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Background: Type 2 diabetes which has insulin resistance as a major risk factor among other non-communicable diseases is a major public health concern with increased significance and prevalence worldwide. Cancer on the other hand was a leading cause of death worldwide in 2008 based on data from the WHO and also 3rd leading cause of death in Malaysia ministry of health hospitals. Studies have found links between carcinogenesis and insulin resistance which has been attributed to hyperinsulinemia. However, studies on the South-east Asian/ Malaysia population are largely absent. Insulin sensitivity is known to differ across different ethnicities with South-east Asians and Asian Indians least insulin sensitive. The aim of this study was to determine the association between cancer and Insulin resistance (IR) regardless of the aforementioned trait. Design: Case-control study. Method: Fasting insulin and glucose concentrations (which were used to derive the Homeostasis model assessment insulin resistant HOMA-IR) were determined in 100 respondent of which 45 were cancer patients and 55 in the control group. Data on demographics, anthropometrics, lifestyle and physical activity level and metabolic parameters were also determined in all respondents. Independent sample t-test was used to check for association between cancer and HOMA-IR and logistic regression was used to control for other co-factors. Results: From the results, there was significant difference between the mean HOMA-IR of the cancer group (3.00 ±1.52) compared to that of the controls (2.07 ±0.69) with a p-value of 0.001. Insulin Resistance was also independently associated with cancer (adjusted OR= 12.25. 95%CI = 3.20- 46.83) There was also significant association between obesity and cancer (adjusted OR = 3.33, 95% CI = 1.08 – 10.31). Conclusion: Even though there were some justifiable discrepancies, significant association was seen between cancer and HOMA-IR in this Malaysian population. These results are in line with previous studies which check for association in select cancers. Keywords: Cancer, Insulin Resistance, HOMA-IR, Non-diabetic, Malaysia, Epidemiology.
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International Journal of Public Health and Clinical Sciences
e-ISSN : 2289-7577. Vol.2:No. 2
March/April 2015
Ezinne Igwe, Ahmad Zaid Fattah Azman, Abdul Jalil Nordin, Norhafizah Mohtarrudin
21
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ASSOCIATION BETWEEN HOMA-IR AND CANCER IN A
MEDICAL CENTRE IN SELANGOR, MALAYSIA
Ezinne Igwe1, Ahmad Zaid Fattah Azman1*,
Abdul Jalil Nordin2, Norhafizah Mohtarrudin3
1Department of Family Medicine, Faculty of Medicine and Health Sciences, Universiti Putra
Malaysia, Selangor, Malaysia
2 Centre for Diagnostic Nuclear Imaging, Universiti Putra Malaysia.
3 Department of Pathology, Faculty of Medicine and Health Sciences, Universiti Putra
Malaysia.
*Corresponding author: Ahmad Zaid Fattah Azman; email: azfamy@gmail.com,
Tel:+6016-6521141, Fax: +603-89450151
ABSTRACT
Background: Type 2 diabetes which has insulin resistance as a major risk factor among other
non-communicable diseases is a major public health concern with increased significance and
prevalence worldwide. Cancer on the other hand was a leading cause of death worldwide in
2008 based on data from the WHO and also 3rd leading cause of death in Malaysia ministry
of health hospitals. Studies have found links between carcinogenesis and insulin resistance
which has been attributed to hyperinsulinemia. However, studies on the South-east Asian/
Malaysia population are largely absent. Insulin sensitivity is known to differ across different
ethnicities with South-east Asians and Asian Indians least insulin sensitive. The aim of this
study was to determine the association between cancer and Insulin resistance (IR) regardless
of the aforementioned trait.
Design: Case-control study.
Method: Fasting insulin and glucose concentrations (which were used to derive the
Homeostasis model assessment insulin resistant HOMA-IR) were determined in 100
respondent of which 45 were cancer patients and 55 in the control group. Data on
demographics, anthropometrics, lifestyle and physical activity level and metabolic parameters
were also determined in all respondents. Independent sample t-test was used to check for
association between cancer and HOMA-IR and logistic regression was used to control for
other co-factors.
Results: From the results, there was significant difference between the mean HOMA-IR of
the cancer group (3.00 ±1.52) compared to that of the controls (2.07 ±0.69) with a p-value of
0.001. Insulin Resistance was also independently associated with cancer (adjusted OR= 12.25.
95%CI = 3.20- 46.83) There was also significant association between obesity and cancer
(adjusted OR = 3.33, 95% CI = 1.08 10.31).
