JOURNAL OF CARDIOVASCULAR DISEASE
ISSN: 2330-4596 (Print) / 2330-460X (Online)
VOL.3 NO.1
JANUARY 2015
http://www.researchpub.org/journal/jcvd/jcvd.html
Relation of Sedentary Lifestyle with
Cardiovascular Parameters
in Primary Care Patients
Jaspinder Kaur, MBBS*,# and Mandeep Kaur, MD
Abstract
Physical inactivity contributes to all-cause mortality and
higher hospitalization risk. The present study aimed to
estimate relation between sedentary lifestyle and
cardiovascular parameters. A cross-sectional study was
conducted on the retired defense personnel to relate
socio-demographic variables, body mass index, dietary
habits, alcohol, sleep, stress, dysglycaemia, hypertension
and dyslipidemia with sedentary behaviour. Total
prevalence of sedentary behaviour was 62.40%, which
increases with age. Insomnia, stress, low education,
unemployment, and upper social class were associated with
sedentary behavior. A statistical inverse association of
alcohol and sedentary behaviour was reported. Higher
prevalence of metabolic syndrome, hypertension and
obesity was observed in sedentary than active subjects.
Rising sedentary lifestyles and its association with
metabolic syndrome prompt to develop strategies of proper
city designs with sidewalks, personal motivation, climbing
stairs, doing household work, use of standing desks and
break-prompting software at work place to discourage this
behaviour.
Keywords — Age, metabolic syndrome, sedentary behavior,
stress.
Cite this article as: Kaur J. and Kaur M. Relation of sedentary
lifestyle with cardiovascular parameters in primary care
patients. JCvD 2015;3(1):284-300.
I. INTRODUCTION
S
edentary behavior refers to activities involving energy
expenditure equivalent to 1.0–1.5 metabolic equivalent
units, 1 and includes <150minutes of moderate physical
activity or <60minutes of vigorous physical activity per week.2
Operationally, sedentary behavior can be referred to as ‘sitting
time’ rather than simply low levels of physical activity which
From ECHS Polyclinc, Sultanpur Lodhi, Kapurthala, Punjab (JK), and
Government Medical College, Amritsar, Punjab (MK), India
Conflict of interest: None. #Current address: J. Kaur, Medical Officer,
ECHS Polyclinic, Kapurthala, Punjab, India-144601
*Corresponding Author: [email protected]
involves activities such as lying down, sitting, watching
television, using computer and other screen based
entertainment. Studies have shown individuals can spend more
than half of their waking hours in sedentary activities.3
Physical inactivity is considered as the fourth leading risk
factor for global mortality, which accounts for 6% global
deaths; and ranks before overweight and obesity (5%), and after
hypertension (13%), tobacco use (9%), and high blood glucose
(6%).4 Sedentary lifestyle attributes to >2million deaths and
19million disability adjusted life year globally each year. 5
Physical inactivity contributes to all-cause mortality;6 low
quality of life;7 higher risk of obesity, diabetes, hypertension,
cardiovascular disease (CVD), osteoporosis, fractures, colon
cancer, breast cancer, prostate cancer, psychiatric disorders; 6,7
and an overall higher hospitalization risk.8 Environment plays a
major role in influencing the physical activity through
significant changes in the form of rapid urbanization,
automobile dominance for the personal travel, introduction of
labor-saving devices in the home and the workplace, surplus
availability of energy dense-calorie foods, satellite TV,
increased reliance on computers and telecommunication
technology as well as decreased occupational-work demands.9
These changes have had a remarkable lifestyle transformation
by reducing the daily life physical requirements and
encouraging sedentary lifestyles which consequently lead to an
epidemic of non communicable diseases and contributes
substantially to the global burden of disease, disability and
death.6
Public health recommendations have evolved to reduce
sedentary behavior with an emphasize on a “lifestyle” approach
towards increasing physical activity through common
behaviors of brisk walking, climbing stairs, doing house and
yard work, and engaging in active recreational pursuits. [6]
Physical activity is a therapeutic option due to its inverse
relation with CVD risks and thus often prescribed to patients as
a means of improving cardiometabolic profile. 10 However,
changes in individual risk factors with physical activity tend to
be modest, on the order of 5% for blood lipids, 11 3-5mmHg for
blood pressure (BP),12 and 1% for hemoglobin A1c 13 in
contrast to the large 30-50% reductions in CVD risk and
increased longevity seen with physical activity independent of
weight or body fat loss.14 Other CVD risk factors particularly
related to inflammation and hemostasis are further favorably
modified with physical activity.15 The strength of the
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ISSN: 2330-4596 (Print) / 2330-460X (Online)
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relationship between physical activity and health outcomes
persists throughout individual lives; which highlights that
avoiding a sedentary lifestyle during adulthood not only
prevents CVD independent of other risk factors but also
substantially expands the total life expectancy and the
cardiovascular disease-free life expectancy in both sexes.16
Thus, the need of orientation of those tending towards being
sedentary on how to adopt healthier lifestyles is of paramount
interest in public health. However, assessing the prevalence of
sedentary lifestyles in the current study population is an initial
process towards achieving this orientation. Hence, the present
comparative study of socio-demographic variables and
cardiovascular parameters of sedentary and non-sedentary
subjects was designed.
