Overweight and Obesity, Lipid Profile and Atherogenic Indices among Civil Servants in Abakaliki, South Eastern Nigeria
- *Corresponding Author:
- Dr. Emmanuel Ugwuja
Department of Chemical Pathology, Faculty of Clinical Medicine, Ebonyi State University, P.M.B 053 Abakaliki, Nigeria
Citation: Ugwuja EI, Ogbonna NC, Nwibo AN, Onimawo IA. Overweight and Obesity, Lipid Profile and Atherogenic Indices among Civil Servants in Abakaliki, South Eastern Nigeria. Ann Med Health Sci Res 2013;3:13-8.
Background: The association between dyslipidaemia, obesity and hypertension is well established, and all have been found to be risk factors for cardiovascular disease (CVD). Aim: To determine the prevalence of overweight and obesity, plasma lipid profile and atherogenic indices as markers for CVD among civil servants. Subjects and Methods: Two hundred and five (205) apparently healthy civil servants (106, 51.7% males) aged 21-60 years, mean and standard deviation (SD) 40.9 (11.3) years, enrolled between February and April 2008 were assessed for their plasma lipid profile and anthropometrics (body weight and height) using standard methods and techniques. Results: Prevalent rates of overweight and obesity were 34.2% (70/205) and 6.8% (14/205), respectively, with more men affected than women. Abnormal lipids observed were: Elevated total cholesterol 37.1% (76/205), low-density lipoprotein-cholesterol (LDL-C) 37.1% (76/205), triglyceride 6.8% (14/205), reduced high-density lipoprotein-cholesterol (HDL-C) 8.8% (18/205) and elevated Atherogenic Index 10.7% (22/205) and Coronary Risk Index 9.8% (20/205), with the older age groups and higher Body Mass Index (BMI) groups being the most affected. Male subjects were found to have more favorable plasma lipid profile (lower LDL-C and higher HDL-C) than the females. Plasma lipids were positively correlated with BMI and artherogenic indices, except for HDL-C, which was negatively correlated with artherogenic indices and LDL-C but positively correlated with BMI. Conclusion: The findings show that civil servants in Abakaliki, particularly the females, those with higher BMI and advanced in age, exhibited unfavorable plasma lipids and social habits with a low level of physical activity, which may predispose them to CVD. In addition to epidemiological study of the general population, there is a need for education on healthier lifestyles such as good nutrition, weight reduction, smoking and alcohol cessation, greater physical activity and regular medical check-up.
Cardiovascular disease, Dyslipidaemia, Obesity, Overweight
Cardiovascular diseases (CVDs), the leading cause of morbidity and mortality in the western World, are now emerging public health challenges in developing countries, accounting for 80% of deaths and 87% of related disability currently recorded in the low-and middle-income countries. In developing countries, mortality due to CVD is expected to rise to 19 million by 2020, with deaths among persons 15-59 years of age three to eight times as high in Tanzania and Nigeria as in England and Wales. In fact, it has been reported that CVD in developing countries causes twice as many deaths as HIV, malaria and tuberculosis combined. According to earlier speculation, almost all unexpected deaths of medical origin in Nigeria are due to cardiovascular cause.
The association between dyslipidemia, obesity and hypertension is well established,[6,7] and all have been found to be major risk factors for the development of CVD, a leading cause of visits to physicians and cause of death. Dyslipidaemia is becoming increasingly common in Africa. For instance, a study in Tanzania observed 25% prevalence of elevated serum total cholesterol (TC > 5.2 mmol/L) and 15% prevalence of elevated triglyceride (Tg > 1.7 mmol/L) among adults over 35 years of age, with women being affected more than men. This abnormal lipid metabolism has been associated with urbanisation and westernisation. Although there have been reports of plasma and/or serum lipids among different Nigerian populations,[11-14] little is known about the lipid profile of Nigerian civil servants, a population viewed as much vulnerable to dyslipidemia and other cardiovascular risk factors due to western lifestyle, such as alcohol consumption, cigarette smoking, sedentary life and consumption of diet with high fat contents (especially the unsaturated fats), all of which are associated with abnormal lipid metabolism. Therefore, the present study was designed to investigate the prevalence of obesity (high Body Mass Index [BMI]), plasma lipid profile and artherogenic indices as markers for CVD among civil servants in Ebonyi State.
