Transcript Association between Lifestyle and Self

Association between Lifestyle and
Self-Rated Health of Chinese
Oldest-Old
Li Jianxin, Sociology Dept., Peking U.
Zhang Zhen, CHAFS, Peking U.
Wang Jiabao, Ph.D student, Peking U.
Outline
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•
•
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1, Background
2, Data and Methodology
3, Findings
4, Conclusions
1.Background
• As we know, One of the most important population trends in China
over the next half a century will be the aging process and the
increasing number of the “oldest old”. By the 2040s and 2080s,
China will have more than 300 million people aged 65 and above,
peaking at 370 million.
• The age 80 and above group, in particular, will be the fastestgrowing. Prof.Zeng Yi estimate that assuming a moderate mortality
rate, by 2050, China will have 114 million people aged 80 and above;
assuming a more optimistic low mortality rate, that number will
reach 160 million.
• Like other countries that have undergone population aging, the
health of the elderly population – particularly the oldest-old – has
become a serious concern in China and an area of research of much
attention.
Figure1 Population aged 65/80 and
above in the future
0.1b
3.5
3
Aged 65 and above
2.5
Aged 80 and above
2
1.5
1
0.5
0
2000
2020
2040
year
2050
• In recent years, many researchers have
•
examined the impact of different lifestyles –
such as smoking, drinking, exercising, leisure
(including religion) – on the health status of the
elderly.
This study attempts to examine the relationship
between lifestyles and self-rated health from a
sociological perspective in the hope that it will
shed some light from a quantitative and more
practical point of view.
2. Data and Methodology
• Data
– Our study based on the Chinese Longitudinal
Healthy Longevity Survey (2000), In this
survey, 11,200 people were aged 80 and
above. In the analytic model used in this
study, there were more than 20 variables.
Excluding the irrational responses, 9,960
cases were used in the calculations of the
model.
• Variables
– This study focused on analyzing the factors affecting
Self-Rated Health. The dependent variable was the
SRH, i.e. “what do you think of your health
conditions?” this is a very ordered variable with 1
being “very good”, 2 “good”, 3 “so-so”, 4 “bad” and 5
“very bad”. Because only a small percentage of people
answered “very bad”, we merged “very bad” with
“bad”. Therefore, the dependent variable in this study
was categorized into four values.
– The independent variable was lifestyle. In this
study, we examined different aspects of a
lifestyle, i.e. smoking, drinking, exercising,
leisure, form of residence. We assumed that
these different lifestyles all had varying
degrees of impact on a person’s SRH.
– We also attempted to examine the socioeconomic
conditions, personal health and other controlled
variables. Socioeconomic variable included marital
status, level of education, past occupations, identity
of residence and economic conditions. The physical
health variable included the ability to take care of
oneself in daily life (ADL); suffering from chronic
diseases and suffering from serious diseases. These
indicators, such as the ability to take a shower, get
dressed and eating, other old-age diseases such as
high blood pressure, arthritis, and history of suffering
from major diseases, will be discussed in depth in the
following model.
Table 1 Variables description
Name
Mean or Std.
%
Deviation
Description
SRH
2.6
0.88
1 if “bad”; 2 if “so-so”;3 if “good”; 4 if “very
good”
Age
90.64
7.39
1 if octogenarians; 2 if nonagenarians;
centenarians=0 (reference group)
Sex
0.43
0.5
1 if male; 0 if female
Smoking
0.18
0.38
1 if smoking; 0 if no
Drinking
0.21
0.4
1 if drinking; 0 if no
Exercising
0.35
0.48
1 if do exercise; 0 if no
Growing plants
0.13
0.34
1 if doing; 0 if no
Reading
0.19
0.39
1 if reading; 0 if no
Religious faith
0.17
0.37
1 if participate religion activities; 0 if no
Form of residence 0.81
0.39
1 if with family; 0 if no
• Methodology
–
Because this dependent variable is an ordered one
(very good, good, so-so, bad), this study can be
used the Ordered Logit model for analysis. That
model, however, requires very strong assumptions
(Parallel Regression). Other models such as
Multinomial Logit, though not requiring those
assumptions, are not capable of including ordered
variables into the formula and will therefore lose
some important information about data. We
therefore opted not to use those models.
– In 1984, the American scholar Anderson
modified traditional models and developed the
“stereotype ordered regression model” which
retains the ordered variables while not
requiring assumptions with parallel regression
and allowing variance between different types
of dependent variables. Put simply, this model
can be expressed as follows:
Pr(Y  y s | x ) 
exp( s   s  ' x )

