Prevalence of stroke, risk factors, disability and care needs in older adults in Singapore: Results from the WiSE study

Abstract

Objectives
The aims of the present study were to establish the prevalence of stroke, and to explore the association between stroke prevalence and sociodemographic and health factors, disability, cognitive functioning and care needs among older adult residents in Singapore.

Setting
Data were drawn from the Well-being of the Singapore Elderly study—a cross-sectional epidemiological survey conducted from 2012 to 2013 on older adults living in Singapore.

Participants
Participants were Singapore residents (citizens and permanent residents) 60 years and above who were living in Singapore during the survey period . Older adult residents who were institutionalised were also included in this study. Those who were not living in Singapore or who were not contactable were excluded from the study. The response rate was 65.6 % (2565/3913). A total population sample of 2562 participants completed the survey. Participants comprised 43.6% males and 56.4% females. The sample comprised 39.4% Chinese, 29.1% Malay, 30.1% Indian and 1.4% other ethnicities .

Primary and secondary outcome measures
History of stroke, along with other health and mental health conditions, disability and cognitive functioning, were determined by self-report.

Results
Weighted stroke prevalence was 7.6% among older adults aged 60 and above. At a multivariate level, Malay ethnicity (OR 0.41, p=0.012, 95% CI 0.20 to 0.82), hypertension (OR 4.58, p=0.001, 95% CI 1.84 to 11.40), heart trouble (OR 2.45, p=0.006, 95% CI 1.30 to 4.63), diabetes (OR 2.60, p=0.001, 95% CI 1.49 to 4.53) and dementia (OR 3.57, p=0.002, 95% CI 1.57 to 8.12) were associated with stroke prevalence.

Conclusions
Several findings of this study were consistent with previous reports. Given that Singapore’s population is ageing rapidly, our findings may indicate the need to review existing support services for stroke survivors and their caregivers. Future research could investigate the association between various sociodemographic and health conditions and stroke prevalence to confirm some of the findings of this study.

Full text

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TehWL, etal. BMJ Open 2018;8:e020285. doi:10.1136/bmjopen-2017-020285
Open Access
Prevalence of stroke, risk factors,
disability and care needs in older adults
in Singapore: results from the WiSE
study
Wen Lin Teh,1 Edimansyah Abdin,1 Janhavi Ajit Vaingankar,1 Esmond Seow,1
Vathsala Sagayadevan,1 Saleha Shae,1 Shazana Shahwan,1 Yunjue Zhang,1
Siow Ann Chong,1 Li Ling Ng,2 Mythily Subramaniam1
To cite: TehWL, AbdinE,
VaingankarJA, etal. Prevalence
of stroke, risk factors, disability
and care needs in older adults
in Singapore: results from
the WiSE study. BMJ Open
2018;8:e020285. doi:10.1136/
bmjopen-2017-020285
►Prepublication history for
this paper is available online.
To view these les, please visit
the journal online (http:// dx. doi.
org/ 10. 1136/ bmjopen- 2017-
020285).
Received 1 November 2017
Revised 8 February 2018
Accepted 9 February 2018
1Research Division, Institute
of Mental Health, Singapore,
Singapore
2Psychogeriatrics, Changi
General Hospital, Singapore,
Singapore
Correspondence to
MsWen LinTeh;
Wen_ Lin_ TEH@ imh. com. sg
Research
ABSTRACT
Objectives The aims of the present study were to
establish the prevalence of stroke, and to explore
the association between stroke prevalence and
sociodemographic and health factors, disability, cognitive
functioning and care needs among older adult residents in
Singapore.
Setting Data were drawn from the Well-being of
the Singapore Elderly study—a cross-sectional
epidemiological survey conducted from 2012 to 2013 on
older adults living in Singapore.
Participants Participants were Singapore residents
(citizens and permanent residents) 60 years and above
who were living in Singapore during the survey period
. Older adult residents who were institutionalised
were also included in this study. Those who were not
living in Singapore or who were not contactable were
excluded from the study. The response rate was 65.6
% (2565/3913). A total population sample of 2562
participants completed the survey. Participants comprised
43.6% males and 56.4% females. The sample comprised
39.4% Chinese, 29.1% Malay, 30.1% Indian and 1.4%
other ethnicities .
Primary and secondary outcome measures History
of stroke, along with other health and mental health
conditions, disability and cognitive functioning, were
determined by self-report.
