Research Article
Clin Oncol Res. 2018; 1(2): 1006.
Dietary Patterns and Oncological Morbidity in European and Mediterranean Countries
Radkevich LA and Radkevich DA*
FGBUN Center of Theoretical Problems of Physico- Chemical Pharmacology RAS, Kosygina, Moscow, Russia
*Corresponding author: Radkevich DA, FGBUN Center of Theoretical Problems of Physico-Chemical Pharmacology RAS; 119991, Kosygina st. 4, Moscow, Russia
Received: April 17, 2018; Accepted: August 23, 2018; Published: August 30, 2018
Abstract
Purpose of the study is an analysis of the impact of per capita income, latitude and nutrition structure on the cancer incidence in European (Euro) and Mediterranean (Med) countries.
Materials and Methods: Study design is observational. Nutrition structures for countries are presented as a general level of food consumption (g/person/ day) and as the percentage contribution of 4 blocks: animal products; grains and vegetables; fruit and drinks; alcoholic beverages.
Results: In European countries, compared with the Med countries, the incidence of 7 cancer types in Euro countries depend on per capita income and latitude. In Euro countries, the incidence of 5 cancer types depends on “clean” per capita income. The incidence of 5 cancer types depends on “clean” latitude. The incidence of 7 cancer types in Euro and Mediterranean countries does not depend on per capita income, nor on latitude.
The nutrition structure in Euro and Med countries depends on per capita income. The higher is per capita income in Euro countries, the higher is a share of animal products and alcoholic beverages in the nutrition structure. (p = 0.004). The level of macronutrients of animal in Euro countries is 1.5, 2.3 and 3.0 times higher than in Med countries and depends on per capita income (p = 0.001).
Conclusions: The nutrition structure as a risk factor for cancer in the Euro and Med countries depends on per capita income. The composition and sources of macronutrients play an important role in the nutrition structure.
Keywords: Dietarypatterns; Cancer; European; Mediterranean countries
Reductions
NCD: Chronic Noncommunicable Diseases; Euro: European countries; Med: Mediterranean Countries; BMI: Body Mass Index; BH: Blood Cholesterol Level; BG: Blood Glucose; BP: Blood Pressure; GDP: Per Capita Income; EEI: Ecological Efficiency Index; HDI: Human Development Index; QR: Interquartile Range; FAO: Food and Agriculture Organization of the United Nations.
Introduction
Each year, 15 million people die from a Chronic Noncommunicable Diseases (NCD) between the ages of 30 and 69 years; over 59% of these followed by cancers (8.8 million), which pose a threat to human longevity [1]. Cancer is the main cause of morbidity and mortality in developed countries [2].
It is shown that in the Mediterranean countries the incidence of breast cancer and Alzheimer’s disease are lower [3-9]. The authors point out the protective effect of the Mediterranean diet, with low share of animal protein containing products and high share of unsaturated fatty acids [3-9]. It is shown that eating disorders in prenatal period can contribute to predisposition to non-infectious chronic diseases (NCD) at an older age [10]. Diets with high share of fats and calories are risk factors for cancer [11,12]. There is little information about the risk of high-calorie diets with different sources of calories (fats, proteins, carbohydrates) [13,14]. We have shown that a risk factor for breast cancer may be a Western diet that contains the same level of total energy as the Mediterranean diet, but a different source of Proteins and Fats [6,7]. It is shown that food behavior, the regulation of which is complicated, may be a risk factor for obesity and breast cancer, as well as other cancer types [15,16]. But food is a modifiable factor. Therefore, the negative impact of nutrition on NCD can be reduced by developing safe, low-immune diets.
A number of authors believe that observational studies can be used to study nutrition as a risk of NCD, since they operate with large data sources [17-19]. However, observational analyzes based on correlation methods are considered weakly evidence-based. This is due to the possible influence of hidden variables [8]. At the same time, case-control studies on the effect of animal fats on the risk of breast cancer have not been repeated [9]. Objective: comparative analysis of oncological morbidity in European and Mediterranean countries. The study of the influence of GDP (per capita income) and latitude on the incidence of cancer of different locations and the nutrition structure, including macronutrients, in the European and Mediterranean countries.
Materials and Methods
Studies design is observational. Incidence rates in 160 countries standardized by age per 100,000 of population was selected from the GLOBOCAN database for 2008; WHO 2004 [20,21].
Data on and life expectancy were selected from the database of the Internet resource [22]. The level of food consumption for each country was selected from the FAO for 2005 [23]. The countries’ dietary patterns were presented as a general level of food consumption (g / person / day), and also in the form of 4 blocks as a percentage of the total consumption level: 1 - animal products; 2 - cereals and vegetables; 3 - fruit and drinks; 4 - alcoholic beverages (6).
In order to characterize the social conditions in countries, the following indicators were used: GDP (Per Capita Income), (Human development index) 2008 and 2016 ($/person/day) [24]; Health care Indices [25], Environmental Performance Index [26] and Happiness Index 2016 [27]. The geographical position of each country was judged by the latitude [28]. As predictors of the Metabolic Syndrome [29].
The statistical analysis of the comparative country samples was carried out using the nonparametric Mann-Whitney-Wilcoxon U-test for independent samples, since some of the country sample indicators were not normally distributed. The central trend in the distribution of data in the sample was represented by the Median. The variance of the data in the samples was estimated using the Interquartile range (QR) between the first and third quartiles, that is, between the 25th and 75th percentiles (StatSoft 13) [30].
Study Results
Analysis of the nutrition structure and cancer incidence in European and Mediterranean countries with a 2 times difference in per capita income
For the study were used 16 European countries, in which the average per capita income was 2 times higher than in 16 Mediterranean countries (Table 1). The per capita income of Euro countries was $39 (QR-6.7), in 16 Med countries it was $14 (QR-23.4), (p=0.001). Euro countries are located in high latitudes - 52°(QR-8.5), Med countries are located in mid-latitudes - 36°(QR-7.0) (p=0.001) (Table1).
Indicator
U n-16/16
Z
p-value
Median 1
Quartile 1
Median 2
Quartile 2
Total morbidity
Male - general morbidity (DALY - person/100 thousand) standardized by age
77
-1,90
0,0570
11573,8
1624,40
17060,8
6899,03
Female - general morbidity (DALY - person/100 thousand) standardized by age
83
-1,68
0,0935
9970,0
780,97
14739,8
6872,95
Humandevelopmentindex
32
3,60
0,0003
0,957
0,017
0,833
0,177
HealthRating
21
-4,01
0,0001
12,5
13,50
58,0
45,50
HappinessIndex 2016
18
4,13
0,0000
7,057
0,658
5,468
1,319
Ecologicalefficiencyindex
14
4,17
0,0000
77,8
4,04
57,0
14,34
Average life expectancy
Male life expectancy
90
1,41
0,1576
75,9
1,40
74,8
6,15
Female life expectancy
82
1,73
0,0830
82,2
1,95
79,9
7,35
Economic and geographical factors
Of GDP($) 2008 - per capita income
18
4,15
0,0000
38,7
6,65
13,9
23,35
lat°-geographical latitude
4
4,65
0,0000
51,6
8,45
36,2
6,95
Frequency of cancer diseases - person/100 thousand age-standardized population
Blader
109
0,72
0,4739
17,0
6,95
15,6
9,15
Brain
51
2,90
0,0037
6,6
0,70
5,6
2,40
Breast
47
3,05
0,0023
84,5
16,20
46,6
40,45
Cervix
62
2,47
0,0136
7,6
4,65
5,2
3,10
Colorect
38
3,37
0,0007
42,3
9,65
13,6
23,05
Corpusut
32
3,62
0,0003
12,8
3,55
8,1
7,70
Gollblad
87
1,55
0,1223
1,6
1,05
1,4
0,80
Hodgkin l
117
-0,40
0,6923
2,4
0,75
2,5
1,15
Kaposi s
128
0,02
0,9850
0,0
0,00
0,0
0,00
Kidney
40
3,30
0,0010
10,1
4,80
4,2
6,75
Laryngx
78
-1,87
0,0621
4,3
2,65
5,4
1,60
Leukaemia
75
2,00
0,0458
8,5
1,25
7,3
4,25
Liporal
58
2,62
0,0088
5,8
2,65
3,4
4,30
Liver
113
0,57
0,5718
4,7
2,80
3,7
5,40
Lung
87
1,53
0,1269
42,0
11,40
33,0
22,75
Melanoma
12
4,35
0,0000
11,4
4,35
2,4
5,25
Nasophar
15
-4,24
0,0000
0,4
0,20
1,1
1,70
Oesophar
24
3,90
0,0001
6,1
2,95
1,8
2,35
Ovary
29
3,73
0,0002
10,3
3,40
6,6
3,65
Pancreas
64
2,41
0,0159
8,1
2,80
4,5
4,50
Prostate
20
4,05
0,0001
82,9
29,30
19,1
43,15
Stomach
94
1,26
0,2067
9,1
2,65
7,3
6,75
Testis
11
4,39
0,0000
8,3
2,10
2,5
3,55
Thyroid
87
1,53
0,1269
2,2
1,10
1,2
2,15
Allcancer
28
3,75
0,0002
319,3
33,45
184,8
148,95
Table 1: Analysis of the nutrition structure and cancer incidence in European and Mediterranean countries with a 2 times difference in per capita income (Mann- Whitney U-test).
