Epidemiology of Overweight and Obesity in a Greek Adult Population: the ATTICA Study

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1 Brief Epidemiologic Report Epidemiology of Overweight and Obesity in a Greek Adult Population: the ATTICA Study Demosthenes B. Panagiotakos,* Christos Pitsavos, Christina Chrysohoou, Grigoris Risvas,* Meropi D. Kontogianni,* Antonis Zampelas,* and Christodoulos Stefanadis Received for review February 18, Accepted in final form October 18, The costs of publication of this article were defrayed, in part, by the payment of page charges. This article must, therefore, be hereby marked advertisement in accordance with 18 U.S.C. Section 1734 solely to indicate this fact. *Department of Nutrition and Dietetics, Harokopio University, Athens, Greece and First Cardiology Clinic, School of Medicine, University of Athens, Athens, Greece. Address correspondence to Demosthenes B. Panagiotakos, 46 Paleon Polemiston Street, , Attica, Greece. d.b.panagiotakos@usa.net Copyright 2004 NAASO Abstract PANAGIOTAKOS, DEMOSTHENES B., CHRISTOS PITSAVOS, CHRISTINA CHRYSOHOOU, GRIGORIS RISVAS, MEROPI D. KONTOGIANNI, ANTONIS ZAMPELAS, AND CHRISTODOULOS STEFANADIS. Epidemiology of overweight and obesity in a Greek adult population: the ATTICA Study. Obes Res. 2004;12: Objective: To evaluate the status of overweight and obesity in a Greek random sample. Research Methods and Procedures: From 2001 to 2002, 1514 men (20 to 87 years old) and 1528 women (20 to 89 years old) were enrolled into the study. Among several sociodemographic, lifestyle, and bioclinical factors, anthropometric characteristics were also recorded. Overweight and obesity were defined according to the World Health Organization classification. Results: The prevalences of overweight and obesity were 53% and 20% in men and 31% and 15% in women (p for gender differences 0.05). The age-adjusted peak prevalence of obesity was observed in men older than 40 years old and women between 50 and 59 years old (Bonferonni 0.001). Central obesity prevailed in 36% of men and 43% of women (p for gender differences 0.001). Obesity varied from 10% in rural to 25% in urban areas, but this difference was explained mainly by differences in occupational status (p 0.9). Moreover, obese and overweight participants were older, less educated, more frequently sedentary, consumed higher quantities of alcoholic beverages, and were devoted to an unhealthier diet as compared with those of normal weight (all p 0.05). A positive association was also observed between BMI and diastolic and systolic blood pressures, total cholesterol, triglycerides, and glucose levels (all p 0.001). Discussion: Overweight and obesity seem to be a great health problem in the Greek population, especially in middle-aged and older adults. Unfavorable lifestyle habits, low education, and the classical cardiovascular risk factors were associated with the prevalence of these health conditions. Key words: overweight, Greece, cardiovascular, education Introduction Overweight and obesity are now considered as a serious health problem, with an increasing prevalence worldwide (1 5). Previous data from observational studies in Greek samples (that included specific age ranges or volunteers) have shown that a considerable proportion of the population is overweight or obese. However, during the past 2 decades, the Greek population has experienced marked but uneven socioeconomic development, the lifestyle of people has worsened, and stable, age-old dietary habits and high habitual physical activity have gradually given way to Westerntype diets and a more sedentary lifestyle. In this work, we aimed to evaluate the prevalence of overweight and obesity and its association with various sociodemographic, lifestyle, and other cardiovascular risk factors in a randomly selected population sample of Greek adults. Research Methods and Procedures The ATTICA study is a health and nutrition survey that was carried out in the Attica region (including 78% urban and 22% rural areas) of Greece. The sampling was random and multistage (by city), and it was based on the age-sex distribution of the province of Attica, as provided by the National Statistical Service (census of 2001). From May 2001 to December 2002, 4056 inhabitants from the above area were randomly selected to enroll into the study. Of these, 3042 agreed to participate (75% participation rate); 1914 OBESITY RESEARCH Vol. 12 No. 12 December 2004

