Published on

Human movement 2010

Published in: Education
  • Be the first to comment

  • Be the first to like this

No Downloads
Total views
On SlideShare
From Embeds
Number of Embeds
Embeds 0
No embeds

No notes for slide


  1. 1. HUMAN MOVEMENT 2010, vol. 11 (1), 45–50BODY FAT DEPOSITION AND RISK FACTORSOF CARDIOVASCULAR DISEASES IN MENDOI: 10.2478/v10038-009-0022-2 Maria Fátima Glaner1*, William Alves Lima1, Zbigniew Borysiuk2 1 Post-Graduate Physical Education Program, Catholic University of Brasília, Brasília, DF, Brazil 2 Faculty of Physical Education and Physiotherapy, Opole University of Technology, Opole, PolandABSTRACTPurpose. To determine whether risk factors for cardiovascular diseases (anthropometry, blood pressure, blood lipid profile) differbetween men classified into the three relative body fat %BF categories (%BF £ 19: healthy; %BF > 19 and %BF < 30: overweight, and%BF ³ 30: obesity). Basic procedures. A total of 112 volunteers from Brasília, Brazil, were submitted to the measurement of bodyweight, height and waist, abdominal and hip circumference. The body mass index (BMI) and waist-to-hip ratio (WHR) werecalculated. %BF and body fat topography (arm, leg and trunk %BF) were estimated by dual-energy X-ray absorptiometry (DXA).Blood pressure was measured by auscultation and blood variables were determined by an enzymatic method. Univariate analysis ofvariance, one-way analysis of variance and the Scheffé post hoc test were used for statistical analysis (p < 0.05). Main findings. Thethree %BF groups differed significantly in terms of body weight and body circumference measures, with higher mean values beingobserved the higher the %BF. Fasting glycemia and high-density lipoprotein did not differ between groups, indicating the interferenceof other factors. BMI, WHR, blood pressure, total cholesterol, low-density lipoprotein, triglycerides, atherogenic index andatherogenic cholesterol were statistically similar in the overweight and obese groups and differed significantly from the healthygroup. Conclusions. Abdominal, waist, hip circumference and body fat topography (arm, leg and trunk %BF) differ between the three%BF groups. None of the blood variables differed significantly between the overweight and obese groups. The cutoff %BF > 19(measured by DXA) seems to be a good parameter to indicate cardiovascular risk factors in men.Key words: anthropometry, body fat, coronary disease, DXA, HDL, LDL Introduction systolic and diastolic blood pressure, fasting glycemia, total cholesterol (TC), low-density lipoprotein (LDL), Worldwide, more than one billion adults present ex- triglycerides (TG), atherogenic index (AI) and athero-cess body fat and at least 300 million of them are obese genic cholesterol, in addition to a decrease in high-densi-[1]. In Brazil, about 43% of the adult population is esti- ty lipoprotein (HDL) concentrations.mated to present some degree of excess body fat, with Individuals presenting some degree of obesity (%BF11% of severe cases [2]. Excess body fat contributes to >30) and an android profile of body fat distribution (to-the development of different risk factors related to car- pography) characterized by greater fat deposition in thediovascular diseases. In addition, excess body fat repre- central region of the body are at a higher risk of develop-sents a constant overload which puts an extra workload ing cardiovascular diseases [6, 12]. To classify these car-on the heart [3]. diovascular risks resulting from excess body fat, some Studies have indicated that men with a relative body studies have used indicators such as body mass indexfat (%BF) above 19% are at a higher risk for the develop- (BMI), waist-to-hip ratio (WHR), body circumferencement of nontransmissible chronic diseases such as heart [8, 12–14] and body fat topography [4, 6, 10]. However, itdiseases, strokes [4–6], hypertension [7], dyslipidemias, remains to be determined whether variations in these riskdiabetes mellitus, atherosclerosis [8–10], gallstones, neo- factors indeed exist with increasing %BF stores (%BF ≤plasms, and liver diseases, among others [11]. Thus, the 19: healthy; %BF > 19 and %BF < 30: overweight, andfollowing important factors should be monitored for the %BF ≥ 30: obesity). This %BF classification is based onevaluation of the development of these diseases: a rise in conclusions reported in different studies [2, 5, 8, 11, 13]. Therefore, the objective of the present study was to* Corresponding author. determine whether risk factors for cardiovascular dis- 45