II. METHODS
Design overview: This nonexperimental and crosssectional
study was undertaken to determine the relationship between
self-graded physical activity and the cardiometabolic
parameters in a community-based Ex-Servicemen registered
with Ex-Servicemen Contributory Health Scheme (ECHS)
Polyclinic, Sultanpur Lodhi, Kapurthala, Punjab (India). The
study population was representative of the primary care
attendees in the primary care clinic of the Northern India which
provides free at-the-point-of-access medical and follow up
services for all kind of acute and chronic diseases solely to the
registered retired defence personnel under health scheme. The
selection criteria for the study subjects was the subjects who
had been retired from the defence services; their family
members comprising spouse, children and parents; registered
with ECHS Polyclinic, and had attended the polyclinic during
the study period. Institutional ethical committee approval was
obtained prior to the start of study and informed written consent
was taken from all the subjects who attended the polyclinic
from July, 2013 to Nov, 2013. Chi Square test was used for
statistical analysis with a statistically significance of p value
<0.05.
Physical activity assessment: The Johnson Space Centre (JSC)
physical activity scale was used to assess the participant
activity level over the preceding three months.17 This 8-point
Likert scale consist of the following score choices:
0: Avoid physical activities whenever possible;
1: Light physical activities done occasionally;
2: Moderate physical activities done regularly for less than 1
hour per week;
3: Moderate physical activities done regularly for more than 1
hour per week;
4: Heavy physical activities done regularly for less than 30
minutes per week;
5: Heavy physical activities done regularly between 30 and
60minutes per week;
6: Heavy physical activities done regularly between 1 and
3hours per week; and
7: Heavy physical activities done regularly for more than
3hours per week.
The patients were asked to select the appropriate score (0 to 7)
which best described their general physical activity level.
Patients who selected a score of either 0 or 1 were classified as
sedentary because these activity values represent either no
physical activity or an insufficient and inconsistent amount of
physical activity that was far below the minimum
recommendations. Those patients who selected a score of 2 or
higher were classified as non- sedentary because these activity
levels either approach or exceed the recommendations. 18 The
JSC physical activity scale has a strong independent
relationship with maximal oxygen uptake in both sexes
between 20-79 years of age group.17
Survey Questionnaires: A structured in-person interview was
conducted to record socio-demographic and cardiometabolic
risk factors. Metabolic syndrome was defined on the basis of
consensus statement for Asians Indians with three out of five
variables abnormal for the diagnosis: Obesity >25.00kg/m2,
fasting blood glucose >100mg/dl (>5.6mmol/l), hypertension
≥130/≥85mmHg, triglycerides (TGs) >150mg/dl (>1.7mmol/l)
and/or High Density Lipoprotein Cholesterol(HDL-C)
<40mg/dl (<1.03mmol/l) in men or <50mg/dl (<1.29mmol/l) in
women. It includes those previously diagnosed with
hypertension, high TGs, low HDL-C, impaired fasting glucose
(IFG), impaired glucose tolerance (IGT) or diabetes mellitus
and being on treatment for these disorders.19 Heavy alcohol
consumption was defined by a self-reported >5 drinks on a
single occasion, or a daily drinking of >1 drink per day. 20 Job
strain, social constraints, financial un-stability, and family
distress were included subjectively under “stress” which
significantly affects the daily life activities. Sleep adequacy
was subjectively evaluated on the basis of sleep duration (7 to 8
hours), difficulty in initiating and maintaining sleep, and early
awakenings.
