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Mediterranean diet and metabolic syndrome in three countries of Calabria

Cornelli U

Loyola University School of Medicine, Chicago, USA

E-mail : bhuvaneswari.bibleraaj@uhsm.nhs.uk

Cassano G

MAP (Monitoring Alimentary Pathology center, Rende, Italy

Meringolo G

Department of Cardiology, Rende Hospital, Italy

Rausa M

Department of Public Health, Rende, Italy

Valente O

Municipal administration, Rovito, Italy

Recchia M

Statistical Dept University of Lugano, Switzerland

DOI: 10.15761/GMO.1000149

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Abstract

Mediterranean diet has been associated with low prevalence and progression of metabolic syndrome (MetS). However, no specific foods have been described as causative of MetS.

Six hundred subjects of both sexes (between 35-65 years) have been studied in the investigational centers of MAP (Monitoraggio Alimenti Patologia) organized by the local Municipalities of three countries in Calabria-Italy. The enrollment was suggested by family doctors who were addressing subjects suffering from MetS matched with subject non MetS in the same age range. Food intake was analyzed through a weakly questionnaire (FIA or Food Intake assessment).

529 subjects (85 MetS/297 females, and 75 MetS/232 males) concluded the study. In both genders cardiovascular diseases and ultrasound carotid damages were significantly higher, and in males osteoarthosis also was more frequent. Caloric intake was significantly more consistent in MetS with no distinction among carbohydrates, proteins, fibers or fats but with different food pattern in females and males.

Among 77 different foods, in females more white meat, less carrots, cauliflower and red wine were found in MetS. In males red wine, beer, garlic, milk, salami, fruit of the season, and chocolate were lower in MetS and canned tuna was higher.

Multivariate analysis indicate that a complex food combination is determining MetS, with different figures for males and females.

In an area typical for the Mediterranean diet, MetS seems determined by an excessive caloric intake with different food pattern depending upon the gender, indicating that it is not possible to generalize about diet components as causative of the disease.

Key words

mediterranean diet, metabolic syndrome, calabria

Introduction

Metabolic syndrome (MetS) is a multi-factorial disorder including hyperglycemia, dyslipidemia, hypertension, and abdominal obesity that is becoming one of the most common pathologies affecting the adult worldwide in a similar proportion for both genders [1,2].

Despite some argument about its role and value in clinical practice, subjects presenting the three of the 5 components as defined by the ATP III (Adult Panel Treatment III) consisting of the increase of blood glucose, triglycerides,  blood pressure, abdominal circumference, and reduction of HDL cholesterol,  have five times risk or more for type 2 diabetes mellitus, three times risk of developing coronary heart attack or stroke, and two times higher cardiovascular mortality than subjects without the syndrome [1,3].

Considering the pathophysiology, overweight and obesity are central to the risk of the disease predisposing to the insulin resistance, hypertension and dyslipidemia.

Evidence of genetic component have been suggested in term of heritability: family studies provided information about a consistent heritability of some component;  linkage studies have shown combinations among the different determinants (e.g, HDL, blood pressure, triglyceride, abdominal visceral fats) in Caucasian, African-American, Mexican-American; genoma wide association studies (GWAS) have detected some single nucleotide polymorphism of fat mass and obesity associated protein (FTO) [4-8].

The inflammatory condition and modification of the gut microbiota are also considered as causative and witness the complexity of the disease [9,10].

The prevalence of MetS is increasing despite a large difference between countries estimated from 10 to 84 % depending on the ethnicity, age, gender, and race of the population [11]. Accompanied to a rapid increase of the life expectancy, it is estimated that around a quarter of the world’s adult population has MetS.

The major risk factor for developing the disease are considered to be the diet rich in fats and carbohydrates and physical inactivity [1,2].

However, among carbohydrates and lipids many distinctions have been made.

For carbohydrates, although they are the only foods constituents that directly increase blood glucose, a distinction has to be made between those with high glycemic index  (GI) or glycemic load (GL) -as refined grains, potatoes and sugar sweetened beverages- from other foods as the minimally processed  grains, legumes, whole fruits and also pasta in that they do not have a sudden impact on insulin release because of  the hifgh fiber content [12]. At the end the quality of carbohydrates seems to have a more important role than the quantity.

The same is for lipids, because saturated fats have different metabolic activity compared to unsaturated lipids which behave differently depending upon the degree of unsaturation as for seed oil, extravirgin olive oil, palm oil. Even more the production process to refine oils can generate toxic compounds as for palm oil.

Lifestyle modification is considered one of the keys to counteract the MetS.

In a meta-analysis of some randomized controlled study on lifestyle modification was shown that the adherence to a healthy diet or a combination of diet and physical activity increase were associated with the reversion of MetS [13]. Talking about healthy diet, in a meta-analysis of several studies (50) -consisting in total of > 500.000 subjects- the Mediterranean diet was shown to be appropriate by all the population groups for primary and secondary prevention of the disease [14,15].

Italy, Spain, Serbia, Greece -just to mention some of the countries on the Mediterranean Sea- use to eat very different foods, or similar foods with different recipe. Despite the common use of extra virgin olive oil, fruit and vegetables in this diet one may consider also that countries are not comparable in terms of MetS prevention or treatment due to environment and lifestyle differences.

The consequence of all these distinctions is that the total amount of food components in the diet such as carbohydrates, lipids, proteins, fibers do not give enough information on the MetS development.

Even more, the same components in different area of the same country may have a different impact. In other terms, is almost impossible to draw conclusion about the effect of foods in determining the MetS unless a restricted territory will be analyzed where subjects are used to eat similar food and similar traditional way of preparing foods.

For this reason, after having crossed the Italy with a mobile unit [16] we decided to choose an Italian region (Calabria) where to start an observational study in different towns controlling the food intake in subjects with MetS compared to matched non MetS people. The aim was to identify what kind of food if any was relating to the disease using a weekly validated food Intake questionnaire (FIA) consisting of 250 different foods [17].

Material and methods

This research represents a pilot study of the three countries aimed to drive the long-term study (10 years) that will consider the relationship between Foods and MetS (called MAP or Monitoraggio Alimenti Patologia) in ten countries of Calabria-Italy. The data concerning the first evaluation of 600 cases were evaluated.

Three countries were selected: Rovito which is located on a hill, San Lucido on the sea side, and Rende on the plain.

Enrollment method

A conference on “food and pathology” open to the public was organized in three towns     (Rovito, San Lucido, and Rende) with the aid of the relative Municipalities. Family doctors were asked to participate and requested to help in the enrollment of their patients suffering from MetS matched with other non-MetS subjects coming for a routine check out.

The enrolment duration was three month/town in the same period of the year and in total the study lasted 3 years. The Ethical Committees of the three Municipalities involved approved the protocol.

Admission criteria

Subject of both sexes aging between 35 and 60 years were admitted suffering from MetS matched with subjects suffering from other diseases provided that only one of the 5 typical variables of MetS (according to ATP III or Adult Treatment Panel) was present. The capacity to fill up correctly the FIA (weakly Food Intake Assessment-see later) after the training was a prerequisite to enter the study.

Exclusion criteria

Cancer of any type, severe psychiatric or metabolic disorders, chronic diseases not under adequate therapy control,  more than one variable of MetS according to ATP III,  FIA questionnaire unreliable.

FIA questionnaire

FIA consisted of a list of the most common 250 foods in Italy [17]. Following a training with a nutritionist the subject had to fill up a 7 days questionnaire recording the amount (in g or mL) of each of the listed foods.  The questionnaire was fundamental for the study, and subjects presenting records with a caloric intake lower than 90 % of the Mifflin St Jeor (MSJ) were excluded. However, the latter were excluded from the current evaluation but continued study.

The FIA was taken at least twice in the period of two years of observation and the data were reported as averages.

Smokers were included in the study and were considered as current smokers or nonsmokers. The latter where those subjects with at least 5 years of interruption. Physical activity was measured through a very simple 4 points questionnaire considering the following items: sedentariness, limited activity, normal activity, physical training.

Lab analysis and anthropometric measures, echography

The common variables for MetS according to ATP III were measured consisting of HDL, triglycerides (TG), blood pressure (BP), abdominal circumference (AC), and glucose. Blood samples were taken before the enrollment to confirm the diagnosis.