  2. 2. HUMAN MOVEMENTM.F. Glaner, W.A. Lima, Z. Borysiuk, Body fat and cardiovascular risk eases (anthropometry, blood pressure, blood lipid pro- very low-density lipoprotein (VLDL) in relation to file) differ between men classified into the three %BF HDL, the higher the chances of developing atheroscle- categories (healthy, overweight and obese). rotic disease [13]. The concentration of atherogenic cholesterol (AC) was calculated by the formula AC = Material and methods TC – HDL, since TC corresponds to the sum of HDL + LDL + VLDL [16, 17]. Subjects After data collection, the sample was divided into groups by %BF and age: %BF ≤ 19 (n = 53) classified The sample consisted of 112 adult men living in as healthy and characterized as subjects at a lower risk Brasília, DF, Brazil. All participants were employees of for cardiovascular diseases, %BF > 19 and %BF < 30 the same metallurgy company but performed different (n = 44) classified as overweight, %BF ≥ 30 (n = 15) functions (workers and administrators). The study was classified as obesity; age 40 years old, and age > 40 approved by the Ethics Committee of the Catholic Uni- years old. versity of Brasília. The volunteers signed a free in- formed consent form containing detailed information Statistical analysis regarding the type, conditions and place of data collec- tion and an authorization for the use of their data in sci- Descriptive variables are reported as mean, standard entific publications. deviation and range. With %BF as the dependent varia- ble, was performed a univariate analysis of variance on Variables the independent variables %BF groups and age groups. The results in terms of main effects showed that there is The following variables were measured on the first no interaction between %BF groups and age groups. day of data collection: body weight, height, waist cir- Therefore, the one-way analysis of variance was used to cumference (WC) 2.5 cm above the umbilical scar, ab- compare %BF groups. The post hoc Scheffé test was dominal circumference over the umbilical scar and hip adopted to localize possible differences (p < .05). circumference (HC) in the most prominent portion of the greater trochanters. BMI and WHR were calculated Results using the following formulas: BMI = weight (kg) / height2 (m) and WHR = WC / HC (cm). A wide variation in minimum and maximum values Whole body fat and body fat topography (arm, leg was observed for age, body weight, height, BMI, body and trunk %BF) were estimated by dual-energy X-ray circumference measures and %BF, characterizing the absorptiometry (DXA). A whole-body scan was per- heterogeneity of the sample (Tab. 1). formed with a Lunar DPX-IQ apparatus (software ver- The age has no significant effect on %BF and there sion 4.7e) according to manufacturer’s instructions. was no interaction between %BF groups and age groups After the end of this procedure, the volunteers re- (Tab. 2). mained in the supine position for the measurement of The anthropometric variables according to the accu- systolic and diastolic blood pressure in the left arm by mulation of %BF are presented in Tab. 3. Height was auscultation using a stethoscope and an aneroid sphyg- momanometer. Table 1. Descriptive characteristics of the 112 adult men participating in the study On the second day, a venous blood sample was col- lected between 6:00 and 8:00 am after a minimum fast- Variables Mean ± SD Range ing period of 12 h for the quantification of plasma glyc- Age (years) 34.1 ± 9.0 20–55 