Measurements: Height was determined using a wall mounted
non extendable measuring tape with subjects standing in an
erect barefoot position, arms by side, and feet together with
0.1cm precision. Weight measurements were taken with each
subject standing at the centre of the weighing scale in light
clothing with no shoes and socks with 0.5kg precision. Weight
was divided on the basis of consensus statement: Normal
weight (18.00-22.99kg/m2), Overweight (23.00-24.99kg/m2)
and Obesity (>25.00kg/m2). 20 BP was measured in the right
arm with the subject seated and rested for 5 minutes using a
standard mercury sphygmomanometer and suitable calibrated
cuff. A venous blood sample was obtained from all the
pre-informed individuals after 8–10 hours of fasting to measure
blood glucose using Erba glucose kit (GOD-POD method, end
point), TGs with Erba triglyceride Des kit (GPO-Trinder
method, end point) and HDL-C by cholesterol kit
(Phosphotungstic acid method, end point).
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III. RESULTS
All participants (N=351) were divided into two groups on the
basis of physical activity level: sedentary (N=219; 62.40%) and
non-sedentary (N=132; 37.61%). Table 1 shows sedentary and
active lifestyle predominates in subjects who were younger and
elder than 50years, respectively. Figure 1 further represents
graphical presentation of age specific prevalence of active and
sedentary lifestyle.
Figure 1. Age-specific prevalence of active and sedentary lifestyle
A statistically significant active and sedentary lifestyle was
observed in men (72.72%; p<0.001) and women (64.38%;
p<0.001), respectively. The study further observed subjects
with low and high level of education leads a statistically
significant sedentary (68.48%; p<0.001) and active lifestyle
(49.23%; p<0.001), respectively.
Subjects belonging to middle socioeconomic status reported
physically active lifestyle (62.12%) as compared to their
counterparts (39.72%). Similarly, statistically significant
employed subjects were physically active (46.21%; p<0.001),
and unemployed individuals leads sedentary lifestyle (81.27%;
p<0.001).
Table 2 displays a statistically significant predisposition of
sedentary lifestyle to obesity (56.63%; p<0.05), and active
lifestyle to normal BMI range (34.10%; p<0.05). Figure 2
further shows the BMI specific prevalence of active and
sedentary lifestyle.
Subjects who consume alcoholic beverages reported a
statistically significant active (40.15%; p<0.001) than
sedentary lifestyle (20.54%; p<0.001). Furthermore, sedentary
subjects had a higher prevalence of sleep inadequacy (29.68%)
than non-sedentary participants (23.48%). The prevalence of
sedentary and active lifestyle was approximately the same
among both vegetarians (sedentary: 60.73%; active: 59.84%)
and omnivores subjects (sedentary: 39.26%; active: 40.15%),
respectively. A statistically significant stress levels had
predisposed the subjects to inactive (22.37%; p<0.05) than
active lifestyle (12.12%; p<0.05).
Table 1. Comparisons of the socio-demographic
in the all study subjects*
Category
Non sedentary Sedentary
(132)
(219)
AGE (years)
20-35
02.27% (03)
04.56% (10)
36-50
16.66% (22)
26.02% (57)
51-65
45.45% (60)
35.61% (78)
>65
35.60% (47)
33.78% (74)
SEX
Men
72.72% (96)
35.61% (78)
Women
27.27% (36)
64.38% (141)
EDUCATION
No/Little
20.45% (27)
36.98% (81)
Primary
30.30% (40)
31.50% (69)
Secondary
42.42% (56)
28.31% (62)
Graduation 06.81% (09)
03.19% (07)
SOCIO ECONOMIC STATUS
Middle
62.12% (82)
60.27% (132)
Upper
37.87% (50)
39.72% (87)
OCCUPATION
Retired
53.78% (71)
81.27% (178)
Employed
46.21% (61)
18.72% (41)
variables
p value
6.44
120.01
(<0.001)
14.58
(<0.001)
0.09
30.20
(<0.001)
*
parentheses represent absolute number of the subjects in a sample.