The enrolled subjects underwent to the ultrasound carotid analysis using VIVID L8 ultrasound machine. The degree of the arterial lesion was according to a classification into VI different classes: from Class I (normal artery) to class VI (presence of complex plaques with stenosis) [18].

Statistical analysis

Sample

The number of cases to be enrolled was on heuristic base to analyzes the possibility continue the long-term study and in case to adapt the protocol.  Two hundred cases for each country (600 cases in total) were analyzed considering obtaining valuable data in at least 500 cases. With these figures, the hypothesis was to analyze about 30 % of the cases with a MetS. However, to be sure to obtain at least 150 cases of MetS, the family doctors were asked to make a first selection consisting of one case of MetS (no matter about the sex) and two matched patients non MetS provided within the admission criteria.

Calculations

Each variable was analyzed calculating the average and SD. The t test or Wilcoxon test were used to determine the relative differences between groups (MetS, Vs non MetS defined as “Controls”) for all the variables. The frequencies of concomitant diseases in the two groups were measured using the chi square test (Fisher, with or without Yates correction).

For what concern the FIA, the average weekly data (of two FIA taken within the period) for any food (e.g. pasta, wine, red meat) were determined only to have a rough indication of the quantities (in g or mL).  Following the control of the variables distribution, the category analysis was based on discretization (D) of each variable using from 2 to 5 (or D2-D5) different cut off. The Pearson chi square (77 of the 250 considered in FIA) was used to differentiate the two groups followed by the Nominal Logistic Fit value.

For each food, odds ratios were analyzed to compare the differences between various D levels comparing controls and MetS. The logistic regression model (Likelihood Ratio test) was applied to analyze the connection between foods within MetS and controls to describe which were more frequent in MetS compared to controls [19].

Results

In the three selected countries Rovito, San Lucido and Rende a total of 600 subjects were analyzed.

The flow chart of the study is reported in Table 1.

Table 1. Enrollment flow chart

 

Towns

Total

 

Rovito

San Lucido

Rende

Subjects

200

200

200

600

Drop out (no FIA report)

3

15

6

24

FIA Incorrect

13

27

7

47

 

 

 

 

 

Total non-included

16

42

13

71

 

 

 

 

 

Females Controls

72

69

71

212

Females with MetS

30

38

17

85

Male controls

52

39

66

157

Male with MetS

30

12

33

75

  

 

 

 

 

Total females

102

107

88

297

Total males

82

51

99

232

 

 

 

 

 

Total evaluated

184

158

187

529

The percentages of MetS in the three towns were respectively 32.6 % in Rovito, 31.6 % in San Lucido, and 26.7 % in Rende. These values indicate that the family doctors were making a similar selection of the cases.

The compliance of the study was 88 % since only 529 subjects concluded correctly the questionnaire. Seventy-one were excluded: 47 because of an incorrect FIA, and 24 were not returning at all the FIA.

The general characteristics of the subjects are reported in Table 2. The caloric intake measured through FIA analysis was between the 96% to 98 % of the theoretical intake calculated according to the MSJ formula.

Table 2. General characteristics of the subjects: mean values ± SD or frequencies

Gender

 

Females

Males

Disease

[N of cases]

 

Controls

 [212]

 

MetS

[85]

 

Controls

[157]

 

MetS

 [75]

 

Variables

Measure

Mean

SD

Mean

SD

Mean

SD

Mean

SD

Age

Years

47.5

6.95

47.5

7.97

50.0

7.98

51.9

8.35

Height

m

1.58

0.055

1.59

0.054

1.70

0.061

1.71

0.072

Weight

Kg

66.1

11.26

79.9a

15.7

80.2

11.59

89.9a

11.70

BMI

Kg/m2

26.6

4.69

31.7a

5.37

27.9

3.26

30.7a

3.87

AC

cm

87.9

13.93

102.4a

19.42

97.1

13.68

105.4a

25.45

BP min

mmHg

82

27.0

87a

28.3

82

28.3

88a

35.9

BP mx

mmHg

129

47.8

139a

46.7

132

50.4

140a

49.8

Total CH

mg/dL

205

37.9

212

41.6

214

37.7

204

36.6

LDL

mg/dL

126

33.2

138a

40.4

137

34.6

130

36.4

HDL

mg/dL

61

11.5

46a

11.1

51

9.9

40a

11.2

Triglycerides

mg/dL

101

34.5

175a

63.5

134

57.8

245a

153.3

Glucose

mg/dL

88

10.8

94a

16.8

93

13.6

103a

29.0

Smoking

Yes/no

12/200

 

5/85

 

8/149

 

5/70

 

Physical activity b

S/O

195/17

 

77/8

 

150/7

 

8/69

 

MSJ c

Kcal/week

11751

1479.1

12923

1511.8

15437

1659.2

16136

1882.0

Calorie intake d

Kcal/week

11304

4021.4

12378

4892.0

15045

5043.1

15752

4855.4

a t test Controls Vs MetS p < 0.05; b S = sedentariness and O = limited activity, normal activity, physical training; Caloric intake using Mifflin St Jeor formula; d Caloric intake calculated from the FIA

The differences between controls and MetS subjects were statistically significant (t test p < 0.05) for all the variables that are typical of the syndrome.

Total and LDL cholesterol in male with MetS was found lower than in controls despite the differences were not statistically significant (t test p > 0.05). This could be due to the treatment of dyslipidemia that was more common in these subjects than in control group (respectively 9.3 % Vs 5.1 %; Table 3.

Table 3. Concomitant diseases: percentage of the total subjects

Gender

Females

Males

Disease

[N of cases]

Controls

 [212]

MetS

[85]

Controls

[157]

MetS

 [75]

Concomitant

disease

%

%

%

%

Allergic

1.9

1.2

2.5

4.0

Bronchopulmonary

0.5

0

0

0

Cardiovascular

13.2

29.4a

15.3

38.7a

Dyslipidemic

4.7

3.5

5.1

9.3

Dermatological

0.5

0

0.5

0

Endocrinological

10.4

10.5

1.3

2.7

ENT

0.5

1.2

0

0

Gastroenterological

3.3

7.1

2.5

8.0

Gynecological

0.9

0

-

-

Hematological

0.9

2.4

0

2.7

Osteoarthritic

58.0

50.6

31.8

45.3a

Odonatological

1.4

1.2

0

2.7

Ophthalmological

1.4

1.2

0

0

Neurological

3.3

4.7

0.6

1.3

Psychiatric

0.9

3.5

0

1.5

Urological

-

-

3.2

6.7

Cancer b

2.8

0

0

0

EC0 class IV

5.7

11.8

3.8

14.7 a

Total/person

1.10

1.24

0.6

1.30

% increase Vs control

 

13

 

117

a Chi square p < 0.05; b no malignancy

The total caloric intake measured according to FIA was significantly higher in both groups with MetS and similar to the respective MSJ formula (the differences were < 4 %).

For what concerns the concomitant diseases, in the group of MetS the number of subjects suffering from cardiovascular disease was significantly higher (chi square p < 0.01) in both males and females (Table 3). This was confirmed by the ultrasound analysis (ECO) where class IV images (presence of small plaques) were higher in both groups of MetS although the difference was significant in males only (chi square test p < 0.05). The percentages of all the other diseases were similar, a part of osteroarthrosis that was present with significantly higher incidence in males only.

In males a higher incidence of total diseases/person in the groups of MetS was found, the differences were   statistically significant (Wilcoxon test p < 0.05). In females the total disease/person were slowly higher (+ 12.4 %) but not statistically significant (Wilcoxon test p > 0.05).

Considering the main food components, the only difference between groups was detected for proteins intake with a significant increase in males with MetS, and surprisingly a lower intake of alcohol (mainly due to lower red wine drinking) was shown (Table 4). Carbohydrates and lipids do not present any important difference between groups as for the fibers.  The ratio carbohydrates/lipids or soluble sugars/lipids in term of caloric intake were not significantly different in both sexes.

