Why was the cohort set up?
During the past century, there have been dramatic improvements in life expectancy
in Taiwan, with the average life span increasing from 30.0 and 32.1 years for men
and women in 1908 to 77 and 83.5 years in 2016, respectively.
1
As a consequence of this demographic transition, the population in Taiwan has rapidly
been ageing. Currently, persons aged 65 and older comprise about 12.5% of the Taiwanese
population; this proportion is projected to reach 14% in 2018 and 20% in 2025.
2
With the ageing of a population comes an increase in prevalence of chronic diseases
and geriatric syndromes, and an expansion in healthcare costs that impose a huge burden
on the whole society.
3
For example, cancer, coronary heart disease, stroke, diabetes, hypertension and chronic
kidney disease have been listed among the 10 leading causes of death among the elderly
in Taiwan for the past decade.
4
The high prevalence of chronic kidney disease in the elderly (estimated to be over
37%
5
) is another example indicating that an ageing population is one of the most important
factors behind the high incidence and prevalence of end-stage renal disease (ESRD)
in Taiwan.
6
Thus, it is essential to understand more about risk factors attributable to the ethnicity-specific
ageing process so that effective prevention programmes can be developed for the elderly.
To address different age-related health issues, several longitudinal Chinese ageing
studies have previously been conducted in Taiwan or other Asian countries, such as
the Chinese Longitudinal Health Longevity Survey (CLHLS),
7
the China Health & Retirement Longitudinal Study (CHARLS),
8
the Beijing Longitudinal Study of Aging (BLSA),
9
the Taiwan Longitudinal Study of Aging (TLSA)
10
and the Singapore Chinese Longitudinal Aging Study.
11
However, most of these established senescent cohorts, which were mainly followed up
by collecting self-reported information, had not acquired comprehensive biomedical
profiles for their participants. To further understand determinants of healthy longevity
and geriatric issues, additional functional status measurements and biochemical data
collections have been appended to some sub-studies
7
,
8
,
12
but their sample sizes were far smaller compared with their original cohorts. For
example, lack of statistical power (n = 639) is one of major limitations of the Social
Environment and Biomarkers of Aging Study (SEBAS),
12
a sub-study of the TLSA, in spite of its enrichment with biochemical, genetic and
functional measurements. To overcome the common barriers in geriatric cohort research,
the Healthy Aging Longitudinal Study in Taiwan (HALST) was therefore established and
funded by the National Health Research Institutes in Taiwan to address issues related
to healthy ageing (ClinicalTrials.gov: NCT02677831).
The main study objectives of the HALST are to investigate: (i) factors that may influence
trajectories of physical functioning; (ii) impacts of healthy lifestyles on incidence
of chronic diseases, quality of life and mortality; (iii) individual, social and environmental
determinants of cardiovascular diseases; (iv) association of neuropsychiatric risk
factors and well-being; and (v) interaction between genetic traits and environmental
risk factors in frailty versus successful ageing processes in older adults. The project
also involves a variety of ancillary sub-studies focusing on important health-related
issues that are unique to local people (such as betel quid chewing, dietary pattern,
hepatitis due to viral infection and chronic renal disease). These issues are frequently
overlooked but are crucial for the development of health-promotion programmes in older
populations.
Who is in the cohort?
