Food Patterns, Diabetes and Overweight/Obesity and Some Socio-Economic Indicators in the Italy Regions

Special Article – Food Disorders

Austin J Nutri Food Sci. 2018; 6(2): 1101.

Food Patterns, Diabetes and Overweight/Obesity and Some Socio-Economic Indicators in the Italy Regions

Ma L1* and Elvirasapienza2

¹Department Faculty of Medicine, National Autonomous University of Mexico, Mexico

²Faculty of Law, University Federico II of Naples, Italy

*Corresponding author: Moreno-Altamirano Laura, Public Health Department Faculty of Medicine, National Autonomous University of Mexico, Cuidad Universitaria, Mexico

Received: February 26, 2018; Accepted: March 21, 2018; Published: March 28, 2018


Background: There were over 3.5 million cases of diabetes in Italy in 2015. Research has provided a better understanding of the role of dietary patterns and their relation with socio-economic conditions and non-communicable diseases.

Objective: To identify the differences in mortality rate due to type 2 diabetes, the prevalence of overweight and obesity in the different regions of Italy and their relation with change in dietary patterns in the framework of some economic indicators.

Methods: We analyze the mortality rate of diabetes and the prevalence of overweight and obesity by region in Italy. The most frequent foods (kcalpercapita per day) from the Food Balance Sheet released by the Food and Agriculture Organization, were organized it for decades from 1961 to 2013. The average annual expenditure of several foods was calculated. Gross Domestic Product and the Gini coefficient for each region were calculated.

Results: Mortality rates for diabetes and the percentage of overweight and obesity show a continuous increase and they were differ in each region. Wheat showed a decrease in apparent consumption, while consumption of food of animal origin, vegetable oils and animal fats increased. The prices of sweets, packaged food and sugary drinks decreased.

Conclusion: Promoting healthy and ways of life to reduce the global burden of non-communicable diseases requires a multi-sectorial management of the social determinants of health.

Keywords: Diabetes; Overweight/Obesity; Food patterns; Socio economic conditions


The purpose of this study is to identify the differences in mortality due to type 2 diabetes (T2D), the increase of overweight and obesity in the different regions of Italy and their relation with change in dietary patterns within the framework of some economic indicators.

In Italy in 2015, the total adult population (1000s) (20-79 years) were 44,704; the prevalence of diabetes in adults (20-79 years) was 7.9%. The number of deaths in adults due to this disease was 22,226. Cost per person with diabetes (USD) was 3,450.1. The number of undiagnosed cases of this disease in adults was (1000s) 1,324.3 [1].

According to the International Diabetes Federation (IDF) the overall prevalence of T2D in 2015 was 8.8%, of which approximately 75% were people living in low and middle-income countries. The fastest increase of cases occurred in regions where the economy moved from low to middle-income. In low and middle-income regions, the number of people with diabetes will increase 150% over the next 25 years. Moreover, 318 million people live with impaired glucose worldwide. The IDF calculated that in the same year about 46.5% (193 million) patients were undiagnosed worldwide and one in seven births was affected by gestational diabetes. The disease caused 5 million deaths and resulting in 673 billion dollars being spent on care [2].

In 2015, 415 million people had diabetes worldwide. More than 59.8 million of those were in the EUR Region and over 3.5 million cases (adults 20-79 years) were in Italy [2].

In this regard, structural social determinants should be considered, covering a wide and complex combination of socio-economic conditions and interacting cultural and other environmental elements. The conditions in which the population is born, grows, lives, works, and ages, as well as the type of systems used to combat the disease are those that determine inequality and social inequity. Political and economic forces in each region in turn influence these conditions [3]. Analysis of health problems using social determinants is a framework of reference for research in various areas of public health and epidemiology. The field of knowledge and purpose of the DSS is to analyze inequities in the distribution of social goods and how avoidable inequalities are manifested in the state of health of social groups [4-6].

Economic development has led to greater availability and diversity of the food in almost all countries and a gradual decree in food shortages, resulting in nutritional condition. There have also been improved living standards and increased access to services. However, these improvements differ between countries with low, medium and high income and between population groups within each country [7].