Results Weighted stroke prevalence was 7.6% among
older adults aged 60 and above. At a multivariate level,
Malay ethnicity (OR 0.41, p=0.012, 95% CI 0.20 to 0.82),
hypertension (OR 4.58, p=0.001, 95% CI 1.84 to 11.40),
heart trouble (OR 2.45, p=0.006, 95% CI 1.30 to 4.63),
diabetes (OR 2.60, p=0.001, 95% CI 1.49 to 4.53) and
dementia (OR 3.57, p=0.002, 95% CI 1.57 to 8.12) were
associated with stroke prevalence.
Conclusions Several ndings of this study were
consistent with previous reports. Given that Singapore’s
population is ageing rapidly, our ndings may indicate
the need to review existing support services for
stroke survivors and their caregivers. Future research
could investigate the association between various
sociodemographic and health conditions and stroke
prevalence to conrm some of the ndings of this study.
BACKGROUND
Stroke is defined as ‘a neurological deficit
attributed to an acute focal injury of the
central nervous system (CNS) by a vascular
cause’.1 Older age and male gender are
associated with greater stroke risk.2 Health
conditions such as hypertension, cardiovas-
cular diseases and diabetes are established
risk factors of stroke,3 whereas lifestyle factors
such as smoking, alcohol consumption and
obesity are found to contribute to stroke risk,
some of which are dose dependent.4 Depres-
sion and dementia are also found to be asso-
ciated with stroke.5 6
Stroke is one of the leading causes of
disability and disease burden worldwide.7
Despite the global severity of stroke, stroke
prevalence estimates outside Western coun-
tries, especially those from South Asian
or East Asian regions are less readily avail-
able.8 9 Establishing stroke prevalence esti-
mates is important in providing feedback and
planning of stroke rehabilitation and preven-
tion, and stroke data from Asian regions
Strengths and limitations of this study
►This study was based on a large nationwide popula-
tion sample of 2562 older adult participants.
►An extensive list of sociodemographic and health
factors of stroke were accounted for during multi-
variate regression analyses.
►Older adults who were institutionalised were repre-
sented in this study.
►This study examined self-reported stroke which may
be subjected to errors such as false reporting result-
ing in overestimation or underestimation of stroke
prevalence. As this is a cross-sectional study, tem-
poral relationships between stroke and other factors
cannot be established.
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Open Access
provide a basis for comparison against Western estimates
and trends.10
Singapore has a resident population of 3.93 million.11
The population comprises 74.3% Chinese, 13.4% Malay,
9.1% Indian and 3.2% other ethnicities. Singapore’s
population is ageing mainly due to an increase in the life
expectancy—82.7 years in 2015 from 65.8 years in 1970.12
Singapore’s older adult residents (defined as Singapore
citizens and permanent residents aged 65 and above)
constitute 12.4% of the resident population, which is an
increase from 7.2% in the year 2000.11 13 The prevalence of
chronic diseases including stroke is expected to be higher
among this ageing population. Despite its growing impor-
tance and relevance, there exists a paucity of research on
stroke prevalence in Singapore. To our knowledge, only
one study (2005) was found to have reported stroke prev-
alence. In that study, stroke prevalence was found to be
7.67% among adults aged 65 years and above. However,
since the data were collected in 2001–2003, it is unclear at
this current juncture of at least a decade later, how stroke
prevalence has changed in Singapore. Newer estimates
can help to provide a more relevant, up-to-date under-
standing of stroke prevalence in a multiethnic Singapore,
which can be useful in substantiating timely feedback
for local public health policies and also provide a basis
of relevant comparison against Western estimates and
trends.
The aims of the current study were: (1) to establish
the prevalence of stroke among adults aged 60 years
and above in Singapore, (2) to explore the correlation
of stroke with sociodemographic factors and health
conditions and (3) to explore the association of stroke
with disability, cognitive functioning and care needs.
METHODS
This study used data from the Well-being of the Singa-
pore Elderly (WiSE) study which was conducted from
October 2012 to December 2013. Participants provided
written consent to participate in this study.
The overall sample comprised older adult Singapore
residents (Singapore citizens and permanent residents)
aged 60 years and above, who were living in Singapore
at that point in time. Older adult residents who were
institutionalised were also included in this study. Those
who were not living in Singapore or who were not
contactable were excluded from the study.
Sampling was conducted at random using a dispro-
portionate stratified sampling design where the Malays
and Indians, and those aged 75 and above were over-
sampled so as to increase precision of subgroup estima-
tion. To ensure that the results of the WiSE study are
generalisable to the older adult population in Singa-
pore, the results were weighted against the older adult
resident population of 2011 (table 1).