Body weight (kg) 71.7 ± 10.2 51.7–95.0 emia, TC, HDL, and TG. These variables were meas- Height (cm) 168.4 ± 7.0 152.0–189.0 ured by a colorimetric enzymatic method using Doles Body mass index (kg/m2) 25.3 ± 3.1 17.8–33.6 kits in a semiautomatic BIO-2000 spectrophotometer Waist circumference (cm) 85.6 ± 9.1 67.5–103.0 (Bioplus®). LDL was estimated using the formula of Abdominal circumference (cm) 86.9 ± 9.5 54.7–106.0 Friedewald et al. [15]: LDL = ((TG / 5) + HDL) – TC). Hip circumference (cm) 93.5 ± 6.2 77.0–109.3 In addition, the AI was estimated using the formula AI Relative body fat 20.0 ± 8.3 6.0–31.7 = TC / HDL [9, 13]. The higher the amount of LDL and SD – standard deviation 46
  3. 3. HUMAN MOVEMENT M.F. Glaner, W.A. Lima, Z. Borysiuk, Body fat and cardiovascular risk Table 2. Relative body fat (%BF) in the two age groups %BF group Age group Mean ± SD %BF ≤ 19 ≤ 40 years (n = 46) 12.3 ± 3.9 > 40 years (n = 7) 13.9 ± 3.4 Total (n = 53) 12.5 ± 3.8 %BF > 19 and %BF < 30 ≤ 40 years (n = 26) 24.1 ± 3.1 > 40 years (n = 18) 26.2 ± 2.2 Total (n = 44) 24.9 ± 3.0 %BF ≥ 30 ≤ 40 years (n = 13) 32.5 ± 2.0 > 40 years (n = 2) 31.8 ± 1.4 Total (n = 15) 32.4 ± 1.9 Total ≤ 40 years (n = 85) 19.0 ± 8.5 > 40 years (n = 27) 23.4 ± 6.4 Total (n = 112) 20.0 ± 8.3SD – standard deviation%BF group: F test = 145.4 (p = 0.000), observed power = 1Age group: F test = 1.1 (p = 0.304), observed power = 0.176Interaction %BF group × age group: F test = 0.611 (p = 0.545), observed power = 0.150 Table 3. Anthropometric variables in the three relative body fat (%BF) groups Variables %BF ≤ 19 %BF > 19 and %BF < 30 %BF ≥30Body weight (kg) 65.2a ± 8.5 75.9b ± 7.5 82.2c ± 6.1Height (cm) 168.7a ± 6.8 167.1a ± 7.2 171.0a ± 6.4Body mass index (kg/m2) 22.9a ± 2.2 27.3b ± 2.0 28.1b ± 2.2 aWaist circumference (cm) 77.9 ± 5.6 91.5b ± 5.3 95.2c ± 3.6 aAbdominal circumference (cm) 79.1 ± 6.6 92.6b ± 5.6 97.4c ± 3.5 aHip circumference (cm) 89.6 ± 4.8 96.0b ± 5.1 100.1c ± 3.7 aWaist-hip ratio 0.88 ± 0.06 0.97b ± 0.04 0.97b ± 0.04Data are reported as mean ± standard deviationMeans followed by the same letter did not differ significantly (p > .05) Table 4. Blood pressure and body fat topography in the three relative body fat (%BF) groups Variables %BF ≤ 19 %BF > 19 and %BF < 30 %BF ≥ 30 SBP (mmHg) 124.0a ± 11.2 133.6b ± 17.3 141.0b ± 20.0 DBP (mmHg) 78.4a ± 11.0 90.0b ± 12.8 93.3b ± 13.3 % Arm fat 6.7a ± 2.4 15.4b ± 3.6 19.4c ± 3.2 % Leg fat 12.6a ± 3.8 23.6b ± 4.0 32.3c ± 4.0 % Trunk fat 14.0a ± 4.8 28.0b ± 4.7 36.4c ± 1.9 %BF 12.5a ± 3.8 24.9b ± 3.0 32.4c ± 1.9SBP – systolic blood pressure, DBP – diastolic blood pressureData are reported as mean ± standard deviationMeans followed by the same letter did not differ significantly (p > .05) Table 5. Blood variables in the three relative body fat (%BF) groups Variables %BF ≤ 19 %BF > 19 and %BF < 30 %BF ≥ 30Fasting glycemia (mg/dL) 91.2a ± 10.0 96.8a ± 21.3 94.5a ± 6.7Total cholesterol (mg/dL) 147.3a ± 28.4 174.7b ± 40.9 188.4b ± 29.8High-density lipoprotein (mg/dL) 41.9a ± 12.5 36.5a ± 8.6 36.1a ± 7.8Low-density lipoprotein (mg/dL) 84.1a ± 26.7 105.0b ± 41.1 120.2b ± 26.6Triglycerides (mg/dL) 109.8a ± 71.0 168.4b ± 91.6 164.3b ± 72.4Atherogenic index 3.8a ± 1.5 5.1b ± 1.8 5.4b ± 1.3Atherogenic cholesterol (mg/dL) 109.1a ± 35.8 143.5b ± 49.2 153.1b ± 29.2Data are reported as mean ± standard deviationMeans followed by the same letter did not differ significantly (p > .05) 47
