Prevalence of Metabolic Syndrome and Its Relationship with Clinically Prevalent Cardiovascular Disease in the Veneto Region,Northeastern Italy

Abstract

Background:

Cardiovascular disease (CVD) is more frequent in adults with metabolic syndrome than in those without. We wished to assess the prevalence of the metabolic syndrome and the role of its specific components on prevalent CVD in a large cohort of subjects from the general population.

Methods:

Seventy-eight general practitioners among 3,542 were identified and participated in this study. Personal, anthropometric, and lifestyle data were obtained as was data relevant to CVD [coronary heart disease (CHD) or stroke or both]. A stratified random sample of 6,347 subjects taken from the population of the Veneto region in northeastern Italy was analyzed.

Results:

The prevalence [and its 95% confidence limits (CL)] of metabolic syndrome by gender and age classes was higher in men than women (21.9% vs. 16.8) and it increased with age (29.8% in ages 60–69 vs. 8.0 in ages 30–39). The most frequent triad of metabolic syndrome was waist circumference (WC)–blood pressure (BP)–hyperglycemia (GLYC) (33%). Metabolic syndrome was significantly associated with CVD [odds ratio (OR)=1.53, 95% CL, 1.02–2.29] and gender (men have about six times the risk of women), and the risk of CVD increases with age (11% per additional year of age). High-density lipoprotein (HDL) is the only component of metabolic syndrome associated with CVD: The OR was 2.12 (95% CL, 1.32–3.43) and remains significant in sex-specific models only in men.

Conclusions:

The prevalence of metabolic syndrome in the Veneto region among subjects ages 30–69 is high. There is a significant association between prevalent CVD and metabolic syndrome, but the biological basis of association is strongly influenced by gender.

Introduction

C oronary heart disease (CHD) and cardiovascular disease (CVD) are significantly higher in adults with metabolic syndrome than in those without.^1

–7 This is true not only in the general population but also in patients with the syndrome and type 2 diabetes mellitus, where it accounts for up to one-third of CVD in men and approximately half of new cases.^8,9 Yet, this association has been seriously questioned,^10
–12 so that it appears that this issue is far from being settled clinically and semantically.^13
–15 This discrepancy of opinions is probably dictated by the complex pathophysiology of the syndrome itself. Meigs observed that metabolic syndrome defined by the National Cholesterol Education Program Adult Treatment Panel III (NCEP ATP III) criteria may require insulin resistance to increase risk for CVD, and that only the simultaneous presence of metabolic syndrome and insulin resistance identifies an especially high-risk individual.^16,17

If we take for granted that subjects with metabolic syndrome are at risk for future CVD, then it also important to establish not only the number of its components, but also the combination of the components that more strongly identify this risk. It has been observed that at least two components of metabolic syndrome are required for a significantly elevated risk for CVD, and that any two among waist circumference (WC), hypertension, and dyslipidemia could be used to identify significantly higher risk for CVD, regardless of gender.¹⁸ The number of components was shown to be more informative than the dichotomous metabolic syndrome classification.^19,20 In both nonsmokers and current smokers, the relative risks of incidence of CVD increases as the number of components increases.^21
–23 Furthermore, metabolic syndrome appears to increase the risk of CVD in type 2 diabetes, and individual traits in some clusters with hypertension and low high-density lipoprotein cholesterol (HDL-C).²⁴ In patients with pre-existing CHD, metabolic syndrome confers a higher risk of long-term death, and dysglycemia appears to be responsible for most of the associated risk.²⁵ Franco and colleagues have shown that hyperglycemia and central obesity experienced the highest increase in CVD.²⁶ Patients who have metabolic syndrome with a combination of central obesity, high blood pressure (BP), and hyperglycemia had a 2.36-fold increase of incident CVD events and a 3-fold increased risk of mortality.

With this background data in mind, it appears that to relate metabolic syndrome with either prevalent or incident CVD may be reductive. A clinically important issue is to ascertain the specific components of the syndrome rather than the syndrome itself. Therefore, the scope of this study was to assess the prevalence of metabolic syndrome, and the role of its specific components, identified with the ATP III criteria, on prevalent cardiovascular complications in a large cohort of subjects from the general population who had the diagnosis of metabolic syndrome.