2 1514 of the participants were men (20 to 87 years old), and 1528 were women (20 to 89 years old). The questionnaire included questions about demographic and behavioral characteristics, detailed medical history of cardiovascular risk factors, and dietary and other lifestyle habits of the participants. The educational level of the participants was measured by the years of school. Mean annual income during the past 3 years was recorded. Occupation was also recorded and evaluated through a 10-point scale from unskilled [hand workers (lower values)] to executive [skilled workers (higher values)]. Current smokers were defined as those who smoked at least one cigarette per day, and former smokers were defined as those who had stopped smoking for at least the last year. Occasional smokers ( seven cigarettes per week) were recorded and combined with current smokers due to their small sample size. The rest of the participants were defined as nonsmokers. For a more detailed evaluation of smoking habits, we calculated the packs per year (cigarette packs per day years of smoking). For the evaluation of physical activity status, we developed an index (score) of weekly energy expenditure. At first, we recorded frequency (as times per week), duration (in minutes per time), and intensity of sports-related physical activity during the last year. Intensity was gradated in qualitative terms such as: light (expended calories 4 kcal/min), moderate (expended calories 4 to 7 kcal/min), and vigorous (expended calories 7 kcal/min). Then, we calculated the physical activity score. In particular, we multiplied weekly frequency of exercise with duration per time and intensity class (giving values of 1 to 3 for light to high intensity). Higher values of this score indicated more physically active. Participants who did not report any physical activities were defined as physically inactive (sedentary). Height was measured, to the nearest 0.5 cm, without shoes, back square against the wall tape, eyes looking straight ahead (visual axis is horizontal when the top of external auditory meatus is level with the inferior margin of bony orbit), with a right-angle triangle resting on the scalp and against the wall. Weight was measured with a lever balance, to the nearest 100 grams, without shoes, in light undergarments. BMI was calculated as weight (in kilograms) divided by height (in meters) squared. Based on the World Health Organization classification (4), overweight was defined as BMI between 25 and 29.9 kg/m 2, and obesity was defined as BMI 30 kg/m 2. We also measured waist circumference (in centimeters) in the middle between the 12th rib and iliac crest and hip circumference (in centimeters) around the buttocks at the level of the maximum extension. Waist-to-hip ratio was then calculated. The waist and hip circumferences and waist-to-hip ratio were used to determine the extent of central adiposity. For waist circumference, cut-off points of 94 cm in men and 80 cm in women were used because they correspond to increased risk for metabolic complications according to the World Health Organization (6). A waist-to-hip ratio 0.95 in men and 0.8 in women was considered to represent central obesity (6). Arterial blood pressure was measured three times, at the end of the physical examination, with subject in sitting position and at least 30 minutes at rest. Patients whose average blood pressure levels were 140/90 mm Hg or were under antihypertensive medication were classified as hypertensives. Serum total cholesterol and triglycerides were measured using chromatographic enzymic method in a Technicon automatic analyzer RA-1000 (Dade Behring, Marburg, Germany). The intra- and interassay coefficients of variation of cholesterol levels did not exceed 3% and those of triglycerides did not exceed 4%. Hypercholesterolemia was defined as total serum cholesterol levels 200 mg/dl or the use of lipid lowering agents. Finally, type 2 diabetes was defined as a fasting blood sugar 125 mg/dl or the use of antidiabetic medication. The evaluation of nutritional habits was based on a validated food frequency questionnaire (7). We asked all participants to report the average intake (per day or week) of several food items that they consumed (during the last 12 months). Then, the frequency of consumption was quantified approximately in terms of the number of times per month a food was consumed. Thus, daily consumption was multiplied by 30 and weekly consumption was multiplied by 4, and a value of 0 was assigned to food items rarely or never consumed. Ethanol consumption was measured in wineglasses (of 100 ml) and quantified by ethanol intake (grams per drink). One wineglass was equal to 12-gram ethanol concentration. According to a Harvard-led group with substantial input from Greek scientists (8), a dietary pyramid has been developed to describe the