  4. 4. HUMAN MOVEMENTM.F. Glaner, W.A. Lima, Z. Borysiuk, Body fat and cardiovascular risk similar in the three groups. Body weight and the body With respect to the lack of a significant difference in circumference parameters differed significantly be- the WHR between the overweight and obese groups, one tween the three groups. In contrast, BMI and WHR may speculate that, although the mean difference in waist were statistically similar in the overweight and obese and hip circumference between the two groups was ap- groups and differed significantly from the healthy proximately 6 and 5 cm, respectively (Tab. 3), the mathe- group. The overweight and obese groups were also matical equation adopted masked this difference. Since similar in terms of systolic and diastolic blood pressure. the ratio of these measures generates values close to 1.0, Body fat topography and %BF differed significantly very close results are obtained and no statistical diffe- between the three groups (Tab. 4). rence might be observed. Thus, waist and/or abdominal With respect to the blood variables, fasting glycemia circumference analyzed separately might be better pre- and HDL did not differ significantly between the three dictors of the risk for cardiovascular diseases since in the %BF groups. Atherogenic cholesterol, TC, LDL, TG present sample these measures differed between the three and AI were statistically similar in the overweight and %BF groups. In this respect, the WHR loses its expres- obese groups and differed significantly from the healthy siveness for overweight or obese individuals (Tab. 3). group (Tab. 5). This conclusion agrees with the results reported in other studies which also emphasized that waist and abdominal Discussion circumference alone are better indicators of the develop- ment of cardiovascular risk [12, 13, 18, 23]. Although Several lines of evidence indicate that excess body these measures are not related to height, they are still fat promotes the development of non-transmissible a better parameter of excess fat in the abdominal region. chronic diseases and risk factors for cardiovascular dis- Analysis of body fat topography showed that fat ac- eases [1, 2, 6–8, 10], and that %BF is affected by age, cumulated in the trunk and body segments increased sex, body build and level of physical fitness [18]. In this concomitantly with increasing %BF. In addition, the study, it was shown that there is no interaction between amount of trunk fat predominated compared to the oth- %BF groups and age groups, and that age has no sig- er body fat deposits, a fact emphasizing the android pat- nificant effect on %BF. This can be explained by the tern of body fat distribution, irrespective of %BF clas- rise in worldwide obesity and/or overweight [1, 2] and sification (Tab. 4). Greater trunk-fat mass was associat- in Brazilian children and adolescents [19, 20]. Thus, in ed with unfavorable values of most cardiovascular view of the practicality of BMI for the classification of disease risk [24]. subjects into underweight, healthy weight, overweight No difference in systolic or diastolic blood pressure or obesity, this parameter has become one of the indices was observed between the overweight and obese groups, most often used worldwide for this purpose [12, 13]. in agreement with other studies [7, 25]. This finding However, its main utility is to facilitate the comparison may indicate that the simple state of overweight is suf- and interpretation of body weight estimates standard- ficient for a blood pressure rise. As a result of physio- ized for height based on the assumption that excess logical adaptations of an organism, the process of blood body weight corresponds to large amounts of stored pressure increases and then becomes slower and is sub- body fat [21]. However, it should be emphasized that ject to lifestyle, dietary habits and the use of pharmaco- BMI does not distinguish between body mass compo- logical drugs [11, 21]. nents (fat, muscle and bone mass), a fact requiring Despite discussions regarding the existence of greater care when using this index as an indicator of a strong positive association between arterial hyperten- adiposity. Although not discriminatory for true amounts sion and obesity [7, 25], the present results (Tab. 4) of body fat, BMI can be a good epidemiological marker show that a state of overweight is already an aggravat- [22]. This affirmation seems to agree with the present ing factor for high blood pressure. The state of obesity, results since BMI did not differ significantly between however, will render the process of weight loss more overweight and obese subjects (Tab. 3), indicating an time consuming and difficult, with a consequent in- important classification error that might assign obese crease in the duration of installed hypertension. This individuals to a less worrisome condition and thus delay fact, together with an increase in the concentrations of appropriate treatment. blood risk factors, may accelerate the development of cardiovascular diseases. 48