Methods

Data were extracted in October, 2009. After intensive training, all GPs participating in this study had to use specially designed software (Millewin; Millenium, Dedalus, www.millewin.it) to record data during their normal daily clinical practice. The GPs were selected to be representative of the entire Italian population. The software system codes all diagnostic records by using the International Classification of Diseases, Ninth Revision, Clinical Modification (ICD-9-CM). Prescription records were coded according to the Anatomical Therapeutic Chemical classification system. A unique identification number links patient demographic details, medical records (e.g., diagnoses, tests and test results, and hospitalization), and drug therapy anonymously so that no identifying details are available. Data were subjected to a range of quality checks. The completeness and accuracy of information were assessed by running a set of queries on the recorded data. All quality indicators were included in a composite score ranging from 0 to 1. Any variation outside agreed ranges was investigated and submitted to each participating GP. Physicians who failed to reach standard quality criteria (composite score >0.7) were not taken into consideration for epidemiologic studies. This survey was cross sectional. Seventy-eight GPs among 3,542 were identified through the use of a random sampling and participated in this study; they were homogeneously distributed in the Veneto region located in northeastern Italy. Dedicated software was used to record data during normal daily clinical practice.

The participants underwent routine medical history, physical examination, including BP measurement, anthropometry, laboratory assessment of CVD risk factors, and testing for the presence of subclinical CVD. The Padova University Hospital institutional review board approved the study, and all participants gave written informed consent.

Recorded information included personal, anthropometric, and lifestyle data (including smoking habits and alcohol consumption); clinical history and data relevant to macrovascular (CHD, stroke, and peripheral amputations) complications; laboratory data; and pharmacological treatment. Systolic blood pressure (SBP) and diastolic blood pressure (DBP) were measured after the patient had been seated for at least 5 min. Patients were classified as having CHD if they had one of the following: (1) A history of hospital admission for either fatal or nonfatal acute myocardial infarction (AMI) or an episode of angina; (2) a 12-lead electrocardiogram positive for prior AMI or angina by the Minnesota Coding System (criteria I, 1–3; IV, 1–3; V, 1–2; and VII, 1), and (3) a history of coronary artery bypass graft or percutaneous transluminal coronary angioplasty. Stroke was defined according to World Health Organization criteria for confirmed and possible stroke (i.e., a clinical syndrome consisting of a rapidly developing neurological deficit persisting for >24 h or leading to death, in the absence of other diseases that could explain the symptoms). All patients had had at least one electrocardiogram in the 12 months preceding enrollment to exclude prior AMI. All documentation was reviewed by an ad hoc committee to confirm diagnosis.

Cigarette smoking was defined by self-report of cigarette use within the year preceding the study baseline examination. Diabetes was defined as a fasting plasma glucose ≥126 mg/dL or use of insulin or oral hypoglycemic agents. Metabolic syndrome was defined according to the NCEP ATP III criteria by the presence of three or more of the following: Increased WC (≥102 cm for men, ≥88 cm for women), elevated BP (≥130 mmHg SBP or ≥85 mmHg DBP or treatment for hypertension), hyperglycemia (fasting blood glucose ≥100 mg/dL or treatment for elevated glucose), hypertriglyceridemia (≥150 mg/dL or treatment with nicotinic acid or fibrates), or low HDL-C (<40 mg/dL in men, <50 mg/dL in women).

A theoretical sample size of 11,095 subjects was calculated from the 30- to 69-year-old population of the Veneto region of northeastern Italy. We based this calculation on an expected prevalence of metabolic syndrome in adults of 10% for ages 30–39, 15% for ages 40–49, 20% for ages 50–59, 25% for ages 60–69 years old, with an absolute precision of±1.5%, a confidence level (CL) of 95%, and a refuse/nonresponse rate of 15%.^27,28 A stratified sampling process was performed, with 10-year age classes and gender as stratum. Of all potential participants, 4,748 people were excluded because they had missing data in all the components defining metabolic syndrome or could not be classified with respect to metabolic syndrome (e.g., they have only two positive components and three missing): 5,302 subjects had complete data on all variables used to define metabolic syndrome [large WC, BP, HDL-C cholesterol, hyperglycemia (GLYC), hypertriglyceridemia (TRIGL)], another 1,045 persons could be classified as either positive or negative with respect to metabolic syndrome, increasing the total number of analyzed subjects to 6,347, a number corresponding to an absolute precision of 2% and a nonresponse rate of 17%.

