Anthropometric measures as predictors of cardiovascular disease risk factors in the urban population of Iran

Abstracts

FUNDAMENTO: O sobrepeso e a obesidade são um importante problema de saúde pública na sociedade pela sua associação com diversas doenças crônicas. OBJETIVO: O objetivo deste estudo é determinar a prevalência e a distribuição de sobrepeso e obesidade, usando diferentes medidas antropométricas, e identificar o melhor indicador antropométrico intimamente relacionado aos fatores de risco de Doenças Cardiovasculares (DCV) em população iraniana urbana. MÉTODOS: O presente estudo transversal foi realizado com 991 homens e 1.188 mulheres de 15 a 64 anos. Foram medidos Índice de Massa Corporal (IMC), Circunferência Abdominal (CA), Relação Cintura-Quadril (RCQ), Relação Cintura-Altura (RCA) e porcentagem de gordura corporal. Foi obtida amostra de sangue em jejum. Foram avaliados os fatores de risco cardiovascular, incluindo glicemia de jejum, triglicerídeos, colesterol total (col-T), colesterol de baixa densidade (LDL-colesterol) e colesterol da lipoproteína de alta densidade (HDL-colesterol). RESULTADOS: Em relação ao IMC, 49% dos homens e 53% das mulheres estavam acima do peso ou obesos, e 10,2% dos homens e 18,6% das mulheres encontravam-se obesos. Tanto nos homens quanto nas mulheres, a prevalência de sobrepeso esteve maior entre aqueles com 40-49 anos de idade, e a prevalência de obesidade esteve maior entre aqueles com 50 anos ou mais. Usando a análise de regressão múltipla, IMC, RCA e RCQ explicaram o maior percentual de variação de triglicerídeos, razão entre col-T e HDL-colesterol e LDL-colesterol em homens, respectivamente, ao passo que RCQ explicou o maior percentual de variação de triglicerídeos e CA explicou o maior percentual de variação da razão entre col-T e HDL-colesterol e LDL-colesterol em mulheres. CONCLUSÃO: Nossos dados indicam que RCQ e RCA foram os indicadores antropométricos que melhor previram fatores de risco cardiovascular em homens e RCQ e CA, em mulheres.

Peso e Medidas Corporais; Peso Corporal; Doenças Cardiovasculares; Fatores de Risco; População Urbana; Irã (Geográfico)

^IDepartamento de Educação Física e Ciências Desportivas - Faculdade de Ciências Humanas - Universidade de Tarbiat Modares, Teerã, Irã

^IIDivisão de Epidemiologia e Saúde Comunitária da Faculdade de Saúde Pública da Universidade de Minnesota, Minneapolis, EUA

Mailing Address

ABSTRACT

BACKGROUND: Overweight and obesity are an important public health problem in society, due to their association with various chronic diseases.

OBJECTIVE: The purpose of this study is to determine the prevalence and distribution of overweight and obesity, using different anthropometric measurements and to identify the best anthropometric indicator which is most closely related to cardiovascular disease (CVD) risk factors in an Iranian urban population.

METHODS: This cross-sectional study was conducted with 991 men and 1188 women aged 15 to 64 years. Body mass index (BMI), waist circumference (WC), waist-to-hip ratio (WHR), waist-to-height ratio (WHtR) and percentage of body fat were measured. A fasting blood specimen was obtained. CVD risk factors, including fasting blood glucose, triglycerides, total cholesterol (Tchol), low-density (LDL-C) and high-density-lipoprotein cholesterol (HDL-C) were assessed.

RESULTS: Based on BMI, more than 49% of men and 53% of women were either overweight or obese with 10.2% of men and 18.6% of women being obese. In both men and women, the prevalence of overweight was greater among 40-49 year olds and the prevalence of obesity was greater among those 50+ years. Using the multiple regression analysis, BMI, WHtR and WHR explained the highest percentage of variation of triglycerides, Tchol/HDL-C ratio and LDL-C in men, respectively, whereas WHR explained the highest percentage of variation of triglycerides and WC explained the highest percentage of variation of Tchol/HDL-C ratio and LDL-C in women.

CONCLUSION: Our data indicated that WHR and WHtR were the anthropometric indicators that best predicted CVD risk factors in men and WHR and WC in women.

Keywords: Body weights and measures; body weight; cardiovascular diseases; risk factors; urban population; iran.

