144 J I M D C   2 0 1 7  144 

Op e n  Ac c e ss  
F u l l  L e n g t h  A r t i c l e  
 
 

 Changes in Lipid Profiles According to Body Mass Index in 

Individuals Coming to a Tertiary Care Hospital 

Saman Waqar 1, Haroon Khan 2, Rafi Raza Ahmed 3 

1 Assistant Professor, Department of Chemical Pathology, Federal Medical and Dental College Islamabad 
2 Professor, Department of Chemical Pathology, Pakistan Institute of Medical Sciences, Islamabad 

3 Post graduate resident, Dept. of Pediatric Surgery, Pakistan Institute of Medical Sciences, Islamabad 

A B S T R A C T  

Objective: The aim of this study was to quantify dyslipidemia among people with different Body mass index.  

Patients and Methods: This cross-sectional study was performed in the Pathology Department of Pakistan Institute 

of Medical Sciences, Islamabad. A total of 198 participants were enrolled in the study. All the participants were above 20 

years of age coming as caretakers to the patients coming to OPD and indoor departments. People under 20 years, with 

cardiac diseases and those reluctant to give consent were excluded from the study. The outcomes were measured in the 

form of quantification of dyslipidemia among different classes of Body mass index (BMI). 

Results: The mean age of the participants was 34.9 + 9.4 years with predominance of male participants, 141 (71.2%). 

The overall frequency of dyslipidemia was 56.1%. It was observed that 51 (42.5%) individuals with normal BMI also had 

dyslipidemia. Out of 38 overweight cases 32 (84.2%) were found to be associated with dyslipidemia (p-value = <0.001). 

Conclusion: From the above study, it was found that dyslipidemia is not only associated with obese or overweight 

individuals, but also in individuals with normal BMI. This shows that normal BMI individuals are also at risk of developing 

cardiovascular disorders and should be routinely screened for dyslipidemia. 

Keywords: BMI, Cardiovascular disorders, Dyslipidemia, Lipid profile. 

Author`s Contribution 
1
 Conception, synthesis, planning of 

research and manuscript writing 
2 

Interpretation and discussion 
3
 Data analysis, interpretation and 

manuscript writing, Active participation in 
data collection 

Address of Correspondence 
Saman Waqar 
Email. samanwaqar@yahoo.com 

Article info. 
Received: July 25, 2017 
Accepted: August 11, 2017 
 

Cite this article: Waqar S, Khan H, Ahmed RR. Changes in Lipid Profiles According 
to Body Mass Index in Individuals Coming to a Tertiary Care Hospital Nephrotic. 
JIMDC. 2017; 6(2):144-147. 

Funding Source: Nil 
Conflict of Interest: Nil 

I n t r o d u c t i o n  

Dyslipidemia means the abnormal quantity of lipid 

circulating in the blood. These lipids include triglycerides, 

phospholipids, and cholesterol. The most common 

dyslipidemia is hyperlipidemia, which is an elevation in the 

lipids in blood. Two major contributing factors in this 

regard are diet and lifestyle.1 The commonly used 

classification of dyslipidemia is increased total cholesterol, 

increased Low Density Lipids (LDL), increased 

Triglycerides (TC) and decreased High Density Lipids 

(HDL).2  For the screening of dyslipidemia, a lipid profile is 

required which is a panel of blood tests that serve as a 

screening tool for abnormalities in total lipids and 

approximate risk of developing cardiovascular disease 

and other diseases.2 Dyslipidemia is among the most 

common risk factors for atherosclerotic disease and 

cardiovascular diseases.2 Dyslipidemia is very much 

O R I G I N A L  A R T I C L E  



 

                           145 J I M D C   2 0 1 7  145 

prevalent in the region of South Asia and this region is 

more prone to have increased levels of total cholesterol 

(TC), triglycerides (TG) and high density lipoprotein 

cholesterol (HDL-C).2,3 Dyslipidemia is a common finding 

in obese population and increased levels of lipid 

parameters in blood are associated with atherosclerotic 

plaque formation.4 

This study was planned to determine the changes in lipid 

profiles of healthy individuals coming as attendants with 

the admitted patients in Pakistan Institute of Medical 

Sciences, Islamabad. The aim of the study was to 

categorize the population according to BMI and at the 

same time investigating their lipid profile to assess their 

association. 