Conclusion: Even though there were some justifiable discrepancies, significant association
was seen between cancer and HOMA-IR in this Malaysian population. These results are in
line with previous studies which check for association in select cancers.
Keywords: Cancer, Insulin Resistance, HOMA-IR, Non-diabetic, Malaysia, Epidemiology.
International Journal of Public Health and Clinical Sciences
e-ISSN : 2289-7577. Vol.2:No. 2
March/April 2015
Ezinne Igwe, Ahmad Zaid Fattah Azman, Abdul Jalil Nordin, Norhafizah Mohtarrudin
22
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1.0 Introduction
The worldwide public health burden of cancer has become tremendous. In 2008, it was the
most common cause of death worldwide (WHO, 2011) and the 3rd most common cause of
death in Malaysia Ministry of Health hospitals in 2007. In Malaysia, there has been a
noticable increase in cancer incidence. In the 2006 report of the National cancer registry, the
incidence of the 3 most common cancers were; Breast (16.5%), colorectal (13.2%) and lung
(9.4%), a year later in 2007, an increase was noticeable in some of these values. The 2007
report of the NCR had Breast cancer incidence at 18.0%, Colorectal at 12.3% and Trachea,
Bronchus, Lung at 10.2% (Ariffin & Saleha, 2007).
Even though cancer is a multifactorial disease caused by external factors (tobacco, chemicals,
radiation, and infectious organisms) and internal factors (inherited mutations, hormones,
immune conditions, and mutations that occur from metabolism), one of the persistent
characteristic of cancer cells is its ability to multiply uncontrollably and reject programmed
death (Levin et. al., 2004, Darbre, 2011, Narayanan et. al., 2010, Rook & Dalgleish, 2011,
Roberts et. al., 2012, Baglietto et. al., 2010, Grivennikov et. al., 2010, Dang, 2012)
The exact role of insulin resistance (IR) in the development as well as progression of cancer
has yet to be well established. In humans, insulin functions to balance carbohydrate, protein
and lipid metabolism. In the digestion of carbohydrate, insulin regulates glucose stable
equilibrium and promotes glucose usage. A defect in this process causes pancreatic β cells to
increase insulin production which leads to a state of chronic hyperinsulinemia which is insulin
resistance (Gungor et. al., 2005).
Insulin resistance is known to inhibit the production of insulin-like growth factor-1 binding
proteins thereby increasing the level of circulating free IGF-1 in the blood (Harish et. al.,
2007). The action of insulin as a mitogen on both normal and malignant tissue via the IGF1
system is considered the most plausible mechanism linking insulin resistance to cancer. A
number of studies have attributed the association between insulin resistance and cancer to this
(LeRoith & Roberts Jr, 2003, Abbasi et. al., 2010, Albanes et. al., 2009, Goodwin et. al.,
2009, Garmendia et. al. 2007). However, most of these findings are taken from the western
population. To the best of our knowledge, there are only a few published reports on this
association in the Asian population (Sato et. al., 2011, Shebl et. al., 2011, Zhang et. al., 2010)
and none in the South-east Asian/Malaysian population.
Although the prevalence of IR in Malaysia is unknown, the progressive increase in Type 2
Diabetes Milletus (TTDM) suggests that similar trend maybe occurring insidiously (NHMS
II, 2008). Asians especially South-east Asians and Asian Indians have been shown to be much
more prone to insulin resistance (leading up to Type 2 diabetes) compared to Caucasians even
with relatively little weight gain and much lower BMI (Dickson et. al., 2002). Thus, it is
pertinent to also determine the presence of this association in South-east Asians (Malaysians)
as it could elucidate further on the aetiology of common cancers and also offer more insights
on the prevention and management.
The aim of this case-control study is to assess the association between IR and cancer in this
Malaysian population and to determine whether this association is affected other known co-
factors (obesity, lipoproteins, and physical inactivity, hypertension and lifestyle behaviours)
of insulin resistance.
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2.0 Materials and Methods
2.1 Study Location and Study Subjects
This case- control study was conducted in the in a government medical institution in the state
of Selangor. Both centres are located next to each other and receive patients from the central
region of Malaysia, the Klang Valley. As of 2012, the Klang valley is home roughly to about
7.5million people.
