AGING AND HEALTH IN ASIA
AGING AND HEALTH-SES
CORRELATIONS
IN ASIA:
EVIDENCE FROM INDONESIA
JOHN STRAUSS - USC
FIRMAN WITOELAR - WORLD BANK/SURVEY METER
BONDAN SIKOKI - SURVEY METER
YOUNOH KIM - USC
Health and Nutrition Transitions
• Nutrition: from under-nutrition and malnutrition to
over-nutrition
• Health: from infectious to chronic diseases
• Implications:
– Chronic diseases affect elderly more
– Unawareness of chronic illness by individuals
– The public health system is designed to handle infectious
diseases and not chronic diseases
– Low incomes: inadequate resources to handle the expensive
treatment of chronic illnesses
•
•
•
•
Data: Indonesia Family Life Survey
IFLS : a large-scale broad -based longitudinal survey of
households and individuals that not only collects a set of socioeconomic characteristics , but also physical health biomarkers
and self-reported health measures
Four waves of IFLS: IFLS1 (1993), IFLS2 (1997), IFLS3
(2000), IFLS4 (2007).
V ery low attrition rates: over 90% of HHs from 1993 found in
2007, 88% of individuals
The paper will focus on markers and measures known to be
important for elderly health for which we have data for multiple
waves:
• Data available at http://www.rand.org/labor/FLS/IFLS
• Paper is RAND Labor and Population working paper WR-704
CDF of Body Mass Index Over Time: males and females 45+
Indonesia
.8
.6
.4
.2
0
0
.2
.4
.6
.8
1
Female 45+
1
Male 45+
10
15
18.5
25
30
BMI
1993
2000
Source: IFLS1, IFLS2, IFLS3, IFLS4
35
10
15
18.5
25
30
BMI
1997
2007
1993
2000
1997
2007
35
Body Mass Index: Male and Female 45+
Male
1993
45-54
1997
2000
2007
12.49
9.46
22.28
16.52
12.98
9.39
% Overweight (BMI ≥ 25)
11.25
13.32
17.00
22.65
17.04
24.46
30.83
40.18
1,042
1,187
1,467
1,870
1,232
1,333
1,561
2,106
29.88
27.07
24.22
18.22
31.96
28.15
27.14
16.64
8.11
9.06
12.68
17.26
14.24
17.82
21.19
30.57
819
923
1,035
1,096
942
1,132
1,261
1,211
42.50
39.46
35.66
27.95
36.86
33.89
34.26
29.57
4.65
6.28
7.37
8.59
10.70
12.29
15.44
18.82
481
512
639
713
485
581
763
878
48.68
50.36
48.39
38.05
50.09
46.35
44.65
33.60
4.33
2.49
3.05
6.31
4.25
8.30
8.98
13.96
172
218
306
338
184
241
359
438
% Overweight (BMI ≥ 25)
% Undernourished (BMI < 18.5)
% Overweight (BMI ≥ 25)
Observations
% Undernourished (BMI < 18.5)
% Overweight (BMI ≥ 25)
Observations
Mean BMI
45+
1993
16.34
Observations
75+
2007
17.02
% Undernourished (BMI < 18.5)
65-74
2000
% Undernourished (BMI < 18.5)
Observations
55-64
1997
Female
% Undernourished (BMI < 18.5)
% Overweight (BMI ≥ 25)
Observations
Source: IFLS1, IFLS2, IFLS3, IFLS4.