Introduction

The prevalence of overweight and obesity is rapidly increasing in developing as well as in industrialized countries^1,2. Unhealthy diets and physical inactivity are the main contributors to overweight and obesity, which are among the leading risk factors for major non-communicable diseases. Previous research has consistently shown that both absolute total body fat and central distribution of body fat are closely associated with the risks of diabetes, hypertension, hyperlipidemia and cardiovascular disease (CVD)³. Cardiovascular disease mortality is about 3-fold higher among obese men and women, and about 21 and 28% of cardiovascular disease mortality in men and women, respectively may be attributed to overweight and obesity⁴.

Iran is an urbanized city-state country in the Middle East Region and is considered to be a country in nutrition transition. Like most countries that have undergone rapid economic and demographical transition, non-communicable diseases, especially cardiovascular disease, are the major cause of mortality and morbidity in Iran with a high prevalence reported⁵. On the other hand, although abdominal visceral adipose tissue measured by computed tomography (CT) or magnetic resonance imaging may more accurately reflect body fat distribution to predict metabolic risks^6,7, the inherent high cost and radiation hazard prevent their use in large-scale epidemiological studies or self-assessments. Various indicators for obesity have been described over the last 25 years or so⁸. Body mass index (BMI) is often used to reflect total body fat while the waist circumference (WC), waist to hip ratio (WHR), and waist to height ratio (WHtR) are used as surrogates for central body fat^9,10. Recent studies have shown that WC is the best simple anthropometric measure of abdominal visceral adipose tissue, and may be the best indicator for predicting cardiovascular risks^11-13. Since there are marked gender differences in regional body fat distribution, the anthropometric indicators may also vary in applicability by sex.

Whereas the prevalence of obesity has been increasingly reported in all regions of the world, the status of the prevalence of obesity as a better predictor of cardiovascular risk factors in an urban population of Iran is unknown. Therefore, this study was designed to: (1) provide baseline data on the prevalence and distribution of overweight and obesity, using anthropometric measurements in the population from urban cities in Iran; and (2) determine the relationships between selected cardiovascular risk factors and anthropometric indicators and to identify the anthropometric indicator most closely related to CVD risk factors and whether the magnitude of association varies with gender in the study population.

Methods

Study Population

The study individuals were recruited through a random telephone survey¹⁴ from 7 big cities of Iran based on their populations and invited to one of the appointed health screen centers to undergo anthropometric examination and laboratory tests. In this cross-sectional study, 2179 healthy individuals aged 15 to 74 years (991 men and 1188 women) without any previous systemic diseases or medications related to body weight change or affecting glucose and lipid levels, were included in our study and completed blood tests and anthropometric measurements. The individuals were divided by gender and age (into five age groups: 15-19, 20-29, 30-39, 40-49 and 50+ years old). All the individuals were volunteers and gave their consent for participation into the study, whose protocol was approved by the Ethics Committee of the School of Medical Sciences of Tarbiat Modares University and was in accordance with the Declaration of Helsinki.

Anthropometric measures

The following anthropometric variables were evaluated in all individuals: weight, height, BMI, WC, WHR, WHtR, sum of three-point skinfolds and percentage of body fat. For height, the individuals were instructed to stand as straight as possible with their back against a wall-mounted vertical ruler. Feet were flat on the floor with shoes removed. Weight was measured to the nearest 100 g using a calibrated balance beam scale and with the individual standing and wearing underwear only. BMI was calculated as weight/height squared (kg/m²)¹² and was classified into five categories: underweight (BMI < 18.5 kg/m²), normal weight (BMI 18.5-24.9 kg/m²), overweight (BMI 25.0-29.9 kg/ m²) and obese (BMI > 30.0 kg/m²)¹⁵. Circumferences were measured to the nearest millimeter using a flexible tape. WC was taken at the end of normal expiration, with the measuring tape positioned at the midway between the lower rib and the iliac crest. Men with waist circumference of < 94, 94-101.9 and > 102 cm were classified as normal weight, overweight and obese, respectively, while women were classified in the same obesity categories based on WC < 80, 80-87.9 and > 88 cm. Hip circumference was measured at the level of maximal protrusion of the gluteal muscles. WHR was calculated as WC (cm) divided by hip circumference (cm) and WHtR was calculated as WC (cm) divided by height (cm). Men with WHR < 0.90, 0.90-0.99 and > 1.0 were classified as normal weight, overweight or obese, respectively, while women were classified in the same categories based on WHR of < 0.80, 0.80-0.84 and > 0.85¹. Skinfold thickness (Chest, abdominal, midthigh for men and triceps, suprailium, midthigh for women) was measured in triplicate to the nearest mm, on the right side of the body by Holtain Skinfold Caliper (Holtain Ltd, Crymmych, Dyfed, UK). The mean of three measurements represented the value for each site. Percentage of body fat (PBF) was calculated using the three-site equation^16,17.