In this context, research in recent years on epidemiology and other population based scientific fields has helped the understanding of the role of dietary patterns and their relation with socio- economic conditions and non-communicable diseases. In short, we have identified some specific food components that increase the probability of disease. Available data provide a solid and plausible foundation on the relationship of diet with some diseases. Thus it is known that diet is crucial as a social determinant of chronic diseases [8-15].

The election of behaviours such as meal choice is related to “collective life styles” and understanding that the life styles are not individual decisions, but conducts influenced by the opportunities defined by the social environment in which individuals live. People’s behaviour is socially imposed, and their ability to freely choose what to eat, for example, is dependent on income, marketing and availability [16,17]. Today, even in the most remote locations, products have displaced the traditional diet. This reflects the lack of control in the market and is a policy that has encouraged the consumption of processed foods harmful to health [8].

Dietary changes along with decreased energy expenditure, sedentary life, mechanized transport, labor saving appliances in the home workplace and a preferences in leisure time for computer games requiring no physical effort, have given rise to the so-called “Nutritional Transition”. This transition is characterized by changes in both the quantity and type of food [18-20].

Due to changes in eating habits and way of life, the NCDs, including obesity, diabetes mellitus, cardiovascular diseases, hypertension, cerebrovascular accidents and some types of cancer, are increasingly causes of disability and premature death in both developing and newly developed areas, especially among the poor [21].


Using data on health conditions from the health conditions “Health for All” [22] database, we analyzed the mortality rate of diabetes from 1990 to 2014 and the proportion of people with overweight and obesity from 2002 to 2013 by regions: Italy, North, Central, South and Islands. The European database “Health for All” provides a selection of indicators for the 53 member countries of WHO Europe.

Reviewing and analyzing data from the Food Balance Sheet (FBS), produce annually by the Food and Agriculture Organization (FAO), we organize in decades the information available of kcalpercapita per day (kcal/per/day from 1961 to 2013) of the most frequent foods [23].

The variation in prices of fruit, vegetables, sugar, chocolate, sweets and sugary drinks was analysed, from 2002 to 2013, employing the “Consumer Price Index for the whole nation” [24] (base 95 = 100) in terms of average annual percentage changes. Index in relation to the population present in the country and to the set of all goods and services purchased by households with an actual market price by reference to a base year: 1995.

With the data on “Final consumption expenditure of resident and non-residents households on the economic territory” (chained values-2010) [24] the average annual expenditure on the following foods was calculated: bread and cereals, meat, fish and seafood, milk, cheese and eggs, vegetable oils and animal fats, fruit, vegetables, cakes, sugar and chocolate and sugary drinks. Actual values in chained prices were constructed values with the so-called chaining methodology, in which the basis for the calculation of the actual values is changed in each period. Chaining involves building a series of real values, where each value is calculated using the previous year’s prices, but later in the rebuilding. Using the annual percentage rates of change, an entire time series is reported in a single year of arbitrary reference, so that the values of several years become comparable. The concatenated indices are opposed to so-called fixed-base indices, where the base year is kept constant for a certain number of periods (Real values at constant prices).

Average monthly expenditure for sugar was calculated in the different areas of the country [25]. Finally, Gross Domestic Product (GDP) [26] per capita was calculated at market prices (chained values with reference year 2010 and percentage changes). GDP is a monetary measure of the market value of all final goods and services produced in a period. Per capita values are average values obtained by comparing the economic aggregates (such as GDP, household final consumption, value added, compensation of employees) to the number of inhabitants or variables relating to labour input. The Ginico efficient for each region was calculated. This is a measure of the deviation of the distribution of income among individuals or households within a country from a perfectly equal distribution. A value of 0 represents absolute equality, a value of 100 absolute inequalities [27-29].



Between 1990 and 2013, national mortality rates for diabetes did not vary greatly. There were some oscillations with the rate going from 3.41 to 3.46. In the 1990s the rate fell in relation to previous years, and from 2005 this rate showed a slight but steady increase. The southern region shows a continuous increase from 3.9 to 4.49. The central region showed a similar trend to the general mortality rate. The northern region had the lowest rates and in the islands the highest mortality rates of diabetes were observed for the whole period analyzed, as shown in the (Figure 1).