All participants who consented to the study were
administered a series of questionnaires which
comprised questions on sociodemographics, health,
cognition and neurological tests in a single assess-
ment. For each participant, an informant was also
chosen and administered informant-adapted ques-
tionnaires. An informant was defined as the ‘person
who knows the older person best’. Some informants
were caregivers while others were in close contact
with the older person without a caregiving role. The
face-to-face assessments were carried out based on
the participants’ and informants’ preferred language
or dialect, and these interviews were conducted by
trained interviewers. Participants completed the ques-
tionnaires without influence of their informants even
in cases when participants had cognitive deficits. The
questionnaires were valid, reliable and made culturally
relevant for the older adults in Singapore. An earlier
article14 provides further details of the study.
The main questionnaires relevant to this current anal-
ysis were:
Sociodemographic questionnaire: Participants were asked to
provide sociodemographic information such as their age,
gender, ethnicity, education level, and height and weight
measurements.
Stroke and health conditions: Participants were asked if
they had ever been told by a doctor that they had stroke.
Participants were questioned in the same way for other
health conditions such as hypertension, heart trouble
and diabetes. Additionally, they were asked to provide
more details about who diagnosed their health condi-
tion and whether they were still seeking treatment for the
condition.
Smoking: Participants provided a response for the
following question, ‘Has there ever been a period when
you smoked cigarettes, cigars, or a pipe, chewing tobacco,
beedi (Indian cigarette) or snuff nearly every day?’,
responses were binary 0 (no) and 1 (yes) and, ‘Do you
still use tobacco regularly?’, responses were binary 0 (no)
and 1 (yes). Responses for the two questions were then
categorised into 0 (non-smoker), 1 (ex-smoker) and 2
(current smoker).
Alcohol use: Participants provided responses for the
following question, ‘Was there ever a period in your life
when you drank at least 12 drinks in a year?’ Responses
were 0 (never drank alcoholic drinks), 1 (no, less than
12 drinks in a year), 2 (yes, more than 12 drinks a year).
Responses were recoded as 0 (never drank alcoholic
drinks), original responses 1 and 2 were recoded as 1
(yes, ever drank alcoholic drinks).
Body mass index (BMI) and waist–hip ratio (WHR): BMI
was calculated dividing the weight in kilograms with
the square of height in metres. Those with BMI ≥30 kg/
m2 were considered obese.15 WHR is a measurement
of abdominal obesity, measured by a ratio of the waist
circumference to the hip circumference. Men with WHR
greater than 0.90 and women greater than 0.80 were
considered to be obese.15
Geriatric Mental State-Automated Geriatric Examination for
Computer-Assisted Taxonomy (GMS-AGECAT, Depression):
A diagnostic assessment for depression as well as other
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mental illnesses that uses a computerised algorithm
(AGECAT) to make diagnoses. Six levels of severity are
generated from 0 (none) to 5 (severe). A severity level
0 would indicate no depression; levels 1–2 indicate
subsyndromal depression, levels 3–5 indicate AGECAT
depression. For the purpose of this analysis, responses
were recoded as binary responses 0 (levels 0–2), 1 (levels
3 to 5). Inter-rater agreement on depression diagnoses
between AGECAT and psychiatrists’ achieved a kappa
value of 0.88.16
Table 1 Descriptive characteristics of the sample population
Variable Category n
Unweighted
% Weighted % SE
Singapore’s general
population 2011
N (000) %
Age group 60–74 1493 58.3 75.1 0.02 420.5 75.0
75–84 668 26.1 19.4 0.02 109.1 19.5
85+ 401 15.7 5.5 0.01 31.0 5.5
Gender Male 1116 43.6 44.1 1.41 258.9 46.2
Female 1446 56.4 55.9 1.41 301.7 53.8
Ethnicity Chinese 1009 39.4 83.3 0.03 467.0 83.3
Malay 745 29.1 9.3 0.01 52.00 9.3
Indian 772 30.1 6.0 0.02 33.50 6.0
Others 36 1.4 1.4 0.01 8.10 1.4
Education None 510 16.4 0.98
Some, but did not
complete primary
620 24.0 1.21
Completed
primary
639 24.8 1.23
Completed
secondary
517 22.4 1.20
Completed tertiary 262 12.4 0.97
Smoking No 1888 74.5 1.21
Ex-smoker 438 15.9 0.99
Current smoker 236 9.5 0.83
BMI* <30 kg/m2 (not
obese)
1969 91.4 0.75
≥30 kg/m2 (obese) 318 8.6 0.75
WHR† Not obese 401 20.2 1.20
Obese 1924 79.8 1.20
Alcohol drinkers No 1579 48.2 1.40
Yes 983 51.8 1.40
Depression Yes 176 3.7 0.45
No 2386 96.3 0.45
Hypertension No 1010 40.6 1.39
Yes 1549 59.4 1.39
Heart problem No 2106 86.7 0.90
Yes 449 13.3 0.90
Diabetes No 1756 74.5 1.21
Yes 798 25.5 1.21
10/66 dementia No 2021 90.0 0.70
Yes 398 10.0 0.70
*Criteria based on WHO BMI cut-off for obesity.