Table 4. Main food components as percentage of the total caloric intake and ratios with lipids: Mean ± SD

Gender

Females

Males

Disease

Controls

MetS

Controls

MetS

Components

Mean

SD

Mean

 SD

Mean

SD

Mean

SD

Carbohydrates

23.3

13.57

20.3

15.76

23.2

16.02

24.6

15.14

Soluble sugars

26.3

12.72

29.3

17.16

25.1

15.28

24.7

13.53

Proteins

16.3

2.86

16.8

4.25

16.0

2.96

16.7a

2.26

Lipids

33.8

5.98

33.6

6.90

31.0

6.13

31.4

6.28

Alcohol

1.5

2.05

1.1

1.90

5.4

4.30

3.7a

4.53

 

 

 

 

 

 

 

 

 

Fiber g/week

93

43.8

95

61.1

102

42.8

98

52.6

Ratio carbohydrates/lipids

0.72

0.469

0.62

0.517

0.78

0.585

0.88

0.758

Ratio

soluble sugars/lipids

0.82

0.526

0.91

0.560

0.86

0.630

0.82

0.484

a= t test Controls Vs MetS p < 0.05

The analysis of food intake was conducted for all the 250 foods reported in the FIA (Food Intake Assessment). Seventy-seven type of food were measured and the others up to 250 were not used or reported (Table 5).

Following a careful analysis of foods distribution, for each item an arbitrary classification (discretization) was settled in terms of cut off forming from 2 to 5 different classes (Table 5).

Some of the listed foods in FIA were not part of the usual diet of the area or were used by few subjects only (e.g.   mushrooms, pumpkin, pate, wurstel, big burghers, canned soup) and were not considered in the analysis. In total, the caloric intake of the foods listed accounted for at least the 90 % of the total caloric amount/subject (Table 5).

Table 5. Average intake (g or mL) of different foods in Females (F) and Males (M) in the two groups of subjects, Controls and MetS, and relative discretization cut off for the different foods

Food

Controls

means

MetS

means

Discretization categories

and cut off values a

 

F/M

F/M

0

1

2

3

4

5

Carbohydrates based food

Biscuits

68/52

54/40

0

40

140

280

480

-

Bread  

433/587

456/550

0

200

450

950

2550

-

Breadsticks

4/4

8/2

0

20

100

280

-

-

Croissant

80/73

80/68

0

75

275

700

-

-

Crackers

17/10

22/7

0

40

80

280

-

-

Gnocchi

13/23

15/14

0

3

50

80

-

-

Oatmeal

10/8

15/8

0

80

280

600

-

-

Rusks

45/26

62/26

0

40

80

140

420

-

Sandwich homemade

85/107

55/97

0

40

280

1120

-

-

Sandwich commercial

13/22

21/21

0

54

315

630

-

-

Pasta

304/404

302/402

0

182

395

690

1200

-

Polenta

5/1

7/3

0

30

122

360

-

-

Pizza

153/163

153/140

0

34

150

422

1470

-

Potatoes

75/63

42/63

0

75

300

1060

-

-

Rice

50/50

55/49

0

25

145

280

560

-

Tortellini

11/13

15/9

0

25

100

240

-

-

Fruits

Apples

476/560

457/539

0

200

700

1400

4200

-

Banana

217/230

189/171

0

199

600

2800

-

-

Citrus fruit

500/542

360/498

0

200

1700

4000

-

-

Dried fruit

97/81

73/114

0

80

280

1900

-

-

Fruit in syrup

8/20

22/1

0

18

100

1050

-

-

Fruit of the season b

460/521

673/491

0

475

950

1450

4000

-

Fruit Juice mL

48/35

65/104

0

75

450

2100

-

-

Grapes

65/43

72/41

0

50

300

2350

-

-

Homemade juice mL

90/74

85/130

0

75

160

300

-

-

Pineapple

30/18

43/35

0

68

300

495

-

-

Plums

1/2

1/0

0

20

150

180

-

-

Vegetables/pulses

Carrots

47/41

36/33

0

40

140

690

-

-

Cauliflower

56/33

40/35

0

60

260

1820

-

-

Celery

19/11

21/12

0

3

140

330

-

-

Chicory/lettuce

187/193

160/194

0

90

245

490

500

1170

Fennels

108/93

70/124

0

480

2000

3380

-

-

Garlic

1.6/1.7

1.7/1

0

1.5

7

20

-

-

Onions

82/83

70/61

0

90

290

630

-

-

Pepper

61/68

100/52

0

50

250

1750

-

-

Pulses dry

21/27

21/25

0

45

90

225

-

-

Pulses canned

36/37

33/33

0

19

160

240

400

-

Savoy cabbage

40/43

50/45

0

15

320

1280

-

-

Soy germ

2/0

0/0

0

30

210

-

-

-

Spinach

93/76

87/54

0

80

350

1440

-

-

Tomato

326/367

320/360

0

60

340

820

2450

-

Zucchini

149/93

175/153

0

100

280

500

1890

-

Beverages

Spirits

5.5/32

3.6/17

0

80

300

560

-

-

Beer mL

108/319

128/205

0

240

760

3750

-

-

Coffee mL

250/267

247/282

0

195

280

480

1280

-

Sweet beverages mL

272/382

402/356

0

1980

3000

11880

-

-

Tea

1.9/4.4

2.6/1.1

0

1

5

21

210

-

Water [L]

6.3/6.8

7.1/7.3

0

2.8

5.8

8.5

21.0

-

Wine white mL

25/93

27/36

0

65

380

1820

-

-

Wine red mL

157/609

92/415

0

65

325

800

4400

 

Meat, processed meat, and fish

White meat

171/178

293/201

0

50

190

380

980

-

Red meat

201/260

209/216

0

100

140

400

-

-

Salami

124/184

117/135

0

75

170

280

340

820

Offal

13/14

6/13

0

50

140

340

-

-

Bacon

16/28

24/12

0

26

80

160

-

-

Ham

70/63

53/76

0

30

120

250

700

-

Speck

3/8

6/8

0

30

90

180

-

-

Fish

206/224

202/230

0

70

140

700

1400

-

Canned tuna

24/23

19/53

0

24

82

180

800

-

Dairy products

Milk mL

846/639

707/412

0

400

900

1400

2800

4800

Cheese

149/181

145/168

0

95

190

295

635

-

Ice cream

38/41

50/54

0

25

75

125

700

-

Mozzarella

70/67

76/72

0

25

75

160

640

-

Ricotta cheese

37/30

35/34

0

25

70

120

490

-

Yogurt

107/61

90/78

0

60

360

1680

-

-

Eggs

57/61

55/60

0

25

125

350

700

-

Dressing

Butter

7/7

6/8

0

40

160

270

-

-

Mayonnaise

2/4

4/1

0

5

21

320

-

-

Margarine

1/1

2/2

0

10

140

-

-

-

Olive oil

108/105

104/104

0

100

180

405

 

 

Desserts

Homemade jam

10/11

13/12

0

20

40

210

-

-

Honey

1/1

3/1

0

3

35

85

-

-

Chocolate

17/19

17/9

0

15

55

210

-

-

Cake

149/155

149/107

0

35

175

560

1330

-

Other foods miscellanea

Sweeteners

1.1/1.0

0.9/2.2

0

1

5

7

21

-

Salt added

25/25

24/23

0

12

22

35

43

140

Sugar added

37/31

35/33

0

14

31

75

270

-

example: biscuits - discretization category 1 (from 0 to 40 g); category 2 (from 40 g to 140 g); category 3 (from 140 g to 280 g); category 4 (from 280 g to 480 g); b Fruit of the season: mainly figs, peaches, apricot, strawberry, pear, and cherries.

The percentages of subjects within the given discretization were summarized together with the relative statistical analysis to compare controls and MetS subjects (Table 6).