Blood sampling and analysis

Blood samples were collected between 7:00 am and 9:00 am after a 12-hour overnight fast. Serum total cholesterol (Tchol) and triglycerides (TGs) were measured using enzymatic colorimetric tests with cholesterol esterase and cholesterol oxidase and glycerol phosphate oxidase, respectively. High-density lipoprotein cholesterol (HDL-C) was measured using the same method after precipitating apolipoprotein B containing lipoproteins with phosphotungstic acid. Serum glucose concentration was assayed using the enzymatic colorimetric method with the glucose oxidase technique (Chemistry analyzer, Roche/Hitachi 904, with Pars Azmoun kits, Tehran, Iran). Inter- and intra-assay coefficients of variations were 2, 0.5% for Tchol and 1.6, 0.6% for TGs and both 2.2% for serum glucose, respectively. Low-density lipoprotein cholesterol (LDL-C) was calculated from the serum Tchol, TGs, and HDL-C concentrations expressed in mg/dl using the Friedwald formula¹⁸ if TGs concentration is lower than 400 mg/dl.

Statistical analysis

All variables are presented as mean and standard deviation or percentage. Independent t-test and repeated-measures analysis of variance (ANOVA) were used to compare quantitative variables between the two groups (men and women) and more than two groups, respectively. Age-adjusted partial correlation coefficients were calculated to investigate the association between anthropometric variables and cardiovascular risk factors. Multiple regression analysis (stepwise method) of the data was carried out. All tests for statistical significance were two-tailed and performed assuming a type I error probability of < 0.05. All data were analyzed by the SPSS software package (SPSS for Windows; SPSS Inc., Chicago, IL, USA; Version 16.00).

Results

Anthropometric measurements

There were significant trends across the age groups for each anthropometric measure in both genders (p < 0.05; Table 1). Within any given age category, men had higher weight and WHR and lower PBF than women (p < 0.001). The greatest differences in WC and WHR were seen between the 20-29 and 30-39 y age groups and 40-49 and 50+ y age groups in men and women, respectively (p = 0.000). The greatest difference in WHtR were seen between the 15-19 and 20-29 y age groups and 40-49 and 50+ y age groups in men and women, respectively (p = 0.000).

Prevalence of overweight and obesity

Irrespective of age or measures used, women had a higher prevalence of obesity than men (Table 2). Based on BMI, almost half of men and over 50% of women were either overweight or obese with 10.2% of men and 18.6% of women in the obese category. The prevalence of BMI obesity increased with age until 50+ yrs. This trend was more pronounced among women (main effect for age-gender interaction p = 0.001). The difference in the prevalence of obesity between men and women was particularly large in the older age group (50+ years).

Cardiovascular risk factors

Glucose, TGs and Tchol/HDL-C ratio were significantly higher in men, while LDL-C and HDL-C were significantly higher in women (p < 0.05; Table 3). The mean values of glucose, Tchol and TGs increased significantly in ascending age groups in men, while values of Tchol, TGs, LDL-C and Tchol/HDL-C ratio increased significantly in ascending age groups in women (p < 0.05).

Anthropometric indicators and cardiovascular risk factors based on BMI groups

The mean values of weight, WC, WHR, WHtR and PBF increased significantly in ascending BMI categories in both genders (p < 0.001; Table 4). In addition, significant differences were observed in cardiovascular risk factors according to different BMI groups in men (p < 0.05), while it was just significant in Tchol/HDL-C ratio for women.

Correlation between anthropometric measurements

WC, BMI, WHR and WHtR were strongly correlated in both sexes (p < 0.001; Table 5), suggesting that measures of obesity based on these parameters will provide comparable information. However, PBF showed a weaker correlation with the other anthropometric measurements in women.