Subjects and Methods
A total of 205 apparently healthy civil servants (106 males and 99 females) from 10 ministries (Health, Public Utility, Works and Transport, Commerce and Industry, Education, Agriculture, Women Affairs, Justice, Urban and Rural Development and Youths and Sports) in Abakaliki, the capital city of Ebonyi State, were enrolled between February and April 2008. The age of the participants ranged between 21 and 60 years. Convenient sampling method was used. The protocol for the study was approved by the Research and Ethics Committee of the Federal Medical Centre, Abakaliki. Written consent of the participants was obtained before the commencement of the study. Set of questionnaires were used to collect subjects’ sociodemographic data, such as age, sex, marital status, educational level, living accommodation, alcohol and tobacco intakes. The anthropometrics (weight [kg] and height [m]) of the participants were measured using weighing scale and measuring tape, respectively, and the BMI (kg/m2) was calculated. All the measurements were taken by one of the researchers (ANN). Based on the values of BMI, the subjects were classified as underweight (BMI < 18.5 kg/m2), normal (BMI 18.5-24.9 kg/m2), overweight (BMI 25-29.9 kg/m2) and obese (BMI ≥ 30 kg/m2). Blood samples (5.0 mL) were obtained once from the subjects between the hours of 08.00-10.00 after overnight fast and dispensed into EDTA bottles. The blood samples were placed on ice until separation within 2 h. The samples were centrifuged at 2000 g for 5 min, after which plasma was isolated into dry plain plastic screw-capped containers and stored frozen-20°C prior to analyses. Plasma TC and Tg concentrations were determined by enzymatic colorimetric assay as described previously and modified by Richmond, and high-density lipoprotein-cholesterol (HDL-C) and low-density lipoprotein-cholesterol (LDL-C) were determined enzymatically after precipitation of other lipoproteins as described by Burstein et al., and Assmann et al., respectively, using kits from Biosystem Laboratories (Spain).
All samples were analyzed in duplicates, after which the mean was determined. Atherogenic Index (AI = LDL-C/HDL-C) and Coronary Risk Index (CRI = TC/HDL-C) were thereafter calculated for individual subjects. Plasma lipid abnormality was based on the expert panel of the National Cholesterol Education Programme (NCEP) cut-off values.
Data collected were analyzed using SPSS® software for Window® version 16 (SPSS Inc., Chicago, IL, USA). The differences between groups were compared using one-way analysis of variance (ANOVA). Data were expressed either as mean and standard deviation or percentage. The statistical significance was set at the P value of ≤ 0.05.
The means and standard deviation (SD) of the parameters determined were age 40.9 (11.3) years, BMI 24.6 (3.6) kg/m2, TC 4.92 (1.00) mmol/L, LDL-C 2.83 (0.92) mmol/L, HDL-C 1.50 (0.59) mmol/L, Tg 1.29 (0.57) mmol/L, AI 2.28 (1.33) and CRI 3.75 (1.59). Taken together, all the participants had normal BMI, artherogenic indices and lipid parameters within the NCEP reference ranges. However, prevalence rates of abnormal lipid parameters observed were: Elevated TC 37.1% (76/205), elevated LDL-C 37.1% (76/205), elevated Tg 6.8% (14/205), reduced HDL-C 8.8% (18/205), elevated AI 10.7% (22/205) and elevated CRI 9.8% (20/205) (data not shown).
Table 1 shows the general characteristics of the study population. Majority of the subjects were in the age group of 31-40 years (32.2%, 66/205) and >50 years (30.2%, 62/205), had tertiary education (77.1%, 158/205) and lived in single rooms (50.2%, 103/205) and flats (42.4%, 87/205). As regards social habits and physical activity, 5.9% (12/205) of the subjects take tobacco, 23.9% (49/205) take alcohol and 2.4% (5/205) take both alcohol and tobacco, while 9.3% (19/205) were involved in physical activity. Five (5) subjects were found to be underweight, representing 2.4% of the study population (2.7% (3/106) males and 2.2% (2/99) females), while 34.1% (70/205) were overweight (41.5% (44/106) males and 26.3% (26/99) females) and 6.8% (14/205) (7.8% (8/106) males and 6.1% (6/99) females) were obese.