Results

The prevalence estimate (and its 95% CL) of metabolic syndrome in the Veneto region by gender and age classes is shown in Table 1. It is higher for men that for women (21.9% vs. 16.8, respectively) and it increases with age (29.8% in ages 60–69 vs. 8.0 in ages 30–39). We used the SURVEYFREQ procedure in SAS that incorporates the sample design in the data analysis. The anthropometric and biochemical characteristics of subjects are given in Table 2, with the significant differences (P<0.0001) between subjects with or without metabolic syndrome in bold.

Table 1.

Prevalence of Metabolic Syndrome in the Veneto Region by Gender and Age (%)

Persons	N	%	Prevalence (%)	95% confidence limits
30–39	645	10%	8.0	5.9	10.2
40–49	1,270	20%	12.8	11.0	14.5
50–59	1,898	30%	23.1	21.3	24.9
60–69	2,534	40%	29.8	28.2	31.5
Total	6,347	100%	19.2	18.3	20.1
Men
30–39	291	10%	8.2	5.1	11.3
40–49	595	20%	18.1	15.1	21.2
50–59	901	30%	26.3	23.6	29.1
60–69	1,252	41%	30.4	28.0	32.7
Total	3,039	100%	21.9	20.5	23.3
Women
30–39	354	11%	7.9	5.1	10.8
40–49	675	20%	7.9	5.9	9.9
50–59	997	30%	20.1	17.8	22.5
60–69	1,282	39%	29.3	27.0	31.7
Total	3,308	100%	16.8	15.6	18.0

Table 2.

Anthropometric and Biochemical Characteristic of Subjects

	Overall			Metabolic Syndrome			No Metabolic Syndrome
Characteristic	N	Mean	STD	N	Mean	STD	N	Mean	STD
Age (Years)^*	6,347	55.8	10.3	1,425	59.6	8.6	4,922	54.7	10.5
Weight (Range 40–150 Kg)^*	3,867	75.6	15.5	1,057	85.7	15.3	2,810	71.8	13.9
Height (Range 140–210 cm)	3,938	167.7	8.8	1,077	167.8	9.0	2,861	167.6	8.8
BMI^*	3,874	26.8	4.8	1,055	30.3	4.8	2,819	25.4	4.1
Systolic blood pressure (60–300 mm Hg)^*	5,972	133.2	14.7	1,405	141.1	13.1	4,567	130.7	14.2
Diastolic blood pressure (Range 40–150 mm Hg)^*	5,970	82.3	8.1	1,404	85.5	7.4	4,566	81.4	8.0
Total cholesterol (Range 20–1000 mg/dL)^*	6,306	212.7	38.7	1,417	213.4	43.0	4,889	212.5	37.4
HDL-C (Range 10–200 mg/dL)^*	6,177	56.7	15.9	1,398	45.8	12.1	4,779	60.0	15.4
LDL-C, mg/dL	6,125	132.1	35.1	1,389	131.4	40.5	4,736	132.3	33.8
Triglycerides (Range 10–2000 mg/dL)^*	6,270	120.8	77.6	1,409	182.9	109.5	4,861	102.8	50.8
Waist Circumference (Range 40–200 cm)^*	5,711	89.9	14.5	1,321	101.7	13.7	4,390	86.3	12.8
Glycaemia (Range 30–500 mg/dL)^*	6,251	102.0	25.7	1,411	121.4	39.5	4,840	96.3	16.1

P<0.0001.

STD, standard deviation; BMI, body mass index; HDL cholesterol, high-density lipoprotein cholesterol; LDL cholesterol, low-density lipoprotein cholesterol.

The distribution of the single components of metabolic syndrome stratified for both metabolic syndrome yes/no and prevalent CVD is provided in Fig. 1. Among those with metabolic syndrome, elevated BP was present in almost the entire cohort, whereas elevated glucose was present in a significantly higher proportion in those with prevalent metabolic syndrome. On the contrary, increased waist girth was significantly less frequent in those with CVD. Among those without metabolic syndrome, the prevalence of the single components was significantly less likely to be present; among the isolated components, elevated glucose was significantly higher in those with prevalent CVD.

FIG. 1.

Prevalence of the components of tmetabolic syndrome in patients with (top panel) and without metabolic syndrome (bottom panel) stratified by prevalent cardiovascular disease (CVD). (Top) (black bars) Metabolic syndrome with CVD; (gray bars) metabolic syndrome without CVD. (Bottom) (black bars) No metabolic syndrome with CVD; (gray bars) no metabolic syndrome without CVD. Statistically significant (P<0.05) between those with and those without CVD.