    P a t i e n t s  a n d  M e t h o d s  

This cross-sectional study was conducted in the 

Department of Pathology, Pakistan Institute of Medical 

Sciences, Islamabad for the duration of 6 months. Total 

198 healthy individuals after taking informed consent were 

enrolled in the study. Sample size was calculated through 

WHO calculator by using alpha error=5%, confidence 

level=95% and anticipated population=84.8%.2 Sampling 

technique was non-probability consecutive sampling. All 

the adults, aged 20 or more and either gender, who came 

as caregivers with OPD visiting patients were enrolled in 

the study. Individuals less than 20 years, with known 

cardiac disease or other chronic morbidity and patients 

who refused to give the consent were excluded from the 

study. The blood samples were taken from study subjects 

under aseptic measures. Lipid parameters including TC, 

LDL-C, HDL-C and TG were measured in the laboratory. 

The results were noted on the study performa. SPSS 

version 12.0 was used to enter and analyze the data. 

Descriptive statistics were used to calculate mean and 

standard deviation from continuous variables like age, 

height, weight, BMI and lipid parameters. Frequency and 

percentages were calculated for categorical variables like 

sex, family history of diabetes, hypertension, smoking 

habits and dyslipidemia. Chi-square test was applied to 

find out the association of BMI with dyslipidemia. A p-

value of <0.05 was considered statistically significant. 

R e s u l t s  

A total of 198 healthy individuals were enrolled in this 

study to determine their lipid profile. The mean age of all 

the subjects was 34.9 + 9.4 years. Most of the study 

participants 68 (34.3%) were between the age 31 to 40 

years, followed by 46 (23.2%) between 26 to 30 years 

(Table 1).  

Table 1: Demographic characteristics of participants 
(n=198) 

Variables Number Percentage  

Age (years)   

   20-25 36 18.2 

   26-30 46 23.2 

   31-40 68 34.3 

   41-50 33 16.6 

   51 or above 15 7.5 

Family h/o diabetes 

   Yes 63 31.8 

   No 135 68.2 

Family h/o hypertension 

   Yes 67 33.8 

   No 131 66.2 

Smoking   

   Yes 53 26.8 

   No 145 73.2 

 

The predominant gender of this study was males i.e. 141 

(71.2%) and females were 57 (28.8%). Considering 

anthropometric measurements mean height was found to 

be 3.0 + 0.3 m2. The average weight came out to be 68.2 

+ 8.5 Kg. Using these parameters; the average BMI came 

out to be 22.6 + 2.5 Kg/m2. Among the study subjects, 63 

(31.8%) patients had a family history of diabetes. 

Hypertension was more prevalent i.e. 67 (33.8%) among 

patients. Apart from these, there were 53 (26.7%) 

smokers in the study (Table 1). The lipid profile of the 

patients was also analyzed. The mean LDL-C was 83.0 + 

32.1 mg/dl. Similarly, the average HDL-C was 39.4 + 

8.8mg/dl and TG was 155.9 + 94.5 mg/dl. The total 

cholesterol was found to be 154.5 + 37.4 mg/dl.  Out of 

the total 198 cases, 14 (7.1%) had increased levels of 

LDL-C i.e. greater than 130mg/dl. A part of population 

also had decreased levels of HDL-C i.e. in 102 (51.5%) 

subjects having less than 40mg/dl of HDL-C. A total of 18 

(9.1%) had raised levels of total cholesterol. Increase in 

triglycerides level was observed in 80 (40.4%) individuals. 

Considering the BMI of the study patients, out of the total 

198 subjects, 120 (60.6%) had BMI within normal range 

(18.9 to 24.5%), 38 (19.2%) were overweight (24.6 to 

30%) whereas 40 (20.2%) were obese (greater than 30%) 

in this study. It was noticed that out of 120 cases with 



 

                           146 J I M D C   2 0 1 7  146 

normal BMI, majority i.e. 69 (57.5%) had normal lipid 

levels. This shows that even the population with normal 

BMI may be at a risk of developing CVD. Dyslipidemia 

was a common finding in overweight and in obese 

individuals (Table 2).  

Positive family history of diabetes, hypertension and 

smoking habit was significantly related to dyslipidemia. 