Table 6. Percentages of subject in each discretization category (from D1 to D5) divided by sex

Gender

Female

Male

Disease

Controls

MetS

 

Controls

MetS

Discretization [D]

1

2

3

4

5

1

2

3

4

5

1

2

3

4

5

1

2

3

4

5

Carbohydrates based foods

Biscuits

42

38

17

3

-

55

29

13

3

-

58

29

9

4

-

67

19

13

1

- a

Bread

25

33

34

8

-

17

38

36

9

-

15

24

45

16

-

9

32

49

9

-

Breadsticks

92

6

2

-

-

94

4

2

-

-

92

6

1

-

-

92

8

0

-

-

Croissant

76

21

3

-

-

80

15

5

-

-

80

15

5

-

-

77

21

1

-

-

Crackers

83

7

10

-

-

80

9

11

-

-

90

5

5

-

-

92

5

3

-

-

Gnocchi

83

0

7

10

-

81

1

8

10

-

78

1

6

14

-

83

1

3

13

-

Oatmeal

91

8

1

-

-

94

4

2

-

-

97

2

1

-

-

95

5

0

-

-

Rusks

66

8

10

15

-

55

9

13

23

-

78

6

7

9

-

79

7

5

9

-

Sandwich homemade

63

24

12

1

-

65

28

6

1

-

61

26

11

2

-

60

24

13

3

-

Sandwich commercial

90

8

1

-

-

88

10

2

-

-

89

9

2

-

-

88

10

2

-

-

Pasta

26

49

21

4

-

30

38

30

2

-

15

41

37

7

-

12

41

36

11

-

Polenta

96

3

1

-

-

96

2

1

-

-

99

1

0

-

-

97

1

1

-

-

Pizza

31

30

36

3

-

26

41

31

2

-

28

34

34

4

-

33

32

33

1

-

Potatoes

75

19

6

-

-

83

11

6

-

-

81

10

9

-

-

77

17

5

-

-

Rice

48

43

8

1

-

50

41

7

2

-

51

39

6

4

-

55

35

11

0

-

Tortellini

87

9

3

-

-

81

14

5

-

-

85

11

4

-

-

89

7

4

-

-

Fruits

Apples

42

28

21

9

-

39

33

17

11

-

39

27

17

17

-

43

21

20

16

-

Banana

55

30

15

-

-

57

32

11

-

-

59

23

8

-

-

63

27

10

-

-

Citrus fruit

44

49

7

-

-

56

38

6

-

-

41

51

8

-

-

49

45

5

-

-

Dried fruit

69

21

10

-

-

57

25

8

-

-

70

18

12

-

-

66

23

11

-

-

Fruit in syrup

95

0

5

-

-

89

0

11

-

-

94

0

6

-

-

99

0

1

-

-

Fruit of the season b

62

18

12

8

-

57

13

15

14

-

60

16

15

9

-

71

7

9

13

- a

Fruit juice

95

5

-

-

-

94

6

-

-

-

95

4

1

-

-

88

9

3

-

-

Grapes

81

10

9

-

-

82

10

8

-

-

83

8

9

-

-

91

2

7

-

-

Homemade fruit juice

88

7

5

-

-

86

8

6

-

-

89

7

4

-

-

83

9

8

-

-

Pineapple

87

11

2

-

-

83

13

4

-

-

92

7

1

-

-

84

11

5

-

-

Plums

98

2

0

-

-

96

4

0

-

-

99

0

1

-

-

99

1

0

-

-

Vegetables and pulses

Carrots

58

32

10

-

-

71

20

8

-

- a

63

27

10

-

-

70

27

3

-

- a

Cauliflower

73

16

11

-

-

87

9

4

-

- a

82

12

6

-

-

81

15

4

-

-

Celery

74

22

4

-

-

78

17

5

-

-

85

12

3

-

-

88

7

5

-

-

Chicory/lettuce

31

42

21

1

5

36

33

25

2

4

27

41

25

3

4

35

37

20

1

7

Fennels

92

8

-

-

-

96

4

-

-

-

92

8

0

-

-

95

4

1

-

-

Garlic

63

30

7

-

-

60

33

7

-

-

62

31

7

-

-

77

19

4

-

- a

Onions

62

32

6

-

-

65

30

5

-

-

60

34

6

-

--

64

31

5

-

-

Pepper

72

20

8

-

-

68

20

13

-

-

72

18

10

-

-

77

15

8

-

-

Pulses dry

55

26

16

3

-

54

31

8

7

-

53

21

16

10

-

59

17

13

11

-

Pulses canned

72

16

9

3

-

76

13

7

4

-

73

17

5

5

-

68

25

4

3

-

Savoy cabbage

83

14

3

-

-

84

12

4

-

-

80

13

6

-

-

83

12

5

-

-

Soy germs

98

2

-

-

-

99

1

-

-

-

99

1

-

-

-

99

1

-

-

-

Spinach

69

23

8

-

-

69

27

4

-

-

74

20

6

-

-

85

8

7

-

-

Tomatoes

27

39

27

7

-

37

31

19

13

-

27

30

29

14

-

27

36

26

11

-

Zucchini

57

20

15

8

-

62

20

11

7

-

67

17

12

4

-

67

11

14

8

-

 Beverages

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Spirits

97

3

-

-

-

99

1

-

-

-

86

12

2

-

-

91

9

0

-

-

Beer

76

23

1

-

-

74

24

2

-

-

53

37

10

-

-

75

17

8

-

- a

Coffee

24

36

31

9

-

23

37

32

8

-

26

34

30

10

-

27

33

29

11

-

Sweet beverages

97

2

1

-

-

94

5

1

-

-

93

4

3

-

-

91

6

3

-

-

Tea

73

14

12

1

-

72

15

12

1

-

70

17

12

1

-

71

16

12

1

-

Water

3

32

40

25

-

2

33

39

26

-

2

35

37

26

-

3

31

41

25

-

Wine white

86

12

2

-

-

86

13

1

-

-

81

13

6

-

-

90

7

3

-

-

Wine red

61

19

15

5

-

73

19

3

5

a

20

17

29

34

-

45

20

16

19

- a

Meat, processed meat, and fish

White meat

26

28

35

8

3

12

36

32

12

8 a

25

28

34

9

4

28

23

29

11

9

Red meat

69

22

9

-

-

80

12

8

-

-

74

13

13

-

-

77

16

7

-

-

Salami

48

17

20

5

10

54

13

16

9

8

38

13

21

9

19

37

29

17

8

8 a

Offal

93

2

5

-

-

95

1

4

-

-

89

6

5

-

-

95

0

5

-

a

Bacon

76

15

9

-

-

79

15

6

-

-

75

15

10

-

-

74

16

10

-

-

Ham

38

33

27

2

-

45

32

21

1

-

41

27

28

4

-

37

28

29

5

-

Speck

95

3

1

-

-

92

6

2

-

-

86

10

4

-

-

89

8

3

-

-

Fish

29

59

11

1

-

35

52

12

1

-

31

52

12

5

-

27

60

11

2

-

Canned tuna

76

17

6

1

-

79

15

6

0

-

81

12

4

3

-

67

17

9

7

a

Dairy products

Milk

38

17

14

8

-

51

11

8

25

5

54

10

8

22

5

60

19

8

13

0 a

Cheese

32

35

21

12

-

31

43

13

13

-

26

29

27

18

-

36

27

17

20

-

Ice cream

64

15

12

9

-

62

12

11

15

-

68

11

11

10

-

57

13

15

15

-

Mozzarella

39

23

28

10

-

36

25

25

14

-

41

22

27

10

-

41

19

28

12

-

Ricotta cheese

60

17

14

9

-

62

18

14

6

-

57

22

13

8

-

63

15

14

8

-

Yogurt

68

18

14

-

-

71

17

12

-

-

80

9

11

-

-

83

8

9

-

-

Eggs

40

47

12

1

-

45

43

11

1

-

38

43

17

2

-

40

44

15

1

-

Dressing

Butter

93

7

-

-

-

96

4

-

-

-

94

5

1

-

-

92

8

0

-

-

Mayonnaise

89

7

4

-

-

84

12

4

-

-

88

10

23

-

-

91

8

1

-

-

Margarine

96

4

-

-

-

96

4

-

-

-

99

1

-

-

-

98

2

-

-

-

Olive oil

40

43

17

-

-

35

51

13

-

-

36

51

13

-

-

48

30

21

-

-

Desserts

Homemade jam

81

9

10

-

-

80

4

14

-

-

78

9

13

-

-

79

10

11

-

-

Honey

85

7

8

-

-

84

6

10

-

-

85

6

9

-

-

86

5

5

-

-

Chocolate

62

29

9

-

-

63

28

9

-

-

64

27

9

-

-

82

8

10

-

- a

Cake

35

31

28

6

-

37

29

29

5

-

36

30

27

7

-

35

30

29

6

-

Other foods miscellanea and water

Sweeteners

83

8

2

7

-

80

6

4

10

-

82

9

3

6

-

81

10

4

5

-

Salt

13

46

16

21

4

14

45

18

17

6

12

47

16

20

5

13

47

15

20

5

Sugar (added)

31

15

42

11

-

40

27

30

13

-

30

16

40

14

-

35

18

27

20

-

a = Nominal Logistic Fit p < 0.05 Controls Vs MetS; see Table 5 for the average values

The following results were found:

-for the carbohydrates-based foods, in females no differences were shown between controls and MetS, whereas in males the biscuits intake was significantly lower in MetS group with a Nominal Logistic Fit value (NLF) of p = 0.03804.