  5. 5. HUMAN MOVEMENT M.F. Glaner, W.A. Lima, Z. Borysiuk, Body fat and cardiovascular risk Among the blood variables studied, fasting glycemia This finding indicates that the presence of excess bodydid not differ significantly between the three groups, fat was sufficient to increase the AI in this sample. Onedemonstrating that, on average, the volunteers presented of the main consequences of an increased AI is the fa-no problems of decompensation, irrespective of the cilitation of the formation of atheroma plaques due toamount of %BF. Changes in fasting glycemia generally excess circulating LDL compared to HDL. This facttend to occur with a concomitant increase of lipid blood also indicates that, although TC and LDL did not exceedvariables (TC, LDL and TG) above reference values [10, their tolerable borderline values, the balance between13], a fact generally not observed in the present sample. LDL and HDL was not acceptable, demonstrating theHigh total fat mass and lower trunk-fat mass cannot be need for interventions to regulate these concentrations.explained by insulin sensitivity [24] and, fasting glyce- In this case, nonpharmacological treatment should in-mia was not predicted by total or regional %BF [4]. clude a specific diet and regular systematic physical On average, TC and LDL did not exceed the border- exercise adapted to the needs of each individual [11].line reference values (200 mg/dL and 130 mg/dL, re- Although, on average, atherogenic cholesterol (Tab. 5)spectively) for the desired fasting concentration [13]. did not exceed the borderline reference value (<160 mg/However, overweight and obese subjects were statisti- dL) [16, 17], a significant increase in this parameter wascally similar but differed significantly from the healthy observed for overweight and obese subjects comparedgroup. Higher TC and LDL concentrations are observed to individuals with healthy %BF. These two groupsduring the period of installation of the state of over- were also found to be highly heterogenous, indicatingweight or obesity. This condition may stabilize over the presence of subjects in whom atherogenic cholester-time and the organism tends to potentiate the uptake of ol exceeded the reference value, in partial agreementLDL into adipose tissue by an increase in the number of with other studies [16, 17]. It should be emphasized that,receptors, consequently reducing TC [26]. This fact even when LDL concentrations are within acceptablewould explain the lack of difference between over- limits, they might be high in relation to HDL which, ac-weight and obese subjects. cording to lifestyle, may result in the future formation In view of the cross-sectional character of the of atheroma plaques. This applies to both atherogenicpresent study, we do not know for how long the subjects cholesterol and AI. Thus, the ideal would be to increasewere sustaining the current amounts of %BF. A longitu- HDL concentrations and to reduce LDL levels. Accord-dinal follow-up of the sample would be necessary for ing to some studies [16, 17], the best way to achieve thisfurther conclusions as done by Mansur et al. [27], who goal is the implementation of a systematic aerobic train-emphasized that the longer the time a subject is obese, ing program.the greater the chances of developing atheroma plaques Limitations of the present study were its cross-sec-because of the subsequent inability to remove choles- tional character (which does not permit the determi-terol and TG from blood. nation of how long the volunteer was sustaining the In the present study, on average, the