The distribution of the triads is given in Table 3. The triads are the simultaneous combination of any three different components defining diagnosis of metabolic syndrome, so every subject could have more than one triad, e.g., if a person has a metabolic syndrome because of large WC, high BP, hyperglycemia, and low HDL-C, this patient experienced three triads: WC–BP–GLYC, WC–BD–HDL, and HDL–BP–GLYC.

Table 3.

The Distribution of the Triads and the Prevalence of CVD

Triads	Number of subjects	%	With CVD	%
WC-BP-GLYC	472	33%	13	2.8%
WC-BP-TRIGL	451	32%	8	1.8%
WC-BP-HDL	415	29%	8	1.9%
BP-HDL-TRIGL	409	29%	12	2.9%
BP-GLYC-TRIGL	370	26%	12	3.2%
HDL-BP-GLYC	282	20%	14	5.0%
HDL-WC-TRIGL	260	18%	3	1.2%
WC-GLYC-TRIGL	214	15%	5	2.3%
HDL-GLYC-TRIG	190	13%	8	4.2%
HDL-WC-GLYC	180	13%	5	2.8%

CVD, cardiovascular disease; WC, waist circumference; BP, high blood pressure; GLYC, hyperglycemia; TRIGL, elevated triglyceride concentration; HDL, low high-density lipoprotein cholesterol.

We then assessed the age- and sex-adjusted relationship between cardiovascular occurrence (myocardial infarction or stroke or coronary bypass) and metabolic syndrome components with a logistic regression performed with the SURVEYLOGISTIC procedure in SAS to take into account the sample design in the analysis. The five components of metabolic syndrome were entered in the model as dummy variables (absence or presence of the condition). The association of cardiovascular occurrence with the metabolic syndrome components, adjusted for the stratification variables age and gender, is shown in Table 4.

Table 4.

Association of Cardiovascular Occurrence with Metabolic Syndrome and Component Conditions

	Cardiovascular occurrence
	Odd ratio	95% Confidence level
All subjects
Sex (female vs. male)	0.17	0.11	0.29
Age (1-year difference)	1.11	1.08	1.14
Metabolic syndrome	1.53	1.02	2.29
Syndrome components
WC	1.03	0.66	1.60
BP	0.70	0.45	1.08
GLYC	1.43	0.94	2.19
HDL	2.12	1.32	3.43
TRIGL	1.15	0.72	1.83
Men
Age (1-year difference)	1.11	1.08	1.14
Metabolic syndrome	1.57	1.00	2.45
Syndrome components
WC	1.04	0.64	1,71
BP	0.61	0.38	0.99
GLYC	1.49	0.94	2.36
HDL	2.39	1.43	4.00
TRIGL	1.13	0.69	1.87
Women
Age (1-year difference)	1.14	1.08	1.21
Metabolic syndrome	1.31	0.54	3.18
Syndrome components
WC	0.93	0.36	2.39
BP	1.32	0.48	3.62
GLYC	1.22	0.38	3.92
HDL	1.24	0.34	4.55
TRIGL	1.22	0.33	4.52

WC, waist circumference; BP, high blood pressure; GLYC, hyperglycemia; HDL, low high-density lipoprotein cholesterol; TRIGL, elevated triglyceride concentration.

The metabolic syndrome was significantly associated with CVD (OR=1.53, 95% CL 1.02–2.29), sex (men have about six times the risk of women) and the risk of CVD increases with age (11% per additional year of age). HDL is the only significant component of metabolic syndrome: The OR is 2.12 (95% CL1.32–3.43) and remains significant in sex-specific models only in men.

Discussion

The major findings of this investigation are the following: (1) The prevalence of metabolic syndrome in the Veneto region is 19.2% among patients aged between 30 and 69 years; (2) the most prevalent combination of the components defining the syndrome is WC, hypertension, and elevated glucose; (3) a significant association (P=0.0004) between prevalent CVD and metabolic syndrome—the proportion of subjects with prevalent CVD is double in patients with metabolic syndrome (2.8%) as compared to people without metabolic syndrome (1.4%); (4) sex, age, and metabolic syndrome were all significantly associated with CVD. In women, only age was significantly associated with prevalent CVD.

