Food Effect on Diabetes

 
 

 

 

C O N T E N T S

1. Study Basis and Approach

2. Conclusions

3. Food vs. Diabetes Graphics

 

4. Complementary Graphics

 

5. Appendix

 

 

 

Study Basis and Approach

  • To evaluate the effect that different kind of food has on Diabetes, we used the statistic information of 106 to 127 countries, plotting on XY graphics food type consumption versus Diabetes Crude Prevalence.

 

  • The source to calculate the Crude Diabetes Prevalence (all ages) is WHO statistics “Prevalence of Diabetes Worldwide” for the year 2000. To do so, we divided the total prevalence of each country between its total population (all ages), and expressed in percentage. We are aware however, that Age Standardized Prevalence Rate would be the ideal data to be used.

 

  • As weather temperature has an important influence on diabetes, we classify countries in four categories: Cold (C), Medium Cold (MC), Temperate (T), and Hot (H). The classification is a subjective estimation based on “World Atlas” web page data.

 

  • The source used for Food Consumption (expressed on Calories) is FAO (Food and Agriculture Organization).

 

  • South African countries are not considered on the study because their prevalence level of AIDS affects the Diabetes Prevalence Statistics. From the 153 countries considered in the original tables we end up with 127 countries. When considering Not Cold Countries (NCC) the list is only of 106 countries.

 

  • The study considers 16 XY graphics relating Food Consumption with Diabetes Prevalence Rate. Food Consumption is expressed in Calories per person per day. The study includes an Evaluation Table that uses some parameters to compare the quality of the graphics.

 

  • Additional to the mentioned Food vs. Diabetes graphics, 8 other complementary graphics are included to express particular ideas related with Diabetes causes.

 

  • Using as base reference the food graphic with the biggest influence on Diabetes (Animal plus Sugar Consumption) there is a table of countries with diabetes values too high or too low with respect to the graphic. The idea is to identify the countries with unknown factors that are affecting in a positive or negative way the Diabetes Rate (see table P2-10b in appendix).

 

 

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C o n c l u s i o n s

1.-

Main cause of Diabetes in this study is related with the amount of Calories we give to our body from food, minus the energy we spend. In other words, the biggest the amount of calories we keep, the highest are the chances for Diabetes.

 

2.-

But not all the food calories have the same effect. Animal source and Sugar are the type of Calories with the highest negative effect on diabetes prevalence (see graphics P2-40 and P2-75).

 

3.-

We found no conclusion of the effect of alcohol Calories (see graphic P2-82).

 

4.-

Fat and Vegetable Oils Calories does not show an important effect on Diabetes (see graphic P2-43).

 

5.-

Calories from Vegetal food does not show any positive or negative effect on Diabetes (see graphic P2-76).

 

6.-

IIn spite of the high food energy consumption on cold countries, Diabetes prevalence is not high. This can be explained as a good part of these Calories are used or spend by the body to keep it warm (see graphic P2-88).

 

7.-

Most cold countries have high health expenditures and some relatively low diabetes rates (in spite of their high energy consumption). On graphic P2-86 we made a comparison of diabetes prevalence among cold and not cold wealthy countries. The graphic demonstrate that is the cold weather what reduces diabetes prevalence and not the health care.

 

8.-

The influence of the type of food calories is even bigger than the temperature effect as it is shown on graphic P2-89 where we compare the diabetes prevalence on two groups of countries: The biggest vegetal eaters against the biggest animal and sugar eaters. In the second group, in spite that more than half of the countries are cold or medium cold, their diabetes prevalence is much bigger than for the vegetal eaters.

 

9.-

We were not able to demonstrate the relationship between Obesity and Diabetes (see graphic P2-98).

