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Burden of Obesity in Sedentary Jobs

Authors:
  • Hi-tech Medical college and Hospital, Rourkela

Abstract and Figures

Introduction: Obesity is a disease that adversely affects mortality, morbidity, and quality of life (QOL), as a result of its associated complications, like cardiometabolic, mechanical and lifestyle based. The health risks include diabetes, cardiovascular disease (CVD), hypertension, dyslipidemia, sleep apnea, musculoskeletal disease, infertility, and dementia. Moderate weight loss (5-10%) has been associated with improvements in these obesity-related comorbidities. Objectives: With an aim to estimate the frequency of overweight and obesity in the adult population with sedentary life style, a camp was organized at a private firm to screen the employees. Materials and methods: A total of 218 individuals were selected for analysis. Height, weight, pulse, blood pressure (BP), waist circumference, and body mass index (BMI) were measured. Plasma fasting sugar and fasting serum lipid profile were analyzed. Results: The frequency of normal BMI in the study population was found to be 27.5%. The total frequency of overweight subjects was 48.6% and that of obese subjects was 23.9%. The raised BMI could be significantly associated with high blood pressure, waist circumference, diet and exercise as well as glycemic status. All lipid parameters except HDL depicted significant odds ratio (OR) and thus predicted the risk factor for obesity. Conclusion: Obesity has assumed an epidemic proportion and necessary intervention are important to prevent morbidity and mortality.
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IOSR Journal of Dental and Medical Sciences (IOSR-JDMS)
e-ISSN: 2279-0853, p-ISSN: 2279-0861.Volume 18, Issue 11 Ser.8 (November. 2019), PP 51-54
www.iosrjournals.org
DOI: 10.9790/0853-1811085154 www.iosrjournals.org 51 | Page
Burden of Obesity in Sedentary Jobs
Dr Brijesh Mukherjee1, Dr Gargi Sarangi2
1Associate Professor (Biochemistry), Hi-tech Medical College and Hospital, Rourkela, Odisha.
2Consultant Physician, Sambandh Finserve Private Limited, Rourkela, Odisha.
Corresponding author: Dr Brijesh Mukherjee,
Associate Professor, Dept. of Biochemistry, Hi-tech Medical College and Hospital, Rourkela- 769004, Odisha,
India.
Abstract: Introduction: Obesity is a disease that adversely affects mortality, morbidity, and quality of life
(QOL), as a result of its associated complications, like cardiometabolic, mechanical and lifestyle based. The
health risks include diabetes, cardiovascular disease (CVD), hypertension, dyslipidemia, sleep apnea,
musculoskeletal disease, infertility, and dementia. Moderate weight loss (5-10%) has been associated with
improvements in these obesity-related comorbidities.
Objectives: With an aim to estimate the frequency of overweight and obesity in the adult population with
sedentary life style, a camp was organized at a private firm to screen the employees.
Materials and methods: A total of 218 individuals were selected for analysis. Height, weight, pulse, blood
pressure (BP), waist circumference, and body mass index (BMI) were measured. Plasma fasting sugar and
fasting serum lipid profile were analyzed.
Results: The frequency of normal BMI in the study population was found to be 27.5%. The total frequency of
overweight subjects was 48.6% and that of obese subjects was 23.9%. The raised BMI could be significantly
associated with high blood pressure, waist circumference, diet and exercise as well as glycemic status. All lipid
parameters except HDL depicted significant odds ratio (OR) and thus predicted the risk factor for obesity.
Conclusion: Obesity has assumed an epidemic proportion and necessary intervention are important to prevent
morbidity and mortality.
Keywords: Obesity; dyslipidemia; hypertension
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Date of Submission: 06-11-2019 Date of Acceptance: 21-11-2019
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I. Introduction:
World Health Organization (WHO) defines obesity as body mass index (BMI) greater than or equal to 30
kg/m2. BMI is calculated by dividing the body weight in kilograms (kg) by the square of the height in
meters (m).
Worldwide obesity has nearly tripled since 1975.