Large number of smokers were also significantly found to 

be dyslipidemic (Table 3). The overall prevalence of 

dyslipidemia collectively came out to be 56.1% with 111 

cases being dyslipidemic. D i s c u s s i o n  
 

This study was conducted to find association of 

dyslipidemia in different BMI categories in order to assess 

the relative risk of developing cardiovascular disorders in 

our community. The region of South Asia has been shown 

to be more susceptible to develop cardiovascular 

disorders. Due to increased burden of CVD in population, 

we planned to assess the population at risk. It is a well-

known fact that a sufferers of dyslipidemia are at a great 

risk of developing CVD. The current study showed the 

average age of the participants was 34.9 + 9.4 years. 

More than 80% of the cases were between 20-40 years of 

age. A study done by Sherpa LY et al3 reported mean age 

of their participants to be 48 years. This difference in the 

age presentation may be due to different geographical. 

regions according to developed and underdeveloped 

countries. 

 In this study, we found that male gender was more 

prevalent i.e. 71.2% among the study subjects. Humayun 

A et al6 found a similar trend in their study. The study by 

Shah AZA et al2 also showed this inclination towards the 

male gender. Opposite finding i.e. female preponderance 

was seen in a study by Sherpa LY et al3. The male 

dominance may be due to the fact that in majority of the 

cases, the attendants coming with the patients are usually 

male, so that may be the reason behind this. The overall 

prevalence of dyslipidemia was found to be in 56.1%. The 

most surprising fact about this study was that out of 120 

individuals with normal BMI, 51 (42.5%) had dyslipidemia. 

This clearly shows that dyslipidemia may be seen in non-

obese individuals and people with normal BMI may be 

vulnerable to dyslipidemia. In this study, about 32% of 

overweight individuals had dyslipidemia and 70.0% of 

obese participants had dyslipidemia. Our findings are 

somewhat comparable to the findings of Humayun A et al6 

reporting in their study that a significant population of 

otherwise normal and healthy adults are at the verge of 

developing dyslipidemia. Considering the lipid parameters 

and comparing it with other studies, decrease in HDL-C 

was observed in (51.5%) individuals as compared to Shah 

SZA et al who noted 46% individuals with decreased 

HDL-C, both these findings are comparable. The huge 

difference was seen in LDL-C levels, in our study, 7.1% of 

the individual had increased LDL-C levels whereas in 

Shah SZA et al study, almost one-third population had 

high LDL-C levels. So prevalent feature of dyslipidemia in 

this study was decreased HDL-C levels. Similarly, 

Mohanna et al12 also observed low HDL-C levels in 30.4% 

individuals and hypercholesterolemia in 34.3% cases. 

Evidence from literature suggest that all these features of 

deranged lipid profile i.e. increased TG, LDL-C, TC and 

decreased HDL-C are atherogenic.13 Thus in order to 

prevent cardiovascular diseases, these risk factors should 

be taken care of.14 BMI should be part of routine medical 

checkup which would give us an estimate of obesity in a 

population. Studies have shown that obesity is related to 

dyslipidemia, which eventually leads to cardiovascular 

disorders.15 This study gives us alarming outcomes in 

Table 3: Predictors of dyslipidemia among participants 
(n=198) 

Variables Lipid profile p-value 

Dyslipidemia  
(n=111) 

Normal Lipids 
(n=87) 

 Family h/o diabetes;  
n=63(31.8%) 

43 (68.1) 63(31.8) <0.001 

 Family h/o 
hypertension; 
n=67(33.8%) 

48 (71.6) 67 (33.8) <0.001 

Smoking; 
n=53(26.7%) 

41 (77.3) 53 (26.7) 53 (26.7) 

Table 2: Association of BMI categories with dyslipidemia 
among participants (n=198) 

BMI categories Lipid profile p-value 

Dyslipidemia  
n (%) 

Normal Lipids 
n (%) 

Normal; 
n=120(60.6%) 

51 (42.5) 120 (60.6) 0.01 

Over weight 
n=38(19.2%) 

32 (84.2) 38(19.2) <0.001 

Obesity; 
n=40(20.2%) 

28 (70.0) 40 (20.2) <0.001  



 

                           147 J I M D C   2 0 1 7  147 

which the normal BMI people are also found to be at risk 

of developing CVD. So, based on the findings of the 

current study, one can say that the lipid profile to assess 

dyslipidemia should be done in people irrespective of their 

BMI levels. Chances of occult dyslipidemia may be there 

in otherwise healthy and even non-obese people. 

