Periodic Reporting for period 1 - GlucoMatchMaker (A new tool to guide consumers on how to mix and match foods to improve their blood glucose profiles)
Periodo di rendicontazione: 2021-04-01 al 2023-03-31
Starchy foods are one of the main components of our diet. They supply up to half of our energy needs and, because starch is exclusively made of glucose, these foods play a major role in our blood glucose levels. High blood glucose is linked to a number of chronic diseases and the rate at which starch in a given food is digested is directly correlated with blood glucose levels (i.e. the glycaemic response). Simply put, quickly digested starchy foods lead to high blood glucose levels. However, this effect can be counteracted by an adequate combination with other foods.
Low pH foods can attenuate the glycemic response to starch-rich foods. It has been demonstrated, for example, that lemon juice, due to its low pH (pH≈2.3) inhibited key digestive enzymes, thereby interrupting gastric digestion of starch in vitro . This effect can significantly reduce the glycemic response in humans. In particular, adding lemon juice to a starch rich meal reduced the mean blood glucose concentration peak by 30% .
Considering the panoply of food options available to consumers, it is likely that other combinations have similar effects but no work had ever been conducted to develop a consolidated knowledge base to exploit this strategy. GlucoMatchMaker went beyond the state-of-the art with a work plan designed to address this knowledge gap.
The main goal was to test, in a real-life context, the effectiveness of guiding individuals on how to mix and match foods and beverages to improve glucose responses.
Four specific objectives have been defined:
Specific objective 1:
To select and characterize starch-rich foods, low-pH foods and beverages and to investigate how their combination influences the rate of starch digestion in vitro (WP1).
Specific objective 2:
To determine the conditions of effectiveness of these combinations (in silico models) (WP2).
Specific objective 3:
To develop the first mobile app that will integrate this knowledge to guide the user on how to mix and match starch-rich foods to lower their glycemic impact (WP3).
Specific objective 4:
To test the effectiveness of the developed strategy in a real-life context (Secondment, WP5).
Low pH foods can attenuate the glycemic response to starch-rich foods. It has been demonstrated, for example, that lemon juice, due to its low pH (pH≈2.3) inhibited key digestive enzymes, thereby interrupting gastric digestion of starch in vitro . This effect can significantly reduce the glycemic response in humans. In particular, adding lemon juice to a starch rich meal reduced the mean blood glucose concentration peak by 30% .
Considering the panoply of food options available to consumers, it is likely that other combinations have similar effects but no work had ever been conducted to develop a consolidated knowledge base to exploit this strategy. GlucoMatchMaker went beyond the state-of-the art with a work plan designed to address this knowledge gap.
The main goal was to test, in a real-life context, the effectiveness of guiding individuals on how to mix and match foods and beverages to improve glucose responses.
Four specific objectives have been defined:
Specific objective 1:
To select and characterize starch-rich foods, low-pH foods and beverages and to investigate how their combination influences the rate of starch digestion in vitro (WP1).
Specific objective 2:
To determine the conditions of effectiveness of these combinations (in silico models) (WP2).
Specific objective 3:
To develop the first mobile app that will integrate this knowledge to guide the user on how to mix and match starch-rich foods to lower their glycemic impact (WP3).
Specific objective 4:
To test the effectiveness of the developed strategy in a real-life context (Secondment, WP5).
The experimental approach was based on combining the novel knowledge about starch digestion developed during the researcher’s PhD with novel technologies and with a human study in a real-life context with state-of the art glucose monitoring devices.
There were 7 WPs in this project:
WP 1: Identification and characterization of potential foods (addresses specific objective 1)
WP 2: Selection of effective combinations (addresses specific objective 2)
WP 3: Development of a digital tool to guide dietary choices (addresses specific objective 3)
WP 4: Ethics requirements (this WP4 prepared the human study and therefore had to be completed before WP5 was initiated)
WP 5: Real-life application/test (addresses specific objective 4)
WP 6: Dissemination, communication and exploitation
WP 7: Management and Training
The applied research work employed multidisciplinary knowledge and methodologies and was divided into four main parts which integrated Work packages 1, 2, 3 and 5, as described below:
(1) Selection and characterization of starch-rich foods, low-pH foods/beverages and of how their combination influences starch digestion in vitro (WP1).
