Research Proposal
1. TITLE OF STUDY
PREVALENCE OF DIABETES AND ITS RELATION WITH CENTRAL OBESITY IN
GOKARNESHWOR
2. INTRODUCTION /BACKGROUND INFORMATION
Type 2 Diabetes Mellitus (T2DM) is characterized by a rise in blood glucose level as a result of
either impaired insulin secretion or insulin resistance or a combination of both.It is much more
common than type 1 diabetes mellitus (T1DM) or gestational diabetes 1. Diagnosis of T2DM
is made on the basis of an elevated random plasma glucose test (≥200mg per dl
with classic symptoms of hyperglycemia), fasting plasma glucose levels (≥126mg per dl after at
least an 8‑hour fast), 2‑hour post-glucose-load glucose level (≥200 mg per dl after 75 g oral
glucose) or HbA1c (≥6.5%) confirmed by repeat testing unless unequivocally elevated 2. Type 2
diabetes mellitus has been seen to be increasing steadily all over the world. According to the
International Diabetic Federation, global prevalence of diabetes in 20-79 year age group was
10.5% in 2021 which is expected to rise to 12.2% by 2045 3. About 60% of the world's diabetic
population belongs to Asia, where India and China are the top two epicenters 4. This global
epidemic has impacted Nepal as well. A population based nationwide survey conducted by
Namuna Shrestha et al from 2016-2018 estimated the prevalence of diabetes mellitus type 2 to
be 8.5% 5.As per the World Health Organization (WHO), there are 436,000 people living with
diabetes in Nepal and it is predicted that this number will rise to 1,328,000 by the year 2030(4).
Individuals with T2DM are at a higher risk of cardiovascular complications which is the
leading cause of morbidity and mortality in this population. Other significant issues with T2DM
include neuropathy, nephropathy and retinopathy which adds to the disease burden 6. The
dramatic increase in T2DM has also been accompanied by an increase in incidence of obesity
.According to a report published by World Obesity Federation , global prevalence of obesity is
estimated to be 18% by 2030 rising from 15% in 2020 7. This report further estimates that the
prevalence of obesity in adult men and women of Nepal will reach 4%and 8% respectively by
2030.Even though other causes like genetic predisposition and environment have a partial role
in determining individual susceptibility to T2DM; obesity has been seen to be an important
driver of the current global epidemic of diabetes 8.There are different parameters of obesity that
have been used for predicting T2DM. These include waist circumference, waist-to-height ratio
(WHtR) and body mass index (BMI). The waist-to-height ratio (WHtR), calculated by dividing
Waist Circumference by height, has gained a lot of attention recently as an anthropometric
index for measuring central adiposity 9.
This study uses quantitative methods to calculate prevalence of T2DM and to estimate its
relation with central obesity using WHtR among people in Gokarneshwor municipality.
(3) RATIONALE OF STUDY
Many middle and low income countries including Nepal, currently face a double burden of
T2DM. T2DM is strongly associated with obesity, as it stands out as a risk factor for T2DM.
Most of the patients are unaware of their disease and are thus more prone to developing diabetic
complications.
The current study aims to assess the prevalence of diabetes and its relation with central obesity
using WHtR. It emphasizes the need for therapeutic strategy in order to achieve a healthy body
weight in obese patients with T2DM. Our study indicates an important need to raise public
health awareness to address obesity and prevent the development of comorbid conditions
associated with diabetes.
(4) LITERATURE REVIEW
The accumulation of an excessive amount of body fat leads to a constellation of metabolic
abnormalities and diseases[1]. Type 2 Diabetes Mellitus has also been found to be
attributable to obesity. Furthermore, clinical evidence suggests that the association of
diabetes with central obesity is stronger than the association with general obesity. Studies
using computed tomography and magnetic resonance imaging have provided further
evidence to support that central obesity is the major contributor to the metabolic
complications(2).
In their study, Goergios S. Papaetis and colleagues examined the possible cellular
mechanisms that connect central obesity with defects in the insulin pathway required to
cause diabetes(3) .They found that beta cell dysfunction induced by adiposity and insulin
resistance is the link between obesity and diabetes mellitus. Moreso, central obesity was
found to be a key player in the causation of diabetes . This relationship between central
obesity and Type 2 Diabetes Mellitus has further been observed in numerous other studies.