Mediterranean dietary pattern (i.e., daily consumption of nonrefined cereals and products, whole-grain bread, pasta, brown rice, vegetables, fruits, olive oil, and dairy products; weekly consumption of fish, poultry, olives, pulses, nuts, potatoes, eggs, and sweets; and monthly consumption of red meat and meat products, as well as moderate consumption of wine). Based on this dietary pattern and the reported monthly frequency consumption of various food groups, we calculated a special diet score for each participant that assessed adherence to the Mediterranean diet (range 0 to 55). In particular, for the consumption of items presumed to be close to this pattern (i.e., those suggested to be consumed on daily basis or four servings per week), we assigned a score of 0 when a participant reported no consumption, 1 when a participant reported consumption of 1 to 4 times/mo, 2 for 5 to 8 times/mo, 3 for 9 to 12 times/mo, 4 for 13 to 18 times/mo, and 5 for 18 times/mo. On the other hand, for the consumption of foods presumed to be not included in this diet (such as meat and meat products), we assigned the opposite scores (i.e., 0 when a participant reported almost daily consumption to 5 for rare or no consumption). Espe- OBESITY RESEARCH Vol. 12 No. 12 December

3 cially for alcohol, we assigned a score of 5 for consumption of three wineglasses per day, a score of 0 for consumption of seven wineglasses per day, and scores of 1 to 4 for consumption of three, four to five, six, and seven wineglasses per day. Higher values of this diet score indicate greater adherence to the Mediterranean diet, whereas lower values indicate adherence to the Westernized diet. Further details about the aims, design, and methods of the ATTICA study may be found elsewhere (9 11). Statistical Analysis Continuous variables are presented as mean SD. Categorical variables are presented as absolute and relative frequencies. Estimations of the frequency of overweight and obesity in the total adult Greek population were based on the census of Associations among categorical variables were tested by the use of contingency tables and the calculation of 2 test. Relationships between categorical and continuous variables were tested by the use of multiway analysis of covariance (for normally distributed), after controlling for several potential confounders, and by the use of Kruskal-Wallis criterion for the skewed variables. Pearson s r (simple and partial) correlation coefficients evaluated the relationships among continuous variables. Kolmogorov- Smirnov test evaluated the assumption of normality. Multivariate logistic regression analysis was applied to estimate the odds ratio of overweight or obesity through the levels of various explanatory factors. A backward step-wise procedure was used to evaluate the variables that were significantly associated with the outcome. In particular, age, sex, packs per years of smoking, annual income, occupation index, years of school, physical activity status, presence of hypercholesterolemia, hypertension, diabetes, and the diet score were included in the initial model. The final model (presented in Table 4) included only the variables that remained statistically significant after the step-wise backward elimination procedure (p for removal of a variable from the model 0.05). Moreover, multiple linear regression analysis was also applied to assess the extent to which cardiovascular risk markers (i.e., blood pressures, lipids, and glucose) were associated with BMI of the participants. All reported p values are based on two-sided tests and compared with a significance level of 5%. However, due to multiple significance tests, we used the Bonferroni correction to account for the increase in Type I error. SPSS (SPSS Inc., Chicago, IL) software was used for all of the statistical calculations. Results Epidemiology of Obesity Mean BMI was kg/m 2 in men and kg/m 2 in women. Men had higher BMI compared with women across all age groups (p 0.001). The prevalences of overweight and obesity were 53% and 20% in men and 31% and 15% in women, respectively (p for gender differences 0.05). The observed difference between genders regarding BMI levels and, consequently, obesity status was not explained even when we took into account the age of the participants, the education and occupation status, the physical activity index, and the diet score. Moreover, 1% of men and women were found to be underweight (BMI 18.5 kg/m 2 ), 16% of men and 11% of women were class I obese (BMI between 30 and 35 kg/m 2 ), and 1% of men and women were class III obese (BMI 40 kg/m 2 ). An inverse parabolic distribution of obesity regarding the age