healthy group current %BF) and the use of a semiautomatic spectro-did not exceed the desired TG concentration of 150 mg/ photometer (which is less accurate than an automaticdL, in contrast to overweight and obese subjects. The one). However, various medium- and small-size labora-lack of difference in TG between the last two groups tories in Brazil use this instrument for the diagnosis ofmight be explained by the fact that this parameter is biochemical factors such as those studied here. Anotheronly partially influenced by %BF and is better ex- limitation is the fact that we did not evaluate the life-plained by genetic factors, dietary habits and level of style of the volunteers in order to identify subjects pre-physical activity, among others [8]. Similarly, HDL con- senting greater risk behaviors for the development ofcentration highly depends on genetic factors and the cardiovascular diseases.level of physical activity and is poorly influenced by theaccumulation of body fat [16, 17]. Therefore, this varia- Conclusionsble probably did not show significant differences be-tween the three %BF groups. In conclusion, among the anthropometric variables, In contrast to the healthy group, overweight and abdominal, waist, hip circumference and body fat topog-obese volunteers presented an AI above the reference raphy (arm, leg and trunk %BF) differs between thevalue: > 4.5 [9, 13], but did not differ from one another. three %BF groups. None of the blood variables differed 49
  6. 6. HUMAN MOVEMENTM.F. Glaner, W.A. Lima, Z. Borysiuk, Body fat and cardiovascular risk significantly between the overweight and obese groups, Res, 2004, 45 (10), 1892–1898. DOI: 10.1194/jlr.M400159- JLR200. demonstrating that an increase of %BF itself above 14. Lean M.E.J., Han T.S., Seidell J.C., Impairment of health and healthy levels is a source of concern that should be taken quality of life in people with large waist circumference. Lancet, into account even before the onset of obesity. The cutoff 1998, 351 (9106), 853–856. DOI: 10.1016/S0140-6736(97)10004-6. %BF > 19 (measured by DXA) seems to be a good pa- 15. Friedewald W.T., Levy R.I., Fredrickson D.S., Estimation of the concentration of low-density lipoprotein cholesterol in plasma rameter to indicate cardiovascular risk factors in men. without use of preparative ultracentrifuge. Clin Chem, 1972, 18 (6), 499–502. References 16. Lu W., Resnick H.E., Jablonski K.A., Jones K.L., Jain A.K., 1. World Health Organization. Obesity and overweight. Global Howard W.J. et al., Non-HDL cholesterol as a predictor of cardio- strategy on diet, physical activity and health, 2003. Available vascular disease in type 2 diabetes. The strong heart study Dia- from: URL: betes Care, 2003, 26 (1), 16–23. DOI: 10.2337/diacare.26.1.16. 2. Brazilian Ministry of Health. Vigitel Brazil 2006: Surveillance 17. Tuomilehto J., Marti B., Kartovaara L., Korhonen H.J., Pietnen of risk factors and protection for chronic diseases for phone in- P., Body fat distribution, serum lipoproteins and blood pressure quiry [in Portuguese], 2007. Available from: URL: http:// in middle-aged Finnish men and women. Rev Epidemiol Sante Publique, 1990, 38, 507–515. marco_2007.pdf. 18. Ricciardi R., Metter E.J., Cavanaugh E.W., Ghambaryan A., 3. Eckel R.H., York D.A., Rössner S., Hubbard V., Caterson I., Talbot L.A., Predicting cardiovascular risk using measures of Jeor S.T.S. et al., Prevention Conference VII: Obesity, a world- regional and total body fat. Appl Nurs Res, 2009, 22 (1), 2–9. wide epidemic related to heart disease and stroke: Executive DOI: 10.1016/j.apnr.2007.01.011. summary. Circulation, 2004, 110 (18), 2968-2975. DOI: 10.1161/ 19. Glaner M.F., Secular trend of physical growth and body mass 01.CIR.0000140086.88453.9A. index in schoolchildren [in Portuguese]. Rev Min Educ Fis, 4. Lima W.A., Glaner M.F., Body fat topography as a predictor of 1998, 6, 59–69. an increase in blood lipids. RBM Rev Bras Med, 2009, 66 (1), 20. Glaner M.F. Health-related physical fitness of rural and urban 3–9. adolescents in relation to the reference criteria [in Portuguese]. 