20.30
20.69
21.06
21.75
20.86
21.43
21.88
22.90
28.25
26.60
23.50
17.54
29.77
25.78
24.51
17.40
8.49
9.83
12.68
17.31
14.20
18.84
22.78
31.14
2,514
2,840
3,447
4,017
2,843
3,287
3,944
4,633
Body Mass Index and education: males and females 45+
Indonesia
20
20
21
21
22
BMI
23
22 BMI
23
24
24
25
25
26
Female 45+
26
Male 45+
0
1
2
3
1993
4 5 6 7 8
Y ears of Education
1997
Source: IFLS1, IFLS2, IFLS3, IFLS4
9
10 1 1 12
2000
2007
0
1
2
3
1993
4 5 6 7 8
Y ears of Education
1997
9
10 1 1 12
2000
2007
Waist circumference and BMI: male and female 45+
Indonesia
1 10
100
W aist (cm)
80
90
70
60
50
50
60
70
W aist (cm)
80
90
100
1 10
120
Female 45+
120
Male 45+
12 14 16 18 20 22 24 26 28 30 32 34 36
BMI
2000
Source: IFLS1, IFLS2, IFLS3, IFLS4
2007
12 14 16 18 20 22 24 26 28 30 32 34 36
BMI
2000
2007
Hemoglobin level: males 45+
Indonesia
0
.2
.4
.6
.8
1
Male Age 45+,1997, 2000, and 2007
8
9
10
11
1997
12
13
Hb level
2000
14
15
2007
16
17
Hemoglobin level: females 45+
Indonesia
0
.2
.4
.6
.8
1
Female Age 45+, 1997, 2000, and 2007
8
9
10
11
1997
12
13
Hb level
2000
14
15
2007
16
17
Table 2. Percentage of adults 25+ with blood hemoglobin level below 13.0 g/dL (men) or
12.0 g/dL (women), 1997, 2000 and 2007
Men
Women
2000
2007
Age groups
1997
2000
2007
1997
25-44 years
% <12.0/13.0
22.01
15.45
9.69
36.07
38.62
26.58
Observations
3,397
4,961
6,485
4,478
5,555
6,904
45-54 years
% <12.0/13.0
32.22
22.09
17.72
39.49
39.96
28.08
Observations
1,167
1,460
1,869
1,298
1,553
2,091
55-64 years
% <12.0/13.0
41.57
37.32
26.01
40.16
41.96
32.82
Observations
911
1,039
1,093
1,122
1,260
1,212
65-74 years
% <12.0/13.0
48.53
46.58
40.86
46.00
48.93
40.25
Observations
513
645
728
575
774
886
75+ years
% <12.0/13.0
62.81
53.60
52.24
53.52
53.49
50.06
Observations
220
312
350
237
387
461
45+ years
%<12.0/13.0
40.62
34.08
27.12
41.91
43.66
33.81
Observations
2,811
3,456
4,040
3,232
3,974
4,650
Source: IFLS2, IFLS3, IFLS4
Observations are weighted using individual sampling weights. The thresholds are 12.0 g/dL for
women and 13.0 g/dL for men.
Hemoglobin level against years of education:
males 45+ in Indonesia
Hb (g/DL)
14
15
Male Age 45+, 1997, 2000, and 2007
12
13
1997
2000
2007
0
1
2
3
4
5
6
7
8
Years of Education
9
10
11
12
Number of difficulties with ADLs and age over time :
males and females 45+ in Indonesia
Female 45+
0
0
1 Number 2of difficulties
3
1 Number of2difficulties 3
4
4
Male 45+
45
50
60
70
80
45
50
Age
1993
1997
Source: IFLS1, IFLS2, IFLS3, IFLS4
60
70
80
Age
2000
2007
1993
1997
2000
2007
CES-D 10 Score by years of education: male and female 45+
Indonesia
CES-D Score
3.5
4
4.5
Age 45+, 2007
2.5
3
Male
Female
0
2
4
6
8
Years of Education, 2007
10
12
Word recall by age and education: male and female 45+
Indonesia
Word recall and education
3.5
3
Words Recalled
1
2
2.5
3
2
Words Recalled
4
4
4.5
Word recall and age
40
50
Male 45+
Source: IFLS4
60
Age
70
Female 45+
80
0
2
4
6
8
Years of Education, 2007
Male 45+
10
Female 45+
12
Proportion with hypertension: female 45+
Indonesia
Proportion with hypertension
.4
.5
.6
.7
Female Age 45+, 1997, 2000, and 2007
.3
1997
2000
2007
40
50
60
Age
70
80
Hypertension: male and female 45+
Male
Female
% with hypertension
1997
2000
2007
1997
2000
2007
Age 45-54 (%)
35.16
36.06
34.72
41.11
36.95
41.15
Observations
1,189
1,472
1,876
1,330
1,565
2,101
Age 55-64 (%)
47.17
46.23
48.76
54.69
50.94
53.79
Observations
926
1,044
1,098
1,140
1,272
1,216
Age 65-74 (%)
52.86
55.01
56.02
65.69
67.07
68.74
Observations
519
646
723
585
783
892
63.57
62.52
61.90
79.52
72.87
76.32
Observations
222
313
347
252
391
464
Age 45+ (%)
43.78
44.21
44.19
52.61
49.63
52.70
Mean systolic
137.47
136.96
139.76
143.55
141.2
144.52
Mean diastolic
82.19
83.39
82.62
82.95
83.51
83.22
Observations
2,856
3,475
4,044
3,307
4,011
4,673
Age 75+ (%)
Source: IFLS2, IFLS3, IFLS4.