The HALST is designed as a longitudinal study recruiting community-dwellers aged 55
and above in seven selected areas in Taiwan: two in the north (Shilin District and
Yangmei Township), two in the central region (Miaoli City and Changhua City), two
in the south (Puzi Township and Lingya District) and one in the east (Hualien). These
seven locations (Figure 1) cover both urban and rural areas, as well as different
ethnic groups speaking different dialects, representing the diverse socio-demographic
characteristics of the Taiwanese population. In each catchment area, a regional hospital
was selected to be the medical facility for clinical examinations, and all eligible
residents living within about a 2-km radius of this local hospital were ascertained
from the household registry archives. By using a systemic sampling method, beginning
with around 3000–3500 residents aged 55 and above in each catchment area, we created
a recruitment roster within the target population. To ensure that our study sample
covered a sufficient number of the elderly with different socio-demographic backgrounds,
the older adults (≥ 65 years of age) were over-sampled (70% for those ≥ 65 years and
30% for those in 55–64 years); on the other hand, the sampling distributions of gender
and educational level (none, primary school, high school and above) are based on the
demographic distribution within a li (village), a basic house registration unit defined
by the Taiwan government. Individuals with any of the following conditions at the
recruiting interview were excluded: highly contagious infectious diseases (including
scabies and open tuberculosis), severe illnesses (including cancer under treatment),
physician-diagnosed dementia, bedridden and/or too frail to stand and walk, severe
mental disorder or cognitive impairment with a Mini-Mental Status Score < 16,
13
mental retardation or severe hearing loss. Individuals who were then hospitalized
or institutionalized were also excluded. Figure 2 presents a flow chart with details
of the subject selection process and the number of participants who completed the
first annual follow-up telephone interview. Compared with the recruited subjects,
the non-participants were more likely to be women, older and illiterate. In the first-wave
survey (2009–13), we enrolled 5664 community-dwellers aged 55 or above.
Figure 1.
Map of participating sites in the HALST.
Figure 2.
Selection flow chart for the HALST participants.
How often have they been followed up?
The longitudinal assessments conducted in the HALST consist of home interviews and
hospital-based clinical examinations every 5 years. The first-wave survey (recruitment
and baseline survey) was carried out in 2009–13. The field study team took about 6–8
months to finish the work in one catchment area, starting in Miaoli City and then
moving to the next (Shilin District was the last) for the processes of recruitment,
interview and examination. The second-wave follow-up (2014–19) of home interviews
and examinations is currently under way. After enrolment, those who have completed
both home interviews and hospital-based examinations (n = 5349) are to be followed
up by telephone contact every year for updates on vital status and health-related
conditions.
What has been measured?
In the sampling area of each site, community residents who met the inclusion criteria
were invited to participate in the HALST study. A home interview was arranged for
those who completed the consent form. Within 2 weeks after the home visit, study participants
received a physical examination and provided morning spot urine and up to 30 ml of
fasting blood specimens in one of the local hospitals. The home interview took about
90 to 120 min to complete; and the clinical examination required about 120 min. All
interviewing and examination processes are based on the standardized manual of operation;
the field sites are periodically inspected by the responsible investigators every
season; and a routine call-back interview for quality and reliability control is performed
for around 8% of the enrolled subjects by random selection.
As seen in Table 1, information obtained through the measurements and analyses employed
in the HALST can be organized into four parts: home visit, clinical examination, laboratory
analysis and follow-up telephone survey. ‘Home visit’ and ‘clinical examination’,
including blood and urine samples collection, constitute the formal investigation
conducted every 5 years; ‘follow-up telephone survey’ is the annual survey of vital
status and new health events occurring between formal home visit and clinical examination.
The main measures are aimed at collecting information on physical function and geriatric
conditions (e.g. lifestyle profiles, cardiovascular diseases, cognitive and mental
health and longevity-related genetic factors) necessary for our research interests.
In addition, the design of measures and instruments is mainly based on three practical
considerations: (i) our results could be compared with those from well-recognized
ageing-related studies, such as the Chicago Healthy Aging Study and Baltimore Longitudinal
Study of Aging; (ii) the instruments have been used in similar population-based studies
in ethnic Chinese communities; and (iii) the Chinese-language version questionnaires
were chosen from those validated and widely recognized for use in community-based
studies such as assessments of leisure time physical activity,
14
the Chinese version of Lawton and Brody’s measure
15
for instrumental activities of daily living (IADLs),
16
the Mini-Mental State Exam (MMSE),
17
the Center for Epidemiologic Studies Depression Scale (CES-D)
18
and the Short-Form 12 Health Survey (SF-12).
19
,
20
The food intakes were measured from a food frequency questionnaire (FFQ) containing
more than 80 items of Chinese food. The validation of this FFQ has been reported elsewhere.