of the participants was observed in both genders (Table 1). Specifically, the age-specific peak prevalence of obesity in men was observed between 40 and 59 years old as compared with younger or older adults (Bonferonni 0.001). Similarly, the peak prevalence of obesity in women was observed between 50 and 59 years old (Bonferonni 0.001). The parabolic association of BMI with age was significant even when we adjusted for the physical activity status of the participants (F test 55.9, p 0.001). Mean waist circumference was cm in men and cm in women (p 0.001), whereas mean hip circumference was cm in men and cm in women (p 0.001). Central obesity prevailed in 549 (36%) men and 653 (43%) women (p 0.001). A significant strong correlation between BMI and waist (r for men 0.7, p and r for women 0.7, p 0.001) and hip (r for men 0.6, p and r for women 0.7, p 0.001) circumferences was observed. Table 2 presents body fat distribution indices by BMI group. The majority of obese men and women had abnormal waist circumference or waist-to-hip ratio, whereas 17% of men and 22% of women who were defined as normal according to BMI group had abnormal waist circumference. Moreover, 14% of men and 28% of women of the normal BMI group had abnormal waist-to-hip ratio. Both waist circumference and waist-tohip ratio were strongly correlated with age in men (r 0.27, p 0.001, and r 0.34, p 0.001, respectively) and women (r 0.40, p 0.001, and r 0.34, p 0.001, respectively). The highest values of waist circumference were observed among 50- to 59-year-old men (Bonferonni 0.01) and in 60-year-old women (Bonferonni 0.01), whereas waist-to-hip ratio showed a linear trend among the age groups of the participants (p for trend 0.01, data not shown in text or tables). Obesity, Sociodemographic, and Lifestyle Characteristics The prevalence of obesity varied from 10% in rural areas to 25% in urban areas of the Attica region ( , unadjusted p for regional differences 0.01), suggesting a region-specific association with obesity. However, participants in rural areas had lower values of the occupation index as compared with participants in urban areas (5 3 vs OBESITY RESEARCH Vol. 12 No. 12 December 2004

4 Table 1. Age- and sex-specific prevalence of normal, overweight, and obesity in Greek adults Age group (years) 20 to to to to 59 >60 Overall Men (n 1514) BMI 25 kg/m 2 n (%) 93 (51) 92 (29) 180 (23) 22 (17) 19 (24) 406 (27) BMI 25 to 29.9 kg/m 2 n (%) 75 (41) 184 (58) 416 (52) 83 (62) 54 (58) 811 (53) BMI 30 kg/m 2 n (%) 16 (8) 41 (13) 203 (23) 29 (21) 17 (18) 307 (20) Women (n 1528) BMI 25 kg/m 2 n (%) 194 (86) 210 (67) 355 (49) 34 (23) 27 (18) 820 (54) BMI 25 to 29.9 kg/m 2 n (%) 24 (11) 73 (23) 242 (33) 73 (50) 53 (64) 465 (31) BMI 30 kg/m 2 n (%) 9 (3) 33 (10) 127 (18) 39 (27) 25 (18) 233 (15) 3, p 0.01), indicating that they were more likely to be unskilled hand workers. Therefore, we had to adjust the observed differences in obesity between regions with occupational activity (through the 10-scale index). We ultimately found that the aforementioned differences were mainly explained when presence of occupational activity was taken into account as a potential confounder in the model that evaluated the association between BMI and region of the participants (F test 0.31, occupation-adjusted p for regional differences 0.93). The distribution of several other sociodemographic and lifestyle characteristics of the participants according to their classification of BMI (normal, overweight, and obese) is shown in Table 3. Obese and overweight participants were older, less educated, more frequently sedentary, consumed higher quantities of alcoholic beverages, and were devoted to an unhealthier diet (i.e., lower diet score), as compared with normal-weight individuals. A strong negative correlation was observed between adherence to Mediterranean diet (as measured by the diet score) and BMI (partial r in men 0.6, p and r in women 0.89, p 0.001), after adjusting for age. Obese and overweight participants consumed higher quantities of alcoholic beverages as compared with normal-weight individuals ( vs vs ml/d, respectively, p 0.001). Moreover, nevermarried participants were less frequently obese and overweight as compared with married participants (Table 3). However, the differences in marital status were explained mainly by the age of men and women because nevermarried were younger as compared with married participants (32 10 vs years old, p 0.001). No associations were observed between obesity status and smoking habits, annual income, and occupation index in both genders (Table 3). Table 4 presents the results from the logistic regression model that