Table 3.

Impact of the Nutri-Score 2.0 on primary outcomes (ie, objective understanding of nutritional quality and food ultraprocessing), NutriNet-Santé, 2022, France, n=21 159

	OR* (95% CI) [experimental arm vs. control arm)			P-trend
All products
Number of correct answers	0–2	3–6	7–9
Understanding of nutritional quality	1	0.54 (0.51–0.57)	29.0 (23.4–35.9)	<0.0001
Number of correct answers	0–12	13–19	20–22
Understanding of ultraprocessing	1	1.94 (1.75–2.14)	174.3 (151.4–200.5)	<0.0001
Cookies
Number of correct answers	0	1–2	3
Understanding of nutritional quality	1	0.50 (0.47–0.53)	6.46 (5.86–7.13)	<0.0001
Number of correct answers	0–4	5–7	8
Understanding of ultraprocessing	1	1.89 (1.73–2.06)	191.4 (164.2–223.1)	<0.0001
Breakfast cereals
Number of correct answers	0	1–2	3
Understanding of nutritional quality	1	2.75 (2.51–3.00)	86.8 (70.2–107.3)	<0.0001
Number of correct answers	0–4	5–6	7
Understanding of ultraprocessing	1	2.37 (2.16–2.60)	35.6 (32.4–39.2)	<0.0001
Ready-to-eat meals
Number of correct answers	0	1–2	3
Understanding of nutritional quality	1	0.59 (0.56–0.63)	17.3 (14.4–20.8)	<0.0001
Number of correct answers	0–4	5–6	7
Understanding of ultraprocessing	1	2.38 (2.16–2.62)	100.0 (89.5–111.7)	<0.0001

*ORs were derived from multinomial logistic regression models to predict the number of correct answers according to the experimentation arm, adjusted for age, sex, educational level, household monthly income, professional situation and area of residence