21
Specifically, we show participants wooden blocks representing the volume of the food
to approximately measure for each food item; then the frequency and the volume are
converted accordingly. The final results are the amount consumed per day.
Table 1.
Measurements in the Healthy Aging Longitudinal Study in Taiwan (HALST)
Type
Measures
Instruments
Interviewer-administered home visit
Questionnaires
Physical functioning
Barthel Index, Lawton-Brody IADL Scale
Frailty
CHS frailty phenotype, the Edmonton frail scale, CSHA-CFA, SOF
Cognitive function
MMSE
Mental health
20-item CES-D
Health-related quality of life
SF-12
Diet assessment
FFQ
Others: evaluation of general conditions, social demography, health conditions, geriatric
conditions (fall, pain), chronic disease risk factor, sleep, use of healthcare, lifestyle
(smoking, alcohol, betel, physical activity, nutritional supplements) and family history
of chronic diseases
Physical assessment
Performance-based measures
Peak flow test, grip strength, SPPB
Clinical examination
Examinations
Anthropometry
Height and weight, and hip circumference
Brief physical examination
Lower extremity function
Single-leg stand test, timed up-and-go test, 6-min walk
Cardiovascular function
Blood pressure, heart rate, electrocardiogram, ankle-brachial index measurement, heart
rate variability
Cognitive function
Digit symbol substitution test, clock drawing test
Vision
Visual acuity
Mental health
PRIME-MD
Questionnaires
Clinical assessment of cardiovascular symptoms
Rose questionnaire, TIA questionnaire
Other: vision, hearing, incontinence
Laboratory analysis
Blood tests
Routine biochemistry
Cholesterol, triglyceride, HDLC, LDLC, globulin, albumin, total protein, AST, ALT,
GGT, insulin, glucose, creatinine, BUN, uric acid
Haematology
HbA1c, complete blood count (RBC, WBC, platelet), haemoglobin, HCT, MCV, MCH, MCHC,
differential count of WBC
Inflammation-related
High-sensitivity CRP (hsCRP), intact PTH, ionized calcium, vitamin B12, folic acid
Hepatitis virus titre
HBsAg, Anti-HCVAb
Coagulation factor
D-dimer, fibrinogen
DNA
Genes associated with ageing (SNPs)
Other
IL-6, TNF-R1, IGF-1, sIL-6r, vitamin D
Urine test
Routine urinalysis
Colour, clarity, specific gravity, pH, glucose, protein, occult blood, urobilinogen,
bilirubin, nitrite, ketone body, RBC, WBC, epithelial cells, casts, crystals, bacteria,
parasites, urinary albumin, urine creatinine, leukocyte esterase
Follow-up telephone questionnaire
Questionnaires
Self-rated health status, physical functioning, pain, weight changes, smoking, physical
activity, vision, falls and fractures, depressive symptoms, new events and health
conditions, specific examinations and surgeries
BSRS-5
IADL, Instrumental Activity of Daily Living; CHS, Cardiovascular Health Study; CSHA-CFA,
Chinese-Canadian Study of Health and Ageing Clinical Frailty scale physical version;
SOF, Study of Osteoporotic Fractures; MMSE, Mini-Mental State Examination; CES-D,
Center for the Epidemiologic Studies Depression Scale; SF-12, Short Form 12; FFQ,
Food Frequency Questionnaire; SPPB, Short Physical Performance Battery; PRIME-MD,
Primary Care Evaluation of Mental Disorders; TIA, transient ischaemic attack; HDLC,
high-density lipoprotein cholesterol; LDLC, low-density lipoprotein cholesterol; AST,
aspartate aminotransferase; ALT, alanine aminotransferase; GGT, gamma-glutamyl transpeptidase;
BUN, blood urea nitrogen; HbA1c, glycated haemoglobin; RBC, red blood cells; WBC,
white blood cells; HCT, haematocrit; MCV, mean cell volume; MCH, mean corpuscular
haemoglobin; MCHC, mean corpuscular haemoglobin concentration; CRP, C-reactive protein;
PTH, parathyroid hormone; HBsAg, hepatitis B surface antigen; Anti-HCVAb, anti-hepatitis
C virus antibody; IL-6, interleukin-6; TNF-R1, tumour necrosis factor-R1; IGF-1, insulin-like
growth factor-1; SNPs, single nucleotide polymorphisms; sIL-6r, soluble interleukin-6
receptor; BSRS-5, Brief Symptom Rating Scale-5.