was applied to evaluate factors that were associated with the likelihood of being overweight or obese. Low education, unhealthy diet, presence of hypertension, Table 2. Anthropometric characteristics of the participants BMI (kg/m 2 )ofmen(n 1514) BMI (kg/m 2 ) of women (n 1528) <25 25 to 29.9 >30 <25 25 to 29.9 >30 p* Number of participants Waist circumference (cm) Abnormal waist circumference (%) Hip circumference (cm) Waist-to-hip ratio Abnormal waist-to-hip ratio (%) Continuous variables (waist and hip circumferences and waist-to-hip ratio) are presented as mean SD, whereas categorical variables (abnormal waist circumference and waist-to-hip ratio) are presented as relative frequencies (percentage). * Age- and gender-adjusted p value for the evaluation of the associations between groups of BMI and the investigated variables. OBESITY RESEARCH Vol. 12 No. 12 December

5 Table 3. Sociodemographic and lifestyle characteristics of the participants BMI (kg/m 2 ) of men (n 1514) BMI (kg/m 2 ) of women (n 1528) <25 25 to 29.9 >30 <25 25 to 29.9 >30 p* Number of participants Age (years) Years of school Annual income (#,000 Eurs) Occupation index (1 to 10) Current smokers (%) Physically inactive (%) Marital status Never married (%) Married (%) Divorced-widowed (%) Diet score (0 to 55) Alcoholic beverages (ml/d) * Age- and gender-adjusted p values for the evaluation of the associations between groups of BMI and the investigated variables. Continuous variables (age, years of school, annual income, diet score, and alcoholic beverages) are presented as mean SD, whereas categorical variables (current smokers, sedentary, and marital status) are presented as relative frequencies (percentage). hypercholesterolemia, or diabetes, and physical inactivity were significantly associated with the prevalence of overweight or obesity. No associations were found between overweight or obesity status and sex, smoking habits, occupation level, and income of the participants in the multivariate analysis. Furthermore, linear regression analysis showed that BMI was highly associated with presence of hypertension (standardized coefficient 0.19, p 0.005), diabetes (standardized coefficient 0.09, p 0.003), and hypercholesterolemia (standardized coefficient 0.04, p 0.008), after controlling for age, sex, and physical activity index. More prominent associations were observed between waist circumference and waist-to-hip ratio and presence of hypertension (standardized coefficient 0.21, p 0.001, and 0.24, p 0.001), diabetes (standardized coefficient 0.10, p and 0.09, p 0.001), and hypercholesterolemia (standardized coefficient 0.08, p and 0.11, p 0.001). We found that roughly one of five men and one of six women were obese. In addition, a considerable proportion of men and women (53% and 31%, respectively) were found to be overweight. According to the recent (2001) age-sex distribution of the Greek population, it could be speculated that 2.4 million men and 1.4 million women are overweight, and 900,000 men and 675,000 women are obese. Furthermore, 36% of men and 43% of women had central obesity. Prevalence of overweight and obesity was higher in middle-aged and older adults, in the less educated, in the physically inactive, and in those who were devoted to an unhealthier diet. Furthermore, overweight and obesity were associated with an adverse health status, defined by increased prevalence of hypertension, hypercholesterolemia, and diabetes. Discussion So far, to our knowledge, there are no data regarding the prevalence of overweight and obesity in Greece, based on random and representative samples. The existing information comes from studies with either small samples or limited age range (12,13). An exception is the study of Moulopoulos et al. in the early 1980s (14), which was based on a random sample of 4097 men and women from urban areas of the Athens region (18 to 90 years old). In this study, the prevalence of obesity (as defined by BMI 27 kg/m 2 ) was 24% in men and 23% in women, which was somewhat higher than our rates (however, we used a higher cut-off for defining obesity). Recently, the EPIC Study (15) published results for overweight, obesity, and fat distribution in 50- to 64-year-old participants. According to these data, 51% of Greek men were overweight and 30% obese, and 40% of women were overweight and 43% obese. Additionally, 64% of men and 66% of women had abnormal waist-to-hip ratio OBESITY RESEARCH Vol. 12 No. 12 December 2004