exp(




'
x
)
l
l
l 1
k
, s  1,..., k
– In the above model, β is the to-be-rated coefficient of
independent variable x; k is the cut-point of the
dependable variables; α’s are the intercepts of the
model. By defining a single increment (i.e. Ø), we can
arrive at the regression of the ordered variable. In our
model, our definition is that , Ø(1)=0, Ø(4)=1 which
corresponds to SRHs ranging from “bad” to “very
good”. With that assumption, a positive coefficient
means a senior citizen with that characteristic is
inclined toward better SRH; in other words, this factor
has a positive impact on the health conditions of that
individual and vice versa.
– All the calculations in this study were done using the
SOREG command of the STATA program developed by
Lunt in 2001.
Table 2: Results of SRH analysis
Model 1
Lifestyle
Model 2
Lifestyle+SES
Model 3
Coef.
Coef.
Coef.
Ф1
0
0
0
Ф2
0.45***
0.44***
0.38***
Ф3
0.69***
0.69***
0.73***
Ф4
1
1
1
80-89 age (100+ =0)
-0.11
-0.02
-0.30**
90-99 age (100+ =0)
0.16
0.20+
0.05
Sex (female=0)
-0.1
0.06
0.03
Smoking (no=0)
0.05
0.07
-0.07
Drinking (no=0
0.58***
0.52***
0.34**
Regular exercises (no=0)
1.39***
1.35***
1.08***
Growing plants and birds (no=0)
0.81***
0.81***
0.65***
Reading (no=0)
0.38***
0.62***
0.44**
religious activities (no=0)
-0.02
-0.02
-0.12
Living with family (no=0)
0.44***
0.38***
0.57***
Lifestyle+SES+Physical condition
(Continued)
Model 1
Lifestyle
Model 2
Lifestyle+SES
Model 3
Lifestyle+SES+Physical
condition
LR chi2
516.17***
791.54***
1929.90***
df
12
19
28
N=9960; ***: p<0.001; **: p<0.01; *: p<0.05; +: p<0.1
3. Findings
• In the oldest-old group, sex did not have an
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impact on their SRH. Comparing reference
group, age group 80-89 had a minus impact on
SRH;
In the same group, after taking into
consideration the other lifestyles such as
drinking, smoking did not have an impact on
their SRH. As a matter of fact, for many senior
citizens, drinking and smoking go hand in hand.
Therefore, after controlling the drinking
variable, smoking ceased to be effective, too.
This, of course, has to do with the choice of
lifestyle;
• Those that regularly exercise reported positive
SRH; attendance at Buddhist activities,
however, did not have a significant impact.
This may be due to the fact that in China,
most people believe in multiple religions or are
polytheists and do not have a serious religious
faith in the Western sense. Regular, purely
religious activities are rare in life. This may
account for the difference between this study
and the many other studies done in the West;
• Form of residence had an impact on SRH.
Living with family appeared far superior
to living in solitude or in a nursery home
for obvious reasons: access to assistance
from family and freedom from loneliness.
Therefore, those living with their family
reported more positive SRH than those
living in solitude or in nursery homes.
4. Conclusions
• The foregoing analysis shows that lifestyles did have a
strong correlation with the SRH of the “oldest old”. Our
research indicated that even for the “oldest old” group of
people whose physical functions have declined to varying
degrees, healthy lifestyles and practices still have a
positive impact on their SRH. These positive and healthy
lifestyles are familiar to us: exercising, laid-back and
leisure lifestyles such as growing plants, reading, limited
drinking and living with family. Obviously, positive and
healthy lifestyles are an important way to seek health
and longevity.
• In studying the socioeconomic characteristics of the
“oldest old”, we found that marital status, level of
education, occupation, identity of residence and income
level had a very limited impact on SRH, contrary to the
findings of similar studies done abroad. In fact, this is
the actual conditions that the “oldest old” in China find
themselves in today. It does not mean the variables
themselves are not important. Within that group, the
level of education is universally low and the difference is
minimal; the difference in the distribution of occupation
is not significant, either; and their living standards are
very close. In short, their socioeconomic conditions did
not display a significant heterogeneity.
• In comparison, the physical health of the “oldest old”
had a more significant impact on their lifestyle and SRH.
Their physical health directly impacts their daily life and
their lifestyle, and – directly or indirectly – impacts their
SRH. As a matter of fact, the variables of physical
diseases, health, lifestyle and SRH are interactive and
their interrelationships are very complex. A sound
lifestyle, sound mental health and a positive attitude
toward life, for example, all have an impact on people’s
physical health. In this study, we simply simplified their
interrelationships, examining the factors impacting the
physical health of the “oldest old” from one perspective
and one dimension.