Correlation between anthropometric measurements and cardiovascular risk factors

In men, a highly significant correlation was found between WC, BMI, WHR and WHtR on the one hand and serum lipid values on the other hand (p < 0.05; Table 6). When adjustments were made for both age and BMI, there were just significant correlations between WC, WHR, WHtR and HDL-C and between WC and Tchol/HDL-C ratio (p < 0.05). When adjustments were made for both age and WC, there were just significant correlations between BMI, WHR, WHtR and triglycerides (data not shown in table; p < 0.05). There were weaker correlations between anthropometric measurements and serum lipid values in women. WC, WHR and WHtR had significant correlations with most of the serum lipid values (p < 0.05). When adjustments were made for both age and BMI, there were just significant correlations between WC, WHtR and Tchol/HDL-C ratio and between WHR and triglycerides (p < 0.05). When adjustments were made for both age and WC, there were just significant correlations between WHR and triglycerides (data not shown in table; p < 0.05).

Independent determinants of cardiovascular risk factors

In men, WHR was a significant predictor for glucose, Tchol and LDL-C, whereas WHtR was a significant predictor for glucose, HDL-C and Tchol/HDL-C ratio (Table 7). On the other hand, BMI was a significant predictor for triglycerides and HDL-C. The percentage of variation of glucose and lipid levels explained by these parameters, however, was modest. WHR explained 7.4% of glucose variation, 31.1% of Tchol variation and 29.2% of LDL-C variation. WHtR explained 9.3% of glucose, 15.2% of HDL-C and 36% of Tchol/HDL-C ratio variation. BMI explained 26.4% of triglyceride and 10% of HDL-C variation. In women, WHR was a significant predictor for glucose, Tchol and triglycerides, whereas WC was a significant predictor for LDL-C, HDL-C and Tchol/HDL-C ratio. WHR explained 17% of glucose, 20.4% of Tchol and 31.7% of triglyceride variation. WC explained 16.1% of LDL-C, 8.6% of HDL-C and 22.7% of Tchol/HDL-C ratio variation.

Discussion

The International Obesity Task Force reported that the Middle East is one of the regions with the highest prevalence rates of obesity worldwide¹⁹. In our study, prevalence of overweight as defined by BMI increased to a peak of 63.0% and 42.7% in the 40-49 y age group in men and women, respectively. Prevalence of obesity as calculated by BMI continued to increase to a maximum of 14.8 and 35.7% in the 50+ y age group in men and women, respectively. In addition, central obesity is a recognized predictor of coronary artery disease, and men usually have a higher WC and WHR than women³; however, we found that central obesity was more frequent in the women of any age groups. The prevalence of general overweight and obesity in this population (BMI > 25 kg/m², males 49.6% and females 53%) is higher than that among the urban population of Cameroon (males 28.1% and females 48.1%)². Based on these findings, overweight and obesity were of high prevalence in the adult urban population of Iran and the prevalence of obesity in women of any age groups was higher than that of men. Ideal BMI for the prevention of cardiovascular disease is considered to be 22.6 and 21.1 for men and women, respectively²⁰. In this study, the mean BMI of each sex-age group was above these cutoff points. The results of few studies conducted in some cities of Iran showed large differences.

A study in Tehran, the capital of Iran, showed much higher prevalence rates of general and abdominal obesity; 67% of women and 29% of men were obese and abdominal obesity was detected in 93% of women and 74.1% of men²¹. Hosseinpanah et al²² studied the prevalence of obesity in a follow-up study in district 13 of Tehran. The prevalence of general obesity was 15.8, 18.6 and 21% in men and 31.5, 37.7 and 38.6% in women in phases I, II and III, respectively, while the prevalence of abdominal obesity in men was 36.5, 57.2 and 63.3% and in women was 76.7, 83.8 and 83.6% in the three periods mentioned. These results showed an increasing trend of obesity in the adult Tehranian population over 6.6 years of follow-up. Prevalence rates in various studies from the Middle East show considerable variation.

In a study conducted in Egypt, the prevalence of obesity was 40.6% among women living in urban areas²³. The prevalence of obesity among Turkish women and men was 32.4% and 14.1%²⁴, whereas the prevalence of abdominal obesity was 29.4% (38.9% among women and 18.1% among men)²⁵. A recent national study in Lebanon demonstrated that the prevalence of overweight was higher in men than in women, i.e. 57.7% vs. 49.4%, respectively, but obesity was more prevalent in women (18.8%) than in men (14.3%)²⁶. Similarly, the prevalence of overweight was higher in men than women, i.e. 39.4% vs. 34.4%, respectively, but obesity was more prevalent in women (18.6%) than in men (10.2%) in our study.