Table 3 reveals sedentary lifestyle had predisposed subjects to
higher prevalence of metabolic syndrome (29.68%),
hypertension (47.94%), obesity (56.63%; p<0.05) than
non-sedentary individuals (metabolic syndrome: 26.51%,
hypertension: 43.93%, obesity: 43.38%; p<0.05). Conversely,
dysglycemia (25.00%) and dyslipidemia (30.30%) was
observed more frequently in non-sedentary than sedentary
subjects (dysglycemia: 23.74%; dyslipidemia: 25.57%).
IV. DISCUSSION
This survey appears to be the first attempt to comprehensively
analyze sedentary behavior in the study area of Northern India
with the representative population sample >20 years; where
sedentary lifestyle was found prevalent among 62.40% of the
study population. Similarly, Varo et al. 21 has found sedentary
lifestyles ranged between 43.3% (Sweden) and 87.8%
(Portugal) across European countries. However, World Health
Organization has global projection for the prevalence of
physical inactivity between 31% and 51% across the 14
sub-regions with a global average of 41%.5 The application of
varying measures and protocols to estimate prevalence of
physical activity/inactivity makes results difficult to compare
and interpret, since large differences in estimates are
obtained.22 Brownson et al. 23 reported an ability to be
physically active was influenced by personal factors (time and
lack of motivation); social factors (family responsibilities, lack
of role models and support from family and friends),
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environmental factors (safety from crime and need to travel to
exercise facilities), and policies (few workplace policies that
encouraged physical activity).
Figure 2. Body mass index specific prevalence in active and sedentary
lifestyle
The current study reported an increase in sedentary lifestyle as
age advances (Figure 1). However, in comparison to active
lifestyle (Table 1), it was more prevalent in subjects with the
age range of 20-50 years than >50 years old. This can be
contributed to less time available for physical exercise in
subjects younger than 50 years due to involvement in jobs
and/or raising and looking after their children and elderly
family members. Subjects who were older than 50 years might
consider physical activity as a non pharmacological approach
to prevent, control and/or treat metabolic syndrome and its
components. Conversely, Varo et al. 21 found active lifestyle
among younger subjects and sedentary lifestyle in elder
subjects. Furthermore, Milanović et al. 24 found the age related
reduction in physical activity level and functional fitness in
both sexes due to the reduced muscle strength in both upper and
lower limbs; and changes in body-fat percentage, flexibility,
agility and endurance.