Hypertension if systolic ≥ 140 or diastolic ≥ 90.
o
l
ci
≥
9
0
.
s
sty
o
icl
≥
1
4
0
ro
iad
st
IF
L
S
3
,
I
F
L
S
4
.H
y
p
re
et
sin
o
n
if
T able 5. Underdiagnosis of hypertension, adult 45+, 2007
Adult 45 + years
Men
4,044
Observations
% hypertensive
% diagnosed
a)
44.2
Women
4,676
52.8
26.4
37.9
Underdiagnosis of hypertension by education, adult 45+
highest completed level of education
no schooling
primary schooling
junior high
senior high +
all adult 45+
a)
% underdiagnosed
79.0
69.4
74.4
58.1
73.2
52.1
68.0
62.3
73.6
62.1
Source: IFLS4
Observations are weighted using individual sampling weights.
a) "Diagnosed" if answered "Yes" to the question "Has a
doctor/nurse/paramedic ever told you that you have hypertension?".
Percentages are out of individuals 45+ whose sytolic>=140 or diastolic
>=90.
Table 6. Hypertension and medication, adult 45+, 2000 and 2007
Men
Adult 45 + years
2000
2007
Women
2000
2007
Observations
3,477
4,044
3,631
% hypertensive
44.2
44.2
49.6
% taking medication for hypertension a)
2.6
4.7
2.5
a) Percentages are out of individuals 45+ whose systolic >=140 or diastolic >=90
4,674
52.8
4.7
a)
Hypertensive and not taking medication, by completed education
Men
Highest completed level of education
no schooling
primary schooling
junior high
senior high +
all adult 45+
2000
98.7
99.1
95.4
93.9
97.4
2007
97.6
96.7
91.2
92.5
95.3
Women
2000
2007
98.7
97.3
96.9
94.9
96.7
88.1
92.3
94.1
97.5
95.4
Source: IFLS3 and IFLS4
a) Percentages are out of individuals 45+ whose systolic >=140 or diastolic >=90.
Observations are weighted using individual sampling weights.
Health status-SES gradients
• SES variables: education, log per capita expenditure
•In this analysis is not causal!
•Omitted variables:
•For instance childhood health which can affect
completed schooling and adult income
•Reverse causality from health to income
•Can show health status differentials by SES
Impact of Respondent Schooling and
Household Per Capita Expenditure
• Have data on household PCE-better measure of longrun resources than current income
• Regress health outcomes for those 45+ in each wave
(1993, 1997, 2000, 2007) on health measures-pooled
regression for measures collected in multiple waves
• Covariates include:
– dummies for level of schooling
– linear spline in log PCE (around median)
– dummies for respondent age
– dummies for location (province/rural-urban) at
survey, year and interaction of year/location
dummies
Multivariate results
BMI*
Male
Hemoglobin†
Female
Male
N=
Female
Hypertension†
Male
N=
Female
#ADL
problems*
Male
N=
Female
Poor GHS*
Male
N=
Female
N=
12,836
14,735
10,035
11,853
10,376
11,994
12,711
14,095
12,705
14,094
---
---
---
---
++
+++
+++
+++
++
.
Education
+++
+++
++
.
.
.
.
.
.
++
Age x educ
+++
+
.
.
++
.
.
.
--
---
PCE
+++
+++
+++
++
+++
++
++
+
--
.