Results from CT indicate that central obesity, especially intra-abdominal fat accumulation, is a critical variable in the study of the ratio of body fat distribution to metabolic complications³. Despite the close association between central adiposity and cardiovascular risks, there is still some controversy regarding the best anthropometric measure for central adiposity. Since there are marked gender differences in regional body fat distribution, the anthropometric indicators may also vary in applicability by sex. In this study, we compared the correlations between five obesity parameters (BMI, WC, WHR, WHtR and PBF) and selected cardiovascular risk factors. The anthropometric measurements, except PBF, were strongly correlated with each other in this study. The correlations of indices of overall and central obesity are highly suggestive of an association between increased overall obesity (as measured by BMI) with increased abdominal obesity.

Després et al have reported that the regional distribution of body fat, especially an excessive deposition of abdominal fat, was associated with low concentrations of HDL-C.³ In the Canadian Heart Health Survey, Ledoux et al²⁷ found that anthropometric measures were moderately associated with the presence of high blood pressure, dyslipidemia and diabetes mellitus in adults and that BMI as well as waist circumference and WHR played a roughly equal role. Of all risk factors measured for CVD in this study, increased TGs and Tcho/HDL-C ratio were significantly associated with most of the anthropometric indices in both men and women in our study; however, the correlations were more pronounced in men. Using computed tomographic scanning to measure adipose tissue, WC is found to be a better estimate of abdominal visceral adipose accumulation than WHtR and may be a better predictor of multiple cardiovascular risk factors than WHR¹⁰. Based on the results of multiple regression analysis in our study, BMI, WHtR and WHR explained the highest percentage of variation of TGs, Tcho/HDL-C ratio and LDL-C in men, respectively, whereas WHR explained the highest percentage of variation of TGs and WC explained the highest percentage of variation of Tcho/HDL-C ratio and LDL-C in women. Ho et al¹⁴ found that BMI in men and WHR in women were the important anthropometric indices to predict metabolic syndrome (hypertension or diabetes or dislipidemia). Furthermore, the relationship between anthropometric indices and cardiovascular risk factors may be age-specific. Rimm et al²⁸, for instance, found in a large prospective study of US men, that before the age of 65 y, BMI was the best predictor of coronary heart disease, whereas in men aged > 65 y the WHR was a better predictor of risk. Goodman-Gruen and Barret-Connor²⁹ found that after the age of 80 y, WHR is a poor method of assessing central or visceral adiposity and waist circumference is a better measure of fat distribution. The Iowa Women's Health Study cohort³⁰ examined the relation of both self-reported WHR and BMI with 5-year mortality in a cohort of older women. They showed that WHR is strongly and positively associated with risk of death in a monotonic dose-response fashion. Onat and coworkers³¹ reported that only WHR was independently associated with coronary morbidity in women. In another study, Ward et al³² reported that WHR was related to triglycerides regardless of BMI and insulin levels in middle-aged and older people. Similar results were observed in our study. Clearly, there is a need for clarification about the appropriate use for these indicators when examining their relationship with CVD risk factors. The literature lacks a systematic evaluation of the proposed indicators for adiposity, taking into account possible differences between the genders, age categories and ethnic groups and different diseases as well as mortality. Important limitations of WHR are that WHR cannot be clearly interpreted, because two variables are involved and a high ratio that may be obtained in an individual with a small hip circumference or a low ratio in an individual with a large hip circumference for the same abdominal girth³. On the other hand, the lack of a standard body location for measuring WC makes comparison with other studies difficult. Standard methodology is necessary to obtain reliable measures of abdominal circumference. It has also been reported that the association between WC and risk factors for cardiovascular disease may be population-dependent⁸. Furthermore, in the elderly, waist circumference measurements may be overestimated and be inaccurate, since the laxity of abdominal muscles, which is typical in the elderly, is likely to undermine the predictive value of abdominal circumferences³³. Therefore, no single cut-off point of WC is optimal for all ages and for different cardiovascular risk factors.

Conclusions

The study provided insights into the relationship between age, sex, overweight and obesity using a variety of anthropometric measures. Our results highlighted the high prevalence of general and abdominal overweight and obesity in both sexes of urban populations of Iran as defined by the WHO criteria and provided evidence to support the establishment of intervention programs to manage and prevent obesity-related disorders such as diabetes and hypercholesterolemia. There currently is an increasing rate of urbanization in developing countries, which may have an impact on obesity and its associated CVD risk factors in the future. In addition, the association of anthropometric indices and cardiovascular risk factors varied with gender. Our data indicated that WHR and WHtR were the anthropometric indicators that best predicted CVD risk factors in men and WHR and WC in women living in Iran.