For the laboratory analysis, routine fasting blood and morning urine tests are analysed
at a certified clinical laboratory. In addition to the routine standardization and
calibration tests performed by the laboratory, duplicate samples for about 5% of the
specimens blinded to the laboratory are submitted together with other control samples
to test reliability. We created three different levels (high, medium and low) of serum
pools from control samples to assess accuracy of the assays operated by the central
laboratory. All the remaining blood is centrifuged, aliquoted and stored in a -80°C
freezer at the National Health Research Institutes, where other blood tests—including
inflammatory markers, blood clotting markers, hepatitis B and hepatitis C markers
and genetic assays—are undertaken in the principal investigators’ laboratories. The
results of annual validity and reliability tests regarding between-run and within-run
quality control of some major laboratory items are acceptable.
In addition to the measures set in the routine investigations, a number of measures
in relation to our main research interests are also conducted through ancillary sub-studies
by collaborative researchers. For example, to better understand the relationship between
bone/muscle mass and older adults’ health, examinations of bone mineral density and
whole body scan using dual-energy X-ray absorptiometry were carried out at the Puzi,
Changhua and Hualien sites.
In addition to the home interviews and hospital-based examinations which are conducted
every 5 years, we also perform annual telephone contact to update participants’ health
conditions such as changes in body weight, lifestyle behaviours, newly diagnosed diseases
and conditions and new events of fall and fall-induced fractures and hospitalizations.
To ascertain mortality and cause of death, we link the identification number of the
HALST participants to the National Death Registry Database on a yearly basis. Similarly,
medical records are requested for the ascertainment of any hospitalized events. In
addition, we also assess health outcomes, healthcare utilization and medical costs
from the National Health Insurance database (NHID) for those who have signed an informed
consent (n = 5152, 91%) for the data linkage.
What has been found? Key findings and publications
Table 2 shows some selected baseline socio-demographic characteristics by different
age groups. Women outnumbered men for those younger than 75. The prevalence of widowhood
increased with older ages. The percentages of self-identified ‘mainlanders’ (immigrants
from China) and no education were the highest (20.0% and 24.6%, respectively) in the
oldest group. As regards lifestyle characteristics, about 13% of the study participants
were current smokers and 3% were betel-quid chewers. The prevalence of these risky
behaviours declined as the participants became older. The percentage in each age group
that engaged in leisure-time physical activity was about the same (around 71%). With
regard to the self-reported major cardiovascular diseases (such as heart disease and
stroke) and some age-related conditions (such as cataract, arthritis and prostatic
disorders in males), the prevalence generally increased with age.
Table 2.
