Cross-sectional comparisons of dietary indexes underlying nutrition labels: nutri-score, Canadian 'high in' labels and Diabetes Canada Clinical Practices (DCCP) Article Swipe
Laura Paper
,
Mavra Ahmed
,
Jenn Lee
,
Emmanuelle Kesse‐Guyot
,
Mathilde Touvier
,
Serge Herçberg
,
Pilar Galán
,
Benoı̂t Salanave
,
Charlotte Verdot
,
Mary R. L’Abbé
,
Valérie Deschamps
,
Chantal Julia
·
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.32920/26767744
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.32920/26767744
Purpose: To assess the cross-sectional association between dietary indexes (DI) that underlie, respectively, the Nutri-score (NS), the proposed Canadian 'High In' Symbol (CHIL) and the Diabetes Canada Clinical Practice Guidelines (DCCP) with food consumption, nutrient intakes and metabolic markers. Methods: 1836 adults (18-74 years) participating in the representative ESTEBAN study, conducted in mainland France in 2014-2016, were included in the analysis. Food consumption was assessed with three repeated 24 h dietary recalls. Anthropometric measurements and biomarkers of metabolic risk (cholesterol-total, LDL (Low Density Lipoprotein), HDL (High Density Lipoprotein)-triglycerides, glucose) were obtained through a clinical examination and fasting blood draw. The DI were assessed for their association with food consumption, dietary intakes and metabolic biomarkers as quintiles and continuous variables using multi-adjusted linear regression. Heathier diets were assigned to lower scores. Results: Correlations between scores ranged from + 0.62 between CHIL-DI and NS-DI to + 0.75 between NS-DI and DCCP-DI. All DIs discriminated individuals according to the nutritional quality of their diets through food consumption and nutrient intakes (healthier diets were associated with lower intakes of energy, added sugars and saturated fat; and with higher intakes of fiber, vitamins and minerals). NS-DI was associated with blood glucose (adjusted mean in Q1 = 5 vs. Q5 = 5.46 mmol/dl, ptrend = 0.001) and DCCP-DI was associated with BMI (Q1 = 24.8 kg/m2 vs. Q5 = 25.8 kg/m2, ptrend = 0.025), while CHIL showed no significant association with any anthropometric measures or biomarkers. Conclusions: This study provides elements supporting the validity of the nutrient profiling systems underlying front-of-package nutrition labellings (FOPLs) to characterize the healthiness of diets.
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Metadata
- Type
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- Language
- en
- Landing Page
- https://doi.org/10.32920/26767744
- OA Status
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- Related Works
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- OpenAlex ID
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All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W4401660182Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.32920/26767744Digital Object Identifier
- Title
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Cross-sectional comparisons of dietary indexes underlying nutrition labels: nutri-score, Canadian 'high in' labels and Diabetes Canada Clinical Practices (DCCP)Work title
- Type
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preprintOpenAlex work type
- Language
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enPrimary language
- Publication year
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2024Year of publication
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2024-08-17Full publication date if available
- Authors
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Laura Paper, Mavra Ahmed, Jenn Lee, Emmanuelle Kesse‐Guyot, Mathilde Touvier, Serge Herçberg, Pilar Galán, Benoı̂t Salanave, Charlotte Verdot, Mary R. L’Abbé, Valérie Deschamps, Chantal JuliaList of authors in order
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https://doi.org/10.32920/26767744Publisher landing page
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YesWhether a free full text is available
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goldOpen access status per OpenAlex
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https://doi.org/10.32920/26767744Direct OA link when available