Acknowledgements

This study was funded by the Sport Sciences Research Center (SSRC-850607). We would like to acknowledge the study participants and field workers for their participation in the hard work of this study.

References

• 1. WHO Investigators. Obesity: preventing and managing the global epidemic. Report of a WHO consultation. World Health Organ Tech Rep Ser 2000; 894:i-xii, 1-253.
• 2. Kamadjeu RM, Edwards R, Atanga JS, Kiawi EC, Unwin N, Mbanya JC. Anthropometry measures and prevalence of obesity in the urban adult population of Cameroon: an update from the Cameroon Burden of Diabetes Baseline Survey. BMC Public Health. 2006 Sep 13;6:228.
• 3. Després JP, Moorjani S, Lupien PJ, Tremblay A, Nadeau A, Bouchard C. Regional distribution of body fat, plasma lipoproteins, and cardiovascular disease. Arteriosclerosis. 1990;10(4):497-511.
• 4. Seidell JC, Verschuren WM, van Leer EM, Kromhout D. Overweight, underweight, and mortality: a prospective study of 48287 men and women. Arch Intern Med. 1996;156(9):958-63.
• 5. Azizi F, Ghanbarian A, Momenan AA, Hadaegh F, Mirmiran P, Hedayati M, et al. Prevention of non-communicable disease in a population in nutrition transition: Tehran Lipid and Glucose Study phase II. Trials. 2009 Jan 25;10:5.
• 6. Fujioka S, Matsuzawa Y, Tokunaga K, Tarui S. Contribution of intra-abdominal fat accumulation to the impairment of glucose and lipid metabolism in human obesity. Metabolism. 1987;36(1):54-9.
• 7. Caprio S, Hyman LD, McCarthy S, Lange R, Bronson M, Tamborlane WV. Fat distribution and cardiovascular risk factors in obese adolescent girls: importance of the intra-abdominal fat depot. Am J Clin Nutr. 1996;64(1):12-7.
• 8. Molarius A, Seidell JC. Selection of anthropometric indicators for classification of abdominal fatnessa critical review. Int J Obes Relat Metab Disord. 1998;22(8):719-27.
• 9. Mueller WH, Wear ML, Hanis CL, Emerson JB, Barton SA, Hewett-Emmett D, et al. Which measure of body fat distribution is best for epidemiologic research? Am J Epidemiol. 1991;133(9):858-69.
• 10. Pouliot MC, Després JP, Lemieux S, Moorjani S, Bouchard C, Tremblay A, et al. Waist circumference and abdominal sagittal diameter: best simple anthropometric indexes of abdominal visceral adipose tissue accumulation and related cardiovascular risk in men and women. Am J Cardiol. 1994;73(7):460-8.
• 11. Lemieux S, Prud'homme D, Bouchard C, Tremblay A, Després JP. A single threshold value of waist girth identifies normal-weight and overweight subjects with excess visceral adipose tissue. Am J Clin Nutr. 1996;64(5):685-93.
• 12. Dobbelsteyn CJ, Joffres MR, MacLean DR, Flowerdew G. A comparative evaluation of waist circumference, waist-to-hip ratio and body mass index as indicators of cardiovascular risk factors. The Canadian Heart Health Surveys. Int J Obes Relat Metab Disord. 2001;25(5):652-61.
• 13. Olinto MT, Nacul LC, Gigante DP, Costa JS, Menezes AM, Macedo S. Waist circumference as a determinant of hypertension and diabetes in Brazilian women: a population-based study. Public Health Nutr. 2004;7(5):629-35.
• 14. Ho SC, Chen YM, Woo JL, Leung SS, Lam TH, Janus ED. Association between simple anthropometric indices and cardiovascular risk factors. Int J Obes Relat Metab Disord. 2001;25(11):1689-97.
• 15. Physical status: the use and interpretation of anthropometry. Report of a WHO Expert Committee. World Health Organ Tech Rep Ser. 1995;854:1-452.
• 16. Jackson AS, Pollock ML. Generalized equations for predicting body density of men. Br J Nutr. 1978;40(3):497-504.