-for fruits, in the female groups no significant differences were found between groups, whereas in males with MetS the intake of the fruit of the season was found significantly lower (NLF p = 0.04556)

-for vegetables, in the females group with MetS differences were found in the carrots and cauliflowers intakes which were significantly lower (respectively an NLF with p = 0.03182 and 0.03796). In the males group with MetS garlic and carrots intakes were significantly lower, respectively with an NFT with p = 0.01764 and 0.04715.

-for beverages, in the females group with MetS the red wine intake was significantly lower (NLF p = 0.00232) and in man the red wine and beer intakes were significantly lower in the MetS group (respectively NLF p = 0.03694 and 0.04853).

-For meat, processed meat and fish categories, in females with MetS the white meat intake was significantly higher than Controls (NFT p = 0.01515), whereas for all the other foods within the categories no significant differences were detected. For males the intakes of salami and offal were significantly lower in MetS group (respectively NFT p = 0.02932 and 0.0414), whereas in the same group the canned tuna consumption was much higher (NFT p = 0.03473).

- For dairy derivatives, in females no differences were found between the two groups, whereas in males the milk intake was significantly lower in the MetS subjects (NFT p = 0.04176).

-In the miscellanea group, no differences between MetS and Controls were found a part of chocolate whose intake was lower in males of the MetS group (NFT p = 0.0397).

All the differences determined through the NFT were confirmed by the relative analysis of the Odds Ratios.

The combination of foods that can be characteristic of MetS and Controls were reported according to the Likelihood Ratio Test (Table 7).

Table 7. Likelyhood ratio test for genders: foods within the observed range (whole model test)

Females

Males

 variable increase

 pertinence to 

variable increase

pertinence to

Water

MetS

Carrot

Controls

Alcohol

Controls

Chicory

MetS

Butter

Controls

Chocolate a

Controls

Coffee

MetS

Dried fruit

MetS

Crackers

MetS

Fennels

MetS

Fruit syrup

MetS

Fruit of the season

MetS

Fruit of the season

MetS

Garlic a

Controls

Ham

Controls

Ham

MetS

Homemade jam

MetS

Homemade jam

MetS

Homemade sandwich

Controls

Ice cream

MetS

Homemade fruit juice

MetS

Milk a

Controls

Lettuce

Controls

Pasta

MetS

Mayonnaise

MetS

Red Wine a

Controls

Potato

Controls

Sweeteners

MetS

Onions

Controls

White wine

Controls

White meat a

Mets

Yogurt

Controls

 

 

Zucchini

MetS

 

 

Pinapple

MetS

a = foods that were shown to be significantly different comparing the control Vs MetS if tested separately

It is evident that considering the combination of foods, a very different picture is coming out, such that only two foods (fruit of the season and homemade Jam) are common for the two sexes and all the other are different and a more complex figure seems to takes shape in the development of the MetS or to maintain the control condition. Some aspects are very difficult to explain as for example the increase of the fruit of the season that turns out to increase the possibility of MetS in both sexes, whereas in the single item analysis a non-significant higher intake was found in females only.

Discussion

Some limitations are present in this research concerning first of all the enrollment, since a selection was operated by the doctors asking their patients with MetS to participate matching them subjects of the same age. This means that only subjects interested to the relationship between food and MetS were participating to the study.

The second weak point concerns the foods tested because they were representing about 90 % of the total amount of the weekly caloric intake, and the lowest percentages were represented in the two groups suffering from MetS. This means that theoretically about 10 % of the foods not included in the analysis could be partially responsible of MetS.

Another limitation can be determined by the lack of evaluation of micronutrients that are considered to counteract MetS [20,21].

However, the micronutrients that were not part of the analysis were in relation only to the about 10 % of foods not considered in the analysis and should not influence critically the comparison between groups.

In general, the subjects participating to this study were those that the family doctor has to take care off in the daily practice and most of Control cases could not considered belonging to a healthy population.

Furthermore, it was not possible to compare the data of the three countries because the relative numbers were not enough to compare the two groups of subjects.

A part of these limitations some interesting indications can be drawn from the study.

The first observation which was common for both, female and males suffering from MetS, was a more consistent caloric intake. Compared to the values calculated with MSJ algorithm the caloric intake in MetS subjects was respectively >9.5 % in females and >4.7 % in males. Despite not excessive, at long term these increases may be determinant for the development of the disease.

The age of the two groups was < 52 years and one may not speculate about the incidence of MetS in relation to age since the subjects were selected by the family doctors. Because of this the incidence of the disease in the present study are higher than what has been determined in a previous survey conducted in some Italian towns where the incidence in a population between 35 and 65 years was < 20 % of the cases [16].

Foods were found to have a different impact in relation to the gender, and this could mean that the epidemiological studies should consider these aspects in long term survey and also the need of different treatment in terms of drugs.

The reason of this difference between genders is unknown and probably belongs to the hormonal balance. This hypothesis may arise also by the evidence that the intake of white meat was more consistent in females with MetS. The quite common practice (although is prohibited) to give estrogens to reduce the aggression of chickens and turkey in breeding farm may be one of the causes. Meat deriving from these animals is a substantial part of the white meat intake in Italy.

Some data that are considered common determinants of MetS, such as the excessive intake of carbohydrates, is not emerging from this study. At the opposite the total amount of carbohydrate-based food (consisting of about 80 % of the weight in carbohydrates) were respectively 1366 g in the normal females and 1203 g in females with MetS, the same was for males consisting of 1606 g/week for controls and 1499 g/week for MetS.

The amount of calories from fats were similar in all the groups (difference < 2 %) and also the ratio between carbohydrates or soluble sugars and fats was not having a discriminant power to differentiate MetS.

Some author found that carbohydrate restriction has a more favorable impact on the disease than low fat diet and our results do not confirm these findings [22]. Furthermore, our data do not confirm the negative impact of soluble sugars as other author have shown to be associated with MetS in females [23].

In terms of processed meat, it was shown that salami intake was lower in the MetS group and also the offal intake.

This may indicate more prudence in defining the processed meat as “carcinogenic to humans” [24].

A part of the quantity of processed meat intake, a quite careful distinction should be made about the way of producing this type of food which in many cases do not contain nitrates (or minimal amount), particularly when they are produced directly by the consumers like in some rural community.

The red wine seems to be protective in males, at least in the amount used in this study, that at the end was less than one alcoholic unit/day for both groups.

Other foods such as garlic and chocolate seem to be protective in males (not in females) and one may speculate the presence of powerful antioxidants in both [25,26].

One particular food, canned tuna, was found significantly more used in MetS males. Fish and fish oil are giving conflictual results on the disease, but recently were considered healthy for some author [27]. In our study we could not show any favorable activity of these foods. This is an example on how the food quantities, the context of a diet, the country, down to the single community may be determinant for the disease. All these aspect makes more complex the pathogenesis of MetS which also belongs to the genetics and epigenetics traits together with the microbiota.

Once the foods were analyzed together, a quite different picture was emerging where the interactions take place and single elements are diluted or amplified such that even drinking water may have a role (in females only), and genders differences are becoming extremely evident. Among the 17 foods for females and 18 foods for males which are bound respectively to the Controls or MetS conditions, only two are common: fruit of the season and homemade jam whose increasing intake was found related to the MetS.