A significant sedentary lifestyle in women (64.38%; p<0.001)
than men (35.61%; p<0.001) has been found consistence to
Cabrera de León et al. 25 However, Vernon et al.26 found that
married women spent more time doing household activities
such as food preparation, housework and primary childcare
than leisure time physical activities. Moreover, Young and
Voorhees27 noticed that social and environmental factors did
not significantly influence physical activity level among
women. The study further found a statistically significant
relation of employment with active (46.21%; p<0.001), and
unemployment with sedentary lifestyle (81.27%; p<0.001)
which is consistent with Ishii et al. 28 Furthermore, Van
Domelen et al.29 revealed that women with full-time sedentary
jobs had less physical activity compared with unemployed
women. This observation, however, is in contrast to
unemployed men who are less physically active than their
employed male counterparts even those employed in sedentary
jobs. This shows women should increase their physical activity
levels to regain their gender advantage in terms of
cardiovascular risk. A statistically significant (p<0.001)
positive relation between the level of education and physical
activity in the present study is consistent with the data of
Thornórarinsson et al. 30 Conversely, Norman et al.31 reported
that those with high education had lower total physical activity
than those with elementary school. Furthermore, Shaw and
Spokane32 found that education-based disparities in physical
activity widened over time during early old age and suggests
the education influences health through promoting active
lifestyle behaviors, which accumulate and grow over time. On
the other hand, materialistic problems and a poor perceived
health experienced by lower educated people additionally
predicted educational differences in decreased leisure time
physical activity among older individuals.33 Sedentary lifestyle
(39.72%) was more prevalent in upper social class than middle
class subjects in the current study. Contrarily, Gidlow et al. 34
found higher levels of moderate-vigorous intensity physical
activity in those at the top of the socio-economic strata
compared with those at the bottom. Furthermore, the income
gradient increases with age and more financially costly forms
of physical activity are associated with larger socioeconomic
positions contributing to the financial and cultural barriers
which need to be overcome to reduce physical inactivity
prevalence.35
Table 2. Comparison of the lifestyle risk factors in
sedentary and non sedentary subjects*
Category
Non sedentary Sedentary
P value
(132)
(219)
BODY MASS INDEX
Normal
34.10% (45)
22.38% (49)
6.21
(<0.05)
Overweight
20.46% (27)
21.00% (46)
Obesity
45.45% (60)
56.63% (124)
ALCOHOL CONSUMPTION
Yes
40.15% (53)
20.54% (45)
15.72
(<0.001)
No
59.84% (79)
79.45% (174)
SLEEP
Adequate
76.51% (101)
70.31% (154)
1.58
In adequate
23.48% (31)
29.68% (65)
DIETARY HABITS
Vegetarian
59.84% (79)
60.73% (133)
0.04
Omnivores
40.15% (53)
39.26% (86)
STRESS LEVELS
Significant
12.12% (16)
22.37% (49)
5.74
(<0.05)
Insignificant 87.87% (116)
77.62% (170)
*
parentheses represent absolute number of the subjects in a sample.
A significant relation (Table 2) of alcohol consumption and
active lifestyle (40.15%; p<0.001) was found similar to French
et al. 36 which could be contributed to people socialized
drinking and further engaging themselves in frequent physical
exercise to compensate for the extra calories gained through
drinking or to counter-balance the negative health effects of
drinking. However, studies have found no association, 37 a
positive relationship, 38 or a negative correlation.39
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Table 3. Comparison of the metabolic syndrome and its
components in all the study subjects*
Category
Non
sedentary Sedentary (219)
p
(132)
valu
Health Disease Healthy Disease e
y
d
d
Metabolic
73.48% 26.51% 70.31%
29.68% 0.40
syndrome
(97)
(35)
(154)
(65)
Hypertensi 56.06% 43.93% 52.05%
47.94% 0.53
on
(74)
(58)
(114)
(105)
Dysglycem 75.00% 25.00% 76.25%
23.74% 0.07
ia
(99)
(33)
(167)
(52)
Obesity
54.53% 45.45% 43.38%
56.63% 4.14
(72)
(60)
(95)
(124)
(<0.
05)
Dyslipide
69.69% 30.30% 76.25%
25.57% 0.92
mia
(92)
(40)
(163)
(56)
*
parentheses represent absolute number of the subjects in a sample.