• 17. Jackson AS, Pollock ML, Ward A. Generalized equations for predicting body density of women. Med Sci Sports Exerc. 1980;12(3):175-81.
• 18. Friedewald WT, Levy RI, Fredrickson DS. Estimation of the concentration of low-density lipoprotein cholesterol in plasma, without use of the preparative ultracentrifuge. Clin Chem. 1972;18(6):499-502.
• 19. James PT, Leach R, Kalamara E, Shayeghi M. The worldwide obesity epidemic. Obes Res. 2001;9(Suppl 4):228S-233S.
• 20. Kannel WB, D'Agostino RB, Cobb JL. Effect of weight on cardiovascular disease. Am J Clin Nutr. 1996;63(3 Suppl):419S-422S.
• 21. Azadbakht L, Mirmiran P, Shiva N, Azizi F. General obesity and central adiposity in a representative sample of Tehranian adults: prevalence and determinants. Int J Vitam Nutr Res. 2005;75(4):297-304.
• 22. Hosseinpanah F, Barzin M, Sarbakhsh-Eskandary P, Mirmiran P, Azizi F. Trends of obesity and abdominal obesity in Tehranian adults: acohort study. BMC Public Health. 2009 Nov 23;9:426.
• 23. Galal OM. The nutrition transition in Egypt: obesity, under nutrition and the food consumption context. Public Health Nutr. 2002;5(1A):141-8.
• 24. Yumuk VD, Hatemi H, Tarakci T, Uyar N, Turan N, Bagriacik N, et al. High prevalence of obesity and diabetes mellitus in Konya, a central Anatolian city in Turkey. Diabetes Res Clin Pract. 2005;70(2):151-8.
• 25. Erem C, Arslan C, Hacihasanoglu A, Deger O, Topbas M, Ukinc K, et al. Prevalence of obesity and associated risk factors in a Turkish population (Trabzon city, Turkey). Obes Res. 2004;12(7):1117-27.
• 26. Sibai AM, Hwalla N, Adra N, Rahal B. Prevalence and covariates of obesity in Lebanon: findings from the first epidemiological study. Obes Res. 2003;11(11):1353-61.
• 27. Ledoux M, Lambert J, Reeder BA, Després JP. Correlation between cardiovascular disease risk factors and simple anthropometric measures. Canadian Heart Health Surveys Research Group. CMAJ. 1997;157(Suppl 1):S46-53.
• 28. Rimm EB, Stampfer MJ, Giovannucci E, Ascherio A, Spiegelman D, Colditz GA, et al. Body size and fat distribution as predictors of coronary heart disease among middle-aged and older US men. Am J Epidemiol. 1995;141(12):1117-27.
• 29. Goodman-Gruen D, Barrett-Connor E. Sex differences in measures of body fat and body distribution in the elderly. Am J Epidemiol. 1996;143(9):898-906.
• 30. Folsom AR, Kaye SA, Sellers TA, Hong CP, Cerhan JR, Potter JD, et al. Body fat distribution and 5-year risk of death in older women. JAMA. 1993;269(4):483-7
• 31. Onat A, Sansoy V, Uysal O. Waist circumference and waist-to-hip ratio in Turkish adults: interrelation with other risk factors and association with cardiovascular disease. Int J Cardiol. 1999;70(1):43-50.
• 32. Ward KD, Sparrow D, Vokonas PS, Willett WC, Landsberg L, Weiss ST. The relationships of abdominal obesity, hyperinsulinemia and saturated fat intake to serum lipid levels: the Normative Aging Study. Int J Obes Relat Metab Disord. 1994;18(3):137-44.
• 33. Turcato E, Bosello O, Di Francesco V, Harris TB, Zoico E, Bissoli L, et al. Waist circumference and abdominal sagittal diameter as surrogates of body fat distribution in the elderly: their relation with cardiovascular risk factors. Int J Obes Relat Metab Disord. 2000;24(8):1005-10.

Anthropometric measures as predictors of cardiovascular disease risk factors in the urban population of Iran

Reza Gharakhanlou^I; Babak Farzad^I; Hamid Agha-Alinejad^I; Lyn M. Steffen^II; Mahdi Bayati^I

Publication Dates

• Publication in this collection
  09 Jan 2012
• Date of issue
  Feb 2012

History

• Received
  20 June 2011
• Accepted
  24 Aug 2011
• Reviewed
  11 Aug 2011