14-0.26)

Cuba 1 (ref) 1 (ref) 1 (ref)

DR 0.99 (0.92-1.08) 1.01 (0.95-1.07) 1.11 (0.96-1.27)

Peru 1.00 (0.92-1.09) 0.97 (0.91-1.04) 1.00 (0.88-1.14

Venezuela 0.82 (0.75-0.90) 0.87 (0.82-0.93) 1.26 (1.10-1.45)

Mexico 0.75 (0.68-0.83) 0.98 (0.91-1.06) 2.25 (1.96-2.58)

China 0.58 (0.52-0.64) 1.13 (1.06-1.22) 3.95 (3.46-4.50)

India 1.83 (1.69-1.99) 1.40 (1.31-1.48) 0.42 (0.36-0.49)

Log pseudolikelihood -45623.224 -42413.65

Wald chi2 4211.99 3303.87

Between site variation in a performance test –

walking speed

Conclusions

• The 12 item WHODAS 2.0 is a unidimensional scale with robust IRT properties

• Brief to complete and easy to score

• Reasonably strong evidence for measurement invariance across countries, cultures, and health conditions

• Can be used to compare the impact of mental and physical conditions, and the relative effectiveness of interventions

• Critical impairment in high item difficulty items corresponds to ‘dependence’

• Challenges to modelling can be addressed by allowing for overdispersion and zero-inflation

0

2

4

6

8

10

12

14

16

18

65 70 75 80 85 90 95 100

Cuba

DR

Peru

Venezuela

Mexico

China

India

Nigeria

Dependence free life expectancy (DepFLE) for men from age

65 in 10/66 countries

Life expectancy for women at age 65 in 10/66 countries, free

from dependence (DepFLE) and with dependence

0

2

4

6

8

10

12

14

16

18

20

LE (years)

CubaDR

Venez

uela

Peru (u

rb)

Mex

ico

China

India

Niger

ia

with dependence

free of dependence

10/66 prevalence data

(needing ‘much care’)

applied to WHO life

tables, using Sullivan’s

method

Disclosures

Sources of Research Support

1. Wellcome Trust

2. World Health Organisation

3. US Alzheimer’s Association

4. FONACIT/ CDCH/ UCV (Venezuela)

5. Rockefeller Foundation

6. Psychiatry Research Trust

Paid Editorial Relationship None

Consulting Relationship

Alzheimer’s Disease International (not for

profit)

WHO Instrument Development Group

(WHODAS II)

Stock Equity (>$10,000)

None

Speaker’s Bureau

None

www.alz.co.uk/1066

Measuring disability – key 10/66 publications

1. Sousa RM et al. Contribution of chronic diseases to disability in elderly

people in countries with low and middle incomes: a 10/66 Dementia

Research Group population-based survey. Lancet. 2009 Nov

28;374(9704):1821-30.

2. Sousa RM et al. The contribution of chronic diseases to the prevalence

of dependence among older people in Latin America, China and India: a

10/66 Dementia Research Group population-based survey. BMC

Geriatrics. 2010 Aug 6;10:53

3. Sousa RM et al. Measuring disability across cultures; the psychometric

properties of the WHODAS II in older people from seven low- and

middle-income countries. The 10/66 Dementia Research Group

population-based survey. Int J Methods Psychiatr Res. 2010 Jan 26.

4. Prince M et al. Measuring disability across physical, mental and

cognitive disorders. In “The Conceptual Evolution of DSM-V” ed Regier

DA et al, American Psychopathological Association 2010