Ultra-processed foods: Implications for gastrointestinal health

Table 5 Summary of available studies on positive association of ultra-processed foods with non-alcoholic fatty liver disease/obesity/metabolic syndrome[77,79,80-102]

Ref.	Study design & population (n)	UPFs assessment method	Diagnosis of MASLD	Main findings
Zhang et al[77], 2024	Prospective cohort (United Kingdom Biobank, n = 143073)	24-hour diet recall, NOVA classification	Hospitalizations, mortality records (ICD codes)	26% ↑ risk of severe MASLD (HR: 1.26; 95%CI: 1.15-1.38)
Zhang et al[80], 2022, China	Prospective, n = 16168	NOVA (g/1000 kcal/day)	AUS	The highest UPFs quartile had 18% higher MASLD risk (HR 1.18); dose-response noted
Liu et al[81], 2023	Cross-sectional (NHANES 2011-2018, n = 5499)	24-hour dietary recall, NOVA classification	US-FLI > 30	83% ↑ odds of MASLD (OR: 1.83; 95%CI: 1.42-2.37)
Konieczna et al[79], 2022	Prospective cohort (PREDIMED-Plus subset), n = 5867	FFQ, NOVA classification	FLI	Greater UPFs consumption: Associated with ↑ ALT, AST, and hepatic fat accumulation, especially in high-risk metabolic groups
Rauber et al[82], 2018	Cross-sectional (United Kingdom, 2008-2014)	National Diet and Nutrition Survey data + NOVA classification	Nutrient profile analysis; indirect MASLD risk via dietary patterns	Diets high in UPFs had ↓ fiber, ↑ sugars, and ↑ fats-suggestive of ↑ MASLD risk
Hall et al[83], 2020, United States	RCT, n = 20	NOVA (controlled feeding trial)	MRS	No significant change in liver fat after 2-week UPFs or unprocessed diet
Fridén et al[84], 2022, Sweden	Cross-sectional, n = 286	NOVA (% of kcal)	MRI	Positive crude association with liver fat; not significant after adjustment
Ivancovsky-Wajcman et al[85], 2021, Israel	Cross-sectional, n = 789	NOVA (% of kcal)	AUS + FibroMax panel	No direct UPFs-MASLD link; higher UPFs linked to ↑ NASH and fibrosis in smokers and MASLD patients
Canhada et al[86], 2023, Brazil	Prospective, n = 8065	Semi-quantitative 114-item FFQ NOVA classification	-	Higher UPFs consumption was associated with a 19% ↑ risk of incident MetS. 150 g increase in UPFs consumption/day: Associated with a 4% ↑ risk of incident MetS
Pan et al[87], 2023, China	Prospective, n = 5147	24-hour dietary recall, Cumulative mean UPF intake, NOVA classification (g/day)	-	Higher UPFs consumption: Associated with 17% ↑ risk for MetS (HR 1.17, 95%CI: 1.01-1.35)
Martínez Steele et al[88], 2019, United States	Cross-sectional (NHANES), n = 6385	24-hour dietary recall NOVA classification	-	A 10% ↑ increase in UPFs consumption was associated with a 4% higher prevalence of MetS (PR 1.04, 95%CI: 1.02-1.07). Higher UPFs consumption: Associated with a ↑ prevalence of MetS (PR 1.28, 95%CI: 1.09-1.50)
Lavigne-Robichaud et al[89], 2018, Canada	Cross-sectional, n = 811	24-hour dietary recall NOVA classification	-	Higher UPFs consumption: Associated with ↑ prevalence of MetS (OR 1.90, 95%CI: 1.14-3.17; P for trend = 0.04)
Li et al[90], 2021, China	Prospective, n = 12451	24-hour dietary recall of 3 consecutive days at each survey, Cumulative mean UPF intake NOVA classification (g/day)	-	Higher UPFs consumption: Associated with ↑ risk of overweight/obesity and central obesity
Cordova et al[91], 2021, 9 European countries	EPIC study, prospective, n = 348748	Quantitative dietary questionnaires or semi-quantitative FFQ, or a combination of semi-quantitative FFQ and 7- and 14-day records, NOVA classification	-	Higher consumption of UPFs (per 1 SD increment) was positively associated with weight gain (0.12 kg/5 years, 95%CI: 0.09-0.15)
Rauber et al[92], 2021, United Kingdom	Prospective, n = 18218	24-hour dietary recall, NOVA classification	-	Higher UPFs consumption: Associated with ↑ risk for obesity (HR = 1.79, 95%CI: 106-3.03), and abdominal obesity (HR = 1.30, 95%CI: 113-1.48)