A systematic review and meta-analysis conducted by Temesgen Muche Ewunie et al in
Ethiopia showed that burden of diabetes mellitus was almost 6 times higher in centrally
obese people (4). Corroborating to this finding, a quantitative cross-sectional study
conducted in South Africa by Mobitsela H. Mphasa et al showed that prevalence of central
obesity was very high (75) among diabetic patients.(5).Likewise, a retrospective cohort
study conducted in Japan by chhongchun Cau et al showed that centrally obese people are
at 72% higher risk of developing diabetes mellitus than the non-central obese (6).The link
between central obesity and type 2 diabetes is further seen in a systematic review and
dose-response meta analysis of cohort studies conducted by Ahmad Jayedi et al(7). Their
study used waist circumference and Waist-Height Ratio as the parameters for measuring
central Obesity. The authors in the study found that the relative risk of developing Diabetes
Mellitus increases by 1.61 and 1.73 when Waist Circumference and Waist-Height Ratio
increases by 10 cm and 0.1 unit respectively.
Waist-Height Ratio and Waist Circumference are the widely used anthropometric indicators
of central obesity. Waist circumference, however, is affected by age, gender, and ethnicity,
making a single cutoff difficult [8] WHtR, on the other hand, has been found to be a
sensitive universal screening tool to detect health risks (9). A large survey conducted on
Iranian children and adolescents as a national school-based surveillance study in 2015 by
Roya Kelishad et al concluded that the Waist-Height Ratio ≥ 0.5 is a simple and useful
screening tool(10). The study also found Waist-Height Ratio to be better than Waist
Circumference, for predicting general and central Obesity. Likewise a study from
Prospective Epidemiological Research Studies (PERSIAN) conducted by Yahya Pasdar et al
in the Iranian Kurdish cities, also concluded that Waist-Height Ratio might be a better
predictor than Waist Circumference and BMI for cardiovascular diseases(11).
#References :
1. https://www.cell.com/cell-metabolism/fulltext/S1550-4131(21)00631-8?_returnURL=https
%3A%2F%2Flinkinghub.elsevier.com%2Fretrieve%2Fpii%2FS1550413121006318%3Fsh
owall%3Dtrue
2. https://nmcth.edu/images/gallery/Editorial/beVZNa_shah.pdf)
3. https://www.ncbi.nlm.nih.gov/pmc/articles/pmid/26170839/
4.https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9187119/
5.https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9210144/
6.
7.https://pubmed.ncbi.nlm.nih.gov/32967840/
8.https://doi.org/10.1016%2Fj.jpeds.2014.02.018
9. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5118501/
10. https://www.ncbi.nlm.nih.gov/pmc/articles/pmid/25789140/
11.https://www.nature.com/articles/s41598-020-73224-8
Keywords : Diabetes Mellitus; Obesity; Prevalence; Waist Circumference; Waist-Height Ratio.
(5) CONCEPTUAL FRAMEWORK
(6) OBJECTIVES OF STUDY
(a) General objective
To estimate the prevalence of diabetes and its relation with central obesity in
Gokarneshwor
(b) Specific objectives
1) To calculate the prevalence of type 2 DM
2) To understand the relationship of age and sex with type 2 diabetes mellitus.
3) To calculate the prevalence of central obesity in diabetic population
(7) RESEARCH DESIGN
We want to analyze the prevalence of central obesity in a Diabetic population. It is a
quantitative study. A community based cross-sectional study was conducted in
Gokarneshwor. The study population were people of age 18 years and above. They were
interviewed using a questionnaire given by the Community Medicine department. The
questionnaire included personal information and diabetic status.
The equation of calculating sample size is as follows:
Sample size(S)= z2p(1-p)/e2
= 1.96 × 1.96 × 0.5(1 - 0.5) / (0.1 × 0.1)
= 96
Where:
z= 1.96 taking level of confidence 95%
p= prevalence of Central Obesity in diabetics;since it is unknown assumed to be 50%
e= the margin of error 10%
For finite population,
Sample Size(S")= S/(1 + S/N)
=96 /(1+ 96/N)
=
Where, N= Estimated Diabetic population under study
=Total population under study<yo hamro commed families ma kati ota adults xan
over 18 sodhera lekhne;=voli class ma timi haru circulate garera sodha yo>*0.96
Therefore, the required sample size is
Method of data collection - Anthropometric measurements by the students after visiting the
families.
Data management method - Microsoft Excel
Data analysis tool - R studio
Cross sectional study was carried out on families of Gokarneshwor area . The study sample
consists of people belonging to both sexes independent of age. The sample size was
calculated with the help of equation: n=z2p(1-p)/e2. Convenience sampling technique was
followed in the sampling procedure. The collection of data was carried out by undergraduate
medical students from the families alloted by the Community Medicine department.