Cases were newly diagnosed cancer patients who came in for imaging scan and histologically
confirmed cancer patients in the surgical ward of the institution. Non-cancer patients with no
recent history of malignancy were included as controls. Both cases and controls were diabetes
free. The respondents were age (±5 years) and sex-matched and they were consecutively
recruited.
Using mean and standard from a previous similar study (Garcia et. al. 2005), a sample size of
80 was calculated using the formula for case-control studies by Lehr (1992) for analysis by
independent t-test to find a minimum difference between the mean HOMA-IR of the cancer
and control group. However, the final recruitment of subjects was 45 cases and 55 controls
(100). Alpha was set at 0.05
2.2 Ethical Considerartions
This study was approved by the Medical Research Ethics Committee, Faculty of Medical and
Health Sciences, University Putra Malaysia and the Ministry of Health Medical Research
Ethics Committee.
All patients were informed that joining in the study was voluntary, anonymous and
confidential. An information sheet was provided to respondents concerning the purpose of the
study, how information would be processed, stored and used. Contact information was also
provided for any questions that could arise about the study.
2.3 Data Collection
2.3.1 Questionnaire and physical measurement
A self developed questionnaire was used to gather information on the demographics and
socioeconomic status, smoking status, alcohol consumption, and family history diabetes of the
responders.
The short International Physical Activity Questionnaire (IPAQ) was used to collect
information on activity levels.
Obesity defined by BMI of equal 30kg/m2 and over was calculated using weight and height
values determined using the SECA electronic weighting and measuring station.
Blood pressure was measured using a Mec 1000 portable multi parameter patient monitor.
Hypertension was defined as a systolic blood pressure of >140mmHg and/or >90mmHg.
Waist and hip circumference was measured using a simple measuring tape. A total of 5ml of
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fasting blood samples was collected from each subject and put in heparin tubes for analysis on
fasting insulin levels and sodium fluoride tubes for analysis on fasting glucose, triglycerides,
cholesterol, LDL-cholesterol, HDL- cholesterol levels.
After the blood collection, the samples were taken to the pathology laboratory of the Faculty
of medicine and health sciences, University Putra Malaysia. There, the blood samples were
centrifuged for 10minutes at the speed of 35000rpm. Following centrifugation, a pipette was
used to collect the blood serum and put in and put in Eppendorf tubes for preservation. The
samples were preserved in the low temperature freezer which is maintained at a temperature
of -70°c. The blood remnant was put in specific waste bins in the laboratory for autoclave and
disposal.
Insulin and glucose levels were treated as continuous variables. Glucose levels over 100
mg/dL were considered elevated. IR was measured by the Homeostasis Model Assessment
Index (HOMA) and defined as 2.79 or more as values above the 75th percentile (Eslam et. al.,
2011).
2.3.2 Biochemical analysis
All laboratory assays was carried out using Cobas® c systems supplied by Roche
Diagnostics, Indianapolis, IN.
Fasting glucose was determined using enzymatic reference method with hexokinase.
Mercodia Insulin Elisa immunoassay was used to determine insulin levels and the Rate
method and a single point calibration and enzymatic colorimetric method were used to
determine the HDL-cholesterol and triglyceride respectively.
2.3.3 Data analysis
Descriptive Statistics
Normal distribution of the continuous variables was accessed using the Kolmogorov-Smirnov
test, normal Q-Q plots and histogram which showed that data was normally distributed. The
dependent variable was confirmed cancer cases (from histology or imaging.) In the analysis,
cases were coded as 1 and controls as 0. While the independent variables were;
HOMA-IR as the main exposure variable of interest and; Obesity, Hypertension, Lipids level,
Cholesterol levels, Lifestyle (smoking habit and alcohol intake) and Physical inactivity as the
co factors.
Bivariate Analysis
For the continuous variables which included; HOMA-IR, SBP, DBP, Lipids and cholesterol
levels, BMI, waist-hip ratio, glucose and insulin levels, comparison was made between
CANCER and NON-CANCER groups using independent sample t-test.
The categorical variables which included; HOMA-IR treated as a categorical variable with
values higher than 2.79 described as insulin resistant, gender, ethnicity, marital status,
education level, smoking and alcohol use, physical activity, history of diabetes, obesity which
was defined as BMI equal or greater than 30, hypertension and monthly family income;
association was determined using Chi-square.
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Some of the variables were recoded into different variables. Among them were;
Glucose and insulin was used to calculate HOMA-IR
Waist and hip circumference was recoded to waist-hip ratio
Height and weight which was recoded to BMI
BMI was recoded to obese status
2.3.4 Multivariable Analysis
Logistic regression was used to control for other covariates. The crude and adjusted odds ratio
of select variables and their corresponding 95% confidence interval (CI) were determined
using binary logistic.