Most of the world’s population lives in countries where overweight and obesity kills more people than
underweight.
41 million children under the age of 5 were overweight or obese in 2016. Over 340 million children and
adolescents aged 5-19 were overweight or obese in 2016.
In 2016, more than 1.9 billion adults, 18 years and older, were overweight. Of these over 650 million were
obese.
39% of adults aged >18 years were overweight and 13% were obese
Worldwide, the highest percentage of obese seen in Cook Islands of Australia, followed by Middle
Eastern countries (like Qatar, Kuwait) and developed countries like United States of America, Australia,
Canada, and New Zealand. In India, 11.0% of men and 15.0% of women are obese. The state of Punjab has a
maximum percentage of obese, female being 30%, and male being 22% of general population.
Obesity is generally caused by physical inactivity rather than consuming more calories, for example,
spending lots of time sitting down at desks, on sofas, watching TV, using lift rather than stairs, or in the car;
children playing indoor games more than outdoor, use of mobile and a computer at peak. Obesity is an
increasingly common problem because of our lifestyle which involves eating excessive amounts of high-calorie
food and particularly those which are fatty and sugary. Processed foods and some high energy foods are cheaper
than fruits/vegetables. Fast food meals have tripled its frequency, leading to quadrupling risk of obesity. The
excess energy is stored by the body as fat.
Burden of Obesity in Sedentary Jobs
DOI: 10.9790/0853-1811085154 www.iosrjournals.org 52 | Page
BMI of 30 to 35kg/m2 reduces life expectancy by 2 to 4 years, while severe obesity reduces life expectancy by
10 years. For individuals aged between 30 and 42 years, the risk of death increases by 1% for each 0.5 KG
weight rise. For individuals between the ages of 50 and 62, this figure becomes 2% for each 0.5 KG weight rise.
II. Objectives:
With an aim to screen for obesity, in the adult population of Rourkela city and estimate the frequency of
overweight and obesity cases in the community involved in sedentary jobs, a camp was arranged in a private
firm.
III. Materials And Methods:
A camp was organized at Sambandh Finserve Private Limited, Rourkela after obtaining prior
permission of the management of the firm. Most of the employees of the firm were involved in desk jobs with
minimal physical activity. Concise instructions and preparatory information (overnight fasting of 8 hours)
inscribed in pamphlets, in Odia and English, were distributed among all the employees. This camp was
approved by our Institutional Ethics Committee.
A total of 218 individuals got enrolled for the camp. All individuals were asked to sign the informed
consent form after registration. Height, weight, and waist circumference were measured, and BMI was
calculated for all of them. Pulse and BP were measured by manual sphygmomanometer in sitting position.
Fasting plasma glucose and serum lipid profile (cholesterol, TG, HDL) were estimated immediately
after in automated analyzer (Erba Manheim EM 200) and HbA1c in D10 hemato analyzer. The LDL was
calculated by Friedewald’s method.
Desirable ranges for the variables measured were as per Atherosclerotic Cardiovascular Disease Risk
Categories given in Table 1.[1]
Statistical analysis was performed using Graph Pad Prism. Causal relationship between the variables
was determined by chi-square (χ2) test. The OR with 95% confidence interval (CI) was estimated using logistic
regression predicting the factors associated with obesity. For two-tailed p-values of <0.05 were considered
significant, with 95% CIs.
IV. Results:
The data analysis revealed that 67.9% (n = 148) of the participants were young adults of age group less
than 40 years. The frequency of overweight was calculated to be 48.6% (106/218) in this community (Table 2).
The incidence of obesity was observed to be 23.9% (52/218).
The mean age of participants was 37.4 ± 11.1 years, frequency of hypertension was 40.82%, 53.67%
had greater waist circumference, and 28.4 were hyperglycemic, of which 11% (n = 24/158) were diabetic.
Addiction history was positive in 41.28% cases and the diet of 68.8% study subjects were found to be
mixed.63.3% subjects did not do any exercise. Dyslipidemia was represented in 57.5% of the study population.
