Beatriz Silva Nunes
Biographic Data
| ID | 7549947 |
|---|---|
| NAME | Beatriz Silva Nunes |
| GIVEN NAMES | Beatriz Silva |
| FAMILY NAME | Nunes |
| SIGNATURE | NUNES B S |
| AFFILIATIONS | Universidade Estadual de Campinas (UNICAMP) |
| ORCID | 0000-0002-6431-8670 |
| VERIFIED | Yes |
| TOTAL WORKS | 3 |
| TOTAL CITATIONS | 0 |
| WORKS AS AUTHOR | 3 |
| WORKS AS EDITOR | 0 |
| FIRST PUBLICATION YEAR | 2025 |
| LATEST PUBLICATION YEAR | 2025 |
| H-INDEX | 0 |
Applying the Nova food classification to food product databases using discriminative ingredients
Background: Growing interest in the Nova food classification system surged among various stakeholders, driven primarily by compelling evidence linking the consumption of ultra-processed foods (UPFs) to negative health outcomes. This growing interest underscores the potential value of identifying clear markers to classify UPFs, particularly to support research and regulatory efforts. Objective: To propose replicable methods to identify UPFs, by te…
Perceptions of non-sugar sweeteners and front-of-package labels among parents of preschool and school-aged children in Brazil
Objective: To describe Brazilian parents’ perceptions of non-sugar sweeteners (NSS) in beverages consumed by children and their views for NSS front-of-package labels (FOPL). Design: A qualitative-driven mixed-methods embedded design was used. Seven focus groups with parents of children explored perceptions of NSS. Qualitative data were coded and analyzed using thematic analysis. Participants also completed a closed-ended survey assessing familiar…
Using commercial dataset for extracting information on nutrition composition for policy evaluation purposes
Objective: This study assessed the suitability of nutritional composition data from a commercial dataset for policy evaluation in Brazil. Design: We compared the proportions of packaged foods and beverages, classified according to the Nova food classification and the nutritional composition of matched products using data from a commercial database of food labels (Mintel-Global New Products Database (GNPD)) and the Brazilian Food Labels Database (…
No prominent works on this page.
Applying the Nova food classification to food product databases using discriminative ingredients
Background: Growing interest in the Nova food classification system surged among various stakeholders, driven primarily by compelling evidence linking the consumption of ultra-processed foods (UPFs) to negative health outcomes. This growing interest underscores the potential value of identifying clear markers to classify UPFs, particularly to support research and regulatory efforts. Objective: To propose replicable methods to identify UPFs, by te…
Perceptions of non-sugar sweeteners and front-of-package labels among parents of preschool and school-aged children in Brazil
Objective: To describe Brazilian parents’ perceptions of non-sugar sweeteners (NSS) in beverages consumed by children and their views for NSS front-of-package labels (FOPL). Design: A qualitative-driven mixed-methods embedded design was used. Seven focus groups with parents of children explored perceptions of NSS. Qualitative data were coded and analyzed using thematic analysis. Participants also completed a closed-ended survey assessing familiar…
Using commercial dataset for extracting information on nutrition composition for policy evaluation purposes
Objective: This study assessed the suitability of nutritional composition data from a commercial dataset for policy evaluation in Brazil. Design: We compared the proportions of packaged foods and beverages, classified according to the Nova food classification and the nutritional composition of matched products using data from a commercial database of food labels (Mintel-Global New Products Database (GNPD)) and the Brazilian Food Labels Database (…
Consumer Attitudes and Food Labeling (3 works) · Nutrition, Genetics, and Disease (2 works) · Biochemical Analysis and Sensing Techniques (1 work) · Biology (1 work) · Composition (language (1 work) · Computer Science (1 work) · Consumption (sociology (1 work) · Discriminative model (1 work) · Distribution (mathematics (1 work) · Food composition data (1 work)