Table 2 compares BMI, plasma lipids (TC, LDL-C, HDL-C and Tg) and the artherogenic indices (CRI and AI) among the age groups. Subjects in the age group of 41-50 years had significantly (P = 0.023) higher BMI than the other age groups. For the plasma lipids, significantly (P = 0.019) higher values were observed for TC and LDL-C in the age groups 41-50 and >50 years, respectively, while significantly (P = 0.036) higher Tg was observed in the age group of >50 years only. However, there was no age difference in the value of plasma HDL-C. Although subjects in the higher age groups tend to have higher artherogenic indices, only values in subjects in the age groups of 31-40 and >50 years were found to be statistically significant (P = 0.011).
Both overweight and obese subjects had significantly (P < 0.05) higher plasma lipids when compared with individuals that were either underweight or normal weight, while the obese subjects had significantly (P = 0.037) higher Tg in comparison with overweight subjects [Table 3]. Nevertheless, there was no difference in the artherogenic indices among the BMI groups.
|Parameters||BMI groups (kg/m2)|
|<18.5 (n=5)||18.5-24.9(n=116)||25-29.9(n=70)||≥30 (n=14)|
|Total cholesterol||4.16 (1.15)a||4. 55(0.86)a||5.41 (0.87)b||5.82 (1.12)bc|
|LDL‑C||2.10 (0.94)a||2.57 (0.88)a||3.21 (0.83)b||3.29 (0.86)bc|
|HDL‑C||1.44 (0.47)a||1.42 (0.54)a||1.60 (0.64)b||1.70 (0.62)b|
|Triglyceride||1.34 (1.05)a||1.22 (0.52)a||1.31 (0.50)b||1.83 (0.83)c|
|Coronary risk index||3.32 (2.03)||3.69(1.70)||3.87 (1.44)||3.79 (1.46)|
|Artherogenic index||1.75 (1.41)||2.22(1.38)||2.42 (1.23)||2.27 (1.32)|
Table 3: Comparison of lipid profile and artherogenic indices in relation to the body mass index groups
BMI was found to be comparable (P = 0.107) between male and female subjects [Table 4]. While plasma TC, HDL-C and Tg were higher in males in comparison with their female counterparts, only TC was statistically significant (P = 0.040). However, LDL-C was lower (P = 0.473) in males in comparison with females [Table 4]. Although female subjects seem to have higher artherogenic indices in comparison with the males, the differences were not statistically significant.
|Body mass index||24.96 (4.17)||24.07 (3.59)||0.107|
|Total cholesterol||4.96 (0.98)||4.89 (1.03)||0.040*|
|LDL‑C||2.78 (0.95)||2.87 (0.89)||0.473|
|HDL‑C||1.58 (0.63)||1.42 (0.53)||0.061|
|Triglyceride||1.30 (0.54)||1.29 (0.61)||0.908|
|Coronary risk index||3.66 (1.63)||3.84 (1.54)||0.318|
|Artherogenic index||2.19 (1.36)||2.38 (1.29)||0.419|
Table 4: Comparison of BMI, lipid profile and artherogenic indices in relation to sex
From Table 5, although the effect of alcohol and tobacco intakes was not significant on BMI, plasma lipids and artherogenic indices (CRI and AI), physical activity was found to significantly lower (plasma TC, LDL-C and Tg and CRI and AI). However, physical activity tends to increase HDL-C, although this was not statistically significant (P = 0.405).
|No||24.66 (3.79||4.89 (0.95)||2.84 (0.91)||1.46 (0.56)||1.30 (0.60)||3.86 (1.68)||2.37 (1.40)|
|Yes||24.48 (3.14||5.02 (1.17)||2.79 (0.95)||1.63 (0.65)||1.27 (0.46)||3.41 (1.21)||1.98 (0.99)|
|No||24.62 (3.57||4.92 (1.01)||2.84 (0.93)||1.49 (0.56)||1.29 (0.58)||3.76 (1.54)||2.29 (1.30)|
|Yes||24.68 (3.35||4.92 (0.91)||2.59 (0.78)||1.70 (0.90)||1.28 (0.45)||3.66 (2.99)||2.12 (1.75)|
|No||24.60 (3.44||4.98 (1.01)||2.88 (0.91)||1.48 (0.59)||1.34 (0.57)||3.85 (1.61)||2.35 (1.34)|
|Yes||24.77 (4.61||4.42 (0.77)†||2.33 (0.85)†||1.71 (0.49)||0.88 (0.40)†||2.80 (0.94)†||1.56 (0.86)†|
Table 5: Comparison of BMI, lipid profile and artherogenic indices in relation to alcohol and tobacco intake and physical activity
Table 6 shows the interrelationships between plasma lipids, age, BMI and artherogenic indices (CRI and AI). While the TC, LDL-C and Tg were significantly (P=0.013) positively correlated with BMI and artherogenic indices, there were negative (P=0.021) correlations between HDL-C and the artherogenic indices. There was also a significantly (r = 0.232; P = 0.001) positive correlation between age and TC. However, LDL-C was significantly (r = −0.350; P = 0.002) negatively correlated with HDL-C.