The total 2010 population of Veneto was 4,912,438; a prevalence of 19.2% represents numerically a total of 943,188 subjects with metabolic syndrome. Our data are remarkably similar to those of Ford and colleagues, who reported an age-adjusted prevalence of metabolic syndrome of 23.7% among the Caucasian U.S. population aged 20 or older.²⁹ Their prevalence increased up to 45% among people aged 60–69, whereas our prevalence is roughly 30% for this age range. In a smaller number of subjects, the Bruneck Study reported a prevalence of metabolic syndrome defined by NCEP ATP III criteria of 17.8% among subjects aged 40–79 years.³⁰ Comparable data were observed in the Tuscany region, where Miccoli and colleagues reported a prevalence of 18% in women and 15% in men aged 19 years or more; the prevalence increased to 25% in subjects aged 70 years or older.³¹ A slightly higher prevalence was found in the Massa Lombarda Projects.³² In 2010, the Italian population numbered 60,340,328; one can assume that there are at least 11.6 million people with metabolic syndrome. This represents an important economic burden that will be increasing continuously by up to 157% by 2020.³³

The most prevalent combination of components defining metabolic syndrome is increased WC, hypertension, and elevated glucose. It was shown that in five Mediterranean countries the overall prevalence of metabolic syndrome was 27.2%³⁴; interestingly, that study also demonstrated that the most frequent combination of components identifying metabolic syndrome was WC, low HDL-C, and BP (10.2%) followed by high triglycerides, BP, and HDL (10.2%), with WC, BP, and hyperglycemia having only 1.1% prevalence. However, in that study, hyperglycemia was defined as plasma glucose ≥110 mg/dL, while we set the plasma glucose threshold at 100 mg/dL. We now show that among 1,425 subjects affected by metabolic syndrome, the combination of WC, BP, and hyperglycemia was the most prevalent, whereas the combination of HDL-C, high BP, and hyperglycemia was the combination in which the prevalence of CVD was highest. In a French cohort, Guize and colleagues found that among the combinations significantly associated with all-cause mortality, WC plus elevated glucose, plus either elevated BP or elevated triglycerides³⁵ is the most prevalent combination.

These observations not only underscore the heterogeneous distribution of the components of the syndrome, but also the role of their combination in determining mortality. As emphasized by Kuk and Ardern, the metabolic syndrome is a heterogeneous entity with age and sex variation in component clusters that may have important implications for interpreting the association between metabolic syndrome and mortality risk.³⁶ This heterogeneity is further complicated not only by the different definition of the syndrome employed, but also by the ethnic group considered. Sone and colleagues have shown that the commonly used definitions of metabolic syndrome have limited clinical usefulness for Asian diabetic patients and may need some ethnic group-specific modifications for global use.³⁷ This is further complicated by the presence of type 2 diabetes. Such heterogeneity may be partly explained by the variation in food pattern, which has been emphasized as an important contributor not only in terms of component but also in term of adverse effect of metabolic syndrome.³⁸

As shown in Fig. 1, the most prevalent single component of the metabolic syndrome was high BP; a remarkably similar high prevalence of hypertension was observed previously in another Italian cohort of type 2 diabetic patients where there was a prevalence of hypertension.³⁹ However, this is at variance with the figures from those found in a Finnish population, where the most prevalent component was abdominal obesity.⁴⁰ When we compared among those with and without the syndrome, with the prevalence of each single component stratified for prevalent CVD, we found that elevated glucose was significantly higher irrespective of the presence of the syndrome. This highlights the concept that fasting glucose level above normal is a progressive risk factor for cardiovascular outcomes.⁴¹ The second indirect message is that elevated plasma glucose is not targeted to normal values (<100 mg/dL) despite the ongoing CVD.⁴²

The clustering combination of the individual components of metabolic syndrome may be also relevant in terms of CVD risk. Our finding that the most prevalent triad is the combination of WC, BP, and hyperglycemia is similar to the report of Franco and colleagues, who also found that this combination was the most negative in terms of incident CVD.²⁶ In this study, we endorse that there is a significant association between prevalent CVD and metabolic syndrome, the proportion of subjects with prevalent CVD being double in patients with metabolic syndrome. Our data also ratify the meta-analysis of Mottillo and colleagues, who showed that metabolic syndrome is associated with a two-fold increase in CVD outcome.⁴³ The value of the metabolic syndrome as a predictor of cardiovascular risk has been met with much debate. This is supported by other reports that have shown that the syndrome was associated with a greater likelihood of undergoing progression of coronary atherosclerosis; nonetheless, after adjusting for its individual components, metabolic syndrome was no longer an independent predictor. Furthermore, Sattar and colleagues have shown that metabolic syndrome was only modestly associated with incident CVD, despite strong association with diabetes.¹⁰ Here we show that, at multivariate analysis, metabolic syndrome was independently associated with prevalent CVD along with age and sex only when the study sample was pooled. Guzder found that metabolic syndrome was independently associated with CVD, and also an independent predictor of incident CVD.⁴⁴