The forward LR method was used for the multivariate logistic regression. The underlying
principle of the forward LR is basically to find out how all the independent variables
collectively affect the dependent variable. This method initially runs the first model with only
the constant 0) thereafter it searches for predictor which has highest simple correlation with
outcome variable and if this significantly improves model, it is retained it goes on to search
for predictor which has second highest semi-partial correlation with the dependent variable
and if this significantly improves model, it is also retained and it goes on like this. Since the
independent variables varied in importance in regards to cancer association with HOMA-IR
the most important, the forward LR method was the best option.
All statistical analysis was performed using IBM SPSS version 21.
3.0 Result
The demographics, socio-economic, lifestyle, anthropometric and lifestyle variables are
shown in table 1 below.
No significant difference was noticed in the demographic and socio-economic characteristics
between the cases and controls. There were more smokers in the control (20%) than the cases
(2.2%; p value 0.02). This significant observation was not put in consideration as the smokers
were in the control group. The majority of the ethnicity was Malay so alcohol intake was at
minimal in this study.
Significant difference was observed in HOMA-IR which was used to define insulin
resistance, the metabolic risk factors including Hypertension, triglycerides, Obesity.
In this study, the 45 cancer cases were made up of 16 colorectal cancers (35.56%), 6 breast
cancers (13.33%), 5 neuroendocrine tumours (11.11%), 4 paragangliomas (8.89%), 4 stomach
cancer (8.89%), 2 lung cancers (4.44%), 2 thyroid cancers (4.44%) and one each of pancreas,
Hodgkin lymphoma, cerebral tumour, follicular lymphoma, melanoma and testicular cancer.
In the bivariate analysis, significance mean difference was observed in the HOMA-IR values
of the cases vs the controls. Mean HOMA-IR was 3.00 ± 1.52 in cases and 2.07 ± 0.69 in
controls; p value 0.001. When HOMA-IR was treated as a categorical variable with values
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≥2.79 defined as insulin resistant (Kamath et. al., 2011), 46.7% of the cases and 7.3% of the
controls were insulin resistant; p value <0.001.
In the logistic regression model (table 2), 4 variables were significant predictors of cancer.
Presence of IR which was defined as a HOMA-IR value ≥ 2.79 was a major predictor in this
study (adjusted OR = 12.25. 95% CI 3.20 46.83. p < 0.001). Also predictors were
hypertension (adjusted OR = 5.03. 95% CI 1.76 14.42. p =0.003), obesity (adjusted OR =
3.33. 95% CI 1.08 10.31. p =0.037) and triglycerides (adjusted OR = 2.69. 95% CI 1.05
6.89. p =0.039). Below are the tabulated results.
Table 1: Characteristics of all respondents; cancer cases and controls
Variables
Case
(n=45)
Control
(n=55)
n
%
%
P
DEMOGRAPHICS
Gender Males
Females
27
18
60
40
67.3
32.7
0.451
Age(year, Mean & SD)
52.51
11.45
10.66
0.849
Ethnicity
Malay
Chinese
Indian
30
12
3
66.7
26.7
6.7
90.9
5.5
3.6
0.012
Marital Status
Single
Married
Others(Divorced/Widowed)
4
39
2
8.9
86.7
4.4
29.1
65.5
5.4
0.033
Religion Islam
Buddha
Others
30
10
5
66.7
22.2
11.1
90.9
3.6
5.4
0.019
Monthly Fam.Income (RM)
<2000
2000-2999
3000-3999
4000-4999
≥5000
15
3
6
9
12
33.3
6.7
13.3
20.0
26.7
27.3
3.6
23.6
10.9
34.5
0.406
Level of Education
Primary
Secondary
Diploma
Uni. Degree+
7
17
8
13
15.6
37.8
17.8
28.9
5.5
36.4
18.2
40.0
0.392
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Fam. History of DM
Present
Absent
19
22
42.2
57.8
40
60
0.822
Alcohol Intake
Drinker
Quit
Non-Drinker
1
3
41
2.2
6.7
91.1
1.8
5.5
92.7
0.957
Smoking Status
Smoker
Quit
Non-Smoker
1
3
41
2.2
6.7
91.1
20.0
14.5
65.5
0.007
Physical Activity
Low
Moderate
High
30
15
0
66.7
33.3
0
34.5
27.3
38.2
<0.001
ANTHROPOMETRICS
BMI
Mean(kg/m2) (mean & SD)
Obesity (BMI ≥ 30)
29.96
20.00
7.4
44.4
5.34
20.00
0.009
0.009
WHR
Mean(inches) (mean & SD)
Obesity (WHR ≥ 0.90)
0.89
23
0.12
51.1
0.06
18.2
0.014
<0.001
METABOLIC VAR.