|TC vs. CRI||0.246||0.001*|
|TC vs. AI||0.2360||0.001*|
|LDL‑C vs. CRI||0.641||0.004*|
|LDL‑C vs. AI||0.691||0.004*|
|HDL‑C vs. CRI||−0.774||0.003*|
|HDL‑C vs. AI||−0.775||0.003*|
|Tg vs. CRI||0.241||0.001*|
|Tg vs. AI||0.133||0.057|
|TC vs. BMI||0.500||0.004*|
|TC vs. age||0.232||0.001*|
|TC vs. LDL‑C||0.777||0.004*|
|TC vs. Tg||0.399||0.002*|
|LDL‑C vs. HDL‑C||−0.350||0.002|
|LDL‑C vs. BMI||0.391||0.002*|
|Tg vs. BMI||0.225||0.001*|
Table 6: Relationship between lipid profile and artherogenic indices
This study has documented prevalent rates of underweight, overweight and obesity of 2.4%, 34.2% and 6.8%, respectively, among the population. Again, unfavorable plasma lipid profile and artherogenic indices were documented among older subjects and subjects in the higher BMI groups. Male subjects were found to have more favorable plasma lipid profile (lower LDL-C and higher HDL-C) than the females. Although a significant percentage of the population were involved in social habits that may predispose them to CVD, such as cigarette smoking (5.9%) and alcohol consumption (23.9%), few were involved in physical activities (9.3%). Plasma lipids were positively correlated with BMI and artherogenic indices, except for HDL-C, which was negatively correlated with artherogenic indices and LDL-C but positively correlated with BMI.
The prevalence of overweight (34.2%) and obesity (6.8%) recorded in the present study are comparable to 36.0% and 6.5% for overweight and obesity, respectively, reported among senior civil servants in Kuala Lumpur and 33.4% for overweight/obesity reported among civil servants in Nepal. However, the values for obesity in males and females (7.8% and 6.1%, respectively) in the present study are lower than 41.5% and 25.6% in females and males, respectively, reported among civil servants in Tamale metropolis in the northern region of Ghana and 36% and 10% for women and men, respectively, in urban civil servants in Ghana. Previously, Okeke et al., reported that 40.58% of the top civil servants in Anambra State were 20% above desirable weight-for-age. Although the higher prevalent rate of overweight and obesity among male subjects observed in the present study was in corroboration with the findings of Oghagbon et al., and Bakari et al., (for obesity), it contrasted the findings of some studies that reported a higher prevalence of overweight[27,28] and obesity in females than in males. The disparities in these findings may best be explained by differences in the subjects studied. However, it has been shown that men gain more weight than women until the perimenopausal period, when the trend is reversed. The finding from this study has an important health implication. It may be speculated that a reasonable proportion of civil servants in Ebonyi State may be at risk of CVD. It is even more worrisome considering the lipid profile pattern and low level of physical activity of the subjects. Previously, higher lipid profile has been reported among hypertensive Nigerians.