Sedentary lifestyle had predisposed the present study subjects
to sleep inadequacy (29.68%). Similarly, Reid et al. 40 noticed
that aerobic physical activity with sleep hygiene education is an
effective therapeutic approach to improve mood, sleep and life
quality in individuals with chronic insomnia. Conversely,
Sutton et al. 41 reported no relationship between a sedentary
lifestyle and insomnia. The current study found no relation of
dietary habits to sedentary behavior. Similarly, Agarwal et al. 42
observed high sedentary lifestyle has weak association with the
dietary covariates. Furthermore, Platat et al.43 found sedentary
behaviours and physical activity were separately linked to
distinct dietary habits, where physical activity appears to be
associated more with healthy choices and sedentary activities
with unhealthy choices. A statistically significant relation of
stress and sedentary behavior was found in the present study
(22.37%; p<0.05). Chronic stress have been reported with
binge or comfort type eating with preferences for more
palatable, higher fat and energy dense foods; reduced physical
activity levels; increased sedentary behaviors and increased
television viewing time.44
A higher prevalence (Table 3) of metabolic syndrome
(29.68%) among sedentary subjects was found similar to
Edwardson et al.45 Similarly, a statistically significant higher
prevalence of obesity (56.63%; p<0.05) among the present
study sedentary subjects was found consistent to Cabrera de
León et al.25 However, Ekelund et al.46 shows the physical
inactivity or sedentary behavior may be a consequence rather
than a cause of body-weight gain. Hypertension (47.94%) was
diagnosed more frequently in sedentary than non-sedentary
subjects. Similarly, Huai et al. 47 meta-analysis suggested an
inverse dose–response association between levels of
recreational physical activity and hypertension risk, however
noticed no significant association between occupational
physical activity and hypertension. Furthermore, Santulli et
al.48 recently highlighted that regular physical activity even
among elderly subjects ameliorates β adrenergic activity which
contributes to the clinical improvement of cardiovascular
health.
Dyslipidemia was observed more frequently in non-sedentary
(30.30%) than sedentary subjects (23.74%). Skoumas et al. 49
depicted physically active subjects had significantly lower
levels of total serum cholesterol, LDL-C, TGs,
apolipoprotein B and higher levels of HDL-C and
apolipoprotein A1. However, the Diabetes Prevention
Program50 experienced improvements in all the metabolic
syndrome
components
except
plasma
HDL-C
concentrations,
indicating
that
plasma
HDL-C
concentrations are somewhat resistant to modification
through general diet and physical activity changes.
Furthermore, dysglycemia (25.00%) was observed more
frequently in non-sedentary than sedentary subjects
(23.74%) in the present study. The Diabetes Prevention
Program50 found that lifestyle interventions including
∼150min/week of physical activity and diet-induced weight
loss of 5–7% reduced the progression risk of IGT to diabetes
mellitus by 58%. On the other hand, sedentary lifestyle is
associated with prolonged sitting time and fewer skeletal
muscle contractions which results in reduced lipoprotein
lipase activity and TGs clearance, reduced oral glucose
clearance load, and less glucose-stimulated insulin secretion,
and further predisposes to high glucose and lipid levels.51
However, a higher prevalence of dyslipidemia and
dysglycemia in the present study non-sedentary subjects
might have led them to live active lifestyle; however these
results are not consistent with previous findings and must be
further explored.
Study Limitations: Physical activity can be assessed
subjectively using self-reported questionnaire or objectively
(directly measured) using equipments such as pedometers or
accelerometers. Self-reported questionnaires are commonly
used in primary care centre because they are cheap and easy to
use. However, both methods have drawbacks and are subjected
to potential bias. Self-reported questionnaires may not be able
to capture all types of physical activity, whereas certain devices
may not be worn in activities such as swimming to measure
physical activity.22 Troiano52 recommended using both
objective and subjective measurements to validate the results
for better measurements and physical activity recording.
However, assessment of leisure-time physical activity has been
controversial and there is still a lack of a universal
measurement. The current study is based on self-reporting of
the physical activity where the trend to over-report the actual
level of physical activity is well known. Therefore, future
longitudinal studies including multiple, repeated, precise
measurements of the exposure and outcome from early age are
more likely to be able to address the causality.
V. CONCLUSIONS
Rising distribution of sedentary lifestyles and its association
with metabolic syndrome should be taken into account to
identify at-risk groups and develop strategies to discourage this
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behavior. Safety of the social environment and transportation;
city designs with proper sidewalks; personal motivation;
climbing stairs instead of using elevators; doing house and yard
work; use of standing desks and break-prompting software at
work place; further incorporating physical activity into the
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lunch and other breaks between productive work time; and
elaborating weight loss associations with physical activities
may make an important contribution to increase physical
activity and reduce sedentary behavior.
VI. ACKNOWLEDGEMENTS
We acknowledge all the patients who gave their permission to
be a part of this study and thankful to the entire staff of
polyclinic for their consistent support and Ms. Manjit Kaur for
her assistance in the statistical analysis.
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