SBP (mean & SD) mmHg
Hypertension (SBP ≥135)
138
33
15.9
73.3
21.3
30.9
0.005
<0.001
Cholesterol (mean & SD) mM
4.14
1.19
1.38
0.33
Triglycerides (mean & SD) mM
1.27
0.64
0.49
0.001
HDL-Cholesterol(mean & SD) mM
0.76
0.33
0.31
0.66
LDL-Cholesterol(mean & SD) mM
2.34
0.99
0.81
0.21
Glucose (mean & SD) mg/dl
Glucose ≥ 100
105.39
20
44.69
44.40
19.67
9.1
<0.001
<0.001
Insulin (mean & SD) pmol
HOMA-IR (mean & SD)
HOMA ≥ 2.79
11.33
3.00
21
1.98
1.52
46.7
2.59
0.69
7.3
0.12
<0.001
<0.001
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Figure 1: Mean HOMA-IR of cancer cases and controls
Multivariate Logistic Regression, Final Model Showing Adjusted Odds Ratio
Table 3: Adjusted ORs for IR, Hypertension, Obesity and Triglycerides
B
S.E
p value
Adjusted
OR
95% C.I
Lower
Upper
HOMA-IR
2.505
0.684
<0.001
12.247
3.203
46.832
Hypertension
1.616
0.537
0.003
5.032
1.756
14.423
Obesity
1.203
0.576
0.037
3.331
1.076
10.307
Triglyceride
levels
0.989
0.480
0.039
2.690
1.050
6.888
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4.0 Discussion
The major objective of this study which was to determine the association between HOMA-IR
and cancer was significant. Even though South-East Asians have been known to be insulin
resistant in the absence of IR risk factors, HOMA-IR was still increased in cancer patients
compared to the control subjects. This is in line with previous studies (Capasso et. al., 2012,
Oh et. al., 2011, Kang et. al., 2009, Loh et. al., 2010) carried out in various populations with
reduced risk to be insulin resistant in the absence of the risk factors.
In this study, the effect of insulin resistance was rather strong and remained significant after
adjusting for cofounders. In the logistic regression model, which showed adjusted odds ratios
[ORs] and 95% confidence intervals [CIs] for HOMA-IR, there was an increased risk for
cancer with higher HOMA-IR values (OR = 11.15, 95% CI: 3.45-36.1, P<0.001, model 1).
Adjustment for hypertension slightly increased the strength of the association between
HOMA-IR and cancer (OR = 12.27, 95% CI: 3.39-44.48, P<0.001, model2). When
triglycerides was put into consideration, the magnitude of this association was slightly
reduced but remained statistically significant (OR = 9.63, 95% CI: 2.66-34.91, P=0.001,
model 3). In the fully adjusted model (table 4.9), which included HOMA-IR, hypertension,
triglycerides and obesity, the strength of association between HOMA-IR and cancer was
increased from the value in the 3rd model (OR = 12.25, 95% CI: 3.2-46.83, P<0.001, model
4). No significant interactions between HOMA-IR and obesity, hypertension or triglycerides
were observed.
When triglyceride was included in the model, the association between HOMA-IR and cancer
remained significant but there was infinitesimal reduction in the strength. This is a minor
observation but the fact that insulin resistance and triglycerides are closely related could be a
possible explanation. Kamath et. al.(2011) in their study inferred that liver triglyceride
content was proportional to hepatic and peripheral IR.
Cancer has also been commonly associated with metabolic risk factors obesity and lifestyle
behaviours. Research has been carried out over the years on the association between
hypertension and cancer. Results from these studies have been controversial also. In a review
(Grossman et. al., 2002), renal cell cancer was found to be mostly associated with
hypertension but no definite association was found between hypertension and other cancer
sites. Contrary to the above conclusion, a different study (Peeters et. al., 2000) supported the
hypothesis that a positive link exist between select cancer (gastrointestinal, lung, lymphatic,
haematopoietic, uterus, cervix and ovary among others) and hypertension.