A more favorable lipid profile of the male subjects (lower LDL-C and higher HDL-C) in comparison with their female counterparts observed in the present study raises some gender-related questions in the metabolism of lipids, and suggests that males in this population may be more protected from CVD than the females. Although the reason for unfavorable lipid profile in women in the present study is obscure, it may not be unconnected with unhealthy lifestyle, such as eating of “fast foods” and low level of physical activity, as only 9.3% of the study population were involved in physical activity. Low physical activity and consumption of diet with high contents of carbohydrate and saturated fatty acids, such as “fast foods,” have been associated with dyslipidemia.[32-35] According to Dancy et al., habitually active men and women are less likely to have hypertriglyceridemia and low HDL-C concentrations. Although dyslipidemia was a significant feature in the present study, the plasma lipid profile was better (except for TC) than that reported by Odenigbo et al., among the health professionals in Asaba, south-south Nigerian, in which 5% of the study population had hypercholesterolemia, 23% elevated total serum cholesterol, 51% elevated LDL-C and 60% low HDL-C, with females recording better overall lipid profile. It may be argued that our study population in general may be a bit protected from CVD, as reduced HDL-C was observed only in 8.8% of the study population, with the general population having lipid profile within the NCEP reference values. However, with significant percentage of the population involved in social habits that may predispose them to CVD, such as cigarette smoking (5.9%) and alcohol consumption (23.9%), with few involved in physical activities (9.3%), such protection may not be sustained. The positive correlations observed between the lipids and BMI on one hand and age on the other hand were in corroboration with previous studies,[12,31,36] and reaffirmed the role of lipids in the pathophysiology of overweight and obesity as well as increasing accumulation of lipids with aging. The present data show that civil servants in Abakaliki exhibited abnormal lipid profile and artherogenic indices, particularly the females, those with high BMI and those advanced in age, which may predispose them to CVD based on the high prevalence of overweight and obesity and low level of physical activity. We therefore recommend that in addition to the epidemiological study of the general population, there is need for education on healthier lifestyles, such as good nutrition, weight reduction, smoking and alcohol cessation, greater physical activity and regular medical check-up.
- World Health Organisation. The world health report: Reducing risks, promoting healthy lifestyles. Geneva; 2002.
- Murray CJ, Lopez AD. Alternative visions of the future: Projecting mortality and disability, 1990-2020. In: Murray CJ, Lopez AD, editors. The Global Burden of Disease. Boston, MA: World Health Organization/World Bank/Harvard University Press; 1996. p. 325‑95.
- Reddy KS. Cardiovascular disease in developing countries: Dimensions, determinants, dynamics and directions for public health action. Public Health Nutr 2002;5:231‑7.
- Lopez AD, Mathers CD, Ezzati M, Jamison DT, Murray CJ. Global and regional burden of disease and risk factors, 2001: Systematic analysis of population health data. Lancet 2006;367:1747‑57.
- Oviasu VO. Risk factors of cardiovascular disease in Africa. Postgraduate Doctor 1982;4:190.
- Nguyen NT, Magno CP, Lane KT, Hinojosa MW, Lane JS. Association of hypertension, diabetes, dyslipidemia, and metabolic syndrome with obesity: Findings from the national health and nutrition examination survey, 1999 to 2004. J Am Coll Surg 2008;207:928‑34.
- 7. Brown CD, Higgins M, Donato KA, Rohde FC, Garrison R, Obarzanek E, et al. Body mass index and the prevalence of hypertension and dyslipidaemia. Obes Res 2000;8:605‑19.
- Gordon H. Hypertensive vascular disease. In: Braunwald E, Fauci AS, Kasper DL, Hauser SL, longo DL, Jameson JL, editors. Harrison’s Principles of Internal Medicine. 15th ed. New York: McGraw; 2000. p. 141‑30.
- Kadiri S, Walker O, Salako BL, Akinkugbe O. Blood pressure, hypertension and correlates in urbanized workers in Ibadan, Nigeria: A revisit. J Hum Hypertens 1999;13:23‑7.
- Njelekela M, Negishi H, Nara Y, Tomohiro M, Kuga S, Noguchi T, et al. Cardiovascular risk factors in tanzania: A revisit. Acta Trop 2001;79:231‑9.
- Ademuyiwa O, Ugbaja RN, Rotimi SO. Plasma lipid profile, artherogenic and coronary risk indices in some residents of Abeokuta in south‑werstern Nigeria. Biokemistri 2008;20:85‑91.
- Akpa MR, Agomouh DI, Alasia DD. Lipid profile of healthy adult Nigerians in Port Harcourt, Nigeria. Niger J Med 2006;15:137‑40.
- Amodu PH, Mba IO, Lawson L. Prevalence of obesity and dyslipidaemia in hypertensives in Abuja, Nigeria. Scand J Clin Lab Invest 2005;240:14‑7.
- Abubakar A, Mabruok MA, Gerie AB, Dikko AA, Aliyu S, Yusuf T, et al. Relation of body mass index with lipid profile and blood pressure in healthy female of lower socioeconomic group in Kaduna northern Nigeria. Asian J Med Sci 2009;1:94‑6.
- Tinder P. Determination of glucose in blood using glucose oxidase with an alternative oxygen acceptor. Ann Clin Biochem 1969;6:24‑7.
- Richmond N. Preparation and properties of a cholesterol oxidase from nocardia sp. and its application to the enzymatic assay of total cholesterol in serum. Clin Chem 1973;19:1350‑6.
