Biology of Nutrition
A.Y. 2021/2022
Learning objectives
Aims of the course are: (i) the understanding of how a correct nutritional state is important in order to assure an optimal health state and to compensate the energy expenditure related physical activity; (ii) the knowledge of principles at the basis of an optimal and healthy diet according to scientific national (LARN and National guidelines) and international guidelines (EFSA) and to deal with physical and sport activity; (iii) the knowledge of the features and properties of the various nutrients required in a balanced diet; (iv) the knowledge and understanding of the concepts and procedures of statistics applied to biomedical sciences, including hypothesis testing in the analysis of continuous and categorical variables, correlation and regression.
Expected learning outcomes
At the end of the course, students should know principles for defining a dietary scheme and to critically analyze some of the most common dietary regimes. Through specific practical exercises, students should have become able to know and select most appropriate sources of energetic nutrients and their best assortment to compose diets suited for specific type of physical activities and sports. Students should have become able to know pros and cons of dietary supplements. Moreover, students are expected to become able to know the usefulness of linear and non-linear regression and how to apply it to generate predictive models. By means of examples of application of statistics to nutritional topics, students should have become able to interpret the results of statistical analyses published in the biomedical literature, and should have acquired the ability to select the best statistical approach to analyze different datasets.
Lesson period: First semester
Assessment methods: Esame
Assessment result: voto verbalizzato in trentesimi
Single course
This course cannot be attended as a single course. Please check our list of single courses to find the ones available for enrolment.
Course syllabus and organization
Single session
Responsible
Lesson period
First semester
More specific information on the delivery modes of training activities for academic year 2021/22 will be provided over the coming months, based on the evolution of the public health situation
Prerequisites for admission
For Biology of nutrition module knowledge of biochemistry, biochemistry of nutrition and physiology of nutrition are required.
For Data analysis and predictive modeling module knowledge of basic maths principles is recommended
For Data analysis and predictive modeling module knowledge of basic maths principles is recommended
Assessment methods and Criteria
For Biology of nutrition module the verification of students' preparation is in form of an oral test. During the oral examination, open questions about the basic nutrition and the nutrition topics for physical activity and sport will be done. Exercises on diet planning may also be required. The expected duration of the test is 30 minutes. The evaluation expressed in thirtieths is the result of both the knowledge of the topics covered and the student's critical analysis ability.
For the Data analysis and predictive modeling module is a written test, consisting of a series of problems covering the topics explained during the course. The expected duration of the test is three hours
The final score is the weighted average of the individual marks relating to the credits of the two modules
For the Data analysis and predictive modeling module is a written test, consisting of a series of problems covering the topics explained during the course. The expected duration of the test is three hours
The final score is the weighted average of the individual marks relating to the credits of the two modules
Modulo: Biologia della nutrizione
Course syllabus
Nutritional requirements according to the LARN, EFSA documents, the Guidelines for the Italian population, the documents of the Italian Society of Human Nutrition, SINU
Nutrients: characteristics, properties and food sources
Antioxidants and bioactive compounds
Hydration, nervous and alcoholic drinks
The methodology to estimate the basal expenditure and the energy requirements
The use of food databases
Setting balanced eating patterns for healthy adults
Mediterranean diet and diets widespread in the population
Nutritional investigation methods
The regulation CE 1169/11 for nutritional labeling
The energy needs and fuel requirements to support training program
Quantity, quality of nutrients and their correct distribution in the daily diet during training, competition and the recovery phase
The timing of the introduction of nutrients in the various phases of physical activity
Integration and supplements
Hydration for physical activity and sports
Nutrients: characteristics, properties and food sources
Antioxidants and bioactive compounds
Hydration, nervous and alcoholic drinks
The methodology to estimate the basal expenditure and the energy requirements
The use of food databases
Setting balanced eating patterns for healthy adults
Mediterranean diet and diets widespread in the population
Nutritional investigation methods
The regulation CE 1169/11 for nutritional labeling
The energy needs and fuel requirements to support training program
Quantity, quality of nutrients and their correct distribution in the daily diet during training, competition and the recovery phase
The timing of the introduction of nutrients in the various phases of physical activity
Integration and supplements
Hydration for physical activity and sports
Teaching methods
Lectures supported by projected material and exercises; collective critical analysis of the scientific literature
Class attendance is strongly recommended
Class attendance is strongly recommended
Teaching Resources
A pdf copy of the power point presentations shown in class will be available on ARIEL
Costantini, Cannella, Tomassi, "Alimentazione e nutrizione umana" IL PENSIERO SCIENTIFICO EDITORE
LARN 2014, Italian guide lines 2018, Scientific literature analyzed in class
Riccardi, Pacioni, Rivellese,"Manuale di nutrizione applicata" ILDESON GNOCCHI
Mc Ardle, Katch, Katch "Alimnetazione nello sport" Casa Editrice Ambrosiana
LARN 2014
Costantini, Cannella, Tomassi, "Alimentazione e nutrizione umana" IL PENSIERO SCIENTIFICO EDITORE
LARN 2014, Italian guide lines 2018, Scientific literature analyzed in class
Riccardi, Pacioni, Rivellese,"Manuale di nutrizione applicata" ILDESON GNOCCHI
Mc Ardle, Katch, Katch "Alimnetazione nello sport" Casa Editrice Ambrosiana
LARN 2014
Modulo: Analisi e modellistica predittiva dei dati
Course syllabus
The principal topics of the course are illustrated in the followings:
Type of study in the clinical setting: observational studies and association measures (odds ratio and relative risk), experimental studies (the role of randomization)
Descriptive statistics: tables, graphical plots, summary measures of central tendency and variability (mean, variance, standard deviation, median, percentiles, quartiles).