Numbers of study subjects in the HALST cohort presenting with selected socio-demographic
characteristics (and percentages in parentheses) and reported health conditions
Total (n = 5664)
55–64 years (n = 1686)
65–74 years (n = 2497)
≥ 75 years (n = 1481)
P
Sex
0.001
Male
2676 (47.2)
800 (47.4)
1121 (44.9)
755 (51.0)
Female
2988 (52.8)
886 (52.6)
1376 (55.1)
726 (49.0)
Marital status
< 0.001
Married
4140 (73.1)
1428 (84.7)
1823 (73.0)
889 (60.0)
Widowed
1235 (21.8)
121 (7.2)
570 (22.8)
544 (36.7)
Other
a
289 (5.1)
137 (8.1)
104 (4.2)
48 (3.2)
Ethnicity
b
< 0.001
Fukien
3326 (58.8)
1017 (60.4)
1573 (63.0)
736 (49.8)
Hakka
1638 (28.9)
475 (28.2)
746 (29.9)
417 (28.2)
Mainlander
574 (10.1)
157 (9.3)
121 (4.8)
296 (20.0)
Aborigine
122 (2.2)
36 (2.1)
56 (2.2)
30 (2.0)
Level of education
< 0.001
No education
799 (14.1)
49 (2.9)
386 (15.5)
364 (24.6)
Primary school
2322 (41.0)
570 (33.8)
1135 (45.5)
617 (41.7)
High school
1628 (28.8)
643 (38.2)
648 (26.0)
337 (22.8)
University
911 (16.1)
422 (25.1)
328 (13.1)
161 (10.9)
Smoking status
< 0.001
Current smoker
723 (12.8)
290 (17.2)
293 (11.7)
140 (9.5)
Past smoker
894 (15.8)
208 (12.3)
350 (14.0)
336 (22.7)
Non-smoker
4047 (71.5)
1188 (70.5)
1854 (74.2)
1005 (67.9)
Betel quid
< 0.001
Current chewer
180 (3.2)
86 (5.1)
76 (3.0)
18 (1.2)
Past chewer
512 (9.0)
194 (11.5)
218 (8.7)
100 (6.8)
Non-chewer
4972 (87.8)
1406 (83.4)
2203 (88.2)
1363 (92.0)
Engage in physical activity
c
4039 (71.3)
1196 (70.9)
1799 (72.0)
1044 (70.5)
0.533
Falls in previous year
1103 (19.5)
247 (14.7)
488 (19.5)
368 (24.8)
< 0.001
Chronic disease
d
Heart disease
1215 (21.5)
248 (14.7)
532 (21.3)
435 (29.4)
< 0.001
Stroke
303 (5.3)
44 (2.6)
147 (5.9)
112 (7.6)
< 0.001
Cataract
2214 (39.1)
236 (14.0)
1045 (41.9)
933 (63.0)
< 0.001
Arthritis
986 (17.4)
207 (12.3)
441 (17.7)
338 (22.8)
< 0.001
Osteoporosis
1118 (19.7)
300 (17.8)
538 (21.5)
280 (18.9)
0.007
Prostatic disorders
e
875 (32.7)
143 (17.9)
384 (34.3)
348 (46.1)
< 0.001
aIncludes divorced, separated, and single.
bThe ethnicity of participants was classified based on the origin of the participants’
fathers.
cEngage in physical activity: having any leisure-time physical activity in the past
year.
dPhysician-diagnosed chronic disease.
eThe percentage was calculated for males.
Table 3 reveals baseline biomarker profiles of the HALST participants. Systolic blood
pressure increased but diastolic blood pressure decreased along with age. In addition,
the levels of haemoglobin, albumin, glomerular filtration rate, cholesterol and triglyceride,
and gait speed also all decreased with age, whereas the prevalence of under-weight
[body mass index (BMI) < 20 kg/m2] increased with age. For those older than 75 years, >
11% and > 6% had BMI < 20 kg/m2 and serum albumin < 4 g/dl, respectively, indicating
a risk of malnutrition that medical personnel should be on the alert for. Some common
chronic diseases—such as hypertension, diabetes, chronic kidney disease and anaemia—also
increased with age. In general, the intake of food and nutrients decreases in older
participants, except for beans and dairy intake in males (data not shown). Regarding
the physical function performance, the mean gait speed of those older than 75 (0.7 m/s)
was slower than the cutoff point suggested in the European consensus, indicating the
need for refining the definition of sarcopenia for the Asian population.
22
Similar situations can also be found with gender-specific handgrip strength (about
5 kg lower than that of Caucasian counterparts)
22
and distance in 6-min walking test (> 15% of those older than 75 years could walk
no farther than 250 m).
Table 3.