Metabolic Syndrome
Male BMI>25 (kg/m2) - body mass index
77
1,92
0,0546
64,6
7,10
Female BMI>25 (kg/m2) - body mass index
86
-1,56
0,1178
52,3
6,80
60,1
7,10
Male ch> 5.0 (mmol/L) - blood cholesterol level
30
3,67
0,0002
64,8
9,40
57,3
12,85
Female ch>5.0 (mmol/L) - blood cholesterol level
33
3,56
0,0004
62,8
7,45
43,8
22,75
Male glu>7.0 (mmol/L) - blood glucose level
123
0,17
0,8653
10,8
2,50
45,9
17,00
Female glu>7.0 (mmol/L) - blood glucose level
82
-1,71
0,0864
8,1
2,60
10,7
2,20
Male AD>140/90 (mmHg) - level of arterial blood pressure
45
3,11
0,0019
47,3
4,65
9,8
2,60
Female AD >140/90 (mmHg) - level of arterial blood pressure
84
1,64
0,1011
41,1
8,20
43,4
7,95
Male insact<60 minutes/day walking - low physical activity
62
-0,79
0,4273
39,6
16,30
38,3
6,00
Female insact<60 minutes / day walking - low physical activity
47
-1,61
0,1063
39,4
17,00
47,7
21,00
Dietary patterns
53,6
22,70
The general level of consumption (g/person/day)
97
1,17
0,2427
2192,0
206,00
2155,0
560,50
Animal products (%)
47
3,03
0,0024
35,9
7,46
25,0
10,17
Grain-vegetables (%)
6
-4,58
0,0000
35,9
5,18
58,4
16,80
Fruitdrinks (%)
56
2,71
0,0067
13,7
3,80
11,6
2,60
Alcoholicbeverages (%)
9
4,47
0,0000
14,7
4,80
1,9
6,81
Macro nutrients
Nutrients Animal products
Energy %
22
4,00
0,0001
31,5
5,50
19,0
17,00
?rotein %
37
3,43
0,0006
61,0
5,50
45,5
28,00
Fat %
37
3,43
0,0006
59,0
5,00
33,5
19,00
Percentage composition of Energy
Carboh %
69
-2,22
0,0262
51,0
2,00
59,0
12,50
Proteins %
118
0,36
0,7203
12,0
2,00
12,0
2,00
Fats %
71
2,15
0,0317
36,0
3,00
29,5
11,00
T?tal Energy 100%
Energy (kcal / person / day)2003-05
100
1,06
0,2913
3400,0
350,00
3300,0
435,00
Proteins (g/person / day) 2003-05
101
1,00
0,3179
104,0
10,00
96,5
27,50
Fats (g/person / day) 2003-05
72
2,09
0,0365
136,5
20,50
105,5
56,00
Proteins/Fats 2003-05 %
78
-1,87
0,0621
77,0
13,00
83,0
33,00
Micro nutrients
Animal origin2003-05
93
1,30
0,1935
3,5
0,80
2,8
2,75
Vit. ? 2003-05
59
2,60
0,0093
6,5
1,00
6,0
1,00
Vegetal origin 2003-05
52
-2,86
0,0042
9,5
2,60
13,3
3,00
Diversification of nutrition
Energy % 2003-05
39
3,34
0,0009
71,0
7,00
58,0
18,50
Proteins % 2003-05
48
3,00
0,0027
72,0
6,50
62,0
24,00
Fats % 2003-05 Fats %
65
2,36
0,0185
97,0
1,00
94,0
4,50
Table 1 of 2:
In Euro and Med countries, the total morbidity and life expectancy were statistically the same (p=0.1). But in Med countries, the Health Care Index, the Happiness Index and the Eco-Efficiency Index were lower than in Euro countries (p=0.001).
Cancer incidence: in Euro countries, the incidence of 13 out of the 25 cancer types (Brain, Breast, Cervix, Colorect, Corpus ut, Kidney, Lip oral, Melanoma, Oesophar, Ovary, Pancreas, Prostate, Testis) was 1.7 times higher (p=0.01). In Med countries, the incidence of Nasophar cancer was 2.5 times higher (p=0.0001). The incidence of 10 cancer types (Blader, Gollblad, Hodgkin, Kaposi s, Liver, Laryngx, Leukaemia, Lung, Stomach, Thyroid) had no statistical differences between Euro and Med countries (p=0.9).
In Euro and Med countries, the number of men and women (% of the population) with a BMI> 25kg/m2 was not statistically different (p=0.1), but was higher than 50%. In Euro countries, there were 1.7 times more men and women with a blood cholesterol level> 7mmol/L (p=0.001) and men with arterial pressure> 140/90mmHg (p=0.001). In Euro and Med countries, there were 45-50% of men and women with low physical activity.
Nutrition structure: In Euro countries, the nutrition structure was statistically different from that of Med countries. A share of animal products in Euro countries was 35.9%, in Med countries it was 25.0% (p=0.002). A share of grain and vegetables in Euro countries was 36.0%, in Med countries it was 58.4% (p=0.001). A share of alcoholic beverages in Euro countries was 14.7%, in the Med countries it was 1.9% (p=0.001). A share of fruits and drinks in Euro countries was 13.7%, in Med countries it was 11.6% (p=0.06). The level of total Energy in Euro and Med countries did not differ (p=0.4) and amounted to 3390 and 3300kcal /person/day, respectively. The general level of food consumption in Euro and Med countries did not differ and was 2185 and 2155 (g/person/day) (p=0.5). The composition of macronutrients in the total Energy (Carbohydrates, Proteins, Fats) did not differ (p=0.5) in Euro and Med countries. Macronutrient levels of animal products (Energy, Proteins and Fats) were 1.5-2 times higher in Euro countries than in Med countries (p=0.001). Diversification of nutrition in Euro countries was higher than in Med countries (p=0.001).
Thus, in Euro countries, despite the high standard of living, the incidence of 13 cancer types out of 24 was higher than in Med countries. The incidence of 10 cancer types did not differ from those of Med countries. It is logical to assume that in Euro countries with a higher per capita income, the number of the cancer types with a changed incidence will increase.
Analysis of the nutrition structure and cancer incidence in European and Mediterranean countries with a 4 times difference in per capita income
Euro2 included countries with the per capita income of $30 (QR- 6.2), four times higher than the per capita income of Med2, $7 (QR- 4.3) (p = 0.001) (Table 2). Latitude of Euro2 and Med2 countries was the same (p=0.7), which allowed to assess the “clear” impact of per capita income on the countries characteristics, that is without the influence of latitude.
Indicator
U m- 8/8
Z
p-value
Median 1
Quartile 1
Median 2
Quartile 2
Totalmorbidity
Male - general morbidity (DALY - person/100 thousand) standardized by age
-
-3,31
0,0009
10790,6
1521,19
17689,7
2,159,544
Female - general morbidity (DALY - person/100 thousand) standardized by age
-
-3,31
0,0009
9344,3
1532,85
16217,2
2,762,776
Human development index
-
3,31
0,0009
0,939
0,045
0,762
0,082
Health Rating
-
-3,31
0,0009
27,0
10,50
69,0
21,000
Happiness Index 2016
8
2,47
0,0136
6,169
0,966
5,087
0,762
Ecological efficiency index
5
2,78
0,0054
66,8
9,82
54,6
5,930
Average life expectancy
Male life expectancy
3
2,99
0,0028
77
1
71
4
Female life expectancy
2
3,15
0,0016
83
2
75
3
Economic and geographical factors
Of GDP ($)2008 - per capita income
-
3,31
0,0009
30,1
6,20
6,8
4,350
lat° - geographical latitude
20
1,21
0,2271
39,2
9,75
35,9
5,000
Frequency of cancer diseases - person/100 thousand age-standardized population
Blader
21
1,10
0,2701
17,0
8,80
15,6
10,200
Brain
10
2,26
0,0239
6,1
1,75
3,7
2,450
Breast
2
3,10
0,0019
69,9
32,65
33,4
14,300
Cervix
31
0,11
0,9164
6,0
2,75
5,3
5,850
Colorect
-
3,31
0,0009
37,9
17,70
10,9
5,150
Corpusut
-
3,31
0,0009
10,9
2,80
3,2
3,050
Gollblad
18
1,47
0,1415
1,7
0,95
1,2
1,250
Hodgkin l
17
1,52
0,1278
2,8
0,75
2,1
1,250
Kaposi s
32
-0,05
0,9581
0,0
0,00
0,0
0,000
Kidney
5
2,78
0,0054
9,4
5,50
2,6
1,750
Laryngx
29
0,32
0,7527
5,5
3,65
5,7
1,650
Leukaemia
4
2,89
0,0039
9,850
2,25
5,000
2,250
Liporal
13
2,00
0,0460
6,2
5,40
2,8
2,100
Liver
15
1,73
0,0831
6,5
6,95
2,3
3,350
Lung
13
1,94
0,0520
46,6
20,10
26,5
24,100
Melanoma
3
2,99
0,0028
6,8
5,05
0,5
1,350
Nasophar
15
-1,79
0,0742
0,9
0,60
1,6
3,000
Oesophar
20
1,26
0,2076
2,9
3,45
1,3
2,000
Ovary
5
2,84
0,0046
8,4
2,80
5,0
2,500
Pancreas
8
2,47
0,0136
7,2
1,75
2,7
1,750
Prostate
2
3,10
0,0019
53,2
12,30
10,7
10,800
Stomach
18
1,42
0,1563
10,0
5,75
5,9
9,500
Testis
2
3,10
0,0019
5,4
3,45
0,7
1,700
Thyroid
18
1,47
0,1415
3,2
2,50
1,2
0,550
Allcancer
2
3,10
0,0019
306,8
107,20
130,7
75,950
Metabolic Syndrome
Male BMI>25 (kg/m2) - body mass index
13
2,00
0,0460
63,3
6,10
59,2
17,200
Female BMI>25 (kg/m2) - body mass index
17
-1,52
0,1278
52,0
10,50
60,1
12,100
Male ch> 5.0 (mmol/L) - blood cholesterol level
-
3,31
0,0009
59,4
11,10
36,7
3,450
Female ch>5.0 (mmol/L) - blood cholesterol level
-
3,31
0,0009
56,9
8,45
41,4
5,650
Male glu>7.0 (mmol/L) - blood glucose level
18
1,47
0,1415
11,2
1,20
10,2
2,400
Female glu>7.0 (mmol/L) - blood glucose level
29
-0,26
0,7929
10,0
2,85
9,7
1,950
Male AD>140/90 (mmHg) - level of arterial blood pressure
11
2,21
0,0274
45,9
3,55
38,7
6,250
Female AD>140/90 (mmHg) - level of arterial blood pressure
18
1,42
0,1563
39,9
5,60
36,6
6,150
Male insact<60 minutes/day walking - low physical activity
12
-0,28
0,7768
47,7
23,20
39,5
19,850
Female insact<60 minutes/day walking - low physical activity
13
0,09
0,9247
56,3
38,20
44,8
13,850
Table 2: Analysis of the nutrition structure and cancer incidence in European and Mediterranean countries with a 4 times difference in per capita income (Mann- Whitney U-test).