†Criteria based on WHO WHR cut-off of >0.80 for females, >0.90 for males.
BMI, body mass index; GMS, Geriatric Mental State; WHR, waist–hip ratio. Depression, GMS-AGECAT.
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A cognitive test battery comprising two cognitive tests,
(1) the community screening instrument for dementia
(CSI’D) which incorporated the animal naming verbal
fluency task by the Consortium to Establish a Registry for
Alzheimer’s Dementia (CERAD), and (2) a 10-word-list
learning task with delayed recall by CERAD (modified).
An aggregated cognitive score called the COGSCORE was
generated by taking the summation of all item-weighted
scores of the entire cognitive test battery.
10/66 dementia: A 10/66 dementia diagnosis was
given to older adults based on a cut-off determined by
logistic regression coefficients of CSI’D COGSCORE,
RELSCORE (unweighted total informant score of func-
tional and cognitive decline in the older adult), GMS/
AGECAT, and the modified CERAD. A cut-off of more
than 0.25 was used as it produced the best sensitivity and
specificity to identify dementia cases.17 Validation of the
10/66 diagnosis revealed that it had a substantial agree-
ment with clinician diagnosis in the WiSE study.14
WHO-Disability Assessment Schedule (WHO-DAS) 2.0: It is a
12-item questionnaire which assesses 6 domains of func-
tioning in cognition, mobility, self-care, getting along, life
activities and participation. Item responses range from 0
(no difficulty) to 4 (extremely difficulty or cannot do). A
total WHO-DAS score is calculated by the summation of
the domain scores.
Care need: Defined as the amount of care needed by the
older person that is provided by the informant. Infor-
mants were asked to respond to whether: the older person
needs care much of the time (1), needs care occasionally
(2), does not need care; they are able to do everything for
themselves (3).
Statistical analysis
Statistical analyses were carried out using the SAS system
V.9.3. All of the statistical analyses used in this study were
based on weighted data. First, simple logistic regression
was used to analyse the correlates of stroke prevalence at
a univariate level. Second, multiple logistic regression was
used to analyse sociodemographic and health correlates
of stroke at a multivariate level. Sociodemographic
factors such as age group, gender, ethnicity, education
and health or lifestyle conditions such as hypertension,
heart trouble, diabetes, smoking, alcohol use, depression
and dementia were used as predictors in both regression
analyses. Associations with cognitive and disability scores
were estimated using multiple linear regressions, while
association with care needs was estimated using multino-
mial logistic regression after accounting for covariates.
Missing answers were deleted listwise. Statistical signifi-
cance was set at a conventional cut-off point at p<0.05,
two tailed.
The target sample size was determined by a power
calculation for binary proportions. After adjusting
for design effect for the overall prevalence estimate,
subgroups by age and ethnicity with the precision of 5%,
it was estimated that a sample size of 2500 was sufficient
in providing adequate precision.14
RESULTS
The characteristics of the sample population are
summarised in table 1. The overall response rate was 65.6
% (2565/3913) . In all, 2562 participants were included
in the current analysis (3 missing answers were removed
listwise). The mean age was approximately 70 years
old (M=69.9, SD=7.84). Participants comprised 44.1%
males and 55.9% females. The sample comprised 83.3%
Chinese, 9.3% Malay, 6% Indian and other ethnicities
1.4%.
Out of 2562 older adult participants, 199 respondents
reported that they had ever been told by a doctor to have
had stroke. The overall weighted stroke prevalence was
7.6%, (95% CI 6.2% to 9.0%) among older adult residents
aged 60 years and above. Weighted stroke prevalence for
those aged 65 years and above was 9.3%. A detailed break-
down of the prevalence of stroke by sociodemographic
and health variables are presented in table 2.
Sociodemographic and health correlates of stroke
Simple logistic regression revealed that sociodemographic
features such as older age, no education, ex-smokers
were associated with higher stroke prevalence (p<0.05).
Stroke was 2.4 times higher in the 75–84 age group, and
three times higher in the above 85 years old age group
as compared with the younger age group 60–74. Stroke
was three times higher in those who self-reported no
education than those who had completed tertiary educa-
tion. Stroke was two times higher among ex-smokers than
those who had never smoked. Malay ethnicity was asso-
ciated with lower stroke prevalence (p<0.05), having 0.6
times lower odds of having stroke as compared to Chinese
ethnicity.