Baseline biomarker profiles for the study subjects in the HALST cohort
Total (n = 5664)
55–64 years (n = 1686)
65–74 years (n = 2497)
≥ 75 years (n = 1481)
P
BMI (kg/m2)
24.6 (3.5)
24.7 (3.5)
24.7 (3.5)
24.2 (3.5)
< 0.001
SBP(mmHg)
128.6 (18.8)
122.6 (17.3)
129.4 (18.0)
134.4 (19.7)
< 0.001
DBP(mmHg)
70.6 (10.8)
72.2 (11.1)
70.7 (10.6)
68.4 (10.6)
< 0.001
Fasting glucose (mg/dl)
111.9 (31.4)
110.0 (29.8)
113.2 (33.8)
111.6 (28.7)
0.007
HbA1c (%)
6.2 (1.1)
6.1 (1.0)
6.3 (1.1)
6.3 (1.1)
< 0.001
Haemoglobin (g/dl)
13.6 (1.5)
14.0 (1.5)
13.7 (1.4)
13.2 (1.5)
< 0.001
Albumin (g/dl)
4.4 (0.2)
4.4 (0.2)
4.4 (0.2)
4.3 (0.2)
< 0.001
GFR (ml/min/1.73 m
2
)
83.2 (22.0)
91.2 (20.4)
83.6 (21.1)
72.8 (21.2)
< 0.001
ALT (U/l)
27.0 (19.0)
29.3 (21.6)
27.3 (19.2)
23.7 (14.2)
< 0.001
AST (U/l)
28.9 (14.6)
28.8 (13.8)
29.2 (16.8)
28.4 (11.1)
0.228
Uric acid (mg/dl)
6.0 (1.6)
5.8 (1.5)
5.9 (1.5)
6.3 (1.6)
< 0.001
LDL-C (mg/dl)
118.1 (33.1)
121.4 (33.9)
118.6 (32.7)
113.0 (32.3)
< 0.001
HDL-C (mg/dl)
52.5 (13.7)
52.8 (13.9)
52.6 (13.4)
52.0 (13.8)
0.288
TG (mg/dl)
124.1 (87.6)
131.5 (102.6)
123.2 (86.6)
116.7 (66.4)
< 0.001
Gait speed (m/s)
a
0.9 (0.3)
1.0 (0.3)
0.9 (0.3)
0.7 (0.3)
< 0.001
Handgrip strength (kg)
b
28.4 (10.2)
32.5 (10.3)
28.3 (9.6)
23.8 (9.0)
< 0.001
SPPB
c
10.0 (2.0)
11.0 (1.0)
11.0 (2.0)
9.0 (3.0)
< 0.001
6-min walk (m)
d
382.2 (82.0)
421.5 (69.6)
381.2 (74.9)
328.0 (80.8)
< 0.001
BMI (kg/m2)
< 0.001
< 20
432 (8.1)
107 (6.6)
174 (7.3)
151 (11.3)
20–24.9
2672 (50.0)
824 (50.6)
1175 (49.5)
673 (50.3)
25–29.9
1876 (35.1)
574 (35.3)
870 (36.6)
432 (32.3)
≥ 30
360 (6.7)
123 (7.6)
156 (6.6)
81 (6.1)
Hypertension
e
3017 (53.3)
657 (39.0)
1370 (54.9)
990 (66.9)
< 0.001
Diabetes
f
1365 (25.5)
343 (21.1)
652 (27.4)
370 (27.5)
< 0.001
Haemoglobin < 12 g/dl
609 (11.4)
118 (7.3)
242 (10.2)
249 (18.5)
< 0.001
Albumin < 4 g/dl
186 (3.5)
31 (1.9)
67 (2.8)
88 (6.6)
< 0.001
GFR < 60 ml/min/1.73 m
2
696 (13.0)
91 (5.6)
255 (10.7)
350 (26.0)
< 0.001
ACR ≥ 30 mg/g
1278 (24.0)
252 (15.6)
535 (22.6)
491 (36.7)
< 0.001
LDL-C ≥ 200 mg/dl
74 (1.4)
30 (1.8)
34 (1.4)
10 (0.7)
0.037
TG ≥ 200 mg/dl
594 (11.1)
223 (13.7)
252 (10.6)
119 (8.9)
< 0.001
Uric acid ≥ 8 mg/dl
591 (11.1)
138 (8.5)
246 (10.4)
207 (15.4)
< 0.001
Hepatitis B carrier
498 (9.4)
210 (12.9)
202 (8.5)
86 (6.5)
< 0.001
Hepatitis C carrier
273 (5.1)
73 (4.5)
119 (5.0)
81 (6.1)
0.141
Slow gait speed
< 0.8 m/s
1994 (35.7)
281 (16.8)
848 (34.3)
865 (60.3)
< 0.001
< 0.7 m/s
1298 (23.3)
131 (7.8)
523 (21.1)
644 (44.9)
< 0.001
Low handgrip strength (kg)
male < 30, female < 20
1520 (27.1)
155 (9.3)
594 (23.9)
771 (52.8)
< 0.001
male < 25, female < 15
616 (11.0)
49 (2.9)
184 (7.4)
383 (26.2)
< 0.001
SPPB ≤ 9
1199 (21.8)
105 (6.3)
452 (18.5)
642 (45.9)
< 0.001
6-min walk < 250 m