Dietary patterns
The general level of consumption (g/person/day)
3
2,99
0,0028
2283,5
234,50
1770,0
380,000
Animal products (%)
8
2,47
0,0136
30,2
5,61
22,1
6,440
Grain-vegetables (%)
4
-2,89
0,0039
45,7
11,17
65,5
8,340
Fruit drinks (%)
23
0,89
0,3720
11,9
1,55
10,6
3,900
Alcoholic beverages (%)
1
3,20
0,0014
8,8
5,15
1,0
0,895
Macro nutrients
Nutrients Animal products
Energy %
7
2,57
0,0101
26,5
6,50
10,5
6,500
?rotein %
1
3,20
0,0014
54,5
10,00
26,5
12,500
Fat %
11
2,15
0,0313
44,5
14,00
31,0
7,500
Percentage composition of Energy
Carboh %
5
-2,78
0,0054
50,5
8,00
63,0
11,500
Proteins %
16
1,68
0,0929
13,0
1,00
11,0
0,500
Fats %
4
2,89
0,0039
37,0
7,00
26,0
10,500
T?tal Energy 100%
Energy (kcal/person/day)2003-05
12
2,10
0,0357
3565,0
385,00
3175,0
250,000
Proteins (g/person/day) 2003-05
8
2,47
0,0136
114,50
12,00
89,00
9,000
Fats (g/person/day) 2003-05
3
2,99
0,0028
146,0
33,00
90,0
35,000
Proteins/Fats 2003-05 %
9
-2,42
0,0157
75,5
11,00
106,0
51,000
Micro nutrients
animal origin2003-05
2
3,10
0,0019
4,4
1,20
1,7
0,800
vit. ? 2003-05
24
0,79
0,4309
6,0
1,00
5,5
2,000
vegetal origin2003-05
32
0,00
10,000
12,9
5,80
13,3
2,400
Diversification of nutrition
Energy% 2003-05
-
3,31
0,0009
67,0
7,50
48,5
16,000
Proteins% 2003-05
1
3,20
0,0014
68,5
8,50
44,5
16,000
Fats% 2003-05 Fats%
5
2,78
0,0054
97,0
2,00
92,5
6,500
Table 2 pf 2:
In Euro2 countries with high per capita incomes, overall morbidity was lower (p=0.001), life expectancy (p=0.002), Happiness Index, Eco-efficiency Index and Health Care Index (p=0.02) were higher.
Cancer incidence: In Euro2 countries with a high per capita income, the incidence of 12 cancer types out of 24 (Brain, Breast, Colorect, Corpus ut, Kidney, Leukaemia, Lip oral, Melanoma, Ovary, Pancreas, Prostate, Testis) was 2-5 times higher than (p=0.01). The incidence of the other 12 cancer types out of 24 again did not differ between countries (Blader, Cervix, Gollblad, Hodgkin L, Kaposi s, Laryngx, Liver, Lung, Nasophar, Oesophar, Stomach, Thyroid) (p=0.5) .
In countries with a high per capita income, there were 1.1 times more men with a BMI> 25 (p=0.04), 1.5 times more men and women with cholesterol level> 5.0 (p=0.001), 1.3 times more men with high blood pressure> 140/90mmHg (p=0.02).
The nutrition structure: The nutrition structure of Euro2 countries contained 30.2% and 22.1% of animal products compared to the Med2 countries (p=0.01); 45.7% and 65.5% of grain and vegetables (p=0.003); 8.8% and 1.0% (p=0.001) of alcoholic beverages; 11.9% and 10,6% (p=0.4) of fruit and drinks. In Euro2 countries, the food consumption level was 1.5 times higher (p=0.002). In Euro2 countries, the level of Energy was 1.05 times higher than in Med2 (p=0.03), Proteins and Fats were 1.8 times higher in Euro2 than in the Med2 countries (p=0.01). The level of macronutrients of animal products (Energy, Proteins and Fats) was 2 times higher in Euro2 countries than in Med2 countries (p=0.01). Diversification of nutrition in Euro2 countries was 1.5 times higher than in Med2 countries (p=0.005).
Thus, in Euro2 countries with 4 times higher per capita income than in Med2 countries, the incidence of the same 12 cancer types out of 24 was higher than in Med2 countries. The incidence of the remaining 12 cancer types did not differ between countries. To find out the reasons for the increase in incidence only for certain cancer types in response to the increase of per capita income, we undertook one more study. We have chosen 8 European countries, in which a per capita income was 6 times higher than in Med2 countries.
Analysis of the nutrition structure and cancer incidence in European and Mediterranean countries with 6 times difference in per capita income
For the analysis, 8 European countries with a per capita income of $41 and 8 Mediterranean countries with a per capita income of $7 (p=0.001) were selected (Table 3). Euro3 countries are located in higher latitudes (52°) compared to Med3 countries (36°) (p=0.001). Social characteristics in Euro3 countries were 3-10 times higher than in Med3 countries (p=0.001).
Indicator
U n-8/8
Z
p-value
Median 1
Quartile 1
Median 2
Quartile 2
Totalmorbidity
Male - general morbidity (DALY - person/100 thousand) standardized by age
-
-3,31
0,0009
11167,2
1487,77
17689,7
2159,54
Female - general morbidity (DALY - person/100 thousand) standardized by age
-
-3,31
0,0009
9512,7
707,08
16217,2
2762,78
Human development index
-
3,31
0,0009
0,962
0,007
0,762
0,08
Health Rating
-
-3,31
0,0009
7,0
10,50
69,0
21,00
Happiness Index 2016
-
3,31
0,0009
7,315
0,491
5,087
0,76
Ecological efficiency index
-
3,31
0,0009
78,1
3,47
54,6
5,93
Average life expectancy
Male life expectancy
-
3,31
0,0009
76
2
71
3,60
Female life expectancy
1,0
3,20
0,0014
82
2
75
2,55
Economic and geographical factors
Of GDP ($)2008 - per capita income
-
3,31
0,0009
41,1
13,05
6,8
4,35
lat° - geographical latitude
-
3,31
0,0009
52,0
9,10
35,9
5,00
Frequency of cancer diseases - person/100 thousand age-standardized population
Blader
19,0
1,31
0,1893
18,1
8,70
15,6
10,20
Brain
8,5
2,42
0,0157
6,6
1,30
3,7
2,45
Breast
-
3,31
0,0009
85,9
12,40
33,4
14,30
Cervix
20,5
1,16
0,2480
7,6
4,25
5,3
5,85
Colorect
-
3,31
0,0009
41,1
9,70
10,9
5,15
Corpusut
-
3,31
0,0009
12,6
2,00
3,2
3,05
Gollblad
28,5
0,32
0,7527
1,5
0,30
1,2
1,25
Hodgkin l
27,0
0,47
0,6365
2,5
0,55
2,1
1,25
Kaposi s
32,0
-0,05
0,9581
0,0
0,00
0,0
0,00
Kidney
7,0
2,57
0,0101
9,250
1,75
2,600
1,75
Laryngx
11,0
-2,15
0,0313
4,0
1,65
5,7
1,65
Leukaemia
5,0
2,78
0,0054
8,7
1,25
5,0
2,25
Liporal
7,0
2,57
0,0101
5,6
0,95
2,8
2,10
Liver
21,0
1,10
0,2701
3,7
5,75
2,3
3,35
Lung
17,5
1,47
0,1415
38,2
8,35
26,5
24,10
Melanoma
-
3,31
0,0009
14,3
5,10
0,5
1,35
Nasophar
-
-3,31
0,0009
0,4
0,20
1,6
3,00
Oesophar
3,5
2,94
0,0033
6,1
3,45
1,3
2,00
Ovary
1,5
3,15
0,0016
10,2
2,95
5,0
2,50
Pancreas
8,0
2,47
0,0136
7,7
2,20
2,7
1,75
Prostate
-
3,31
0,0009
87,2
40,80
10,7
10,80
Stomach
19,0
1,31
0,1893
8,1
2,10
5,9
9,50
Testis
-
3,31
0,0009
8,5
2,70
0,7
1,70
Thyroid
11,0
2,15
0,0313
1,8
1,60
1,2
0,55
Table 3: Analysis of the nutrition structure and cancer incidence in European and Mediterranean countries with 6 times difference in per capita income (Mann-Whitney U-test).