6 Table 4. Results from logistic regression model* that evaluated the associations between various characteristics of the participants with the likelihood of being overweight or obese Odds ratio 95% Confidence interval Age (per 5 years) to 1.15 Years of school (per 10 years) to 0.97 Physical inactivity (yes vs. no) to 2.38 Diet score (per 5 units) to 0.49 Hypercholesterolemia (yes vs. no) to 2.23 Hypertension (yes vs. no) to 3.16 Diabetes (yes vs. no) to 2.29 * These are the results from the final model. In the initial model: sex, pack years of smoking and annual income, were also included, but they were not significantly associated with the likelihood of being overweight or obese. In 2002, the International Obesity Task Force (IOTF) 1 published a position paper on obesity in Europe (16), according to which the prevalence of both overweight and obesity in Greek women was the highest among other European countries (74%), whereas Greek men were second in the IOTF s classification (72%). Our study showed similar cumulative prevalence of overweight and obesity in men (73%) with that of IOTF s data but much lower prevalence of both overweight and obesity in women (46%). Moreover, our data regarding overweight and obesity as well as central obesity differed from those presented by the EPIC Study investigators, especially in women. These differences may be attributed to the different source of the populations studied and the different sampling procedures (i.e., the IOTF s data and the EPIC Study included people from all Greek areas and within a specific age range). We also found a sex-specific association with overweight and obesity. The lower obesity rates observed among women as compared with men were not explained by the differences in various lifestyle and sociodemographic variables. However, when the prevalence of the classical cardiovascular risk factors was taken into account, sex did not show any significant association with the presence of overweight or obesity (Table 4). Additionally, other genetic, lifestyle, or behavioral factors that were not measured in this study could also explain the observed sex differences. We confirmed results from previous studies (2 5) that obesity is associated with various cardiovascular risk factors, such as diabetes, hypertension, and hypercholesterolemia. Moreover, we found that obese participants were less educated, more frequently sedentary, consumed higher quantities of alcoholic beverages, and were devoted to an unhealthier diet. Similar findings regarding the associations of obesity with educational level and physical activity status 1 Nonstandard abbreviation: IOTF, International Obesity Task Force. have been observed in other studies in Australia (17) and the U.S. (18). We found no associations of obesity with marital status, after adjusting for age of the participants. Concerning this issue, although Jeffery and Rick (19) reported no relationship between BMI and the likelihood of marriage or divorce, they also found that marriage was associated with a weight gain and divorce with a weight loss. Finally, we revealed the benefits of the consumption of the Mediterranean diet on the likelihood of being overweight or obese. It seems that a dietary pattern that is high in total lipid intake ( 40% of total energy intake) but also characterized by a high monounsaturated-to-saturated fat ratio (especially due to the liberal use of olive oil) and large consumption of nonrefined cereals, fruits, and vegetables (20) may independently reduce the prevalence of obesity. This may be attributed to the increased consumption of rich-in-fiber, monounsaturated fat, carbohydrate-containing, and low-glycemic index foods that the Mediterranean dietary pattern provides (20); however, further metabolic studies are needed to confirm or refute this hypothesis. Because this study was a cross-sectional one, it cannot establish causal relations but can only generate hypotheses about the associations between obesity and sociodemographic, lifestyle, biological, and clinical characteristics of the participants. The prevalence of obesity or overweight in Greece was based on the information provided by a single region (i.e., Attica). Thus, the exact figures of obese or overweight Greek adults could be over- or underestimated. Misreporting of food items consumed and especially ethanol consumption, due to social class, could influence the calculation of the diet score and bias the results from the data analysis. Nevertheless, the present study provides current evidence regarding the prevalence and the distribution of obesity and overweight in a representative random sample of Greek adults from the Attica region (which includes about the OBESITY RESEARCH Vol. 12 No. 12 December