Health conditions such as hypertension, heart trouble,
diabetes, and dementia significantly predicted stroke
prevalence (p<0.001) at the univariate level. Stroke was
higher among those who self-reported having hyperten-
sion (4.5 times), heart trouble (4.3 times), diabetes (2.7
times) and dementia (8 times) as compared with those
without the respective health conditions. Gender, obesity
(BMI and WHR), alcohol consumption and depression
were not associated with stroke in this study.
Multivariate logistic regression revealed that only hyper-
tension, heart trouble, diabetes and 10/66 dementia were
independently associated with higher stroke prevalence
(p<0.05). At the multivariate level, stroke was higher
among those with self-reported hypertension (4.6 times),
heart trouble (2.5 times), diabetes (2.6 times) and 10/66
dementia (3.6 times) as compared with those without
the respective health conditions. Ethnic differences
maintained significance at the multivariate level—ethnic
Malays had significantly lower odds (OR=0.4) of stroke
when compared with ethnic Chinese. There was no signif-
icant difference in stroke prevalence between those of
Indian and Chinese ethnicities.
Age group, gender, education, depression and other life-
style (smoking, alcohol, BMI and WHR) conditions were not
associated with stroke prevalence (p>0.05) at a multivariate
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level. The complete results of the sociodemographic and
health correlates of stroke are presented in table 3.
Cognition, disability and care needs correlates of stroke
After adjusting for sociodemographic and health covari-
ates in multiple linear regression analyses, stroke was
negatively associated with cognitive scores (β=−1.15,
p=0.011) and positively associated with disability scores
(β=9.01, p<0.001). This meant that respondents with
stroke were associated with greater cognitive deficits as
well as greater physical disabilities.
After adjusting for covariates in multinomial
logistic regression analysis, stroke and care needs
Table 2 Number of stroke and non-stroke cases by sociodemographic and health factors
Variable Category
Without stroke Stroke
n % SE n % SE
Age group 60–74 1415 94.3 0.8 78 5.7 0.8
75–84 599 87.4 1.8 69 12.6 1.8
85+ 349 84.5 2.4 52 15.5 2.4
Gender Male 1033 92 1.1 83 8 1.1
Female 1330 92.7 0.9 116 7.3 0.9
Ethnicity Chinese 913 92.2 0.8 96 7.8 0.8
Malay 704 94.9 0.9 41 5.1 0.9
Indian 715 93.7 0.9 57 6.3 0.9
Others 31 85.6 6.1 5 14.4 6.1
Education None 455 87.8 2.1 55 12.2 2.1
Some, but did not
complete primary
566 91.8 1.5 54 8.2 1.5
Completed
primary
596 93.4 1.4 43 6.6 1.4
Completed
secondary
485 93.7 1.4 32 6.3 1.4
Completed
tertiary
249 95.5 1.7 13 4.5 1.7
Smoking No 1749 93.2 0.8 139 6.8 0.8
Ex-smoker 393 87.7 2.2 45 12.3 2.2
Current smoker 221 93.8 2.2 15 6.2 2.2
BMI* <30 kg/m2 (not
obese)
1850 94.1 0.7 119 5.9 0.7
≥30 kg/m2 (obese) 304 94.1 2.3 14 5.9 2.3
WHR† Not obese 382 96 1.2 19 4 1.2
Obese 1809 93.5 0.8 115 6.5 0.8
Alcohol
drinkers
No 1451 91.4 1.1 128 8.6 1.1
Yes 912 93.3 1 71 6.7 1
Depression Yes 156 86.7 4.5 20 13.3 4.5
No 2207 92.6 0.7 179 7.4 0.7
Hypertension No 972 97.3 0.7 38 2.7 0.7
Yes 1388 89 1.1 161 11 1.1
Heart problem No 1981 94.4 0.7 125 5.6 0.7
Yes 377 79.8 2.9 72 20.2 2.9
Diabetes No 1657 94.5 0.7 99 5.5 0.7
Yes 699 86.3 1.8 99 13.7 1.8
10/66
dementia
No 1913 94.9 0.7 108 5.1 0.7
Yes 214 69.7 3.7 84 30.3 3.7
*Criteria based on WHO BMI cut-off for obesity.
†Criteria based on WHO WHR cut-off of >0.80 for females, >0.90 formales.
BMI, body mass index; WHR, waist–hip ratio; Depression, GMS-AGECAT.
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were found to be positively associated (p<0.001).
Among older adults with stroke, there was a 4 and
10 times increase in the odds of needing care ‘occa-
sionally’ and ‘much of the time’, respectively, when
compared with those without stroke The results of
the correlates of stroke with cognitive, disability
scores and care needs are presented together in
table 4.