 

 

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Food vs. Diabetes Graphics

Evaluation Table

16 Graphics

Comments of Graphics

 

 

 

Table P2-11a  Food Consumption vs. Diabetes

Evaluation of Graphics

GRAPHIC   NUMBER    P2-

FOOD  CONSUMPTION

DISPERSION      (1)

TOTAL  INCREMENT   (2)

SMOOTHNESS EVALUATION   (3)

GRAPHIC  EVALUATION  (PLACE)            (4) (6)

40

Total Calories

1.31

3.4

F

4

43

Total Oils

1.52

2.3

NC

none

45

Oils and Sugar

1.41

2.1

NC

none

50

Total Calories (NCC)  (5)

1.35

3.6

G

3

51

Animal and Sugar

1.29

2

R

11

55

Meat, Milk and Sugar

1.33

2.5

R

9

75

Animal and Sugar (NCC)

1.32

3.7

VG

1

76

Total Vegetal

1.53

1.1

NC

none

77

Vegetal But Sugar

1.61

-0.5

NC

none

78

Sugar

1.37

3.3

F

5

79

Meat, Milk and Sugar (NCC)

1.29

3.5

R

8

80

Total Animal

1.17

1.5

R

12

81

Total Animal (NCC)

1.33

3.7

G

2

82

Sugar and Alcohol Beverages

1.36

2.6

R

10

83

Sugar and Alcohol Bev. (NCC)

1.40

3.4

F

6

 84

Sugar (NCC)

1.4

3.4

R

7

 

NOTES:

(1) Graphics are made with 10 points each representing the average of a group of countries

      (from 10 to 13). Dispersion indicate how faraway (bigger or smaller) are the countries´

      individual values from the group average value. To evaluate Dispersion we use the Standard

      Deviation of each group and then we average the ten values.

(2) Total Increment is the difference of the Diabetes Prevalence value of group 10 minus the

      value of group 1

(3) This is a visual (subjective) evaluation of the smoothness. Because we consider a linear

      effect of the food consumption on the disease, perfect curve would be a straight line.  NC

     means Not Conclusive. R means Regular. F means Fair. G means Good. VG means Very Good.

(4) Base on values of Dispersion, Total Increment and Smoothness, we give a final evaluation for

     each graphic, where 1 would be the more conclusive graphic and the biggest number the less

     conclusive. None means we see no relationship between food consumption and Diabetes.

(5) (NCC) means Not Cold Countries. The reason of these graphics is because there is a direct

      direct relationship between the amount of energy we keep and Diabetes. The energy (Calories)

      we keep are the energy we eat minus the energy we spend. In cold countries the body spends 

       a big part of his energy in keeping it warm.

(6) Fromgraphics placed 1 to 5 we can observe that main cause of Diabetes is the energy

      we take from food and we do not spend. Also the type of food has a grate influence as

      we may see in graphic P2-76 where Vegetal food has no influence in the disease. On the

      other hand in graphic P2-75 (placed 1) we see that Animal food and Sugar have a very

          negative effect on Diabetes Prevalence.

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Comments of Food vs. Diabetes Graphics

P2-40 Total Calories: Amount of food energy show a clear influence on Diabetes, but curve is not smooth because this is not the only cause.
P2-43 Total Fat and Vegetal Oil. We don’t see a clear effect of oil consumption on diabetes.
P2-45 Oil and Sugar. We see a relationship only in the first 3 groups where energy is low and Diabetes is under 2. In the rest of the groups there is no effect of oils and sugar on Diabetes.
P2-50 Total Energy in Not Cold Countries. In this graphic we can see another condition for Diabetes that we could not see on graphic P2-40. The Energy that causes Diabetes is not actually the Calories we eat but the Calories we keep. Cold countries are calories eaters but the levels of diabetes are not high because the body spends part of the energy to keep it warm.
P2-51 Animal and Sugar Energy: The reason why the curve goes down on groups 9 and 10 is because on these groups most of the countries are cold. Graphics 86 and 88 were made to demonstrate this effect. Also, the same graphic but without Cold countries (P2-75) is the best of all graphics..
P2-55 Meat, Milk and Sugar: The curve is too erratic and also goes down in the last groups.
P2-75 Animal and Sugar in Not Cold Countries: The graphic shows a clear relationship between these food and Diabetes. We gather here all the conditions to have diabetes: High food energy that the body keeps (do not spend) and the calories coming from animal and sugar. We can see a big improvement on the conclusiveness of the graphic with respect to P2-51.
P2-76 Total Vegetal: In spite of the fact that vegetal origin calories provide the biggest part of the energy, we can see from this graphic that they have no influence on diabetes.
P2-77 Total Vegetal but Sugar: On this graphic is even clearer (than in P2-76) that Calories from vegetal origin (but sugar) does not have any negative influence on Diabetes.
P2-78 Sugar: Even though the curve is erratic, it shows a definite influence of sugar on Diabetes.
P2-79 Meat, Milk and Sugar in Not Cold Countries: This graphic is not as good as All Animal and Sugar (P2-75). Does it mean that animal fat, eggs or fish not considered in this graphic have a negative effect on Diabetes?
P2-80 Animal: Graphic drops at group 10 because 9 out 12 of the group countries are “cold”. Group dispersion is the lowest of all graphics which means there is consistency on the results.
P2-81 Animal in Not Cold Countries: The graphic shows a clear relationship between Animal consumption and Diabetes prevalence. If we compare the graphics of animal and sugar alone we may conclude that the effect of animal on diabetes is clearer than the effect of sugar.
P2-82 Sugar and Alcohol: The data of Pure Alcohol Consumption is taken from WHO because FAO source includes all the volume of all alcoholic beverages.
P2-83 Sugar and Alcohol in Not Cold Countries: We don’t see any important effect of alcohol on Diabetes in this graphic nor in previous.
P2-84 Sugar in Not Cold Countries: This is not a conclusive graphic.
 