Allcancer
-
3,31
0,0009
321,2
35,90
130,7
75,95
Metabolic Syndrome
Male BMI>25 (kg/m2) - body mass index
21,0
1,10
0,2701
60,2
7,00
59,2
17,20
Female BMI>25 (kg/m2) - body mass index
8,5
-2,42
0,0157
48,6
6,50
60,1
12,10
Male ch> 5.0 (mmol/L) - blood cholesterol level
-
3,31
0,0009
64,8
5,45
36,7
3,45
Female ch>5.0 (mmol/L) - blood cholesterol level
-
3,31
0,0009
62,3
4,15
41,4
5,65
Male glu>7.0 (mmol/L) - blood glucose level
30,5
-0,11
0,9164
10,0
2,40
10,2
2,40
Female glu>7.0 (mmol/L) - blood glucose level
7,5
-2,52
0,0117
7,2
1,90
9,7
1,95
Male AD>140/90 (mmHg) - level of arterial blood pressure
6,5
2,63
0,0087
46,5
2,85
38,7
6,25
Female AD>140/90 (mmHg) - level of arterial blood pressure
22,5
0,95
0,3446
37,7
5,25
36,6
6,15
Male insact<60 minutes/day walking - low physical activity
14,0
-0,09
0,9247
45,1
16,20
39,5
19,85
Female insact<60 minutes/day walking - low physical activity
11,0
-0,47
0,6366
44,3
10,80
44,8
13,85
Dietary patterns
The general level of consumption (g/person/day)
7,0
2,57
0,0101
2228,0
416,00
1770,0
380,00
Animal products (%)
7,0
2,57
0,0101
36,6
7,33
22,1
6,44
Grain-vegetables (%)
-
-3,31
0,0009
34,5
4,86
65,5
8,34
Fruit drinks (%)
6,0
2,68
0,0074
15,9
2,70
10,6
3,90
Alcoholic beverages (%)
-
3,31
0,0009
14,4
7,00
1,0
0,90
Macro nutrients
Nutrients Animal products
Energy %
-
3,31
0,0009
33,0
5,00
10,5
6,50
?rotein %
-
3,31
0,0009
64,0
4,50
26,5
12,50
Fat %
7,0
2,57
0,0101
60,5
3,00
31,0
7,50
Percentage composition of Energy
Carboh %
-
-3,31
0,0009
51,0
1,50
63,0
11,50
Proteins %
13,0
1,94
0,0520
12,5
1,0
11,0
0,50
Fats %
-
3,31
0,0009
37,0
3,00
26,0
10,50
T?tal Energy 100%
Energy (kcal/person/day)2003-05
8,5
2,42
0,0157
3420,0
370,00
3175,0
250,00
Proteins (g/person/day) 2003-05
3,0
2,99
0,0028
107,0
8,00
89,0
9,00
Fats (g/person/day) 2003-05
-
3,31
0,0009
139,5
23,00
90,0
35,00
Proteins/Fats 2003-05 %
8,5
-2,42
0,0157
78,5
12,50
106,0
51,00
Micro nutrients
animal origin2003-05
-
3,31
0,0009
3,8
1,30
1,7
0,80
vit. ? 2003-05
16,0
1,63
0,1036
6,5
1,00
5,5
2,00
vegetal origin2003-05
14,0
-1,84
0,0661
10,3
2,90
13,3
2,40
Diversification of nutrition
Energy% 2003-05
-
3,31
0,0009
72,0
5,50
48,5
16,00
Proteins% 2003-05
-
3,31
0,0009
74,0
4,50
44,5
16,00
Fats% 2003-05 Fats%
1,5
3,15
0,0016
98,0
1,00
92,5
6,50
Table 3 of 1:
Indicators
U n-8/8
Z
p-value
Median 1
Quartile1
Median2
Quartile2
Totalmorbidity
M DALY
-
-3,31
0,0009
11167,2
1487,77
17689,7
2,159,544
M Death
-
-3,31
0,0009
591,1
94,86
951,0
119,126
F DALY
-
-3,31
0,0009
9512,7
707,08
16217,2
2,762,776
F Death
-
-3,31
0,0009
379,6
55,41
704,2
95,837
Health Rating
-
-3,31
0,0009
7,0
10,50
69,0
21,000
Access to improved medicine1990
4,0
2,72
0,0065
100,0
0,00
86,0
12,000
Access to clean water 1990
-
3,18
0,0015
100,0
0,00
79,0
13,000
air pollution Short-circuit protection of children under 5 years of age 2004
-
-3,31
0,0009
0,0
0,00
38,5
40,500
Ecological efficiency index
-
3,31
0,0009
78,1
3,47
54,6
5,930
????? 2016
-
-3,31
0,0009
8,5
12,50
95,5
30,500
Happiness Index 2016
-
3,31
0,0009
7,315
0,491
5,087
0,762
Human development index
-
3,31
0,0009
0,962
0,007
0,762
0,082
Average life expectancy
Male life expectancy
-
3,31
0,0009
76
2
71
4
Female life expectancy
1,0
3,20
0,0014
82
2
75
3
Economic and geographical factors
6
4
Of GDP ($)2008
-
3,31
0,0009
41,1
13,05
6,8
4,350
Of GDP ($) 2016
-
3,31
0,0009
147,4
71,13
11,0
14,548
lat°
-
3,31
0,0009
52,0
9,10
35,9
5,000
UV rad J/m2 2004
-
-3,31
0,0009
1674,5
241,50
3257,5
596,000
lon°
15,0
-1,73
0,0831
7,8
7,17
25,2
24,925
Frequency of diseases-person/100 thousand age-standardized population
Bladerinc
19,0
1,31
0,1893
18,1
8,70
15,6
10,200
Braininc
8,5
2,42
0,0157
6,6
1,30
3,7
2,450
Breastinc
-
3,31
0,0009
85,9
12,40
33,4
14,300
Cervixinc
20,5
1,16
0,2480
7,6
4,25
5,3
5,850
Table 3a: Analysis of the nutrition structure and cancer incidence in European and Mediterranean countries with 6 times difference in per capita income (Mann-Whitney U-test) (chronic infectious diseases and levels of consumption).
FEMALES Alcohol use disorders
-
3,31
0,0009
190,2
140,20
3,5
43,093
Epilepsdaly rates
4,0
-2,89
0,0039
61,5
8,00
82,0
49,500
Osteoarth Daly
17,0
1,52
0,1278
275,5
18,50
185,0
149,500
MAL Diabetes m
13,0
-1,94
0,0520
192,2
55,07
314,6
174,608
FEM Diabetes m
11,0
-2,15
0,0313
184,4
37,47
417,7
259,324
Endocrine dis Daly
29,0
0,26
0,7929
169,5
65,50
161,0
148,000
Cirrhosis of the liver Daly
27,0
0,47
0,6365
100,4
164,80
112,6
145,975
Poisonings Daly
28,0
-0,37
0,7132
39,5
74,11
45,1
26,719
Falls Daly
14,0
-1,84
0,0661
145,3
48,66
211,8
85,984
Respiratory infections
-
-3,31
0,0009
107,1
68,76
538,3
389,370
Drag daly rates
26,0
0,58
0,5635
157,0
105,65
112,5
145,149
Suiside death rates
-
3,31
0,0009
14,0
4,23
3,4
2,844
Suiside daly rates
1,0
3,20
0,0014
261,9
56,05
80,9
83,748
Metabolic Syndrome
Male BMI? 25 crude
21,0
1,10
0,2701
60,2
7,00
59,2
17,200
Female BMI ? 25 crude
8,5
-2,42
0,0157
48,6
6,50
60,1
12,100
Male ch ? 5.0 crude
-
3,31
0,0009
64,8
5,45
36,7
3,450
Female ch ? 5.0 crude
-
3,31
0,0009
62,3
4,15
41,4
5,650
Male glu ? 7.0 crude
30,5
-0,11
0,9164
10,0
2,40
10,2
2,400
Female glu ? 7.0 crude
7,5
-2,52
0,0117
7,2
1,90
9,7
1,950
Male AD 2 crude
6,5
2,63
0,0087
46,5
2,85
38,7
6,250
Female AD 2 crude
22,5
0,95
0,3446
37,7
5,25
36,6
6,150
Male insactcrude
14,0
-0,09
0,9247
45,1
16,20
39,5
19,850
Female insactcrude
11,0
-0,47
0,6366
44,3
10,80
44,8
13,850
CCR5 rs333+
-
-2,76
0,0058
0,890
0,032
0,979
0,047
CCR5 rs333-
-
2,85
0,0043
0,1100
0,033
0,018
0,033
%NAT2
-
0,00
10,000
43,0
13,00
39,0
0,000
level of consumption (g/person/day)
Meat, Other 2003-05
1,0
3,20
0,0014
53,0
4,00
21,5
11,500
Bovine Meat 2003-05
9
2,36
0,0181
61,00
18,50
17,00
21,000
Poultry Meat 2003-05
9,0
2,36
0,0181
48,0
25,50
30,0
9,000
Mutton&Goat Meat 2003-05
14,0
-1,84
0,0661
3,5
7,00
14,0
7,500
Pig meat 2003-05
-
3,31
0,0009
107,5
54,00
3,5
14,500
Milk, Whole 2003-05
25,0
0,68
0,4948
244,0
301,50
201,5
159,500
Milk, Skimmed 2003-05
19,0
1,31
0,1893
43,5
106,50
29,5
42,500
Eggs 2003-05
6,5
2,63
0,0087
29,0
16,00
17,5
8,000
Cheese 2003-05
1,0
3,20
0,0014
49,5
19,50
9,5
17,500
Butter, Ghee 2003-05
10,0
2,26
0,0239
8,5
6,50
4,5
3,000
Offals, Edible 2003-05
22,5
0,95
0,3446
5,5
7,00
4,5
4,000
Fats, Animals, Raw 2003-05
1,0
3,20
0,0014
12,5
9,00
1,5
2,500
Freshwater Fish 2003-05
7,0
2,57
0,0101
10,0
8,50
2,0
2,500
Demersal Fish 2003-05
5,0
2,78
0,0054
15,5
11,00
2,0
6,500
Table 3a of 1:
FEMALES Alcohol use disorders
-
3,31
0,0009
190,2
140,20
3,5
43,093
Epilepsdaly rates
4,0
-2,89
0,0039
61,5
8,00
82,0
49,500
Osteoarth Daly
17,0
1,52
0,1278
275,5
18,50
185,0
149,500
MAL Diabetes m
13,0
-1,94