Table 3 Sociodemographic and health correlates of stroke
Variable Categories
Simple logistic regression Multiple logistic regression
OR
95% Wald
CI P values OR
95% Wald
CI P values
Age group 60–74 Reference Reference
75–84 2.38 1.54 to 3.69 <0.001 1.23 0.67 to 2.25 0.498
85+ 3.04 1.90 to 4.87 <0.001 0.79 0.31 to 2.02 0.627
Gender Male Reference Reference
Female 0.91 0.61 to 1.37 0.657 0.73 0.37 to 1.42 0.347
Ethnicity Chinese Reference Reference
Malay 0.63 0.41 to 0.96 0.030 0.41 0.20 to 0.82 0.012
Indian 0.79 0.55 to 1.15 0.217 0.61 0.33 to 1.11 0.103
Others 1.98 0.74 to 5.36 0.176 2.71 0.81 to 9.13 0.107
Education None 2.94 1.22 to 7.09 0.017 1.24 0.38 to 4.04 0.725
Some, but did
not complete
primary
1.89 0.78 to 4.58 0.161 1.23 0.39 to 3.90 0.720
Completed
primary
1.50 0.60 to 3.74 0.388 1.66 0.49 to 5.69 0.418
Completed
secondary
1.43 0.57 to 3.62 0.447 1.30 0.42 to 4.10 0.651
Completed
tertiary
Reference Reference
Smoking Non-smoker Reference Reference
Ex-smoker 1.94 1.22 to 3.10 0.006 1.75 0.80 to 3.82 0.160
Current smoker 0.92 0.42 to 2.03 0.830 1.15 0.44 to 2.98 0.774
BMI* <30 kg/m2 (not
obese)
Reference Reference
≥30 kg/m2 (obese) 1.00 0.43 to 2.32 0.996 1.17 0.44 to 3.13 0.757
WHR† Not obese Reference Reference
Obese 1.67 0.84 to 3.33 0.143 1.24 0.57 to 2.69 0.590
Alcohol drinkers No Reference Reference
Yes 0.77 0.51 to 1.15 0.201 0.56 0.30 to 1.06 0.076
Depression No Reference Reference
Yes 1.92 0.87 to 4.26 0.109 0.76 0.21 to 2.84 0.687
Hypertension No Reference Reference
Yes 4.52 2.55 to 8.00 <0.001 4.58 1.84 to 11.40 0.001
Heart trouble No Reference Reference
Yes 4.25 2.75 to 6.58 <0.001 2.45 1.30 to 4.63 0.006
Diabetes No Reference Reference
Yes 2.72 1.80 to 4.12 <0.001 2.60 1.49 to 4.53 0.001
10/66 Dementia No Reference Reference
Yes 8.06 5.19 to 12.52 <0.001 3.57 1.57 to 8.12 0.002
*Criteria based on WHO BMI cut-off for obesity.
†Criteria based on WHO WHR cut-off of >0.80 for females, >0.90 for males.
BMI, body mass index; WHR, waist–hip ratio; Depression, GMS AGECAT.
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DISCUSSION
Stroke prevalence
The weighted stroke prevalence found in this study was
7.6% among the older adults aged 60 and above. In an
earlier population-based study that was conducted in
Singapore in the year 2001–2003, stroke prevalence
among older adults aged 65 and above was found to be
7.7%.18 For the purpose of comparison, weighted stroke
prevalence among those 65 years and above was found to
be 9.3% in this study, which was higher as compared with
the figures reported by the earlier study.18
Stroke prevalence found in this study was comparable
to the figures reported in Western populations, such as
8.3% in the USA among older adults 65 years and above.19
However, the figures were higher than that reported in
several non-Western ageing populations, such as 4.5% in
Korea,20 4.9% in Hong Kong21 and 2.7% in Thailand22
among older adults aged 65 years and above.
In the previous study, stroke prevalence among the
three major ethnic groups (Chinese, Malay, Indian) was
found to range from 3.32% to 3.75%.18 Chinese ranked
the highest in prevalence, followed by Indian and Malay
ethnicities. While the ranking remained the same in this
study, there was an increase in stroke prevalence across
all three ethnic groups, ranging from 5.1% to 7.8%.