The χ2 test in Table 3 revealed that blood pressure, waist circumference, diet and exercise have a
significant (p < 0.05) difference in proportion within each group.
The patient with diabetes and prediabetes have high risk for obesity (p=0.00029).
As shown in Table 4, associated hyperlipedemia increases the risk for obesity. Highest risk was
associated with cholesterol and least with HDL.
Pearson correlation analysis demonstrated significant positive correlation between obesity with BP
(p =0.0077), waist circumference (p < 0.001), plasma glucose (p=0.0011), TC (p =0.0181) and TG (p=0.0381) as
tabulated in Table 5.
Table 1: Desirable range for the measured variables
Variables
Desirable range
Waist circumference
Men: <94 cm; Women: <80 cm
BMI
18.524.9 kg/m2
Pulse
60-90 bpm
BP
<130/80
FPG
<100 mg/dl
HbA1c
<5.7%
Serum cholesterol
<200 mg/dl
Serum TG
<150 mg/dl
Serum LDL
<130 mg/dl
Serum HDL
>50 mg/dl
Serum VLDL
<30 mg/dl
Burden of Obesity in Sedentary Jobs
DOI: 10.9790/0853-1811085154 www.iosrjournals.org 53 | Page
Table 2: Distribution of study population according to body mass index (BMI)
Dependent variables according to BMI in
kg/m2
Frequency
Percentage
Normal (18.5-24.9)
60 (n=218)
27.5
Overweight (25.0-29.9)
106 (n=218)
48.6
Obese (≥30.0)
52 (n=218)
23.9
Table 3: Percentage distribution of obesity status by physiological characteristics and glycemic status by
chi-squared test.
Variable
Normal
Overweight
Total
p-value
Age group in years
20-40
>40
40
20
76
30
148
70
0.4256
Gender
Males
Females
38
22
60
46
128
90
0.7453
BP (mm Hg)
Normotensive
Hypertensive
47
13
55
51
129
89
0.0019
Waist circumference
(cm)
Normal
High
50
10
30
76
101
117
<0.0001
Diet
Vegetarian
Mixed
10
50
42
64
68
150
0.0091
Addiction history
Positive
Negative
20
40
44
62
90
128
0.2022
Exercise
Yes
No
40
20
30
76
80
138
<0.0001
Glycemic status
Normoglycemic
Prediabetes
Diabetes
50
7
3
80
20
6
156
38
24
0.00029
*p < 0.05 significant difference
Table 4: Lipid profile association with BMI
Variables
Odds ratio
95% CI
Lower
95% CI
Higher
p-value
Total cholesterol (mg/dl) Desirable (<200)
Moderate and high risk (≥200)
3.75
2.75
5.11
<0.01**
TG (mg/dl)
Desirable (<150)
Moderate and high risk (≥150)
3.18
2.43
4.16
<0.01**
HDL (mg/dl)
Desirable (≥50)
Moderate and high risk (<50)
1.76
1.25
2.47
0.12
LDL (mg/dl)
Desirable (<129)
Moderate and high risk (≥129)
3.28
2.46
4.37
<0.01**
(Logistic regression, *p < 0.05 significant difference)
Table 5: Pearson correlation between BMI and physiological and biochemical parameters
BMI
Pearson correlation
Significance (two tailed)
n
Age
0.12
0.077
218
Pulse
0.10
0.141
218
BP
0.18
0.0077*
218
BMI
1
218
Waist circumference
0.27
<0.001**
218
Plasma glucose
0.22
0.0011*
218
Cholesterol
0.16
0.0181*
218
TG
0.14
0.0381*
218
Burden of Obesity in Sedentary Jobs
DOI: 10.9790/0853-1811085154 www.iosrjournals.org 54 | Page
LDL
0.11
0.1053
218
HDL
-0.08
0.2395
218
*p < 0.05 significant difference
V. Discussions:
The prevalence of overweight (48.6%) and obesity (23.9%) recorded in the present study are more than
to 36.0% and 6.5% for overweight and obesity, respectively, reported among senior civil servants in Kuala
Lumpur[2] and 33.4% for overweight/obesity reported among white collar employees in Nepal.[3]
Previously, higher lipid profile and obesity have been reported among hypertensive Nigerians [4]
which was similar in our study. The positive correlations observed between the lipids and BMI were in
corroboration with previous studies,[5,6] and reaffirmed the role of lipids in the pathophysiology of overweight
and obesity
Patients with type 2 diabetes have increased risk of cardiovascular disease associated with atherogenic
dyslipidaemia.[7] This signifies that individuals having diabetes-associated obesity are more prone to develop
cardiovascular disease than obese non-diabetic individuals. It has been well documented that high levels of
cholesterol and LDL play a significant role in the development of arteriosclerosis and hence coronary artery
disease.[8,9]. We found out that diabetics and prediabetics are at more risk for obesity which increases the risk
of CVD in the subjects.