Similar to results reported by Wilson et al. in the Framingham Heart Study, we have shown that metabolic syndrome remains independently associated with CVD only in men.⁸ We did not find any significant association between prevalent CVD and metabolic syndrome or any of its components in women. This suggests that the relationship between the syndrome and CVD may be gender specific. Indeed, we found that only age is independently associated with metabolic syndrome in women. This discrepancy between males and females may be dictated by several factors. McCarthy and colleagues have found that the genetic basis predisposing to metabolic syndrome may be strongly modified by gender. Unfortunately, we do not provide information on this issue in the present study.⁴⁵ Among patients with metabolic syndrome, lipid metabolism, specifically in the postprandial phase, was reported more serious in men than in women.⁴⁶ This difference may further explain gender disparity in the determinants of CVD in people with metabolic syndrome. Understandably, the difference in sex hormones may also explain the gender differences observed in this study. A limitation of this study is that we were not able to determine hormone profile in our patients or to verify the proportion of postmenopausal women. Another reason may reside in the different degree of exposure between males and females to each different component of the syndrome. Females present much lower BP levels (135±14 mmHg vs. 132±15, P<0.0001, and 84±8 mmHg vs. 81±8, P=0.003, respectively, for males vs. females), WC (95±8 cm vs. 85±15, P<0.0001), glucose (106±29 mg/dL vs. 98±21, P<0.0001), HDL (52±14 vs. 62±16, P<0.0001), and triglycerides (135±88 mg/dL vs. 107±54, P<0.0001). In the presence of less severe effect of metabolic syndrome component, age may probably overcome their effect in terms of CVD risk factor.

In conclusion, this study shows that the prevalence of metabolic syndrome in the Veneto region among subjects aged between 30 and 69 years is high. There is a significant association between prevalent CVD and metabolic syndrome, but the biological basis of association is strongly influenced by gender. A prospective study is needed to determine the biological plausibility of these cross-sectional results.

Footnotes

Acknowledgments

The GPs who participated in this study are: Cristina Andrich, Gianluigi Antiga, Paola Bassetto, Roberto Benetti, Giulio Bergamasco, Evandro Bertelle, Graziella Bianchin, Maria Grazia Bianchini, Stefania Bordignon, Annarosa, Bovo, Monica Braggion, Agostino Buzzatti, Cancian Maurizio, Casalena Michelino, Cassol Maria Antonia, Cavallo Giovanni, Cesaro Andrea, Federico Cesaro, Marilisa Crestani, Giovanni Cucciarrè, Aurelio D'Agostino, Alberto Dolci, Livio Fanton, Isabella Fracasso, Bianca Maria Fraccaro, Carlo Andrea Franchini, Arianna Franco, Bruno Franco Novelletto, Federico Franzoso, Angelo Frascati, Massimo Fusello, Roberto Galante, Marilena Gall, Sandro Girotto, Edoardo Gurian, Renzo Laurora Nicola, Livio Libardi, Serenella Longhi, Liliana Lora, Maria Pia Grazia Lora, Claudio Marafetti, Maria Laura Marciani, Raffaella Marrocchella, Giuseppe Massarelli, Dino Mario Massignani, Sebastiano Matterazzo, Michela Mazzorana, Gianni Mazzucato, Gennaro Merola, Raffaella Michieli, Osvaldo Morbioli, Giuseppe Mulato, Luigi Naibo, Giuseppe Nastrini, Guido Novella, Giancarlo Ometto, Licia Orrasch, Nicola Pantaleoni, Paola Pasquato, Caterina Pastori, Cludio Penco, Giulio Pirolo, Luisa Scarrocchia, Nicolò Seminara, Sandro Severi, Alberto Simiele, Giuliana Simioni, Sergio Soldati, Maria Cristina Taccola, Massimo Tirelli, Paolo Tonello, Barbara Toniolo, Riccardo Tonon, Eugenio Visonà, Luciana Zanolli, Dino Zenere, Luciana Zollino, Maria Carla Zovi.

Author Disclosure Statement

No competing financial interests exist.

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