While the previous study did not find ethnic differences
in stroke prevalence, the WiSE study found significant
differences between the Chinese and Malay ethnicities
with ethnic Malays having significantly lower stroke prev-
alence as compared with ethnic Chinese. These results
were unexpected because according to the National
Health Survey (2010), Malay ethnicity has been associ-
ated with various stroke risk factors such as hypertension
and obesity.23 There appears to be no clear explanations
for our findings, however, as it was previously reported
that ethnic minority groups, such as Malays, have a lower
tendency of self-rating poor health,24 it is possible that
either they did not want to mention being diagnosed,
they were not diagnosed or did not remember being
diagnosed with stroke. Additionally, according to the
Singapore’s census population statistics (2010), it has
been reported that those belonging to the Malay ethnic
group have the lowest median household income.25 Thus,
it could be possible that they have fewer opportunities to
be informed about their health, which could also explain
the lower self-reported stroke. As stroke prevalence data
in Singapore is scarce, comparisons with past studies are
insufficient, thereby making it difficult to draw sound
conclusions. Future research could take into account any
administrative data or registries to draw clearer outcomes
on ethnic differences in stroke epidemiology.
Sociodemographic correlates of stroke
Age was significantly associated with stroke prevalence at
a univariate level, a finding that was consistent with past
research.18 26 After controlling for sociodemographic and
health conditions, however, the association disappeared.
These findings were consistent with an earlier study that
examined stroke risk factors and stroke prevalence among
Thai adults aged 45–80 years, where older age was not
associated with higher stroke prevalence after all other
factors were considered.22 Unexpectedly, gender was not
associated with stroke prevalence in this study and it is
unclear why this is so.
Biological changes that come with old age may affect
existing age/gender association with stroke risk factors,
which in turn may contribute to the lack of association
between age/gender and stroke prevalence. Hypertension,
diabetes and cardiovascular complications usually arise with
increasing age. For instance, increased high blood pressure
is greatly attributed to the changes to the cardiovascular
system, structure of arteries and large artery stiffness that
come with age.27 28 Cardiovascular problems and diabetes are
usually associated with thesedentary lifestyle of old age.29 30
By the age of 60–69 years, women have a higher risk of devel-
oping hypertension due to menopause.31 However, research
has also shown that certain health conditions become less
prevalent with increasing age. In one study, existing age/
Table 4 Relationship between stroke and cognitive, WHO-DAS, and care needs scores
Cognitive and
disability scores
Without stroke With stroke
B* SE P values 95% CIn Mean SE n Mean SE
Cognitive score
(COGSCORE)
2363 28.6 0.09 199 22.6 0.91 −1.15 0.45 0.011 −2.04 to −0.27
WHO-DAS 2363 8.70 0.36 199 37.0 3.26 9.01 2.07 <0.001 4.96 to 13.07
n % SE n % SE OR† SE P values 95% CI
Needs care much
of the time
237 57.7 4.40 92 42.3 4.40 10.1 0.43 <0.001 4.35 to 23.31
Needs care
occasionally
320 84.3 3.11 43 15.7 3.11 4.09 0.40 <0.001 1.86 to 9.01
Does not need care 1670 96.5 0.61 57 3.50 0.61 Reference
*B coefcient derived from multiple linear regression analysis after adjusting for sociodemographic and health covariates.
†OR derived from multinomial logistic regression analyses after adjusting for sociodemographic and health covariates.
WHO-DAS, WHO-Disability Assessment Schedule.
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8TehWL, etal. BMJ Open 2018;8:e020285. doi:10.1136/bmjopen-2017-020285
Open Access
gender associations with several stroke risk factors tend to
diminish or change among older age groups (70–80 years)
and especially for men.32 Our findings suggest that health
complications that come with age and gender may have
been better predictors of stroke prevalence among older
adults in this study.
Health correlates of stroke
The WiSE study found that hypertension, heart trouble
and diabetes were independently associated with stroke
prevalence. These findings were expected since these
health conditions are established determinants of stroke.3
Stroke was also associated with 10/66 dementia, which is
also an expected finding since stroke and Alzheimer’s
disease have various overlapping risk characteristics.17 33
Obesity was not associated with stroke prevalence.
While it was not unexpected that there was no association
between BMI and stroke risk, WHR was an unexpected
finding since WHR was found to be a stronger predictor
of stroke risk than BMI.34 35 Our findings, however, were
similar to the aforementioned study among Thai older
adults. In both studies, BMI was not a significant predictor
at a univariate level and WHR did not independently
predict stroke prevalence at a multivariate level.22 Having
ever smoked (current and ex-smokers) and alcohol
consumption were not associated with stroke prevalence
among older adult residents. These results were unantic-
ipated, however, as research has shown that these factors
are dose dependent,36–39 it could be possible that the
sample of older adult respondents in this study were not
heavy smokers and did not consume alcohol excessively.
Stroke prevalence was not associated with depression
in this study. Our finding differed from several other
existing studies and meta-analyses which found other-
wise.5 40 Although meta-analyses have shown a positive
association, majority of the studies included in these
meta-analyses did not take into account stroke risk factors
such as BMI or alcohol use.41 The results of this study
were consistent with at least one prospective study which
found that depression was not associated with stroke
risk among older adults, after adequately controlling for
covariates.42 43 Taken together, depression did not appear
to be a relevant risk factor of stroke in older adults.