Diagnostic tests: sensitivity, specificity, likelihood ratios and predictive values. How to evaluate the discriminant performance.
Basic concepts of inferential statistics
Sampling distribution for means and proportions
Central limit theorem and Gaussian distribution for sample means, the binomial distribution
T Student distribution
Confidence intervals for means and proportions
Hypothesis testing and statistical significance. Statistical errors of the first and second type.
Comparison of one-mean with a population reference value
The comparison of two means
Comparison of one proportion with a population reference value.
The comparison of two proportions
How to analyze the relationship between two variables by means of correlation analysis.
Predictive modelling: linear and nonlinear regression.
Categorical data analysis: the chi squared test.
The software R: fundamentals of programming and statistical analysis
Type of study in the clinical setting: observational studies and association measures (odds ratio and relative risk), experimental studies (the role of randomization)
Descriptive statistics: tables, graphical plots, summary measures of central tendency and variability (mean, variance, standard deviation, median, percentiles, quartiles).
Diagnostic tests: sensitivity, specificity, likelihood ratios and predictive values. How to evaluate the discriminant performance.
Basic concepts of inferential statistics
Sampling distribution for means and proportions
Central limit theorem and Gaussian distribution for sample means, the binomial distribution
T Student distribution
Confidence intervals for means and proportions
Hypothesis testing and statistical significance. Statistical errors of the first and second type.
Comparison of one-mean with a population reference value
The comparison of two means
Comparison of one proportion with a population reference value.
The comparison of two proportions
How to analyze the relationship between two variables by means of correlation analysis.
Predictive modelling: linear and nonlinear regression.
Categorical data analysis: the chi squared test.
The software R: fundamentals of programming and statistical analysis
Teaching methods
The module is divided in 8 lessons, three hours each. Lessons are divided in didactics, for learning the fundamental principles included in the objectives of the course, and exercises, for strengthening the comprehension and providing critical reasoning skills through the application of the acquired concepts.
Each lesson will be subdivided in two hours for explaining methodological statistical argumenta and one hour of exercises concerning the application of statistical methods previously discussed on clinical studies
Attendance to the lessons is strongly recommended.
Each lesson will be subdivided in two hours for explaining methodological statistical argumenta and one hour of exercises concerning the application of statistical methods previously discussed on clinical studies
Attendance to the lessons is strongly recommended.
Teaching Resources
Daniel and Cross
Biostatistica : concetti di base per l'analisi statistica delle scienze dell'area medico sanitaria
Ed. Edises
Course lecture notes, available on Ariel
Biostatistica : concetti di base per l'analisi statistica delle scienze dell'area medico sanitaria
Ed. Edises
Course lecture notes, available on Ariel
Modulo: Analisi e modellistica predittiva dei dati
ING-INF/06 - ELECTRONIC AND INFORMATICS BIOENGINEERING
MAT/06 - PROBABILITY AND STATISTICS
MAT/06 - PROBABILITY AND STATISTICS
Lessons: 24 hours
Professor:
Boracchi Patrizia
Modulo: Biologia della nutrizione
MED/49 - FOOD AND DIETETIC SCIENCES - University credits: 6
Practicals: 8 hours
Lessons: 44 hours
Lessons: 44 hours
Professor:
Ferraretto Anita
Professor(s)
Reception:
On appointment (email)