293 (5.9)
18 (1.1)
103 (4.6)
172 (15.4)
< 0.001
Data are n (%) unless indicated otherwise.
BMI, body mass index; SBP, systolic blood pressure; DBP, diastolic blood pressure;
GFR, glomerular filtration rate; ALT, alanine aminotransferase; AST, aspartate aminotransferase;
HDL-C, high density lipoprotein cholesterol; LDL-C, low density lipoprotein cholesterol;
TG, triglyceride; ACR, urine albumin-to-creatinine ratio.
a5580 study subjects had received measurement of gait speed.
b5612 study subjects had received measurement of handgrip strength.
c5490 study subjects had received measurement of SPPB.
d4954 study subjects had received measurement of 6-min walk.
eHypertension: SBP ≥ 140 mmHg, or DBP ≥ 90 mmHg, or taking anti-hypertensive drugs.
fDiabetes: fasting glucose ≥ 126 mg/dl, or HbA1c ≥ 6.5%, or taking anti-diabetic drugs.
Among those who had completed the first annual telephone interview (n = 4930), 123
(2.49%) had a new diagnosis of hypertension, 99 (2.01%) developed diabetes, 34 (0.69%)
had stroke and 38 (0.77%) had cancer diagnosed in the previous year of the first telephone
survey. We also found, in the previous year, 752 (15.26%) had falls, 589 (11.95%)
had been admitted to hospitals, 267 (5.53%) had body weight loss of more than 3 kg
and 52 (1.09%) had various degrees of depression syndrome [BSRS-5 score 10–14: 45
(0.94%), score ≥ 15: 7 (0.15%)].
In addition to the unique characteristics described above, several interesting results
have been found in the HALST study. For example, we found a strong relationship between
dietary fibre intake and physical performance in the elderly, providing potential
practical preventive strategies for frail older adults.
23
Those who had higher education, higher BMI and lower fish and milk intake were found
to be more likely to have vitamin D insufficiency.
24
The results of gait speed and handgrip strength performed by the HALST participants
were adopted to refine cutoffs and prevalence of sarcopenia in Taiwan.
25
We also illustrated a synergistic impact of sarcopenia and obesity on elders’ physical
performance.
26
The HALST study is a member of the TaiChi consortium, joining international efforts
to identify genetic determinants of atherosclerosis and metabolic-related traits in
multi-ethnic populations. For the past 3 years, collaboration within the TaiChi consortium
has been fruitful. For example, four new genetic loci have been found related to obesity;
27
some novel genetic variants associated with HbA1c, plasma triglycerides and risk of
coronary artery disease were identified;
28
,
29
a novel independent type 2 diabetes locus was found in the Chinese population;
30
and some other important findings were also published in renowned journals.