V ariables
Age
Source:
* = IFLS1, IFLS2, IFLS3, IFLS4
† = IFLS2, IFLS3, IFLS4
Multivariate results
Underdiagnosis of
hypertension
Cognition /
Correct #
Words
Male
Male
Female
N=
Female
# IADL
Problems
Male
N=
Female
CES-D 10
Score
Male
N=
Female
Vigorous
physical
activity
Male
N=
Female
Moderate
physical
activity
Male
N=
Female
N=
1,813
2,474
3,748
4,063
3,902
4,401
3,901
4,402
3,902
4,403
3,902
4,403
Age
---
.
---
---
.
.
+++
+++
---
---
---
---
Educ
.
---
+++
+++
++
.
.
.
-
-
.
+++
Age x
Educ
.
.
+++
+++
---
---
---
--
---
.
.
-
PCE
.
---
+++
+++
--
-
.
.
--
.
---
.
Variables:
Source: IFLS4
Impact of Parental Health and Schooling
• Have measures of mother and father schooling and
health
• Health measures:
– Mother/father dead at 2007 (about 5% of sample parents
still alive)
– Mother/father in poor health at time of 2007 survey or just
prior to death, if dead
– Mother/father has difficulties with ADLs at time of 2007
survey or just prior to death, if dead
•
Regress health outcomes for those 50+ in 2007
on these measures, plus dummies for level of
parental schooling, plus dummies for respondent
age, plus dummies for province/rural-urban
location at birth
• Then regress changes 2007-1993 or 2007-1997 on same vars
Static Analysis
Static 07
# ADL Problems
V ariables
Male
Female
Male
Female
Male
Female
N= 3081 N= 3605 N = 2983 N = 3491 N = 3081 N= 3608
Age
Educ father
Educ mother
Death father
Death mother
Poor GHS father
Poor GHS mother
ADL problems father
ADL problems mother
Static 07
V ariables
Age
Educ father
Educ mother
Death father
Death mother
Poor GHS father
Poor GHS mother
ADL problems father
ADL problems mother
+++
-.
.
.
++
.
.
.
# IADL Problems
+++
+
+
.
.
+
+++
.
BMI
--.
+
.
.
.
.
.
.
Hemoglobin
Poor GHS
--+++
.
.
.
.
.
.
+
+++
.
-.
.
+
++
.
.
Hypertension
+++
.
.
+++
+++
.
.
.
Cognition
/Correct # Words
Male
Female
Male
Female
Male
Female
Male
Female
N= 3081 N = 3605 N= 2980 N= 3475 N= 2985 N = 3493 N= 2317 N= 2309
+++
--+
.
.
+++
++
.
.
+++
.
+
.
.
++
++
.
--.
++
.
-.
.
.
.
--+++
.
.
.
.
.
.
.
+++
.
.
.
++
.
.
.
.
+++
.
.
.
++
.
.
.
.
+++
+++
+++
.
.
.
.
.
.
+++
+++
+
-.
.
.
.
.
Dynamic Analysis
Dynamic diff
V ariables
# ADL
Problems
BMI
Poor GHS
Hemoglobin
Hypertension
Male
Female
Male
Female
Male
Female
Male
Female
Male
Female
N=2380 N=2820 N=2200 N=2710 N=2388 N=2828 N=2309 N=2843 N=2340 N=2894
+++
+++
---
---
+++
.
--
---
.
---
Educ father
.
+
.
.
.
+++
-
-
.
--
Educ mother
.
.
.
.
-
-
.
--
.
.
Death father
.
++
.
+
.
.
.
.
+
.
Death mother
.
.
.
.
.
.
.
.
.
+
Poor GHS
father
Poor GHS
mother
ADL problems
father
ADL problems
mother
.
.
.
.
.
.
.
.
.
.
++
.
.
.
.
.
.
.
.
.
.
+
.
.
.
.
.
.
.
.
.
.
.
+
.
.
.
.
.
.
Age
CONCLUSIONS
Asian countries in midst of demographic, health and nutrition
transitions- Indonesia illustrative
V ery rapid aging, decline in importance of infectious diseases
and increase in importance of chronic diseases
Health sectors are behind in keeping up with these transitions, as
underdiagnosis of hypertension in Indonesia (and China) shows
Are strong health-SES gradients in Indonesia, similar to higher
income countries, but also to China
Also strong intergenerational correlations between measures of
parental health and schooling and health of their adult children
when 50+