0,0520
192,2
55,07
314,6
174,608
FEM Diabetes m
11,0
-2,15
0,0313
184,4
37,47
417,7
259,324
Endocrine dis Daly
29,0
0,26
0,7929
169,5
65,50
161,0
148,000
Cirrhosis of the liver Daly
27,0
0,47
0,6365
100,4
164,80
112,6
145,975
Poisonings Daly
28,0
-0,37
0,7132
39,5
74,11
45,1
26,719
Falls Daly
14,0
-1,84
0,0661
145,3
48,66
211,8
85,984
Respiratory infections
-
-3,31
0,0009
107,1
68,76
538,3
389,370
Drag daly rates
26,0
0,58
0,5635
157,0
105,65
112,5
145,149
Suiside death rates
-
3,31
0,0009
14,0
4,23
3,4
2,844
Suiside daly rates
1,0
3,20
0,0014
261,9
56,05
80,9
83,748
Metabolic Syndrome
Male BMI? 25 crude
21,0
1,10
0,2701
60,2
7,00
59,2
17,200
Female BMI ? 25 crude
8,5
-2,42
0,0157
48,6
6,50
60,1
12,100
Male ch ? 5.0 crude
-
3,31
0,0009
64,8
5,45
36,7
3,450
Female ch ? 5.0 crude
-
3,31
0,0009
62,3
4,15
41,4
5,650
Male glu ? 7.0 crude
30,5
-0,11
0,9164
10,0
2,40
10,2
2,400
Female glu ? 7.0 crude
7,5
-2,52
0,0117
7,2
1,90
9,7
1,950
Male AD 2 crude
6,5
2,63
0,0087
46,5
2,85
38,7
6,250
Female AD 2 crude
22,5
0,95
0,3446
37,7
5,25
36,6
6,150
Male insactcrude
14,0
-0,09
0,9247
45,1
16,20
39,5
19,850
Female insactcrude
11,0
-0,47
0,6366
44,3
10,80
44,8
13,850
CCR5 rs333+
-
-2,76
0,0058
0,890
0,032
0,979
0,047
CCR5 rs333-
-
2,85
0,0043
0,1100
0,033
0,018
0,033
%NAT2
-
0,00
10,000
43,0
13,00
39,0
0,000
level of consumption (g/person/day)
Meat, Other 2003-05
1,0
3,20
0,0014
53,0
4,00
21,5
11,500
Bovine Meat 2003-05
9
2,36
0,0181
61,00
18,50
17,00
21,000
Poultry Meat 2003-05
9,0
2,36
0,0181
48,0
25,50
30,0
9,000
Mutton&Goat Meat 2003-05
14,0
-1,84
0,0661
3,5
7,00
14,0
7,500
Pig meat 2003-05
-
3,31
0,0009
107,5
54,00
3,5
14,500
Milk, Whole 2003-05
25,0
0,68
0,4948
244,0
301,50
201,5
159,500
Milk, Skimmed 2003-05
19,0
1,31
0,1893
43,5
106,50
29,5
42,500
Eggs 2003-05
6,5
2,63
0,0087
29,0
16,00
17,5
8,000
Cheese 2003-05
1,0
3,20
0,0014
49,5
19,50
9,5
17,500
Butter, Ghee 2003-05
10,0
2,26
0,0239
8,5
6,50
4,5
3,000
Offals, Edible 2003-05
22,5
0,95
0,3446
5,5
7,00
4,5
4,000
Fats, Animals, Raw 2003-05
1,0
3,20
0,0014
12,5
9,00
1,5
2,500
Freshwater Fish 2003-05
7,0
2,57
0,0101
10,0
8,50
2,0
2,500
Demersal Fish 2003-05
5,0
2,78
0,0054
15,5
11,00
2,0
6,500
Table 3a of 2:
Molluscs, Other 2003-05
-
3,18
0,0015
8,00
10,00
0,00
1,000
Marine Fish, Other 2003-05
23,5
0,84
0,4008
4,0
5,50
2,0
4,000
Pelagic Fish 2003-05
16,5
1,58
0,1152
13,0
11,50
10,0
7,000
Animal products
5,0
2,78
0,0054
801,5
293,50
409,5
162,500
Fish
3,5
2,94
0,0033
62,0
23,00
21,0
18,000
% Fish
6,0
2,68
0,0074
2,5
1,01
1,0
1,070
% Animal products
7,0
2,57
0,0101
36,6
7,33
22,1
6,440
Wheat 2003-05
-
-3,31
0,0009
241,5
52,50
458,0
136,500
Rice 2003-05
24,0
-0,79
0,4309
12,0
4,50
21,5
24,000
Maize 2003-05
10,0
-1,74
0,0814
8,0
27,00
40,0
81,000
Potatoes 2003-05
11,0
2,15
0,0313
186,5
78,50
97,5
70,500
Tomatoes 2003-05
-
-3,31
0,0009
44,0
18,50
146,5
143,500
Vegetables, Other 2003-05
5,0
-2,78
0,0054
180,0
37,50
260,0
105,000
Onions 2003-05
10,0
-2,26
0,0239
18,5
18,00
44,5
30,000
Barley 2003-05
28,0
0,37
0,7132
4,0
2,50
1,5
29,500
Beans 2003-05
18,5
-1,37
0,1722
1,0
1,00
2,5
5,000
Rye 2003-05
4,0
2,27
0,0233
17,5
30,50
0,0
2,000
Nuts 2003-05
31,5
0,00
10,000
11,5
12,50
11,0
17,500
Soyabean Oil 2003-05
27,0
-0,47
0,6365
6,0
7,00
8,0
16,500
Sunflowerseed Oil 2003-05
21,5
-1,05
0,2936
3,5
5,50
6,0
9,500
Olive Oil 2003-05
23,5
-0,84
0,4008
2,0
1,50
3,5
7,000
Grain-vegetables
-
-3,31
0,0009
756,0
108,00
1221,0
153,000
Oil
10,0
-2,26
0,0239
15,0
9,00
25,5
13,000
% Oil
8,0
-2,47
0,0136
0,6
0,52
1,5
0,985
% Grain-vegetables
-
-3,31
0,0009
34,5
4,86
65,5
8,340
Oranges 2003-05
12,0
2,05
0,0406
132,0
103,00
58,5
33,500
Apples 2003-05
10,0
2,26
0,0239
79,0
72,00
35,0
16,000
Coffee 2003-05
2,0
3,10
0,0019
24,0
9,50
3,0
4,500
Honey 2003-05
11,0
2,15
0,0313
2,0
1,50
0,5
1,000
Sugar (RawEquivalent) 2003-05
8,0
2,47
0,0136
115,5
6,50
87,0
26,000
Lemons, Limes 2003-05
23,0
-0,89
0,3720
5,0
2,50
8,5
9,500
Tea 2003-05
23,5
-0,84
0,4008
1,0
2,50
2,5
4,000
Fruit drinks
1,0
3,20
0,0014
370,0
64,50
206,0
55,000
% Fruit drinks
6,0
2,68
0,0074
15,9
2,70
10,6
3,900
Beverages, Alcoholic 2003-05
1,0
3,20
0,0014
12,0
9,50
1,0
3,000
Wine 2003-05
-
3,31
0,0009
67,5
52,50
1,5
6,000
Beer 2003-05
-
3,31
0,0009
236,5
153,50
13,0
16,000
Alcoholic beverages
-
3,31
0,0009
316,5
209,00
17,5
20,500
% Alcoholic beverages
-
3,31
0,0009
14,4
7,00
1,0
0,895
Dietary patterns
The general level of consumption (g/person/day)
7,0
2,57
0,0101
2228,0
416,00
1770,0
380,000
Animal products (%)
7,0
2,57
0,0101
36,6
7,33
22,1
6,440
Grain-vegetables (%)
-
-3,31
0,0009
34,5
4,86
65,5
8,340
Fruit drinks (%)
6,0
2,68
0,0074
15,9
2,70
10,6
3,900
Alcoholic beverages (%)
-
3,31
0,0009
14,4
7,00
1,0
0,895
Table 3a of 3:
Nutrients AP
Energy %
-
3,31
0,0009
33,0
5,00
10,5
6,500
?rotein %
-
3,31
0,0009
64,0
4,50
26,5
12,500
Fat %
7,0
2,57
0,0101
60,5
3,00
31,0
7,500
Percentage composition of Energy
1,06
0,86
Carboh %
-
-3,31
0,0009
51,0
1,50
63,0
11,500
Proteins %
13,0
1,94
0,0520
12,5
1,0
11,0
0,500
Fats %
-
3,31
0,0009
37,0
3,00
26,0
10,500
T?tal Energy 100%
??????? (????/???/????) 1990-92
11,5
1,85
0,0641
3310,0
330,00
3000,0
330,000
Energy (kcal/person/day) 2003-05
8,5
2,42
0,0157
3420,0
370,00
3175,0
250,000
Proteins (g/person/day) 2003-05
3,0
2,99
0,0028
107,0
8,00
89,0
9,000
Fats (g/person/day) 2003-05
-
3,31
0,0009
139,5
23,00
90,0
35,000
Proteins/Fats 2003-05 %
8,5
-2,42
0,0157
78,5
12,50
106,0
51,000
Micro nutrients
Animal origin 2003-05
-
3,31
0,0009
3,8
1,30
1,7
0,800
Vit. ? 2003-05
16,0
1,63
0,1036
6,5
1,00
5,5
2,000
Vegetal origin 2003-05
14,0
-1,84
0,0661
10,3
2,90
13,3
2,400
Diversification of nutrition
Energy% 2003-05
-
3,31
0,0009
72,0
5,50
48,5
16,000
Proteins% 2003-05
-
3,31
0,0009
74,0
4,50
44,5
16,000
Fats% 2003-05 Fats%
1,5
3,15
0,0016
98,0
1,00
92,5
6,500
Smoking
M Daily Age
22,0
-1,00
0,3184
27,3
11,10
32,4
17,900
F Daily Age
-
3,18
0,0015
23,9
9,20
1,0
6,800
Table 3a of 4:
Cancer incidence: In Euro3 countries, the overall incidence was 1.5 times lower than in Med3 countries (p=0.001). In Euro3 countries, life expectancy was 6 years higher than in Med3 countries (p=0.001). In Euro3 countries, the incidence of 14 cancer types out of 24 was 2.7 times higher than in Med3 countries (Brain, Breast, Colorect, Corpus ut, Kidney, Leukaemia, Lip oral, Melanoma, Oesophar, Ovary, Pancreas, Prostate, Testis, Thyroid) (p=0.001). The incidence of 2 cancer types out of 24 was twice higher in Med3 countries (Laryngx, Nasophar) (p=0.03). The incidence of 8 cancer types out of 24 do not differ between countries (Blader, Cervix, Gollblad, Hodgkin l, Kaposi s, Liver, Lung, Stomach) (p=0.9).