- Burstein M, Scholnick HR, Morfin R. Rapid method for the isolation of lipoproteins from human serum by precipitation with polyanions. Scand J Clin Lab Invest 1980;40:583‑95.
- Assmann G, Jabs HU, Kohnert U, Nolte W, Schriewer H. LDL‑cholesterol determination in blood serum following precipitation of LDL with polyvinylsulfate. Clin Chim Acta 1984;140:77‑83.
- National Cholesterol Education Program (NCEP) Expert Panel on Detection, Evaluation, and Treatment of High Blood Cholesterol in Adults (Adult Treatment Panel III). 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;106:3143‑421.
- Liew YM, Zulkifli A, Tan H, Ho YN, Khoo KL. Health status of senior civil servants in Kuala Lumpur. Med J Malaysia 1997;52:348‑66.
- Simkhada P, Poobalan A, Simkhada PP, Amalraj R, Aucott L. Knowledge, attitude, and prevalence of overweight and obesity among civil servants in Nepal. Asia Pac J Public Health 2011;23:507‑17.
- Mogre1 V, Mwinlenaa PP, Oladele J, Amalba A. Impact of physical activity levels and diet on central obesity among civil servants in Tamale metropolis. J Med Biomed Sci 2012;1:1‑9.
- Addo J, Smeeth L, Leon DA. Obesity in urban civil servants in Ghana: Association with pre‑adult wealth and adult socio‑economic status. Public Health 2009;123:365‑70.
- Okeke EC, Nnanyelugo DO, Ngwu E. The prevalence of obesity in adults by age, sex, and occupation in Anambra State, Nigeria. Growth 1983;47:263‑71.
- Oghagbon KE, Odili VU, Nwangwa EK, Pender KE. Body mass index and blood pressure pattern of students in a Nigerian University. Int J Health Res 2009;2:177‑82.
- Bakari AG, Onyemelukwe GC, Sani BG, Aliyu IS, Hassan SS, Aliyu TM. Obesity, overweight and underweight in suburban northern Nigeria. Int J Diabetes and Metabolism 2007;15:68‑9.
- Puepet FH, Zoakah AI, Chuhwak EK. Prevalence of overweight and obesity among Urban Nigeria Adults in Jos. Highland Med Res J 2002;1.
- Misra A, Pandey RM, Devi JR, Sharma R, Vikram NK, Khanna N. High prevalence of diabetes, obesity and dyslipidaemia in urban slum population in northern. India. Int J Obes Relat Metab Disord 2001;25:1722‑9.
- Habib SS, Aslam M, Hameed W. Gender differences in lipids and lipoprotein (a) profiles in healthy individuals and patients with type 2 diabetes mellitus. Pak J Physiol 2005;1:1‑2.
- Idemudia JA, Ugwuja EI. Plasma lipid profiles in hypertensive Nigerians. Internet J Cardiovasc Res 2009;6.
- Kelishadi R, Alikhani S, Delavari A, Alaedini F, Safaie A, Hojatzadeh E. Obesity and associated lifestyle behaviours in Iran: Findings from the first national non‑communicable disease risk factor surveillance survey. Public Health Nutr 2008;11:246‑51.
- Dancy C, Lohsoonthorn V, Williams MA. Risk of dyslipidemia in relation to level of physical activity among Thai professional and office workers. Southeast Asian J Trop Med Public Health 2008;39:932‑41.
- Kraus WE, Houmard JA, Duscha BD, Knetzger KJ, Wharton MB, McCartney JS, et al. Effects of the amount and intensity of exercise on plasma lipoproteins. N Engl J Med 2002;347:1483‑92.
- Krauss RM, Blanche PJ, Rawlings RS, Fernstrom HS, Williams PT. Separate effects of reduced carbohydrate intake and weight loss on atherogenic dyslipidemia. Am J Clin Nutr 2006;83:1025‑31.
- Odenigbo CU, Oguejiofor OC, Odenigbo UM, Ibeh CC, Ajaero CN, Odike MA. Prevalence of dyslipidaemia in apparently healthy professionals in Asaba, South South Nigeria. Niger J Clin Pract 2008;11:330‑5.
- Hajian‑Tilaki KO, Heidari B. Prevalence of obesity, central obesity and the associated factors in urban population aged 20‑70 years, in the north of Iran: A population‑based study and regression approach. Obes Rev 2007;8:3‑10.