Al the other foods are different, no matter if the increased quantities are bound to MetS or Controls.

One further important aspect arising from this study has to be mentioned and concerns the concomitant diseases. It was clear that people suffering from MetS have to be treated with more drugs. Considering the costs in terms of drug expenses- which in Italy is covered mostly by the Government- for an average life expectancy of 25 years more (from about 50 years up to about 75) the estimated cost is > € 20,000/subject.

This means that will be much more convenient   to use this money for prevention and education to give more life to the years.

Conclusions

In the context of a Mediterranean diet and in our experimental conditions it seems that MetS both in females and males was determined by higher amount of caloric intake, without a clear distinction between carbohydrates, fats, fibers, proteins and alcohol. Concomitant diseases such as CVD and osteoarthritis (in males only) were more common indicating a fragile healthy condition in subjects suffering from MetS.

A part of the caloric intake, the pattern of foods bound to the MetS was found completely different in females and males.

Some particular foods were more common in MetS, such as white meat (in females) or seasonal fruits and homemade fruit juice (for both genders). In males, the processed meat and red wine intake -in the relative limited quantities that have been determined - were found to be protective.

However, once the different foods were analyzed together a completely different relationship with MetS emerged, indicating that a single food category cannot be considered the cause of the disease which seems to be determined by the interactions of many foods, that again are different for females and males.

The disease has a heavy social and economic impact and despite common diagnostic aspects the causes and the remedies of MetS in terms of foods have such a proteiform aspect that any community (country, town, village) could have peculiar way to face it.

Larger epidemiological studies in each territorial context with specific food pattern are needed to give appropriate information on healthy foods. These aspects belong to the social/educational area and can be faced only with the help of the Governments, family doctors and local Municipalities.

Acknowledgements

The study was supported largely by private funding and no competing interest have to be declared. The Bracco Spa- Milan- Italy was supporting this study with a grant of € 100, 000.

The authors are grateful to the Municipalities of Rende, Rovito and San Lucido which made the surgeries available.

Contribution

UC was preparing the protocol, visited all the subjects and wrote the article; GC  visited all the subjects and was charged for the FIA; GM was charged with the ultrasound analysis; MR was assisting in the logistic of the investigation; OV was taking care of data input; MR was making all the statistical calculations using  JMP Pro 14.1 software of SAS institute Inc.

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Editorial Information

Editor-in-Chief

Article Type

Research Article

Publication history

Received date: November 20, 2018
Accepted date: December 03, 2018
Published date: December 06, 2018

Copyright

© 2018 Cornelli U. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Citation

Cornelli U (2018) Mediterranean diet and metabolic syndrome in three countries of Calabria, 2: DOI: 10.15761/GMO.1000149

Corresponding author

Cornelli Umberto

Loyola University School of Medicine, Chicago 2160 First Ave Maywood IL, Piazza Novelli 5 20129 Milan, Italy

E-mail : bhuvaneswari.bibleraaj@uhsm.nhs.uk

Table 1. Enrollment flow chart

 

Towns

Total

 

Rovito

San Lucido

Rende

Subjects

200

200

200

600

Drop out (no FIA report)

3

15

6

24

FIA Incorrect

13

27

7

47

 

 

 

 

 

Total non-included

16

42

13

71

 

 

 

 

 

Females Controls

72

69

71

212

Females with MetS

30

38

17

85

Male controls

52

39

66

157

Male with MetS

30

12

33

75

  

 

 

 

 

Total females

102

107

88

297

Total males

82

51

99

232

 

 

 

 

 

Total evaluated

184

158

187

529

Table 2. General characteristics of the subjects: mean values ± SD or frequencies

Gender

 

Females

Males

Disease

[N of cases]

 

Controls

 [212]

 

MetS

[85]

 

Controls

[157]

 

MetS

 [75]

 

Variables

Measure

Mean

SD

Mean

SD

Mean

SD

Mean

SD

Age

Years

47.5

6.95

47.5

7.97

50.0

7.98

51.9

8.35

Height

m

1.58

0.055

1.59

0.054

1.70

0.061

1.71

0.072

Weight

Kg

66.1

11.26

79.9a

15.7

80.2

11.59

89.9a

11.70

BMI

Kg/m2

26.6

4.69

31.7a

5.37

27.9

3.26

30.7a

3.87

AC

cm

87.9

13.93

102.4a

19.42

97.1

13.68

105.4a

25.45

BP min

mmHg

82

27.0

87a

28.3

82

28.3

88a

35.9

BP mx

mmHg

129

47.8

139a

46.7

132

50.4

140a

49.8

Total CH

mg/dL

205

37.9

212

41.6

214

37.7

204

36.6

LDL

mg/dL

126

33.2

138a

40.4

137

34.6

130

36.4

HDL

mg/dL

61

11.5

46a

11.1

51

9.9

40a

11.2

Triglycerides

mg/dL

101

34.5

175a

63.5

134

57.8

245a

153.3

Glucose

mg/dL

88

10.8

94a

16.8

93

13.6

103a

29.0

Smoking

Yes/no

12/200

 

5/85

 

8/149

 

5/70

 

Physical activity b

S/O

195/17

 

77/8

 

150/7

 

8/69

 

MSJ c

Kcal/week

11751

1479.1

12923

1511.8

15437

1659.2

16136

1882.0

Calorie intake d

Kcal/week

11304

4021.4

12378

4892.0

15045

5043.1

15752

4855.4

a t test Controls Vs MetS p < 0.05; b S = sedentariness and O = limited activity, normal activity, physical training; Caloric intake using Mifflin St Jeor formula; d Caloric intake calculated from the FIA

Table 3. Concomitant diseases: percentage of the total subjects

Gender

Females

Males

Disease

[N of cases]

Controls

 [212]

MetS

[85]

Controls

[157]

MetS

 [75]

Concomitant

disease

%

%

%

%

Allergic

1.9

1.2

2.5

4.0

Bronchopulmonary

0.5

0

0

0

Cardiovascular

13.2

29.4a

15.3

38.7a

Dyslipidemic

4.7

3.5

5.1

9.3

Dermatological

0.5

0

0.5

0

Endocrinological

10.4

10.5

1.3

2.7

ENT

0.5

1.2

0

0

Gastroenterological

3.3

7.1

2.5

8.0

Gynecological

0.9

0

-

-

Hematological

0.9

2.4

0

2.7

Osteoarthritic

58.0

50.6

31.8

45.3a

Odonatological

1.4

1.2

0

2.7

Ophthalmological

1.4

1.2

0

0

Neurological

3.3

4.7

0.6

1.3

Psychiatric

0.9

3.5

0

1.5

Urological

-

-

3.2

6.7

Cancer b

2.8

0

0

0

EC0 class IV

5.7

11.8

3.8

14.7 a

Total/person

1.10

1.24

0.6

1.30

% increase Vs control

 

13

 

117

a Chi square p < 0.05; b no malignancy

Table 4. Main food components as percentage of the total caloric intake and ratios with lipids: Mean ± SD

Gender

Females

Males

Disease

Controls

MetS

Controls

MetS

Components

Mean

SD

Mean

 SD

Mean

SD

Mean

SD

Carbohydrates

23.3

13.57

20.3

15.76

23.2

16.02

24.6

15.14

Soluble sugars

26.3

12.72

29.3

17.16

25.1

15.28

24.7

13.53

Proteins

16.3

2.86

16.8

4.25

16.0

2.96

16.7a

2.26

Lipids

33.8

5.98

33.6

6.90

31.0

6.13

31.4

6.28

Alcohol

1.5

2.05

1.1

1.90

5.4

4.30

3.7a

4.53

 

 

 

 

 

 

 

 

 

Fiber g/week

93

43.8

95

61.1

102

42.8

98

52.6

Ratio carbohydrates/lipids

0.72

0.469

0.62

0.517

0.78

0.585

0.88

0.758

Ratio

soluble sugars/lipids

0.82

0.526

0.91

0.560

0.86

0.630

0.82

0.484

a= t test Controls Vs MetS p < 0.05

Table 5. Average intake (g or mL) of different foods in Females (F) and Males (M) in the two groups of subjects, Controls and MetS, and relative discretization cut off for the different foods