In Euro3 countries, the proportion of men and women with a blood cholesterol level> 5.0 (p=0.001) was 1.5 times higher. In Euro3 and Med3 countries, more than 60% of the population had BMI> 25. More than 40% had arterial pressure> 140/90mmHg; and there were more than 40% of the population in Euro3 and Med3 countries with low physical activity.
The nutrition structure: The nutrition structure of Euro3 countries with high per capita income had 36.6% and 22.1% of animal products (p=0.01) compared to Med3 countries with low per capita income; 34.5% and 65.5% of grain and vegetables (p=0.001); 14.4% and 1.0% (p=0.001) of alcoholic beverages; 15.9% and 10.6% (p=0.007) of fruit and drinks. The food consumption level in Euro3 countries was 1.4 times higher than in Med3 countries (p=0.01). The level of Energy in Euro3 countries was 1.07 times higher than in Med3 countries (p=0.01), Proteins was 1.2 times and Fats was 2.6 times higher than in Med3 countries (p=0.01). The level of macronutrients of animal products: Energy and Proteins were 3 times higher (p = 0.001), Fats was 2 times higher (p=0.01) in Euro3. Diversification of the nutrition structure in Euro3 countries was 1.7 times higher than the Med3 countries (p=0.001).
Thus, one can conclude with a reasonable certainty that in 3 groups of Euro countries with a 2, 4 and 6 times higher per capita income than that of Med countries, incidence of 12-14 almost the same cancer types increases almost dose-dependent in 1.7, 2.3 and 2.5 times. The incidence of 12-10 cancer types does not change in response to an increase in per capita income. We hypothesized that these 12-10 cancer types may depend on the latitude and the factors associated with it. To test this hypothesis, we selected from European and Mediterranean countries 44 countries with the same per capita income as in 22 European and Mediterranean(EM1) and 22 (EM2) countries.
However, the latitude of EM1 and EM2 countries differs statistically significant (p=0.001). We assumed that the influence of per capita income was fixed.
Analysis of the nutrition structure and cancer incidence in European and Mediterranean countries with the same income, but located in different latitudes
Per capita income in EM1 and EM12 countries was statistically the same (p=0.64) and amount $20 (QR 24.6) in Euro4 and $27 (QR 26.2) in Med4 countries. The latitudes of EM1 countries were statistically different from those of EM2 countries (p = 0.001)/ In EM1 it was 52° (QR 7.0°), in EM2 it was 40° (QR 11.0°) (Table 4).
Indicator
U n-22/22
Z
p-value
Median 1
Quartile 1
Median 2
Quartile2
Totalmorbidity
Male - general morbidity (DALY - person/100 thousand) standardized by age
186
1,30
0,1927
15065,6
9327,84
12520,8
6470,05
Female - general morbidity (DALY - person/100 thousand) standardized by age
209
0,76
0,4455
10933,2
3000,70
10055,6
5497,18
Human development index
235
0,15
0,8787
0,9
0,13
0,9
0,15
Health Rating
217
- 0,58
0,5652
35,5
28,00
31,5
47,00
Happiness Index 2016
200
0,97
0,3300
5,8
1,51
5,7
1,75
Ecological efficiency index
216
0,35
0,7246
69,1
14,69
66,8
21,52
Average life expectancy
Male life expectancy
191
- 1,20
0,2313
72,8
6,30
75,0
6,10
Female life expectancy
211
- 0,72
0,4740
79,6
3,40
80,6
6,90
Economic and geographical factors
Of GDP ($)2008 - per capita income
242
0,01
0,9906
20,2
21,60
26,6
21,60
lat° - geographical latitude
69
4,05
0,0001
52,3
7,30
39,8
10,80
Frequency of cancer diseases - person/100 thousand age-standardized population
Blader
190
1,21
0,2267
16,4
3,70
15,6
5,10
Brain
178
1,49
0,1361
6,6
3,00
6,5
2,30
Breast
206
0,85
0,3981
56,8
38,00
60,5
39,70
Cervix
154
2,05
0,0400
10,3
6,70
6,3
6,70
Colorect
187
1,29
0,1967
33,4
14,50
31,5
28,00
Corpusut
134
2,52
0,0116
13,2
4,40
10,9
6,90
Gollblad
190
1,21
0,2267
1,6
0,80
1,5
0,70
Hodgkin l
236
0,14
0,8880
2,3
0,90
2,3
0,80
Kaposi s
242
- 0,01
0,9906
0,0
0,00
0,0
0,00
Kidney
88
3,60
0,0003
11,6
6,20
6,2
6,00
Laryngx
196
1,08
0,2803
6,7
4,10
5,3
2,90
Leukaemia
134
2,52
0,0116
8,4
1,90
7,3
4,00
Liporal
139
2,42
0,0156
7,2
3,10
4,9
4,00
Liver
231
- 0,25
0,8053
4,1
2,60
3,9
5,80
Lung
115
2,97
0,0030
52,2
16,90
36,4
23,20
Melanoma
157
1,98
0,0473
8,2
6,80
3,5
9,90
Nasophar
144
- 2,30
0,0214
0,5
0,20
1,0
0,90
Oesophar
115
2,98
0,0029
5,4
2,60
2,9
3,80
Ovary
118
2,91
0,0036
11,2
3,60
8,3
5,30
Pancreas
137
2,45
0,0142
8,7
3,10
7,0
4,50
Prostate
178
1,49
0,1361
53,7
53,60
48,5
50,00
Stomach
142
2,35
0,0189
12,5
13,40
8,9
9,00
Testis
185
1,34
0,1809
5,4
5,10
3,4
6,00
Thyroid
192
1,16
0,2453
1,9
1,20
1,3
2,40
Allcancer
143
2,31
0,0208
301,2
56,20
243,1
166,90
Metabolic Syndrome
Male BMI>25 (kg/m2) - body mass index
213
0,67
0,5035
63,4
6,10
61,1
7,30
Female BMI>25 (kg/m2) - body mass index
205
- 0,86
0,3916
53,7
7,60
55,4
9,30
Male ch> 5.0 (mmol/L) - blood cholesterol level
199
1,00
0,3185
55,7
13,80
54,7
25,80
Female ch>5.0 (mmol/L) - blood cholesterol level
176
1,54
0,1242
56,9
10,40
55,8
18,70
Male glu>7.0 (mmol/L) - blood glucose level
206
0,85
0,3981
10,9
1,50
10,7
2,50
Female glu>7.0 (mmol/L) - blood glucose level
207
0,81
0,4181
9,7
2,90
9,8
3,00
Male AD>140/90 (mmHg) - level of arterial blood pressure
105
3,22
0,0013
50,5
7,20
45,5
8,90
Female AD>140/90 (mmHg) - level of arterial blood pressure
123
2,79
0,0052
46,8
11,40
39,1
7,20
Male insact<60 minutes/day walking - low physical activity
102
- 1,87
0,0615
29,2
20,50
45,1
18,50
Female insact<60 minutes/day walking - low physical activity
77
- 2,66
0,0078
31,1
19,60
47,9
19,60
Table 4: Analysis of the nutrition structure and cancer incidence in European and Mediterranean countries with the same income, but located in different latitudes (Mann-Whitney U-test).
Dietary patterns
The general level of consumption (g/person/day)
238
0,09
0,9252
2176,0
152,00
2143,5
654,00
Animal products (%)
168
1,73
0,0845
33,9
9,06
30,2
11,82
Grain-vegetables (%)
172
- 1,63
0,1028
41,3
14,44
49,7
28,79
Fruit drinks (%)
210
- 0,74
0,4597
11,2
4,50
11,6
3,60
Alcoholic beverages (%)
155
2,03
0,0423
11,9
6,25
8,5
12,31
Macro nutrients
Nutrients Animal products
Energy %
162
1,88
0,0604
28,0
8,00
25,0
18,00
?rotein %
194
1,13
0,2599
57,0
12,00
53,5
32,00
Fat %
108
3,13
0,0017
58,0
8,00
43,5
26,00
Percentage composition of Energy
Carboh %
241
0,02
0,9813
56,0
8,00
54,0
11,00
Proteins %
228
- 0,33
0,7424
12,0
2,00
12,0
2,00
Fats %
239
- 0,06
0,9532
33,5
6,00
33,5
10,00
T?tal Energy 100%
Energy (kcal/person/day)2003-05
134
- 2,52
0,0116
3140,0
450,00
3370,0
410,00
Proteins (g/person/day) 2003-05
172
- 1,64
0,1004
96,0
18,00
103,0
24,00
Fats (g/person/day) 2003-05
203
- 0,92
0,3600
115,0
30,00
131,5
48,00
Proteins/Fats 2003-05 %
234
- 0,18
0,8603
81,5
15,00
79,0
26,00
Micro nutrients
animal origin2003-05
227
- 0,35
0,7248
3,1
0,80
3,5
2,60
vit. ? 2003-05
163
1,85
0,0637
6,5
1,00
6,0
2,00
vegetal origin2003-05
80
- 3,79
0,0002
9,4
1,30
12,3
2,60
Diversification of nutrition
Energy% 2003-05
196
1,08
0,2803
66,0
13,00
64,0
16,00
Proteins% 2003-05
209
0,77
0,4386
66,5
11,00
67,5
24,00
Fats% 2003-05 Fats%
200
0,97
0,3300
96,0
3,00
95,0
4,00
Table 4 of 1:
Social characteristics: the social indicators of EM1 and EM2 countries did not differ (p=0.9). The total incidence, life expectancy (p=0.9) did not differ between countries.