A total of around 60 foods (both starch rich foods and low pH foods) have been screened in the first part of this work. Subsequently, eleven in vitro digestions (starch rich foods in the absence or presence of a low pH food) have been conducted in triplicate, generating over 200 samples. Each sample has been analyzed using at least 3 analytical protocols, to evaluate the starch digestion profile.
(2) Determination of the conditions of effectiveness of these combinations (in silico models) (WP2).
The data sets generated in WP1, have been processed to estimate the impact of the different low pH foods on the glycemic response of each starch-rich food, i.e. for each starch-rich food, effective low pH foods have been identified and the corresponding proportions determined.
(3) A digital guide integrating the knowledge developed in the previous two stages has been developed to guide the user on how to mix and match starch-rich foods with others to lower their glycemic impact (WP3).
(4) The effectiveness of the developed strategy has been tested in a dietary intervention study conducted in a real-life context (WP5).
More than 29 000 glucose concentration values have been recorded for all participants throughout the study. These are related to the consumption of a total of more than 900 meals by all the participants in the study.
There were 7 WPs in this project:
WP 1: Identification and characterization of potential foods (addresses specific objective 1)
WP 2: Selection of effective combinations (addresses specific objective 2)
WP 3: Development of a digital tool to guide dietary choices (addresses specific objective 3)
WP 4: Ethics requirements (this WP4 prepared the human study and therefore had to be completed before WP5 was initiated)
WP 5: Real-life application/test (addresses specific objective 4)
WP 6: Dissemination, communication and exploitation
WP 7: Management and Training
The applied research work employed multidisciplinary knowledge and methodologies and was divided into four main parts which integrated Work packages 1, 2, 3 and 5, as described below:
(1) Selection and characterization of starch-rich foods, low-pH foods/beverages and of how their combination influences starch digestion in vitro (WP1).
A total of around 60 foods (both starch rich foods and low pH foods) have been screened in the first part of this work. Subsequently, eleven in vitro digestions (starch rich foods in the absence or presence of a low pH food) have been conducted in triplicate, generating over 200 samples. Each sample has been analyzed using at least 3 analytical protocols, to evaluate the starch digestion profile.
(2) Determination of the conditions of effectiveness of these combinations (in silico models) (WP2).
The data sets generated in WP1, have been processed to estimate the impact of the different low pH foods on the glycemic response of each starch-rich food, i.e. for each starch-rich food, effective low pH foods have been identified and the corresponding proportions determined.
(3) A digital guide integrating the knowledge developed in the previous two stages has been developed to guide the user on how to mix and match starch-rich foods with others to lower their glycemic impact (WP3).
(4) The effectiveness of the developed strategy has been tested in a dietary intervention study conducted in a real-life context (WP5).
More than 29 000 glucose concentration values have been recorded for all participants throughout the study. These are related to the consumption of a total of more than 900 meals by all the participants in the study.
Worldwide, high blood glucose kills about 3.4 million people annually. In Ireland, 854,165 adults over 40, i.e. 18% of the population, are at increased risk of developing (or have) Type-2 diabetes. Portugal has is also among the countries with the highest levels of prevalence of diabetes in Europe (15%), and after correction for the effect of age and gender, the most affected region is The Azores. The EU-funded GlucoMatchMaker project developed and tested the first guide to help people mix and match starchy foods with other foods and beverages to attenuate glycemic responses. By creating a solution to improve glucose levels, this project addresses the United Nations and EU target to reduce premature mortality from non-communicable diseases - including diabetes - by one third as part of the 2030 Agenda for Sustainable Development. The research plan has been developed within the framework of the “H2020 Work Programme - Health, demographic change and wellbeing”, specifically the general aim to “translate new knowledge into innovative applications and accelerate large-scale uptake and deployment” .
Ireland is a world leader in scientific excellence and research capability (top 10 in the world). In contrast, as highlighted in “H2020-FORWARD”, in outermost European regions such as the The Azores, the potential for excellent research remains largely unexplored due in part to the lack of connectivity with excellent research partners. Therefore, this project also tackled this H2020 challenge by leading the first research activity of this type in The Azores and in collaboration with world-class research organizations.
Ireland is a world leader in scientific excellence and research capability (top 10 in the world). In contrast, as highlighted in “H2020-FORWARD”, in outermost European regions such as the The Azores, the potential for excellent research remains largely unexplored due in part to the lack of connectivity with excellent research partners. Therefore, this project also tackled this H2020 challenge by leading the first research activity of this type in The Azores and in collaboration with world-class research organizations.