Anthropometric measurements included Waist Circumference and Height measured with the
help of measuring tape and stadiometer. Waist-Height Ratio was calculated. Normal
Waist-Height Ratio is below 0.5.
Permission to conduct the study was obtained from the Research and Ethics Committee at
Nepal Medical College and Teaching Hospital, Jorpati. Confidentiality of data was
maintained throughout the study.
GANTT CHART
Tasks
2022
September
October
2023
November
December January
February
March
Literature Review
Proposal Writing
Ethical Clearance
Data collection
and analysis
Manuscript
preparation
Manuscript
submission
Publication
(8) LIMITATION & DELIMITATION:
The study will only include those who have been already diagnosed with Diabetes Mellitus
in the past and will not include Diabetic Mellitus population unaware of their diagnosis. The
sample size is too small to establish any definitive conclusion.The study design we will be
using is cross sectional study so there may be some recall bias.Moreover, the
anthropometric data was collected by different individuals with different instruments so
there is likely to be measurement and instrumental error.
During this study the genetic determinant for Obesity is not taken under consideration.Also,
the relation of physical exercise and daily dietary intake with Obesity is not considered in
this study.
(9) EXPECTED RESULTS
Table 1-Socio-demographic characteristics of studied cases,
PARAMETER
frequency (n= )
percentage
AGE (in years)
SEX
male
female
Table 2- Prevalence of DM among studied cases
Diabetes
Frequency(n)
Percentage(%)
Not present
Present
Total
Table 3-Relationship between diabetes, age, Sex, and waist to height ratio among studied cases
VARIABLES
DIAGNOSIS
normal
(n= )
age (year)
sex
male
female
waist-height
ratio
<0.5
>0.5
diabetic
(n= )
TOTAL
(n= )
Chi-square
p-value
.
(10) REFERENCE
1. DeFronzo RA, Ferrannini E, Groop L, Henry RR, Herman WH, Holst JJ, et al. Type 2 diabetes
mellitus. Nat Rev Dis Primers [Internet]. 2015 Jul 23 [cited 2022 Sep 20] ;1(1):1–22. Available
from: https://www.nature.com/articles/nrdp201519 (DeFronzo)
2. American Diabetes Association. Standards of medical care in diabetes—2014. Diabetes Care
[Internet]. 2013 Dec 16 [cited 2022 Sep 20];37 Suppl 1 (Supplement_1):S14-80. Available from:
https://doi.org/10.2337/dc14-S014
3. Sun H, Saeedi P, Karuranga S, Pinkepank M, Ogurtsova K, Duncan BB, et al. IDF Diabetes
Atlas:
Global, regional and country-level diabetes prevalence estimates for 2021 and projections for 2045.
Diabetes Research and Clinical Practice [Internet]. 2022 Jan 1;183(109119). Available
from: https://doi.org/10.1016/j.diabres.2021.109119
4. Baral S, Uprety S, Lamichanne B. Diabetes [Internet]. 2016 Feb [cited 2022 Sep]. Available
from:
https://www.herd.org.np/uploads/frontend/Publications/PublicationsAttachments1/1480578900-Bac
kgrounder%20on%20DIABETES.pdf
5. Shrestha N, Karki K, Poudyal A, Aryal KK, Mahato NK, Gautam N, et al. Prevalence of diabetes
mellitus and associated risk factors in Nepal: findings from a nationwide population-based survey.
BMJ Open [Internet]. 2022;12(2):e060750. Available from:
http://dx.doi.org/10.1136/bmjopen-2022-060750
6. Lobstein T, Brinsden H, Neveux M. World Obesity Atlas 2022 [Internet]. 2022 Mar 4 [cited
2022 Sep 27];
Available from:
https://policycommons.net/artifacts/2266990/world_obesity_atlas_2022_web/3026660/
7. Urbanavičius V, Abalikšta T, Brimas G, Abraitienė A, Gogelienė L, Strupas K. Comparison of
changes in Blood Glucose, Insulin Resistance Indices, and Adipokine Levels in Diabetic and
Nondiabetic Subjects With Morbid Obesity After Laparoscopic Adjustable Gastric Banding.
Medicina [Internet]. 2013 Jan 26;49(1):2. Available from:
https://doi.org/10.3390/medicina49010002
8. Yoo EG. Waist-to-height ratio as a screening tool for obesity and cardiometabolic risk. Korean J
Pediatr [Internet]. 2016 Nov 18;59(11):425–31. Available from:
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5118501/