Cancer incidence: In EM1 countries with the same per capita income but located in different latitudes, the incidence of 12 cancer types out of 24 was 1.5 times higher than in Med4 countries (p=0.001) (Cervix, Corpus ut, Kidney, Lung, Leukaemia, Lip oral, Melanoma, Oesophar, Ovary, Pancreas, Stomach, Nasophar). The incidence of 12 cancer types out of 24 in EM1 countries did not differ from the incidence of these cancers in EM2 countries (p=0.4) (Blader, Brain, Breast, Colorect, Gollblad, Hodgkin L, Kaposi s, Laryngx, Liver, Prostate, Testis, Thyroid) (Table 4).
Comparing the results of stages 2 and 4, it was noted that incidence of 7 cancer types in EM1 countries (Corpus ut, Kidney, Leukaemia, Lip oral, Melanoma, Ovary, Pancreas) depends on per capita income and latitude. In EM1 countries, incidence of 5 cancer types depends on “clear” per capita income (Brain, Breast, Colorect, Prostate, Testis). The incidence of 5 cancer types depends on the “clear” latitude (Cervix, Lung, Nasophar, Oesophar, Stomach). Incidence of 7 cancer types in EM1 and EM2 countries does not depend on per capita income and latitude (Blader, Hodgkin L, Kaposi s, Gollblad, Laryngx, Liver, Thyroid) (Table 5).
24 types of cancer per capita income - 3.2. stage geographical latitude - 3.4. stage
percapitaincome - 3.2. stage
geographicallatitude - 3.4. stage
Corpusut
3,31
0,0009
2,52
0,011626
Kidney
2,78
0,0054
3,60
0,000315
Leukaemia
2,89
0,0039
2,52
0,011626
Liporal
2,00
0,0460
2,42
0,015620
Melanoma
2,99
0,0028
1,98
0,047319
Ovary
2,84
0,0046
2,91
0,003608
Pancreas 7
2,47
0,0136
2,45
0,014172
Brain
2,26
0,0239
1,49
0,136091
Breast
3,10
0,0019
0,85
0,398103
Colorect
3,31
0,0009
1,29
0,196707
Prostate
3,10
0,0019
1,49
0,136091
Testis 5
3,10
0,0019
1,34
0,180917
Cervix
0,11
0,9164
2,05
0,039991
Lung
1,94
0,0520
2,97
0,002985
Nasophar
-1,79
0,0742
- 2,30
0,021431
Oesophar
1,26
0,2076
2,98
0,002873
Stomach 5
1,42
0,1563
2,35
0,018913
Blader
1,10
0,2701
1,21
0,226725
Gollblad
1,47
0,1415
1,21
0,226725
Hodgkin l
1,52
0,1278
0,14
0,888000
Kaposi s
-0,05
0,9581
- 0,01
0,990636
Laryngx
0,32
0,7527
1,08
0,280258
Liver
1,73
0,0831
- 0,25
0,805324
Thyroid 7
1,47
0,1415
1,16
0,245279
Allcancer
3,10
0,0019
2,31
0,020775
Table 5: The impact of per capita income and geographical latitude on the frequency of 24 types of cancer in Euro and Med countries (summary table) (Mann-Whitney U-test).
In EM1 countries, there are 1.5 times more men and women (>50%) with arterial pressure >140/90 (p = 0.001). In Med4 countries, there are 1.5 times (>50%) more women with low physical activity (p=0.02).
The nutrition structure: The nutrition structure differed little between EM1 and EM2 countries. The shares of animal products, grains and vegetables, fruit and drinks were not statistically different in EM1 and EM2 countries (p=0.1). The share of alcoholic beverages was 2 times higher in EM1 countries than in EM2 countries (p=0.005).
Levels of total macronutrients: Energy, Proteins and Fats did not have statistical differences in EM1 and EM2 countries (p=0.9). However, the level of fat of animal products macronutrients was 1.5 times higher in EM1 countries (p=0.005).
Discussion of the Results
We estimated the impact of per capita income and latitude on social characteristics, the incidence of 24 cancer types, predictors of the Metabolic Syndrome and the nutrition structure, including macronutrients, in the Euro and Med countries. It was done in order to answer the question: what is the advantage of Mediterranean diet, thanks to which the incidence of breast cancer in Mediterranean countries is lower than in other countries?
In Euro countries, at 3 stages of research, per capita income was 2, 4 and 6 times higher than in Med countries. Latitude at the 2nd stage of the study did not differ between Euro and Med countries (Table 2). Therefore, we could compare oncological morbidity in Euro and Med countries under the influence of the gradient of per capita income, regardless of the influence of latitude. At 4th stage, Euro and Med countries had the same per capita income, but differed in latitude. In this case, we could evaluate the effect of “clear” latitude, i.e. regardless of per capita income. Earlier it was shown that per capita income, food consumption levels and cancer incidence in different countries are positively correlated with latitude (r=0.8) [4,5,11,12]. In [12] Grant W.B. noted that some cancer types are more correlated with food than with latitude.
In addition, it was found that per capita income is a factor of racial-ethnic inequality in access to monitoring, diagnosis, prevention and treatment of cancer. The authors show that in countries with low per capita incomes, the actual cancer incidence can be higher [31-35]. At the same time, positive association of oncological morbidity and certain cancer types with the Human Development Index has been established [36]. It is well known that per capita income is included in the evaluation system of the Human Development Index, the higher is the per capita income the higher is the Human Development Index. Therefore, stages 2 and 4 of our study were conducted to assess the contribution of the “clear” per capita income factors and latitude to the differences in cancer incidence and nutrition structures in Euro and Med countries.
Influence of per capita income and latitude on the cancer incidence in Euro and Med countries
In Euro countries, social characteristics and living standards are higher, the higher per capita income in these countries is. In Euro countries with high per capita income, the overall incidence is lower than in Med countries. Life expectancy in Euro countries is 6 years higher than in Med countries.
The first paradox: In Euro countries in comparison with Med countries, the overall oncological incidence is higher and increases dose-dependent on per capita income at 1.7, 2.2, 2.5 times, respectively, with the growth of per capita income in Euro countries in 2, 4 and 6 times.
The second paradox: In Euro countries, the dose-related growth of oncological morbidity affects 12 cancer types (Tables 1-3). The incidence of the other 12 cancer types does not depend on the growth of per capita income in Euro countries (Tables 1-3). We hypothesized that this cancer group depends on the latitude gradient between Euro and Mediterranean countries. To this end in view, the 2nd and 4th stages of research were carried out. As a result of the 2nd stage, in Euro countries with 4 times higher per capita income than in Med countries, there were 2-5 times higher incidence of 12 cancer types out of 24 (Brain, Breast, Colorect, Corpus ut, Kidney, Leukaemia, Lip oral, Melanoma, Ovary, Pancreas, Prostate, Testis) (p=0.01). The incidence of the remaining 12 cancer types did not differ between countries (Blader, Cervix, Gollblad, Hodgkin L, Kaposi s, Laryngx, Liver, Lung, Nasophar, Oesophar, Stomach, Thyroid) (p=0.5).
At the 4th stage, the EM1 and EM2 countries were compared, in which per capita income was the same ($23) (p=0.7), and the latitude differed by 12° (p=0.001) (Table 4). As a result, it was found that the incidence of the 12 cancer types in EM1 countries differed from those of EM2 countries (p=0.001) (Cervix, Corpus ut, Kidney, Lung, Leukaemia, Lip oral, Melanoma, Oesophar, Ovary, Pancreas, Stomach, Nasophar) (Table 4). The incidence of 12 cancer types in EM1 countries did not differ from that in EM2 countries (p=0.5) (Brain, Blader, Breast, Gollblad, Colorect, Laryngx, Liver, Hodgkin L, Kaposi s, Prostate, Testis, Thyroid) (Table 4).
Comparing the results of stages 2 and 4 it was noted that 7 cancer types (Corpus ut, Kidney, Leukaemia, Lip oral, Melanoma, Ovary, Pancreas) in Euro countries depend on per capita income and latitude. In Euro countries, the incidence of 5 cancer types depends on “clean” per capita income (Brain Breast, Colorect, Prostate, Testis). The incidence of 5 cancer types depends on “clean” latitude (Cervix, Lung, Nasophar, Oesophar, Stomach). The incidence of 7 cancer types in Euro and Mediterranean countries does not depend on per capita income, nor on latitude (Blader, Hodgkin l, Kaposi s, Gollblad, Laryngx, Liver, Thyroid), of which 3 types are associated with viral infections (Hodgkin L, Kaposi s, Liver ) [4,12].
Anisimov V.N et al [37] using multiple regression analysis and prognosis have shown that the incidence of hormone-dependent tumors in countries depends on per capita income, while tumors of the gastrointestinal tract are associated with latitude. Chetty R et al [38] in studies on US residents have found that a person’s life expectancy depends on per capita income that has a threshold, after which the life expectancy does not increase. Our results confirm the data of these authors on the dependence of life expectancy on per capita income.