Therefore, these people should be targeted for screening 

for dyslipidemia before development of heart diseases. 

C o n c l u s i o n  

Dyslipidemia or deranged lipid profile is the most common 

risk factor for developing CVD. From this study, it was 

observed that 56.1% individuals who were otherwise 

healthy had dyslipidemia. It is not limited to obese and 

overweight individuals and a person with normal BMI can 

also present with dyslipidemia. The most common 

derangement observed was decreased HDL-C and 

increased TG. 

R e c o m m e n d a t i o n s  

People with normal BMI should also have routine check-

up for lipid profile. The healthcare professionals should 

spread awareness about dyslipidemia in population. 

R e f e r e n c e s  
1. Medical Definition of Dyslipidemia [Internet]. Merriam-

webster.com. 2016.  
2. Shah SZA, Devrajani BR, Devrajani T, Bibi I. Frequency of 

dyslipidemia in obese versus non - obese in relation to Body 
mass index (BMI), waist hip ratio (WHR) and waist circumference 
(WC). Pak J Sci 2010; 62: 27-31. 

3. Sherpa LY, Stigum H, Chongsuvivatwong V, Luobu O, Thelle DS, 
Nafstad P, Bjertness E. Lipid profile and its association with risk 
factors for coronary heart disease in the highlanders of Lhasa, 
Tibet. High altitude medicine & biology. 2011; 12(1):57-63. 

4. Flegal KM, Carroll MD, Ogden CL, Curtin LR. Prevalence and 
trends in obesity among US adults, 1999-2008. Jama. 2010; 
303(3):235-41. 

5. Finucane MM, Stevens GA, Cowan MJ, Danaei G, Lin JK, 
Paciorek CJ, et al. National, regional, and global trends in body-
mass index since 1980: systematic analysis of health 
examination surveys and epidemiological studies with 960 
country-years and 9· 1 million participants. The Lancet. 2011; 
377(9765):557-67. 

6. Humayun A, Shah AS, Alam S, Hussein H. Relationship of body 
mass index and dyslipidemia in Different age groups of male and 
female population of Peshawar. J Ayub Med Coll Abbottabad 
2009;21(2): 141-44. 

7. National Cholesterol Education Program (Ncep) Expert Panel On 
Detection, E. (2002). "Third Report of the National Cholesterol 
Education Program (NCEP) Expert Panel on Detection, 
Evaluation, and Treatment of High Blood Cholesterol in Adults 
(Adult Treatment Panel III) final report". Circulation 2002; 106: 
3143–3421. 

8. Ito MK, McGowan MP, Moriarty PM. Management of familial 
hypercholesterolemias in adult patients: recommendations from 
the National Lipid Association Expert Panel on Familial 
Hypercholesterolemia. J Clin Lipidol 2011;5(3):S38–45. 

9. Hooper L, Summerbell CD, Thompson R, Sills D, Roberts FG, 
Moore HJ, Smith GD. Reduced or modified dietary fat for 
preventing cardiovascular disease. Sao Paulo Medical Journal. 
2016; 134(2):182-3. 

10. Jolliffe JA, Rees K, Taylor RS, Thompson D, Oldridge N, Ebrahim 
S. Exercise-based rehabilitation for coronary heart disease. 
Cochrane Database Syst Rev. 2001; 1(1). 
DOI: 10.1002/14651858.CD001800 

11. McKenney JM, Davidson MH, Jacobson TA, Guyton JR. Final 
conclusions and recommendations of the National Lipid 
Association Statin Safety Assessment Task Force. Am J Cardiol 
2006;97(suppl 8a):89C-94C. 

12. Mohanna S, Baracco R, Seclén S. Lipid profile, waist 
circumference, and body mass index in a high altitude population. 
High altitude medicine & biology. 2006; 7(3):245-55. 

13. Howard BV, G Ruotolo, DC Robbins. Obesity and dyslipidemia. 
Endocrinol Metab Clin North Am. 2003; 32:855-67. 

14. Toth, P.P. Low-density Lipoprotein Reduction in highrisk patients: 
How Low Do You Go? Curr Atheroscler Rep. 2004; 6(5):348-52. 

15. Flegal KM, Carroll RJ, Kuczmarski, Johnson CL. Overweight and 
obesity in the United States: prevalence and trends, 1960-1994. 
Int J Obes Relat Metab Disord. 1998; 22(1):39- 
47