Food

Controls

means

MetS

means

Discretization categories

and cut off values a

 

F/M

F/M

0

1

2

3

4

5

Carbohydrates based food

Biscuits

68/52

54/40

0

40

140

280

480

-

Bread  

433/587

456/550

0

200

450

950

2550

-

Breadsticks

4/4

8/2

0

20

100

280

-

-

Croissant

80/73

80/68

0

75

275

700

-

-

Crackers

17/10

22/7

0

40

80

280

-

-

Gnocchi

13/23

15/14

0

3

50

80

-

-

Oatmeal

10/8

15/8

0

80

280

600

-

-

Rusks

45/26

62/26

0

40

80

140

420

-

Sandwich homemade

85/107

55/97

0

40

280

1120

-

-

Sandwich commercial

13/22

21/21

0

54

315

630

-

-

Pasta

304/404

302/402

0

182

395

690

1200

-

Polenta

5/1

7/3

0

30

122

360

-

-

Pizza

153/163

153/140

0

34

150

422

1470

-

Potatoes

75/63

42/63

0

75

300

1060

-

-

Rice

50/50

55/49

0

25

145

280

560

-

Tortellini

11/13

15/9

0

25

100

240

-

-

Fruits

Apples

476/560

457/539

0

200

700

1400

4200

-

Banana

217/230

189/171

0

199

600

2800

-

-

Citrus fruit

500/542

360/498

0

200

1700

4000

-

-

Dried fruit

97/81

73/114

0

80

280

1900

-

-

Fruit in syrup

8/20

22/1

0

18

100

1050

-

-

Fruit of the season b

460/521

673/491

0

475

950

1450

4000

-

Fruit Juice mL

48/35

65/104

0

75

450

2100

-

-

Grapes

65/43

72/41

0

50

300

2350

-

-

Homemade juice mL

90/74

85/130

0

75

160

300

-

-

Pineapple

30/18

43/35

0

68

300

495

-

-

Plums

1/2

1/0

0

20

150

180

-

-

Vegetables/pulses

Carrots

47/41

36/33

0

40

140

690

-

-

Cauliflower

56/33

40/35

0

60

260

1820

-

-

Celery

19/11

21/12

0

3

140

330

-

-

Chicory/lettuce

187/193

160/194

0

90

245

490

500

1170

Fennels

108/93

70/124

0

480

2000

3380

-

-

Garlic

1.6/1.7

1.7/1

0

1.5

7

20

-

-

Onions

82/83

70/61

0

90

290

630

-

-

Pepper

61/68

100/52

0

50

250

1750

-

-

Pulses dry

21/27

21/25

0

45

90

225

-

-

Pulses canned

36/37

33/33

0

19

160

240

400

-

Savoy cabbage

40/43

50/45

0

15

320

1280

-

-

Soy germ

2/0

0/0

0

30

210

-

-

-

Spinach

93/76

87/54

0

80

350

1440

-

-

Tomato

326/367

320/360

0

60

340

820

2450

-

Zucchini

149/93

175/153

0

100

280

500

1890

-

Beverages

Spirits

5.5/32

3.6/17

0

80

300

560

-

-

Beer mL

108/319

128/205

0

240

760

3750

-

-

Coffee mL

250/267

247/282

0

195

280

480

1280

-

Sweet beverages mL

272/382

402/356

0

1980

3000

11880

-

-

Tea

1.9/4.4

2.6/1.1

0

1

5

21

210

-

Water [L]

6.3/6.8

7.1/7.3

0

2.8

5.8

8.5

21.0

-

Wine white mL

25/93

27/36

0

65

380

1820

-

-

Wine red mL

157/609

92/415

0

65

325

800

4400

 

Meat, processed meat, and fish

White meat

171/178

293/201

0

50

190

380

980

-

Red meat

201/260

209/216

0

100

140

400

-

-

Salami

124/184

117/135

0

75

170

280

340

820

Offal

13/14

6/13

0

50

140

340

-

-

Bacon

16/28

24/12

0

26

80

160

-

-

Ham

70/63

53/76

0

30

120

250

700

-

Speck

3/8

6/8

0

30

90

180

-

-

Fish

206/224

202/230

0

70

140

700

1400

-

Canned tuna

24/23

19/53

0

24

82

180

800

-

Dairy products

Milk mL

846/639

707/412

0

400

900

1400

2800

4800

Cheese

149/181

145/168

0

95

190

295

635

-

Ice cream

38/41

50/54

0

25

75

125

700

-

Mozzarella

70/67

76/72

0

25

75

160

640

-

Ricotta cheese

37/30

35/34

0

25

70

120

490

-

Yogurt

107/61

90/78

0

60

360

1680

-

-

Eggs

57/61

55/60

0

25

125

350

700

-

Dressing

Butter

7/7

6/8

0

40

160

270

-

-

Mayonnaise

2/4

4/1

0

5

21

320

-

-

Margarine

1/1

2/2

0

10

140

-

-

-

Olive oil

108/105

104/104

0

100

180

405

 

 

Desserts

Homemade jam

10/11

13/12

0

20

40

210

-

-

Honey

1/1

3/1

0

3

35

85

-

-

Chocolate

17/19

17/9

0

15

55

210

-

-

Cake

149/155

149/107

0

35

175

560

1330

-

Other foods miscellanea

Sweeteners

1.1/1.0

0.9/2.2

0

1

5

7

21

-

Salt added

25/25

24/23

0

12

22

35

43

140

Sugar added

37/31

35/33

0

14

31

75

270

-

example: biscuits - discretization category 1 (from 0 to 40 g); category 2 (from 40 g to 140 g); category 3 (from 140 g to 280 g); category 4 (from 280 g to 480 g); b Fruit of the season: mainly figs, peaches, apricot, strawberry, pear, and cherries.

Table 6. Percentages of subject in each discretization category (from D1 to D5) divided by sex

Gender

Female

Male

Disease

Controls

MetS

 

Controls

MetS

Discretization [D]