7 one-half of the total population). It seems that overweight and obesity constitute a great health problem. We found that roughly one of five men and one of six women were obese, and approximately one-half of the population studied was overweight. Among several factors that were associated with the prevalence of obesity, we could underline that greater adherence to the Mediterranean diet was associated with lower prevalence of obesity. Because the causes of obesity are incompletely understood, adherence to this traditional diet could be an effective prevention strategy for reducing this epidemic at the population level. Acknowledgments The ATTICA study is supported by research grants from the Hellenic Society of Cardiology (Grant HCS2002). We thank the field investigators of the ATTICA study: Natasa Katinioti (physical examination), Akis Zeimbekis (physical examination), Spiros Vellas (physical examination), Efi Tsetsekou (physical/psychological evaluation), Dina Masoura (physical examination), Lambros Papadimitriou (physical examination), and Yannis Skoumas (physical examination), as well as the technical team: Marina Toutouza (principal investigator in biochemical analysis), Carmen Vasiliadou (genetic analysis), Manolis Kambaxis (nutritional evaluation), Konstadina Paliou (nutritional evaluation), Constadina Tselika (biochemical evaluation), Sia Poulopoulou (biochemical evaluation), and Maria Toutouza (database management). References 1. Allison DB, Fontaine KR, Manson JE, Stevens J, VanItallie TB. Annual deaths attributable to obesity in the US. JAMA. 1999;282: Must A, Spadano J, Coakley EH, Field AE, Colditz G, Dietz WH. The disease burden associated with overweight and obesity. JAMA. 1999;282: Trojano RP, Flegal KM. Overweight children and adolescents: description, epidemiology and demographics. Pediatrics. 1998;101: World Health Organization. Obesity: preventing and managing the global epidemic: report of a World Health Organization Consultation. presented at the World Health Organization. Geneva, Switzerland, June 3-5, Eckel RH, Krauss RM. American Heart Association call to action: obesity as a major risk factor for coronary heart disease. Circulation. 1998;97: Dobbelsteyn C, Joffres M, MacLean D, Flowerdew G, and the Canadian Heart Health Surveys Research Group. 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: Katsouyanni K, Rimm EB, Gnardellis C, Trichopoulos D, Polychronopoulos E, Trichopoulou A. Reproducibility and relative validity of an extensive semi-quantitative food frequency questionnaire using dietary records and biochemical markers among Greek schoolteachers. Int J Epidemiol. 1997; 26:S Willett WC, Sacks F, Trichopoulou A, et al. Mediterranean diet pyramid: a cultural model for healthy eating. Am J Clin Nutr. 1995;6:1402 6S. 9. Pitsavos C, Panagiotakos DB, Chrysohoou C, Stefanadis C. Epidemiology of cardiovascular risk factors in Greece; aims, design and baseline characteristics of the ATTICA study. BMC Public Health. 2003;3:32: Panagiotakos DB, Pitsavos H, Chrysohoou C, et al. Status and management of hypertension in Greece; the role of the adoption of a Mediterranean diet: the Attica study. J Hypertens. 2003;21: Panagiotakos DB, Pitsavos CH, Chrysohoou C, et al. The impact of lifestyle habits on the prevalence of the metabolic syndrome among Greek adults from the ATTICA study. Am Heart J. 2003;147: Mamalakis G, Kafatos A. Prevalence of obesity in Greece. Int J Obes. 1996;20: Bertsias G, Mammas I, Linardakis M, Kafatos A. Overweight and obesity in relation to cardiovascular disease risk factors among medical students in Crete, Greece. BMC Public Health. 2003;3: Moulopoulos SD, Adamopoulos PN, Diamantopoulos EI, Nanas SN, Anthopoulos LN, Iliadi-Alexandrou M. Coronary heart disease risk factors in a random sample of Athenian adults: the Athens Study. Am J Epidemiol. 1987;126: Haftenberger M, Lahmann PH, Panico S, et al. Overweight, obesity and fat distribution in 50- to 64-year-old participants in the European Prospective Investigation into Cancer and Nutrition (EPIC). Public Health Nutr. 2002;5: IOTF. Obesity in Europe: The Case for Action: (accessed February 10, 2004). 17. Cameron AJ, Welborn TA, Zimmet PZ, et al. Overweight and obesity in Australia: the Australian Diabetes, Obesity and Lifestyle Study (AusDiab). Med J Aust. 2003; 178: Flegal KM, Carroll MD, Ogden CL, Johnson CL. Prevalence and trends in obesity among US adults, JAMA. 2002;288: Jeffery RW, Rick AM. Cross-sectional and longitudinal associations between body mass index and marriage-related factors. Obes Res. 2002;10: Trichopoulou A, Lagiou P. Healthy traditional Mediterranean diet: an expression of culture, history and lifestyle. Nutr Rev. 1997;55: OBESITY RESEARCH Vol. 12 No. 12 December 2004