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Complementary Graphics

8 Graphics

Comments of Graphics

 

 

 

 

 

 

 

 

 

 

 

 

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Comments of Complementary Graphics

P2-85 Health Expenditures: Reduction of Prevalence in group 10 is explained because most of these countries (8 out of 12) are cold “C” (see graphic P2-86). Health Care has a great effect reducing Death Rate due to Diabetes however we don’t see a clear positive effect on reducing the Prevalence Rate. This is probably because health strategies are directed more towards corrective actions than to prevention.
P2-86 Cold vs. Not Cold Countries: The graphic shows the reduction effect that cold weather has on Diabetes Prevalence.
P2-87 Total Calories Consumption Effect: We may say that high food energy consumption is a condition for Diabetes.
P2-88 Weather Effect: What we can infer from the graphic is that the excess of calories that cause diabetes are the ones we eat but not spend.
P2-89 Type of Food Calories Effect: In spite of the fact that calories from Vegetal are higher than from Animal plus Sugar, the second group shows a much bigger Diabetes Prevalence. We can say that main problem of Diabetes is not the amount of Calories but the type of food calories we consume.
P2-90 Geographic and Food Region: Middle East shows higher prevalence than expected with respect to their Animal and Sugar consumption. On the other hand, Latin America shows a lower value than expected. We don’t have an explanation.
P2-94 Cancer vs. Diabetes: It is not clear the relationship between both diseases.
P2-98 Obesity vs. Diabetes: We don’t see a clear relationship between them.

 

 

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A p p e n d i x

Nota a Lectores de la Página: Por razones de tamaño de archivo, no se incluyen estas Tablas. Si desea alguna o todas, solicitarlas en el botón Contacto, y con gusto se las enviamos.

 

 

 

Source and Calculation Tables

P2-01 World Food Consumption Table

P2-02 World Energy Consumption table

P2-03 General Data Table

P2 Diabetes Related Table

P2 FAO Consum. Meat as %

P2 Calories in Meat, Milk and Sugar

P2 Calories in Pure Alcohol and Sugar

P2 Animal and Sugar Energy

P2 Table Total Oil

 

 

 

 

Food vs. Diabetes Graphic Tables (same numbers as graphics)

Table P2-40                    Table P2-77

Table P2-42                    Table P2-78

Table P2-44                    Table P2-79

Table P2-50                    Table P2-80

Table P2-51                    Table P2-81

Table P2-55                    Table P2-82

Table P2-75                    Table P2-83

Table P2-76                    Table P2-84

 

Complementary Graphic Tables (same numbers as graphics)

Table P2-85

Table P2-86

Table P2-87

Table P2-88

Table P2-89

Table P2-90

Table P2-94

Table P2-98

 

Off Rates Countries Table

Table P2-10b 

 

 

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