Sandoval-Insausti H et al[93], 2020, Spain	Prospective, n = 652	Face-to-face dietary history, recording all food consumed in a typical week in the preceding year, NOVA classification	-	Participants with a higher UPFs consumption were more likely to develop abdominal obesity (OR = 1.62, 95%CI: 104-2.54; P for linear trend = 0.037)
Beslay et al[94], 2020, France	NutriNet-Sante cohort, n = 110260	24-hour dietary recall, NOVA classification	-	Risk of overweight (HR for an absolute ↑of 10% of UPFs = 1.11, 95%CI: 1.08-1.14, P < 0.001), and for obesity (HR for an absolute increment of 10% of UPF = 1.09, 95%CI: 1.05-1.13, P < 0.001)
Canhada et al[95], 2020, Brazil	Prospective, n = 11827	Semi-quantitative 114-items FFQ NOVA classification	-	UPFs consumption: Associated with a ↑ risk of weight gain and waist gain, overweight/obesity incidence (RR = 1.20, 95%CI: 1.03-1.40), and obesity incidence (RR = 1.02, 95%CI: 0.85-1.21)
Mendonça et al[96], 2016, Spain	SUN project, prospective, n = 8451	Self-administered semi-quantitative 136-item FFQ, NOVA classification	-	↑ incidence of overweight and obesity with ↑ baseline quartiles of UPFs
Silva Meneguelli et al[97], 2022, Brazil	Cross-sectional, n = 325	24-hour dietary recall NOVA classification	-	Positive associations between UPF consumption and excessive body weight (PR = 1.004, 95%CI: 1.00-1.01), and abdominal obesity (PR = 1.004, 95%CI: 1.00-1.01)
Martinez-Perez et al[98], 2021, Spain	Cross-sectional, PREDIMED-Plus trial, n = 5636	Semi-quantitative 143-items FFQ NOVA, IARC, IFIC, and UNC classification	-	5% ↑ in UPFs consumption: Associated with 0.11 higher BMI (95%CI: 0.05-0.18)
Machado et al[99], 2020, Australia	Cross-sectional, NNPAS, n = 7411	24-hour dietary recall NOVA classification	-	UPFs consumption: Associated with higher BMI and WC and ↑ prevalence of obesity and abdominal obesity (P < 0.001 for all outcomes)
Nardocci et al[100], 2021, Canada	Cross-sectional, CCHS, n = 13608	24-hour dietary recall NOVA classification	-	10% ↑ in UPFs consumption: Associated with 6% ↑ odds of obesity (OR 1.06, 95%CI: 1.02-1.11)
Juul et al[101], 2018, United States	Cross-sectional, NHANES, n = 15977	24-hour dietary recall NOVA classification	-	Higher UPFs consumption is associated with a 161-unit increase in BMI (95%CI: 1.11-2.10), a 407 cm increase in WC (95%CI: 2.94-5.19), and greater odds of being overweight (OR 1.48, 95%CI: 1.25-1.76), obese (OR 1.53, 95%CI: 1.29-1.81), and having abdominal obesity (OR 1.62, 95%CI: 1.39-1.89)
Silva et al[102], 2018, Brazil	Brazilian Longitudinal Study of Adult Health (ELSA-Brazil), cross-sectional, n = 8977	Semi-quantitative FFQ, NOVA classification	-	Higher UPFs consumption: Associated with a higher BMI (b = 0.80, 95%CI: 0.53-1.07 kg/m2), WC (b = 1.71, 95%CI: 1.02-2.40 cm) and higher odds for being overweight (OR 1.31, 95%CI: 1.13-1.51), obese (OR 1.41, 95%CI: 1.18-1.69) and increased WC (OR 1.41, 95%CI: 1.20-1.66)

AUS: Abdominal ultrasound; FLI: Fatty Liver Index; US: Ultrasound; MRS: Magnetic resonance spectroscopy; MRI: Magnetic resonance imaging; NNPAS: Cross-sectional, National Nutrition and Physical Activity Survey; CCHS: Canadian Community Health Survey; AST: Aspartate aminotransferase; ALT: Alanine aminotransferase; BMI: Body Mass index; CI: Confidence interval; FFQ: Food frequency questionnaire; HOMA-IR: Homeostatic model assessment for insulin resistance; HR: Hazard ratio; HSI: Hepatic steatosis index; IARC: International Agency for Research on Cancer; IFIC: International food information council; IR: Insulin resistance; Mets: Metabolic syndrome; MASLD: Non-alcoholic fatty liver disease; NHANES: National Health and Nutrition Examination Survey; OR: Odds ratio; QUICKI: Quantitative insulin-sensitivity check index; RCT: Randomized controlled trial; RR: Relative risk; UNC: University of North Carolina; UPF: Ultra-processed food; WC: Waist circumference.