Our study showed that diet played an important role in obesity which is again in accordance to different
studies all over the world. The role of addiction (smoking, alcohol) in obesity was confirmed in our study.
Prevention is the key to controlling the obesity epidemic. The various prevention strategies
recommended by the WHO include; a universal or public health approach directed at all members of a
community; a selective approach directed at high-risk individuals and groups; and a targeted approach directed
at individuals with weight-related problems and those at high risk of diseases associated with overweight and
obesity. Of these the population-wide obesity prevention programs have a greater potential of stemming the
obesity epidemic and being more cost-effective than the clinic-based treatments.[10].
VI. Conclusion:
India is going through an economic development along with nutrition transition and experiencing an
increase in the prevalence of obesity and obesity-related illnesses. There is the need now, more than ever, to set
up a multi-sectoral taskforce to assess the national prevalence, trends, determinants and impact of obesity and its
related NCDs (non communicable diseases) on the society as a whole and on health care provision in the
country.
References:
[1]. Jellinger PS, Smith DA, Mehta AE, Ganda O, Handelsman Y, Rodbard HW, Shepherd MD, Seibel JA, AACE Task Force for
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Management of Dyslipidemia and Prevention of Atherosclerosis: executive summary. Endocr 2012 MarApr;18(2):269-293.
[2]. Liew YM, Zulkifli A, Tan H, Ho YN, Khoo KL. Health status of senior civil servants in Kuala Lumpur. Med J
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[3]. Simkhada P, Poobalan A, Simkhada PP, Amalraj R, Aucott L. Knowledge, attitude, and prevalence of overweight and obesity
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[4]. Idemudia JA, Ugwuja EI. Plasma lipid profiles in hypertensive Nigerians. Internet J Cardiovasc Res. 2009:6.
[5]. Akpa MR, Agomouh DI, Alasia DD. Lipid profile of healthy adult Nigerians in Port Harcourt, Nigeria. Niger J Med. 2006;15:137
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[6]. Hajian-Tilaki KO, Heidari B. Prevalence of obesity, central obesity and the associated factors in urban population aged 20-70 years,
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[7]. Toth PP. Effective management of the type 2 diabetes patient with cardiovascular and renal disease: Secondary prevention strategies
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[8]. Pyörälä K, Laakso M, Uusitupa M. Diabetes and atherosclerosis: An epidemiologic view. Diabetes Metab Rev 1987;3:463-524.
[9]. Kannel WB. Lipids, diabetes, and coronary heart disease: Insights from the Framingham Study. Am Heart J 1985;110:1100-7.
[10]. World Health Organisation, author. Obesity: preventing and managing the global epidemic: report of a WHO consultation, Geneva.
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Dr Brijesh Mukherjee. Burden of Obesity in Sedentary Jobs. IOSR Journal of Dental and
Medical Sciences (IOSR-JDMS), vol. 18, no. 11, 2019, pp 51-54.
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World Health Organisation, author. Obesity: preventing and managing the global epidemic: report of a WHO consultation
World Health Organisation, author. Obesity: preventing and managing the global epidemic: report of a WHO consultation, Geneva. 2000. WHO Technical Report Series 894.