5. Caterson I.A., Hubbard V., Bray G.A., Grunstein R., Hansen Rev Bras Educ Fís Esp, 2005, 16, 13–24. B.C., Hong Y. et al., Prevention Conference VII: Obesity, a 21. Sandowski S.A., What is the ideal body weight? Family Prac- worldwide epidemic related to heart disease and stroke: Group tice, 2000, 17 (4), 348–351. DOI: 10.1093/fampra/17.4.348. III: Worldwide comorbidities of obesity. Circulation, 2004, 110 22. Gallagher D., Visser M., Sepúlveda D., Pierson R.N., Harris T., (18), e476–e483. DOI: 10.1161/01.CIR.0000140114.83145.59. Heymsfield S.B., How useful is body mass index for compari- 6. Shen W., Punyanitya M., Chen J., Gallagher D., Albu J., Pi- son of body fatness across age, sex, and ethnic groups? Am J Sunyer X. et al., Waist circumference correlates with metabolic Epidemiol, 1996, 143 (3), 228–239. syndrome indicators better than percentage fat. Obesity, 2006, 23. Zhu S., Heshka S., Wang Z., Shen W., Allison D.B., Ross R. et 14 (4), 727–736. DOI: 10.1038/oby.2006.83. al., Combination of BMI and waist circumference for identify- 7. Rahmouni K., Correia M.L.G., Haynes W.G., Mark A.L. Obes- ing cardiovascular risk factors in whites. Obes Res, 2004, 12 ity-associated hypertension: new insights into mechanisms. (4), 633–645. DOI: 10.1038/oby.2004.73. Hypertension, 2005, 45 (1), 9–14. DOI: 10.1161/01.HYP.000015 24. Boorsma W., Snijder M.B., Nijpels G., Guidone C., Favuzzi 1325.83008.b4. A.M.R., Mingrone G. et al., Body composition, insulin sensi- 8. Hu D., Hannah J., Gray R.S., Jablonski K.A., Henderson J.A., tivity, and cardiovascular disease profile in healthy Europeans. Robbins D.C. et al., Effects of obesity and body fat distribution Obesity, 2008, 16 (12), 2696–2701. DOI:10.1038/oby.2008.433. on lipids and lipoproteins in nondiabetic American Indians: the 25. Sironi A.M., Gastaldelli A., Mari A., Ciociaro D., Postano V., strong heart study. Obes Res, 2000, 8 (6), 411–421. DOI: Buzzigoli E. et al., Visceral fat in hypertension: influence on 10.1038/oby.2000.51. insulin resistance and beta-cell function. Hypertension, 2004, 9. Chang C.J., Wu C.H., Lu F.H., Wu J.S., Chiu N.T., Yao W.J., 44 (2), 127–133. DOI: 10.1161/01.HYP.0000137982.10191.0a. Discriminating glucose tolerance status by regions of interest 26. Després J.P., Cardiovascular disease under the influence of ex- of dual-energy X-ray absorptiometry. Clinical implications of cess visceral fat. Crit Pathw Cardiol, 2007, 6 (2), 51–59. DOI: body fat distribution. Diabetes Care, 1999, 22 (12), 1938–1943. 10.1097/HPC.0b013e318057d4c9. DOI: 10.2337/diacare.22.12.1938. 27. Mansur A.P., Favarato D., Souza M.F.M., Avakian S.D., Ald- 10. Thomas G.N., Ho S-Y, Lam K.S.L., Janus E.D., Hedley A.J., righi J.M., César L.A.M. et al., Trends in death for circulatory Lam T.H. et al., Impact of obesity and body fat distribution on diseases in Brazil between 1979 and 1996. Arq Bras Cardiol, cardiovascular risk factors in Hong Kong Chinese. Obes Res, 2001, 76 (6), 504–510. DOI: 10.1590/S0066-782X2001000600007. 2004, 12 (11), 1805–1813. DOI: 10.1038/oby.2004.224. 11. World Health Organization. Obesity: preventing and managing Paper received by the Editors: February 25, 2009. the global epidemic (WHO technical report series v. 849). Paper accepted for publication: October 6, 2009. WHO, Geneva 2000. 12. Hu G., Tuomilehto J., Silventoinen K., Barengo N., Jousilahti P., Address for correspondence Joint effects of physical activity, body mass index, waist circum- ference and waist-to-hip ratio with the risk of cardiovascular dis- Maria Fátima Glaner ease among middle-aged Finnish men and women. Eur Heart J, Quadra 201, Lote 6, Bloco B – apt. 803 2004, 25 (24), 2212–2219. DOI: 10.1016/j.ehj.2004.10.020. Águas Claras 13. Goh V.H.H., Tain C.F., Tong T.Y.Y., Mok H.P.P., Wong M.T., ZIP-Code 71937-540 Are BMI and other anthropometric measures appropriate as Brasília, DF, Brazil indices for obesity? A study in an Asian population. J Lipid e-mail: 50