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Medicine, Anthropometry, Diabetes mellitus, Dietary fiber, Cross-sectional study, Nutrient, Food science, Animal science, Environmental health, Internal medicine, Endocrinology, Biology, Pathology, EcologyTop concepts (fields/topics) attached by OpenAlex
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0Total citation count in OpenAlex
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| abstract_inverted_index.Canadian | 18 |
| abstract_inverted_index.Clinical | 27 |
| abstract_inverted_index.DCCP-DI. | 148 |
| abstract_inverted_index.Diabetes | 25 |
| abstract_inverted_index.Heathier | 123 |
| abstract_inverted_index.Practice | 28 |
| abstract_inverted_index.assessed | 64, 102 |
| abstract_inverted_index.assigned | 126 |
| abstract_inverted_index.clinical | 93 |
| abstract_inverted_index.elements | 244 |
| abstract_inverted_index.glucose) | 88 |
| abstract_inverted_index.included | 57 |
| abstract_inverted_index.mainland | 52 |
| abstract_inverted_index.measures | 237 |
| abstract_inverted_index.mmol/dl, | 206 |
| abstract_inverted_index.nutrient | 34, 165, 250 |
| abstract_inverted_index.obtained | 90 |
| abstract_inverted_index.proposed | 17 |
| abstract_inverted_index.provides | 243 |
| abstract_inverted_index.recalls. | 71 |
| abstract_inverted_index.repeated | 67 |
| abstract_inverted_index.validity | 247 |
| abstract_inverted_index.vitamins | 187 |
| abstract_inverted_index.(adjusted | 196 |
| abstract_inverted_index.according | 153 |
| abstract_inverted_index.analysis. | 60 |
| abstract_inverted_index.conducted | 50 |
| abstract_inverted_index.metabolic | 37, 77, 112 |
| abstract_inverted_index.nutrition | 255 |
| abstract_inverted_index.profiling | 251 |
| abstract_inverted_index.quintiles | 115 |
| abstract_inverted_index.saturated | 179 |
| abstract_inverted_index.underlie, | 11 |
| abstract_inverted_index.variables | 118 |
| abstract_inverted_index.(healthier | 167 |
| abstract_inverted_index.2014-2016, | 55 |
| abstract_inverted_index.Guidelines | 29 |
| abstract_inverted_index.associated | 170, 192, 213 |
| abstract_inverted_index.biomarkers | 75, 113 |
| abstract_inverted_index.continuous | 117 |
| abstract_inverted_index.labellings | 256 |
| abstract_inverted_index.minerals). | 189 |
| abstract_inverted_index.supporting | 245 |
| abstract_inverted_index.underlying | 253 |
| abstract_inverted_index.Nutri-score | 14 |
| abstract_inverted_index.association | 5, 105, 233 |
| abstract_inverted_index.consumption | 62, 163 |
| abstract_inverted_index.examination | 94 |
| abstract_inverted_index.healthiness | 261 |
| abstract_inverted_index.individuals | 152 |
| abstract_inverted_index.nutritional | 156 |
| abstract_inverted_index.regression. | 122 |
| abstract_inverted_index.significant | 232 |
| abstract_inverted_index.Correlations | 131 |
| abstract_inverted_index.characterize | 259 |
| abstract_inverted_index.consumption, | 33, 108 |
| abstract_inverted_index.measurements | 73 |
| abstract_inverted_index.Lipoprotein), | 83 |
| abstract_inverted_index.discriminated | 151 |
| abstract_inverted_index.participating | 44 |
| abstract_inverted_index.respectively, | 12 |
| abstract_inverted_index.Anthropometric | 72 |
| abstract_inverted_index.anthropometric | 236 |
| abstract_inverted_index.multi-adjusted | 120 |
| abstract_inverted_index.representative | 47 |
| abstract_inverted_index.cross-sectional | 4 |
| abstract_inverted_index.front-of-package | 254 |
| abstract_inverted_index.diets.</div> | 263 |
| abstract_inverted_index.(cholesterol-total, | 79 |
| abstract_inverted_index.scores.</div> | 129 |
| abstract_inverted_index.markers.</div> | 38 |
| abstract_inverted_index.biomarkers.</div> | 239 |
| abstract_inverted_index.Lipoprotein)-triglycerides, | 87 |
| abstract_inverted_index.<div><strong>Methods:</strong> | 39 |
| abstract_inverted_index.<div><strong>Purpose:</strong> | 0 |
| abstract_inverted_index.<div><strong>Results:</strong> | 130 |
| abstract_inverted_index.<div><strong>Conclusions:</strong> | 240 |
| cited_by_percentile_year | |
| countries_distinct_count | 0 |
| institutions_distinct_count | 12 |
| citation_normalized_percentile.value | 0.22554841 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | False |