31–37
By linking with the NHID, we have recently conducted a prospective study and found
that the older adults performing a healthy lifestyle (higher diet score, physical
activity and psychosocial score) would be less likely to develop diabetes (manuscript
under revision). More findings based on the follow-up data will be realized when we
finish the second wave which started in 2014. The HALST, because of its prospective
nature and extended data linkage, is a good epidemiological research platform to better
understand multidimensional health risks in the elderly.
What are the main strengths and weaknesses?
Strengths
The HALST study has several strengths. First, composed of comprehensive geriatric
assessment and extended biochemical and genetic measurements, the HALST is more feasible,
compared with other Chinese longitudinal ageing studies, to investigate factors related
to healthy ageing. We have established some international collaboration to conduct
genetic and biomarker studies for ageing-related genetic traits. Results from the
HALST study will provide information unique to Asian societies and allow a direct
comparison with those from Western countries which differ in lifestyle and in genetic
and environmental characteristics. Second, the study design includes data linkage
with National Health Insurance databases, the mortality registry, the cancer registry,
and medical records, which allows a tracking of participant incidence of health-related
events and use of healthcare. Third, the HALST has a close link with the Chicago Healthy
Aging Study.
38
Most methods of procedures (MOP) between these two studies are similar. This provides
opportunities to make ethnicity and cross-country comparisons in various geriatric
research issues. For example, researchers on both sides have recently been working
on developing and cross-validating a sensitive but important questionnaire about filial
piety which is unique to Chinese culture. Finally, all measurements in the HALST have
been conducted by a well-trained team containing 15 fieldworkers who are trained to
strictly follow the study protocols. Data collection, management, validation and processing
are also being carried out to an exceptionally high standard.
Weaknesses
First, the HALST cohort is not a completely random sample from the elderly population
in Taiwan; instead, the study is targeted at recruiting enough people with different
socio-demographic backgrounds. This incomplete representation of Taiwan’s general
population limits the data applicability for estimation of disease prevalence. However,
our study focuses on searching for the risk factors of ageing-related diseases and
conditions, so the sampling effects would be minimal. Second, as with other longitudinal
studies for ageing, response rate, sample attrition and missing data are always great
concerns in the interpretation of the results. Third, although our study has a relatively
large sample size, several years of longitudinal observations are necessary before
it can obtain statistical power for new outcomes.
Can I get hold of the data? Where can I find out more?
The HALST study group encourages domestic and international research collaboration.
To learn more about the HALST study, access the data and explore potential collaboration,
please contact the principal investigator, Dr. Chao A. Hsiung [hsiung@nhri.org.tw].
HALST in a nutshell
HALST is a prospective cohort study aiming at investigating multidimensional determinants
of healthy aging—including lifestyle behaviours and genetic, metabolic and inflammatory
factors—in an older Asian population.
A total of 5664 community-dwellers aged 55 and over, recruited from seven selected
cities/counties to represent the socio-demographic diversity of the Taiwanese population,
participated in home interviews and hospital-based clinical examinations in the first-wave
survey (2009–13).
Participants have annual telephone contact to update health-related conditions and
hospitalized events. The HALST dataset has been linked to Taiwan’s National Health
Insurance database, the national mortality registry, the national cancer registry
and medical records.
The HALST dataset comprises a broad scope of measurements, including socio-demographic
information, lifestyle pattern, dietary habit, metabolic profile, inflammatory biomarkers,
cognitive function, depression assessment, physical function, medication and genetic
components.
The first-wave HALST data (2009–13) have been compiled and are available for analysis;
the second-wave survey (2014–19) is ongoing. Further enquiries about research collaboration
should be addressed to the principal investigator, Dr. Chao A. Hsiung [hsiung@nhri.org.tw].
Funding
This study was supported by the National Health Research Institutes in Taiwan [project
no. BS-097-SP-04, PH-098-SP-02, PH-099-SP-01, PH-100-SP-01, PH-101-SP-01, PH-102-SP-01,
PH-103-SP-01, PH-104-SP-01].