Table 2.

Associations between candidate sQ-HPF items and tertile agreement variable by binomial logistic regression

Predictor variable	β	SE	p (Bonf)
Fatty dairy products	0.33	0.10	0.024
Sugary dairy products	1.37	0.22	< 0.001
Cured meat	0.59	0.07	< 0.001
Fats	0.63	0.14	0.001
Fermented alcohol	1.59	0.07	< 0.001
Distilled alcohol	3.90	0.45	< 0.001
Sugary drinks	3.90	0.17	< 0.001
Sweets	0.46	0.05	< 0.001
Snacks	3.93	0.43	< 0.001
Ready To Eat (RTE)	2.91	0.33	< 0.001
Refined cereals	0.30	0.04	< 0.001
Sauces	0.97	0.18	< 0.001
Additives	0.10	0.02	< 0.001
Fried food	0.84	0.15	< 0.001
Whole dairy products	−0.01	0.06	1
Semi-skimmed dairy products	− 0.15	0.03	< 0.001
Eggs	−0.31	0.19	1
Red meat	0.05	0.15	1
White meat	−1.41	0.17	< 0.001
White fish	−1.40	0.16	< 0.001
Blue fish	−1.29	0.15	< 0.001
Vegetables	−0.55	0.03	< 0.001
Fruit	−1.01	0.04	< 0.001
Potatoes	−0.88	0.18	< 0.001
Nuts	−0.87	0.07	< 0.001
Legumes	−2.46	0.23	< 0.001
Oils	−0.21	0.03	< 0.001
Non-sugary drinks	−0.09	0.03	0.302
Wholegrain cereals	−0.53	0.04	< 0.001
Vitamin/supplements	−0.10	0.12	1
Binge eating	0.17	0.14	1
N° binges/week	0.05	0.05	1
Snacking	0.06	0.08	1

Binomial logistic regression adjusted for age, sex, recruitment center, energy intake, physical activity level, medication for blood pressure and diabetes, working status, educational level, and civil status. Tertile agreement is the outcome variable (score 0 – “low HPF consumer” if a subject is classified in T1 of HPF consumption by at least two classification systems; score 1 – “high HPF consumer” if a subject is classified in T3 by at least two classification systems). Food groups expressed in frequency of consumption (times/day). HPF: highly processed food. Items selected for the sQ-HPF are shown in bold. Bonf: Bonferroni adjustment. N = 4400