1

2

3

4

5

1

2

3

4

5

1

2

3

4

5

1

2

3

4

5

Carbohydrates based foods

Biscuits

42

38

17

3

-

55

29

13

3

-

58

29

9

4

-

67

19

13

1

- a

Bread

25

33

34

8

-

17

38

36

9

-

15

24

45

16

-

9

32

49

9

-

Breadsticks

92

6

2

-

-

94

4

2

-

-

92

6

1

-

-

92

8

0

-

-

Croissant

76

21

3

-

-

80

15

5

-

-

80

15

5

-

-

77

21

1

-

-

Crackers

83

7

10

-

-

80

9

11

-

-

90

5

5

-

-

92

5

3

-

-

Gnocchi

83

0

7

10

-

81

1

8

10

-

78

1

6

14

-

83

1

3

13

-

Oatmeal

91

8

1

-

-

94

4

2

-

-

97

2

1

-

-

95

5

0

-

-

Rusks

66

8

10

15

-

55

9

13

23

-

78

6

7

9

-

79

7

5

9

-

Sandwich homemade

63

24

12

1

-

65

28

6

1

-

61

26

11

2

-

60

24

13

3

-

Sandwich commercial

90

8

1

-

-

88

10

2

-

-

89

9

2

-

-

88

10

2

-

-

Pasta

26

49

21

4

-

30

38

30

2

-

15

41

37

7

-

12

41

36

11

-

Polenta

96

3

1

-

-

96

2

1

-

-

99

1

0

-

-

97

1

1

-

-

Pizza

31

30

36

3

-

26

41

31

2

-

28

34

34

4

-

33

32

33

1

-

Potatoes

75

19

6

-

-

83

11

6

-

-

81

10

9

-

-

77

17

5

-

-

Rice

48

43

8

1

-

50

41

7

2

-

51

39

6

4

-

55

35

11

0

-

Tortellini

87

9

3

-

-

81

14

5

-

-

85

11

4

-

-

89

7

4

-

-

Fruits

Apples

42

28

21

9

-

39

33

17

11

-

39

27

17

17

-

43

21

20

16

-

Banana

55

30

15

-

-

57

32

11

-

-

59

23

8

-

-

63

27

10

-

-

Citrus fruit

44

49

7

-

-

56

38

6

-

-

41

51

8

-

-

49

45

5

-

-

Dried fruit

69

21

10

-

-

57

25

8

-

-

70

18

12

-

-

66

23

11

-

-

Fruit in syrup

95

0

5

-

-

89

0

11

-

-

94

0

6

-

-

99

0

1

-

-

Fruit of the season b

62

18

12

8

-

57

13

15

14

-

60

16

15

9

-

71

7

9

13

- a

Fruit juice

95

5

-

-

-

94

6

-

-

-

95

4

1

-

-

88

9

3

-

-

Grapes

81

10

9

-

-

82

10

8

-

-

83

8

9

-

-

91

2

7

-

-

Homemade fruit juice

88

7

5

-

-

86

8

6

-

-

89

7

4

-

-

83

9

8

-

-

Pineapple

87

11

2

-

-

83

13

4

-

-

92

7

1

-

-

84

11

5

-

-

Plums

98

2

0

-

-

96

4

0

-

-

99

0

1

-

-

99

1

0

-

-

Vegetables and pulses

Carrots

58

32

10

-

-

71

20

8

-

- a

63

27

10

-

-

70

27

3

-

- a

Cauliflower

73

16

11

-

-

87

9

4

-

- a

82

12

6

-

-

81

15

4

-

-

Celery

74

22

4

-

-

78

17

5

-

-

85

12

3

-

-

88

7

5

-

-

Chicory/lettuce

31

42

21

1

5

36

33

25

2

4

27

41

25

3

4

35

37

20

1

7

Fennels

92

8

-

-

-

96

4

-

-

-

92

8

0

-

-

95

4

1

-

-

Garlic

63

30

7

-

-

60

33

7

-

-

62

31

7

-

-

77

19

4

-

- a

Onions

62

32

6

-

-

65

30

5

-

-

60

34

6

-

--

64

31

5

-

-

Pepper

72

20

8

-

-

68

20

13

-

-

72

18

10

-

-

77

15

8

-

-

Pulses dry

55

26

16

3

-

54

31

8

7

-

53

21

16

10

-

59

17

13

11

-

Pulses canned

72

16

9

3

-

76

13

7

4

-

73

17

5

5

-

68

25

4

3

-

Savoy cabbage

83

14

3

-

-

84

12

4

-

-

80

13

6

-

-

83

12

5

-

-

Soy germs

98

2

-

-

-

99

1

-

-

-

99

1

-

-

-

99

1

-

-

-

Spinach

69

23

8

-

-

69

27

4

-

-

74

20

6

-

-

85

8

7

-

-

Tomatoes

27

39

27

7

-

37

31

19

13

-

27

30

29

14

-

27

36

26

11

-

Zucchini

57

20

15

8

-

62

20

11

7

-

67

17

12

4

-

67

11

14

8

-

 Beverages

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Spirits

97

3

-

-

-

99

1

-

-

-

86

12

2

-

-

91

9

0

-

-

Beer

76

23

1

-

-

74

24

2

-

-

53

37

10

-

-

75

17

8

-

- a

Coffee

24

36

31

9

-

23

37

32

8

-

26

34

30

10

-

27

33

29

11

-

Sweet beverages

97

2

1

-

-

94

5

1

-

-

93

4

3

-

-

91

6

3

-

-

Tea

73

14

12

1

-

72

15

12

1

-

70

17

12

1

-

71

16

12

1

-

Water

3

32

40

25

-

2

33

39

26

-

2

35

37

26

-

3

31

41

25

-

Wine white

86

12

2

-

-

86

13

1

-

-

81

13

6

-

-

90

7

3

-

-

Wine red

61

19

15

5

-

73

19

3

5

a

20

17

29

34

-

45

20

16

19

- a

Meat, processed meat, and fish

White meat

26

28

35

8

3

12

36

32

12

8 a

25

28

34

9

4

28

23

29

11

9

Red meat

69

22

9

-

-

80

12

8

-

-

74

13

13

-

-

77

16

7

-

-

Salami

48

17

20

5

10

54

13

16

9

8

38

13

21

9

19

37

29

17

8

8 a

Offal

93

2

5

-

-

95

1

4

-

-

89

6

5

-

-

95

0

5

-

a

Bacon

76

15

9

-

-

79

15

6

-

-

75

15

10

-

-

74

16

10

-

-

Ham

38

33

27

2

-

45

32

21

1

-

41

27

28

4

-

37

28

29

5

-

Speck

95

3

1

-

-

92

6

2

-

-

86

10

4

-

-

89

8

3

-

-

Fish

29

59

11

1

-

35

52

12

1

-

31

52

12

5

-

27

60

11

2

-

Canned tuna

76

17

6

1

-

79

15

6

0

-

81

12

4

3

-

67

17

9

7

a

Dairy products

Milk

38

17

14

8

-

51

11

8

25

5

54

10

8

22

5

60

19

8

13

0 a

Cheese

32

35

21

12

-

31

43

13

13

-

26

29

27

18

-

36

27

17

20

-

Ice cream

64

15

12

9

-

62

12

11

15

-

68

11

11

10

-

57

13

15

15

-

Mozzarella

39

23

28

10

-

36

25

25

14

-

41

22

27

10

-

41

19

28

12

-

Ricotta cheese

60

17

14

9

-

62

18

14

6

-

57

22

13

8

-

63

15

14

8

-

Yogurt

68

18

14

-

-

71

17

12

-

-

80

9

11

-

-

83

8

9

-

-

Eggs

40

47

12

1

-

45

43

11

1

-

38

43

17

2

-

40

44

15

1

-

Dressing

Butter

93

7

-

-

-

96

4

-

-

-

94

5

1

-

-

92

8

0

-

-

Mayonnaise

89

7

4

-

-

84

12

4

-

-

88

10

23

-

-

91

8

1

-

-

Margarine

96

4

-

-

-

96

4

-

-

-

99

1

-

-

-

98

2

-

-

-

Olive oil

40

43

17

-

-

35

51

13

-

-

36

51

13

-

-

48

30

21

-

-

Desserts

Homemade jam

81

9

10

-

-

80

4

14

-

-

78

9

13

-

-

79

10

11

-

-

Honey

85

7

8

-

-

84

6

10

-

-

85

6

9

-

-

86

5

5

-

-

Chocolate

62

29

9

-

-

63

28

9

-

-

64

27

9

-

-

82

8

10

-

- a

Cake

35

31

28

6

-

37

29

29

5

-

36

30

27

7

-

35

30

29

6

-

Other foods miscellanea and water

Sweeteners

83

8

2

7

-

80

6

4

10

-

82

9

3

6

-

81

10

4

5

-

Salt

13

46

16

21

4

14

45

18

17

6

12

47

16

20

5

13

47

15

20

5

Sugar (added)

31

15

42

11

-

40

27

30

13

-

30

16

40

14

-

35

18

27

20

-

a = Nominal Logistic Fit p < 0.05 Controls Vs MetS; see Table 5 for the average values

Table 7. Likelyhood ratio test for genders: foods within the observed range (whole model test)

Females

Males

 variable increase

 pertinence to 

variable increase

pertinence to

Water

MetS

Carrot

Controls

Alcohol

Controls

Chicory

MetS

Butter

Controls

Chocolate a

Controls

Coffee

MetS

Dried fruit

MetS

Crackers

MetS

Fennels

MetS

Fruit syrup

MetS

Fruit of the season

MetS

Fruit of the season

MetS

Garlic a

Controls

Ham

Controls

Ham

MetS

Homemade jam

MetS

Homemade jam

MetS

Homemade sandwich

Controls

Ice cream

MetS

Homemade fruit juice

MetS

Milk a

Controls

Lettuce

Controls

Pasta

MetS

Mayonnaise

MetS

Red Wine a

Controls

Potato

Controls

Sweeteners

MetS

Onions

Controls

White wine

Controls

White meat a

Mets

Yogurt

Controls

 

 

Zucchini

MetS

 

 

Pinapple

MetS

a = foods that were shown to be significantly different comparing the control Vs MetS if tested separately