Stroke, disability and care need
As expected, stroke was found to be associated with low
cognitive and high disability scores. Stroke is among the
top three leading cause of disability among older adults
aged 65 years and above in Singapore and involves long-
term dependency on healthcare services.44 Despite the
severity of stroke disability, a substantial number of stroke
patients tend not go for poststroke therapy citing high
financial costs, inconvenience and lack of interest.45
Our study revealed stroke to be associated with greater
care needs. In Singapore, given that close to 95% of older
adult residents stay with family members46 and that age-re-
lated diseases will rise in view of the ageing population in
Singapore, it is expected that there will be a substantial
increase in burden and reliance on family members for
their daily needs if disabled. These findings, thus, indi-
cate the need to extend and improve on existing services
to stroke survivors and to caregivers.
This study has some limitations, with foremost the nature
of self-reported stroke which may be subjected to errors such
as false reporting resulting in overestimation or underestima-
tion of stroke prevalence. However, most population-based
prevalence studies use self-report for ease of administration,
cost-effectiveness and for direct comparison with the majority
of studies which used similar methods. Third, as this is a
cross-sectional study, temporal relationships between stroke
and other factors cannot be established.
Future research should take into consideration the
importance of establishing stroke incidence to provide
a well-informed understanding of stroke epidemiology
in Singapore. Published research articles on stroke inci-
dence in Singapore are rare—the most recent study was
published in the year 2000.47 In Adelaide, possibly owing
to advances in healthcare intervention and public initia-
tives, stroke incidence rates have declined despite an
ageing population.48 49 At the present juncture, it remains
unclear whether recent incidence estimates of stroke have
increased or decreased in Singapore relative to past data
and worldwide.
CONCLUSION
The prevalence of stroke survivors in Singapore is rela-
tively high when compared with other Asian countries. Our
findings provide support for the existing body of research
on stroke prevalence and its correlates. Given that Singa-
pore’s population is ageing rapidly, our findings may indi-
cate a need to review existing support services for stroke
survivors and their caregivers. Finally, future research could
take into consideration incidence rates for more relevant
understanding of stroke epidemiology in Singapore, and
also investigate the role of gender, ethnicity and lifestyle risk
factors such as smoking, alcohol use and obesity on stroke
prevalence to confirm the findings of this study.
Contributors WLT wrote the rst draft of the manuscript. EA provided statistical
analysis. JAV, ELSS, VS, SShae, SShahwan and YJZ were involved in data
collection and literature review searches. MS and SAC wrote the protocol and
designed the study. LLN provided intellectual input in the area of data collection and
analyses. All authors contributed and approved the nal manuscript.
Funding The study was funded by the Ministry of Health, Singapore and the
Singapore Millennium Foundation of the Temasek Trust.
Competing interests None declared.
Patient consent Obtained.
Ethics approval National Healthcare Group Domain Specic Review Board and the
SingHealth Centralised Institutional Review Board.
Provenance and peer review Not commissioned; externally peer reviewed.
Data sharing statement Data are not available for online access; however,
readers who wish to gain access to the data can write to the senior author (MS)
at mythily@ imh. com. sg with their requests. Access can be granted and subjected
to the Institutional Review Board (IRB) and the research collaborative agreement
guidelines. This is a requirement mandated for this research study by our IRB and
funders.
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9
TehWL, etal. BMJ Open 2018;8:e020285. doi:10.1136/bmjopen-2017-020285
Open Access
Open Access This is an Open Access article distributed in accordance with the
Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which
permits others to distribute, remix, adapt, build upon this work non-commercially,
and license their derivative works on different terms, provided the original work is
properly cited and the use is non-commercial. See: http:// creativecommons. org/
licenses/ by- nc/ 4. 0/
© Article author(s) (or their employer(s) unless otherwise stated in the text of the
article) 2018. All rights reserved. No commercial use is permitted unless otherwise
expressly granted.
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results from the WiSE study
and care needs in older adults in Singapore:
Prevalence of stroke, risk factors, disability
Yunjue Zhang, Siow Ann Chong, Li Ling Ng and Mythily Subramaniam
Seow, Vathsala Sagayadevan, Saleha Shafie, Shazana Shahwan,
Wen Lin Teh, Edimansyah Abdin, Janhavi Ajit Vaingankar, Esmond
doi: 10.1136/bmjopen-2017-020285
2018 8: BMJ Open
http://bmjopen.bmj.com/content/8/3/e020285
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