The influence of per capita income and latitude on the Metabolic Syndrome
In studies in Euro and Med countries, a blood cholesterol level >5.0mmol/L (the predictor of the metabolic syndrome) depends on per capita income. The proportion of men with high blood cholesterol levels in Euro countries in comparison with Med countries increased by 1.3-1.8 times, respectively (p=0.001). The proportion of women with cholesterol level >5.0mmol/L in Euro countries was lower than that of men and increased by 1.3-1.5 times, respectively, with per capita income (p=0.001). BMI >25kg/m2 in populations of Euro and Med countries exceeded 60% of the population, did not differ statistically between Euro and Med countries, and did not depend on per capita income (p=0.1). At the same time, a blood pressure >140/90mmHg was 1.5 times more frequent in the populations of Euro countries in high latitudes than in countries in low latitudes (p=0.001) and accounted for more than 50% of the populations of men and women in Euro countries. In the researchers’ opinion, the predictors of metabolic syndrome can serve as reliable diagnostic and prognostic indicators of breast cancer, prostate cancer, colorectal cancer and other cancer types [39-44].
Influence of per capita income and latitude on the nutrition structure
On the basis of the data obtained, it can be assumed that the increase of the incidence of 12 cancer types with an increase of per capita income in Euro countries compared to Med countries is associated with the characteristic differences in the nutrition structure of Euro and Med countries.
With an increase in per capita income by 2, 4 and 6 times, the level of food consumption in Euro countries grows by 1.01, 1.1, 1.26 times in comparison with Med countries (p=0.001).
In the nutrition structure, with an increase in per capita income in Euro countries, the share of animal products is growing by 1.3, 1.5, 1.7 times (p=0.001); the share of grain and vegetables decreases to 0.7, 0.5, 0.5 (p=0.001); and the share of alcoholic beverages increases dramatically: by 5.2, 8.0, 14.3 times (p=0.001). The share of fruits and drinks is increasing in Euro countries: by 1.1, 1.2, 1.5 times (p=0.01). An increase in the overall level of food consumption, as well as an increase in the share of animal products and alcoholic beverages, as well as a decrease in the share of grain and vegetables in the Nutrition structure, apparently leads to an increase in the incidence of 12-15 cancer types by 1, 7, 2.3, 2.5 times (p=0.001). In this case, the incidence of Breast cancer grows 2.6 times, Colorect, Corpus ut, Kidney - 3.7 times, Oesophar - 4.7 times, Prostate - 8.1 times, Testis - 12.1 times, Melanoma - 28.5 times (p=0.001). But the incidence of 12 cancer types is statistically unchanged (p=0.5) in Euro countries and does not differ from the incidence of these cancer types in Med countries. We assume that the incidence of these cancer types does not depend on the nutrition structure, since these cancer types do not depend on per capita income (Table 2). At the research stage 3.4, we found that in countries with the same per capita income located in high and low latitudes, the nutrition structure does not depend on latitude, except for the share of alcoholic beverages, which is 2.2 times higher in high latitudes (p=0.005). At the same time, the nutrition structure in high and low latitudes contains a significant proportion of animal products - 32% and 29% (p=0.5), and 43% and 53% (p=005) of grain and vegetables. It confirms our data that the cancer incidence that is independent of per capita income, but dependent on latitude, is associated with practically the same diet in high and low latitudes.
Most authors agree on the favorable effect of diets with low share of red meat, well or ultra processed red meat and alcohol, with high share of vegetables, grains, nuts, unsaturated fatty acids, and with a high anti-inflammatory index [45-52]. Loo RL et all believe that the interpersonal variation in the response to a diet is common, but the main mechanism of such a response is not clear [46].
The nutrition structure of Euro countries with 2 times higher per capita income that in Med countries, contains: animal products - 35.7% and 26.7% (p=0.002); grains and vegetables - 36.5% and 56.2% (p=0.001); alcoholic beverages - 13.6% and 2.5% (p=0.001); fruit and drinks - 13.2% and 11.6% (p=0.08).
Influence of per capita income and latitude on the level of macronutrients in Euro and Med countries
With the increase in per capita income in Euro countries in comparison with the Mediterranean countries by 2, 4 and 6 times, the level of common macronutrients changed: the Energy level grew by 1.01-1.08 times and was 3420 (QR=370) - 3170 (QR=250)kcal/person/ day (p=0.01); Carbohydrate level decreased by 1.2 times (p=0.001); the level of Proteins was constant; the level of Fats increased by 1.2- 1.4 times (p=0.001).
In Euro countries with 2, 4, 6 times higher per capita income than in Med countries, the level of macronutrients of animal products increased: Energy by 1.5-2.9 times (p=0.001); Proteins by 1.2 to 2.4 times (p=0.001); Fats by 1.6-1.9 times (p=0.01).
Thus, the “Energy Cocktail” of Euro countries (3,420kcal) and Med countries (3,170kcal) with a 6-fold difference in per capita income between these countries, contains a different ratio of the calories of animal and vegetable origin, including 14-fold difference in calories from alcoholic beverages in total Energy, Proteins, Fats and Carbohydrates, in Euro countries in comparison with Mediterranean countries. It can be assumed that the specific differences in the nutrition structure, general macronutrients and macronutrients from animal products underlie the high incidence of 12 cancer types in Euro countries. The location of Euro countries in higher latitudes than Med countries, also contributes to the high cancer incidence in Euro countries, partly of these 12 types. Our results on the role of nutrition structures with a high content of animal products and alcoholic beverages as a cancer risk factor support the results of many researchers on the beneficial, anti-inflammatory, immunoprotective effect of the Mediterranean diet [53-57]. A decrease in cognitive functions due to the high proportion of Fats and Proteins in total Energy to the detriment of Carbohydrates is reported [58]. Lane JA et all did not confirm the connection of dietary factors with the risk of prostate cancer, including the stage of the disease [59]. Holmberg L1, et all believe that the strongest known risk factors for many cancers are age and ethnic origin [60].
Conclusions
1. In European countries, compared with the Med countries, the incidence of 7 cancer types (Corpus ut, Kidney, Leukaemia, Lip oral, Melanoma, Ovary, Pancreas) in Euro countries depend on per capita income and latitude. In Euro countries, the incidence of 5 cancer types depends on “clean” per capita income (Brain Breast, Colorect, Prostate, Testis). The incidence of 5 cancer types depends on “clean” latitude (Cervix, Lung, Nasophar, Oesophar, Stomach). The incidence of 7 cancer types in Euro and Mediterranean countries does not depend on per capita income, nor on latitude (Blader, Hodgkin L, Kaposi s, Gollblad, Laryngx, Liver, Thyroid), of which 3 types are associated with viral infections (Hodgkin l, Kaposi s, Liver ).
2. In European and Mediterranean countries, the nutrition structure and the composition of macronutrients of animal products depend on per capita income and do not depend on latitude.
3. In European countries, the nutrition structure with a high proportion of animal products (> 30%) and alcoholic beverages (>6%) is a risk factor for 12 cancer types out of 24 (Brain, Colorect, Corpus ut, Kidney, Lip oral, Melanoma, Ovary, Pancreas, Breast, Leukaemia, Prostate, Testis).
Additional Materials
1. Analysis of the daily diet in Euro and Med countries with 6 times difference in per capita income (Table 3a).
In European countries, higher consumption of the following products (g/person/day): total consumption is 1.3 times higher, Bovine Meat- 3.6 times, Poultry Meat - 1.5 times, Pig meat - 40 times, Cheese - 5.1 times, Butter, Ghee -1.9 times, Eggs - 1.7 times, Fats, Animals - 8 times, Freshwater Fish - 5 times, Demersal Fish - 7.7 times, Molluscs- 8 times, Potatoes - 1.9 times, Rye - 1.8 times, Oranges - 2.2 times, Apples - 2.2 times, Coffee - 8 times, Honey - 4 times Sugar -1,3 times, Beverages, Alcoholic -12 times, Wine - 45 times, Beer - 18 times.
In Euro consumption of these food products is lower than in Med countries: Wheat - 2 times, Tomatoes - 3 times, Onions - 1.4 times, Vegetables, Other - 1.3 times.
There are no differences between Euro and Med countries in consumption of: Mutton & Goat Meat, Offals, Edible, Milk, Whole, Milk, Skimmed, Marine Fish, Other, Pelagic Fish, Rice, Maize, Barley, Beans, Nuts, Soyabean Oil, SunflowerseedOil , Olive Oil, Lemons, Lime Tea.
Table 3a provides data on the incidence of 50 types of NCD and 53 types of food.
Country Lists
Stage
Euro: Luxembourg, Norway, Ireland, The Netherlands, Switzerland, Austria, Sweden, Denmark, Finland, Belgium, United Kingdom, Germany, Iceland, Slovenia, Czech Republic, Slovakia.
Med: Albania, Algeria,Cyprus, Egypt, France, Greece, Israel, Italy, Lebanon, Libya, Malta, Morocco, Spain, Syrian Arab Republic, Tunisia, Turkey.
Stage
Euro: Spain, Greece, France, Italy, Cyprus, Israel, Malta, Croatia.
Med: Turkey, Lebanon, Tunisia, Algeria, Albania, Egypt, Syrian Arab Republi, Morocco.
Stage
Euro: Luxembourg, Norway, Ireland, The Netherlands, Switzerland, Austria, Sweden, Denmark.
Med: Turkey, Lebanon, Tunisia, Algeria, Albania, Egypt, Syrian Arab Republic, Morocco.
Stage
EM1: Russian Federation, Belarus, Estonia, Latvia, Lithuania, Lebanon, Ukraine, Albania, Serbia, Finland, Belgium, The Netherlands, Denmark, Czech Republic, Slovakia, Germany, Croatia, Poland, France.
EM2: Slovenia, Malta, Egypt, Morocco, Syrian Arab Republic, Israel, Austria, Switzerland, Norway, Luxembourg, Ireland, Spain, Greece, Romania, Italy, Bulgaria, Portugal, Turkey, Algeria, Tunisia, Libya, Cyprus.
Information on the Financing
Center of Theoretical Problems of Physico-Chemical Pharmacology RAS.
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