In this study, of the four components of lipid profile (cholesterol, triglycerides, LDL and
HDL) only triglyceride levels were found to have significant association with cancer. Lipids
are known for the role they play in cell conformity. Previous studies have found association
between lipid profile and cancer. Patel et. al (2004) attributed the reduced levels of plasma
cholesterol and other lipid components in patients with head and neck cancer to the use by
neoplastic cells for the biogenesis of new membrane. Shah et. al. (2008) also came to a
similar conclusion in their study between breast cancer and lipid profile. They found
significant differences between levels of the different components of lipid profile between
breast cancer cases and controls.
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Glucose and insulin were recoded into HOMA-IR in this study. Individually, glucose was
significantly associated with cancer but not insulin. Studies carried out on cancer and fasting
blood glucose association have been in agreement. Rapp et. al. (2006) found positive
association between elevated blood glucose and several cancers. The results from Stocks et.
al. (2009) also backed up the earlier results. They also determined the strength of this
association. They found that abnormal glucose metabolism independent of BMI was related to
an increased risk of cancer in general and several specific sites. This association was found
also to be stronger in females than males.
Even though insulin was not significantly associated with cancer in this study, some studies
have found this association present while others have not. Clayton et. al. (2011) found no
overall increase in cancer risk with insulin treatment. Meanwhile in the mini review carried
out by Gallagher and LeRoith (2011), they came to a conclusion that insulin seems to have an
independent influence on the development as well as progression of tumor growth.
Lifestyle behaviors including physical activity levels are known as major risk factors for Non-
Communicable Diseases in general. In this study, even though smoking habits and alcohol
consumption were found to be significantly associated with cancer, the results are not useable
in that the frequency for smokers and alcohol users was 1 in both categories. Nonetheless,
smoking, alcohol consumption and sedentary lifestyles are known to have some influence on
the development of cancers. Hashibe et. al. (2009) agreed that combined effect involving
tobacco use and alcohol intake is greater than an interaction on head and neck cancer risk.
Results from Stolzenberg-Solomon et. al. (2006) also follow suit that use of alcohol have
some influence on the development of breast cancer. Obesity defined by BMI and WHR were
also significantly associated with cancer in this study. This is in line with previous studies
which have also found this association. Considering physical inactivity in relation to obesity,
individuals who are physically inactive are prone to be overweight to obese. Studies carried
out decades ago have also found this association between physical activity and cancer. Recent
studies have come up with conclusions that breast and colon cancer patients who are
physically active are at greater advantage at recovery that patients who are either obese or
physically inactive (Wolin et. al., 2010).
These results are in line with previous studies even though a study by Dickson et. al. (2002)
found South-East Asians to be insulin resistant in the absence of risk factors, something he
attributed to genetic and diet factors. These results were able to prove in part that even at
increased risk of being insulin resistant than other races, HOMA-IR is still a risk factor for
cancer in Malaysians according to this study.
5.0 Conclusion and recommendation
In conclusion, this case-control study identified some metabolic and lifestyle behaviours
which can be modified. However some of the commonly reported risk factors such as HDL,
LDL and cholesterol were not found to be significantly associated with cancer in this study.
This could have been attributed to some of this study’s limitation as reduced sample size and
concentration of subject recruitment or it could also mean that no association exist between
these variables in a Malaysian
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Some of the strengths of this study include:
HOMA-IR; a validated measure of insulin resistance was used in this study.
To our knowledge, this is the first study on this association carried out in the South-
east Asian region.
Some of the limitations of this study include;
Conclusion was based on cancer patients from 2 selected institutions and cannot be
generalised for all cancer patients or the Malaysian population in general.
There exists a possible selection bias among controls as secondary source was used ie
individuals attending health screening procedures. It cannot be proved that their exposure
prevalence sufficiently shows in the person-time that gave rise to the cases.
Even though the IGF pathway is the plausible mechanism by which HOMA-IR is
associated to cancer, there was no measurement of IGFs or other insulin resistance
associated hormones and metabolites or their receptors due to cost and some complex
laboratory work involved.
Acknowledgement
This study was funded by research grant (04-01-11-1160RU) from Research University Grant
Scheme (RUGS) of University Putra Malaysia. We also would like to thank our collaborator,
Associate Professor Dr. Mohd Faisal Jabar for his expert help and kind assistance in
recruiting subjects of this study
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